DeVita, Hellman, and Rosenbergs Cancer Principles & Practice of Oncology 11th edition

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DeVita, Hellman, and Rosenberg’s

Cancer Principles & Practice of Oncology

11th edition

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Editors

Vincent T. DeVita Jr., MD Amy and Joseph Perella Professor of Medicine Yale Comprehensive Cancer Center and Smilow Cancer Hospital at Yale-New Haven Professor of Epidemiology and Public Health Yale University School of Public Health New Haven, Connecticut

Theodore S. Lawrence, MD, PhD Isadore Lampe Professor and Chair Department of Radiation Oncology University of Michigan Ann Arbor, Michigan

Steven A. Rosenberg, MD, PhD

Chief, Surgery Branch, National Cancer Institute, National Institutes of Health Professor of Surgery, Uniformed Services University of the Health Sciences School of Medicine Bethesda, Maryland Professor of Surgery George Washington University School of Medicine Washington, District of Columbia

With 384 Contributing Authors

Acquisitions Editor: Ryan Shaw Editorial Coordinator: Tim Rinehart Marketing Manager: Rachel Mante-Leung Production Project Manager: Alicia Jackson Design Coordinator: Holly McLaughlin Manufacturing Coordinator: Beth Welsh Prepress Vendor: Absolute Service, Inc. 11th edition Copyright © 2019 Wolters Kluwer. Copyright © 2015 by Wolters Kluwer Health. Copyright © 2011 by Wolters Kluwer Health / Lippincott Williams & Wilkins. Copyright © 2008 by Lippincott Williams & Wilkins, a Wolters Kluwer business. Copyright © 2005, 2001 by Lippincott Williams & Wilkins. Copyright © 1997, by Lippincott-Raven Publishers. Copyright © 1993, 1989, 1985, 1982 by J.B. Lippincott Company. All rights reserved. This book is protected by copyright. No part of this book may be reproduced or transmitted in any form or by any means, including as photocopies or scanned-in or other electronic copies, or utilized by any information storage and retrieval system without written permission from the copyright owner, except for brief quotations embodied in critical articles and reviews. Materials appearing in this book prepared by individuals as part of their official duties as U.S. government employees are not covered by the above-mentioned copyright. To request permission, please contact Wolters Kluwer at Two Commerce Square, 2001 Market Street, Philadelphia, PA 19103, via email at [email protected], or via our website at shop.lww.com (products and services). 9 8 7 6 5 4 3 2 1 Printed in the United States of America Library of Congress Cataloging-in-Publication Data Names: DeVita, Vincent T., Jr., 1935- editor. | Lawrence, Theodore S., editor. | Rosenberg, Steven A., editor. Title: DeVita, Hellman, and Rosenberg’s cancer : principles & practice of oncology / [edited by] Vincent T. DeVita, Jr., Theodore S. Lawrence, Steven A. Rosenberg. Description: 11th edition. | Philadelphia : Wolters Kluwer, [2019] | Includes bibliographical references. Identifiers: LCCN 2018043829 | eISBN 9781496394651 Subjects: | MESH: Neoplasms Classification: LCC RC263 | NLM QZ 200 | DDC 616.99/4–dc23 LC record available at https://lccn.loc.gov/2018043829 This work is provided “as is,” and the publisher disclaims any and all warranties, express or implied, including any warranties as to accuracy, comprehensiveness, or currency of the content of this work. This work is no substitute for individual patient assessment based on health-care professionals’ examination of each patient and consideration of, among other things, age, weight, gender, current or prior medical conditions, medication history, laboratory data, and other factors unique to the patient. The publisher does not provide medical advice or guidance, and this work is merely a reference tool. Health-care professionals, and not the publisher, are solely responsible for the use of this work including all medical judgments and for any resulting diagnosis and treatments. Given continuous, rapid advances in medical science and health information, independent professional verification of medical diagnoses, indications, appropriate pharmaceutical selections and dosages, and treatment options should be made and health-care professionals should consult a variety of sources. When prescribing medication, health-care professionals are advised to consult the product information sheet (the manufacturer’s package insert) accompanying each drug to verify, among other things, conditions of use, warnings, and side effects, and identify any changes in dosage schedule or contraindications, particularly if the medication to be administered is new, infrequently used, or has a narrow therapeutic range. To the maximum extent permitted under applicable law, no responsibility is assumed by the publisher for any injury and/or damage to persons or property, as a matter of products liability, negligence law, or otherwise, or from any reference to or use by any person of this work. shop.lww.com

Contributing Authors Ghassan Abou-Alfa, MD, MBA Attending, Memorial Sloan Kettering Cancer Center Associate Professor, Weill Medical College at Cornell University New York, New York Ross A. Abrams, MD, FACP, FACR, FASTRO Professor Department of Radiation Oncology Rush University Medical Center Chicago, Illinois Nadeem R. Abu-Rustum, MD Chief, Gynecology Service Memorial Sloan Kettering Cancer Center Professor Avon Chair in Gynecologic Oncology Weill Cornell Medical College New York, New York Gregory P. Adams, PhD Chief Scientific Officer Eleven Biotherapeutics Cambridge, Massachusetts Anupriya Agarwal, PhD Hematology and Medical Oncology, Knight Cancer Institute Oregon Health & Science University Portland, Oregon Manmeet S. Ahluwalia, MD, FACP Miller Family Endowed Chair in Neuro-Oncology Head of Operations, Rose Ella Burkhardt Brain Tumor and Neuro-Oncology Center, Cleveland Clinic Professor, Cleveland Clinic Lerner College of Medicine of the Case Western Reserve University Cleveland, Ohio Shahab Ahmed, MD Senior Data Analyst Department of Gastrointestinal Medical Oncology The University of Texas MD Anderson Cancer Center Houston, Texas Kaled M. Alektiar, MD Attending Physician Department of Radiation Oncology Memorial Sloan Kettering Cancer Center New York, New York James M. Allan, DPhil

Northern Institute for Cancer Research Faculty of Medicine Newcastle University Newcastle upon Tyne, United Kingdom Stephen Ansell, MD, PhD Professor of Medicine Division of Hematology Mayo Clinic Rochester, Minnesota Cristina R. Antonescu, MD Director, Bone and Soft Tissue Pathology Department of Pathology Memorial Sloan Kettering Cancer Center New York, New York Alvaro Arjona-Sanchez, MD, PhD Unit of Oncological and Pancreatic Surgery University Hospital Reina Sofia Cordoba, Spain Amanda K. Ashley, PhD Assistant Professor Department of Chemistry and Biochemistry New Mexico State University Las Cruces, New Mexico Alan Ashworth, PhD, FRS President, UCSF Helen Diller Family Comprehensive Cancer Center San Francisco, California Jon C. Aster, MD, PhD Chief, Division of Hematopathology Department of Pathology Brigham and Women’s Hospital Boston, Massachusetts David A. August, MD Professor of Surgery Chief, Division of Surgical Oncology Rutgers Cancer Institute of New Jersey and Rutgers Robert Wood Johnson Medical School New Brunswick, New Jersey Brittany A. Avin, PhD Candidate Biochemistry, Cellular, and Molecular Biology Program Johns Hopkins University School of Medicine Baltimore, Maryland Itzhak Avital, MD, MBA, FACS Professor of Surgery Ben Gurion University of the Negev Executive Medical Director Soroka Comprehensive Cancer Center Beersheba, Israel Joachim M. Baehring, MD, DSc

Professor Department of Neurology Yale School of Medicine New Haven, Connecticut Sharyn D. Baker, PharmD, PhD Professor Gertrude Parker Heer Chair in Cancer Research Associate Director, Comprehensive Cancer Center College of Pharmacy The Ohio State University Columbus, Ohio Laurence Baker, DO Professor Division of Hematology and Oncology Department of Internal Medicine University of Michigan School of Medicine Ann Arbor, Michigan Lodovico Balducci, MD Senior Member Emeritus Moffitt Cancer Center Tampa, Florida Alberto Bardelli, PhD Full Professor Director Molecular Oncology Department of Oncology University of Torino Candiolo Cancer Institute Candiolo, Italy Ronald Barr, MB, ChB, MD Professor of Pediatrics, Pathology and Medicine McMaster University Hamilton, Ontario, Canada Tracy T. Batchelor, MD Giovanni Armenise Professor of Neurology Harvard Medical School Massachusetts General Hospital Boston, Massachusetts Susan Bates, MD Professor of Medicine Department of Medicine Columbia University Irving Medical Center New York, New York Stephen B. Baylin, MD Virginia and D. K. Ludwig Professor in Cancer Research Co-Director, Cancer Biology Program Department of Oncology Johns Hopkins University School of Medicine Baltimore, Maryland

Whitney H. Beeler, MD Resident Physician Department of Radiation Oncology University of Michigan Ann Arbor, Michigan Michael T. Bender, MD Instructor of Medicine Division of Pulmonary and Critical Care Medicine Department of Medicine Weill Cornell Medical College New York, New York Andrew Berchuck, MD Chief, Gynecologic Oncology Program Duke Cancer Institute Durham, North Carolina Jonathan S. Berek, MD, MMS Laurie Kraus Lacob Professor Stanford University School of Medicine Director Stanford Women’s Cancer Center Senior Scientific Advisor Stanford Cancer Institute Stanford, California Alice Hawley Berger, PhD Assistant Member Human Biology and Public Health Sciences Divisions Fred Hutchinson Cancer Research Center Seattle, Washington Ann M. Berger, MSN, MD Senior Research Clinician Chief, Pain and Palliative Care NIH Clinical Center Bethesda, Maryland Ross S. Berkowitz, MD Director of Gynecologic Oncology Brigham and Women’s Hospital and Dana Farber Cancer Institute William H. Baker Professor of Gynecology Harvard Medical School Boston, Massachusetts Tara Berman, MD, MS Medical Oncologist National Cancer Institute National Institutes of Health Bethesda, Maryland Bryan L. Betz, PhD Associate Professor Department of Pathology

University of Michigan Technical Director Molecular Diagnostics Laboratory University of Michigan Health System Ann Arbor, Michigan Smita Bhatia, MD, MPH Director, Institute for Cancer Outcomes and Survivorship School of Medicine University of Alabama at Birmingham Birmingham, Alabama Manali Bhave, MD Assistant Professor Division of Oncology Department of Hematology and Oncology Emory University School of Medicine Atlanta, Georgia James S. Blachly, MD Assistant Professor of Internal Medicine Division of Hematology Assistant Professor of Biomedical Informatics The Ohio State University Comprehensive Cancer Center—Arthur G. James Cancer Hospital and Richard J. Solove Research Institute Columbus, Ohio Elizabeth M. Blanchard, MD Chief Hematology and Oncology Southcoast Health New Bedford, Massachusetts Archie Bleyer, MD Clinical Research Professor Department of Radiation Medicine Oregon Health & Science University Portland, Oregon Professor of Pediatrics University of Texas Medical School at Houston Houston, Texas Sharon L. Bober, PhD Director, Sexual Health Program Dana-Farber Cancer Institute Boston, Massachusetts Lawrence H. Boise, PhD Professor and Vice Chair for Basic Research Department of Hematology and Medical Oncology Emory University Atlanta, Georgia Danielle C. Bonadies, MS, CGC Director My Gene Counsel

Branford, Connecticut Hossein Borghaei, MS, DO Chief, Thoracic Oncology Department of Hematology and Oncology Fox Chase Cancer Center Philadelphia, Pennsylvania Otis W. Brawley, MD, MACP Chief Medical Officer American Cancer Society Atlanta, Georgia Dean E. Brenner, MD Talpaz Professor of Translational Oncology Professor, Department of Internal Medicine Professor, Department of Pharmacology University of Michigan Medical School Ann Arbor, Michigan J. Chad Brenner, PhD Assistant Professor Department of Otolaryngology Department of Pharmacology University of Michigan Ann Arbor, Michigan Jonathan R. Brody, PhD Professor Department of Surgery Thomas Jefferson University Philadelphia, Pennsylvania Justin C. Brown, PhD Research Fellow Division of Population Sciences Dana-Farber Cancer Institute Harvard Medical School Boston, Massachusetts Paul D. Brown, MD Professor Department of Radiation Oncology Mayo Clinic Rochester, Minnesota Christopher B. Buck, PhD Senior Investigator Lab of Cellular Oncology National Cancer Institute National Institutes of Health Bethesda, Maryland Harold J. Burstein, MD, PhD Dana-Farber Cancer Institute Brigham and Women’s Hospital

Harvard Medical School Boston, Massachusetts Alissa M. Butts, PhD, ABPP Assistant Professor of Psychology Department of Psychiatry and Psychology Mayo Clinic Rochester, Minnesota A. Hilary Calvert, MB, BChir, FRCP, MSc, FMedSci Emeritus Professor of Cancer Therapeutics UCL Cancer Institute London, United Kingdom Matthew T. Campbell, MD, MS Assistant Professor Department of Genitourinary Medical Oncology The University of Texas MD Anderson Cancer Center Houston, Texas Robert B. Cameron, MD Professor of Cardiothoracic Surgery and Surgical Oncology Department of Surgery David Geffen School of Medicine at University of California, Los Angeles Los Angeles, California Michele Carbone, MD, PhD William & Ellen Melohn Chair in Cancer Biology Director, Thoracic Oncology University of Hawaii Cancer Center Professor, Department of Pathology John A. Burns School of Medicine Honolulu, Hawaii Thomas E. Carey, PhD Professor Department of Otolaryngology/Head and Neck Surgery University of Michigan Ann Arbor, Michigan Paolo G. Casali, MD Associate Professor University of Milan Director of Medical Oncology Unit 2 Fondazione IRCCS Istituto Nazionale dei Tumori Milan, Italy Eric J. Cassell, MD, MACP Adjunct Professor Weill Cornell Medical College New York, New York Jane H. Cerhan, PhD, ABPP Department of Psychiatry and Psychology Mayo Clinic Rochester, Minnesota

Jan Cerny, MD, PhD, FACP Associate Professor of Medicine Division of Hematology/Oncology Department of Medicine Director, Leukemia Program Co-Director, Blood and Bone Marrow Transplant Program University of Massachusetts Medical School Associate Director, Cancer Research Office UMass Memorial Cancer Center Worcester, Massachusetts Debyani Chakravarty, PhD Lead Scientist OncoKB Kravis Center for Molecular Oncology Memorial Sloan Kettering Cancer Center New York, New York Ronald Chamberlain, MD, MPA, FACS Clinical Professor The University of Texas MD Anderson Cancer Center Houston, Texas Chief of Surgery Banner MD Anderson Cancer Center Gilbert, Arizona Richard Champlin, MD Chairman, Department of Stem Cell Transplantation and Cellular Therapy The University of Texas MD Anderson Cancer Center Houston, Texas Susan M. Chang, MD Professor Division of Neuro-Oncology in the Department of Neurological Surgery University of California, San Francisco San Francisco, California Douglas B. Chepeha, MD, MScPH, FACS, FRCSC Professor Department of Otolaryngology-Head & Neck Surgery Department of Facial Plastic Reconstructive Surgery University of Toronto Toronto, Ontario, Canada Professor Department of Otolaryngology/Head and Neck Surgery University of Michigan Ann Arbor, Michigan Nathan I. Cherny, MBBS, FRACP, FRCP, LLD Norman Levan Chair of Humanistic Medicine Director, Cancer Pain and Palliative Medicine Service Department of Medical Oncology Shaare Zedek Medical Center Jerusalem, Israel Anne Chiang, MD, PhD Associate Professor

Department of Medicine Yale University School of Medicine New Haven, Connecticut Clifford S. Cho, MD C. Gardner Child Professor of Surgery Chief Division of Hepatopancreatobiliary and Advanced Gastrointestinal Surgery University of Michigan Medical School Ann Arbor, Michigan Edward Chow, MBBS, MSc, PhD, FRCPC Professor Department of Radiation Oncology University of Toronto Sunnybrook Odette Cancer Centre Toronto, Ontario, Canada Sean R. Christensen, MD, PhD Assistant Professor Department of Dermatology Section of Dermatologic Surgery and Cutaneous Oncology Yale University School of Medicine New Haven, Connecticut Alicia Y. Christy, MD Deputy Director Reproductive Health Women’s Health Services Veterans Health Administration Washington, District of Columbia Edward Chu, MD Professor of Medicine and Pharmacology & Chemical Biology Chief, Division of Hematology-Oncology Deputy Director, UPMC Hillman Cancer Center University of Pittsburgh School of Medicine Pittsburgh, Pennsylvania Callisia N. Clarke, MD Assistant Professor of Surgery Division of Surgical Oncology Medical College of Wisconsin Milwaukee, Wisconsin Erin Cobain, MD Assistant Professor Division of Hematology and Oncology Department of Medicine University of Michigan School of Medicine Ann Arbor, Michigan Robert E. Coleman, MB, BS, MD, FRCP Emeritus Professor Department of Oncology and Metabolism University of Sheffield

Sheffield, United Kingdom Nicolò Compagno, MD Research Scientist Institute for Cancer Genetics Columbia University New York, New York Louis S. Constine, MD, FASTRO Professor of Radiation Oncology and Pediatrics Vice Chair, Department of Radiation Oncology Director, Judy DiMarzo Cancer Survivorship Program University of Rochester Medical Center Rochester, New York M. Sitki Copur, MD, FACP Medical Oncology/Hematology MORRISON CANCER CENTER Mary Lanning Healthcare Hastings, Nebraska Professor University of Nebraska Medical Center Omaha, Nebraska Stefan Cordes, MD, PhD Clinical Fellow Hematology Branch National Heart, Lung and Blood Institute National Institutes of Health Bethesda, Maryland Andres F. Correa, MD Urologic Oncology Fellow Fox Chase Cancer Center Philadelphia, Pennsylvania Aimee M. Crago, MD, PhD, FACS Associate Attending Surgeon Gastric and Mixed Tumor Service Department of Surgery Memorial Sloan Kettering Cancer Center New York, New York David Crockett, MD CHI Health St. Francis Cancer Treatment Center Grand Island, Nebraska Jennifer Cuellar-Rodriguez, MD Clinician Researcher Department of Infectious Diseases Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán Associate Professor Universidad Nacional Autónoma de México Mexico City, Mexico Brian G. Czito, MD Gary Hock and Lyn Proctor Associate Professor

Department of Radiation Oncology Duke University Durham, North Carolina Douglas M. Dahl, MD, FACS Associate Professor of Surgery Harvard Medical School Chief, Division of Urologic Oncology Department of Urology Massachusetts General Hospital Boston, Massachusetts Charles Dai, MD Research Fellow Lerner Research Institute Cleveland Clinic Cleveland, Ohio Riccardo Dalla-Favera, MD Director Institute for Cancer Genetics Columbia University New York, New York Professor Executive Vice Chairman Director of Clinical Affairs Department of Therapeutic Radiology Yale School of Medicine New Haven, Connecticut Caroline J. Davidge-Pitts, MB, BCh Assistant Professor Division of Endocrinology Mayo Clinic Rochester, Minnesota Michael A. Davies, MD, PhD Associate Professor, Deputy Chairman Department of Melanoma Medical Oncology The University of Texas MD Anderson Cancer Center Houston, Texas Jeremy L. Davis, MD Surgeon-in-Chief NIH Clinical Center Bethesda, Maryland Marcos de Lima, MD Director, Stem Cell Transplant Program University Hospitals of Cleveland Professor of Medicine Case Western Reserve University Cleveland, Ohio Alan H. DeCherney, MD Head, Reproductive Endocrinology and Gynecology

Eunice Kennedy Shriver National Institute of Child Health and Human Development National Institutes of Health Bethesda, Maryland Roy H. Decker, MD, PhD Professor and Vice Chair Department of Therapeutic Radiology Yale School of Medicine New Haven, Connecticut Angelo Paolo Dei Tos, MD Professor of Pathology Department of Medicine University of Padua School of Medicine Padua, Italy Marcello Deraco, MD Director of Peritoneal Surface Malignancies Unit Fondazione IRCCS Istituto Nazionale dei Tumori Milan, Italy Hari A. Deshpande, MD Associate Professor of Medicine Yale Cancer Center Smilow Cancer Hospital New Haven, Connecticut Frank C. Detterbeck, MD Professor and Chief, Thoracic Surgery Department of Surgery Yale University New Haven, Connecticut Khanh Do, MD Assistant Professor Medical Oncology Dana-Farber Cancer Institute Boston, Massachusetts Ahmet Dogan, MD, PhD Chief Hematopathology Service Memorial Sloan Kettering Cancer Center New York, New York Jessica Donington, MD, MSCR Professor and Chief, General Thoracic Surgery Department of Surgery The University of Chicago Chicago, Illinois James H. Doroshow, MD Director, Division of Cancer Treatment and Diagnosis Deputy Director for Clinical and Translational Research National Cancer Institute

National Institutes of Health Bethesda, Maryland Steven G. DuBois, MD, MS Associate Professor Department of Pediatrics Harvard Medical School Dana-Farber/Boston Children’s Cancer and Blood Disorders Center Boston, Massachusetts Damian E. Dupuy, MD, FACR Professor of Diagnostic Imaging Alpert Medical School of Brown University Director of Tumor Ablation Cape Cod Hospital Hyannis, Massachusetts Peter T. Dziegielewski, MD, FRCSC Chief of Head and Neck Surgical Oncology and Microvascular Reconstructive Surgery Department of Otolaryngology University of Florida Gainesville, Florida James A. Eastham, MD Chief, Urology Service Department of Surgery Memorial Sloan Kettering Cancer Center New York, New York Jason A. Efstathiou, MD, DPhil Associate Professor Harvard Medical School Director, Genitourinary Division Department of Radiation Oncology Massachusetts General Hospital Boston, Massachusetts Christopher A. Eide, BA Research Specialist Division of Hematology/Medical Oncology Knight Cancer Institute Oregon Health & Science University Portland, Oregon Patricia J. Eifel, MD Professor Department of Radiation Oncology The University of Texas MD Anderson Cancer Center Houston, Texas Tobias Else, MD Assistant Professor Department of Internal Medicine University of Michigan Ann Arbor, Michigan Cathy Eng, MD, FACP

Professor Department of Gastrointestinal Medical Oncology The University of Texas MD Anderson Cancer Center Houston, Texas Douglas B. Evans, MD Donald C. Ausman Family Foundation Professor of Surgery Chair, Department of Surgery Medical College of Wisconsin Milwaukee, Wisconsin Jane M. Fall-Dickson, PhD, RN, AOCN Associate Professor and Assistant Chair, Research Department of Professional Nursing Practice Georgetown University School of Nursing & Health Studies Washington, District of Columbia Meagan B. Farmer, MS, CGC, MBA Director, Cancer Genetic Counseling Department of Genetics University of Alabama at Birmingham Birmingham, Alabama Adam S. Feldman, MD, MPH Assistant Professor, Department of Urology Massachusetts General Hospital Harvard Medical School Boston, Massachusetts Mary Feng, MD Professor Department of Radiation Oncology University of California, San Francisco San Francisco, California Andrea Ferrari, MD Pediatric Oncology Unit Fondazione IRCCS Istituto Nazionale Dei Tumori Milan, Italy Paul T. Finger, MD, FACS Director, The New York Eye Cancer Center Clinical Professor of Ophthalmology New York University School of Medicine Director, Ophthalmic Oncology Service The New York Eye and Ear Infirmary of Mt. Sinai New York, New York Joel A. Finkelstein, MD, MSc, FRCSC Feldberg Chair in Spinal Research Associate Professor Division of Orthopaedics Sunnybrook Health Sciences Centre University of Toronto Toronto, Ontario, Canada

Olivera J. Finn, PhD Distinguished Professor Department of Immunology University of Pittsburgh School of Medicine Pittsburgh, Pennsylvania Gini F. Fleming, MD Professor of Medicine Department of Medicine The University of Chicago Chicago, Illinois Tito Fojo, MD, PhD Professor Department of Medicine Columbia University New York, New York Yuman Fong, MD Sangiacomo Chair in Surgical Oncology Chair and Professor, Department of Surgery Professor of Experimental Therapeutics City of Hope National Medical Center Duarte, California Francine M. Foss, MD Professor of Medicine Hematology and Stem Cell Transplantation Yale University School of Medicine New Haven, Connecticut Arnold S. Freedman, MD Professor of Medicine Division of Hematologic Malignancies Dana-Farber Cancer Institute Harvard Medical School Boston, Massachusetts Professor of Medicine Anheuser Busch Chair in Medical Oncology Director, Section of Medical Oncology Division of Oncology Washington University School of Medicine St. Louis, Missouri Chunkit Fung, MD, MSCE Assistant Professor Department of Medicine University of Rochester Rochester, New York Associate Professor Department of Radiation Oncology University of California, San Francisco San Francisco, California Larissa V. Furtado, MD Associate Professor Department of Pathology

University of Utah Medical Director, Molecular Oncology ARUP Laboratories Salt Lake City, Utah Carlo Gambacorti-Passerini, MD Professor of Hematology University of Milano Bicocca Director, Department of Hematology San Gerardo Hospital Monza, Italy Dron Gauchan, MD Assistant Professor, Adjunct Faculty University of Nebraska Medical Center Omaha, Nebraska CHI Health St. Francis Cancer Treatment Center Grand Island, Nebraska Juan C. Gea-Banacloche, MD Senior Associate Consultant Division of Infectious Diseases Mayo Clinic Arizona Phoenix, Arizona Nasrin Ghalyaie, MD, FACS, FASCRS Colon and Rectal Surgeon Adjunct Assistant Professor of Surgery Banner MD Anderson Cancer Center Gilbert, Arizona Michael Girardi, MD Professor and Vice Chair Department of Dermatology Yale School of Medicine New Haven, Connecticut Karthik V. Giridhar, MD Instructor in Oncology Division of Medical Oncology Mayo Clinic Rochester, Minnesota Iulia Giuroiu, MD Bernard and Irene Schwartz Gastrointestinal Oncology Fellow Division of Hematology & Medical Oncology NYU School of Medicine New York, New York Olivier Glehen, MD, PhD Professor General Surgery Chief Department of General Surgery Centre Hospitalier Lyon Sud Pierre-Bénite, France

Matthew P. Goetz, MD Professor of Oncology and Pharmacology Chair, Mayo Breast Cancer Research Mayo Clinic Rochester, Minnesota Stephanie L. Goff, MD, FACS Staff Clinician Surgery Branch National Cancer Institute National Institutes of Health Bethesda, Maryland Talia Golan, MD Medical Director Phase I Program and Pancreatic Cancer Program Oncology Institute Sheba Medical Center Ramat Gan, Israel Donald P. Goldstein, MD Professor of Obstetrics, Gynecology and Reproductive Biology, Emeritus Harvard Medical School Boston, Massachusetts Leonard G. Gomella, MD, FACS The Bernard W. Godwin Professor of Prostate Cancer Chairman, Department of Urology Senior Director, Clinical Affairs Clinical Director Sidney Kimmel Cancer Center at Jefferson Thomas Jefferson University/Thomas Jefferson University Hospital Philadelphia, Pennsylvania Karyn A. Goodman, MD, MS Professor Grohne Chair in Clinical Cancer Research Department of Radiation Oncology University of Colorado Aurora, Colorado Ramaswamy Govindan, MD Professor of Medicine Director, Section of Oncology Department of Internal Medicine Washington University School of Medicine St. Louis, Missouri Michael D. Green, MD, PhD House Officer Department of Radiation Oncology University of Michigan Ann Arbor, Michigan Alessandro Gronchi, MD Chief, Sarcoma Service

Department of Surgery Fondazione IRCCS Istituto Nazionale dei Tumori Milan, Italy Oliver Grundmann, PhD, MS Clinical Associate Professor Department of Medicinal Chemistry University of Florida Gainesville, Florida José G. Guillem, MD, MPH Professor Department of Surgery Memorial Sloan Kettering Cancer Center New York, New York Murat Günel, MD Chairman and Chief, Department of Neurosurgery Nixdorff-German Professor of Neurosurgery Professor of Neurobiology and Genetics Yale School of Medicine Yale New Haven Hospital New Haven, Connecticut Jennifer Moliterno Günel, MD Chief, Section of Neurosurgical Oncology Department of Neurosurgery Yale School of Medicine Smilow Cancer Hospital New Haven, Connecticut Vikas A. Gupta, MD, PhD Assistant Professor Department of Hematology and Medical Oncology Winship Cancer Institute of Emory University Atlanta, Georgia Daphne A. Haas-Kogan, MD Professor and Chair Department of Radiation Oncology Brigham and Women’s Hospital Dana-Farber Cancer Institute Boston Children’s Hospital Harvard Medical School Boston, Massachusetts Mehdi Hamadani, MD Professor of Medicine Director, Blood and Marrow Transplantation Program Center for International Blood and Marrow Transplant Research Medical College of Wisconsin Milwaukee, Wisconsin Gary D. Hammer, MD, PhD Millie Schembechler of Professor of Adrenal Cancer

Director, Endocrine Oncology Program University of Michigan Ann Arbor, Michigan Catherine H. Han, MBChB, FRACP, PhD Medical Oncologist Auckland Cancer Society Research Centre University of Auckland Auckland, New Zealand Douglas Hanahan, PhD Professor and Director Swiss Institute for Experimental Cancer Research School of Life Sciences Swiss Federal Institute of Technology Lausanne Lausanne, Switzerland Christine L. Hann, MD, PhD Assistant Professor of Oncology Johns Hopkins University School of Medicine Baltimore, Maryland Parameswaran N. Hari, MD Chief, Division of Hematology Oncology Department of Medicine Medical College of Wisconsin Milwaukee, Wisconsin Lyndsay Harris, MD, FRCPC Acting Associate Director, Cancer Diagnosis Program National Cancer Institute Rockville, Maryland Jay R. Harris, MD Professor of Radiation Oncology, Emeritus Harvard Medical School Boston, Massachusetts Daniel F. Hayes, MD, FASCO, FACP Stuart B. Padnos Professor of Clinical Research University of Michigan Comprehensive Cancer Center Professor, Department of Internal Medicine Michigan Medicine Ann Arbor, Michigan Jonathan M. Hernandez, MD Investigator National Cancer Institute National Institutes of Health Bethesda, Maryland Paul J. Hesketh, MD Director, Lahey Health Cancer Institute Lahey Hospital & Medical Center Professor of Medicine

Tufts University School of Medicine Boston, Massachusetts Jay L. Hess, MD, PhD Executive Vice President for University Clinical Affairs Dean of the School of Medicine Indiana University Indianapolis, Indiana Christopher J. Hoimes, DO Associate Professor Department of Medicine, Medical Oncology Case Western Reserve University University Hospitals Seidman Cancer Center Cleveland, Ohio Neil S. Horowitz, MD Assistant Professor of Obstetrics, Gynecology, and Reproductive Medicine Harvard Medical School Director of Clinical Research Division of Gynecologic Oncology Brigham and Women’s Hospital Boston, Massachusetts Ralph H. Hruban, MD Baxley Professor and Director of Pathology Director, The Sol Goldman Pancreatic Cancer Research Center Johns Hopkins University School of Medicine Baltimore, Maryland Maureen B. Huhmann, DCN, RD, CSO Adjunct Assistant Professor Department of Nutrition Sciences Rutgers, The State University of New Jersey New Brunswick, New Jersey Carolyn D. Hurst, PhD Senior Postdoctoral Research Fellow Section of Molecular Oncology Leeds Institute of Cancer and Pathology St. James’s University Hospital Leeds, United Kingdom Mark Hurwitz, MD Professor and Vice-Chair for Quality Safety and Performance Excellence Department of Radiation Oncology Thomas Jefferson University Philadelphia, Pennsylvania David H. Ilson, MD, PhD Professor Gastrointestinal Oncology Service, Department of Medicine Memorial Sloan Kettering Cancer Center Weill Cornell Medical College New York, New York

Gopa Iyer, MD Assistant Professor Genitourinary Oncology Service Department of Medicine Memorial Sloan Kettering Cancer Center New York, New York Caron A. Jacobson, MD, MMSc Assistant Professor of Medicine Division of Medical Oncology Dana-Farber Cancer Institute Harvard Medical School Boston, Massachusetts Mohammad S. Jafferji, MD Fellow, Surgical Oncology & Cancer Immunotherapy Surgery Branch National Cancer Institute National Institutes of Health Bethesda, Maryland Reshma Jagsi, MD, DPhil Professor and Deputy Chair Department of Radiation Oncology University of Michigan Ann Arbor, Michigan Ahmedin Jemal, DVM, PhD Vice President Surveillance and Health Services Research Program American Cancer Society Atlanta, Georgia Douglas B. Johnson, MD, MSCI Assistant Professor of Medicine Vanderbilt University School of Medicine Nashville, Tennessee Peter Johnson, MD, FRCP, FMedSci Cancer Research UK Professor of Medical Oncology University of Southampton Southampton, United Kingdom Matthew F. Kalady, MD Professor of Surgery and Vice-Chairman Co-Director, Comprehensive Colorectal Cancer Program Department of Colorectal Surgery Digestive Disease and Surgery Institute Cleveland Clinic Cleveland, Ohio Arif H. Kamal, MD, MBA, MHS Associate Professor Division of Medical Oncology and Section of Palliative Care Duke University Durham, North Carolina

Robert J. Kaner, MD Associate Professor of Clinical Medicine Associate Professor of Genetic Medicine Weill Cornell Medicine New York, New York Jose A. Karam, MD, FACS Associate Professor Departments of Urology and Translational Molecular Pathology The University of Texas MD Anderson Cancer Center Houston, Texas Partow Kebriaei, MD Professor Department of Stem Cell Transplantation and Cellular Therapy The University of Texas MD Anderson Cancer Center Houston, Texas Christopher J. Kemp, MS, PhD Member Human Biology and Public Health Sciences Divisions Fred Hutchinson Cancer Research Center Seattle, Washington Scott E. Kern, MD Kovler Professor of Oncology and Pathology Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins Baltimore, Maryland Tari A. King, MD Associate Chair for Multidisciplinary Oncology Department of Surgery Brigham and Women’s Hospital Chief, Breast Surgery Dana-Farber/Brigham and Women’s Cancer Center Anne E. Dyson Associate Professor of Surgery Harvard Medical School Boston, Massachusetts Christopher J. Kirk, PhD Chief Scientific Officer Kezar Life Sciences South San Francisco, California David G. Kirsch, MD, PhD Barbara Levine University Professor Professor and Vice Chair for Basic & Translational Research Department of Radiation Oncology Professor, Department of Pharmacology & Cancer Biology Duke University School of Medicine Durham, North Carolina Ann H. Klopp, MD, PhD Associate Professor Department of Radiation Oncology The University of Texas MD Anderson Cancer Center

Houston, Texas Margaret A. Knowles, PhD Professor of Experimental Cancer Research Head of Section of Molecular Oncology Leeds Institute of Cancer and Pathology St. James’s University Hospital Leeds, United Kingdom EunJi Michelle Ko, PharmD Senior Safety Program Manager Department of Quality and Safety Brigham and Women’s Hospital Boston, Massachusetts Manish Kohli, MD Consultant and Professor of Oncology Division of Medical Oncology Department of Oncology Mayo Clinic Rochester, Minnesota Rami S. Komrokji, MD Senior Member and Professor of Oncologic Sciences Section Head, Leukemia and MDS Vice Chair, Malignant Hematology Department H. Lee Moffitt Cancer Center and Research Institute Tampa, Florida Panagiotis A. Konstantinopoulos, MD, PhD Director Translational Research Gynecologic Oncology Dana-Farber Cancer Institute Associate Professor of Medicine Harvard Medical School Boston, Massachusetts Rupesh Kotecha, MD Department of Radiation Oncology Miami Cancer Institute Baptist Health South Florida Miami, Florida Anupam Kotwal, MBBS Clinical Fellow Division of Endocrinology, Diabetes, Metabolism and Nutrition Mayo Clinic Rochester, Minnesota Adam J. Krieg, PhD Assistant Professor Department of Obstetrics and Gynecology Oregon Health & Science University Portland, Oregon Robert S. Krouse, MD, FACS

Chief, Surgical Services Corporal Michael J. Crescenz VA Medical Center Department of Surgery University of Pennsylvania Philadelphia, Pennsylvania Lee M. Krug, MD Bristol-Myers Squibb Lawrenceville, New Jersey Shaji Kumar, MD Professor of Medicine Division of Hematology Mayo Clinic Rochester, Minnesota Shivaani Kummar, MD, FACP Professor of Medicine (Oncology) and Radiology Director, Phase I Clinical Research Program Director, Translational Oncology Program at Stanford Stanford University School of Medicine Stanford, California John Kuruvilla, MD, FRCPC Associate Professor, Hematologist Division of Medical Oncology and Hematology Princess Margaret Cancer Centre University of Toronto Toronto, Ontario, Canada Wendy Landier, PhD, CRNP Associate Professor Department of Pediatrics School of Medicine University of Alabama at Birmingham Birmingham, Alabama Brian R. Lane, MD, PhD Chief, Division of Urology Spectrum Health Grand Rapids, Michigan Jill E. Larsen, PhD Senior Research Officer QIMR Berghofer Medical Research Institute Brisbane, Australia Theodore S. Lawrence, MD, PhD Isadore Lampe Professor and Chair Department of Radiation Oncology University of Michigan Ann Arbor, Michigan Yaacov Richard Lawrence, MBBS, MA, MRCP Vice Chair, and Director, Center for Translational Research in Radiation Oncology Department of Radiation Oncology Sheba Medical Center

Tel HaShomer, Israel Senior Lecturer Sackler Faculty of Medicine Tel Aviv University Tel Aviv, Israel Assistant Professor (adjunct) Department of Radiation Oncology Sidney Kimmel Medical College at Thomas Jefferson University Philadelphia, Pennsylvania Hillard M. Lazarus, MD, FACP Professor of Medicine Case Western Reserve University School of Medicine Cleveland, Ohio Philipp le Coutre, MD Professor of Internal Medicine Charité – Universitätsmedizin Berlin Berlin, Germany Thomas W. LeBlanc, MD, MA, MHS, FAAHPM Associate Professor of Medicine Division of Hematologic Malignancies and Cellular Therapy Duke University School of Medicine Durham, North Carolina James J. Lee, MD, PhD Associate Professor of Medicine Division of Hematology-Oncology Department of Medicine University of Pittsburgh School of Medicine Pittsburgh, Pennsylvania Percy P. Lee, MD Associate Professor Vice Chair of Education Department of Radiation Oncology University of California, Los Angeles Los Angeles, California Richard J. Lee, MD, PhD Assistant Professor Harvard Medical School Massachusetts General Hospital Cancer Center Boston, Massachusetts David J. Leffell, MD David Paige Smith Professor of Dermatology & Surgery Chief, Section of Dermatologic Surgery & Cutaneous Oncology Yale School of Medicine New Haven, Connecticut Constance Lehman, MD, PhD Professor

Department of Radiology Harvard Medical School Chief of Breast Imaging Massachusetts General Hospital Boston, Massachusetts Antonio M. Lerario, MD, PhD Assistant Research Scientist Department of Endocrinology and Metabolism Michigan Medicine Ann Arbor, Michigan Rebecca A. Levine, MD Assistant Professor Department of Surgery Montefiore Medical Center Albert Einstein School of Medicine Bronx, New York Steven K. Libutti, MD Director and Professor Rutgers Cancer Institute of New Jersey Rutgers, The State University of New Jersey New Brunswick, New Jersey Jennifer A. Ligibel, MD Associate Professor Harvard Medical School Senior Physician Dana-Farber Cancer Institute Boston, Massachusetts W. Marston Linehan, MD Chief, Urologic Oncology Branch Center for Cancer Research National Cancer Institute National Institutes of Health Bethesda, Maryland Scott M. Lippman, MD Director, Moores Cancer Center Senior Associate Dean and Associate Vice Chancellor for Cancer Research and Care Chugai Pharmaceutical Chair in Cancer Professor of Medicine University of California, San Diego San Diego, California Roy Lirov, MD Endocrine Surgery Fellow University of Michigan Ann Arbor, Michigan Alan F. List, MD Senior Member Department of Malignant Hematology President and CEO, Moffitt Cancer Center

Tampa, Florida Mats Ljungman, PhD Professor Departments of Radiation Oncology and Environmental Health Sciences University of Michigan Ann Arbor, Michigan Patrick J. Loehrer Sr., MD Distinguished Professor HH Gregg Professor of Oncology Director, Indiana University Melvin and Bren Simon Cancer Center Associate Dean for Cancer Research Indiana University School of Medicine Indianapolis, Indiana Christopher J. Logothetis, MD Chair and Professor Genitourinary Medical Oncology The University of Texas MD Anderson Cancer Center Houston, Texas Carlos López-Otin, PhD Professor, Departamento de Bioquímica y Biología Molecular Instituto Universitario de Oncología Universidad de Oviedo Oviedo, Spain Sam Lubner, MD Associate Professor Department of Medicine UW Carbone Cancer Center Madison, Wisconsin Matthew A. Lunning Associate Professor Department of Internal Medicine University of Nebraska Medical Center Omaha, Nebraska Teresa H. Lyden, MA, CCC-SLP Speech Language Pathologist Department of Otolaryngology/Head and Neck Surgery University of Michigan Ann Arbor, Michigan Xiaomei Ma, PhD Professor Department of Chronic Disease Epidemiology Yale University New Haven, Connecticut Hoyoung M. Maeng, MD Acting Clinical Director Vaccine Branch National Cancer Institute

National Institutes of Health Bethesda, Maryland Ajay V. Maker, MD, FACS Associate Professor Department of Surgery, Division of Surgical Oncology University of Illinois at Chicago Director of Surgical Oncology Creticos Cancer Center at Advocate Illinois Masonic Medical Center Chicago, Illinois J. Ryan Mark, MD Assistant Professor Department of Urology Thomas Jefferson University Philadelphia, Pennsylvania Jens U. Marquardt, MD Attending Physician Lichtenberg Professor for Molecular Hepatocarcinogenesis Co-Head Core Facility Bioinformatics Mainz (Bium-Mz) Department of Medicine I Universitätsmedizin Mainz Mainz, Germany Alexander Marx, MD Professor of Pathology Institute of Pathology University Medical Centre Mannheim University of Heidelberg Mannheim, Germany Ellen T. Matloff, MS, CGC President and CEO My Gene Counsel Branford, Connecticut Howard L. McLeod, PharmD, FCCP Chair, Personalized Cancer Medicine Medical Director, DeBartolo Family Personalized Medicine Institute Moffitt Cancer Center Tampa, Florida Minesh P. Mehta, MD, FASTRO Professor and Chair, Department of Radiation Oncology Florida International University Deputy Director Miami Cancer Institute Chief of Radiation Oncology Baptist Health Miami, Florida William M. Mendenhall, MD, FACR, FASTRO Professor Department of Radiation Oncology University of Florida Gainesville, Florida

Jeffrey A. Meyerhardt, MD, MPH Associate Professor of Medicine Dana-Farber Cancer Institute Harvard Medical School Boston, Massachusetts Karin B. Michels, ScD, PhD Professor and Chair Department of Epidemiology Fielding School of Public Health University of California, Los Angeles Los Angeles, California John D. Minna, MD Professor Internal Medicine & Pharmacology UT Southwestern Medical Center Dallas, Texas Sandra A. Mitchell, PhD, CRNP, FAAN Research Scientist and Program Director Outcomes Research Branch National Cancer Institute National Institutes of Health Rockville, Maryland David T. Miyamoto, MD, PhD Assistant Professor of Radiation Oncology Department of Radiation Oncology Harvard Medical School Massachusetts General Hospital Boston, Massachusetts Kabir Mody, MD Assistant Professor and Consultant Division of Hematology and Oncology Mayo Clinic Cancer Center Mayo Clinic Jacksonville, Florida Dipika R. Mohan, BSME Medical Scientist Training Program Fellow, Doctoral Program in Cancer Biology University of Michigan Medical School Ann Arbor, Michigan Bradley J. Monk, MD, FACS, FACOG Arizona Oncology (US Oncology Network) Professor of Gynecologic Oncology University of Arizona and Creighton University Medical Director US Oncology Research Gynecology Program Phoenix, Arizona Meredith A. Morgan, PhD Assistant Professor

Department of Radiation Oncology University of Michigan Ann Arbor, Michigan Daniel Morgensztern, MD Associate Professor Division of Medical Oncology Washington University School of Medicine St. Louis, Missouri David Morris, MB, ChB, FRCS, FRCSE, MD, PhD, FRACS Professor of Surgery Department of Surgery St. George Hospital University of New South Wales New South Wales, Australia Michael J. Morris, MD Associate Member Genitourinary Oncology Service Memorial Sloan Kettering Cancer Center New York, New York Monica Morrow, MD Chief, Breast Surgery Anne Burnett Windfohr Chair of Clinical Oncology Memorial Sloan Kettering Cancer Center New York, New York Andrea Ng, MD, MPH Professor Department of Radiation Oncology Brigham and Women’s Hospital Dana-Farber Cancer Institute Harvard Medical School Boston, Massachusetts Aviram Nissan, MD Professor and Chief Department of General & Oncological Surgery—Surgery C The Chaim Sheba Medical Center Tel Hashomer, Israel Ajay K. Nooka, MD MPH Associate Professor Department of Hematology and Oncology Emory University Atlanta, Georgia Jeffrey A. Norton, MD Professor of Surgery Department of Surgery Chief of Surgical Oncology Stanford University School of Medicine Stanford, California

Ana T. Nunes, MD, PhD Medical Oncology Fellow National Cancer Institute National Institutes of Health Bethesda, Maryland Susan M. O’Brien, MD Associate Director for Clinical Sciences Chao Family Comprehensive Cancer Center University of California, Irvine Irvine, California Richard J. O’Connor, PhD Professor of Oncology Department of Health Behavior Roswell Park Comprehensive Cancer Center Buffalo, New York Richard J. O’Donnell, MD Professor of Clinical Orthopaedic Surgery University of California, San Francisco Chief, Orthopaedic Oncology Service Co-Director, Sarcoma Program Co-Director, International Center for Osseointegration Research, Education, and Surgery University of California, San Francisco Medical Center University of California, San Francisco Benioff Children’s Hospitals University of California, San Francisco Helen Diller Family Comprehensive Cancer Center University of California, San Francisco Bakar Cancer Hospital San Francisco, California Kunle Odunsi, MD, PhD Cancer Center Deputy Director The M. Steven Piver Professor and Chair Department of Gynecologic Oncology Executive Director, Center for Immunotherapy Roswell Park Comprehensive Cancer Center Buffalo, New York Peter J. O’Dwyer, MD Professor of Medicine University of Pennsylvania Philadelphia, Pennsylvania Kevin C. Oeffinger, MD Director, Duke Center for Onco-Primary Care Professor, Department of Medicine Duke University Durham, North Carolina Dawn Owen, MD, PhD Assistant Professor Department of Radiation Oncology University of Michigan Ann Arbor, Michigan Eric Padron, MD

Assistant Member Malignant Hematology H. Lee Moffitt Cancer Center Tampa, Florida Tara N. Palmore, MD Hospital Epidemiologist NIH Clinical Center Bethesda, Maryland Pier Paolo Pandolfi, MD, PhD Director, Cancer Center and Cancer Research Institute Beth Israel Deaconess Medical Center Harvard Medical School Boston, Massachusetts Howard L. Parnes, MD Chief Prostate and Urologic Cancer Research Group Division of Cancer Prevention National Cancer Institute National Institutes of Health Bethesda, Maryland Michael W. Parsons, PhD, ABPP Pappas Center for Neuro-Oncology Massachusetts General Hospital Cancer Center Boston, Massachusetts Mark Parta, MD, MPHTM Clinical Research Directorate/Clinical Monitoring Research Program, Frederick National Laboratory for Cancer Research Acting Chief, Infectious Diseases Consult Service, Warren Grant Magnuson Clinical Center National Institutes of Health Bethesda, Maryland Laura Pasqualucci, MD Professor of Pathology and Cell Biology Department of Pathology and Cell Biology Institute for Cancer Genetics Columbia University New York, New York Harvey I. Pass, MD Stephen A. Banner Professor of Thoracic Oncology Director, General Thoracic Surgery Department of Cardiothoracic Surgery NYU Langone Health New York, New York Tushar Patel, MBChB Dean for Research Mayo Clinic Jacksonville, Florida Sachin Patil, MD, MBBS

General and HPB Surgeon Department of Surgery South Central Regional Medical Center Laurel, Mississippi George Patounakis, MD, PhD Medical Director Reproductive Medicine Associates of Florida Lake Mary, Florida Assistant Professor Department of Obstetrics and Gynecology University of Central Florida College of Medicine Orlando, Florida Anna C. Pavlick, MD, MBA Professor of Medicine and Dermatology Division of Medical Oncology NYU Langone’s Perlmutter Cancer Center New York, New York Tanja Pejovic, MD, PhD Associate Professor Division of Gynecologic Oncology Department of Obstetrics and Gynecology Oregon Health & Science University Portland, Oregon Richard T. Penson, MD, MRCP Associate Professor of Medicine Harvard Medical School Clinical Director Medical Gynecologic Oncology Massachusetts General Hospital Boston, Massachusetts David G. Pfister, MD Member and Attending Physician Chief, Head and Neck Oncology Department of Medicine Co-Leader, Head and Neck Cancer Disease Management Team Memorial Sloan Kettering Cancer Center Professor of Medicine Weill Cornell Medical College New York, New York Manju V. Pillai, MD Assistant Attending Professor Departments of Internal Medicine and Pharmacology Collegiate Professor of Experimental Therapeutics Memorial Sloan Kettering Cancer Center New York, New York Yves Pommier, MD, PhD Chief, Developmental Therapeutics Branch and Laboratory of Molecular Pharmacology Center for Cancer Research National Cancer Institute

National Institutes of Health Bethesda, Maryland James A. Posey, PhD Professor Department of Medicine Thomas Jefferson University Philadelphia, Pennsylvania Mitchell C. Posner, MD, FACS Thomas D. Jones Professor of Surgery and Vice-Chairman Chief, Section of General Surgery and Surgical Oncology Physician-in-Chief, UCM Comprehensive Cancer Center Professor, Radiation and Cellular Oncology The University of Chicago Medicine Chicago, Illinois Mark E. Prince, MD Professor Department of Otolaryngology/Head and Neck Surgery University of Michigan Ann Arbor, Michigan Glen D. Raffel, MD, PhD Associate Professor Division of Hematology-Oncology University of Massachusetts Medical School UMass Memorial Medical Center Worcester, Massachusetts S. Vincent Rajkumar, MD Edward W. and Betty Knight Scripps Professor of Medicine Division of Hematology Mayo Clinic Rochester, Minnesota Ryan Ramaekers, MD Medical Oncology/Hematology CHI Health St. Francis Cancer Treatment Center Grand Island, Nebraska Lee Ratner, MD, PhD Professor of Medicine and Molecular Microbiology Washington University School of Medicine St. Louis, Missouri Farhad Ravandi, MD Janiece and Stephen A. Lasher Professor of Medicine Chief, Section of Developmental Therapeutics Department of Leukemia The University of Texas MD Anderson Cancer Center Houston, Texas Paul Read, MD, PhD Professor of Radiation Oncology University of Virginia

Charlottesville, Virginia Kim A. Reiss, MD Assistant Professor Division of Hematology Oncology University of Pennsylvania Philadelphia, Pennsylvania Natasha Rekhtman, MD, PhD Associate Attending Department of Pathology Memorial Sloan Kettering Cancer Center New York, New York Michelle B. Riba, MD, MS Clinical Professor Department of Psychiatry University of Michigan Ann Arbor, Michigan Antoni Ribas, MD, PhD Professor of Medicine Professor of Surgery Professor of Molecular and Medical Pharmacology Director, Tumor Immunology Program, Jonsson Comprehensive Cancer Center Director, Parker Institute for Cancer Immunotherapy Center at UCLA David Geffen School of Medicine University of California Los Angeles Los Angeles, California Stanley R. Riddell, MD Member, Clinical Research Division Fred Hutchinson Cancer Research Center Seattle, Washington Andreas Rimner, MD Assistant Professor Department of Radiation Oncology Memorial Sloan Kettering Cancer Center New York, New York Brian I. Rini, MD Leader, GU Program Cleveland Clinic Taussig Cancer Institute Cleveland, Ohio R. Taylor Ripley, MD Associate Professor Debakey Department of Surgery Division of General Thoracic Surgery Baylor College of Medicine Houston, Texas Matthew K. Robinson, PhD Vice President, Research & Development Immunome

Exton, Pennsylvania Ashley M. Roque, MD Clinical Fellow Department of Neuro-Oncology Yale New Haven Hospital Medical Director, Healthcare Management Service, Amerigroup, Anthem, Inc. Professor of Surgery (Hon) Colonel, United States Army, Medical Corps (Ret) New Haven, Connecticut Kenneth E. Rosenzweig, MD Professor and Chair Department of Radiation Oncology Icahn School of Medicine at Mount Sinai New York, New York Charles M. Rudin, MD, PhD Hassenfeld Professor and Chief Thoracic Oncology Service Memorial Sloan Kettering Cancer Center New York, New York Anil K. Rustgi, MD Chief of Gastroenterology T. Grier Miller Professor of Medicine and Genetics American Cancer Society Professor University of Pennsylvania Perelman School of Medicine Philadelphia, Pennsylvania Arjun Sahgal, BSc, MD, FRCPC Professor of Radiation Oncology and Surgery University of Toronto Deputy Chief, Department of Radiation Oncology Odette Cancer Centre Sunnybrook Health Sciences Centre Toronto, Ontario, Canada Zeyad T. Sahli, MD Research Fellow Department of Surgery The Johns Hopkins Hospital Baltimore, Maryland Leonard B. Saltz, MD Attending Physician and Member Department of Medicine Memorial Sloan Kettering Cancer Center New York, New York Yardena Samuels, PhD Associate Professor Incumbent of the Knell Family Professional Chair Director, the EKARD Institute for Cancer Diagnosis Research Department of Molecular Cell Biology The Weizmann Institute of Science Rehovot, Israel

Nikhil Sangave, PharmD PGY-2 Quality and Safety Resident Department of Quality and Safety Brigham and Women’s Hospital Boston, Massachusetts John T. Schiller, PhD NIH Distinguished Investigator National Cancer Institute National Institutes of Health Bethesda, Maryland Laura S. Schmidt, PhD Principal Scientist Basic Science Program Leidos Biomedical Research Frederick National Laboratory for Cancer Research Frederick, Maryland Urologic Oncology Branch, Center for Cancer Research National Cancer Institute National Institutes of Health Bethesda, Maryland Kenneth P. Seastedt, MD, USAF Assistant Professor Department of Surgery Uniformed Services University of the Health Sciences F. Edward Hébert School of Medicine Malcolm Grow Medical Center Joint Base Andrews, Maryland Bijal Shah, MD, MS Assistant Professor Department of Malignant Hematology Moffitt Cancer Center Tampa, Florida Mihir M. Shah, MD Fellow, Complex General Surgical Oncology Clinical Instructor of Surgery Division of Surgical Oncology Rutgers Cancer Institute of New Jersey New Brunswick, New Jersey Nima Sharifi, MD Kendrick Family Endowed Chair for Prostate Cancer Research and Professor Cleveland, Ohio Michelle Shayne, MD Associate Professor of Medicine and Oncology Department of Medicine Wilmot Cancer Institute University of Rochester Medical Center Rochester, New York Ramesh A. Shivdasani, MD, PhD Professor

Dana-Farber Cancer Institute and Harvard Medical School Boston, Massachusetts Vani N. Simmons, PhD Associate Member Department of Health Outcomes and Behavior H. Lee Moffitt Cancer Center and Research Institute Tampa, Florida Richard M. Simon, DSc R. Simon Consulting Potomac, Maryland Samuel Singer, MD Chief, Gastric and Mixed Tumor Service Department of Surgery Memorial Sloan Kettering Cancer Center New York, New York Craig L. Slingluff Jr., MD Joseph Helms Farrow Professor Department of Surgery University of Virginia Charlottesville, Virginia David B. Solit, MD Geoffrey Beene Chair in Cancer Research Director, Kravis Center for Molecular Oncology Attending Physician, Department of Medicine Memorial Sloan Kettering Cancer Center Professor of Medicine Weill Cornell Medical College New York, New York Jeffrey A. Sosman, MD Professor of Medicine Director, Melanoma Program Director, Faculty Development Co-Leader, Translational Research in Solid Tumors Robert H. Lurie Comprehensive Cancer Center of Northwestern University Chicago, Illinois Alex Sparreboom, PhD Professor College of Pharmacy The Ohio State University Columbus, Ohio Corey W. Speers, MD, PhD Assistant Professor Department of Radiation Oncology University of Michigan Ann Arbor, Michigan David Spiegel, MD

Willson Professor and Associate Chair of Psychiatry & Behavioral Sciences Stanford University School of Medicine Stanford, California Daniel E. Spratt, MD Associate Chair, Clinical Research Assistant Professor Department of Radiation Oncology University of Michigan Ann Arbor, Michigan Stacey Stein, MD Assistant Professor of Medicine Yale School of Medicine New Haven, Connecticut Tyler Stewart, MD Fellow Department of Medicine (Medical Oncology) Yale University New Haven, Connecticut Alexander Stojadinovic, MD, MBA, FACS Medical Director, Healthcare Management Service, Amerigroup, Anthem, Inc. Professor of Surgery (Hon) Colonel, United States Army, Medical Corps (Ret) Uniformed Services University of the Health Sciences Bethesda, MD Diane E. Stover, MD Attending Physician Memorial Hospital Clinical Professor of Medicine Weill-Cornell Medical Center New York, New York Michael D. Stubblefield, MD Medical Director for Cancer Rehabilitation Kessler Institute for Rehabilitation West Orange, New Jersey Preeti Subhedar, MD, MS Assistant Professor of Surgery Department of Surgery Winship Cancer Institute Emory University School of Medicine Atlanta, Georgia Paul H. Sugarbaker, MD, FACS, FRCS Director Program in Peritoneal Surface Oncology MedStar Washington Hospital Center Washington, District of Columbia John H. Suh, MD Professor and Chairman Department of Radiation Oncology

Cleveland Clinic Cleveland, Ohio Nicholas Szerlip, MD Associate Professor, Neurosurgery Co-Director, Spine Oncology Program University of Michigan Ann Arbor, Michigan Lynn Tanoue, MD Professor of Medicine Section of Pulmonary, Critical Care and Sleep Medicine Yale School of Medicine New Haven, Connecticut William D. Tap, MD Chief, Sarcoma Medical Oncology Memorial Sloan Kettering Cancer Center New York, New York Michael D. Taylor, MD, PhD Division of Neurosurgery Professor, Department of Surgery University of Toronto Faculty of Medicine The Hospital for Sick Children Toronto, Ontario, Canada Randall K. Ten Haken, PhD Professor Department of Radiation Oncology University of Michigan Ann Arbor, Michigan Kenneth D. Tew, PhD, DSc Professor and Chairman, John C. West Chair in Cancer Research Department of Cellular and Molecular Pharmacology and Experimental Therapeutics Medical University of South Carolina Charleston, South Carolina Krishnansu S. Tewari, MD, FACOG, FACS, FRSM Professor and Interim Division Director Division of Gynecologic Oncology Department of Obstetrics & Gynecology University of California, Irvine Irvine, California Anish Thomas, MD, MA, MHS, FAAHPM Investigator, Lasker Clinical Research Scholar Developmental Therapeutics Branch Center for Cancer Research National Cancer Institute National Institutes of Health Bethesda, Maryland Geoffrey B. Thompson, MD

Section Head, Endocrine Surgery Professor of Surgery Mayo Clinic College of Medicine and Science Rochester, Minnesota Snorri S. Thorgeirsson, MD, PhD Senior Scientist Laboratory of Human Carcinogenesis National Cancer Institute National Institutes of Health Bethesda, Maryland Michael J. Thun, MD, MS Vice President Epidemiology & Surveillance Research, Retired Atlanta, Georgia Lindsey A. Torre, MSPH Senior Epidemiologist Surveillance and Health Services Research American Cancer Society Atlanta, Georgia Giovanna Tosato, MD Senior Investigator Laboratory of Cellular Oncology Center for Cancer Research National Cancer Institute National Institutes of Health Bethesda, Maryland Thuy B. Tran, MD General Surgery Resident Department of Surgery University of Illinois at Chicago Metropolitan Group Hospitals Chicago, Illinois Lois B. Travis, MD, ScD Lawrence H. Einhorn Professor of Cancer Research Indiana University Melvin and Bren Simon Cancer Center Indianapolis, Indiana Giorgio Trinchieri, MD Director Cancer and Inflammation Program Center for Cancer Research National Cancer Institute National Institutes of Health Bethesda, Maryland Catherine E. Ulbricht, PharmD, MBA, CPPS Director of Clinical and Academic Programs Department of Quality and Safety Brigham and Women’s Hospital Senior Attending Clinical Pharmacist

Department of Pharmacy Massachusetts General Hospital Boston, Massachusetts Brian R. Untch, MD, FACS Assistant Attending Gastric and Mixed Tumor Service Head and Neck Service Memorial Sloan Kettering Cancer Center New York, New York Robert G. Uzzo, MD, FACS Willing “Wing” Pepper Chair in Cancer Research Professor and Chairman, Department of Surgery Adjunct Professor of Bioengineering Temple University College of Engineering Fox Chase Cancer Center Temple University School of Medicine Philadelphia, Pennsylvania Michael A. Vogelbaum, MD, PhD Professor of Neurosurgery The Robert W. and Kathryn B. Lamborn Chair for Neuro-Oncology Associate Director, Rose Ella Burkhardt Brain Tumor and Neuro-Oncology Center Cleveland Clinic Cleveland, Ohio Christine M. Walko, PharmD, BCOP, FCCP Personalized Medicine Specialist Chair, Clinical Genomic Action Committee Moffitt Cancer Center Tampa, Florida Saiama N. Waqar, MBBS, MSCI Assistant Professor of Medicine Washington University School of Medicine St. Louis, Missouri Edus H. Warren, MD, PhD Program Head, Global Oncology Member, Vaccine and Infectious Disease Division Member, Clinical Research Division Fred Hutchinson Cancer Research Center Seattle, Washington Graham W. Warren, MD, PhD Professor and Vice Chairman for Research Department of Radiation Oncology Department of Cell and Molecular Pharmacology Medical University of South Carolina Charleston, South Carolina Jeffrey Weber, MD, PhD Deputy Director and Head Experimental Therapeutics Laura and Isaac Perlmutter Cancer Center Professor of Medicine

NYU School of Medicine New York, New York Robert A. Weinberg, PhD Whitehead Institute Cambridge, Massachusetts Louis M. Weiner, MD Director, Georgetown Lombardi Comprehensive Cancer Center and MedStar Georgetown Cancer Institute Chair, Department of Oncology Francis L. and Charlotte G. Gragnani Chair and Professor Georgetown University School of Medicine Washington, District of Columbia Batsheva Werman, MD Senior Physician Department of Medical Oncology Shaare Zedek Medical Center Jerusalem, Israel Jeremy Whelan, MD, FRCP, MBBS Professor of Cancer Medicine Consultant Medical Oncologist The London Sarcoma Service University College Hospital London, United Kingdom William G. Wierda, MD, PhD Professor of Medicine Department of Leukemia The University of Texas MD Anderson Cancer Center Houston, Texas Christopher G. Willett, MD Professor and Chair Department of Radiation Oncology Duke University Durham, North Carolina Walter C. Willett, MD, DrPH Professor of Epidemiology and Nutrition Department of Nutrition Harvard T. H. Chan School of Public Health Boston, Massachusetts Lynn D. Wilson, MD, MPH Professor Executive Vice Chairman Director of Clinical Affairs Department of Therapeutic Radiology Yale School of Medicine New Haven, Connecticut Jordan M. Winter, MD Associate Professor

Department of Surgery University Hospital Cleveland Medical Center Case Western Reserve University School of Medicine Cleveland, Ohio Yochai Wolf, PhD Postdoctoral Fellow Department of Molecular Cell Biology The Weizmann Institute of Science Rehovot, Israel M. Abraham Wu, MD Assistant Attending Department of Radiation Oncology Memorial Sloan Kettering Cancer Center New York, New York Joachim Yahalom, MD Member and Professor Memorial Sloan Kettering Cancer Center New York, New York James C. Yao, MD Professor and Chair Department of Gastrointestinal Medical Oncology The University of Texas MD Anderson Cancer Center Houston, Texas Sarah Yentz, MD Assistant Professor Division of Hematology and Oncology Department of Internal Medicine University of Michigan School of Medicine Ann Arbor, Michigan Charles J. Yeo, PhD Professor Thomas Jefferson University Philadelphia, Pennsylvania John Yonge, MD New York University Department of Cardiothoracic Surgery New York, New York Anas Younes, MD Lymphoma Service Memorial Sloan Kettering Cancer Center New York, New York Mark W. Youngblood, BS Department of Neurological Surgery Yale School of Medicine New Haven, Connecticut Herbert Yu, MD, PhD Professor

Director of Cancer Epidemiology Program University of Hawaii Cancer Center Honolulu, Hawaii Martha A. Zeiger, MD, FACS S. Hurt Watts Professor and Chair Department of Surgery University of Virginia School of Medicine Charlottesville, Virginia Michael J. Zelefsky, MD Professor of Radiation Oncology Chief, Brachytherapy Service Memorial Sloan Kettering Cancer Center New York, New York Eric S. Zhou, PhD Instructor Department of Pediatrics Harvard Medical School Boston, Massachusetts Weiping Zou, MD, PhD Charles B. de Nancrede Professor Professor of Surgery, Pathology, Immunology, and Biology University of Michigan School of Medicine Ann Arbor, Michigan Kenneth Zuckerman, MD Emeritus Member, Moffitt Cancer Center Retired Professor of Oncologic Sciences and Internal Medicine University of South Florida Tampa, Florida

PREFACE Cancer: Principles & Practice of Oncology is back again in its 11th edition 36 years after the publication of the first edition in 1982, or a new edition about every 3.5 years. It remains the most popular cancer text in the world and the only cancer text that is both online and continuously updated online. Each new edition provides the opportunity for the editors to mix and match chapter authors to adjust the content of the text to changing times. Indeed, we change about a third of the authors with every edition, and we are grateful to the many physicians and scientists who have contributed and made the book what it is today. The rate of change of scientific discovery continues to be breathtaking and matched by the impressive reduction of time between discovery and application, although clinical trials remain the rate-limiting step in getting discoveries to the bedside. The online updates prepared by experts selected by the editors and imbedded in the text in each chapter will continue to keep each edition fresh. Since the 10th edition, the field of immunotherapy has literally exploded, and there is hardly a tumor type that is not amenable to some type of manipulation of the immune system. These changes are reflected in the new edition, not only in the disease-related chapters but also in new chapters summarizing the scientific basis of the new immunotherapies and the many new immunotherapy agents available and in development. Integrating all the new approaches to the management of cancer is the challenge of the future. Textbooks remain unique in that unlike scientific papers, they present each new advance in the context of what has come before; they remain the ideal way for physicians to refresh their knowledge of the field and laboratory scientists to put their discoveries in proper perspective. PPO, as it is commonly known, was unique in the field when it was first published in 1982, and, with the changes in format, authors, content, and presentation, it remains a unique resource for all providers in cancer medicine. Vincent T. DeVita Jr., MD Theodore S. Lawrence, MD, PhD Steven A. Rosenberg, MD, PhD

ACKNOWLEDGMENT To Mary Kay, Wendy, and Alice

CONTENTS Contributing Authors ■ Preface ■ Acknowledgment

PA R T I

Molecular Biology of Cancer 1. The Cancer Genome Yardena Samuels, Alberto Bardelli, Yochai Wolf, and Carlos López-Otin Introduction Cancer Genes and Their Mutations Identification of Cancer Genes Somatic Alteration Classes Detected by Cancer Genome Analysis Pathway-Oriented Models of Cancer Genome Analysis Networks of Cancer Genome Projects The Genomic Landscape of Cancers Integrative Analysis of Cancer Genomics Immunogenomics The Cancer Genome and the New Taxonomy of Tumors Cancer Genomics and Drug Resistance Perspectives of Cancer Genome Analysis Acknowledgments 2. Molecular Methods in Cancer Larissa V. Furtado, Jay L. Hess, and Bryan L. Betz Applications of Molecular Diagnostics in Oncology The Clinical Molecular Diagnostics Laboratory: Rules and Regulations Specimen Requirements for Molecular Diagnostics Molecular Diagnostics Testing Process Targeted Mutation Analysis Methods Whole-genome Analysis Methods Immunohistochemistry for Tumor Biomarkers Cell-Free DNA Technologies 3. Hallmarks of Cancer: An Organizing Principle for Cancer Medicine Douglas Hanahan and Robert A. Weinberg Introduction Hallmark Capabilities, in Essence Two Ubiquitous Characteristics Facilitate the Acquisition of Hallmark Capabilities The Constituent Cell Types of the Tumor Microenvironment Therapeutic Targeting of the Hallmarks of Cancer Conclusion and a Vision for the Future Acknowledgment 4. Microbiome and Cancer Giorgio Trinchieri

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Introduction Cancer as a Disease of the Metaorganism Bacteria as Cause of Cancer Bacteria as Cancer Drugs Microbiota and Drug Metabolism Microbiota and Chemotherapy Microbiota and Immunotherapy Looking Forward 5. Cancer Susceptibility Syndromes Alice Hawley Berger and Pier Paolo Pandolfi Introduction Principles of Cancer Susceptibility Genetic Testing Cancer Susceptibility Syndromes Principles of Cancer Chemoprevention Emerging Knowledge and New Lessons Conclusion

PA R T I I

Etiology and Epidemiology of Cancer SECTION 1. ETIOLOGY OF CANCER 6. Tobacco Richard J. O’Connor Introduction Epidemiology of Tobacco and Cancer Carcinogens in Tobacco Products and Processes of Cancer Development Conclusion 7. Oncogenic Viruses Christopher B. Buck, Lee Ratner, and Giovanna Tosato Principles of Tumor Virology Papillomaviruses Polyomaviruses Epstein-Barr Virus Kaposi Sarcoma Herpesvirus Animal and Human Retroviruses Hepatitis Viruses Conclusion 8. Inflammation Michael D. Green and Weiping Zou Introduction Tumor-Intrinsic Inflammation Tumor-Extrinsic Inflammation Inflammatory Cell Subsets in the Cancer Microenvironment Inflammatory Molecular Mediators in Cancer Cellular Mechanisms of Inflammation in Cancer Molecular Mechanisms of Inflammation in Cancer Inflammation as a Therapeutic Target

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9. Chemical Factors Amanda K. Ashley and Christopher J. Kemp Introduction Initial Identification and Characterization of Carcinogens Determining Carcinogenicity Characteristics of Chemical Carcinogens Outlook 10. Physical Factors Mats Ljungman Introduction Ionizing Radiation Ultraviolet Light Radiofrequency and Microwave Radiation Electromagnetic Fields Asbestos Nanoparticles 11. Dietary Factors Karin B. Michels and Walter C. Willett Introduction Methodologic Challenges The Role of Individual Food and Nutrients in Cancer Etiology Other Foods and Nutrients Dietary Patterns Diet during Early Phases of Life Diet after a Diagnosis of Cancer The Microbiome Summary Limitations Future Directions Recommendations 12. Obesity and Physical Activity Justin C. Brown, Jeffrey A. Meyerhardt, and Jennifer A. Ligibel Introduction Obesity Obesity and Cancer Risk Obesity and Cancer Outcomes Obesity and Cancer Treatment–Related Complications Interventions Physical Activity Physical Activity and Cancer Risk Physical Activity and Cancer Outcomes Sedentary Behavior Interventions Mechanistic Data Weight and Physical Activity Guidelines American Society of Clinical Oncology Obesity Initiative Conclusion SECTION 2. EPIDEMIOLOGY OF CANCER 13. Epidemiologic Methods Xiaomei Ma and Herbert Yu

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Introduction Analytical Studies Interpretation of Epidemiologic Findings Cancer Outcomes Research Molecular Epidemiology 14. Global Cancer Incidence and Mortality Ahmedin Jemal, Lindsey A. Torre, and Michael J. Thun Introduction Geographic and Temporal Variations in Risk Data Sources Measures of Burden Measures of Risk Demographic Factors that Affect Risk Temporal Trends Incidence and Mortality Patterns for Common Cancers Issues in Interpreting Temporal Trends Conclusion

PA R T I I I

Cancer Therapeutics 15. Precision Medicine in Oncology James H. Doroshow Introduction Approach to Precision Medicine in Oncology Preclinical Models to Inform Precision Oncology Role of Molecular Pharmacodynamics and Diagnostics in Precision Oncology Precision Oncology Clinical Trials and Trial Designs Imaging and Precision Oncology Precision Prevention Future Prospects 16. Essentials of Radiation Therapy Meredith A. Morgan, Randall K. Ten Haken, and Theodore S. Lawrence Introduction Biologic Aspects of Radiation Oncology Factors that Affect Radiation Response Drugs that Affect Radiation Sensitivity Radiation Physics Treatment Planning Other Treatment Modalities Clinical Applications of Radiation Therapy Treatment Intent Fractionation Adverse Effects Principles of Combining Anticancer Agents with Radiation Therapy 17. Cancer Immunotherapy Jeffrey Weber and Iulia Giuroiu Introduction Interferon-α

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Interleukin-2 Talimogene Laherparepvec Granulocyte Macrophage Colony-stimulating Factor Tumor-Infiltrating Lymphocytes Checkpoint Inhibitors—Cytotoxic T-Lymphocyte Antigen 4 and Programmed Cell Death Protein 1 Cytotoxic T-Lymphocyte Antigen 4 Blockade Programmed Cell Death Protein 1 and Programmed Cell Death Protein Ligand 1 Blockade Vaccines Conclusion 18. Pharmacokinetics and Pharmacodynamics of Anticancer Drugs Alex Sparreboom and Sharyn D. Baker Introduction Pharmacokinetic Concepts Pharmacodynamic Concepts Variability in Pharmacokinetics/ Pharmacodynamics Dose Adaptation Using Pharmacokinetic/Pharmacodynamic Principles 19. Pharmacogenomics Christine M. Walko and Howard L. McLeod Introduction Pharmacogenomics of Tumor Response Pathway-Directed Anticancer Therapy Genetic-Guided Therapy: Practical Issues in Somatic Analysis Pharmacogenomics of Chemotherapy Drug Toxicity Conclusions and Future Directions 20. Alkylating Agents Kenneth D. Tew Historical Perspectives Chemistry Classification Clinical Pharmacokinetics/Pharmacodynamics Therapeutic Uses Toxicities Complications with High-Dose Alkylating Agent Therapy Alkylating Agent–Steroid Conjugates Drug Resistance and Modulation Future Perspectives 21. Platinum Analogs Kim A. Reiss, A. Hilary Calvert, and Peter J. O’Dwyer Introduction History Platinum Chemistry Platinum Complexes after Cisplatin Mechanism of Action Cellular Responses to Platinum-Induced DNA Damage Mechanisms of Resistance Clinical Pharmacology 22. Antimetabolites James J. Lee and Edward Chu Antifolates 5-Fluoropyrimidines

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Capecitabine Trifluridine/Tipiracil Cytarabine Gemcitabine 6-Thiopurines Fludarabine Cladribine Clofarabine 23. Topoisomerase-Interacting Agents Anish Thomas, Khanh Do, Shivaani Kummar, James H. Doroshow, and Yves Pommier Biochemical and Biologic Functions of Topoisomerases Topoisomerase Inhibitors as Interfacial Poisons Topoisomerase I Inhibitors: Camptothecins and Beyond Topoisomerase II Inhibitors: Intercalators and Nonintercalators Future Directions 24. Antimicrotubule Agents Christopher J. Hoimes Microtubules Taxanes Vinca Alkaloids Microtubule Antagonists Mitotic Motor Protein Inhibitors Mechanisms of Resistance to Microtubule Inhibitors Summary 25. Kinase Inhibitors as Anticancer Drugs Gopa Iyer, Debyani Chakravarty, and David B. Solit Introduction Validating Mutated Kinases as Cancer Drug Targets—the Development of Imatinib for Patients with Chronic Myelogenous Leukemia and Gastrointestinal Stromal Tumors The Development of HER2-Targeted Therapies in Breast and Other Cancers The Development of EGFR Tyrosine Kinase Inhibitors in Lung Cancer Identifying Therapeutic Targets in EGFR Wildtype Lung Cancers RAF and MEK Inhibitors for BRAF-Mutant Tumors PI3 Kinase Pathway Inhibitors One Target or Several: Multitargeted Kinase Inhibitor Therapy in Renal Cell Carcinoma and Medullary Thyroid Cancer CDK4/6 Inhibitors Bruton Tyrosine Kinase Inhibitors A Potential Pan Cancer Drug Target—TRK Inhibitors Future Directions 26. Histone Deacetylase Inhibitors and Demethylating Agents Stephen B. Baylin Introduction Epigenetic Abnormalities and Gene Expression Changes in Cancer Histone Deacetylase Inhibitors Epigenetic Therapy for Hematologic Malignancies New Approaches to Epigenetic Therapy 27. Proteasome Inhibitors Ajay K. Nooka, Vikas A. Gupta, Christopher J. Kirk, and Lawrence H. Boise Biochemistry of the Ubiquitin-Proteasome Pathway

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Proteasome Inhibitors Proteasome Inhibitors in Cancer 28. Poly(ADP-Ribose) Polymerase Inhibitors for Tumors with Defects in DNA Repair Alan Ashworth Introduction Cellular DNA Repair Pathways BRCA1 and BRCA2 Mutations and DNA Repair The Development of PARP Inhibitors PARP-1 Inhibition as a Synthetic Lethal Therapeutic Strategy for the Treatment of BRCA-Deficient Cancers Initial Clinical Results Testing Synthetic Lethality of PARP Inhibitors and BRCA Mutation PARP Inhibitors Approved for Clinical Use The Use of PARP Inhibitors in Non-BRCA Germline Mutant Cancers Mechanisms of Resistance to PARP Inhibitors Future Prospects 29. Miscellaneous Chemotherapeutic Agents M. Sitki Copur, Ryan Ramaekers, David Crockett, and Dron Gauchan Homoharringtonine and Omacetaxine L-Asparaginase Bleomycin Procarbazine Dactinomycin Vismodegib Ado-Trastuzumab Emtansine Sirolimus and Temsirolimus Everolimus Thalidomide, Lenalidomide, and Pomalidomide Miscellaneous Agents with Potential for Repurposable Chemotherapeutic Use 30. Hormonal Agents Karthik V. Giridhar, Manish Kohli, and Matthew P. Goetz Introduction Selective Estrogen Receptor Modulators Aromatase Inhibitors Resistance to Endocrine-Targeted Therapy in Breast Cancer Gonadotropin-Releasing Hormone Analogs Antiandrogens Resistance to Androgen Therapies in Prostate Cancer Other Sex Steroid Therapies Other Hormonal Therapies 31. Monoclonal Antibodies Hossein Borghaei, Matthew K. Robinson, Gregory P. Adams, and Louis M. Weiner Introduction Immunoglobulin Structure Modified Antibody-Based Molecules Factors Regulating Antibody-Based Tumor Targeting Unconjugated Antibodies Altering Signal Transduction Immunoconjugates Antibodies Approved for Use in Solid Tumors Antibodies Used in Hematologic Malignancies Conclusion

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32. Immunotherapy Agents Jeffrey A. Sosman and Douglas B. Johnson Introduction Human Tumor Antigens Tumor Vaccines Oncolytic Viruses Factors to Activate Immune Effector Cells Signaling Modulation Soluble Factors Adenosine A2α Receptor Axis Innate Immune Modulation Bifunctional Fusion Proteins

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Cancer Prevention and Screening 33. Tobacco Use and the Cancer Patient Graham W. Warren and Vani N. Simmons Introduction Tobacco Use Epidemiology, Addiction, and Tobacco Product Evolution Electronic Nicotine Delivery Systems, or Electronic Cigarettes Defining Tobacco Use by the Cancer Patient Tobacco Use and Cessation by the Cancer Patient Smoking Cessation in the Context of Lung Cancer Screening The Clinical Effects of Smoking on Cancer Patients Addressing Tobacco Use by the Cancer Patient Research Considerations and the Future of Addressing Tobacco Use by Cancer Patients 34. Role of Surgery in Cancer Prevention José G. Guillem, Andrew Berchuck, Jeffrey A. Norton, Preeti Subhedar, Kenneth P. Seastedt, and Brian R. Untch Introduction Risk-Reducing Surgery in Breast Cancer Hereditary Diffuse Gastric Cancer Surgical Prophylaxis of Hereditary Ovarian and Endometrial Cancer Multiple Endocrine Neoplasia Type 2 Hereditary Colorectal Cancer Syndromes: Familial Adenomatous Polyposis, MUTYH-Associated Polyposis, and Lynch Syndrome 35. Cancer Risk–Reducing Agents Dean E. Brenner and Scott M. Lippman Why Cancer Prevention as a Clinical Oncology Discipline Defining Cancer Risk–Reducing Agents (Chemoprevention) Identifying Potential Cancer Risk–Reducing Agents Preclinical Development of Cancer Risk–Reducing Agents Clinical Development of Cancer Risk–Reducing Agents Micronutrients Anti-Inflammatory Drugs Posttranslational Pathway Targets Diet-Derived Natural Products Anti-Infectives 36. Prophylactic Cancer Vaccines

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John T. Schiller and Olivera J. Finn Introduction Overview of Infectious Agents in Cancer Hepatitis B Vaccines Human Papillomavirus Vaccines Prospects for Prophylactic Vaccines against Other Oncogenic Microbes Vaccines for Cancers of Noninfectious Etiology: Tumor-Specific and Tumor-Associated Target Antigens Therapeutic Cancer Vaccines Have Set the Stage for Preventative Cancer Vaccines Prophylactic Vaccines for Cancers of Noninfectious Etiology 37. Cancer Screening Otis W. Brawley and Howard L. Parnes Introduction Performance Characteristics of a Screening Test Assessing a Screening Test Screening Guidelines and Recommendations Breast Cancer Screening Gastrointestinal Tract Cancers 460 Gynecologic Cancer Lung Cancer Screening Prostate Cancer Screening Skin Cancer Screening 38. Genetic Counseling Danielle C. Bonadies, Meagan B. Farmer, and Ellen T. Matloff Introduction Who Is a Candidate for Cancer Genetic Counseling? Components of the Cancer Genetic Counseling Session Issues in Cancer Genetic Counseling Future Directions Conclusion

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Practice of Oncology 39. Design and Analysis of Clinical Trials Richard M. Simon Introduction Phase I Clinical Trials Phase II Clinical Trials Design of Phase III Clinical Trials Factorial Designs Analysis of Phase III Clinical Trials Reporting Results of Clinical Trials False-positive Reports in the Literature Meta-analysis 40. Assessment of Clinical Response Susan Bates and Tito Fojo Introduction Assessing Response

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Determining Outcome 41. Vascular Access Mohammad S. Jafferji and Stephanie L. Goff Introduction Catheter Types External Catheters Implantable Devices Catheter Selection Pediatric Patients Insertion Techniques Catheter-Related Complications 42. Endoscopic and Robotic Surgery Jeremy L. Davis, R. Taylor Ripley, and Jonathan M. Hernandez Introduction Physiologic Effects of Endoscopic Surgery Applications of Endoscopic and Robotic Surgery Special Topics Gastrointestinal and Hepatopancreatobiliary Cancers Genitourinary and Gynecologic Oncology Emerging Techniques Conclusion 43. Tumor Biomarkers Corey W. Speers and Daniel F. Hayes Introduction Uses for Tumor Biomarker Tests What Are the Criteria to Incorporate a Tumor Biomarker Test into Clinical Practice? Tumor Biomarker Tests that Are Accepted for Routine Clinical Utility Special Circumstances Tumor Biomarker Tests of Radiation Response Conclusion SECTION 1. CANCER OF THE HEAD AND NECK 44. The Molecular Biology of Head and Neck Cancers Thomas E. Carey, Mark E. Prince, and J. Chad Brenner Incidence, Risk Factors, and Etiology Oral Tongue Cancer in Young Patients High-Risk HPV in Oropharyngeal Cancer Molecular Mechanisms in HNSCC The Cancer Genome Atlas Project Inhibition of HNSCC Immune Escape Cancer Stem Cells 45. Cancer of the Head and Neck William M. Mendenhall, Peter T. Dziegielewski, and David G. Pfister Incidence and Etiology Anatomy and Pathology Natural History Diagnosis Staging Principles of Treatment for Squamous Cell Carcinoma Management

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NECK Clinically Negative Neck Clinically Positive Neck Lymph Nodes Chemotherapy General Principles of Combining Modalities Chemotherapy as Part of Curative Treatment Follow-up ORAL CAVITY Lip Floor of the Mouth Oral Tongue Buccal Mucosa Gingiva and Hard Palate (Including Retromolar Trigone) OROPHARYNX Anatomy Pathology Patterns of Spread Clinical Picture Staging Treatment: Tonsillar Fossa Results of Treatment: Tonsillar Area Complications of Treatment: Tonsillar Area Treatment: Base of Tongue Results of Treatment: Base of Tongue Follow-up: Base of Tongue Complications of Treatment: Base of Tongue Treatment: Soft Palate Results of Treatment: Soft Palate Complications of Treatment: Soft Palate LARYNX Anatomy Pathology Patterns of Spread Clinical Picture Differential Diagnosis and Staging Treatment: Vocal Cord Carcinoma Treatment: Supraglottic Larynx Carcinoma Treatment: Subglottic Larynx Carcinoma Treatment: Supraglottic Larynx Cancer HYPOPHARYNX: PHARYNGEAL WALLS, PYRIFORM SINUS, AND POSTCRICOID PHARYNX Anatomy Pathology Patterns of Spread Clinical Picture Staging Treatment Results of Treatment Complications of Treatment NASOPHARYNX Anatomy Pathology Patterns of Spread Clinical Picture Staging Treatment

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Results of Treatment Follow-up Complications of Treatment NASAL VESTIBULE, NASAL CAVITY, AND PARANASAL SINUSES Anatomy Pathology Patterns of Spread Clinical Picture Staging Treatment Results of Treatment Complications of Treatment PARAGANGLIOMAS Anatomy Pathology Patterns of Spread Staging Treatment Results of Treatment Complications of Treatment MAJOR SALIVARY GLANDS Anatomy Pathology Patterns of Spread Clinical Picture Differential Diagnosis Staging Treatment Results of Treatment Complications of Treatment MINOR SALIVARY GLANDS Anatomy Pathology Patterns of Spread Clinical Picture Treatment Results of Treatment 46. Rehabilitation after Treatment of Head and Neck Cancer Douglas B. Chepeha and Teresa H. Lyden Introduction Pretreatment Counseling Support during Treatment and Rehabilitation of the Chemoradiation Patient Resources for Rehabilitation of Head and Neck Cancer Patients SECTION 2. CANCER OF THE THORACIC CAVITY 47. The Molecular Biology of Lung Cancer Jill E. Larsen and John D. Minna Introduction Genomics: Tools for Identification, Prediction, and Prognosis Functional Genomics in Lung Cancer Genetic and Epigenetic Alterations in Lung Cancer Metastasis and the Tumor Microenvironment Lung Cancers Stem Cells Telomerase-Mediated Cellular Immortality in Lung Cancer

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Clinical Translation of Molecular Data 48. Non–small-cell Lung Cancer Anne Chiang, Frank C. Detterbeck, Tyler Stewart, Roy H. Decker, and Lynn Tanoue Introduction Incidence and Etiology Anatomy and Pathology Screening and Prevention Diagnosis Stage Evaluation Management by Stage Special Clinical Situations Palliative Care Conclusion 49. Small Cell and Neuroendocrine Tumors of the Lung Christine L. Hann, M. Abraham Wu, Natasha Rekhtman, and Charles M. Rudin Introduction Small Cell Lung Cancer Typical Carcinoid and Atypical Carcinoid Tumors Large Cell Neuroendocrine Carcinoma 50. Neoplasms of the Mediastinum Robert B. Cameron, Patrick J. Loehrer Sr., Alexander Marx, and Percy P. Lee Thymic Neoplasms Thymoma Thymic Carcinoma Germ Cell Tumors SECTION 3. CANCERS OF THE GASTROINTESTINAL TRACT 51. Molecular Biology of the Esophagus and Stomach Anil K. Rustgi Introduction Molecular Biology of Esophageal Cancer Molecular Biology of Gastric Cancer 52. Cancer of the Esophagus Mitchell C. Posner, Karyn A. Goodman, and David H. Ilson Introduction Epidemiology Etiologic Factors and Predisposing Conditions Applied Anatomy and Histology Natural History and Patterns of Failure Clinical Presentation Diagnostic Studies and Pretreatment Staging Tools Staging Guidelines Treatment Predictors of Treatment Response Palliation of Esophageal Cancer with Radiation Therapy Radiotherapy Techniques Treatment of Metastatic Disease Stage-Directed Treatment Recommendations 53. Cancer of the Stomach Itzhak Avital, Aviram Nissan, Talia Golan, Yaacov Richard Lawrence, and Alexander Stojadinovic

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Introduction Anatomic Considerations Pathology and Tumor Biology Histopathology Molecular Classification of Gastric Cancer Patterns of Spread Clinical Presentation and Pretreatment Evaluation Pretreatment Staging Staging, Classification, and Prognosis Gastric Cancer Nomograms: Predicting Individual Patient Prognosis after Potentially Curative Resection Treatment of Localized Disease Technical Treatment-Related Issues Treatment of Advanced Disease (Stage IV) Surgery in Treatment of Metastatic Gastric Cancer Gastric Cancer in the Elderly 54. The Molecular Biology of Pancreas Cancer Scott E. Kern and Ralph H. Hruban Introduction Common Genetic Changes in Pancreatic Ductal Adenocarcinoma Less-Prevalent Genetic Changes in Pancreatic Ductal Adenocarcinoma Other Neoplastic Lesions 55. Cancer of the Pancreas Jordan M. Winter, Jonathan R. Brody, Ross A. Abrams, James A. Posey, and Charles J. Yeo Incidence and Etiology Anatomy and Pathology Exocrine Pancreatic Cancers Endocrine Pancreatic Cancers Pancreatic Ductal Adenocarcinoma: Screening Pancreatic Ductal Adenocarcinoma: Diagnosis Pancreatic Ductal Adenocarcinoma: Staging Stages I and II: Localized Pancreatic Ductal Adenocarcinoma Stage III: Locally Advanced Disease Emerging Role of Stereotactic Body Radiotherapy Stage IV: Metastatic Disease Future Directions and Challenges Conclusion 56. Molecular Biology of Liver Cancer Jens U. Marquardt and Snorri S. Thorgeirsson Introduction Genetic Alterations in Liver Cancer Epigenetic Alterations in Liver Cancer Mutational Landscape of Genetic Alterations—the Next Generation The Microenvironment of Liver Cancer Classification and Prognostic Prediction of Hepatocellular Carcinoma Molecular Basis of Cholangiocarcinoma Conclusion and Perspective 57. Cancer of the Liver Yuman Fong, Damian E. Dupuy, Mary Feng, and Ghassan Abou-Alfa Introduction Epidemiology Etiologic Factors

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Diagnosis Staging Treatment of Hepatocellular Carcinoma Adjuvant and Neoadjuvant Therapy Treatment of Other Primary Liver Tumors 58. Cancer of the Biliary Tree Tushar Patel and Kabir Mody Introduction Anatomy of the Biliary Tract Cholangiocarcinoma Gallbladder Cancer Acknowledgments 59. Small Bowel Cancer Ronald Chamberlain, Nasrin Ghalyaie, and Sachin Patil Introduction Small Bowel Adenocarcinoma Carcinoid Tumors Small Bowel Lymphoma Gastrointestinal Stromal Tumor Metastatic Cancer to the Small Bowel 60. Gastrointestinal Stromal Tumor Paolo G. Casali, Angelo Paolo Dei Tos, and Alessandro Gronchi Introduction Incidence and Etiology Anatomy and Pathology Screening Diagnosis Staging Management by Stage Palliative Care 61. Molecular Biology of Colorectal Cancer Ramesh A. Shivdasani Introduction Multistep Models of Colorectal Cancer and Genetic Instability Mutational and Epigenetic Landscapes in Colorectal Cancer Insights from Mouse Intestinal Crypts and Human Colorectal Cancers Lead to a Coherent Model for Colorectal Cancer Initiation and Progression Inherited Syndromes of Increased Cancer Risk Highlight Early Events and Critical Pathways in Colorectal Tumorigenesis Oncogene and Tumor Suppressor Gene Mutations in Colorectal Cancer Progression 62. Cancer of the Colon Steven K. Libutti, Leonard B. Saltz, Christopher G. Willett, and Rebecca A. Levine Introduction Epidemiology Etiology: Genetic, Environmental, and Other Risk Factors Familial Colorectal Cancer Anatomy of the Colon Diagnosis of Colorectal Cancer Screening for Colorectal Cancer Staging and Prognosis of Colorectal Cancer

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Approaches to Surgical Resection of Colon Cancer Surgical Management of Complications from Primary Colon Cancer Laparoscopic Colon Resection Polyps and Stage I Colon Cancer Stage II and Stage III Colon Cancer Treatment of Stage II Patients Treatment Options for Stage III Patients Investigational Adjuvant Approaches Follow-up after Management of Colon Cancer with Curative Intent Surgical Management of Stage IV Disease Management of Unresectable Metastatic Disease Molecular Predictive Markers 63. Cancer of the Rectum Steven K. Libutti, Christopher G. Willett, Leonard B. Saltz, and Rebecca A. Levine Introduction Anatomy Staging Surgery Does Adjuvant Radiation Therapy Impact Survival? Preoperative Radiation Therapy Which Patients Should Receive Adjuvant Therapy? Support of Nonoperative Management Total Neoadjuvant Therapy Concurrent Chemotherapy Synchronous Rectal Primary and Metastases Management of Unresectable Primary and Locally Advanced Disease (T4) Management of Locally Recurrent Disease Reirradiation in Recurrent Disease Radiation Therapy Technique Radiation Fields 64. Cancer of the Anal Region Brian G. Czito, Shahab Ahmed, Matthew F. Kalady, and Cathy Eng Introduction Epidemiology and Etiology Screening and Prevention Pathology Clinical Presentation and Staging Prognostic Factors Treatment of Localized Squamous Cell Carcinoma Treatment of Other Sites and Pathologies SECTION 4. CANCERS OF THE GENITOURINARY SYSTEM 65. Molecular Biology of Kidney Cancer W. Marston Linehan and Laura S. Schmidt Introduction Clear Cell Renal Cell Carcinoma Papillary Renal Cell Carcinoma Chromophobe Renal Cell Carcinoma Additional Types of Renal Cell Carcinoma Conclusion 66. Cancer of the Kidney Andres F. Correa, Brian R. Lane, Brian I. Rini, and Robert G. Uzzo

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Introduction Epidemiology, Demographics, and Risk Factors Pathology of Renal Cell Carcinoma Differential Diagnosis and Staging Hereditary Kidney Cancer Syndromes, Genetics, and Molecular Biology Treatment of Localized Renal Cell Carcinoma Treatment of Locally Advanced Renal Cell Carcinoma Surgical Management of Advanced Renal Cell Carcinoma Systemic Therapy for Advanced Renal Cell Carcinoma Conclusion and Future Directions Acknowledgments 67. Molecular Biology of Bladder Cancer Carolyn D. Hurst and Margaret A. Knowles Introduction Mutational Landscape Heterogeneity and Clonal Evolution Molecular Subtypes Therapeutic Opportunities and Future Outlook 68. Cancer of the Bladder, Ureter, and Renal Pelvis Adam S. Feldman, Richard J. Lee, David T. Miyamoto, Douglas M. Dahl, and Jason A. Efstathiou Introduction Cancer of the Bladder Cancers of the Renal Pelvis and Ureter 69. The Molecular Biology of Prostate Cancer Charles Dai and Nima Sharifi Introduction The Genomic Landscape of Prostate Cancer The Molecular Subtypes of Primary Prostate Cancer The Clonal Evolution of Lethal Metastatic Prostate Cancer Genetic Basis of Prostate Cancer Heritability Androgen Signaling in Prostate Cancer Other Signaling Pathways in Prostate Cancer Areas of Ongoing Research and Emerging Therapeutic Approaches Conclusion 70. Cancer of the Prostate Michael J. Zelefsky, Michael J. Morris, and James A. Eastham Introduction Incidence and Etiology Anatomy and Pathology Diagnosis, Risk Assessment, and State Assignment Management by Clinical States Palliation Future Directions 71. Cancer of the Urethra and Penis J. Ryan Mark, Mark Hurwitz, and Leonard G. Gomella Introduction Urethral Cancer in the Male Urethral Cancer in the Female Penile Cancer

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72. Cancer of the Testis Matthew T. Campbell, Jose A. Karam, and Christopher J. Logothetis Introduction Incidence and Epidemiology Initial Presentation and Management Histology Biology Immunohistochemical Markers Staging Management of Clinical Stage I Disease Management of Clinical Stage II Disease (Low Tumor Burden) Management of Stage II Disease with High Tumor Burden and Stage III Disease Management of Recurrent Disease Treatment Sequelae Long-term Follow-up Midline Tumors of Uncertain Histogenesis Other Testicular Tumors SECTION 5. GYNECOLOGIC CANCERS 73. Molecular Biology of Gynecologic Cancers Tanja Pejovic, Adam J. Krieg, and Kunle Odunsi Introduction Ovarian Cancer Endometrial Cancer Cervix, Vaginal, and Vulvar Cancers 74. Cancer of the Cervix, Vagina, and Vulva Patricia J. Eifel, Ann H. Klopp, Jonathan S. Berek, and Panagiotis A. Konstantinopoulos Carcinoma of the Cervix Carcinoma of the Vagina Carcinoma of the Vulva 75. Cancer of the Uterine Body Kaled M. Alektiar, Nadeem R. Abu-Rustum, and Gini F. Fleming Endometrial Carcinoma Uterine Sarcomas 76. Gestational Trophoblastic Neoplasia Donald P. Goldstein, Ross S. Berkowitz, and Neil S. Horowitz Introduction Incidence Pathology and Natural History Indications for Treatment Measurement of Human Chorionic Gonadotropin Pretreatment Evaluation Staging and Prognostic Score Treatment Placental Site or Epithelioid Trophoblastic Tumors Subsequent Pregnancy after Treatment for Gestational Trophoblastic Neoplasia 77. Ovarian Cancer Krishnansu S. Tewari, Richard T. Penson, and Bradley J. Monk Incidence and Etiology Anatomy and Pathology

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Screening and Prevention Diagnosis Presentation and Evaluation of Advanced Disease International Federation of Gynecology and Obstetrics Staging Management by Stage Management of Newly Diagnosed Advanced-Stage Disease Management of Recurrent Disease Antiangiogenesis Therapy PARP Inhibitors Clinical Implications of BRCA1/2 Mutation Status Olaparib Rucaparib Niraparib Veliparib Talazoparib BRCA1/2 Reversion Mutations Tolerability of PARP Inhibitors Immunotherapy Therapeutic Vaccines Toll-Like Receptors Oncolytic Viruses Chimeric Antigen Receptors Bispecific T-Cell Engagers Immune-Mediated Toxicity Immune-Related Response Criteria SECTION 6. CANCER OF THE BREAST 78. Molecular Biology of Breast Cancer Ana T. Nunes, Tara Berman, and Lyndsay Harris Introduction Genetics of Breast Cancer Somatic Alterations in Breast Cancer Protein/Pathway Alterations 79. Malignant Tumors of the Breast Reshma Jagsi, Tari A. King, Constance Lehman, Monica Morrow, Jay R. Harris, and Harold J. Burstein Incidence and Etiology Management of the High-Risk Patient Anatomy and Pathology Diagnosis and Biopsy Staging Management by Stage: Ductal Carcinoma In Situ Management by Stage: Primary Operable Invasive Breast Cancer Management by Stage: Adjuvant Systemic Therapy Management by Stage: Special Considerations Management by Stage: Metastatic Disease SECTION 7. CANCER OF THE ENDOCRINE SYSTEM 80. Molecular Biology of Endocrine Tumors Zeyad T. Sahli, Brittany A. Avin, and Martha A. Zeiger Endocrine Syndromes Adrenal Gland Parathyroid Gland Pituitary Gland

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Thyroid Gland Acknowledgments 81. Thyroid Tumors Anupam Kotwal, Caroline J. Davidge-Pitts, and Geoffrey B. Thompson Anatomy and Physiology Thyroid Nodules Thyroid Tumor Classification and Staging Systems Differentiated Thyroid Cancer Treatment of Differentiated Thyroid Cancer Anaplastic Thyroid Carcinoma Medullary Thyroid Cancer Thyroid Lymphoma Children with Thyroid Carcinoma 82. Parathyroid Tumors Anupam Kotwal and Geoffrey B. Thompson Incidence and Etiology Anatomy and Pathology Clinical Manifestations and Screening Diagnosis Staging Management of Parathyroid Cancer Follow-up and Natural History Prognosis 83. Adrenal Tumors Antonio M. Lerario, Dipika R. Mohan, Roy Lirov, Tobias Else, and Gary D. Hammer Introduction Incidence and Etiology Anatomy and Pathology Screening Diagnosis Staging Management Palliative Care 84. Pancreatic Neuroendocrine Tumors James C. Yao, Callisia N. Clarke, and Douglas B. Evans Introduction Incidence and Etiology Classification, Histopathology, and Molecular Genetics Diagnosis and Management of Pancreatic Neuroendocrine Tumors Cytotoxic Chemotherapy Functional Tumors Additional Clinical Considerations Small, Nonfunctioning, Sporadic Pancreatic Neuroendocrine Tumors 85. Carcinoid Tumors and the Carcinoid Syndrome Jeffrey A. Norton Incidence and Etiology Anatomy and Pathology General Principles of Neuroendocrine Tumor Diagnosis, Staging, and Management Diagnosis, Staging, and Management by Primary Tumor Site Diagnosis and Management of Carcinoid Syndrome

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Antitumor Management Management of Liver Metastases Conclusions 86. Multiple Endocrine Neoplasia Jeffrey A. Norton Introduction Multiple Endocrine Neoplasia Type Multiple Endocrine Neoplasia Types 2 and 3 and Familial Medullary Thyroid Cancer Multiple Endocrine Neoplasia Type SECTION 8. SARCOMAS OF SOFT TISSUE AND BONE 87. Molecular Biology of Sarcomas Samuel Singer and Cristina R. Antonescu Introduction Soft Tissue Sarcomas Bone and Cartilaginous Tumors Future Directions: Next-Generation Sequencing and Functional Screens 88. Soft Tissue Sarcoma Samuel Singer, William D. Tap, David G. Kirsch, and Aimee M. Crago Introduction Incidence and Etiology Anatomic and Age Distribution and Pathology Clinical and Pathologic Features of Specific Soft Tissue Tumor Types Diagnosis and Staging Management by Presentation Status, Extent of Disease, and Anatomic Location Palliative Care Future Directions 89. Sarcomas of Bone Richard J. O’Donnell, Steven G. DuBois, and Daphne A. Haas-Kogan Introduction Incidence and Etiology Anatomy and Pathology Screening Diagnosis Staging Management by Diagnosis and Stage Continuing Care: Surveillance and Palliation SECTION 9. CANCERS OF THE SKIN 90. Cancer of the Skin Sean R. Christensen, Lynn D. Wilson, and David J. Leffell General Approach to Nonmelanoma Skin Cancer Basal Cell Carcinoma Squamous Cell Carcinoma and Actinic Keratosis Merkel Cell Carcinoma Dermatofibrosarcoma Protuberans Angiosarcoma Microcystic Adnexal Carcinoma Sebaceous Carcinoma Extramammary Paget Disease Atypical Fibroxanthoma

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91. Molecular Biology of Cutaneous Melanoma Michael A. Davies Introduction The Cancer Genome Atlas Effort in Cutaneous Melanoma The RAS-RAF-MAPK Pathway Additional Oncogenic Pathways Melanin Synthesis Pathway Summary and Future Directions 92. Cutaneous Melanoma Antoni Ribas, Paul Read, and Craig L. Slingluff Jr. Introduction Molecular Biology of Melanoma Epidemiology Changes in Incidence Sex and Age Distribution Melanoma in Children, Infants, and Neonates Anatomic Distribution Etiology and Risk Factors Prevention and Screening Diagnosis of Primary Melanoma General Considerations in Clinical Management of a Newly Diagnosed Cutaneous Melanoma (Stages I and II) Clinical Trials to Define Margins of Excision for Primary Cutaneous Melanomas Surgical Staging of Regional Nodes Selection of Patients for Sentinel Node Biopsy Management Thick Melanomas (T4A, T4B, >4 mm Thick) Special Considerations in Management of Primary Melanomas Primary Melanomas of the Fingers and Toes The Role of Radiation Therapy in the Management of Primary Melanoma Lesions Clinical Follow-up for Intermediate-Thickness and Thick Melanomas (Stage IB to IIC) Regionally Metastatic Melanoma (Stage III): Lymph Node Metastasis, Satellite Lesions, and In-Transit Metastases Management of Regional Metastases in Patients with Visceral or Other Distant Disease Adjuvant Systemic Therapy (Stages IIB, IIC, and III) Management of Distant Metastases of Melanoma (Stage IV) Radiation Therapy for Metastatic Melanoma (Stage IV) SECTION 10. NEOPLASMS OF THE CENTRAL NERVOUS SYSTEM 93. Molecular Biology of Central Nervous System Tumors Mark W. Youngblood, Jennifer Moliterno Günel, and Murat Günel Introduction Pediatric Brain Tumors Adult Brain Tumors Summary Acknowledgments 94. Neoplasms of the Central Nervous System Susan M. Chang, Minesh P. Mehta, Michael A. Vogelbaum, Michael D. Taylor, and Manmeet S. Ahluwalia Epidemiology of Brain Tumors Classification Anatomic Location and Clinical Considerations Neurodiagnostic Tests Surgery

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Radiation Therapy Chemotherapy and Targeted Agents Specific Central Nervous System Neoplasms Gliomatosis Cerebri Optic, Chiasmal, and Hypothalamic Gliomas Brain Stem Gliomas Cerebellar Astrocytomas Gangliogliomas Ependymoma Meningiomas Primitive Neuroectodermal or Embryonal Central Nervous System Neoplasms Pineal Region Tumors and Germ Cell Tumors Pituitary Adenomas Craniopharyngiomas Vestibular Schwannomas Glomus Jugulare Tumors Hemangioblastomas Chordomas and Chondrosarcomas Choroid Plexus Tumors Spinal Axis Tumors SECTION 11. CANCERS IN ADOLESCENTS AND YOUNG ADULTS 95. Adolescents and Young Adults with Cancer Archie Bleyer, Andrea Ferrari, Jeremy Whelan, and Ronald Barr Epidemiology Etiology and Biology Signs, Symptoms, and Delays in Diagnosis Prevention and Screening Diagnosis Management Progress Future Challenges SECTION 12. LYMPHOMAS IN ADULTS 96. Molecular Biology of Lymphoma Nicolò Compagno, Laura Pasqualucci, and Riccardo Dalla-Favera Introduction The Cell of Origin of Lymphoma General Mechanisms of Genetic Alterations in Lymphoma Molecular Pathogenesis of B-Cell Non-Hodgkin Lymphoma Molecular Pathogenesis of T-Cell Non-Hodgkin Lymphoma Molecular Pathogenesis of Hodgkin Lymphoma 97. Hodgkin Lymphoma Anas Younes, Ahmet Dogan, Peter Johnson, Joachim Yahalom, John Kuruvilla, and Stephen Ansell Introduction Pathology of Hodgkin Lymphoma Early-Stage Hodgkin Lymphoma Advanced-Stage Hodgkin Lymphoma Special Circumstances 98. Non-Hodgkin Lymphoma Arnold S. Freedman, Caron A. Jacobson, Andrea Ng, and Jon C. Aster Introduction

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Incidence and Etiology Biology and Pathology Lymphoma Classification: the Principles of the World Health Organization Classification of Lymphoid Neoplasms Diagnosis, Staging, and Management Specific Disease Entities Mature T-Cell and Natural Killer Cell Neoplasms 99. Cutaneous Lymphomas Francine M. Foss, Michael Girardi, and Lynn D. Wilson Introduction Mycosis Fungoides and the Sézary Syndrome Epidemiology and Etiology Pathobiology Diagnosis and Staging The Sézary Syndrome Staging and Prognosis of Mycosis Fungoides and the Sézary Syndrome Clinical Evaluation of Patients with Cutaneous Lymphoma Principles of Therapy of Mycosis Fungoides and the Sézary Syndrome Skin-Directed Therapy Systemic Therapy for Mycosis Fungoides and the Sézary Syndrome Other Cutaneous Lymphomas 100. Primary Central Nervous System Lymphoma Tracy T. Batchelor and Catherine H. Han Epidemiology Histopathology and Molecular Profile Diagnosis Prognostic Models Management of Newly Diagnosed Primary Central Nervous System Lymphoma Treatment in the Elderly Management of Refractory/Relapsed Primary Central Nervous System Lymphoma Monitoring and Follow-up Neurotoxicity SECTION 13. LEUKEMIAS AND PLASMA CELL TUMORS 101. Molecular Biology of Acute Leukemias Glen D. Raffel and Jan Cerny Introduction Leukemic Stem Cell Elucidation of Genetic Events in Acute Leukemia Mutations Affecting Transcription Factors Mutations of Epigenetic Modifiers Mutations Affecting Signaling Mutations in Tumor Suppressor Genes Activating Mutations of NOTCH Mutations Altering Localization of NPM1 Mutations in Cohesin Complex Genes Mutations in Splicing Machinery Mutational Complementation Groups in Acute Leukemias Conclusion 102. Management of Acute Leukemias Partow Kebriaei, Farhad Ravandi, Marcos de Lima, and Richard Champlin

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Introduction Acute Myeloid Leukemia Acute Lymphoblastic Leukemia 103. Molecular Biology of Chronic Leukemias Christopher A. Eide, James S. Blachly, and Anupriya Agarwal Introduction Chronic Myeloid Leukemia Chronic Lymphocytic Leukemia Acknowledgments 104. Chronic Myeloid Leukemia Carlo Gambacorti-Passerini and Philipp le Coutre Introduction Epidemiology and Pathogenesis Diagnosis Differential Diagnosis and Staging Prognostic Factors Therapy Assessment of Response to Tyrosine-Kinase Inhibitors Therapy of Chronic Phase Chronic Myeloid Leukemia Treatment of Advanced Disease Future Directions Acknowledgments 105. Chronic Lymphocytic Leukemias William G. Wierda and Susan M. O’Brien Introduction Immunophenotype Molecular Biology Immune Abnormalities Diagnosis Clinical Manifestations Laboratory Findings Autoimmune Complications Staging Indications for Treatment and Response Criteria Treatments for Chronic Lymphocytic Leukemia Management Recommendations Prolymphocytic Leukemia Large Granular Lymphocyte Leukemia Hairy Cell Leukemia 106. Myelodysplastic Syndromes Rami S. Komrokji, Eric Padron, and Alan F. List Introduction Historical Perspective Epidemiology Etiology Pathology Pathogenesis Clinical Presentation Risk Assessment and Prognosis Management of Myelodysplastic Syndromes

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107. Plasma Cell Neoplasms S. Vincent Rajkumar and Shaji Kumar Introduction Multiple Myeloma Pathogenesis Cytogenetic Classification Clinical Features Diagnostic Tests Differential Diagnosis Staging and Risk Stratification Prognosis Treatment Supportive Care MONOCLONAL GAMMOPATHY OF UNDETERMINED SIGNIFICANCE Introduction Incidence and Prevalence Clinical Features Differential Diagnosis Prognosis Risk Stratification Management SMOLDERING MULTIPLE MYELOMA Introduction Prevalence Clinical Features Differential Diagnosis Prognosis Risk Stratification Management Waldenström Macroglobulinemia Diagnosis Prognosis Treatment Systemic AL (Immunoglobulin Light Chain) Amyloidosis Diagnosis Prognosis Treatment Solitary Plasmacytoma Diagnosis and Prognosis Treatment POEMS Syndrome SECTION 14. OTHER CANCERS 108. Cancer of Unknown Primary Sarah Yentz, Manali Bhave, Erin Cobain, and Laurence Baker Introduction Pathology Evaluation Additional Pathologic Diagnostic Tests in Cancers of Unknown Primary Use of Next-Generation Sequencing Clinical Features and Evaluation Prognostic Factors 109. Benign and Malignant Mesothelioma Harvey I. Pass, Michele Carbone, Lee M. Krug, and Kenneth E. Rosenzweig

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Introduction Epidemiology Mechanism of Asbestos Carcinogenesis Mechanism of Asbestos Pathogenicity Overview of Molecular Mechanisms in Mesothelioma Genetic Predisposition to Mesothelioma: BAP1 Pathology of Mesothelioma Clinical Presentation Diagnostic Approach for Presumed Mesothelioma Natural History Treatment Palliation or Macroscopic Complete Resection Chemotherapy Novel Therapeutic Approaches Radiotherapy for Mesothelioma 110. Peritoneal Metastases and Peritoneal Mesothelioma Alvaro Arjona-Sanchez, Marcello Deraco, Olivier Glehen, David Morris, and Paul H. Sugarbaker Introduction Natural History Studies Document the Importance of Local-Regional Progression Patient Selection Using Quantitative Prognostic Indicators Appendiceal Malignancy Colorectal Peritoneal Metastases: Curative Treatment and Prevention Malignant Peritoneal Mesothelioma Gastric Cancer Peritoneal Metastases in Ovarian Cancer Sarcomatosis 111. Intraocular Melanoma Paul T. Finger and Anna C. Pavlick Introduction Incidence and Etiology Anatomy and Pathology Ophthalmic Diagnosis Staging Management of Primary Uveal Melanoma Overview: Treatment of Uveal Melanoma Treatment for Special Cases Diagnosis of Metastasis Biomarkers: Prognostic and Predictive Factors Summary SECTION 15. ONCOLOGIC EMERGENCIES 112. Superior Vena Cava Syndrome Andreas Rimner and Joachim Yahalom Introduction Anatomy and Pathophysiology Clinical Presentation and Etiology Diagnostic Workup Disease-Specific Management and Outcomes Small-cell Lung Cancer Non–small-cell Lung Cancer Non-Hodgkin Lymphoma Nonmalignant Causes

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Catheter-Induced Obstruction Treatment Areas of Uncertainty Recommendations 113. Increased Intracranial Pressure Ashley M. Roque and Joachim M. Baehring Introduction Pathophysiologic Considerations Epidemiology and Pathogenesis Clinical Presentation Diagnosis Treatment 114. Spinal Cord Compression Nicholas Szerlip, Whitney H. Beeler, and Daniel E. Spratt Incidence and Etiology Anatomy and Pathophysiology Clinical Presentation Differential Diagnosis Diagnosis Grading Management by Stage 115. Metabolic Emergencies Stacey Stein and Hari A. Deshpande Introduction Tumor Lysis Syndrome and Hyperuricemia Hyponatremia Hypercalcemia Lactic Acidosis Hyperammonemia Summary SECTION 16. TREATMENT OF METASTATIC CANCER 116. Metastatic Cancer to the Brain John H. Suh, Rupesh Kotecha, Manmeet S. Ahluwalia, and Michael A. Vogelbaum Introduction Epidemiology Clinical Presentation Imaging and Diagnosis Prognosis Symptom Management Treatment Options Leptomeningeal Metastases 117. Metastatic Cancer to the Lung John Yonge and Jessica Donington Introduction Presentation and Diagnosis of Pulmonary Metastases Surgical Metastasectomy Ablative Therapies Treatment Concerns and Outcomes for Individual Histologies Conclusion

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118. Metastatic Cancer to the Liver Clifford S. Cho, Sam Lubner, and Dawn Owen Introduction Hepatic Colorectal Adenocarcinoma Metastases Hepatic Neuroendocrine Carcinoma Metastases Noncolorectal Nonneuroendocrine Hepatic Metastases 119. Metastatic Cancer to the Bone Edward Chow, Joel A. Finkelstein, Arjun Sahgal, and Robert E. Coleman Introduction Presentation Pathophysiology Diagnostic Evaluation Therapeutic Modalities Optimum Use of Bone-Targeted Agents in Metastatic Bone Disease New Targeted Therapies in the Treatment of Metastatic Bone Disease External-Beam Radiation Therapy Systemic Radionuclides Radiotherapy for Complications of Bone Metastases: Localized External-Beam Radiotherapy for Pathologic Fractures 120. Malignant Pleural and Pericardial Effusions R. Taylor Ripley Malignant Pleural Effusions Treatment Algorithm Malignant Pericardial Effusions Summary 121. Malignant Ascites Thuy B. Tran and Ajay V. Maker Incidence and Etiology Anatomy and Pathology Diagnosis Management 122. Paraneoplastic Syndromes Daniel Morgensztern, Saiama N. Waqar, and Ramaswamy Govindan Introduction Paraneoplastic Neurologic Syndromes Paraneoplastic Endocrinology Syndromes Paraneoplastic Hematologic Syndromes Paraneoplastic Dermatologic Manifestations Paraneoplastic Rheumatologic Manifestations SECTION 17. STEM CELL TRANSPLANTATION 123. Autologous Hematopoietic Cell Transplantation Hillard M. Lazarus, Mehdi Hamadani, and Parameswaran N. Hari Introduction Autologous Hematopoietic Progenitor Cell Collection Autologous Hematopoietic Cell Transplantation Toxicities and Supportive Care Autologous Hematopoietic Cell Transplantation for Plasma Cell Myeloma Older Patients and Those with Comorbidities Maintenance Therapy after Hematopoietic Cell Transplantation Tandem Autologous Hematopoietic Cell Transplantation

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Response and Minimal Residual Disease after HCT Unique Considerations for Hematopoietic Progenitor Cell Collection in Myeloma Salvage Second or Third Transplants at Relapse Future Directions in Autologous Hematopoietic Cell Transplantation for Myeloma Autologous Hematopoietic Cell Transplantation for Rare Plasma Cell Dyscrasias Autologous Hematopoietic Cell Transplantation for Lymphomas Hematopoietic Cell Transplantation for Follicular Lymphoma Hematopoietic Cell Transplantation for Mantle Cell Lymphoma Hematopoietic Cell Transplantation for Waldenström Macroglobulinemia Hematopoietic Cell Transplantation for Marginal Zone and Small Lymphocytic Lymphoma Hematopoietic Cell Transplantation for Diffuse Large B-Cell Lymphoma Hematopoietic Cell Transplantation for Burkitt Lymphoma Hematopoietic Cell Transplantation for Hodgkin Lymphoma Hematopoietic Cell Transplantation for T-Cell Lymphomas Unique Considerations for Hematopoietic Cell Transplantation Mobilization in Lymphomas Tumor Cell Contamination in Autograft Posttransplantation Maintenance Therapies for Lymphoid Malignancies Functional Imaging and Autologous Hematopoietic Cell Transplantation Outcomes Autologous Hematopoietic Cell Transplantation for Acute Myeloid Leukemia Autologous Hematopoietic Cell Transplantation for Acute Lymphoblastic Leukemia Autologous Hematopoietic Cell Transplantation for Germ Cell Tumors Late Complications after Autologous Hematopoietic Cell Transplantation 124. Allogeneic Stem Cell Transplantation Stanley R. Riddell and Edus H. Warren Introduction Conditioning Regimens Stem Cell Sources Immunobiology of Allogeneic Hematopoietic Cell Transplantation Complications of Allogeneic Hematopoietic Cell Transplantation and Their Management Graft Failure Outcome of Allogeneic Hematopoietic Cell Transplantation for Hematologic Malignancies and Solid Tumors Management of Posttransplant Relapse Future Directions SECTION 18. MANAGEMENT OF ADVERSE EFFECTS OF TREATMENT 125. Infections in the Cancer Patient Tara N. Palmore, Mark Parta, Jennifer Cuellar-Rodriguez, and Juan C. Gea-Banacloche RISK FACTORS FOR INFECTIONS IN PATIENTS WITH CANCER AND ANTIMICROBIAL PROPHYLAXIS Risk Factors for Infection Prevention of Infections DIAGNOSIS AND MANAGEMENT OF INFECTIOUS DISEASES SYNDROMES Fever and Neutropenia Multidrug-Resistant Organisms of Interest in Oncology 126. Neutropenia and Thrombocytopenia Lodovico Balducci, Bijal Shah, and Kenneth Zuckerman Introduction 127. Nausea and Vomiting Elizabeth M. Blanchard and Paul J. Hesketh Introduction Nausea and Vomiting Syndromes

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Pathophysiology of Treatment-Induced Nausea and Vomiting Defining the Risk of Nausea and Vomiting Antiemetic Agents Lower Therapeutic Index Antiemetic Treatment by Clinical Setting Special Chemotherapy-Induced Nausea and Vomiting Problems Radiotherapy-Induced Nausea and Vomiting 128. Diarrhea and Constipation Nathan I. Cherny and Batsheva Werman Introduction Diarrhea Neutropenic Colitis Ischemic Colitis (Nonneutropenic Enterocolitis) Targeted Therapy–Associated Diarrhea Immunotherapy-Associated Diarrhea Radiotherapy-Induced Diarrhea Other Causes of Treatment-Related Diarrhea Assessment General Principles in the Management of Diarrhea Antidiarrhea Medications Specific Management Guidelines Radiation Therapy–Induced Diarrhea Immunotherapy-Induced Diarrhea and Colitis Management of Neutropenic Enterocolitis Diarrhea Prophylaxis Constipation Conclusion 129. Oral Complications Jane M. Fall-Dickson, Stefan Cordes, and Ann M. Berger Introduction Oral Mucositis Radiation Therapy–Related Complications Pathogenesis of Chemotherapy- and Radiation Therapy–Induced Oral Mucositis Chronic Graft-Versus-Host Disease Oral Manifestations Sequelae of Oral Complications Strategies for Prevention and Treatment of Oral Complications Treatment Strategies Radioprotectors Biologic Response Modifiers Treatment for Oral Chronic Graft-Versus-Host Disease Symptom Management 130. Pulmonary Toxicity Diane E. Stover, Michael T. Bender, Manju V. Pillai, and Robert J. Kaner Introduction Radiation-Induced Pulmonary Toxicity Chemotherapy-Induced Pulmonary Toxicity Additional Resources 131. Cardiac Toxicity Joachim Yahalom and Matthew A. Lunning Introduction Chemotherapeutics

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Radiotherapy-Associated Cardiac Sequelae Conclusion 132. Hair Loss and Other Hair Changes Hoyoung M. Maeng and Ann M. Berger Introduction Anatomy and Physiology of Hair Classification of Hair Loss Diagnosis of Hair Loss Treatment and Prevention of Chemotherapy-Induced Hair Loss Radiation-Induced Hair Changes Other Hair-Associated Changes Future Considerations 133. Gonadal Dysfunction George Patounakis, Alicia Y. Christy, and Alan H. DeCherney Introduction Effects of Cytotoxic Agents on Adult Men Effects of Cytotoxic Agents on Adult Women Effects of Cytotoxic Agents on Children Gonadal Dysfunction after Cranial Irradiation Preservation of Fertility, Hormone Levels, and Sexual Function Pharmacologic Attempts at Preserving Fertility in Men Pharmacologic Attempts at Preserving Fertility in Women Fertility Preservation in Women with Cervical Cancer Genetic Concerns Acknowledgments 134. Fatigue Sandra A. Mitchell and Ann M. Berger Introduction Definition, Risk Factors, and Mechanisms of Cancer-Related Fatigue Screening and Evaluation of the Patient with Cancer-Related Fatigue Interventions for Cancer-Related Fatigue Pharmacologic Interventions Nonpharmacologic Interventions Complementary and Integrative Therapies Summary 135. Second Cancers Chunkit Fung, Smita Bhatia, James M. Allan, Kevin C. Oeffinger, Andrea Ng, and Lois B. Travis Introduction Carcinogenicity of Individual Treatment Modalities Genetic Susceptibility to Second Primary Cancers Risk of Second Malignancy in Patient with Selected Primary Cancers Pediatric Malignancies Comment 136. Neurocognitive Effects Paul D. Brown, Alissa M. Butts, Michael W. Parsons, and Jane H. Cerhan Introduction Assessment of Cognitive Function Neurocognitive Effects of Central Nervous System Tumors and Treatment Neurocognitive Effects in Non–Central Nervous System Cancer Treatment of Cognitive Dysfunction

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Conclusion 137. Cancer Survivorship Wendy Landier, Michelle Shayne, Kevin C. Oeffinger, Smita Bhatia, and Louis S. Constine Introduction Definition of Survivorship and Scope of the Problem Goals of Survivorship Health Care Care Plans Delivery of Follow-up Care and Best Practice Models Educational Considerations Enhancing Research Survivorship Advocacy Conclusion

PA R T V I

Palliative and Alternative Care SECTION 1. SUPPORTIVE CARE AND QUALITY OF LIFE 138. Management of Cancer Pain Thomas W. Leblanc and Arif H. Kamal Introduction Epidemiology Definition of Pain Types of Pain Temporal Aspects of Pain Intensity of Pain Measurement Schemas Patient-Reported Outcome Measures Common Pain Syndromes Clinical Assessment of Pain Management of Cancer Pain Pharmacologic Management of Cancer Pain Adjuvant Drugs Adjuvants to Treat Side Effects Psychological Approaches Anesthetic and Neurosurgical Approaches Neuropharmacologic Approaches Neuroablative and Neurostimulatory Procedures for the Relief of Pain Trigger Point Injection and Acupuncture Physiatric Approaches Algorithm for Cancer Pain Management Future Directions Acknowledgments 139. Nutrition Support David A. August, Mihir M. Shah, and Maureen B. Huhmann Background Causes of Malnutrition in Cancer Patients Cancer Cachexia Syndrome Nutrition Screening and Assessment Pharmacotherapy of Cancer-Associated Weight Loss and Malnutrition

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Nutrition Support of Cancer Patients 140. Sexual Problems Eric S. Zhou and Sharon L. Bober Introduction Cancer in Men Cancers that Affect Men and Women Cancer in Women Cancer in Children and Young Adults Relevant Sociocultural Considerations Disruption of Intimacy and Relational Considerations Communication About Sexual Problems 141. Psychological Issues David Spiegel and Michelle B. Riba Introduction Common Psychiatric Conditions Screening for Psychological Problems Coping Treatment Interventions Implications for Cancer Progression and Mortality Psychotropic Medication Conclusion 142. Communicating News to the Cancer Patient Eric J. Cassell Introduction Preventing Illness Communication Explanations Uncomfortable Questions Information Meaning Cafeteria Explanations 143. Specialized Care of the Terminally Ill Robert S. Krouse and Arif H. Kamal Introduction Early Specialist Palliative Care Communication Specific Problems in the Setting of Advanced Cancer Impending Death Conclusions 144. Rehabilitation of the Cancer Patient Michael D. Stubblefield Introduction The Rehabilitation Team Complications of Cancer and Its Treatment Neuromuscular Complications of Cancer and Cancer Treatment Musculoskeletal Complications of Cancer and Cancer Treatment Radiation Fibrosis Syndrome Head and Neck Cancer Lymphedema Rehabilitation Interventions

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SECTION 2. COMPLEMENTARY, ALTERNATIVE, AND INTEGRATIVE THERAPIES 145. Complementary, Alternative, and Integrative Therapies in Cancer Care Catherine E. Ulbricht, Oliver Grundmann, Eunji Michelle Ko, and Nikhil Sangave Background Establishing an Integrative Oncology Approach with Patients Standardization and Quality Specific Complementary and Integrative Medicine Therapies Index

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PART I

Molecular Biology of Cancer

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1

The Cancer Genome Yardena Samuels, Alberto Bardelli, Yochai Wolf, and Carlos López-Otin

INTRODUCTION There is a broad consensus that cancer is, in essence, a genetic disease and that accumulation of molecular alterations in the genome of somatic cells is the basis of cancer progression (Fig. 1.1).1 In the past 10 years, the availability of the human genome sequence and progress in DNA sequencing technologies has dramatically improved knowledge of this disease. These new insights are transforming the field of oncology at multiple levels: 1. The genomic maps are redesigning the tumor taxonomy by moving it from a histologic- to a genetic-based level. 2. The success of cancer drugs designed to target the molecular alterations underlying tumorigenesis has proven that somatic genetic alterations are legitimate targets for therapy. 3. Tumor genotyping is helping clinicians individualize treatments by matching patients with the best treatment for their tumors. 4. Tumor-specific DNA alterations represent highly sensitive biomarkers for disease detection and monitoring. 5. Finally, the ongoing analyses of multiple cancer genomes will identify additional targets, whose pharmacologic exploitation will undoubtedly result in new therapeutic approaches. This chapter reviews the progress that has been made in understanding the genetic basis of sporadic cancers. An emphasis is placed on an introduction to novel integrated genomic approaches that allow a comprehensive and systematic evaluation of genetic alterations that occur during the progression of cancer. Using these powerful tools, cancer research, diagnosis, and treatment are poised for a transformation in the next years.

CANCER GENES AND THEIR MUTATIONS Cancer genes are broadly grouped into oncogenes and tumor suppressor genes. Using a classical analogy, oncogenes can be compared to a car accelerator so that a mutation in an oncogene would be the equivalent of having the accelerator continuously pressed.2 Tumor suppressor genes, in contrast, act as brakes2 so that when they are not mutated, they function to inhibit tumorigenesis. Oncogene and tumor suppressor genes may be classified by the nature of their somatic mutations in tumors. Mutations in oncogenes typically occur at specific hotspots, often affecting the same codon or clustered at neighboring codons in different tumors.1 Furthermore, mutations in oncogenes are almost always missense, and the mutations usually affect only one allele, making them heterozygous. In contrast, tumor suppressor genes are usually mutated throughout the gene; a large number of the mutations may truncate the encoded protein and generally affect both alleles, causing loss of heterozygosity (LOH). Major types of somatic mutations present in malignant tumors include nucleotide substitutions, small insertions and deletions (indels), chromosomal rearrangements, and copy number alterations.

IDENTIFICATION OF CANCER GENES The completion of the Human Genome Project marked a new era in biomedical sciences.3 Knowledge of the sequence and organization of the human genome now allows for the systematic analysis of the genetic alterations underlying the origin and evolution of tumors. Before elucidation of the human genome, several cancer genes, such as KRAS, TP53, and APC, were successfully discovered using approaches based on an oncovirus analysis, linkage studies, LOH, and cytogenetics.4,5 The first curated version of the Human Genome Project was released in

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20043 and provided a sequence-based map of the normal human genome. This information, together with the construction of the HapMap, which contains single nucleotide polymorphisms, and the underlying genomic structure of natural human genomic variation,6,7 allowed an extraordinary throughput in cataloging somatic mutations in cancer. These projects now offer an unprecedented opportunity: the identification of all the genetic changes associated with a human cancer. For the first time, this ambitious goal is within reach of the scientific community. Already, a number of studies have demonstrated the usefulness of strategies aimed at the systematic identification of somatic mutations associated with cancer progression. Notably, the Human Genome Project, the HapMap project, as well as the candidate and family gene approaches (described in the following paragraphs), utilized capillary-based DNA sequencing (first-generation sequencing, also known as Sanger sequencing).8 Figure 1.2 clearly illustrates the developments in the search of cancer genes, its increased pace, as well as the most relevant findings in this field.

Cancer Gene Discovery by Sequencing Candidate Gene Families The availability of the human genome sequence provides new opportunities to comprehensively search for somatic mutations in cancer on a larger scale than previously possible. Progress in the field has been closely linked to improvements in the throughput of DNA analysis and in the continuous reduction in sequencing costs. What follows are some of the achievements in this research area as well as how they affected knowledge of the cancer genome. A seminal work in the field was the systematic mutational profiling of the genes involved in the RAS-RAF pathway in multiple tumors. This candidate gene approach led to the discovery that BRAF is frequently mutated in melanomas and is mutated at a lower frequency in other tumor types.9 Follow-up studies quickly revealed that mutations in BRAF are mutually exclusive with alterations in KRAS,9,10 genetically emphasizing that these genes function in the same pathway, a concept that had been previously demonstrated in lower organisms such as Caenorhabditis elegans and Drosophila melanogaster.11,12 In 2003, the identification of cancer genes shifted from a candidate gene approach to the mutational analyses of gene families. The first gene families to be completely sequenced were those that involved protein13,14 and lipid phosphorylation.15 The rationale for initially focusing on these gene families was threefold: The corresponding proteins were already known at that time to play a pivotal role in the signaling and proliferation of normal and cancerous cells. Multiple members of the protein kinases family had already been linked to tumorigenesis. Kinases are clearly amenable to pharmacologic inhibition, making them attractive drug targets.

Figure 1.1 Schematic representation of the genomic and histopathologic steps associated with

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tumor progression: from the occurrence of the initiating mutation in the founder cell to metastasis formation. It has been convincingly shown that the genomic landscape of solid tumors such as that of pancreatic and colorectal tumors requires the accumulation of many genetic events, a process that requires decades to complete. This timeline offers an incredible window of opportunity for the early detection, which is often associated with an excellent prognosis, of this disease. ACF, aberrant crypt focus. The mutational analysis of all the tyrosine-kinase domains in colorectal cancers (CRCs) revealed that 30% of cases had a mutation in at least one tyrosine-kinase gene, and overall mutations were identified in eight different kinases, most of which had not previously been linked to cancer.13 An additional mutational analysis of the coding exons of 518 protein kinase genes in 210 diverse human cancers, including breast, lung, gastric, ovarian, renal, and acute lymphoblastic leukemia, identified approximately 120 mutated genes that probably contribute to oncogenesis.14 Because kinase activity is attenuated by enzymes that remove phosphate groups called phosphatases, the rational next step in these studies was to perform a mutation analysis of the protein tyrosine phosphatases. A combined analysis of the protein tyrosine kinases and the protein tyrosine phosphatases showed that 50% of CRCs had mutations in a tyrosine-kinase gene, a protein tyrosine phosphatase gene, or both, further emphasizing the pivotal role of protein phosphorylation in neoplastic progression. Many of the identified genes had previously been linked to human cancer, thus validating the unbiased comprehensive mutation profiling. These landmark studies led to additional gene family surveys. The phosphatidylinositol 3-kinase (PI3K) gene family, which also plays a role in proliferation, adhesion, survival, and motility, was also comprehensively investigated.16 Sequencing of the exons encoding the kinase domain of all 16 members belonging to this family pinpointed PIK3CA as the only gene to harbor somatic mutations. When the entire coding region was analyzed, PIK3CA was found to be somatically mutated in 32% of CRCs. At that time, the PIK3CA gene was certainly not a newcomer in the cancer arena because it had previously been shown to be involved in cell transformation and metastasis.16 Strikingly, its staggeringly high mutation frequency was discovered only through systematic sequencing of the corresponding gene family.15 Subsequent analysis of PIK3CA in other tumor types identified somatic mutations in this gene in additional cancer types, including 36% of hepatocellular carcinomas, 36% of endometrial carcinomas, 25% of breast carcinomas, 15% of anaplastic oligodendrogliomas, 5% of medulloblastomas and anaplastic astrocytomas, and 27% of glioblastomas.17–21 It is known that PIK3CA is one of the two (the other being KRAS) most commonly mutated oncogenes in human cancers. Further investigation of the PI3K pathway in CRC showed that 40% of tumors had genetic alterations in one of the PI3K pathway genes, emphasizing the central role of this pathway in CRC pathogenesis.22 Although most cancer genome studies of large gene families have focused on the kinome, recent analyses have revealed that members of other families highly represented in the human genome are also a target of mutational events in cancer. This is the case of proteases, a complex group of enzymes consisting of at least 569 components that constitute the so-called human degradome.23 Functional studies have also revealed that beyond the initial recognition of proteases as prometastatic enzymes, they play dual roles in cancer, as assessed by the identification of a growing number of tumor-suppressive proteases.24–27 These findings emphasized the possibility that mutational activation or inactivation of protease genes occurs in cancer. A systematic analysis of genetic alterations in breast and CRCs revealed that proteases from different catalytic classes were somatically mutated in cancer.28 These results prompted the mutational analysis of entire protease families such as matrix metalloproteinases (MMP), a disintegrin and metalloproteinase (ADAM), and ADAMs with thrombospondin domains (ADAMTS) in different tumors. These studies led to the identification of protease genes frequently mutated in cancer, such as MMP8, which is mutated and functionally inactivated in 6.3% of human melanomas.29,30

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Figure 1.2 Timeline of seminal hypotheses, research discoveries, and research initiatives that have led to an improved understanding of the genetic etiology of human tumorigenesis within the past century. The consensus cancer gene data were obtained from the Wellcome Trust Sanger Institute Cancer Genome Project Web site (http://www.sanger.ac.uk/genetics/CGP). miRNA, microRNA. (Redrawn from Bell DW. Our changing view of the genomic landscape of cancer. J Pathol 2010;220:231–243.)

Mutational Analysis of Exomes Using Sanger Sequencing Although the gene family approach for the identification of cancer genes has proven extremely valuable, it still is a candidate approach and thus biased in its nature. The next step forward in the mutational profiling of cancer has been the sequencing of exomes, which is the entire coding portion of the human genome (18,000 protein-encoding genes). The exomes of many different tumors—including breast, colorectal, pancreatic, and ovarian clear cell carcinomas; glioblastoma multiforme; and medulloblastoma—have been analyzed using Sanger sequencing. For the first time, these large-scale analyses allowed researchers to describe and understand the genetic complexity of human cancers.29,31–34 The declared goals of these exome studies were to provide methods for exomewide mutational analyses in human tumors, to characterize their spectrum and quantity of somatic mutations, and, finally, to discover new genes involved in tumorigenesis as well as novel pathways that have a role in these tumors. In these studies, sequencing data were complemented with gene expression and copy number analyses, thus providing a comprehensive view of the genetic complexity of human tumors.32–35 A number of conclusions can be drawn from these analyses, including the following: Cancer genomes have an average of 30 to 100 somatic alterations per tumor in coding regions, which was a higher number than previously thought. Although the alterations included point mutations, small insertions, deletions, or amplifications, the great majority of the mutations observed were single-base substitutions.32,35 Even within a single cancer type, there is a significant intertumor heterogeneity. This means that multiple mutational patterns (encompassing different mutant genes) are present in tumors that cannot be distinguished based on histologic analysis. The concept that individual tumors have a unique genetic milieu is highly relevant for personalized medicine, a concept that will be further discussed. The spectrum and nucleotide contexts of mutations differ between different tumor types. For example, over

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50% of mutations in CRC were C:G to T:A transitions, and 10% were C:G to G:C transversions. In contrast, in breast cancers, only 35% of the mutations were C:G to T:A transitions, and 29% were C:G to G:C transversions. Knowledge of mutation spectra is vital because it allows insight into the mechanisms underlying mutagenesis and repair in the various cancers investigated. A considerably larger number of genes that had not been previously reported to be involved in cancer were found to play a role in the disease. Solid tumors arising in children, such as medulloblastomas, harbor on average 5 to 10 times less gene alterations compared to a typical adult solid tumor. These pediatric tumors also harbor fewer amplifications and homozygous deletions within coding genes compared to adult solid tumors. Importantly, to deal with the large amount of data generated in these genomic projects, it was necessary to develop new statistical and bioinformatic tools. Furthermore, an examination of the overall distribution of the identified mutations allowed for the development of a novel view of cancer genome landscapes and a novel definition of cancer genes. These new concepts in the understanding of cancer genetics are further discussed in the following paragraphs. The compiled conclusions derived from these analyses have led to a paradigm shift in the understanding of cancer genetics. A clear indication of the power of the unbiased nature of the whole-exome surveys was revealed by the discovery of recurrent mutations in the active site of IDH1, a gene with no known link to gliomas, in 12% of tumors analyzed.35 Because malignant gliomas are the most common and lethal tumors of the central nervous system, and because glioblastoma multiforme (GBM; World Health Organization grade IV astrocytoma) is the most biologically aggressive subtype, the unveiling of IDH1 as a novel GBM gene is extremely significant. Importantly, mutations of IDH1 predominantly occurred in younger patients and were associated with a better prognosis.36 Follow-up studies showed that mutations of IDH1 occur early in glioma progression; the R132 somatic mutation is harbored by the majority (greater than 70%) of grades II and III astrocytomas and oligodendrogliomas as well as in secondary GBMs that develop from these lower grade lesions.36–42 In contrast, less than 10% of primary GBMs harbor these alterations. Furthermore, analysis of the associated IDH2 revealed recurrent somatic mutations in the R172 residue, which is the exact analog of the frequently mutated R132 residue of IDH1. These mutations occur mostly in a mutually exclusive manner with IDH1 mutations,36,38 suggesting that they have equivalent phenotypic effects. Subsequently, IDH1 mutations have been reported in additional cancer types, including hematologic neoplasias.43–45

Next-Generation Sequencing and Cancer Genome Analysis In 1977, the introduction of the Sanger method for DNA sequencing with chain-terminating inhibitors transformed biomedical research.8 Over the past 30 years, this first-generation technology has been universally used for elucidating the nucleotide sequence of DNA molecules. However, the launching of new large-scale projects, including those implicating whole-genome sequencing of cancer samples, has made necessary the development of new methods that are widely known as next-generation sequencing technologies.46–48 These approaches have significantly lowered the cost and the time required to determine the sequence of the 3 × 109 nucleotides present in the human genome. Moreover, they have a series of advantages over Sanger sequencing, which are of special interest for the analysis of cancer genomes.49 First, next-generation sequencing approaches are more sensitive than Sanger methods and can detect somatic mutations even when they are present in only a subset of tumor cells.50 Moreover, these new sequencing strategies are quantitative and can be used to simultaneously determine both nucleotide sequence and copy number variations.51 They can also be coupled to other procedures such as those involving paired-end reads, allowing for the identification of multiple structural alterations, such as insertions, deletions, and rearrangements, that commonly occur in cancer genomes.50 Nonetheless, next-generation sequencing still presents some limitations that are mainly derived from the relatively high error rate in the short reads generated during the sequencing process. In addition, these short reads make the task of de novo assembly of the generated sequences and the mapping of the reads to a reference genome extremely complex. To overcome some of these current limitations, deep coverage of each analyzed genome is required and a careful validation of the identified variants must be performed, typically using Sanger sequencing. As a consequence, there is a substantial increase in both the cost of the process and in the time of analysis. Therefore, it can be concluded that whole-genome sequencing of cancer samples is already a feasible task but not yet a routine process. Further technical improvements will be required before the task of decoding the entire genome of any malignant tumor of any cancer patient can be applied to clinical practice.

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The number of next-generation sequencing platforms has substantially grown over the past few years and currently includes technologies from Roche/454, Illumina/Solexa, Life/APG’s SOLiD3, Helicos BioSciences/HeliScope, and Pacific Biosciences/PacBio RS.48 Noteworthy also are the recent introduction of the Polonator G.007 instrument, an open source platform with freely available software and protocols; the Ion Torrent’s semiconductor sequencer; as well as those involving self-assembling DNA nanoballs or nanopore technologies.52–54 These new machines are driving the field toward the era of third-generation sequencing, which brings enormous clinical interest because it can substantially increase the speed and accuracy of analyses at reduced costs and can facilitate the possibility of single-molecule sequencing of human genomes. A comparison of next-generation sequencing platforms is shown in Table 1.1. These various platforms differ in the method utilized for template preparation and in the nucleotide sequencing and imaging strategy, which finally result in their different performance. Ultimately, the most suitable approach depends on the specific genome sequencing projects.48 Current methods of template preparation first involve randomly shearing genomic DNA into smaller fragments, from which a library of either fragment templates or mate-pair templates are generated. Then, clonally amplified templates from single DNA molecules are prepared by either emulsion polymerase chain reaction (PCR) or solid-phase amplification.55,56 Alternatively, it is possible to prepare single-molecule templates through methods that require less starting material and that do not involve PCR amplification reactions, which can be the source of artifactual mutations.57 Once prepared, templates are attached to a solid surface in spatially separated sites, allowing thousands to billions of nucleotide sequencing reactions to be performed simultaneously. The sequencing methods currently used by the different next-generation sequencing platforms are diverse and have been classified into four groups: cyclic reversible termination, single-nucleotide addition, real-time sequencing, and sequencing by ligation (Fig. 1.3).48,58 These sequencing strategies are coupled with different imaging methods, including those based on measuring bioluminescent signals or involving four-color imaging of single molecular events. Finally, the extraordinary amount of data released from these nucleotide sequencing platforms is stored, assembled, and analyzed using powerful bioinformatic tools that have been developed in parallel with next-generation sequencing technologies.59 Next-generation sequencing approaches represent the newest entry into the cancer genome decoding arena and have already been applied to cancer analyses. The first research group to apply these methodologies to whole cancer genomes was that of Ley et al.,60 who reported in 2008 the sequencing of the entire genome of a patient with acute myeloid leukemia (AML) and its comparison with the normal tissue from the same patient, using the Illumina/Solexa platform. As further described, this work allowed for the identification of point mutations and structural alterations of putative oncogenic relevance in AML and represented proof of principle of the relevance of next-generation sequencing for cancer research. TABLE 1.1

Comparative Analysis of Next-Generation Sequencing Platforms

Library/Template Preparation

Sequencing Method

Average ReadLength (Bases)

Roche 454 GS FLX

Fragment, matepair Emulsion PCR

Pyrosequencing

400

0.35

0.45

500,000

Fast run times High reagent cost

Illumina HiSeq 2000

Fragment, matepair Solid phase

Reversible terminator

100–125

8 (matepair run)

150–200

540,000

Most widely used platform Low multiplexing capability

Life/APG’s SOLiD 5500xl

Fragment, matepair Emulsion PCR

Cleavable probe, sequencing by ligation

35–75

7 (matepair run)

180–300

595,000

Inherent error correction Long run times

Helicos BioSciences HeliScope

Fragment, matepair Single molecule

Reversible terminator

32

8 (fragment run)

37

999,000

Nonbias template representation Expensive, high error rates

Platform

Run Time (Days)

Gb Per Run

Instrument Cost (U.S. $)

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Comments

Pacific Biosciences PacBio RS

Fragment Single molecule

Real-time sequencing

1,000

1

0.075

NA

Greatest potential for long reads Highest error rates

Polonator G.007

Mate pair Emulsion PCR

Noncleavable probe, sequencing by ligation

26

5 (matepair run)

12

170,000

Least expensive platform Shortest read lengths

PCR, polymerase chain reaction; NA, not available. Data represent an update of information provided in Metzker ML. Sequencing technologies—the next generation. Nat Rev Genet 2010;11:31–46.

Whole-Genome Analysis Utilizing Second-Generation Sequencing The sequence of the first whole cancer genome was reported in 2008, where AML and normal skin from the same patient were described.60 Numerous additional whole genomes, together with the corresponding normal genomes of patients with a variety of malignant tumors, have been reported since then.43,50,61–72 The first available whole genome of a cytogenetically normal AML subtype M1 (AML-M1) revealed eight genes with novel mutations along with another 500 to 1,000 additional mutations found in noncoding regions of the genome. Most of the identified genes had not been previously associated with cancer. However, validation of the detected mutations did not identify novel recurring mutations in AML.60 Concomitantly, with the expansion in the use of next-generation sequencers, many other whole genomes from a number of cancer types started to be evaluated in a similar manner (Fig. 1.4).73 In contrast to the first AML whole genome, the second did observe a recurrent mutation in IDH1, encoding isocitrate dehydrogenase.43 Follow-up studies extended this finding and reported that mutations in IDH1 and the related gene IDH2 occur at a 20% to 30% frequency in AML patients and are associated with a poor prognosis in some subgroups of patients.66,67,74 A good example illustrating the high pace at which second-generation technologies and their accompanying analytical tools are found is demonstrated by the following finding derived from a reanalysis of the first AML whole genome. Thus, when improvements in sequencing techniques were available, the first AML whole genome (described previously), which identified no recurring mutations and had a 91.2% diploid coverage, was reevaluated by deeper sequence coverage, yielding 99.6% diploid coverage of the genome. This improvement, together with more advanced mutation calling algorithms, allowed for the discovery of several nonsynonymous mutations that had not been identified in the initial sequencing. This included a frameshift mutation in the DNA methyltransferase gene DNMT3A. Validation of DNMT3A in 280 additional de novo AML patients to define recurring mutations led to the significant discovery that a total of 22.1% of AML cases had mutations in DNMT3A that were predicted to affect translation. The median overall survival among patients with DNMT3A mutations was significantly shorter than that among patients without such mutations (12.3 months versus 41.1 months; P < .001). Shortly after this study, complete sequences of a series of cancer genomes, together with matched normal genomes of the same patients, were reported.43,65,70,75 These works opened the way to more ambitious initiatives, including those involving large international consortia, aimed at decoding the genome of malignant tumors from thousands of cancer patients. Thus, over the last few years, many whole genomes of different human malignancies have been made available.61–63 In addition to direct applications of next-generation sequencing technologies for the mutational analysis of cancer genomes, these methods have an additional range of applications in cancer research. Thus, genome sequencing efforts have begun to elucidate the genomic changes that accompany metastasis evolution through a comparative analysis of primary and metastatic lesions from breast and pancreatic cancer patients.64,68,69,71 Likewise, massively parallel sequencing has been used to analyze the evolution of a tongue adenocarcinoma in response to selection by targeted kinase inhibitors.76 Detailed information of several of these whole-genome projects is found in the following paragraph. The first solid cancer to undergo whole-genome sequencing was a malignant melanoma that was compared to a lymphoblastoid cell line from the same individual.75 Impressively, a total of 33,345 somatic base substitutions were identified, with 187 nonsynonymous substitutions in protein-coding sequences, at least one order of magnitude higher than any other cancer type. Most somatic base substitutions were C:G > T:A transitions, and of the 510 dinucleotide substitutions, 360 were CC.TT/GG.AA changes, which is consistent with ultraviolet light exposure mutation signatures previously reported in melanoma.14 (Such results from the most comprehensive catalog of somatic mutations not only provide insight into the DNA damage signature in this cancer type but also

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is useful in determining the relative order of some acquired mutations.) Indeed, this study shows that a significant correlation exists between the presence of a higher proportion of C.A/G.T transitions in early (82%) compared to late mutations (53%). Another important aspect that the comprehensive nature of this melanoma study provided was that cancer mutations are spread out unevenly throughout the genome, with a lower prevalence in regions of transcribed genes, suggesting that DNA repair occurs mainly in these areas.

Figure 1.3 Advances in sequencing chemistry implemented in next-generation sequencers. A: The pyrosequencing approach implemented in 454/Roche sequencing technology detects incorporated nucleotides by chemiluminescence resulting from PPi release. ATP, adenosine triphosphate. B: The Illumina method utilizes sequencing by synthesis in the presence of fluorescently labeled nucleotide analogs that serve as reversible reaction terminators. C: The single-molecule sequencing by synthesis approach detects template extension using Cy3 and Cy5 labels attached to the sequencing primer and the incoming nucleotides, respectively. D: The sequencing by oligonucleotide ligation and detection (SOLiD) method sequences templates by sequential ligation of labeled degenerate probes. Two-base encoding implemented in the SOLiD instrument allows for probing each nucleotide position twice. ABI, Applied Biosystems. (From Morozova O, Hirst M, Marra MA. Applications of new sequencing technologies for transcriptome analysis. Annu Rev Genomics Hum Genet 2009;10:135–151.) An interesting and pioneering example of the power of whole-genome sequencing in deciphering the mutation evolution in carcinogenesis was seen in a study in which a basal-like breast cancer tumor, a brain metastasis, a tumor xenograft derived from the primary tumor, and the peripheral blood from the same patient were compared (Fig. 1.5).71 This analysis showed a clear overlap in mutation incidence between the metastatic and xenograft cases, suggesting that xenografts undergo similar selection as metastatic lesions and, therefore, are a reliable source for genomic analyses. The main conclusion of this whole-genome study was that although metastatic tumors harbor an increased number of genetic alterations, the majority of the alterations found in the primary tumor are preserved. Further studies have confirmed and extended these findings to metastatic tumors from different types, including renal and pancreatic carcinomas.77 The importance of performing whole-genome sequencing has also been emphasized by the recent identification of somatic mutations in regulatory regions, which can also elicit tumorigenesis, such as alterations in the

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telomerase reverse transcriptase (TERT) promoter region in melanoma. (In combination, these TERT mutations are seen in a greater frequency than BRAF- and NRAS-activating mutations. They occur in a mutually exclusive manner and in regions that do not show a large background mutation rate, all suggesting that these mutations are important driver events contributing to oncogenesis.) As the TERT promoter mutation discovery shows, regions of the genome that do not code for proteins are just as vital in our understanding of the biology behind tumor development and progression. Another class of non– protein-coding regions in the genome are the noncoding RNAs. One class of noncoding RNAs are microRNAs (miRNAs). Discovered 20 years ago, miRNAs are known to be expressed in a tissue- or developmentally specific manner, and their expression can influence cellular growth and differentiation along with cancer-related pathways such as apoptosis or stress response. miRNAs do this through either overexpression, leading to the targeting and downregulation of tumor suppressor genes, or inversely through their own downregulation, leading to increased expression of their target oncogene. miRNAs have been extensively studied in cancer, and their functional effects have been noted in a wide variety of cancers like glioma78 and breast cancer,79 to name just two.

Figure 1.4 The prevalence of somatic mutations across human cancer types. Every dot represents a sample, whereas the red horizontal lines are the median numbers of mutations in the respective cancer types. The vertical axis (log scaled) shows the number of mutations per megabase, whereas the different cancer types are ordered on the horizontal axis based on their median numbers of somatic mutations. ALL, acute lymphoblastic leukemia; AML, acute myeloid leukemia; CLL, chronic lymphocytic leukemia. (Used with permission from Alexandrov LB, Nik-Zainal S, Wedge DC, et al. Signatures of mutational processes in human cancer. Nature 2013;500:415–421.) Another class of noncoding RNAs (ncRNA) are the long noncoding RNAs (lncRNA). These RNAs are typically greater than 200 bp and can range up to 100 kb in size. They are transcribed by RNA polymerase II and can undergo splicing and polyadenylation. Although much less extensively studied when compared to miRNAs for their role in cancer, lncRNAs are beginning to come under much more scrutiny. A recent study of the steroid receptor RNA activator revealed two transcripts, an lncRNA (steroid receptor RNA activator) and a translated transcript (steroid receptor RNA activator protein), that coexist within breast cancer cells. However, their expression varies within breast cancer cell lines with different phenotypes. It was shown that in a more invasive breast cancer line, higher relative levels of the noncoding transcript were seen.80 Because this ncRNA acts as part of a ribonucleoprotein complex that is recruited to the promoter region of regulatory genes, it has been hypothesized that this shift in balance between both noncoding and coding transcripts may be associated with growth advantages. When this balance was shifted in vitro, it led to a large increase in transcripts associated with invasion and migration. The results of this study highlight the importance of the investigation into the roles of ncRNA in tumor development or progression and confirm again that the study of coding variants is not sufficient in determining the full genomic spectrum of cancer.

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Figure 1.5 Covering all the bases in metastatic assessment. Ding et al.71 performed a genomewide analysis on three tumor samples: a patient’s primary breast tumor; her metastatic brain tumor, which formed despite therapy; and a xenograft tumor in a mouse, originating from the patient’s breast tumor. They find that the primary tumor differs from the metastatic and xenograft tumors mainly in the prevalence of genomic mutations. (With permission from Gray J. Cancer: genomics of metastasis. Nature 2010;464:989–990.) It must be also noted that the recent analysis of whole genomes of many different human tumors has provided additional insights into cancer evolution. Thus, it has been demonstrated that multiple mutational processes are operative during cancer development and progression, each of which has the capacity to leave its particular mutational signature on the genome. A remarkable and innovative study in this regard was aimed at the generation of the entire catalog of somatic mutations in 21 breast carcinomas and the identification of the mutational signatures of the underlying processes. This analysis revealed the occurrence of multiple, distinct single- and double-nucleotide substitution signatures. Moreover, it was reported that breast carcinomas harboring BRCA1 or BRCA2 mutations showed a characteristic combination of substitution mutation signatures and a particular profile of genomic deletions. An additional contribution of this analysis was the identification of a distinctive phenomenon of localized hypermutation, which has been termed kataegis, and which has also subsequently been observed in other malignancies distinct from breast carcinomas.73 Whole-genome sequencing of human carcinomas has also allowed for the ability to characterize other massive genomic alterations, termed chromothripsis and chromoplexy, occurring across different cancer subtypes.81 Chromothripsis implies a massive genomic rearrangement acquired in a one-step catastrophic event during cancer development and has been detected in about 2% to 3% of all tumors but is present at high frequency in some particular cases, such as bone cancers.82 Chromoplexy has been originally described in prostate cancer and involves many DNA translocations and deletions that arise in a highly interdependent manner and result in the coordinate disruption of multiple cancer genes.83 These newly described phenomena represent powerful strategies of rapid genome evolution, which may play essential roles during carcinogenesis.

Whole-Exome Analysis Utilizing Second-Generation Sequencing Another application of second-generation sequencing involves utilizing nucleic acid “baits” to capture regions of interest in the total pool of nucleic acids. These could either be DNA, as described previously,84,85 or RNA.86 Indeed, most areas of interest in the genome can be targeted, including exons and ncRNAs. Over the last few years, thousands of cancer samples have been subjected to whole-exome sequencing. These studies, combined with data from whole-genome sequencing, have provided an unprecedented level of information about the mutational landscape of the most frequent human malignancies.61–63 In addition, whole-exome sequencing has been used to identify the somatic mutations characteristic of both rare tumors and those that are prevalent in certain geographical regions.63

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Overall, these studies have provided very valuable information about mutation rates and spectra across cancer types and subtypes.73,87,88 Remarkably, the variation in mutational frequency between different tumors is extraordinary, with hematologic and pediatric cancers showing the lowest mutation rates (0.001 per Mb of DNA) and melanoma and lung cancers presenting the highest mutational burden (more than 400 per Mb). Whole-exome sequencing has also contributed to the identification of novel cancer genes that had not been previously described to be causally implicated in the carcinogenesis process. These genes belong to different functional categories, including signal transduction, RNA maturation, metabolic regulation, epigenetics, chromatin remodeling, and protein homeostasis.61 Finally, a combination of data from whole-exome and whole-genome sequencing has allowed for the identification of the signatures of mutational processes operating in different cancer types.73 Thus, an analysis of a dataset of about 5 million mutations from over 7,000 cancers from 30 different types has allowed for the extraction of more than 20 distinct mutational signatures. Some of them, such as those derived from the activity of APOBEC cytidine deaminases, are present in most cancer types, whereas others are characteristic of specific tumors. Known signatures associated with age, smoking, ultraviolet light exposure, and DNA repair defects have been also identified in this work, but many of the detected mutational signatures are of cryptic origin. These findings demonstrate the impressive diversity of mutational processes underlying cancer development and may have enormous implications for the future understanding of cancer biology, prevention, and treatment.

SOMATIC ALTERATION CLASSES DETECTED BY CANCER GENOME ANALYSIS Whole-genome sequencing of cancer genomes has an enormous potential to detect all major types of somatic mutations present in malignant tumors. This large repertoire of genomic abnormalities includes single nucleotide changes, small insertions and deletions, large chromosomal reorganizations, and copy number variations (Fig. 1.6). Nucleotide substitutions are the most frequent somatic mutations detected in malignant tumors, although there is a substantial variability in the mutational frequency among different cancers.47 On average, human malignancies have one nucleotide change per million bases, but melanomas reach mutational rates 10-fold higher, and tumors with mutator phenotype caused by DNA mismatch repair deficiencies may accumulate tens of mutations per million nucleotides. By contrast, tumors of hematopoietic origin have less than one base substitution per million. Several bioinformatic tools and pipelines have been developed to efficiently detect somatic nucleotide substitutions through comparison of the genomic information obtained from paired normal and tumor samples from the same patient. Likewise, there are a number of publicly available computational methods to predict the functional relevance of the identified mutations in cancer specimens.47 Most of these bioinformatic tools exclusively deal with nucleotide changes in protein coding regions and evaluate the putative structural or functional effect of an amino acid substitution in a determined protein, thus obviating changes in other genomic regions, which can also be of crucial interest in cancer. In any case, current computational methods used in this regard are far from being optimal, and experimental validation is finally required to assess the functional relevance of nucleotide substitutions found in cancer genomes. For years, the main focus of cancer genome analyses has been on identifying coding mutations that cause a change in the amino acid sequence of a gene. The rationale behind this is quite sound because any mutation that creates a novel protein or truncates an essential protein has the potential to drastically change the cellular environment. Examples of this have been shown earlier in the chapter with BRAF and KRAS along with many others. With the advancements in next-generation sequencing, larger studies are able to be conducted. These studies give the power to detect mutations occurring in the cancer genome at a lower frequency. Interesting to note is that these studies are leading to the discovery that recurrent synonymous mutations occur in cancer. Previously believed to be merely neutral mutations that maintain no functional role in tumorigenesis, these mutations were largely ignored, but a recent study shows89 that simply dismissing these mutations as silent may be premature. In a review of only 29 melanoma exomes and genomes, 16 recurring synonymous mutations were discovered. When these mutations were screened in additional samples, a synonymous mutation in the gene BCL2L12 was discovered in 12 out of 285 total samples. The observed frequency of this recurrent mutation is greater than expected by chance, suggesting that it has undergone some type of selective pressure during tumor development.89 Noting that BCL2L12 had previously been linked to tumorigenesis, the mutation was further evaluated for its functional effect, with the finding that it led to an abrogation of the effect of an miRNA, leading to the deregulated expression of BCL2L12. BCL2L12 is a negative regulator of the gene p53, which functions by binding and

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inhibiting apoptosis in glioma.90 Accordingly, the dysregulation observed in BCL2L12 led to a reduction in p53 target gene expression.

Figure 1.6 The catalog of somatic mutations in COLO-829. Chromosome ideograms are shown around the outer ring and are oriented pter–qter in a clockwise direction with centromeres indicated in red. Other tracks contain somatic alterations (from outside to inside): validated insertions (light green rectangles), validated deletions (dark green rectangles), heterozygous (light orange bars) and homozygous (dark orange bars) substitutions shown by density per 10 megabases, coding substitutions (colored squares: silent in gray, missense in purple, nonsense in red, and splice site in black), copy number (blue lines), regions of loss of heterozygosity (red lines), validated intrachromosomal rearrangements (green lines), and validated interchromosomal rearrangements (purple lines). (From Pleasance ED, Cheetham RK, Stephens PJ, et al. A comprehensive catalogue of somatic mutations from a human cancer genome. Nature 2010;463:191–196.) Small insertions and deletions (indels) represent a second category of somatic mutations that can be discovered by whole-genome sequencing of cancer specimens. These mutations may not only be about 10-fold less frequent than nucleotide substitutions but may also have an obvious impact in cancer progression. Accordingly, specific bioinformatic tools have been created to detect these indels in the context of the large amount of information generated by whole-genome sequencing projects.91 The systematic identification of large chromosomal rearrangements in cancer genomes represents one of the

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most successful applications of next-generation sequencing methodologies. Previous strategies in this regard had mainly been based on the utilization of cytogenetic methods for the identification of recurrent translocations in hematopoietic tumors. More recently, a combination of bioinformatics and functional methods has allowed for the finding of recurrent translocations in solid epithelial tumors such as TMPRSS2–ERG in prostate cancer and EML4–ALK in non–small-cell lung cancer (NSCLC).92,93 Now, by using a next-generation sequencing analysis of genomes and transcriptomes, it is possible to systematically search for both intrachromosomal and interchromosomal rearrangements occurring in cancer specimens. These studies have already proven their usefulness for cancer research through the discovery of recurrent translocations involving genes of the RAF kinase pathway in prostate and gastric cancers and in melanomas.94 Likewise, massively parallel paired-end genome and transcriptome sequencing has already been used to detect new gene fusions in cancer and to catalog all major structural rearrangements present in some tumors and cancer cell lines.50,95–97 The ongoing cancer genome projects involving thousands of tumor samples will likely lead to the detection of many other chromosomal rearrangements of relevance in specific subsets of cancers. It is also remarkable that whole-genome sequencing may also facilitate the identification of other types of genomic alterations, including rearrangements of repetitive elements, such as active retrotransposons, or insertions of foreign gene sequences, such as viral genomes, which can contribute to cancer development. Indeed, a next-generation sequencing analysis of the transcriptome of Merkel cell carcinoma samples has revealed the clonal integration within the tumor genome of a previously unknown polyomavirus likely implicated in the pathogenesis of this rare but aggressive skin cancer.98 Finally, next-generation sequencing approaches have also demonstrated their feasibility to analyze the pattern of copy number alterations in cancer because they allow researchers to count the number of reads in both tumor and normal samples at any given genomic region and then to evaluate the tumor-to-normal copy number ratio at this particular region. These new methods offer some advantages when compared with those based on microarrays, including much better resolution, precise definition of the involved breakpoints, and absence of saturation, which facilitates the accurate estimation of high copy number levels occurring in some genomic loci of malignant tumors.47

PATHWAY-ORIENTED MODELS OF CANCER GENOME ANALYSIS Genomewide mutational analyses suggest that the mutational landscape of cancer is made up of a handful of genes that are mutated in a high fraction of tumors, otherwise known as mountains, and most mutated genes are altered at relatively low frequencies, otherwise known as hills (Fig. 1.7).28 The mountains probably give a high selective advantage to the mutated cell, and the hills might provide a lower advantage, making it hard to distinguish them from passenger mutations. Because the hills differ between cancer types, it seems that the cancer genome is more complex and heterogeneous than anticipated. Although highly heterogeneous, bioinformatic studies suggest that the mountains and hills can be grouped into sets of pathways and biologic processes. Some of these pathways are affected by mutations in a few pathway members and others by numerous members. For example, pathway analyses have allowed for the stratification of mutated genes in pancreatic adenocarcinomas to 12 core pathways that have at least 1 member mutated in 67% to 100% of the tumors analyzed (Fig. 1.8).32 These core pathways deviated to some that harbored one single highly mutated gene, such as in KRAS in the G1/S cell cycle transition pathway and pathways where a few mutated genes were found, such as the transforming growth factor signaling pathway. Finally, there were pathways in which many different genes were mutated, such as invasion regulation molecules, cell adhesion molecules, and integrin signaling. Importantly, independent of how many genes in the same pathway are affected, if they are found to occur in a mutually exclusive fashion in a single tumor, they most likely give the same selective pressure for clonal expansion. The idea of genetically analyzing pathways rather than individual genes has been applied previously, revealing the concept of mutual exclusivity. Mutual exclusivity has been shown elegantly in the case of KRAS and BRAF, where a KRAS-mutated cancer generally does not also harbor a BRAF mutation because KRAS is upstream of BRAF in the same pathway.9 A similar concept was applied for PIK3CA and PTEN, where both mutations do not usually occur in the same tumor.22

Passenger and Driver Mutations By the time a cancer is diagnosed, it is composed of billions of cells carrying DNA abnormalities, some of which have a functional role in malignant proliferation; however, many genetic lesions acquired along the way have no

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functional role in tumorigenesis.14 The emerging landscapes of cancer genomes include thousands of genes that were not previously linked to tumorigenesis but are found to be somatically mutated. Many of these changes are likely to be passengers, or neutral, in that they have no functional effects on the growth of the tumor.14 Only a small fraction of the genetic alterations are expected to drive cancer evolution by giving cells a selective advantage over their neighbors. Passenger mutations occur incidentally in a cell that later or in parallel develops a driver mutation but are not ultimately pathogenic.99 Although neutral, cataloging passenger mutations is important because they incorporate the signatures of the previous exposures the cancer cell underwent as well as DNA repair defects the cancer cell has. In many cases, the passenger and driver mutations occur at similar frequencies, and the identification of drivers versus the passenger is of utmost relevance and remains a pressing challenge in cancer genetics.100–102 This goal will eventually be achieved through a combination of genetic and functional approaches, some of which are discussed in the following.

Figure 1.7 Cancer genome landscapes. Nonsilent somatic mutations are plotted in a twodimensional space representing chromosomal positions of RefSeq genes. The telomere of the short arm of chromosome 1 is represented in the rear left corner of the green plane, and ascending chromosomal positions continue in the direction of the arrow. Chromosomal positions that follow the front edge of the plane are continued at the back edge of the plane of the adjacent row, and chromosomes are appended end to end. Peaks indicate the 60 highest ranking CAN genes for each tumor type, with peak heights reflecting cAMP scores. The dots represent genes that were somatically mutated in the individual colorectal (Mx38) (A) or breast tumor (B3C) (B). The dots corresponding to mutated genes that coincided with hills or mountains are black with white rims; the remaining dots are white with red rims. The mountain on the right of both landscapes represents TP53 (chromosome 17), and the other mountain shared by both breast and colorectal cancers is PIK3CA (upper left, chromosome 3). (Redrawn from Wood LD, Parsons DW, Jones S, et al. The genomic landscapes of human breast and colorectal cancers. Science 2007;318:1108–1113. Reprinted with permission from the American Association for the Advancement of Science.)

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Figure 1.8 Signaling pathways and processes. A: The 12 pathways and processes whose component genes were genetically altered in most pancreatic cancers. B,C: Two pancreatic cancers (Pa14C and Pa10X) and the specific genes that are mutated in them. The positions around the circles in B and C correspond to the pathways and processes in A. Several pathway components overlapped, as illustrated by the BMPR2 mutation that presumably disrupted both the SMAD4 and hedgehog signaling pathways in Pa10X. Additionally, not all 12 processes and pathways were altered in every pancreatic cancer, as exemplified by the fact that no mutations known to affect DNA damage control were observed in Pa10X. N.O., not observed. (Redrawn from Jones S, Zhang X, Parsons DW, et al. Core signaling pathways in human pancreatic cancers revealed by global genomic analyses. Science 2008;321:1801–1806. Reprinted with permission from the American Association for the Advancement of Science.) The most reliable indicator that a gene was selected for and therefore is highly likely to be pathogenic is the identification of recurrent mutations, whether at the same exact amino acid position or in neighboring amino acid positions in different patients. More than that, if somatic alterations in the same gene occur very frequently (mountains in the tumor genome landscape), these can be confidently classified as drivers. For example, cancer alleles that are identified in multiple patients and different tumor types, such as those found in KRAS, TP53, PTEN, and PIK3CA, are clearly selected for during tumorigenesis. However, most genes discovered thus far are mutated in a relatively small fraction of tumors (hills), and it has been clearly shown that genes that are mutated in less than 1% of patients can still act as drivers.103 The systematic sequencing of newly identified putative cancer genes in the vast number of specimens from cancer patients will help in this regard. However, even if examining large numbers of samples can provide helpful information to classify drivers versus passengers, this approach alone is limited by the marked variation in mutation frequency among individual tumors and individual genes. The statistical test utilized in this case calculates the probability that the number of mutations in a given gene reflects a mutation frequency that is greater than expected from the nonfunctional background mutation rate,28,104 which is different between different cancer types. These analyses incorporate the number of somatic alterations observed, the number of tumors studied, and the number of nucleotides that were successfully sequenced and analyzed. Another approach often used to distinguish driver from passenger mutations exploits the statistical analysis of synonymous versus nonsynonymous changes.105 In contrast to nonsynonymous mutations, synonymous mutations do not alter the protein sequence. Therefore, they do not usually apply a growth advantage and would not be

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expected to be selected during tumorigenesis. This strategy works by comparing the observed-to-expected ratio of synonymous with that of nonsynonymous mutation. An increased proportion of nonsynonymous mutations from the expected 2:1 ratio implies selection pressure during tumorigenesis. Other approaches are based on the concept that driver mutations may have characteristics similar to those causing Mendelian disease when inherited in the germ line and may be identifiable by constraints on tolerated amino acid residues at the mutated positions. In contrast, passenger mutations may have characteristics more similar to those of nonsynonymous single nucleotide polymorphisms with high minor allele frequencies. Based on these premises, supervised machine learning methods have been used to predict which missense mutations are drivers.106 Additional approaches to decipher drivers from passengers include the identification of mutations that affect locations that have previously been shown to be cancer causing in protein members of the same gene family. Enrichment for mutations in evolutionarily conserved residues are analyzed by algorithms, such as sorting intolerant from tolerant (SIFT),107 which estimates the effects of the different mutations identified.

Figure 1.9 Landscape of cancer genomics analyses. Next-generation sequencing data will be generated for hundreds of tumors from all major cancer types in the near future. The integrated analysis of DNA, RNA, and methylation sequencing data will help elucidate all relevant genetic changes in cancers. (Used with permission from Ding L, Wendl MC, Koboldt DC, et al. Analysis of next-generation genomic data in cancer: accomplishments and challenges. Hum Mol Genet 2010;19:R188–R196.)

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Probably the most conclusive methods to identify driver mutations will be rigorous functional studies using biochemical assays as well as model organisms or cultured cells, using knockout and knockin of individual cancer alleles.108 A summary of the various next-generation applications and approaches for their analysis is summarized in Figure 1.9 and Table 1.2.

NETWORKS OF CANCER GENOME PROJECTS The repertoire of oncogenic mutations is extremely heterogeneous, suggesting that it would be difficult for independent cancer genome initiatives to address the generation of comprehensive catalogs of mutations in the wide spectrum of human malignancies. Accordingly, there have been different efforts to coordinate the cancer genome sequencing projects being carried out around the world, including The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC). Moreover, there are other initiatives that are more focused on specific tumors, such as that led by scientists at St. Jude Children’s Research Hospital in Memphis, and Washington University, which aims at sequencing multiple pediatric cancer genomes.109 TCGA began in 2006 in the United States as a comprehensive program in cancer genomics supported by the National Cancer Institute. The initial project focused on three tumors: GBM, serous cystadenocarcinoma of the ovary, and lung squamous carcinoma, but on the basis of initial positive results, the National Institutes of Health expanded the TCGA program with the aim to produce genomic datasets for multiple types.110 To date, TCGA has generated comprehensive maps of the key genomic changes in 33 types of cancer. The current TCGA dataset (October 2017) contains publicly available data describing tumor tissue and matched normal tissues from more than 11,000 patients. The TCGA project came to a close in 2017, but new genomics initiatives, run through the National Cancer Institute Center for Cancer Genomics, use the same model of collaboration for large-scale genomic analysis and by making the genomics data publicly available. TABLE 1.2

Computational Tools and Databases Useful for Cancer Genome Analyses Category

Tool/Database

URL

Alignment

Maqa

http://maq.sourceforge.net

Burrows-Wheeler Alignerb

http://bio-bwa.sourceforge.net

SNVMixc

http://www.bcgsc.ca/platform/bioinfo/software/SNVMix

SAMtoolsd

http://samtools.sourceforge.net

VarScane

http://varscan.sourceforge.net

MuTectf

http://www.broadinstitute.org/cancer/cga/mutect

Indel calling

Pindelg

http://gmt.genome.wustl.edu/pindel/current/

Copy number analysis

CBSh

http://www.bioconductor.org

SegSeqi

http://www.broadinstitute.org/cgibin/cancer/publications/pub_paper.cgi? mode=view&paper_id=182

SIFTj

http://sift.jcvi.org/

PolyPhen-2k

http://genetics.bwh.harvard.edu/pph2

CIRCOSl

http://mkweb.bcgsc.ca/circos

Integrative Genomics Viewerm

http://www.broadinstitute.org/igv

Catalogue of Somatic Mutations in Cancern

http://www.sanger.ac.uk/genetics/CGP/cosmic

Cancer Genome Projecto

http://www.sanger.ac.uk/genetics/CGP

dbSNPp

http://www.ncbi.nlm.nih.gov/SNP

Gene Rankerq

http://cbio.mskcc.org/tcga-generanker/

Mutation calling

Functional effect

Visualization

Repository

aLi H, Durbin R. Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics 2009;25:1754–1760. bLi H, Durbin R. Fast and accurate long-read alignment with Burrows–Wheeler transform. Bioinformatics 2010;26:589–595. cGoya R, Sun MG, Morin RD, et al. SNVMix: predicting single nucleotide variants from next-generation sequencing of tumors.

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Bioinformatics 2010;26:730–736. dLi H, Handsaker B, Wysoker A, et al. The sequence alignment/map format and SAMtools. Bioinformatics 2009;25:2078–2079. eKoboldt DC, Chen K, Wylie T, et al. VarScan: variant detection in massively parallel sequencing of individual and pooled samples. Bioinformatics 2009;25:2283–2285. fCibulski K, Lawrence MS, Carter SL, et al. Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples. Nat Biotechnol 2013;31:213–219. g Ye K, Schulz MH, Long Q, et al. Pindel: a pattern growth approach to detect break points of large deletions and medium sized insertions from paired-end short reads. Bioinformatics 2009;25:2865–2871. hVenkatraman ES, Olshen AB. A faster circular binary segmentation algorithm for the analysis of array CGH data. Bioinformatics 2007;23:657–663. iChiang DY, Getz G, Jaffe DB, et al. High-resolution mapping of copy-number alterations with massively parallel sequencing. Nat Methods 2009;6:99–103. jNg PC, Henikoff S. Predicting deleterious amino acid substitutions. Genome Res 2001;11:863–874. kIdzhubei IA, Schmidt S, Peshkin L, et al. A method and server for predicting damaging missense mutations. Nat Methods 2010;7:248–249. lKrzywinski M, Schein J, Birol I, et al. Circos: an information aesthetic for comparative genomics. Genome Res 2009;19:1639–1645. mRobinson JT, Thorvaldsdóttir H, Winckler W, et al. Integrative genomics viewer. Nat Biotechnol 2011;29:24–26. n Forbes SA, Bhamra S, Dawson E, et al. The Catalogue of Somatic Mutations in Cancer (COSMIC). Curr Protoc Hum Genet 2008;chap 10. oFutreal PA, Coin L, Marshall M, et al. A census of human cancer genes. Nat Rev Cancer 2004;4:177–183. pSherry ST, Ward MH, Kholodov M, et al. dbSNP: the NCBI database of genetic variation. Nucleic Acids Res 2001;29:308–311. q The Cancer Genome Atlas Research Network. Comprehensive genomic characterization defines human glioblastoma genes and core pathways. Nature 2008;455:1061–1068. Based on Meyerson M, Stacey G, Getz G. Advances in understanding cancer genomes through second generation sequencing. Nature Rev Genet 2010;11:685–696, Table 1.2.

The ICGC was formed in 2008 to coordinate the generation of comprehensive catalogs of genomic abnormalities in tumors from 50 different cancer types or subtypes that are of clinical and societal importance across the world.111 The project aims to perform systematic studies of over 25,000 cancer genomes at the genomic level and integrate this information with epigenomic and transcriptomic studies of the same cases as well as with clinical features of patients. At present, there are a total of 89 committed projects involving at least 17 different countries coordinated by the ICGC. All of these projects deal with at least 500 samples per cancer type from cancers affecting a variety of human organs and tissues, including the blood, the brain, the breast, the esophagus, the kidneys, the liver, the oral cavity, the ovaries, the pancreas, the prostate, the skin, and the stomach.111 The last ICGC data release (v.24, 18 May 2017) comprises mutational information from more than 17,000 cancer donors spanning 76 projects and 21 different tumor sites. All of these coordinated projects have already provided new insights into the catalog of genes mutated in cancer and have unveiled specific signatures of the mutagenic mechanisms, including carcinogen exposures or DNA-repair defects, implicated in the development of different malignant tumors.73,112 Furthermore, these cancer genome studies have also contributed to define clinically relevant subtypes of tumors for prognosis and therapeutic management and in some cases have identified new targets and strategies for cancer treatment.61–63,113 The rapid technologic advances in DNA sequencing will likely drop the costs of sequencing cancer genomes to a small fraction of the current price and will allow researchers to overcome some of the current limitations of these global sequencing efforts. Hopefully, worldwide coordination of cancer genome projects, including the PanCancer initiative and the American Association for Cancer Research (AACR) Project Genomics Evidence Neoplasia Information Exchange (GENIE), with those involving large-scale, functional analyses of genes in both cellular and animal models will likely provide us with the most comprehensive collection of information generated to date about the causes and molecular mechanisms of cancer. The integration of these cancer genomic and functional data with clinical outcome data for tens of thousands of cancer patients treated at multiple institutions worldwide will set up the basis for implementing precision cancer medicine.

THE GENOMIC LANDSCAPE OF CANCERS Examining the overall distribution of the identified mutations redefined the cancer genome landscapes whereby the mountains are the handful of commonly mutated genes and the hills represent the vast majority of genes that are infrequently mutated. One of the most striking features of the tumor genomic landscape is that it involves different sets of cancer genes that are mutated in a tissue-specific fashion.114,115 To continue with the analogy, the scenery is very different if we observe a colorectal, a lung, or a breast tumor. This indicates that mutations in specific genes cause tumors at specific sites, or are associated with specific stages of development, cell differentiation, or tumorigenesis, despite many of those genes being expressed in various fetal and adult tissues.

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Moreover, different types of tumors follow specific genetic pathways in terms of the combination of genetic alterations that it must acquire. For example, no cancer outside the bowel has been shown to follow the classic genetic pathway of colorectal tumorigenesis. Additionally, KRAS mutations are almost always present in pancreatic cancers but are very rare or absent in breast cancers. Similarly, BRAF mutations are present in 60% of melanomas but are very infrequent in lung cancers.1 Another intriguing feature is that alterations in ubiquitous housekeeping genes, such as those involved in DNA repair or energy production, occur only in particular types of tumors. In addition to tissue specificity, the genomic landscape of tumors can also be associated with gender and hormonal status. For example, HER2 amplification and PIK3C2A mutations, two genetic alterations associated with breast cancer development, are correlated with the estrogen-receptor hormonal status.116 The molecular basis for the occurrence of cancer mutations in tissue- and gender-specific profiles is still largely unknown. Organspecific expression profiles and cell-specific neoplastic transformation requirements are often mentioned as possible causes for this phenomenon. Identifying tissue and gender cancer mutations patterns is relevant because it may allow for the definition of individualized therapeutic avenues.

Single-Cell Genomics Genomic analysis has provided important insights into the origin, progression, and relapse of human malignancies. However, tumors are similar to complex organs composed of an aggregate of heterogeneous cells. Tumor heterogeneity largely derives from clonal evolution, a multistep process by which random mutations create genetic and epigenetic diversity that is then the subject of natural selection.117 Accordingly, the genome and epigenome of individual cells within the same tumor is unique and distinct from all the others that make up that particular tumor. Next-generation DNA sequencing has allowed identification of the most frequent mutations in the genomes of cancer patients and led to the development of personalized therapies, but this genomic approach is not sufficient to deal with the mutational diversity present in the individual and tireless adaptive cells that comprise a malignant tumor. Recent technologic advances have facilitated the whole-genome sequencing of individual cells, opening new ways to better understanding the cellular heterogeneity inherent to cancer. Pioneering studies by Navin et al.118 in human breast cancer demonstrated that it was possible to infer tumor evolution by single-cell sequencing of multiple cells from the same cancer. These proof of principle studies revealed that besides the well-characterized mutations common to most cells in a malignant tumor, there are also multiple subclonal and de novo mutations. Further single-cell sequencing studies demonstrated that distinct types of DNA alteration accumulate at different rates. Thus, large-scale DNA changes frequently occur early in cancer development, whereas point mutations are accumulated more gradually, finally resulting in the outstanding subclonal diversity found in human malignancies.119 A number of techniques for single-cell genomic analysis, also including single-cell RNA-seq and single-cell epigenomics to characterize the transcriptome and epigenome of individual cancer cells, have now been developed. The strategies underlying these methods are based on the development of methods to isolate individual cells preserving their biologic integrity and then to capture and amplify DNA and RNA from these single cells. Methods to capture both DNA and RNA from the same individual cells have also been developed, facilitating studies to link genotype and phenotype of cancer cells. Likewise, the combination of single-cell genomics with high-throughput experimental perturbations—such as clustered regularly interspaced short palindromic repeats (CRISPR)–based methods—has enabled causal inferences in cancer research to be established at an unprecedented level of resolution.120 These emerging techniques have already provided innovative insights in multiple aspects of cancer pathogenesis such as intratumor heterogeneity, cell of origin, reconstruction of phylogenetic lineages, cell plasticity, clonal evolution, and mechanisms of metastasis.121 Nevertheless, these studies are still hampered by the high cost of single-cell genomics, the errors that arise during the whole-genome or transcriptome amplification requested for individual cell sequencing analysis, and the complexities of the computational methods necessary for handling the massive information derived from single-cell sequence data. The ongoing progress to address these current limitations will likely determine that single-cell genomics is central to precisely define the complex evolutionary trajectories of human cancers and illuminate new clinical strategies for their effective control. Singlecell genomics will also likely shed light on the mechanisms of primary and secondary drug resistance that presently restrict the effectiveness of targeted and immune therapies.

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INTEGRATIVE ANALYSIS OF CANCER GENOMICS The implementation of novel high-throughput technologies is generating an extraordinary amount of information on cancer samples. Accordingly, there is a growing need to integrate genomic, epigenomic, transcriptomic, and proteomic landscapes from tumor samples and then linking this integrated information with clinical outcomes of cancer patients. There are some examples of human malignancies in which this integrative approach has been already performed, such as for AML; glioblastoma; medulloblastoma; and renal cell, colorectal, ovarian, endometrial, prostate, and breast carcinomas,122–129 improving the molecular classification of complex and heterogeneous tumors. These integrative molecular analyses have also provided new insights into the mechanisms disrupted in each particular cancer type or subtype and have facilitated the association of genomic information with distinct clinical parameters of cancer patients and the discovery of novel therapeutic targets.130 Also in this regard, there has been significant progress in the definition of the mechanisms by which the cancer genome and epigenome influence each other and cooperate to facilitate malignant transformation.131,132 Moreover, mutations in epigenetic regulators, such as DNA methyltransferases, chromatin remodelers, histones, and histone modifiers, are very frequent events in many tumors, including hepatocellular carcinomas, renal carcinomas leukemias, lymphomas, glioblastomas, and medulloblastomas. These genetic alterations of epigenetic modulators cause widespread transcriptomic changes, thereby amplifying the initial effect of the mutational event at the cancer genome level.132 TABLE 1.3

Useful Information for the Description and Management of Cancer Bioinformatic Tool or Webservices

Database Used

Webservice or Tool

Upload of Data Possible

Gene Search

Chromosomal Region Search

mRNA Expression

SNV

CNV

Methylation

miRNA Expression

cBioPortal for Cancer Genomics

TCGA

Webservice

—

✓

—

✓

✓

✓

—

—

PARADIGM, Broad GDAC Firehose

TCGA

Webservice

✓

✓

—

✓

✓

✓

✓

—

WashU Epigenome Browser

ENCODE

Webservice

✓

✓

✓

✓

✓

✓

✓

—

UCSC Cancer Genomics Browser

UCSC

Webservice

✓

✓

✓

✓

✓

✓

✓

✓

The Cancer Genome Workbench

TCGA

Webservice

—

✓

✓

✓

✓

✓

✓

—

EpiExplorer

ENCODE and ROADMAP

Webservice

✓

✓

✓

✓

✓

✓

✓

—

EpiGRAPH

ENCODE

Webservice

✓

✓

✓

✓

✓

✓

✓

—

Catalogue of Somatic Mutations in Cancer (COSMIC)

TCGA and ICGC

Webservice

—

✓

—

—

✓

✓

—

—

PCmtl, MAGIA, miRvar, CoMeTa, etc.a

GEO and TCGA

Webservice

✓

✓

—

✓

—

—

—

✓

ICGC

ICGC

Webservice

—

✓

—

✓

✓

✓

—

—

Genomatix

User defined

Tool

—

✓

—

✓

✓

✓

✓

—

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Caleydo

TCGA

Tool

—

✓

✓

✓

✓

✓

✓

✓

Integrative Genomics Viewer

ENCODE

Tool

—

✓

✓

✓

✓

✓

✓

—

iCluster and iCluster Plus

User defined

Tool

—

✓

—

✓

—

✓

—

—

aWeb site with links for integrated analysis of microRNA (miRNA) and messenger RNA (mRNA) expression.

SNV, single-nucleotide variation; CNV, copy-number variation; TCGA, The Cancer Genome Atlas; GDAC, Genomic Data Analysis Center; WashU, Washington University; ENCODE, Encyclopedia of DNA Elements; USCS, University of California, Santa Cruz; ICGC, International Cancer Genome Consortium; MAGIA, miRNA and Genes Integrated Analysis; CoMeTa, Co-expression Metaanalysis of miRNA Targets; GEO, Gene Expression Omnibus. Based on Plass C, Pfister SM, Lindroth AM, et al. Mutations in regulators of the epigenome and their connections to global chromatin patterns in cancer. Nat Rev Genet 2013;14:765–780, Table 1.1.

The recent availability of different platforms for integrative cancer genome analyses will be very helpful in enabling the classification, biologic characterization, and personalized clinical management of human cancers (Table 1.3).131,133

IMMUNOGENOMICS Immunotherapy, such as checkpoint inhibitors and adoptive T-cell therapy, has shown remarkable clinical effects in a wide range of tumor types. However, as many tumors do not respond to these treatments and the determinants of treatment efficacy are largely unknown, a new field of research was launched, namely, cancer immunogenomics. As tumor therapy is advancing toward a personalized approach, in which each patient will be given “tailor made” therapy according to his or her mutational landscape and neoantigen repertoire, it is essential to better understand how the patient can benefit from immunotherapy; thus, identification of specific biomarkers for stratification of patients to immunotherapy is likely to increase treatment response rates (Fig. 1.10).134 The query for tumor neoantigens as therapeutic approach, and investigation on how neoantigens interact with checkpoint blockade, had been in the focus of cancer immunology for the past decade.135–137 Tumor neoantigens are antigens that are unique to the patient’s cancer cells and are presented on the tumor cells human leukocyte antigen (HLA) molecules. They are derived from patient-specific nonsynonymous mutations as well as indels in the cancer cells,138,139 which are unique from patient to patient. Neoantigen-specific T cells can be found in both the tumor140 and the circulation of patients141,142 and healthy donors.143 These have been shown to be highly potent in eliminating tumors by both adoptive transfer144 or using vaccinations that increase their abundance.145,146 Interestingly, neoantigens are usually considered to activate CD8+ T cells, but neoantigens which are recognized by CD4+ T cells were reported as well.147 Neoantigens can be identified using numerous methods.148 The initial step involves whole-exome or wholegenome sequencing to identify patient-specific nonsynonymous mutations.149 The bottleneck remains in deciphering neoantigens from the sequencing data. In recent years, a plethora of computational tools have been generated in order to predict which neoantigens bind the HLAs expressed on the surface of tumor cells in sufficient affinity (reviewed in Hackl et al.150). However, as these technologies are laborious and inaccurate, alternative techniques such as HLA peptidomics are now also in use.151 Regardless of the technique used, for each patient, the literature describes a very restricted number of validated, rather than predicted, neoantigens (between zero and five), which does not correlate with mutational load.141,142,144,149,152 However, it was suggested148 and recently shown in patients153 that it is the quality, or the “foreignness,” of the neoantigen manifested by its homology to antigens derived from infectious diseases, rather than the actual number of the neoantigens, that predict patient survival.

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Figure 1.10 Representation of the immune state within tumors, manifested by various aspects of immunogenomics. Desirable states are located in blue; undesirable states are shown in red gradient. MHC, major histocompatibility complex; IFN-γ, interferon-γ; LDH, lactate dehydrogenase; IL-6, interleukin-6; CRP, C-reactive protein; PD-L1, programmed cell death protein ligand 1. (Adapted from Blank CU, Haanen JB, Ribas A, et al. Cancer immunology. The “cancer immunogram.” Science 2016;352[6286]:658–660.) A complementary approach in cancer immunogenomics is the evaluation of the immune status of the tumor, in order to predict the patient’s survival and potential benefit from therapy, using computational methods. Several such algorithms were developed to decipher the immune cell composition within tumors using transcriptomics.150 Some algorithms, such as the Cell type Identification By Estimating Relative Subsets Of known RNA Transcripts (CIBERSORT154), can be used effectively to characterize the immune composition of tumors in a quantitative manner comparable to that of immunohistochemistry or flow cytometry.155 Other approaches, such as the definition of cytolytic activity by combining the transcript levels of granzyme A and perforin,156 use of single-cell RNA sequencing for immune profiling,157 or sequencing of the T-cell receptor repertoire as a measure of T-cell diversity versus clonality,158 can also provide an insight of the immune state of the tumor. The intersection between immunogenomics, cancer genomics, and immunotherapy has led to a key question in the field concerning the correlation of mutational load and response to immunotherapy. The current hypothesis in the immunotherapy field is that tumors with increased mutational load will present more neoantigens and thus will be more immunogenic.139,159 Accordingly, patients who respond to checkpoint blockade therapy are often characterized with a high mutational load.160,161 Another example is CRC, which is known to be refractory to immunotherapy for most patients,162 with some clinical benefit demonstrated only in a minority of patients with high mutational load due to mutations in the mismatch repair genes.163 Indeed, it was recently reported that mismatch repair defect can predict better response to immunotherapies in other cancer types as well.164 However, other reports undermine the correlation between mutational load and response to immunotherapy.165,166 In addition, low tumor heterogeneity was also shown to predict response for checkpoint blockade,158,167 and melanoma patients who respond to programmed cell death protein 1 (PD-1) blockade exhibit enriched mutation toward BCRA1.166 These observations and their interpretations are currently under heated debate, and their understanding would be instrumental for future patient selection.

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Finally, immunogenomic studies have delineated mechanisms of tumor evasion from elimination by the immune system. One such mechanism is disruption of the antigen presentation machinery. This can be achieved by acquired mutations of the HLA component β2M168,169 or loss of the HLA alleles.170 An alternative escape mechanism is disruption of the interferon-γ signaling pathway, which upregulates HLA surface expression on tumor cells and which is manifested by mutations in genes along the pathway, such as the kinases Janus kinase 1 (JAK1) and JAK2 or the downstream transcription factor STAT1.171–173 On the other hand, interferon-γ can activate other tumor escape mechanisms, such as the upregulation of checkpoint inhibitor molecules on tumor cell surface, including programmed cell death protein ligand 1 (PD-L1).174 Tumors can also immunoedit neoantigens and downregulate their expression in the RNA level or delete the mutant alleles in the DNA level.175,176 In the future, unbiased genomic screens that use the CRISPR-CAS9 whole-genome screen may uncover new such mechanism, as was shown in tumor mouse models.177

THE CANCER GENOME AND THE NEW TAXONOMY OF TUMORS Deciphering the cancer genome has already impacted clinical practice at multiple levels. On the one hand, it allowed for the identification of new cancer genes such as IDH1, a gene involved in glioma, which was discovered recently (see the previous section), and on the other hand, it is redesigning the taxonomy of tumors. Until the genomic revolution, tumors had been classified based on two criteria: their localization (site of occurrence) and their appearance (histology). These criteria are also currently used as primary determinants of prognosis and to establish the best treatments. For many decades, it has been known that patients with histologically similar tumors have different clinical outcomes. Furthermore, tumors that cannot be distinguished based on histologic analysis can respond very differently to identical therapies.178 It is becoming increasingly clear that the frequency and distribution of mutations affecting cancer genes can be used to redefine the histology-based taxonomy of a given tumor type. Lung and colorectal tumors represent paradigmatic examples. Genomic analyses led to the identification of activating mutations in the receptor tyrosine kinase EGFR in lung adenocarcinomas.179 The occurrence of EGFR mutations molecularly defines a subtype of NSCLCs that occur mainly in nonsmoking women, that tend to have a distinctly enhanced prognosis, and that typically respond to epidermal growth factor receptor (EGFR)–targeted therapies.180–182 Similarly, the recent discovery of the EML4-ALK fusion identifies yet another subset of NSCLC that is clearly distinct from those that harbor EGFR mutations, that have distinct epidemiologic and biologic features, and that respond to ALK inhibitors.93,183 The second example is CRCs, the tumor type for which the genomic landscape has been refined with the highest accuracy. CRCs can be clearly categorized according to the mutational profile of the genes involved in the KRAS pathway (Fig. 1.11). It is now known that KRAS mutations occur in approximately 40% of CRCs. Another subtype of CRC (approximately 10%) harbors mutations in BRAF, the immediate downstream effectors of KRAS.10 Of note, KRAS and BRAF mutations have been recently shown to impair responsiveness to the anti-EGFR monoclonal antibodies therapies in CRC patients.184–186 Clearly distinct subgroups can be genetically identified in both NSCLCs and CRCs with respect to prognosis and response to therapy. It is likely that as soon as the genomic landscapes of other tumor types are defined, molecular subgroups like those described previously will also become defined.

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Figure 1.11 Graphic representation of a cohort of 100 patients with colorectal cancer treated with cetuximab or panitumumab. The genetic milieu of individual tumors and their impacts on the clinical response are listed. KRAS, BRAF, and PIK3CA somatic mutations as well as loss of PTEN protein expression are indicated according to different color codes. Molecular alterations mutually exclusive or coexisting in individual tumors are indicated using different color variants. The relative frequencies at which the molecular alterations occur in colorectal cancers are described. (Redrawn from Bardelli A, Siena S. Molecular mechanisms of resistance to cetuximab and panitumumab in colorectal cancer. J Clin Oncol 2010;28:1254–1261.) Genotyping tumor tissue in search of somatic genetic alterations for actionable information has become routine practice in clinical oncology. The genetic profile of solid tumors is currently obtained from surgical or biopsy specimens. As the techniques that have enabled us to analyze tumor tissues become ever more sophisticated, we have realized the limitations of this approach. As previously discussed, cancers are heterogeneous, with different areas of the same tumor showing different genetic profiles (i.e., intratumoral heterogeneity); likewise, heterogeneity exists between metastases within the same patient (i.e., intermetastatic heterogeneity).187 A tissue section (or a biopsy) from one part of a solitary tumor will miss the molecular intratumoral as well as intermetastatic heterogeneity. To capture tumor heterogeneity, techniques that are capable of interrogating the genetic landscapes of the overall disease in a single patient are needed.

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Liquid Biopsies as a Diagnosis Tool In 1948, the publication of a manuscript describing the presence of cell-free circulating DNA (cfDNA) in the blood of humans offered—probably without realizing it—unprecedented opportunities in this area.188 Only recently, the full potential of this seminal discovery has been appreciated. Several groups have reported that the analysis of circulating tumor DNA can, in principle, provide the same genetic information obtained from tumor tissue. The levels of cfDNA are typically higher in cancer patients than healthy individuals, indicating that it is possible to screen for the presence of disease through a simple blood test. Furthermore, the specific detection of tumor-derived cfDNA has been shown to correlate with tumor burden, which changes in response to treatment or surgery.189–191 Although the detection of circulating free tumor DNA (ctDNA) has remarkable potential, it is also challenging for several reasons. The first is the need to discriminate DNA released from tumor cells (ctDNA) from circulating normal DNA. Discerning ctDNA from normal cfDNA is aided by the fact that tumor DNA is defined by the presence of mutations. These somatic mutations, commonly single base pair substitutions, are present only in the genomes of cancer cells or precancerous cells and are present in the DNA of normal cells of the same individual. Accordingly, ctDNA offers exquisite specificity as a biomarker. Unfortunately, cfDNA derived from tumor cells often represents a very small fraction (50 chromosomes) showing a distinctly more favorable course compared with hypodiploid or near diploid cases.9 Detection of gene amplification also has utility in prognostication. For example, MYCN amplification occurs in approximately 40% of undifferentiated or poorly differentiated neuroblastoma subtypes10,11 either appearing as double minute chromosomes or homogeneously staining regions. MYCN amplification is a very strong predictor of poor outcomes particularly in patients with localized (stage 1 or stage 2) disease or in infants with stage 4S metastatic disease, where fewer than half of patients survive beyond 5 years.12

Use of Biomarkers in Predicting Response to Therapy Molecular diagnostics is rapidly playing an increasing role in guiding therapy or “theranostics.” One of the earliest advances was the recognition that AML with PML-RARA translocation is highly sensitive to all-trans retinoic acid, whereas other AMLs are not. With the advent of NGS, an increasing number of mutations in oncogenes (and tumor suppressor genes) are being identified that have therapeutic significance (see Table 2.1). Molecular diagnostics is also playing an increasing role in immunotherapy. Antibody-based therapies directed against immune checkpoint effectors programmed cell death protein ligand 1 receptor (PD-L1), programmed cell death protein 1 (PD-1) and cytotoxic T-lymphocyte antigen 4 (CTLA-4) are transforming treatment of tumors such as melanoma and lung cancer. Companion diagnostics tests to assess the level of PD-L1 protein expression are available to select patients who are candidates for therapy. However, PD-L1 is expressed not only on the tumor cells but also on tumor-infiltrating immune cells as well as stromal cells. This has generated considerable discussion and controversy over which biomarkers best predict responsiveness to immunotherapy. As will be discussed further, cutoffs based on percentage staining of the tumor, and in some cases, stromal cells, differ between the various companion diagnostics.13,14 Molecular assessment of the host is also beginning to play a role in adjusting dosing and in predicting toxicity, for example, in identifying fast versus slow thiopurine metabolizers using polymorphisms in the thiopurine methyltransferase gene in patients receiving thiopurine drugs.15

Use of Biomarkers in Therapeutic Disease Monitoring Molecular diagnostics plays a major role in therapeutic monitoring. Detection of chromosomal translocations and other rearrangements using cytogenetics, FISH, PCR, and to an increasing extent NGS is used to monitor for minimal residual disease in AML, ALL, and CML. Quantification of these biomarker levels have important prognostic and therapeutic implications. For example, serial monitoring of BCR-ABL1 mRNA levels by quantitative PCR is a mainstay of CML management. Detection of sequence-level mutations can be important during monitoring for evaluation of chemotherapy resistance. Roughly a third of CML patients are resistant to the frontline ABL1 kinase inhibitor imatinib, either at the time of initial treatment or more commonly secondarily. In cases of primary failure or secondary failure, over 100 different ABL1 mutations have been identified, including particularly common ones such as T315I and P loop mutations. Whereas some mutations such as Y253H respond to second-generation tyrosine kinase inhibitors (TKIs), others, such as the T315I mutation, are noteworthy because they confer resistance not only to imatinib but also to nilotinib and dasatinib.

Use of Biomarkers in Risk Assessment and Cancer Prevention Molecular diagnostics is playing an increasing role in the evaluation and management of patients at increased risk of developing cancer (Table 2.1). Detection of germline mutations and copy number variation involving tumor suppressor genes can be helpful for the management of patients with a strong family history of cancer. One notable example is the use of BRCA1 and BRCA2 mutation analysis for women with a strong family history of breast cancer. Over 200 mutations (small nucleotide-level mutations and large deletions/duplications) occur in BRCA genes, which are distributed across the genes necessitating full sequencing and additional methods for their detection. These occur at an overall prevalence of about 0.1% in the general population.16,17 The lifetime risk of breast cancer for women carrying BRCA1 mutations is in the range of 47% to 66%, whereas for BRCA2 mutations, it is in the range of 40% to 57%,18,19 and in addition, the risk of other tumors including ovarian, fallopian, and pancreatic cancer is also increased.

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THE CLINICAL MOLECULAR DIAGNOSTICS LABORATORY: RULES AND REGULATIONS Laboratories in the United States that perform molecular diagnostic testing are categorized as high-complexity laboratories under the Clinical Laboratory Improvement Amendments of 1988 (CLIA).20 The CLIA program sets the minimum administrative and technical standards that must be met in order to ensure quality laboratory testing. Most laboratories in the United States that perform clinical testing in humans are regulated under CLIA. CLIAcertified laboratories must be accredited and regularly inspected by professional organizations such as The Joint Commission, the College of American Pathologists, or another agency officially approved by the Centers for Medicare & Medicaid Services (CMS) and must comply with CLIA standards and guidelines for quality assurance. Although the regulation of laboratory services is in the jurisdiction of the U.S. Food and Drug Administration (FDA), the FDA has historically exercised enforcement discretion. Therefore, FDA approval is not currently required for clinical implementation of molecular tests as long as other regulations are met.25,26

SPECIMEN REQUIREMENTS FOR MOLECULAR DIAGNOSTICS Samples typically received for molecular oncology testing include blood, bone marrow aspirates and biopsies, fluids, organ-specific fresh tissues in saline or tissue culture media such as Roswell Park Memorial Institute (RPMI), FFPE tissues, and cytology cell blocks. Molecular tests can be ordered electronically or through written requisition forms but never through verbal requests only. All samples submitted for molecular testing need to be appropriately identified. Sample type, quantity, and specimen handling and transport requirements should conform to the laboratory’s stated requirements in order to ensure valid test results. Blood and bone marrow samples should be drawn into anticoagulated tubes. The preferred anticoagulant for most molecular assays is ethylenediaminetetraacetic acid (lavender). Other acceptable collection tubes include ACD (yellow) solutions A and B. Heparinized tubes are not preferred for most molecular tests because heparin inhibits the polymerase enzyme utilized in PCR, which may lead to assay failure. Blood and bone marrow samples can be transported at ambient temperature. Blood samples should never be frozen prior to separation of cellular elements because this causes hemolysis, which interferes with DNA amplification. Fluids should be transported on ice. Tissues should be frozen (preferred method) as soon as possible and sent on dry ice to minimize degradation. Fresh tissues in RPMI should be sent on ice or cold packs. Cells should be kept frozen and sent on dry ice; DNA samples can be sent at ambient temperature or on ice. For FFPE tissue blocks, typical collection and handling procedures include cutting 4 to 10 microtome sections of 5- to 10-μm thickness each on uncoated slides, air-drying unstained sections at room temperature, and staining one of the slides with hematoxylin and eosin. Because tumor specimens are never pure, a strategy to ensure the sensitivity of the molecular assays is to only test areas of the tissue block that contain a sufficiently high quantity and proportion of neoplastic cells. Therefore, before any molecular test is conducted, the hematoxylin and eosin slide from the specimen in question is reviewed by an anatomic/molecular pathology-trained, board-certified pathologist at a light microscope for assessment of sample cellularity, tumor cell content, and selection of tumorrich areas that will be used to guide macro- or microdissection of the adjacent, unstained slides. The pathologist also provides an estimate of the percentage of neoplastic cells in the area that will be tested, which should exceed the established limit of detection of the assay. Ensuring that a sufficient proportion of tumor DNA is input into the assay, which is crucial for the accuracy of molecular test results.

MOLECULAR DIAGNOSTICS TESTING PROCESS The workflow of a molecular test begins with receipt and accessioning of the specimen in the clinical molecular diagnostics laboratory followed by extraction of the nucleic acid (DNA or RNA), test setup, detection of analyte (e.g., PCR products), data analysis, and result reporting to the patient medical record (Fig. 2.3). Extraction of intact, moderately high-quality DNA is essential for molecular assays. For DNA extraction, preferred age for blood, bone marrow, and fluid samples is fewer than 5 days; for frozen or fixed tissue, it is indefinite; and for fresh tissue, it is overnight. Although there is no age limit for the use of a fixed and embedded tissue specimen for analysis, older specimens may yield a lower quantity and quality of DNA. Because RNA is significantly more labile than DNA, the preferred age for blood and bone marrow is fewer than 48 hours (from

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time of collection). Tissue samples intended for RNA analysis should be promptly processed in fresh state, snap frozen, or preserved with RNA stabilizing agents for transport. Following nucleic acid extraction, the assay is set up according to written procedures established during validation/verification of the assay by qualified laboratory staff. Dedicated areas, equipment, and materials are designated for various stages of the test (e.g., extraction, pre-PCR, and post-PCR for amplification-based assays). For each molecular oncology test, appropriated positive and negative control specimens are included in each run as a matter of routine quality assessment. A no template (blank) control, containing the complete reaction mixture except for nucleic acids, is also included in amplification-based assays to evaluate for amplicon contamination in the assay reagents that may lead to inaccurate results. The controls are processed in the same manner as patient samples to ensure that established performance characteristics are being met for each step of the assay (extraction, amplification, and detection). All assay controls and overall performance of the run are examined prior to interpretation of sample results. Following acceptance of the controls, results are electronically entered into reports. The final report is reviewed and signed to the electronic medical record by the laboratory director or a qualified designee who meets the same qualifications as the director, as defined by CLIA (see previous discussion).

Figure 2.3 Simplified workflow of clinical molecular diagnostic testing. PCR, polymerase chain

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reaction

TARGETED MUTATION ANALYSIS METHODS Several traditional and emerging techniques are currently available for mutation detection in cancer (Table 2.2). In this era of personalized medicine, molecular oncology assays are rapidly moving from mutational analysis of single genes toward multigene panel analysis. As the number of “actionable” mutations such as ALK, EGFR, BRAF, and others increase, and the cost of sequencing continues to drop, the use of NGS platforms is becoming much more widespread. Both traditional and emerging testing approaches have advantages and disadvantages that need to be balanced before a test platform is implemented into practice. An important consideration when adding a new oncology test in the clinical laboratory menu is to define the intended use of the assay (e.g., diagnosis, prognosis, prediction of therapy response). The clinical utility of the assay, appropriate types of specimens, spectrum of possible mutations, and available methods for testing should also be determined. The laboratory director and ordering physicians should also discuss the estimated test volume, optimal reporting format, and required turnaround time for the proposed new test.21–23

Polymerase Chain Reaction PCR24,25 is widely used in all molecular diagnostics laboratories for rapid amplification of targeted DNA sequences. The reaction includes the specimen template DNA, forward and reverse primers (18 to 24 oligonucleotides long) that define the amplification region, Taq DNA polymerase, and each of the four nucleotides bases (dATP, dTTP, dCTP, dGTP). During PCR, selected genomic sequences undergo repetitive temperature cycling (sequential heat and cooling) that allows for denaturation of double-stranded DNA template, annealing of the primers to the targeted complementary sequences on the template, and extension of new strands of DNA by Taq polymerase from nucleotides, using the primers as the starting point. Each cycle doubles the copy number of PCR templates for the next round of polymerase activity, resulting in an exponential amplification of the selected target sequence. The PCR products (amplicons) are detected by electrophoresis, in real-time systems simultaneously to the amplification reaction (see real-time PCR in the following text), or by sequencing. PCR is specifically designed to work on DNA templates because the Taq polymerase does not recognize RNA as a starting material. Nonetheless, PCR can be adapted to RNA testing by including a reverse-transcription step to convert a RNA sequence into its cognate cDNA sequence before the PCR reaction is performed (see reversetranscription PCR in the following text). Multiplex PCR reactions can also be designed with multiple primers for simultaneous amplification of multiple genomic targets. PCR is a highly sensitive and specific technique that can be employed in different capacities for detection of point mutations, small deletions, insertions and duplications, as well as gene rearrangements and clonality assessment. Limits of detection can reach 0.1% mutant allele or lower, which is important for detection of somatic mutations in oncology because tumor specimens are usually composed of a mixture of tumor and normal cells. Some PCR assay formats include the use of chemically modified blocking oligonucleotides (e.g., peptide nucleic acid, locked nucleic acid) or lower denaturation temperature that impedes the amplification of wild-type sequences, thereby increasing the assay sensitivity to detect low-level mutant alleles. This approach is particularly useful for detection of clinically relevant mutated subclones and for monitoring of treatment response or disease relapse. Reverse-transcription PCR (RT-PCR) can also be used for relative quantification of target RNA in minimal residual disease testing, such as BCR-ABL1 transcripts in CML. Another advantage of PCR is its ability to amplify small amounts of low-quality FFPEderived DNA. However, applications of PCR can be limited as it cannot amplify across large or highly repetitive genomic regions. Also, the PCR reaction can be inhibited by heparin or melanin if present in the extracted DNA, which may lead to assay failure. Finally, the risk of false-positives due to specimen or amplicon contamination is an important issue when using PCR-based techniques; therefore, stringent laboratory procedures, as described above, are used to minimize contamination. With the exception of hybridization assays, such as FISH and genomic microarrays, PCR is the necessary initial step in all current molecular oncology assays.

Real-time Polymerase Chain Reaction In real-time PCR, the PCR is performed with a PCR reporter that is usually a fluorescent double-stranded DNAbinding dye or a fluorescent reporter probe. The intensity of the fluorescence produced at each amplification cycle is monitored in real-time, and both quantification and detection of targeted sequences is accomplished in the

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reaction tube as the PCR amplification proceeds. The intensity of the fluorescent signal for a given DNA fragment (wild type or mutant) is correlated with its quantity, based on the PCR cycle in which the fluorescence rises above background (crossing threshold [Ct] or crossing point [Cp]).26 The Ct value can be used for qualitative or quantitative analysis. Qualitative assays use the Ct as a cutoff for determining “presence” or “absence” of a given target in the reaction. Qualitative analysis by real-time PCR is particularly useful for targeted detection of point mutations that are located in mutational hotspots. Examples include the JAK2 V617F mutation, which is located within exon 14 and is found in several myeloproliferative neoplasms (polycythemia vera, essential thrombocythemia, and primary myelofibrosis),27 and the BRAF V600E mutation,28 which is located within exon 15 and is found in various cancer types including melanoma and thyroid and lung cancer. For quantitative analysis, the Ct of standards with known template concentration is used to generate a standard curve to which Ct values of unknown samples are compared to. The concentration of the unknown samples is then extrapolated from values from the standard curve. The quantity of amplicons produced in a PCR is proportional to the prevalence of the targeted sequence; therefore, samples with higher template concentration reaches the Ct at earlier PCR cycles than one with low concentration of the amplified target. Quantitative real-time PCR has high analytical sensitivity for detection of low mutant allele burden. For that reason, this method has been widely utilized for monitoring of minimal residual disease.

Reverse-Transcription Polymerase Chain Reaction RT-PCR is utilized for detection and quantification of RNA transcripts. The first step for all PCR assays that use RNA as a starting material is reverse transcription of RNA into cDNA because RNA is not a suitable substrate for Taq polymerase. In RT-PCR, RNA is isolated and reverse transcribed into cDNA by using a reverse transcriptase enzyme and either (1) random hexamer primers, which anneal randomly to RNA and reverse transcribe all RNA in the cell; (2) oligo dT primers, which anneal to the polyA tail of mRNA and reverse transcribe only mRNA; or (3) gene-specific primers that reverse transcribe only the target of interest. PCR is subsequently performed on the cDNA with forward and reverse primers specific to the gene(s) of interest as in a standard PCR. TABLE 2.2

Molecular Methods in Oncology Analytic Sensitivity

Examples of Applications in Oncology

Detects only specific targeted mutations/chromosomal translocations Not suitable for variable mutations May not determine the exact change in nucleotide sequence

Very high

KRAS, BRAF, and EGFR mutations in solid tumors JAK2, V617F, and MPL mutations in myeloproliferative neoplasms KIT D816V mutation in systemic mastocytosis and AML Quantitation of BCR-ABL1 and PML-RARA transcripts for residual disease monitoring in CML and APL, respectively

Does not determine the exact change in nucleotide sequence Does not detect single nucleotide substitution mutations Limited multiplex capability

High

NPM1 insertion mutations in AML FLT3 internal tandem duplications in AML JAK2 exon 12 insertions and deletions in PV EGFR exon 19 deletions in NSCLC

Method

Advantages

Disadvantages

Real-time PCR Allele-specific PCR Reverse transcription PCR

Flexible platforms that permit detection of a variety of conserved hotspot mutations including nucleotide substitutions, small length mutations (deletions, insertions), and translocations High sensitivity is beneficial for residual disease testing and specimens with limited tumor content Adaptable to quantitative assays

Fragment analysis

Detects small to medium insertions and deletions Detects variable insertions and deletions regardless of specific alteration Provides semiquantitative information regarding

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mutation level FISH

Detects chromosomal translocation, gene amplification, and deletion Morphology of tumor is preserved, allowing for a more accurate interpretation of heterogeneous samples For the quantitative assessment of gene amplification, FISH provides information about copy number assessment of polysomy, which is not possible with PCRbased methods

High cost Unable to detect small insertions and deletions Limited multiplex capability Does not determine the exact breakpoint and change in nucleotide sequence

High

IGH/BCL2 translocation detection in follicular lymphoma and in a subset of diffuse large B-cell lymphoma ALK translocation in NSCLC EWSR1 translocation in soft tissue tumors HER2 amplification in breast cancer 1p/19q deletion in oligodendroglioma

Sanger sequencing

Detects variable single nucleotide substitutions and small insertions and deletions Provides semiquantitative information about mutation level

Low throughput Low analytic sensitivity limits application in specimens with low tumor burden Does not detect copy number changes or large (>500 bp) insertions and deletions

Low

KIT mutations in gastrointestinal stromal tumor and melanoma CEBPA mutations in AML EGFR mutations in NSCLC

Pyrosequencing

Higher analytical sensitivity than Sanger sequencing Detects variable single nucleotide substitutions and small insertions and deletions Provides quantitative information about mutation level

Short read lengths limit analysis to mutational hotspots Low throughput

Medium

KRAS and BRAF mutations in solid tumors

Next-generation sequencing

Quantitative detection of variable single nucleotide substitutions, small insertions and deletions, chromosomal translocations, and gene copy number variations Highly multiplexed High throughput

Requires costly investment in instrumentation and bioinformatics Technology is rapidly evolving Higher error rates for insertion and deletion mutations Limited ability to sequence guaninecytosine–rich regions

High

Small to large gene panels (3– 500) for solid tumor and hematologic malignancies

Genomic microarray

Simultaneous detection of copy number variation and LOH (SNP array)

Does not detect Medium Analysis of recurrent copy balanced translocations number variation and LOH in May not detect low chronic lymphocytic leukemia level mutant allele and myeloproliferative burden neoplasms PCR, polymerase chain reaction; AML, acute myelogenous leukemia; CML, chronic myelogenous leukemia; APL, acute promyelocytic leukemia; PV, polycythemia vera; NSCLC, non–small-cell lung carcinoma; FISH, fluorescent in situ hybridization; LOH, loss of heterozygosity; SNP, single nucleotide polymorphism.

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Figure 2.4 Reverse-transcription polymerase chain reaction (RT-PCR) is a sensitive means to detect BCR-ABL1 fusion transcripts in chronic myeloid leukemia. RT-PCR can be combined with real-time PCR (q-PCR) to quantitate BCR-ABL transcripts across a 5 log range level. Amplification products are detected during each PCR cycle using a fluorescent probe specific to the PCR product. The accumulated fluorescence in log(10) value is plotted against the number of PCR cycles. For a given specimen, the PCR cycle number is measured when the increase in fluorescence is exponential and exceeds a threshold. This point is called the Ct, which is inversely proportional to the amount of PCR target in the specimen (i.e., lower Ct values indicate greater amount of target). Calibration standards of known quantity are used in standard curves to calculate the amount of target in a tested specimen. These are shown in the figure as different colored plots. Note that PCR increases the amount of amplification product by a factor of 2 with each PCR cycle. Therefore, specimens that produce a Ct value that is one cycle lower are expected to have a twofold higher concentration of target. Specimens that differ in target concentration by a factor of 10 (as shown) are expected to have a Ct value 3.3 cycles apart (23.3 = 10). RT-PCR is commonly used for detecting gene fusions during translocation analysis because breakpoints frequently occur within the intron of each partner gene and the precise intronic breakpoint locations may be variable. This variability complicates design of primers used in DNA-based PCR assays. RT-PCR tests are advantageous because mature mRNA has intronic sequence spliced out, allowing for simplified primer design within the affected exon of each partner gene. In this setting, RT-PCR is useful in tests where both translocation partners are recurrent and only one or a few exons are involved in each partner gene. For instance, 95% of acute promyelocytic leukemia cases harbor the reciprocal t(15;17) chromosomal translocation, and these breakpoints always occur within intron 2 of the RARA gene. By contrast, three distinct chromosome 15 breakpoints are involved, all occurring within the PML gene: intron 6, exon 6, and intron 3. Because the breakpoints in the two genes are recurrent, most of the reported PML-RARA fusions can be detected by targeting these three transcript isoforms. RT-PCR is the method of choice when high sensitivity is required to detect gene translocations. For example, PML-RARA transcript detection by RT-PCR can detect this fusion transcript down to 1 tumor cell in the background of 100,000 normal cells. Detecting low levels of fusion transcript can reveal relapse after consolidation and guide further treatment.29 RT-PCR can also be used to quantitate the amount of expression of a gene when utilized with real-time PCR for detection. One major application of RT-PCR in this setting includes

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quantitative detection of BCR-ABL1 fusion transcript for prognostication and minimal residual disease testing in CML (Fig. 2.4). In this setting, a 3 log decrease in BCR-ABL1 levels is associated with an improved outcome.30,31

Allele-Specific Polymerase Chain Reaction Allele-specific PCR (AS-PCR) is a variant of conventional PCR. The method is based on the principle that Taq polymerase is incapable of catalyzing chain elongation in the presence of a mismatch between the 3′ end of the primer and the template DNA. Selective amplification by AS-PCR is achieved by designing a forward primer that matches the mutant sequence at the 3′ end primer. A second mismatch within the primer can be introduced at the adjacent −1 or −2 position to decrease the efficiency of mismatched amplification products. This will minimize the chance of amplifying and therefore detecting the wild-type target. AS-PCR is usually performed as two PCRs: one employing a forward primer specific for the mutant sequence, the other using a forward primer specific for the correspondent wild-type sequence. In this case, a common reverse primer is used for both reactions. Following amplification, the PCR products are detected by electrophoresis (capillary or agarose gel) or in real-time PCR systems. Detection of adequate PCR product in the wild-type amplification reaction is important to control for adequate specimen quality and quantity, particularly when the specimen is negative in the mutation-specific PCR. AS-PCR is particularly useful for the detection of specific point mutations. Multiplex AS-PCR reactions can be designed for the simultaneous detection of multiple mutations by including several mutation-specific primers. The method has high analytical sensitivity and specificity and can be easily deployed in most clinical laboratories. However, an important limitation is this approach will not detect mutations other than those for which specific primers are designed. Therefore, it is utilized for highly recurrent mutations that occur at specific locations within genes, rather than for detection of variable mutations that may occur throughout a gene. Examples of AS-PCR applications in oncology include detection of JAK2 V617F and MPL mutations in myeloproliferative neoplasms (primary myelofibrosis, essential thrombocythemia, and/or polycythemia vera),32 the BRAF V600E mutation,33 and detection of KIT D816V mutations in cases of systemic mastocytosis and in AML.

Fragment Analysis Fragment analysis is a PCR amplicon sizing technique that is relevant for detection of small to medium length affecting mutations (deletions, insertions, and duplications). This is typically performed by capillary electrophoresis, which is capable of resolving length mutations from approximately 1 to 500 base pairs in size. Fragment analysis represents a practical strategy because it enables comprehensive detection of a wide variety of possible length mutations and has high analytic sensitivity. Further, it can provide semiquantitative information regarding the relative amount of mutated alleles. Limitations of this approach include the inability to objectively quantitate mutant allele burdens, to determine the exact change in nucleotide sequence, and to detect non–lengthaffecting mutations such as substitution mutations. Examples of fragment analysis applications in oncology include detection of NPM1 insertion mutations34 (Fig. 2.5), EGFR exon 19 deletions, FLT3 internal tandem duplications, and JAK2 exon 12 mutations.35

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Figure 2.5 Fragment analysis. NPM1 mutations are important prognostic markers in acute myeloid leukemia. Virtually all NPM1 mutations result in a four-nucleotide insertion within exon 12. Detection of these mutations can be accomplished by polymerase chain reaction utilizing primers that flank the mutation region. The amplification products are sized using capillary electrophoresis. A mutation is indicated by a polymerase chain reaction fragment that is 4 bp larger than the wildtype fragment. Mutation positive (A) and negative (B) cases are shown.

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Sanger Sequencing Mutations in single gene assays are commonly analyzed by targeted nucleic acid sequencing, most commonly by Sanger sequencing.36 This method, also known as dideoxy sequencing, is based on random incorporation of modified nucleotides (dideoxynucleotides) into a DNA sequence during rounds of template extension that result in termination of the chain reaction at various fragment lengths. Because dideoxynucleotides lack a 3′ hydroxyl group on the DNA pentose ring, which is required for addition of further nucleotides during extension of the new DNA strand, the chain reaction is terminated at different lengths with the random incorporation of ddNTPs to the sequence. In addition to the dideoxy modification, each ddNTP (ddATP, ddTTP, ddCTP, ddGTP) is labeled with fluorescent tags of different fluorescent wavelengths. In this method, repetitive cycles of primer extension are performed using denatured PCR products (amplicons) as templates. Unlike PCR, in which both forward and reverse primers are added to the same reaction, in Sanger sequencing, the forward and reverse reactions are performed separately. Bidirectional sequencing is performed to ensure that the entire region of interest for each analysis is visualized adequately to produce unequivocal sequence readout. The sequencing products of increasing size are resolved by capillary electrophoresis, and the DNA sequence is determined by detection of the fluorescently labeled nucleotide sequences. Sanger sequencing has the ability to detect a wide variety of nucleotide alterations in the DNA including point mutations, deletions, insertions, and duplications. This technique is especially useful when mutations are scattered across the entire gene, when genes have not been sufficiently studied to determine mutational hot spots, or when it is relevant to determine the exact change in DNA sequence. Sanger sequencing can also provide semiquantitative information about mutation levels in a sample based on the evaluation of average peak drop values from forward and reverse mutant peaks on sequence chromatograms. Limitations of this approach include low throughput and limited diagnostic sensitivity. In general, heterozygous mutations at allelic levels lower than 20% may be difficult to detect by Sanger sequencing. This may be particularly problematic when testing for somatic mutations in oncogenes, such as JAK2 exon 12 in polycythemia vera, which may occur at low level.35 Examples of Sanger sequencing applications in oncology include detection of KIT mutations for gastrointestinal stromal tumor and melanomas that arise from mucosal membranes and acral skin, EGFR mutations for NSCLC, and KRAS mutations for colorectal and lung carcinomas (Fig. 2.6).

Pyrosequencing Pyrosequencing, also known as sequencing by synthesis, is based on the real-time detection of pyrophosphate release by nucleotide incorporation during DNA synthesis.37 In the pyrosequencing reaction, as nucleotides are added to the nucleic acid chain by polymerase, pyrophosphate molecules are released and subsequently converted to adenosine triphosphate (ATP) by ATP sulfurylase. Light is produced by an ATP-driven luciferase reaction via oxidation of a luciferin molecule. The amount of light produced is proportional to the number of incorporated nucleotides in the sequence. When a nucleotide is not incorporated into the reaction, no pyrophosphate is released and the unused nucleotide is degraded by apyrase. Light is converted into peaks in a charge-coupled device camera. Individual dNTP nucleotides are sequentially added to the reaction, and the sequence of nucleotides that produce chemiluminescent signals allow the template sequence to be determined. Mutations appear as new peaks in the pyrogram sequence or variations of the expected peak heights.38 Pyrosequencing is particularly useful for detection of point mutations and insertion/deletion mutation that occur at short stretches in mutational hotspots. This method has higher analytical sensitivity than Sanger sequencing and can provide quantitative information about mutation levels in a sample. Pyrosequencing can also be used for detection and quantification of gene-specific DNA methylation and gene copy number assessment. A microfluidic pyrosequencing platform is available for massive parallel sequencing. However, this method is not well suited for detecting mutations that are scattered across the entire gene because pyrosequencing read lengths are limited to 100 kb, small deletions or insertions will not be detected. In addition, poor tissue fixation, fixation artifacts, nuclear truncation on tissue slides, and nuclear overlap are potential pitfalls of this technique that may hamper interpretation. Some intrachromosomal rearrangements (e.g., RET-PTC and EML4-ALK) may be challenging to interpret by FISH due to subtle rearrangement of the probe signals on the same chromosome arm. Scoring can be time consuming and requires experience.

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Figure 2.7 Fluorescence in situ hybridization. (A) Recurrent chromosomal translocations such as IGH-BCL2 (occurring in B-cell lymphomas) can be effectively detected with a dual-fusion probe strategy. This design utilizes a green probe specific to the IGH locus and a red probe specific to the BCL2 gene, each probe spanning their respective breakpoint region. Individual green and red probe signals indicate a lack of translocation. Colocalization of green and red probes is observed when an IGH-BCL2 translocation is present. (B) ALK rearrangements in non–small-cell lung cancer may involve a variety of translocation partners, including EML4, TFG, and KIF5B. Therefore, a breakapart fluorescence in situ hybridization probe strategy is utilized that will detect any ALK rearrangement, regardless of the partner gene. Fluorescently labeled red and green probes are designed on opposite sides of the ALK gene breakpoint region. With this design, a normal ALK gene is observed as overlapping or adjacent red and green fluorescent signals, whereas a rearranged ALK gene is indicated by split red and green signals. ALK testing in lung cancer has become in widespread use because of the significant therapeutic implications.

WHOLE-GENOME ANALYSIS METHODS Next-Generation Sequencing

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NGS, also known as massive parallel sequencing or deep sequencing, has revolutionized the speed, throughput, and cost of sequencing and has facilitated the discovery of clinically relevant genetic biomarkers for diagnosis, prognosis, and personalized therapeutics. By way of this technology, multiple genes or the entire exome or genome can be interrogated simultaneously in multiple parallel reactions, instead of a single-gene basis as in Sanger sequencing or pyrosequencing. These characteristics make NGS a very cost-effective approach for clinical testing of cancer specimens because many markers can be evaluated simultaneously from a single nucleic acid extraction and test run. This not only improves testing turnaround time but also preserves tissue, which is very relevant for testing in advanced-stage cancer patients where small biopsies obtained by minimally invasive techniques are commonly the only tissue available for testing. Currently, there is no clear consensus for the ideal size and content of NGS panels. Design and strategy decisions are complex and depend on many contributing factors and influences, such as clinician and patient demand for an ever-growing list of clinically relevant genomic findings, cost of test development and implementation, cost of test per reaction, types of specimens expected for testing, in-house expertise, reimbursement, institutional support, etc. Currently, the most common NGS approach for cancer testing in the clinical setting employs targeted sequencing of specific genes and mutation hotspot regions. Available panels commonly range in size from 10 to 150 genes. This targeted approach increases sensitivity for detection of low-level mutations by increasing the depth of sequence coverage without being prohibitively expensive. Genes/genomic regions can be selected for targeted sequencing using hybrid capture or amplicon-based enrichment approaches. Hybrid capture–based assays use biotinylated probes (oligonucleotide sequences) that are complementary to genes/genomic regions targeted by the assay to selectively pull down with streptavidin-coated beads only the genes/regions of interest. Amplicon-based assays use PCR primers to select a subset of genes for sequencing. Each of these approaches has pros and cons, and clinical laboratories may offer targeted NGS panels of different sizes and scope to implement both systems. For instance, amplicon-based tests are an excellent approach for testing small biopsies and cytology specimens because this method requires very low DNA input. Amplicon-based assays usually have faster wet-bench processing time than hybrid capture assays, and they are very suitable for detection of single nucleotide variants and small/medium insertion deletion variants (indels; 50% expression of PD-L1, an even greater benefit was observed in OS at both doses (14.9 versus 8.2 months; HR, 0.54; P = .0002; and 17.3 versus 8.2 months; HR, 0.50; P < .0001) and PFS (5.0 months versus 4.1 months; HR, 0.59; P = .0001; and 5.2 months versus 4.1 months; HR, 0.59; P < .0001) with pembrolizumab at 2 mg/kg or 10 mg/kg compared to docetaxel.122 Patients treated with either dose of pembrolizumab experienced fewer grade 3 to 5 treatment-related adverse events than those treated with docetaxel (13% to 16% versus 35%).122

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KEYNOTE-024 led to the approval of pembrolizumab as first-line treatment of patients with metastatic NSCLC that had at least 50% of tumor cells expressing PD-L1.123 This phase III trial compared first-line treatment with pembrolizumab 200 mg to investigators’ choice of platinum-based chemotherapy and showed a statistically significant improvement in PFS (10.3 versus 6.0 months; HR for disease progression or death, 0.50; P < .001) and a 6-month OS of 80.2% compared to 72.4% with chemotherapy (HR for death, 0.60; P = .005).123 Pembrolizumab was also tolerated better, with 26.6% grade 3 to 5 treatment-related adverse events compared to 53.3% with chemotherapy.123 The combination of pembrolizumab with pemetrexed and carboplatin was approved in 2017 as first-line therapy for patients with advanced or metastatic NSCLC, regardless of PD-L1 expression level.124 The addition of pembrolizumab 200 mg to combination with carboplatin and pemetrexed chemotherapy, followed by pemetrexed maintenance in KEYNOTE-021, led to a near doubling of the ORR from 29% to 55% (26% increase, P = .0016) with similar rates of grade 3 or higher treatment-related adverse events (29% with the addition of pembrolizumab versus 26% with chemotherapy alone).124 In 2016 atezolizumab was approved for the treatment of patients with metastatic NSCLC who progressed after platinum-based chemotherapy. The phase III OAK trial compared atezolizumab with docetaxel in patients with stage IIIB or IV squamous and nonsquamous NSCLC who had previously been treated with at least one nonimmunotherapy regimen.125 Median OS among patients who received atezolizumab was 13.8 months compared to 9.6 months for docetaxel (HR, 0.73; P = .0003).125 PD-L1 expression was quantified on both tumor cells (TC) and on tumor-infiltrating cells (IC), with TC0 or IC0 indicating low or undetectable expression, TC1/2/3 or IC1/2/3 showing ≥1% of cells expressing PD-L1, TC2/3 or IC2/3 corresponding to ≥5% expression, and TC3 or IC3 indicating ≥50% expression.125 Among patients with TC1/2/3 or IC1/2/3 expression, median OS was 15.7 months with atezolizumab versus 10.3 months with docetaxel (HR, 0.74; P = .0102).125 In patients with low or undetectable PD-L1 expression, median OS was 12.6 months with atezolizumab versus 8.9 months with docetaxel (HR, 0.73; P = .0102).125 Atezolizumab was better tolerated, with a grade 3 to 4 treatment-related adverse event rate of 15% versus 43% with docetaxel.125 Durvalumab was approved in 2018 as consolidation therapy for patients with unresectable stage III NSCLC who did not progress after chemoradiation. The phase III PACIFIC trial compared durvalumab with placebo as consolidation therapy for patients with unresectable stage III nonsquamous and squamous NSCLC who had received concurrent radiation therapy and at least two cycles of platinum-based chemotherapy within 42 days prior to randomization.126 Median postrandomization PFS for patients receiving durvalumab was 16.8 months versus 5.6 months for patients receiving placebo (HR, 0.52; P < .001).126 Responses were independent of PD-L1 expression level. Durvalumab significantly increased the median time to distant metastasis or death to 23.2 months compared to 14.6 months with placebo (HR, 0.52; P < .001).126 The reported data represents an interim analysis; thus, OS was not reported. Durvalumab was well tolerated compared to placebo, with grade 3 or 4 rates of pneumonitis or radiation pneumonitis of 3.4% versus 2.6% and grade 3 or 4 pneumonia of 4.4% versus 3.8%, respectively.126 For patients whose tumors harbor mutations in the EGFR or rearrangements within the ALK gene, both of which respond to targeted therapy, the efficacy of checkpoint inhibitors remains under investigation. In the phase III CheckMate-057 trial comparing nivolumab with docetaxel in previously treated advanced NSCLC, both OS and PFS numerically favored the docetaxel cohort in patients with EGFR mutation–positive tumors (HR for death, 1.18; 95% CI, 0.69 to 2.00; HR for disease progression, 1.46; 95% CI, 0.90 to 2.37).119 Subset analysis by EGFR mutation status in patients with previously untreated advanced nonsquamous NSCLC enrolled in the phase I CheckMate-012 study of nivolumab as first-line therapy showed a shorter PFS and lower 24-week PFS rate among patients harboring EGFR mutations.127 The follow-up phase III CheckMate-026 trial comparing nivolumab to platinum-based chemotherapy in patients with 5% or higher tumor PD-L1 expression showed a lower PFS with nivolumab and similar OS among the two treatment arms and did not include patients with EGFR mutations or ALK translocations.128 The multicohort phase I CheckMate-012 trial also assessed the ORR of combination therapy with nivolumab and the tyrosine kinase inhibitor erlotinib in patients with EGFR mutation– positive NSCLC, showing a 19% ORR at a median follow-up of 72 weeks.129 At a 23-month median follow-up, patients with previously treated EGFR wild-type advanced NSCLC enrolled in the phase Ib KEYNOTE-001 study of pembrolizumab survived twice as long as patients with EGFR-mutant tumors (12.1 months versus 6.0 months).130 The combination of immune checkpoint therapy and tyrosine kinase inhibitors is also being explored for ALK rearrangement–positive NSCLC. Early data from a phase Ib trial demonstrated activity for the combination of nivolumab and the ALK inhibitor ceritinib in patients with advanced ALK+ NSCLC, and a

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modified dose escalation phase is ongoing.131

Mismatch-Repair Deficient or Microsatellite Instability-High Cancers Pembrolizumab was approved in 2017 for the treatment of adults and children with MSI-H or dMMR solid tumors who had exhausted all other treatment options. The phase II KEYNOTE-016 trial enrolled patients with dMMR and mismatch-repair proficient (pMMR) metastatic CRC or other solid tumors that progressed after treatment with a fluoropyrimidine and oxaliplatin or irinotecan or other chemotherapy regimen.132 Patients with non-CRC dMMR solid tumors showed a 71% immune-related response rate and a 67% immune-related PFS.132 Patients with dMMR CRC experienced a clear benefit over patients with pMMR CRC, showing a 40% ORR versus no response at all as well as a PFS of 78% as compared to 11%.132 Median OS and PFS were not reached in the dMMR patient populations, whereas patients with pMMR CRC experienced a median PFS of 2.2 months and a median OS of 5.0 months (HR for disease progression or death, 0.10; P < .001; and HR for death, 0.22; P = .05).132 A total of 41% of patients enrolled in this study experienced grade 3 to 4 treatment-related adverse events.132 Nivolumab was also approved in 2017 for the treatment of patients with MSI-H or dMMR CRC who progressed after treatment with a fluoropyrimidine, oxaliplatin, and irinotecan. The phase II CheckMate-142 trial showed a 12-month ORR of 31.1% (95% CI, 20.8% to 42.9%) and 12-week disease control in 69% (95% CI, 57% to 79%) of patients who had received at least one line of therapy with a fluoropyrimidine and oxaliplatin or irinotecan.133 A total of 11% of patients experienced grade 3 to 4 treatment-related adverse events.133

Renal Cell Carcinoma Anti–PD-1 therapy with nivolumab was approved for the treatment of metastatic renal cell carcinoma in 2015. The phase III CheckMate-025 trial compared nivolumab with everolimus in advanced clear-cell renal cell carcinoma that progressed after one to two lines of treatment with antiangiogenic agents.134 Patients who received nivolumab experienced a statistically significant improvement in OS (25.0 months versus 19.6 months; HR for death, 0.73; P = .002) and ORR (25% versus 5%; odds ratio, 5.98; P < .001).134 Nivolumab was also associated with a lower rate of grade 3 to 4 treatment-related adverse events compared to everolimus (19% versus 37%).134 Combination anti–CTLA-4 and anti–PD-1 checkpoint inhibition was approved as first-line therapy for advanced renal cell carcinoma in 2018. The phase III CheckMate-214 trial showed superior OS, PFS, and objective response rate in patients with intermediate-risk and poor-risk advanced clear-cell renal cell carcinoma treated with induction nivolumab 3 mg/kg plus ipilimumab 1 mg/kg for four doses, followed by maintenance nivolumab compared to sunitinib alone for the entire course of treatment.135 Although the median OS was not reached for patients receiving the checkpoint inhibitors, the median OS for sunitinib was 26.0 months, and the median PFS for nivolumab plus ipilimumab was 11.6 months versus 8.4 months with sunitinib.135 The ORR for the combination of checkpoint inhibitors was significantly increased at 42% compared to 27% with sunitinib (P < .001).135 The combination of nivolumab plus ipilimumab was better tolerated than sunitinib, with a 46% rate of grade 3 or 4 adverse events versus 63%, respectively.135

Hodgkin Lymphoma In 2016, nivolumab was approved for the treatment of adults with classical Hodgkin lymphoma who progressed after autologous hematopoietic stem cell transplantation (ASCT) and treatment with the anti-CD30 monoclonal antibody brentuximab vedotin as well as for patients with classical Hodgkin lymphoma who progressed after three or more lines of therapy, including ASCT. The phase I CheckMate-205 trial of nivolumab showed an ORR of 87%, including 17% CR and 70% PR.136 Additionally, 13% of heavily pretreated patients with relapsed or refractory classical Hodgkin lymphoma enrolled in this trial achieved disease stabilization.136 Treatment was well tolerated, with 22% of patients experiencing grade 3 or 4 treatment-related adverse events.136 CheckMate-039, a phase II trial for patients with recurrent classical Hodgkin lymphoma who progressed after hematopoietic stem cell transplantation and brentuximab vedotin, showed a 66.3% ORR to nivolumab at median follow-up of 8.9 months, with only 10% of patients experiencing grade 3 to 4 treatment-related adverse events.137 Among the responders, 9% achieved complete remission and 58% experienced partial remission.137 Pembrolizumab was also approved for the treatment of classical Hodgkin lymphoma in 2017 based on the results of KEYNOTE-087.138 In this phase II trial, patients with relapsed or refractory classical Hodgkin

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lymphoma who progressed either after ASCT with or without subsequent therapy with brentuximab vedotin or after salvage chemotherapy and brentuximab vedotin received a median of 13 cycles of pembrolizumab 200 mg every 3 weeks.138 The ORR was 69% with a greater response rate in patients who had undergone ASCT (73.9% for patients who subsequently received brentuximab vedotin versus 70% for patients who were not treated with brentuximab vedotin).138 A response rate of 64.2% was seen in patients who were treated with salvage chemotherapy and brentuximab vedotin and had not undergone ASCT.138 The CR rate among all patients was 22.4%. Grade 3 to 4 treatment-related adverse events occurred in only 6.4% of patients.138

Head and Neck Squamous Cell Carcinoma Pembrolizumab was approved in 2016 for patients with heavily pretreated recurrent or metastatic HNSCC. The phase Ib KEYNOTE-012 trial assessed the safety and efficacy of pembrolizumab 10 mg/kg in patients with recurrent or metastatic HNSCC with >1% PD-L1 expression.139 The ORR among all patients was 18%, with human papillomavirus (HPV)-positive patients experiencing a response rate of 25% compared to a 14% response rate among HPV-negative patients.139 Grade 3 to 4 treatment-related adverse events occurred in 17% of patients.139 Subsequently, an expansion cohort showed similar efficacy and safety of pembrolizumab administered at a fixed dose of 200 mg every 3 weeks in patients with recurrent or metastatic HNSCC.140 Nivolumab gained approval in 2016 for patients with recurrent or metastatic HNSCC who progressed after chemotherapy with platinum agents based on results from CheckMate-141.141 This phase III trial showed statistically significant improvements in OS (7.5 versus 5.1 months; HR for death, 0.70; P = .01), 1-year OS (36% versus 16.6%), 6-month PFS (19.7% versus 9.9%), and ORR (13.3% versus 5.8%) after treatment with nivolumab compared to single-agent systemic chemotherapy with methotrexate, docetaxel, or the anti-EGFR monoclonal antibody cetuximab.141 Nivolumab was tolerated better, with a 13.1% rate of grade 3 to 4 treatment-related adverse events as compared to 35.1% with standard therapy.141

Urothelial Carcinoma Several checkpoint inhibitors have received FDA approval for the treatment of urothelial carcinoma. Atezolizumab was approved in 2016 for the treatment of patients with locally advanced or metastatic urothelial carcinoma that progressed after platinum-based chemotherapy. The phase II IMvigor210 trial showed an ORR of 27% in patients with PD-L1 levels of IC2/3 compared to 18% in patients with PD-L1 levels of IC1/2/3 or 15% among all patients.142 Atezolizumab led to a statistically significant improvement in the ORR of all patients, regardless of PD-L1 expression level, compared to an ORR of 10% in historical controls.142 Grade 3 to 4 treatment-related adverse events occurred in 16% of patients.142 In 2017, atezolizumab was approved as first-line therapy in patients with bladder cancer who were ineligible for cisplatin-based chemotherapy due to renal impairment, poor performance status, hearing loss, or peripheral neuropathy. The previously untreated cisplatin-ineligible cohort of patients in the IMvigor210 trial showed an ORR of 23% (95% CI, 16% to 31%), a CR rate of 9%, a median OS of 15.9 months, and a median PFS of 2.7 months.143 Longer survival was observed among patients with higher tumor mutation burdens.143 Grade 3 to 4 treatment-related adverse events were observed in 16% of patients.143 Nivolumab was approved in 2017 for patients with locally advanced or metastatic urothelial carcinoma who progressed after chemotherapy with platinum agents. The phase II CheckMate- 275 trial showed responses regardless of PD-L1 expression status.144 Patients whose tumors expressed PD-L1 in >5% of cells showed an ORR of 28.4%, whereas those with >1% PD-L1 expression showed a 23.8% response rate and those with 10% experienced an

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ORR of 47%.146 A total of 18% of patients experienced grade 3 or higher treatment-related adverse events.146 In 2017, pembrolizumab was approved for second-line treatment of patients with locally advanced or metastatic urothelial carcinoma who progressed after platinum-based chemotherapy. The phase III KEYNOTE045 trial compared the efficacy of pembrolizumab with chemotherapy with paclitaxel, docetaxel, or vinflunine, and showed an OS of 10.3 months in the total population of patients who received pembrolizumab versus 7.4 months in patients who received chemotherapy (HR for death, 0.73; P = .002).147 Among patients with CPS >10%, OS was 8.0 months with pembrolizumab versus 5.2 months with chemotherapy (HR, 0.57; P = .005).147 Pembrolizumab proved less toxic than chemotherapy, with a grade 3 to 5 treatment-related adverse event rate of 15.0% versus 49.4%, respectively.147 Durvalumab was also approved in 2017 for the treatment of patients with locally advanced or metastatic urothelial carcinoma that had progressed after platinum-based chemotherapy. In the phase I/II Study 1108, 4.9% of patients experienced a CR, with an ORR of 20.4%.148 CR rates were 4.9% and 5.1% among patients with PDL1–high and PD-L1–low or PD-L1–negative tumors, respectively, whereas 24.6% of PD-L1–high patients and 2.6% of PD-L1–low or PD-L1–negative patients achieved a PR.148 Grade 3 to 4 treatment-related adverse events occurred in 3% of patients.148 Avelumab also received approval in 2017 for the treatment of patients with locally advanced or metastatic urothelial carcinoma that had progressed after treatment with platinum-based chemotherapy. In the phase Ib JAVELIN trial for solid tumors, avelumab showed a 17.6% ORR that included 9 CRs and 18 PRs, with a median OS of 7 months.149 Response was numerically higher among patients who expressed PD-L1 as compared to PDL1–negative patients, although the difference did not reach statistical significance (25.0% versus 14.7%; P = .178).149 Treatment-related grade 3 or higher adverse events occurred in 7.5% of patients.149

Merkel Cell Carcinoma Avelumab was approved in 2017 for the treatment of adults and children 12 years old or older with metastatic Merkel cell carcinoma. In a phase II trial for patients with stage IV Merkel cell carcinoma who had progressed after chemotherapy, treatment with avelumab 10 mg/kg led to an ORR of 31.8% with 9% of patients achieving a CR and 23% attaining a PR.150 Treatment-related grade 3 or 4 adverse events occurred in 6% of patients.150

Hepatocellular Carcinoma Nivolumab was approved in 2017 for the treatment of advanced hepatocellular carcinoma patients who progressed after therapy with sorafenib.151 The phase I/II CheckMate-040 trial enrolled patients with and without chronic hepatitis B or C, as well as patients who had and had not previously received sorafenib, in its dose-expansion phase for treatment with nivolumab administered at 3 mg/kg every 2 weeks.151 The ORR among these expansionphase cohorts was 20% and included 3 CRs and 39 PRs among the 214 patients who were enrolled in the study, with 64% of patients achieving disease control (CR + PR + SD).151 Among patients who had received prior treatment with sorafenib, the objective response rate was 19%, and 5 CRs were recorded per mRECIST (modified RECIST criteria for hepatocellular carcinoma).151 A total of 19% of patients experienced grade 3 to 4 treatmentrelated adverse events.151

Gastric Cancer Pembrolizumab was approved in 2017 for the treatment of patients with recurrent, locally advanced, and metastatic gastric or gastroesophageal junction adenocarcinoma that expressed PD-L1 (CPS ≥1) and were previously treated with at least two lines of fluoropyrimidine- and platinum-based chemotherapy and human epidermal growth factor receptor 2 (HER2)/neu-targeted therapy, if applicable. The phase II KEYNOTE-059 trial enrolled patients in three cohorts based on treatment history and PD-L1 expression levels.152 Patients enrolled in cohort 1 had received prior therapy and were treated with pembrolizumab 200 mg fixed dose regardless of PD-L1 expression status.152 Patients in cohort 2 received first-line therapy with pembrolizumab 200 mg, cisplatin, and fluorouracil or capecitabine, also without regard to PD-L1 expression.152 Finally, patients were enrolled in cohort 3 if their tumors expressed PD-L1 (CPS ≥1%) and received pembrolizumab 200 mg as first-line therapy.152 A higher ORR was observed in patients with PD-L1-positive tumors enrolled in cohorts 1 and 2.152 Median PFS was longer for patients who received combined first-line chemotherapy and anti–PD-1 therapy in cohort 2 as compared to first-line therapy with pembrolizumab alone in cohort 3.152 Median OS was not reached in cohort 3, was 14

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months in cohort 2, and was 6 months in cohort 1. The breakdown of outcomes by PD-L1 expression within cohort 2 was not specified.152

Cervical Cancer Pembrolizumab was approved in 2018 for the second-line treatment of recurrent or metastatic cervical squamous cell carcinoma that expresses PD-L1 (CPS ≥1) and that progressed on or after chemotherapy.153 In the cervical cancer cohort of the phase II KEYNOTE-158 trial, patients with advanced cervical cancer who progressed on or were unable to tolerate at least one line of standard chemotherapy experienced an ORR of 13.3%, with 3% attaining a CR, 10% achieving a PR, and an additional 17% experiencing disease stability.153 All responders expressed PD-L1 (CPS ≥1), and 16% of all patients with PD-L1–positive tumors achieved a response.153 Treatment-related grade 3 or 4 adverse events manifested in 11.2% of patients.153

Primary Mediastinal Large B-Cell Lymphoma Pembrolizumab was approved in 2018 for the treatment of relapsed or refractory primary mediastinal large B-cell lymphoma (rrPMBCL) who relapsed after ASCT or who were ineligible for ASCT and relapsed after or were refractory to two or more lines of therapy. In the rrPMBCL cohort of the phase II KEYNOTE-170 trial, the ORR was 42%, including 14% of patients who achieved a CR and 28% who attained a PR; additionally, disease stability was maintained in 10% of patients.154 Median OS was not reached.154 The rate of grade 3 or 4 treatmentrelated adverse events was 25%.154

Dosing Weight-based dosing established in early trials for nivolumab was subsequently transitioned to flat dosing, with a few exceptions, based on population pharmacokinetics. The FDA approved a nivolumab dose of 240 mg intravenously every 2 weeks (except 1 mg/kg every 3 weeks while administered concurrently with ipilimumab for melanoma and 3 mg/kg intravenously every 2 weeks for classical Hodgkin lymphoma) in 2016, a change from the initial dosing of 3 mg/kg for all indications. Weight-based dosing for pembrolizumab also transitioned to a flat dose of 200 mg every 3 weeks in 2016 with the approval of pembrolizumab for heavily pretreated recurrent or metastatic HNSCC.140,155

VACCINES Sipuleucel-T Sipuleucel-T is a cellular vaccine composed of dendritic cells presenting the fusion protein PA2024, which consists primarily of a protein expressed uniquely in prostate cancer cells.156–158 Full-length prostatic acid phosphatase is coexpressed with full-length GM-CSF to form PA2024, which is then loaded onto autologous dendritic cells isolated from individual patients by leukapheresis.156 GM-CSF was included to strengthen the immune response to prostatic acid phosphatase alone.156 Sipuleucel-T was approved in 2010 for the treatment of patients with metastatic castration-resistant prostate cancer and minimal to no symptoms. The phase III IMPACT trial (9902B) enrolled asymptomatic and minimally symptomatic patients with metastatic castrate-resistant prostate cancer and any Gleason score for treatment with three doses of sipuleucel-T administered every 2 weeks or placebo.158 Patients who received sipuleucel-T experienced longer OS compared to patients in the placebo arm (median OS, 25.8 months versus 21.7 months, respectively) with a 22% relative risk reduction in the risk of death (HR for death, 0.78; P = .03).158 Three-year survival for patients receiving sipuleucel-T was 31.7% versus 23.0% in the placebo arm.158 Due to its cost and concerns about its efficacy, sipuleucel-T has had little penetration into the U.S. market.

CONCLUSION The future of immunotherapy for cancer is a bright one, with hundreds of new trials to assess the utility of new checkpoints, new agonistic molecules, variants of IL-2, novel cytokine or cytokine-receptor fusion constructs,

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bispecific molecules, and adoptive cell therapies. One of the more important advances in recent years has been the revelation that epithelial malignancies are appropriate targets for immunotherapy. Much of the most important work in the future will be to define biomarkers associated with a beneficial outcome for checkpoint inhibition and other immunotherapies, which should facilitate an understanding of the mechanism of action of these new drugs, how to overcome resistance to their efficacy, and how to expand the list of patients that may benefit from these treatments.

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44. Sasse AD, Sasse EC, Clark LG, et al. Chemoimmunotherapy versus chemotherapy for metastatic malignant melanoma. Cochrane Database Syst Rev 2007;(1):CD005413. 45. Ives NJ, Stowe RL, Lorigan P, et al. Chemotherapy compared with biochemotherapy for the treatment of metastatic melanoma: a meta-analysis of 18 trials involving 2,621 patients. J Clin Oncol 2007;25(34):5426–5434. 46. Flaherty LE, Othus M, Atkins MB, et al. Southwest Oncology Group S0008: a phase III trial of high-dose interferon alfa-2b versus cisplatin, vinblastine, and dacarbazine, plus interleukin-2 and interferon in patients with high-risk melanoma—an intergroup study of Cancer and Leukemia Group B, Children’s Oncology Group, Eastern Cooperative Oncology Group, and Southwest Oncology Group. J Clin Oncol 2014;32(33):3771–3778. 47. Sabatino M, Kim-Schulze S, Panelli MC, et al. Serum vascular endothelial growth factor and fibronectin predict clinical response to high-dose interleukin-2 therapy. J Clin Oncol 2009;27(16):2645–2652. 48. Cesana GC, DeRaffele G, Cohen S, et al. Characterization of CD4+CD25+ regulatory T cells in patients treated with high-dose interleukin-2 for metastatic melanoma or renal cell carcinoma. J Clin Oncol 2006;24(7):1169–1177. 49. van der Vliet HJ, Koon HB, Yue SC, et al. Effects of the administration of high-dose interleukin-2 on immunoregulatory cell subsets in patients with advanced melanoma and renal cell cancer. Clin Cancer Res 2007;13(7):2100–2108. 50. Koreth J, Matsuoka K, Kim HT, et al. Interleukin-2 and regulatory T cells in graft-versus-host disease. N Engl J Med 2011;365(22):2055–2066. 51. Clark JI, Wong MKK, Kaufman HL, et al. Impact of sequencing targeted therapies with high-dose interleukin-2 immunotherapy: an analysis of outcome and survival of patients with metastatic renal cell carcinoma from an ongoing observational IL-2 clinical trial: PROCLAIMSM. Clin Genitourin Cancer 2017;15(1):31–41.e4. 52. Buchbinder EI, Gunturi A, Perritt J, et al. A retrospective analysis of high-dose interleukin-2 (HD IL-2) following ipilimumab in metastatic melanoma. J Immunother Cancer 2016;4:52. 53. Maker AV, Phan GQ, Attia P, et al. Tumor regression and autoimmunity in patients treated with cytotoxic T lymphocyte-associated antigen 4 blockade and interleukin 2: a phase I/II study. Ann Surg Oncol 2005;12(12):1005– 1016. 54. Hu JC, Coffin RS, Davis CJ, et al. A phase I study of OncoVEXGM-CSF, a second-generation oncolytic herpes simplex virus expressing granulocyte macrophage colony-stimulating factor. Clin Cancer Res 2006;12(22):6737– 6747. 55. Senzer NN, Kaufman HL, Amatruda T, et al. Phase II clinical trial of a granulocyte-macrophage colony-stimulating factor-encoding, second-generation oncolytic herpesvirus in patients with unresectable metastatic melanoma. J Clin Oncol 2009;27(34):5763–5771. 56. Kaufman HL, Kim DW, DeRaffele G, et al. Local and distant immunity induced by intralesional vaccination with an oncolytic herpes virus encoding GM-CSF in patients with stage IIIc and IV melanoma. Ann Surg Oncol 2010;17(3):718–730. 57. Andtbacka RH, Kaufman HL, Collichio F, et al. Talimogene laherparepvec improves durable response rate in patients with advanced melanoma. J Clin Oncol 2015;33(25):2780–2788. 58. Puzanov I, Milhem MM, Minor D, et al. Talimogene laherparepvec in combination with ipilimumab in previously untreated, unresectable stage IIIB-IV melanoma. J Clin Oncol 2016;34(22):2619–2626. 59. Chesney J, Puzanov I, Collichio F, et al. Randomized, open-label phase II study evaluating the efficacy and safety of talimogene laherparepvec in combination with ipilimumab versus ipilimumab alone in patients with advanced, unresectable melanoma. J Clin Oncol 2018;36(17):1658–1667. 60. Ribas A, Dummer R, Puzanov I, et al. Oncolytic virotherapy promotes intratumoral T cell infiltration and improves anti-PD-1 immunotherapy. Cell 2017;170(6):1109–1119.e10. 61. Shi Y, Liu CH, Roberts AI, et al. Granulocyte-macrophage colony-stimulating factor (GM-CSF) and T-cell responses: what we do and don’t know. Cell Res 2006;16(2):126–133. 62. Gomez-Cambronero J, Horn J, Paul CC, et al. Granulocyte-macrophage colony-stimulating factor is a chemoattractant cytokine for human neutrophils: involvement of the ribosomal p70 S6 kinase signaling pathway. J Immunol 2003;171(12):6846–6855. 63. Fridlender ZG, Albelda SM. Tumor-associated neutrophils: friend or foe? Carcinogenesis 2012;33(5):949–955. 64. Dolcetti L, Peranzoni E, Ugel S, et al. Hierarchy of immunosuppressive strength among myeloid-derived suppressor cell subsets is determined by GM-CSF. Eur J Immunol 2010;40(1):22–35. 65. Fernández A, Oliver L, Alvarez R, et al. Adjuvants and myeloid-derived suppressor cells: enemies or allies in therapeutic cancer vaccination. Hum Vaccin Immunother 2014;10(11):3251–3260. 66. Becher B, Tugues S, Greter M. GM-CSF: from growth factor to central mediator of tissue inflammation. Immunity 2016;45(5):963–973.

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67. Hodi FS, Lee S, McDermott DF, et al. Ipilimumab plus sargramostim vs ipilimumab alone for treatment of metastatic melanoma: a randomized clinical trial. JAMA 2014;312(17):1744–1753. 68. O’Day SJ, Boasberg PD, Piro L, et al. Maintenance biotherapy for metastatic melanoma with interleukin-2 and granulocyte macrophage-colony stimulating factor improves survival for patients responding to induction concurrent biochemotherapy. Clin Cancer Res 2002;8(9):2775–2781. 69. Markovic SN, Suman VJ, Ingle JN, et al. Peptide vaccination of patients with metastatic melanoma: improved clinical outcome in patients demonstrating effective immunization. Am J Clin Oncol 2006;29(4):352–360. 70. Slingluff CL Jr, Petroni GR, Olson WC, et al. Effect of granulocyte/macrophage colony-stimulating factor on circulating CD8+ and CD4+ T-cell responses to a multipeptide melanoma vaccine: outcome of a multicenter randomized trial. Clin Cancer Res 2009;15(22):7036–7044. 71. Spitler LE, Grossbard ML, Ernstoff MS, et al. Adjuvant therapy of stage III and IV malignant melanoma using granulocyte-macrophage colony-stimulating factor. J Clin Oncol 2000;18(8):1614–1621. 72. Weller M, Butowski N, Tran DD, et al. Rindopepimut with temozolomide for patients with newly diagnosed, EGFRvIII-expressing glioblastoma (ACT IV): a randomised, double-blind, international phase 3 trial. Lancet Oncol 2017;18(10):1373–1385. 73. Hoeller C, Michielin O, Ascierto PA, et al. Systematic review of the use of granulocyte-macrophage colonystimulating factor in patients with advanced melanoma. Cancer Immunol Immunother 2016;65(9):1015–1034. 74. Rosenberg SA, Spiess P, Lafreniere R. A new approach to the adoptive immunotherapy of cancer with tumorinfiltrating lymphocytes. Science 1986;233(4770):1318–1321. 75. Rosenberg SA, Packard BS, Aebersold PM, et al. Use of tumor-infiltrating lymphocytes and interleukin-2 in the immunotherapy of patients with metastatic melanoma. A preliminary report. N Engl J Med 1988;319(25):1676– 1680. 76. Aebersold P, Hyatt C, Johnson S, et al. Lysis of autologous melanoma cells by tumor-infiltrating lymphocytes: association with clinical response. J Natl Cancer Inst 1991;83(13):932–937. 77. Schwartzentruber DJ, Hom SS, Dadmarz R, et al. In vitro predictors of therapeutic response in melanoma patients receiving tumor-infiltrating lymphocytes and interleukin-2. J Clin Oncol 1994;12(7):1475–1483. 78. Dudley ME, Wunderlich JR, Yang JC, et al. Adoptive cell transfer therapy following non-myeloablative but lymphodepleting chemotherapy for the treatment of patients with refractory metastatic melanoma. J Clin Oncol 2005;23(10):2346–2357. 79. Muranski P, Boni A, Wrzesinski C, et al. Increased intensity lymphodepletion and adoptive immunotherapy—how far can we go? Nat Clin Prac Oncol 2006;3(12):668–681. 80. Dudley ME, Yang JC, Sherry R, et al. Adoptive cell therapy for patients with metastatic melanoma: evaluation of intensive myeloablative chemoradiation preparative regimens. J Clin Oncol 2008;26(32):5233–5239. 81. Rosenberg SA, Yang JC, Sherry RM, et al. Durable complete responses in heavily pretreated patients with metastatic melanoma using T-cell transfer immunotherapy. Clin Cancer Res 2011;17(13):4550–4557. 82. Besser MJ, Shapira-Frommer R, Itzhaki O, et al. Adoptive transfer of tumor-infiltrating lymphocytes in patients with metastatic melanoma: intent-to-treat analysis and efficacy after failure to prior immunotherapies. Clin Cancer Res 2013;19(17):4792–4800. 83. Goff SL, Dudley ME, Citrin DE, et al. Randomized, prospective evaluation comparing intensity of lymphodepletion before adoptive transfer of tumor-infiltrating lymphocytes for patients with metastatic melanoma. J Clin Oncol 2016;34(20):2389–2397. 84. Besser MJ, Shapira-Frommer R, Treves AJ, et al. Minimally cultured or selected autologous tumor-infiltrating lymphocytes after a lympho-depleting chemotherapy regimen in metastatic melanoma patients. J Immunother 2009;32(4):415–423. 85. Besser MJ, Shapira-Frommer R, Treves AJ, et al. Clinical responses in a phase II study using adoptive transfer of short-term cultured tumor infiltration lymphocytes in metastatic melanoma patients. Clin Cancer Res 2010;16(9):2646–2655. 86. Ellebaek E, Iversen TZ, Junker N, et al. Adoptive cell therapy with autologous tumor infiltrating lymphocytes and low-dose interleukin-2 in metastatic melanoma patients. J Transl Med 2012;10:169. 87. Andersen R, Donia M, Ellebaek E, et al. Long-lasting complete responses in patients with metastatic melanoma after adoptive cell therapy with tumor-infiltrating lymphocytes and an attenuated IL2 regimen. Clin Cancer Res 2016;22(15):3734–3745. 88. Radvanyi LG, Bernatchez C, Zhang M, et al. Specific lymphocyte subsets predict response to adoptive cell therapy using expanded autologous tumor-infiltrating lymphocytes in metastatic melanoma patients. Clin Cancer Res 2012;18(24):6758–6770.

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89. Gros A, Robbins PF, Yao X, et al. PD-1 identifies the patient-specific CD8+ tumor-reactive repertoire infiltrating human tumors. J Clin Invest 2014;124(5):2246–2259. 90. Chacon JA, Wu RC, Sukhumalchandra P, et al. Co-stimulation through 4-1BB/CD137 improves the expansion and function of CD8+ melanoma tumor-infiltrating lymphocytes for adoptive T-cell therapy. PLoS One 2013;8(4):e60031. 91. Noonan KA, Huff CA, Davis J, et al. Adoptive transfer of activated marrow-infiltrating lymphocytes induces measurable antitumor immunity in the bone marrow in multiple myeloma. Sci Transl Med 2015;7(288):288ra78. 92. Zhang L, Morgan RA, Beane JD, et al. Tumor-infiltrating lymphocytes genetically engineered with an inducible gene encoding interleukin-12 for the immunotherapy of metastatic melanoma. Clin Cancer Res 2015;21(10):2278– 2288. 93. Chandran SS, Somerville RPT, Yang JC, et al. Treatment of metastatic uveal melanoma with adoptive transfer of tumour-infiltrating lymphocytes: a single-centre, two-stage, single-arm, phase 2 study. Lancet Oncol 2017;18(6):792–802. 94. Linnemann C, van Buuren MM, Bies L, et al. High-throughput epitope discovery reveals frequent recognition of neo-antigens by CD4+ T cells in human melanoma. Nat Med 2015;21(1):81–85. 95. Tran E, Turcotte S, Gros A, et al. Cancer immunotherapy based on mutation-specific CD4+ T cells in a patient with epithelial cancer. Science 2014;344(6184):641–645. 96. Walker LS, Sansom DM. The emerging role of CTLA4 as a cell-extrinsic regulator of T cell responses. Nat Rev Immunol 2011;11(12):852–863. 97. Fong L, Small EJ. Anti-cytotoxic T-lymphocyte antigen-4 antibody: the first in an emerging class of immunomodulatory antibodies for cancer treatment. J Clin Oncol 2008;26(32):5275–5283. 98. Ishida Y, Agata Y, Shibahara K, et al. Induced expression of PD-1, a novel member of the immunoglobulin gene superfamily, upon programmed cell death. EMBO J 1992;11(11):3887–3895. 99. Freeman GJ, Long AJ, Iwai Y, et al. Engagement of the PD-1 immunoinhibitory receptor by a novel B7 family member leads to negative regulation of lymphocyte activation. J Exp Med 2000;192(7):1027–1034. 100. Dong H, Strome SE, Salomao DR, et al. Tumor-associated B7-H1 promotes T-cell apoptosis: a potential mechanism of immune evasion. Nat Med 2002;8(8):793–800. 101. Zou W, Chen L. Inhibitory B7-family molecules in the tumour microenvironment. Nat Rev Immunol 2008;8(6):467–477. 102. Giuroiu I, Weber J. Novel checkpoints and cosignaling molecules in cancer immunotherapy. Cancer J 2017;23(1):23–31. 103. Hodi FS, O’Day SJ, McDermott DF, et al. Improved survival with ipilimumab in patients with metastatic melanoma. N Engl J Med 2010;363(8):711–723. 104. Rosenberg SA, Yang JC, Schwartzentruber DJ, et al. Immunologic and therapeutic evaluation of a synthetic peptide vaccine for the treatment of patients with metastatic melanoma. Nat Med 1998;4(3):321–327. 105. Schwartzentruber DJ, Lawson DH, Richards JM, et al. gp100 peptide vaccine and interleukin-2 in patients with advanced melanoma. N Engl J Med 2011;364(22):2119–2127. 106. Eggermont AM, Chiarion-Sileni V, Grob JJ, et al. Adjuvant ipilimumab versus placebo after complete resection of high-risk stage III melanoma (EORTC 18071): a randomised, double-blind, phase 3 trial. Lancet Oncol 2015;16(5):522–530. 107. Eggermont AM, Chiarion-Sileni V, Grob JJ, et al. Prolonged survival in stage III melanoma with ipilimumab adjuvant therapy. N Engl J Med 2016;375(19):1845–1855. 108. Robert C, Ribas A, Wolchok JD, et al. Anti-programmed-death-receptor-1 treatment with pembrolizumab in ipilimumab-refractory advanced melanoma: a randomised dose-comparison cohort of a phase 1 trial. Lancet 2014;384(9948):1109–1117. 109. Ribas A, Puzanov I, Dummer R, et al. Pembrolizumab versus investigator-choice chemotherapy for ipilimumabrefractory melanoma (KEYNOTE-002): a randomised, controlled, phase 2 trial. Lancet Oncol 2015;16(8):908–918. 110. Ribas A, Wolchok JD, Robert C, et al. Updated clinical efficacy of the anti-PD-1 monoclonal antibody pembrolizumab (pembro, MK-3475) in 411 patients (pts) with melanoma (MEL). Pigment Cell & Melanoma Research 2014;27(6):1222–1223. 111. Robert C, Schachter J, Long GV, et al. Pembrolizumab versus ipilimumab in advanced melanoma. N Engl J Med 2015;372(26):2521–2532. 112. Robert C, Long GV, Brady B, et al. Nivolumab in previously untreated melanoma without BRAF mutation. N Engl J Med 2015;372(4):320–330. 113. Weber JS, D’Angelo SP, Minor D, et al. Nivolumab versus chemotherapy in patients with advanced melanoma

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who progressed after anti-CTLA-4 treatment (CheckMate 037): a randomised, controlled, open-label, phase 3 trial. Lancet Oncol 2015;16(4):375–384. Postow MA, Chesney J, Pavlick AC, et al. Nivolumab and ipilimumab versus ipilimumab in untreated melanoma. N Engl J Med 2015;372(21):2006–2017. Hodi FS, Chesney J, Pavlick AC, et al. Combined nivolumab and ipilimumab versus ipilimumab alone in patients with advanced melanoma: 2-year overall survival outcomes in a multicentre, randomised, controlled, phase 2 trial. Lancet Oncol 2016;17(11):1558–1568. Larkin J, Chiarion-Sileni V, Gonzalez R, et al. Combined nivolumab and ipilimumab or monotherapy in untreated melanoma. N Engl J Med 2015;373(1):23–34. Wolchok JD, Chiarion-Sileni V, Gonzalez R, et al. Overall survival with combined nivolumab and ipilimumab in advanced melanoma. N Engl J Med 2017;377(14):1345–1356. Weber J, Mandala M, Del Vecchio M, et al. Adjuvant nivolumab versus ipilimumab in resected stage III or IV melanoma. N Engl J Med 2017;377(19):1824–1835. Borghaei H, Paz-Ares L, Horn L, et al. Nivolumab versus docetaxel in advanced nonsquamous non-small-cell lung cancer. N Engl J Med 2015;373(17):1627–1639. Garon EB, Rizvi NA, Hui R, et al. Pembrolizumab for the treatment of non-small-cell lung cancer. N Engl J Med 2015;372(21):2018–2028. Leighl NB, Hellmann MD, Hui R, et al. KEYNOTE-001: 3-year overall survival for patients with advanced NSCLC treated with pembrolizumab. J Clin Oncol 2017;35(Suppl):901. Herbst RS, Baas P, Kim DW, et al. Pembrolizumab versus docetaxel for previously treated, PD-L1-positive, advanced non-small-cell lung cancer (KEYNOTE-010): a randomised controlled trial. Lancet 2016;387(10027):1540–1550. Reck M, Rodríguez-Abreu D, Robinson AG, et al. Pembrolizumab versus chemotherapy for PD-L1-positive nonsmall-cell lung cancer. N Engl J Med 2016;375(19):1823–1833. Langer CJ, Gadgeel SM, Borghaei H, et al. Carboplatin and pemetrexed with or without pembrolizumab for advanced, non-squamous non-small-cell lung cancer: a randomised, phase 2 cohort of the open-label KEYNOTE021 study. Lancet Oncol 2016;17(11):1497–1508. Rittmeyer A, Barlesi F, Waterkamp D, et al. Atezolizumab versus docetaxel in patients with previously treated nonsmall-cell lung cancer (OAK): a phase 3, open-label, multicentre randomised controlled trial. Lancet 2017;389(10066):255–265. Antonia SJ, Villegas A, Daniel D, et al. Durvalumab after chemoradiotherapy in stage III non-small-cell lung cancer. N Engl J Med 2017;377:1919–1929. Gettinger S, Rizvi NA, Chow LQ, et al. Nivolumab monotherapy for first-line treatment of advanced non-smallcell lung cancer. J Clin Oncol 2016;34(25):2980–2987. Carbone DP, Reck M, Paz-Ares L, et al. First-line nivolumab in stage IV or recurrent non-small-cell lung cancer. N Engl J Med 2017;376(25):2415–2426. Rizvi NA, Chow LQM, Borghaei H, et al. Safety and response with nivolumab (anti-PD-1; BMS-936558, ONO4538) plus erlotinib in patients (pts) with epidermal growth factor receptor mutant (EGFR MT) advanced NSCLC. J Clin Oncol 2014;32(15 Suppl):8022. Hui R, Gandhi L, Costa EC, et al. Long-term OS for patients with advanced NSCLC enrolled in the KEYNOTE001 study of pembrolizumab (pembro). J Clin Oncol 2016;34(15 Suppl):9026. Felip E, De Braud FG, Maur M, et al. Ceritinib plus nivolumab (NIVO) in patients (pts) with anaplastic lymphoma kinase positive (ALK+) advanced non-small cell lung cancer (NSCLC). J Clin Oncol 2017;35(15 Suppl):2502. Le DT, Uram JN, Wang H, et al. PD-1 blockade in tumors with mismatch-repair deficiency. N Engl J Med 2015;372(26):2509–2520. Overman MJ, McDermott R, Leach JL, et al. Nivolumab in patients with metastatic DNA mismatch repairdeficient or microsatellite instability-high colorectal cancer (CheckMate 142): an open-label, multicentre, phase 2 study. Lancet Oncol 2017;18(9):1182–1191. Motzer RJ, Escudier B, McDermott DF, et al. Nivolumab versus everolimus in advanced renal-cell carcinoma. N Engl J Med 2015;373(19):1803–1813. Motzer RJ, Tannir NM, McDermott DF, et al. Nivolumab plus ipilimumab versus sunitinib in advanced renal-cell carcinoma. N Engl J Med 2018;378:1277–1290. Ansell SM, Lesokhin AM, Borrello I, et al. PD-1 blockade with nivolumab in relapsed or refractory Hodgkin’s lymphoma. N Engl J Med 2015;372(4):311–319. Younes A, Santoro A, Shipp M, et al. Nivolumab for classical Hodgkin’s lymphoma after failure of both

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autologous stem-cell transplantation and brentuximab vedotin: a multicentre, multicohort, single-arm phase 2 trial. Lancet Oncol 2016;17(9):1283–1294. Chen R, Zinzani PL, Fanale MA, et al. Phase II study of the efficacy and safety of pembrolizumab for relapsed/refractory classic Hodgkin lymphoma. J Clin Oncol 2017;35(19):2125–2132. Seiwert TY, Burtness B, Mehra R, et al. Safety and clinical activity of pembrolizumab for treatment of recurrent or metastatic squamous cell carcinoma of the head and neck (KEYNOTE-012): an open-label, multicentre, phase 1b trial. Lancet Oncol 2016;17(7):956–965. Chow LQM, Haddad R, Gupta S, et al. Antitumor activity of pembrolizumab in bomarker-unselected patients with recurrent and/or metastatic head and neck squamous cell carcinoma: results from the phase Ib KEYNOTE-012 expansion cohort. J Clin Oncol 2016;34(32):3838–3845. Ferris RL, Blumenschein G Jr, Fayette J, et al. Nivolumab for recurrent squamous-cell carcinoma of the head and neck. N Engl J Med 2016;375(19):1856–1867. Rosenberg JE, Hoffman-Censits J, Powles T, et al. Atezolizumab in patients with locally advanced and metastatic urothelial carcinoma who have progressed following treatment with platinum-based chemotherapy: a single-arm, multicentre, phase 2 trial. Lancet 2016;387(10031):1909–1920. Balar AV, Galsky MD, Rosenberg JE, et al. Atezolizumab as first-line treatment in cisplatin-ineligible patients with locally advanced and metastatic urothelial carcinoma: a single-arm, multicentre, phase 2 trial. Lancet 2017;389(10064):67–76. Sharma P, Retz M, Siefker-Radtke A, et al. Nivolumab in metastatic urothelial carcinoma after platinum therapy (CheckMate 275): a multicentre, single-arm, phase 2 trial. Lancet Oncol 2017;18(3):312–322. Balar A, Bellmunt J, O’Donnell PH, et al. Pembrolizumab (pembro) as first-line therapy for advanced/unresectable or metastatic urothelial cancer: preliminary results from the phase 2 KEYNOTE-052 study. Ann Oncol 2016;27(Suppl 6):LBA32_PR. O’Donnell PH, Grivas P, Balar AV, et al. Biomarker findings and mature clinical results from KEYNOTE-052: first-line pembrolizumab (pembro) in cisplatin-ineligible advanced urothelial cancer (UC). J Clin Oncol 2017;35(15 suppl):4502. Bellmunt J, de Wit R, Vaughn DJ, et al. Pembrolizumab as second-line therapy for advanced urothelial carcinoma. N Engl J Med 2017;376(11):1015–1026. Powles T, O’Donnell PH, Massard C, et al. Updated efficacy and tolerability of durvalumab in locally advanced or metastatic urothelial carcinoma. J Clin Oncol 2017;35(6 Suppl):286. Patel MR, Ellerton JA, Infante JR, et al. Avelumab in patients with metastatic urothelial carcinoma: Pooled results from two cohorts of the phase 1b JAVELIN Solid Tumor trial. J Clin Oncol 2017;35(6 Suppl):330. Kaufman HL, Russell J, Hamid O, et al. Avelumab in patients with chemotherapy-refractory metastatic Merkel cell carcinoma: a multicentre, single-group, open-label, phase 2 trial. Lancet Oncol 2016;17(10):1374–1385. El-Khoueiry AB, Sangro B, Yau T, et al. Nivolumab in patients with advanced hepatocellular carcinoma (CheckMate 040): an open-label, non-comparative, phase 1/2 dose escalation and expansion trial. Lancet 2017;389(10088):2492–2502. Wainberg ZA, Jalal S, Muro K, et al. LBA28_PR—KEYNOTE-059 update: efficacy and safety of pembrolizumab alone or in combination with chemotherapy in patients with advanced gastric or gastroesophageal (G/GEJ) cancer. Ann Oncol 2017;28(Suppl 5):v605–v649. Chung HC, Schellens J, Delord J-P, et al. . Pembrolizumab treatment of advanced cervical cancer: updated results from the phase 2 KEYNOTE-158 study. J Clin Oncol 2018;36:5522. Zinzani PL, Thieblemont C, Melnichenko V, et al. Efficacy and safety of pembrolizumab in relapsed/refractory primary mediastinal large B-cell lymphoma (rrPMBCL): updated analysis of the Keynote-170 phase 2 trial. Blood 2017;130:2833. Freshwater T, Kondic A, Ahamadi M, et al. Evaluation of dosing strategy for pembrolizumab for oncology indications. J Immunother Cancer 2017;5:43. Small EJ, Fratesi P, Reese DM, et al. Immunotherapy of hormone-refractory prostate cancer with antigen-loaded dendritic cells. J Clin Oncol 2000;18(23):3894–3903. Small EJ, Schellhammer PF, Higano CS, et al. Placebo-controlled phase III trial of immunologic therapy with sipuleucel-T (APC8015) in patients with metastatic, asymptomatic hormone refractory prostate cancer. J Clin Oncol 2006;24(19):3089–3094. Kantoff PW, Higano CS, Shore ND, et al. Sipuleucel-T immunotherapy for castration-resistant prostate cancer. N Engl J Med 2010;363(5):411–422.

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18

Pharmacokinetics and Pharmacodynamics of Anticancer Drugs

Alex Sparreboom and Sharyn D. Baker

INTRODUCTION Drug selection and therapy considerations in oncology were originally solely based on observations of the effects produced.1 To overcome some of the limitations of this empirical approach and to answer questions related to considerations of dose, frequency, and duration of drug treatment, it is necessary to understand the events that follow drug administration. Preclinical in vitro and in vivo studies have shown that the magnitude of antitumor response is a function of the concentration of drug,2 and this has led to the suggestion that the therapeutic objective can be achieved by maintaining an adequate concentration at the site of action for the duration of therapy. However, drugs are rarely directly administered at their sites of action. Indeed, most anticancer drugs are given intravenously or orally and yet are expected to act in the brain, lungs, or elsewhere. Drugs must, therefore, move from the site of administration to the site of action and, moreover, distribute to all other tissues including organs that eliminate them from the body, such as the kidneys and liver. To administer drugs optimally, knowledge is needed not only of the mechanisms of drug absorption, distribution, and elimination but also of the kinetics of these processes. The treatment of human malignancies involving drugs can be divided into two pharmacologic phases, a pharmacokinetic phase in which the dose, dosage form, frequency, and route of administration are related to drug level–time relationships in the body, and a pharmacodynamic phase in which the concentration of drug at the site(s) of action is related to the magnitude of the effect(s) produced. Once both of these phases have been defined, a dosage regimen can be designed to achieve the therapeutic objective, although additional factors need to be taken into consideration (Fig. 18.1). The clinical application of this approach allows distinctions between pharmacokinetic and pharmacodynamic causes of an unusual drug response. A basic tenet of pharmacokinetics is that the magnitude of both the desired response and toxicity are functions of the drug concentration at the site(s) of action. Accordingly, therapeutic failure results when the concentration is either too low, resulting in ineffective therapy, or too high, producing unacceptable toxicity. Between these limits of concentrations lies a region associated with therapeutic success, the so-called therapeutic window. Because the concentration of a drug at the site of action can rarely be measured directly, with the exception of certain hematologic malignancies, plasma or blood is commonly measured instead as a more accessible alternative.

PHARMACOKINETIC CONCEPTS A drug’s pharmacokinetic properties can be defined by two fundamental processes affecting drug behavior over time, absorption and disposition.

Absorption Historically, most anticancer drugs have been administered intravenously; however, the use of orally administered agents is growing with the development of small-molecule targeted cancer therapeutics, such as tyrosine kinase inhibitors.3 Moreover, drugs may also be administered regionally, for example, into the pleural or peritoneal cavities,4 the cerebrospinal fluid, or intra-arterially into a vessel leading to a cancerous tissue. The process by

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which the unchanged drug moves from the site of administration to the site of measurement within the body is referred to as absorption. Loss at any site prior to the site of measurement contributes to a decrease in the apparent absorption of a drug. For an orally administered agent, this complex series of events involves disintegration of the pharmaceutical dosage form, dissolution, diffusion through gastrointestinal fluids, permeation of the gut membrane, portal circulation uptake, passage through the liver, and, finally, entry into the systemic circulation. The loss of drug as it passes for the first time through organs of elimination, such as the gastrointestinal membranes and the liver, during the absorption process is known as the first-pass effect.5 The pharmacokinetic parameter most closely associated with absorption is availability or bioavailability (F), defined as the fraction (or percentage) of the administered dose that is absorbed intact. Bioavailability can be estimated by dividing the area under the plasma concentration–time curve (AUC) achieved following extravascular administration by the AUC observed after intravenous administration and can range from 0 to 1.0 (or 0% to 100%).

Disposition Disposition is defined as all the processes that occur subsequent to absorption of a drug; by definition, the components of disposition are distribution and elimination. Distribution is the process of reversible transfer of a drug to and from the site of measurement. Any drug that leaves the site of measurement and does not return has undergone elimination, which occurs by two processes, excretion and metabolism. Excretion is the irreversible loss of the chemically unchanged drug, whereas metabolism is the conversion of drug to another chemical species. The extent of drug distribution can be determined by relating the concentration obtained with a known amount of drug in the body and is, in essence, a dilution space. The apparent volume into which a drug distributes in the body at equilibrium in called the volume of distribution (Vd) and may or may not correspond to an actual physiologic compartment. The rate and extent to which a drug distributes into various tissues depend on a number of factors, including hydrophobicity, tissue permeability, tissue-binding constants, binding to serum proteins, and local organ blood flow. Large apparent volumes of distribution are common for agents with high tissue binding or high lipid solubility, although distribution into specific body compartments may be limited by physiologic processes, such as the blood–brain barrier protecting the central nervous system or the blood–testes barrier.6 Just as Vd is needed as a parameter to relate the concentration to the amount of drug in the body, there is also a need to have a parameter to relate the concentration to the rate of drug elimination, which is known as clearance (CL). Of all pharmacokinetic parameters, CL has the most clinical relevance because it defines the key relationship between drug dose and systemic drug exposure (AUC). Derived from Vd and CL is the parameter elimination rate constant, which can be regarded as the fractional rate of drug removal. It is, however, more common to refer to the half-life than to the elimination rate constant of a drug. The half-life of a drug is a useful parameter to estimate the time required to reach steady state on a multidose schedule or during a continuous intravenous drug infusion.

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Figure 18.1 Principal determinants of dosage regimen selection for an anticancer drug.

Dose Proportionality When drug concentrations change in strict proportionality to the dose of drug administered, then the condition of dose proportionality (or linear pharmacokinetics) holds. If doubling the dose exactly doubles the plasma concentration or AUC, then pharmacokinetic parameters, such as Vd and CL, are constant and remain independent of dose and concentration. By strict definition, drugs with linear pharmacokinetics are dose proportional. Dose proportionality is clinically important because it means that dose adjustments will generate predictable changes in systemic drug exposure. For drugs that lack dose proportionality, Vd and CL will demonstrate concentration or time dependence, or both, making it difficult to predict the effect of dose adjustments on drug concentration (Fig. 18.2). Factors that can contribute to a lack of dose proportional pharmacokinetics include saturable oral absorption, capacity-limited distribution or protein binding, and/or saturable metabolism.7 Dose proportionality of anticancer agents is typically assessed in phase I dose-escalation trials in which small groups of patients are treated at a single dose level using a parallel study design, although the statistical power of such studies to detect deviations from dose proportionality is poor. An alternative, more robust study design is a crossover study in which each patient receives a low dose, an intermediate dose, and a high dose over consecutive cycles of treatment.8 However, such studies are relatively rare in oncology because of the required use of low, potentially ineffective doses, which may raise ethical concerns for patients.

PHARMACODYNAMIC CONCEPTS Pharmacodynamic models relate clinical drug effects with drug dose, concentration, or other pharmacokinetic parameters indicative of drug exposures (Table 18.1). In oncology, pharmacodynamic variability may account for substantial differences in clinical outcomes, even when systemic exposures are uniform. Variability in pharmacodynamic response may be heavily influenced by clinical covariates such as age, gender, prior chemotherapy, prior radiotherapy, concomitant medications, or other variables.9 The pharmacokinetic parameters that are most often correlated with drug effects are markers of drug exposure, such as AUC. In general, the specific parameter used as the independent variable in a pharmacodynamic analysis depends on the particular characteristics of the study drug.

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Figure 18.2 Effect of drug dose on systemic exposure to paclitaxel following intravenous (IV) or oral administration in patients with cancer. Data are expressed as mean values (circles) and standard deviation (error bars). The dashed line indicates the hypothetical dose-proportional increase in the area under the plasma concentration time curve (AUC). (Data derived from van Zuylen L, Karlsson MO, Verweij J, et al. Pharmacokinetic modeling of paclitaxel encapsulation in Cremophor EL micelles. Cancer Chemother Pharmacol 2001;47[4]:309–318; Malingré MM, Terwogt JM, Beijnen JH, et al. Phase I and pharmacokinetic study of oral paclitaxel. J Clin Oncol 2000;18[12]:2468– 2475, respectively.) TABLE 18.1

Examples of Systemic Exposure as a Marker of Anticancer Drug Effects Drug

Side Effect

Response/Survival

Carboplatin

Thrombocytopenia

Ovarian cancer

Cisplatin

Nephrotoxicity

Head and neck cancer

Cyclophosphamide

Cardiotoxicity



Docetaxel

Neutropenia

Non–small-cell lung cancer

Doxorubicin

Neutropenia



Epirubicin

Neutropenia



Erlotinib

Skin rash

Non–small-cell lung and head and neck cancers

Etoposide



Non–small-cell lung cancer

5-Fluorouracil

Diarrhea, mucositis

Head and neck cancer

Imatinib



Chronic myeloid leukemia

Irinotecan

Diarrhea, neutropenia



6-Mercaptopurine



Acute lymphoblastic leukemia

Methotrexate

Mucositis

Acute lymphoblastic leukemia

Nilotinib

Anemia, QT interval prolongation



Paclitaxel

Neutropenia



Sorafenib

Hypertension, hand-foot skin reaction

Renal cell cancer

Sunitinib

Neutropenia

Renal cell cancer

Teniposide



Lymphoma

In oncology, pharmacodynamic studies of drug effects have most often focused on toxicity end points. Continuous response variables, such as the percent fall in the absolute blood count from baseline, are easily analyzed using nonlinear regression methods. Dose-limiting neutropenia has been frequently analyzed using a sigmoid maximum effect model described by the modified Hill equation. The pharmacodynamic analysis of

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subjectively graded clinical end points, such as common toxicity criteria scores on a 4-point scale, may require more sophisticated statistical methods.10 Logistical regression methods have been used to model these types of categorical (ordinal) response or outcome variables. Physiologic pharmacodynamic models describing the severity and time course of drug-related myelosuppression have been derived using population mixed-effect methods for several agents.11 The ability of these models to predict both the severity and duration of drug-induced neutropenia substantially enhances their clinical usefulness. In contrast to small-molecule therapeutics, large-molecule therapeutics such as monoclonal antibodies may not demonstrate toxicities directly related to dose levels. For these agents, a thorough understanding of the pharmacokinetic/pharmacodynamic relationships using modeling approaches may be critical for optimal dose selection.12 The antitumor activity of certain chemotherapeutic agents is highly schedule dependent. For such drugs, the dose fractionated over several days can produce a different antitumor response or toxicity profile compared with the same dose given over a shorter period. For example, the efficacy of etoposide in the treatment of small-cell lung cancer is markedly increased when an identical total dose of etoposide is administered by a 5-day divideddose schedule rather than a 24-hour infusion. Pharmacokinetic analysis in that study showed that both schedules produced very similar overall drug exposure (as measured by AUC) but that the divided-dose schedule produced twice the duration of exposure to an etoposide plasma concentration of >1 μg/mL. This finding has led to the use of prolonged oral administration of etoposide to treat patients with cancer. Similar schedule dependence has been demonstrated for a number of other anticancer agents, notably paclitaxel.13 For these agents, the variability in clinically tested treatment schedules is enormous, ranging from short intravenous infusions of less than 30 minutes to 21-day or even 7-week continuous infusion administrations, with large differences in experienced toxicity profiles.

VARIABILITY IN PHARMACOKINETICS/ PHARMACODYNAMICS There is often a marked variation in drug handling between individual patients, resulting in variability in pharmacokinetic parameters (Fig. 18.3), which will often lead to variability in the pharmacodynamic effects of a given dose of a drug.14 That is, an identical dose of drug may result in acceptable toxicity in one patient, and unacceptable and possibly life-threatening toxicity in another, or a clinical response in one individual and cancer progression in another. The principal underlying sources of this interindividual pharmacokinetic/pharmacodynamic variability are discussed in the following paragraphs.

Body Size and Body Composition The traditional method of individualizing anticancer drug dosage is by using body surface area (BSA).15 However, the usefulness of normalizing an anticancer drug dose to BSA in adults has been questioned because, for many drugs, there is no relationship between BSA and CL.16 Likewise, attempts to replace BSA as a size metric in dose calculation with alternate descriptors such as lean body weight, either in an average population or in individuals at the outer extremes of weight (i.e., frail, severely obese patients), have failed for many anticancer agents.17 It should be pointed out that BSA is a much more important consideration in drug dose calculation for pediatric patients as compared to adults because of the larger size range in the former population.18 Based in part on the failure to reduce interindividual pharmacokinetic variability with the use of BSA normalization to obtain a starting dose, many of the more recently developed molecularly targeted agents are currently administered using a flatfixed dose irrespective of an individual’s BSA.17

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Figure 18.3 Interindividual pharmacokinetic variability of select cytotoxic agents and molecularly targeted agents expressed as a percent coefficient of variation (%CV) in apparent (oral) clearance. IV, intravenous. (Data derived from Mathijssen RH, de Jong FA, Loos WJ, et al. Flat-fixed dosing versus body surface area based dosing of anticancer drugs in adults: does it make a difference? Oncologist 2007;12[8]:913–923, and publicly available prescribing information.)

Age Changes in body composition and organ function at the extremes of age can affect both drug disposition and drug effect. For example, maturational processes in infancy may alter the absorption and distribution of drugs as well as change the capacity for drug metabolism and excretion. The importance of understanding the influence of age on the pharmacokinetics and pharmacodynamics of individual anticancer agents has increased steadily as treatment for the malignancies of infants, adolescents, and the elderly has advanced.19 Although pediatric cancers remain rare compared with cancers in adults and the elderly population, in particular, optimizing treatment in a patient group with a high cure rate and a long expected survival becomes critical to minimize the incidence of preventable late complications while maintaining efficacy.

Pathophysiologic Changes Effects of Disease Pathophysiologic changes associated with particular malignancies may cause dramatic alterations in drug disposition. For example, increases in the clearance of both antipyrine and lorazepam were noted after remission induction compared with the time of diagnosis in children with acute lymphoblastic leukemia (ALL). The clearance of unbound teniposide is lower in children with ALL in relapse than during first remission. Because leukemic infiltration of the liver at the time of diagnosis is common, drugs metabolized by the liver may have a reduced clearance, as has been documented in preclinical models. Furthermore, in mouse models, certain tumors elicited an acute phase response that coincided with downregulation of human CYP3A4 in the liver as well as the mouse ortholog Cyp3a11.20 The reduction of murine hepatic Cyp3a gene expression in tumor-bearing mice resulted in decreased Cyp3a protein expression and, consequently, a significant reduction in Cyp3a-mediated metabolism of midazolam. These findings support the

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possibility that tumor-derived inflammation may alter the pharmacokinetic and pharmacodynamic properties of CYP3A4 substrates, leading to reduced metabolism of drugs in humans.21 This supports a possible need for disease-specific design of early clinical trials with anticancer drugs, as has been recommended for docetaxel.22

Effects of Renal Impairment The potential impact of pathophysiologic status on interindividual pharmacokinetic variability can be due to either the disease itself or to a dysfunction of specific organs involved in drug elimination. For example, if urinary excretion is an important elimination route for a given drug, any decrement in renal function could lead to decreased drug clearance, which may result in drug accumulation and toxicity.23 Therefore, it would be logical to decrease the drug dose relative to the degree of impaired renal function in order to maintain plasma concentrations within a target therapeutic window. The best known example of this a priori dose adjustment of an anticancer agent remains carboplatin, which is excreted renally almost entirely by glomerular filtration. Various strategies have been developed to estimate carboplatin doses based on renal function among patients, either using creatinine clearance24 or glomerular filtration rates as measured by a radioisotope method.25 The application of these procedures has led to a substantial reduction in pharmacokinetic variability, such that carboplatin is currently one of the few drugs routinely administered to achieve a target exposure rather than on a milligram per square meter or milligram per kilogram basis. The U.S. Food and Drug Administration (FDA) has developed a guidance on the impact of renal impairment on the pharmacokinetics, dosing, and labeling of drugs.26 The impact of this guidance has been assessed following a survey of 94 new drug applications for small-molecule new molecular entities approved over the years 2003 to 2007. The survey results indicated that 41% of the applications that included renal impairment study data resulted in a recommendation of dose adjustment in renal impairment. Interestingly, the survey results provided evidence that renal impairment can affect the pharmacokinetics of drugs that are predominantly eliminated by nonrenal processes such as metabolism and/or active transport. The latter finding supports the FDA recommendation to evaluate pharmacokinetic/pharmacodynamic alterations in renal impairment for those drugs that are predominantly eliminated by nonrenal processes, in addition to those that are mainly excreted unchanged by the kidneys. A striking example of a drug in the former category is imatinib, an agent that is predominantly eliminated by hepatic pathways but where predialysis renal impairment is associated with dramatically reduced drug clearance, presumably due to a transporter-mediated process.

Effects of Hepatic Impairment In contrast to the predictable decline in renal clearance of drugs when glomerular filtration is impaired, it is difficult to make general predictions on the effect of impaired liver function on drug clearance. The major problem is that commonly applied criteria to establish hepatic impairment are typically not good indicators of drug-metabolizing enzyme activity and that several alternative hepatic function tests, such as indocyanine green and antipyrine, have relatively limited value in predicting anticancer drug pharmacokinetics. An alternative dynamic measure of liver function has been proposed, which is based on totaled values (scored to the World Health Organization [WHO] grading system) of serum bilirubin, alkaline phosphatase, and either alanine aminotransferase or aspartate aminotransferase to give a hepatic dysfunction score.27 Based on pharmacokinetic studies in patients with normal and impaired hepatic function, guidelines have been proposed for dose adjustments of several agents when administered to patients with severe liver dysfunction. It should be emphasized that no uniform criteria have been used in the conduct of these studies and that, ultimately, substantial advances could be made through an a priori determination of the hepatic activity of enzymes of pertinent relevance to the chemotherapeutic drug(s) of interest, as has been done for docetaxel.28

Effects of Serum Proteins The binding of drugs to serum proteins, particularly those that are highly bound, may also have significant clinical implications for a therapeutic outcome. Although protein binding is a major determinant of drug action, it is clearly only one of a myriad of factors that influence the disposition of anticancer drugs. The extent of protein binding is a function of drug and protein concentrations, the affinity constants for the drug–protein interaction, and the number of protein-binding sites per class of binding site. Because only the unbound (or free) drug in plasma water is available for distribution, the therapeutic response will correlate with free drug concentration rather than total drug concentration. Several clinical situations, including liver and renal disease, can significantly decrease the extent of serum binding and may lead to higher free drug concentrations and a possible risk of

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unexpected toxicity, although the total (free plus bound forms) plasma drug concentrations are unaltered.29 It is important to realize, however, that after therapeutic doses of most anticancer drugs, binding to serum proteins is independent of drug concentration, suggesting that the total plasma concentration is reflective of the unbound concentration. For some anticancer agents, including etoposide and paclitaxel, however, protein binding is highly dependent on dose and schedule.

Sex Dependence A number of pharmacokinetic analyses have suggested that male gender is positively correlated with the maximum elimination capacity of various anticancer drugs (e.g., paclitaxel) or with increased clearance (e.g., imatinib) compared with female gender.30 These observations have added to a growing body of evidence that the pharmacokinetic profile of various anticancer drugs exhibits significant sexual dimorphism, which is rarely considered in the design of clinical trials during oncology drug development.

Drug Interactions Coadministration of Other Chemotherapeutic Drugs Favorable and unfavorable interactions between drugs must be considered in developing combination regimens. These interactions may influence the effectiveness of each of the components of the combination and typically occur when the pharmacokinetic profile of one drug is altered by the other. Such interactions are important in the design of trials evaluating drug combinations because, occasionally, the outcome of concurrent drug administration is diminished therapeutic efficacy or increased toxicity of one or more of the administered agents. Although a recent survey indicated that clinically significant pharmacokinetic interactions are relatively rare in phase I trials of oncology drug combinations,31 interactions appear to be more common for combinations of tyrosine kinase inhibitors with cytotoxic chemotherapeutics.32

Coadministration of Nonchemotherapeutic Drugs Many prescription and over-the-counter medications have the potential to cause interactions with anticancer agents by altering their pharmacokinetic characteristics and leading to clinically significant phenotypes. Most clinically relevant drug interactions in this category are due to changes in metabolic routes related to an altered expression or function of cytochrome P450 (CYP) isozymes. This class of enzymes, particularly the CYP3A4 isoform, is responsible for the oxidation of a large proportion of currently approved anticancer drugs. Elevated CYP activity (induction), translated into a more rapid metabolic rate, may result in a decrease in plasma concentrations and to a loss of therapeutic effect. For example, anticonvulsant drugs such as phenytoin, phenobarbital, and carbamazepine can induce drug-metabolizing enzymes and thereby increase the clearance of various anticancer agents.14 Conversely, the suppression (inhibition) of CYP activity, for example with ketoconazole,33 may trigger a rise in plasma concentrations and can lead to exaggerated toxicity commensurate with overdose. It should be born in mind that several pharmacokinetic parameters could be altered simultaneously. Especially in the development of anticancer agents given by the oral route, oral bioavailability plays a crucial role5; this parameter is contingent on adequate absorption and the circumvention of intestinal and, subsequently, hepatic metabolism of the drug. It has been suggested that the prevalence of drug–drug interactions is particularly high in cancer patients receiving oral chemotherapy,34 especially for agents that are weak bases that exhibit pH-dependent solubility.35 An additional consideration is related to a possible influence of food intake on the extent of drug absorption after oral administration, which can increase, decrease, or remain unchanged depending on specific physicochemical properties of the drug in question (Table 18.2). The relatively narrow therapeutic index of most of these agents means that significant inter- and intrapatient variability would predispose some individuals to excessive toxicity or, conversely, inadequate efficacy. TABLE 18.2

Effect of Food on Exposure to Select Oral Anticancer Agents Manufacturer’s

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Drug

Food

Effect on Drug Exposure

Recommendations

Abiraterone

High-fat meal

↑ AUC 1,000%

Without food

Dasatinib

High-fat meal

↑ AUC 14%

With or without food

Erlotinib

High-fat, high-calorie breakfast

Single dose, ↑AUC 200% Multiple dose, ↑AUC 37%–66%

Without fooda

Gefitinib

High-fat breakfast

↓ AUC 14%, ↓ Cmax 35%

With or without food



High-fat breakfast

↑ AUC 32%, ↑ Cmax 35%



Imatinib

High-fat meal

No change

With food and a large glass of waterb





Variability (%CV) ↓ 37%



Lapatinib

Low-fat meal (5% fat, 500 calories)

↑ AUC 167%, ↑ Cmax 142%

Without foodc



High-fat meal (50% fat, 1,000 calories)

↑ AUC 325%, ↑ Cmax 203%



Nilotinib

High-fat meal

↑ AUC 82%

Without food

Sorafenib

Moderate-fat meal (30% fat, 700 calories)

No change in bioavailability

Without food



High-fat meal (50% fat, 900 calories)

↓ Bioavailability 29%



Sunitinib

High-fat, high-calorie meal

↑ AUC 18%

With or without food

Everolimus

High-fat meal

↓ AUC 16%, ↓ Cmax 60%

With or without food

Vismodegib

High-fat meal

↑ AUC 74% for single dose; no effect at steady-state

With or without food

Vorinostat

High-fat meal

↑ AUC 37%

With foodd

a Recommended without food because the approved dose is the maximum tolerated dose. b Recommended with food to reduce nausea. c Recommended without food to achieve consistent drug exposure; was taken without food in clinical trials. d

Was taken with food in clinical trials. AUC, area under the plasma concentration-time curve; Cmax, maximum plasma concentration; %CV, percent coefficient of variation.

Coadministration of Complementary and Alternative Medicine Surveys within the past decade estimate the prevalence of complementary and alternative medicine (CAM) use in oncology patients to be as high as 87%, and in many cases, the treating physician is not aware of the patient’s CAM use.36 With a larger number of participants to phase I clinical trials using herbal treatments combined with allopathic therapies, the risk for herb–drug interactions is a growing concern, and there is an increasing need to understand possible adverse drug interactions in oncology at the early stages of drug development. A number of clinically important pharmacokinetic interactions involving CAM and cancer drugs have now been recognized, although causal relationships have not always been established. Most of the observed interactions point to the herbs affecting several isoforms of the CYP family, either through inhibition or induction. In the context of chemotherapeutic drugs, St. John’s wort, garlic, milk thistle, and Echinacea have been formally evaluated for their pharmacokinetic drug interaction potential in cancer patients. However, various other herbs have the potential to significantly modulate the expression and/or activity of drug- metabolizing enzymes and drug transporters (Table 18.3), including ginkgo biloba, ginseng, and kava.36 Because of the high prevalence of herbal medicine use, physicians should include herb usage in their routine drug histories in order to have an opportunity to outline to individual patients which potential hazards should be taken into consideration prior to participation in a clinical trial. TABLE 18.3

Effects of Complementary and Alternative Medicine on the Activity of Enzymes and Transporters of Relevance to Anticancer Drugs Botanical

Concurrent Chemotherapy/Condition (Suspected Effect)

Ephedra

Avoid with all cardiovascular chemotherapy (synergistic increase in blood pressure)

Ginkgo biloba

Caution with camptothecins, cyclophosphamide, TK inhibitors, epipodophyllotoxins, taxanes, and vinca alkaloids (CYP3A4 and CYP2C19 inhibition); discourage with

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alkylating agents, antitumor antibiotics, and platinum analogs (free-radical scavenging) Ginseng

Discourage in patients with estrogen receptor–positive breast cancer and endometrial cancer (stimulation of tumor growth)

Green tea

Discourage with erlotinib and pazopanib (CYP1A2 induction)

Japanese arrowroot

Avoid with methotrexate (ABC and OAT transporter inhibition)

St. John’s wort

Avoid with all concurrent chemotherapy (CYP2B6, CYP2C9, CYP2C19, CYP2E1, CYP3A4, and ABCB1 induction)

Valerian

Caution with tamoxifen (CYP2C9 inhibition), cyclophosphamide, and teniposide (CYP2C19 inhibition)

Kava

Avoid in all patients with preexisting liver disease, with evidence of hepatic injury (herbinduced hepatotoxicity), and/or in combination with hepatotoxic chemotherapy; caution with camptothecins, cyclophosphamide, TK inhibitors, epipodophyllotoxins, taxanes, and vinca alkaloids (CYP3A4 induction) TK, tyrosine kinase; CYP, cytochrome P450; ABC, adenosine triphosphate–-binding cassette; OAT, organic anion transporter.

Inherited Genetic Factors The discipline of pharmacogenetics describes differences in the pharmacokinetics and pharmacodynamics of drugs as a result of inherited variation in drug metabolizing enzymes, drug transporters, and drug targets between patients.37 These inherited variations are occasionally responsible for extensive interpatient variability in drug exposure or effects. Severe toxicity might occur in the absence of a typical metabolism of active compounds, whereas the therapeutic effect of a drug could be diminished in the case of an absence of activation of a prodrug, such as irinotecan. The importance and detectability of polymorphisms for a given enzyme or transporter depend on the contribution of the variant gene product to pharmacologic response, the availability of alternative pathways of elimination, and the frequency of occurrence of the variant allele. Although many substrates have been identified for the known polymorphic drug-metabolizing enzymes and transporters, the contribution of a genetically determined source of interindividual pharmacokinetic variability has been established for only a few cancer chemotherapeutic agents. Most of these cases involve agents for which elimination is critically dependent on a rate-limiting breakdown by a polymorphic enzyme (e.g., 6-mercaptopurine by thiopurine- Smethyltransferase; 5-fluorouracil by dihydropyrimidine dehydrogenase) or when a polymorphic enzyme is involved in the formation of a toxic metabolite (e.g., tamoxifen by CYP2D6).38 In addition to drug metabolism, pharmacokinetic processes are highly dependent on the interplay with drug transport in organs such as the intestines, kidneys, and liver. Genetically determined variation in drug transporter function or expression is now increasingly recognized to have a significant role as a determinant of intersubject variability in response to various commonly prescribed drugs. The most extensively studied class of drug transporters are those encoded by the family of adenosine triphosphate (ATP)–binding cassette (ABC) genes, some of which also play a role in the resistance of malignant cells to anticancer agents. Among the 48 known ABC gene products, ABCB1 (P-glycoprotein), ABCC1 (multidrug resistance–associated protein 1 [MRP1]) and its homologue ABCC2 (multidrug resistance–associated protein 2 [MRP2]; canalicular multispecific organic anion transporter [cMOAT]), and ABCG2 (breast cancer resistance protein [BCRP]) are known to influence the oral absorption and disposition of a wide variety of drugs. As a result, the expression levels of these proteins in humans have important consequences for an individual’s susceptibility to certain anticancer drug–induced side effects, interactions, and treatment efficacy, for example, in the case of genetic variation in ABCG2 in relation to gefitinib-induced diarrhea.39 Similar to the discoveries of functional genetic variations in drug efflux transporters of the ABC family, there have been considerable advances in the identification of inherited variants in transporters that facilitate cellular drug uptake in tissues that play an important role in drug elimination, such as the liver (Fig. 18.4). Among these, members of the organic anion-transporting polypeptides (OATP), organic anion transporters (OAT), and organic cation transporters (OCT) can mediate the cellular uptake of a large number of structurally divergent compounds. Accordingly, functionally relevant polymorphisms in these influx transporters may contribute to interindividual and interethnic variability in drug disposition and response,40 for example, in the case of the impact of polymorphic variants in the OCT1 gene SLC22A1 on the survival of patients with chronic myeloid leukemia receiving treatment with imatinib.

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Figure 18.4 Common mechanisms for possible interactions between xenobiotics and anticancer drugs in the liver. OCT1, organic cation transporter 1; DME, drug-metabolizing enzyme(s); NTCP, sodium-taurocholate cotransporting polypeptide; OAT2, organic anion transporter 2.

DOSE ADAPTATION USING PHARMACOKINETIC/PHARMACODYNAMIC PRINCIPLES Therapeutic Drug Monitoring Prolonged infusion schedules of anticancer drugs offer a very convenient setting for dose adaptation in individual patients. At the time required to achieve steady-state concentration, it is possible to modify the infusion rate for the remainder of the treatment course if a relationship is known between this steady-state concentration and a desired pharmacodynamic end point. This method has been successfully used to adapt the dose during continuous infusions of 5-fluorouracil and etoposide, and for repeated oral administration of etoposide or repeated intravenous administration of cisplatin. Methotrexate plasma concentrations are routinely monitored to identify patients at high risk of toxicity and to adjust leucovorin rescue in patients with delayed drug excretion. This monitoring has significantly reduced the incidence of serious toxicity, including toxic death, and in fact, has improved outcome by eliminating unacceptably low systemic exposure levels.41 Therapeutic drug monitoring has also been applied to or is currently under investigation for several more recently developed anticancer drugs, including imatinib.42

Feedback-Controlled Dosing It remains to be determined how information on interindividual pharmacokinetic variability can eventually be used to devise an optimal dosage regimen of a drug for the treatment of a given disease in an individual patient. Obviously, the desired objective would be most efficiently achieved if the individual’s dosage requirements could be calculated prior to administering the drug. Although this ideal cannot be met completely in clinical practice, with the notable exception of carboplatin, some success may be achieved by adopting feedback-controlled dosing.

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In the adaptive dosage with feedback control, population-based predictive models are used initially but allow the possibility of dosage alteration based on feedback revision. In this approach, patients are first treated with standard dose, and, during treatment, pharmacokinetic information is estimated by a limited-sampling strategy and compared with that predicted from the population model with which treatment was initiated. On the basis of the comparison, more patient-specific pharmacokinetic parameters are calculated, and dosage is adjusted accordingly to maintain the target exposure measure producing the desired pharmacodynamic effect. Despite its mathematical complexity, this approach may be the only way to deliver the desired and precise exposure of an anticancer agent. The study of population pharmacokinetics seeks to identify the measurable factors that cause changes in the dose–concentration relationship and the extent of these alterations so that if these are associated with clinically significant shifts in the therapeutic index, dosage can be appropriately modified in the individual patient. It is obvious that a careful collection of data during the development of drugs and subsequent analyses could be helpful to collect some essential information on the drug. Unfortunately, important information is often lost by failing to analyze these data or due to the fact that the relevant samples or data were never collected. Historically, this has resulted in the notion that tools for the identification of patient population subgroups are inadequate for most of the currently approved anticancer drugs. However, the use of population pharmacokinetic models is increasingly studied in an attempt to accommodate as much of the pharmacokinetic variability as possible in terms of measurable characteristics. This type of analysis has been conducted for a number of clinically important anticancer drugs, and has provided mathematical equations based on morphometric, demographic, phenotypic enzyme activity, and/or physiologic characteristics of patients, in order to predict drug clearance with an acceptable degree of precision and bias.43–45

REFERENCES 1. DeVita VT Jr, Chu E. A history of cancer chemotherapy. Cancer Res 2008;68(21):8643–8653. 2. Lieu CH, Tan AC, Leong S, et al. From bench to bedside: lessons learned in translating preclinical studies in cancer drug development. J Natl Cancer Inst 2013;105(19):1441–1456. 3. Jeon JY, Sparreboom A, Baker SD. Kinase inhibitors: the reality behind the success. Clin Pharmacol Ther 2017;102(5):726–730. 4. Hasovits C, Clarke S. Pharmacokinetics and pharmacodynamics of intraperitoneal cancer chemotherapeutics. Clin Pharmacokinet 2012;51(4):203–224. 5. DeMario MD, Ratain MJ. Oral chemotherapy: rationale and future directions. J Clin Oncol 1998;16(7):2557–2567. 6. Deeken JF, Loscher W. The blood-brain barrier and cancer: transporters, treatment, and Trojan horses. Clin Cancer Res 2007;13(6):1663–1674. 7. Malingré MM, Terwogt JM, Beijnen JH, et al. Phase I and pharmacokinetic study of oral paclitaxel. J Clin Oncol 2000;18(12):2468–2475. 8. van Zuylen L, Karlsson MO, Verweij J, et al. Pharmacokinetic modeling of paclitaxel encapsulation in Cremophor EL micelles. Cancer Chemother Pharmacol 2001;47(4):309–318. 9. Karlsson MO, Molnar V, Bergh J, et al. A general model for time-dissociated pharmacokinetic-pharmacodynamic relationship exemplified by paclitaxel myelosuppression. Clin Pharmacol Ther 1998;63(1):11–25. 10. Xie R, Mathijssen RH, Sparreboom A, et al. Clinical pharmacokinetics of irinotecan and its metabolites in relation with diarrhea. Clin Pharmacol Ther 2002;72(3):265–275. 11. Minami H, Sasaki Y, Saijo N, et al. Indirect-response model for the time course of leukopenia with anticancer drugs. Clin Pharmacol Ther 1998;64(5):511–521. 12. Keizer RJ, Huitema AD, Schellens JH, et al. Clinical pharmacokinetics of therapeutic monoclonal antibodies. Clin Pharmacokinet 2010;49(8):493–507. 13. Gelderblom H, Mross K, ten Tije AJ, et al. Comparative pharmacokinetics of unbound paclitaxel during 1- and 3hour infusions. J Clin Oncol 2002;20(2):574–581. 14. Undevia SD, Gomez-Abuin G, Ratain MJ. Pharmacokinetic variability of anticancer agents. Nat Rev Cancer 2005;5(6):447–458. 15. Gurney H. Dose calculation of anticancer drugs: a review of the current practice and introduction of an alternative. J Clin Oncol 1996;14(9):2590–2611. 16. Baker SD, Verweij J, Rowinsky EK, et al. Role of body surface area in dosing of investigational anticancer agents in adults, 1991–2001. J Natl Cancer Inst 2002;94(24):1883–1888. 17. Sparreboom A, Wolff AC, Mathijssen RH, et al. Evaluation of alternate size descriptors for dose calculation of anticancer drugs in the obese. J Clin Oncol 2007;25(30):4707–4713.

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18. Bartelink IH, Rademaker CM, Schobben AF, et al. Guidelines on paediatric dosing on the basis of developmental physiology and pharmacokinetic considerations. Clin Pharmacokinet 2006;45(11):1077–1097. 19. Veal GJ, Hartford CM, Stewart CF. Clinical pharmacology in the adolescent oncology patient. J Clin Oncol 2010;28(32):4790–4799. 20. Charles KA, Rivory LP, Brown SL, et al. Transcriptional repression of hepatic cytochrome P450 3A4 gene in the presence of cancer. Clin Cancer Res 2006;12(24):7492–7497. 21. Moore MM, Chua W, Charles KA, et al. Inflammation and cancer: causes and consequences. Clin Pharmacol Ther 2010;87(4):504–508. 22. Franke RM, Carducci MA, Rudek MA, et al. Castration-dependent pharmacokinetics of docetaxel in patients with prostate cancer. J Clin Oncol 2010;28(30):4562–4567. 23. Rahman A, White RM. Cytotoxic anticancer agents and renal impairment study: the challenge remains. J Clin Oncol 2006;24(4):533–536. 24. Egorin MJ, Van Echo DA, Olman EA, et al. Prospective validation of a pharmacologically based dosing scheme for the cis-diamminedichloroplatinum(II) analogue diamminecyclobutanedicarboxylatoplatinum. Cancer Res 1985;45(12 Pt 1):6502–6506. 25. Calvert AH, Newell DR, Gumbrell LA, et al. Carboplatin dosage: prospective evaluation of a simple formula based on renal function. J Clin Oncol 1989;7(11):1748–1756. 26. Huang SM, Temple R, Xiao S, et al. When to conduct a renal impairment study during drug development: US Food and Drug Administration perspective. Clin Pharmacol Ther 2009;86(5):475–479. 27. Twelves C, Glynne-Jones R, Cassidy J, et al. Effect of hepatic dysfunction due to liver metastases on the pharmacokinetics of capecitabine and its metabolites. Clin Cancer Res 1999;5(7):1696–1702. 28. Hooker AC, Ten Tije AJ, Carducci MA, et al. Population pharmacokinetic model for docetaxel in patients with varying degrees of liver function: incorporating cytochrome P4503A activity measurements. Clin Pharmacol Ther 2008;84(1):111–118. 29. Sparreboom A, Nooter K, Loos WJ, et al. The (ir)relevance of plasma protein binding of anticancer drugs. Neth J Med 2001;59(4):196–207. 30. Gardner ER, Burger H, van Schaik RH, et al. Association of enzyme and transporter genotypes with the pharmacokinetics of imatinib. Clin Pharmacol Ther 2006;80(2):192–201. 31. Wu K, House L, Ramírez J, et al. Evaluation of utility of pharmacokinetic studies in phase I trials of two oncology drugs. Clin Cancer Res 2013;19(21):6039–6043. 32. Hu S, Mathijssen RH, de Bruijn P, et al. Inhibition of OATP1B1 by tyrosine kinase inhibitors: in vitro-in vivo correlations. Br J Cancer 2014;110(4):894–898. 33. Kehrer DF, Mathijssen RH, Verweij J, et al. Modulation of irinotecan metabolism by ketoconazole. J Clin Oncol 2002;20(14):3122–3129. 34. van Leeuwen RW, Brundel DH, Neef C, et al. Prevalence of potential drug-drug interactions in cancer patients treated with oral anticancer drugs. Br J Cancer 2013;108(5):1071–1078. 35. Budha NR, Frymoyer A, Smelick GS, et al. Drug absorption interactions between oral targeted anticancer agents and PPIs: is pH-dependent solubility the Achilles heel of targeted therapy? Clin Pharmacol Ther 2012;92(2):203– 213. 36. Sparreboom A, Cox MC, Acharya MR, et al. Herbal remedies in the United States: potential adverse interactions with anticancer agents. J Clin Oncol 2004;22(12):2489–2503. 37. Wheeler HE, Maitland ML, Dolan ME, et al. Cancer pharmacogenomics: strategies and challenges. Nat Rev Genet 2013;14(1):23–34. 38. Huang RS, Ratain MJ. Pharmacogenetics and pharmacogenomics of anticancer agents. CA Cancer J Clin 2009;59(1):42–55. 39. Cusatis G, Gregorc V, Li J, et al. Pharmacogenetics of ABCG2 and adverse reactions to gefitinib. J Natl Cancer Inst 2006;98(23):1739–1742. 40. Sprowl JA, Mikkelsen TS, Giovinazzo H, et al. Contribution of tumoral and host solute carriers to clinical drug response. Drug Resist Updat 2012;15(1–2):5–20. 41. Evans WE, Relling MV, Rodman JH, et al. Conventional compared with individualized chemotherapy for childhood acute lymphoblastic leukemia. N Engl J Med 1998;338(8):499–505. 42. Larson RA, Druker BJ, Guilhot F, et al. Imatinib pharmacokinetics and its correlation with response and safety in chronic-phase chronic myeloid leukemia: a subanalysis of the IRIS study. Blood 2008;111(8):4022–4028. 43. Bruno R, Hille D, Riva A, et al. Population pharmacokinetics/pharmacodynamics of docetaxel in phase II studies in patients with cancer. J Clin Oncol 1998;16(1):187–196.

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44. Gallo JM, Laub PB, Rowinsky EK, et al. Population pharmacokinetic model for topotecan derived from phase I clinical trials. J Clin Oncol 2000;18(12):2459–2467. 45. Li J, Karlsson MO, Brahmer J, et al. CYP3A phenotyping approach to predict systemic exposure to EGFR tyrosine kinase inhibitors. J Natl Cancer Inst 2006;98(23):1714–1723.

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19

Pharmacogenomics Christine M. Walko and Howard L. McLeod

INTRODUCTION The evolution of understanding cancer biology has yielded many advances that have been translated into cancer treatment. Application of this knowledge has allowed for a shift in chemotherapeutics from traditional cytotoxic agents that worked by killing both healthy and malignant fast-growing cells to chemical and biologic therapies aimed at targeting a specific gene or pathway critical to the particular cancer being treated.1 This age of pathwaydirected therapy has been made possible by the increased availability and feasibility of high throughput technology able to provide comprehensive and clinically useful molecular characterization of tumors. Translation of these efforts has resulted in improved degrees of disease control for many common cancers including breast, colorectal, lung, and melanoma as well as long-term survival benefits for chronic myelogenous leukemia (CML), gastrointestinal stromal tumors (GIST), and childhood acute lymphoblastic leukemia (ALL).2 Pharmacogenomic-guided therapy aims to use information encoded in DNA and RNA to optimize not only the treatment choice for an individual patient but also the dose and schedule of that treatment with the ultimate goal of optimizing efficacy and minimizing toxicity. The assessment of both somatic (tumor) and germline mutations contribute to the overall individualization of cancer treatment. Somatic mutations are genetic variations found within the tumor DNA, but not DNA from the normal (germline) tissues, which also have functional consequences that influence disease outcomes and/or response to certain therapies.3 These types of mutations or biomarkers can be classified as either prognostic or predictive. Prognostic biomarkers identify subpopulations of patients with different disease courses or outcomes, independent of treatment. For example, NOTCH1 mutations in patients with chronic lymphocytic leukemia are associated with poorer progression-free survival (PFS) and Richter transformation.4 Predictive biomarkers identify subpopulations of patients most likely to have a response to a given therapy. Examples include the activating epidermal growth factor receptor (EGFR) L858R mutation, seen in 43% of EGFR-mutated lung cancers, that predicts for response to EGFR inhibitors, such as erlotinib and afatinib, as well as the activating BRAF V600E mutation, seen in around 50% of melanomas with lesser prevalence in other malignancies, that predicts response to BRAF and mitogen-activated protein kinase (MAPK) kinase (MEK) inhibitors.5 Some biomarkers can be both prognostic and predictive such as FMS-like tyrosine kinase 3 (FLT3) internal tandem duplication in acute myelogenous leukemia is associated with increased relapse rates and reduced overall survival (OS) as well as response to FLT3 inhibitors, like midostaurin.6 Germline mutations are heritable variations found within the individual and, in practical terms, are focused on DNA markers predictive for toxicity or therapeutic outcomes of a particular therapy as well as inheritable risk of certain cancers. Pharmacogenomic mutations in the germline provide some explanation for the interindividual and interracial variability in drug response and toxicity. For cancer chemotherapy, where cytotoxic agents are administered at doses close to their maximal tolerable dose, and therapeutic windows are relatively narrow, minor differences in individual drug handling may lead to severe toxicities. Therefore, an understanding of the sources of this variability would lead to the possibility of individualizing dosages or influencing clinical decisions that can improve patient care. Pharmacogenomics has putative utility in therapy selection, clinical study design, and as a tool to improve understanding of the pharmacology of a medication. TABLE 19.1

Clinical Examples of Genotype-Guided Cancer Chemotherapy Somatic Mutation Examples Drug Target

Drug(s)

Common Malignancy

EML4-ALK

Crizotinib, alectinib, ceritinib, brigatinib

Non–small-cell lung cancer

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BCR-ABL

Dasatinib, imatinib, nilotinib, bosutinib, ponatinib

Chronic myelogenous leukemia

BRAF

Vemurafenib, dabrafenib

Melanoma

MEK

Cobimetinib, trametinib

Melanoma

Epidermal growth factor receptor

Erlotinib, afatinib, gefitinib, osimertinib

Non–small-cell lung cancer

HER2

Trastuzumab, lapatinib, pertuzumab, Ado-trastuzumab emtansine

Breast cancer, gastric cancer

Janus kinase 2

Ruxolitinib

Myelofibrosis

Rearranged during transfection

Vandetanib, cabozantinib

Medullary thyroid cancer

ROS1

Crizotinib, ceritinib

Non–small-cell lung cancer

Germline Mutation Examples Gene Mutation

Drug

Effect

Cytochrome P450 (CYP) 2C19

Voriconazole

Decreased serum levels of active drug and potential decreased efficacy in patients with high enzyme levels (ultrarapid metabolizers)

CYP2D6

Tamoxifen, codeine, oxycodone, ondansetron, selective serotonin reuptake inhibitors and tricyclic antidepressants

Decreased production of active metabolite and potential decreased efficacy in patients with low enzyme levels

Dihydropyrimidine dehydrogenase

5-Fluorouracil

Decreased elimination and increased risk of myelosuppression, diarrhea, and mucositis in patients with low enzyme levels

Glucose-6-phosphate dehydrogenase (G6PD)

Rasburicase

Risk of severe hemolysis in patients with G6PD deficiency

Thiopurine methyltransferase

Mercaptopurine, thioguanine, azathioprine

Decreased methylation of the active metabolite resulting decreased elimination and increased risk of neutropenia in patients with low enzyme levels

UDP-glucuronosyltransferase 1A1

Irinotecan

Decreased glucuronidation of the active metabolite resulting in decreased elimination and increased risk of neutropenia and diarrhea in patients with low enzyme levels

EML4, echinoderm microtubule-associated protein-like 4; ALK, anaplastic lymphoma kinase; MEK, mitogenactivated protein kinase kinase; HER2, human epidermal growth factor receptor 2. The term pharmacogenetics was initially used to define inherited differences in drug effects and typically focused on individual candidate genes. The field of pharmacogenomics now includes genomewide association studies and is used to describe genetic variations in all aspects of drug absorption, distribution, metabolism, and excretion in addition to drug targets and their downstream pathways.3 Table 19.1 illustrates some current clinical examples of genotype-guided cancer chemotherapy. Variations in the DNA sequences encoding these proteins may take the form of deletions, insertions, repeats, frameshift mutations, nonsense mutations, and missense mutations, resulting in an inactive, truncated, unstable, or otherwise dysfunctional protein. The most common change involves single nucleotide substitutions, called single nucleotide polymorphisms, which occur at approximately 1 per 1,000 base pairs on the human genome. Variability in toxicity or activity can also be mediated by postgenomic events, at the level of RNA, protein, or functional activity.

PHARMACOGENOMICS OF TUMOR RESPONSE Tumor response to chemotherapy is regulated by a complex, multigenic network of genes that encompasses inherent characteristics of the tumor, differentially activated pathways of cell signaling, proliferation and DNA repair, factors that control drug delivery to the tumor cells (e.g., metabolism, transport), and cell death. These may in turn be modulated by previously administered treatment or drug exposure, which may upregulate target proteins or activate alternative pathways of drug resistance. The polygenic nature of drug response implies that a better understanding of genotype–phenotype associations would require more than the usual single-gene

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pharmacogenetic strategies employed to date. However, there are instances where the genomic context of a single gene within a cancer will be of high impact for specific therapeutic agents (see Table 19.1).

PATHWAY-DIRECTED ANTICANCER THERAPY One of the earliest success stories illustrating pathway-driven therapeutics is with CML. The hallmark chromosomal abnormality of this disease is the translocation of chromosomes 9 and 22 that ultimately produces the fusion gene BCR-ABL. This discovery in 1960 eventually led to the development of the targeted tyrosine kinase inhibitor (TKI) imatinib and its subsequent U.S. Food and Drug Administration (FDA) approval for treatment of CML in 2001.7 The International Randomized Study of Interferon and STI571 (IRIS) trial began enrollment in 2000 and compared imatinib with interferon and low-dose cytarabine, which was the previous standard of care for newly diagnosed patients with chronic-phase CML. All efficacy end points favored imatinib, including complete cytogenetic response of 76.2% with imatinib compared with 14.5% with interferon (P < .001). OS after 60 months of follow-up was 89% with imatinib.8 This example is just one of many where a once fatal disease can now be considered more akin to a chronic disease, requiring a daily medication and regular physician follow-up, similar to hypertension or diabetes. Drug development has also kept pace with these advances, and now, several other agents, including dasatinib, nilotinib, bosutinib, and ponatinib, have joined imatinib as treatment options for CML. Sequential genetic analysis may also be used to detect resistance mutations that may develop and provides insight for subsequent therapy decisions. The idea of changing treatment focus from a disease-based model to a pathway-driven model is also evolving. Human epidermal growth factor receptor 2 (HER2) is a transmembrane receptor tyrosine kinase that is overexpressed or amplified in up to 25% of breast cancers. Trastuzumab is a humanized monoclonal antibody directed against HER2 and demonstrated improved response rates (RRs) and time-to-disease progression in patients with metastatic HER2-positive breast cancer and improved disease-free survival (DFS) and OS in HER2positive breast cancer patients treated with adjuvant trastuzumab.9 Several additional agents are now available to target the HER2 pathway and vary in their pharmacology and mechanism of action. Lapatinib is an oral TKI directed against HER2 and EGFR, pertuzumab is a humanized monoclonal antibody that binds at a different location than trastuzumab and inhibits the dimerization and subsequent activation of HER2 signaling, and adotrastuzumab emtansine is an antibody–drug conjugate that targets HER2-positive cells and then releases the cytotoxic antimitotic agent emtansine through liposomal degradation of the linking compound. All of these agents illustrate the progress and pharmacologic diversity of pathway-directed therapy and remain as standard-of-care options for HER2-positive breast cancer in either the adjuvant and/or metastatic settings.10 HER2 expression is not limited to breast cancer, however. Although less common, HER2 expression is seen in numerous solid tumors including bladder, gastric, prostate, and non–small-cell lung cancer (NSCLC) with varying degrees of incidence depending on the method of detection. Based on results from a large, open-label phase III randomized, international trial of 594 patients with gastric or gastroesophageal junction cancer expressing HER2 by either immunohistochemistry or gene amplification by fluorescence in situ hybridization, trastuzumab is also approved for treatment of metastatic gastric or gastroesophageal junction adenocarcinoma that expresses HER2. Patients randomized to chemotherapy in combination with trastuzumab had a median OS of 13.8 months compared with 11.1 months in the patients receiving chemotherapy alone (hazard ratio [HR], 0.74; 0.60 to 0.91; P = .0046).11 Numerous examples also support that pathway-directed therapy will cross the boundaries of disease sites and that tumor genetics will become one of the biggest determining factors for treatment. The uncommon nature of many oncogenic mutations across tumors arising from different anatomic sites combined with the need to acquire clinical efficacy data for inhibitors of these specific mutations has supported the design and conduct of biomarker-driven “basket” trials. These trials match patients with tumors harboring specific genetic alterations to targeted therapies directed against these alterations independent of disease histology.12 This design was used to assess the clinical benefit of the BRAF TKI vemurafenib in seven cohorts of patients with nonmelanoma cancers found to have activating BRAF V600 mutations. A total of 122 patients with a variety of tumor types were enrolled including colorectal cancer (CRC) (n = 37), NSCLC (n = 20), ErdheimChester disease or Langerhans cell histiocytosis (n = 18), and primary brain tumors (n = 13). The RR to vemurafenib was 42% and 43% in the NSCLC and Erdheim-Chester disease or Langerhans cell histiocytosis cohorts, respectively, with anecdotal responses seen among patients with numerous other cancer types.13 The National Cancer Institute (NCI)-MATCH trial is another example of an even more extensive basket trial. The phase II, open-label trial is enrolling patients with a variety of advanced solid tumors and lymphoma to 1 of 30

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treatment arms. Genetic assessment is performed on each tumor, and patients are assigned to receive an agent targeted against the effects of a particular alteration that is identified. The primary goal of the trial is to assess objective RR in each drug-matched arm across tumor types. Since opening on August 12, 2015, the trial has accrued rapidly at sites across the United States with more than 6,000 tumor samples submitted and 660 patients enrolled in treatment as of June 18, 2017. The accrual goal includes having at least 25% of those enrolled to have less common malignancies.14 Simple expression of the drug target does not always translate into desired clinical outcomes. Cetuximab and panitumumab are monoclonal antibodies directed against EGFR; however, it was found that CRC patients who did not have detectable EGFR still experienced responses to these agents similar in extent to EGFR-positive patients. Kirsten rat sarcoma viral oncogene (KRAS) is a downstream effector of the EGFR pathway. Ligand binding to EGFR on the cell surface activates pathway signaling through the KRAS/RAF/MAPK pathway, which is thought to control cell growth, differentiation, and apoptosis.15 Eventually, it was found that CRC patients with a KRAS mutation did not derive benefit from cetuximab or panitumumab. The RR in CRC patients receiving either cetuximab or panitumumab who were KRAS wild-type was 10% to 40% compared with near zero percent in those with KRAS mutations.16 This finding was the result of a retrospective analysis of small group of patients and was confirmed in large, prospective trials. Additionally, it underscores the importance of tissue collection for biomarker assessment in trials with novel therapeutics. A recent clinical trial genomic analysis suggests that mutations in NRAS may also have value in predicting the utility of EGFR antibody therapy in CRC. Although the predictive value of KRAS mutation status in CRC has been well established in clinical trials, the role of KRAS in lung cancer and other malignancies is less well elucidated. Lung cancers harboring KRAS mutations have been shown to have less clinical benefit from the EGFR-targeted erlotinib in some trials, although this has not consistently been the case across all trials. Additionally, lung cancer KRAS mutation status does not appear to reproducibly predict clinical benefit from the EGFR-targeted monoclonal antibodies, as is the case in CRC.17 Unlike the HER2 example discussed previously, the clinical application of some genetic mutations will differ between tissue of origin. Deeper investigations and understandings of mutations driving oncogenic pathways can also elucidate mechanisms of resistance and practical therapeutic strategies for treatment and prevention. Approximately half of all cutaneous melanomas carry mutations in BRAF, with the most common being the V600E mutation. The BRAF inhibitor vemurafenib demonstrated improvements in both PFS and OS when compared with the cytotoxic agent dacarbazine in previously untreated patients with metastatic melanoma carrying the BRAF V600E mutation. Vemurafenib demonstrated a 63% relative reduction in the risk of death compared with dacarbazine (P < .001) along with a higher RR (48% compared with 5% for dacarbazine).18 Based on these results, vemurafenib was the first BRAF-targeted TKI approved by the FDA and was soon joined by dabrafenib. Although dramatic responses to these agents have been observed, relapse almost universally occurs after a median of 6 to 8 months. Activating BRAF mutations, like V600E, result in uncontrolled activity of the MAPK pathway through activation of the downstream kinase MEK, which when phosphorylated, subsequently activates extracellular signal-regulated kinase (ERK), which ultimately translocates to the cell nucleus, resulting in cell proliferation and survival (Fig. 19.1).19 An assessment of serial biopsies from patients treated with vemurafenib suggested numerous mechanisms for acquired resistance, including the appearance of secondary mutations in MEK.20 This finding supports the clinical rationale for using combination therapy with a BRAF and a MEK inhibitor. The combination of dabrafenib (BRAF inhibitor) and trametinib (MEK inhibitor) was assessed in 247 metastatic melanoma patients with BRAF V600 mutations compared with dabrafenib alone. Median PFS was 9.4 months in the combination group compared with 5.8 months in the patients who received single-agent therapy (HR, 0.39; 0.25 to 0.62; P < .001). A complete or partial response was also higher in the combination therapy group (76% compared with 54%; P = .03). The occurrence of cutaneous squamous cell carcinoma, a known side effect of single-agent BRAF inhibitor therapy due to paradoxical activation of RAF in unmutated cells, was also decreased in the combination therapy group (7% compared with 19%; P = .09), further supporting the evidence of downstream inhibition.21 Although combination therapy does prolong the time to disease progression, resistance still occurs in patients through a variety of mechanisms. Utilization of sequential biopsies and a genetic assessment will help to inform rationale combination and sequential pathway-driven therapy trials that will ultimately aid in better understanding and mitigation of common mechanism of resistance.

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Figure 19.1 Mitogen-activated protein kinase (MAPK) pathway in BRAF -mutated melanoma. The BRAF V600E mutation results in activation of the MAPK pathway independent of growth factor binding, initially by phosphorylation (P) of MAPK kinase (MEK). MEK subsequently phosphorylates extracellular signal-regulated kinase (ERK). ERK then translocates to the cell nucleus and causes transcription of cellular factors, resulting in cell proliferation and survival. Because one mechanism of resistance to BRAF inhibition is through mutations in MEK, inhibition at both the upstream target of BRAF and the downstream site of MEK can prolong the clinical benefit of the BRAF inhibitor. Currently, targeted DNA capture is the most common type of somatic genetic screening and involves focusing on a few relevant candidate genes followed by deeper sequencing. These types of techniques may not only reveal common genes associated with a particular malignancy but may also uncover a signaling pathway that would not be obviously associated with a particular histology or tumor site. Application of a next-generation sequencing assay in 40 CRC and 24 NSCLC tissue samples that assessed 145 cancer-relevant genes demonstrated that somatic mutations were seen in 98% of the CRC tumors and 83% of the NSCLCs.22 The number of mutations seen in a tumor, rather than specific activating or inactivating alterations, may also serve as predictive biomarker for therapy (Fig. 19.2). This has been seen for response to immunotherapies such as inhibitors of cytotoxic Tlymphocyte antigen 4 (CTLA-4) and programmed cell death protein 1 (PD-1). A retrospective assessment using whole exome sequencing of 64 patients with melanoma who were treated with the CTLA4 inhibitors ipilimumab or tremelimumab found a relationship between tumor mutation load and clinical benefit, hypothesized to be secondary to neoantigen production.23 Neoantigens can result from mutations in tumor cells and can be recognized as foreign by the immune system, thus enhancing the clinical benefits from immunotherapies.24 This relationship was also shown with the PD-1 inhibitor pembrolizumab in patients with NSCLC. In the discovery cohort of 16 samples and in the validation cohort of 18 samples, patients with a higher nonsynonymous mutation

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burden (above 209 and 200, respectively) had a higher rate of clinical benefit and longer PFS compared with patients whose tumors had lower mutation burdens.25 Additional biomarkers for immunotherapy are being assessed including programmed cell death protein ligand 1 (PD-L1) expression, the presence of tumor-infiltrating lymphocytes, and others.

GENETIC-GUIDED THERAPY: PRACTICAL ISSUES IN SOMATIC ANALYSIS Although advances in basic science and drug development have translated many oncogenic driver mutations across tumor types into pathway-directed therapy, this is not the case for the majority. There are numerous examples of functionally relevant recurrent driver mutations that affect protein targets that are not currently druggable. Regardless of malignancy, one of the most commonly mutated tumor suppressors is the protein p53. Mutations can result in p53 acquiring oncogenic functions that enable proliferation, invasion, metastasis, and cell survival as well as coordinating with different proteins, such as EGFR, to enhance or inhibit its effects.26 However, several challenges have inhibited the success of drugs that can restore wild-type p53 function to cells with inactivation or reduce the levels of the mutant p53 in tumor cells. Several strategies are currently being developed including small inferring RNA specific for mutant TP53, stabilizing ligands directed against common TP53 mutations, and the use of dendritic cell vaccines.27

Figure 19.2 Number of mutations per megabase (Mb) across solid tumors. Next-generation sequencing of 578 solid tumors resulted in a heterogeneous distribution of number of mutations per Mb. Although the majority of patients had lower mutation loads 20 mutations per Mb that may be amenable to treatment with immunotherapy. Another challenge of translating somatic genetic mutations into clinical treatment decisions is the determination of clinical significance for variants of almost known significance (VAKS) and variants of unknown significance (VUS). Whereas VUS are generally genetic alterations with little to no available data supporting their clinical relevance on protein effects, VAKS are those alterations occurring in a clinically relevant gene that are located in a functional protein domain and may have possible functional effects but have not been definitively characterized.28 To further elucidate the actionability of the alterations found on a tumor genetic profile or perhaps provide recommendations regarding sequencing of treatment options based on these results, molecular tumor boards are being developed and conducted as part of standard clinical practice at many major cancer centers and consortiums.28,29 These multidisciplinary meetings typically include a diverse attendance of clinical oncologists, pathologists, geneticists, basic scientists, research coordinators, pharmacists, nurses, and trainees whose goal is to optimize the translation of the findings on a tumor genetic report into clinical recommendations. Numerous examples of successful tumor board implementation have been reported with encouraging outcomes supporting

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translation into meaningful targeted therapy options for patients. One of the largest initiatives has been the MSKIMPACT prospective sequencing initiative at Memorial Sloan Kettering Cancer Center. The tumors and match normal tissue from more than 10,000 patients with diverse solid tumor malignancies were analyzed by nextgeneration sequencing of 341 (and later 410) cancer-associated genetic alterations including mutations, copy number alterations, selected promoter mutations, and rearrangements. This initiative not only added to the available literature supporting the occurrence of common mutations across numerous malignancies but also provided insight into novel alterations and mutation signatures in less common cancers. Of the first 5,009 patients to receive testing, 37% had a clinically relevant alteration identified in their tumor tissue and 11% were subsequently enrolled on a genomically matched clinical trial.30 This information is also publicly available for additional investigation and application at cBioPortal and OncoKB.31 The evolution of sequencing strategies and decreasing costs has made whole-genome sequencing more available in the clinical setting, and several companies offer commercially available tumor profiling services. Several limitations exist that challenge the optimal clinical implementation of these assays, however. Although germline genetic assessments can be done on a peripheral blood sample or buccal swab, somatic assessments typically require tumor tissue biopsy. This tissue is often in limited supply and of varying quality or may not be feasible depending on the site of the cancer. The advancement of sequencing technology with very high sensitivity and specificity has allowed for development of clinically available “liquid biopsy” assays to assess circulating cell free tumor DNA (cfDNA). This technique takes advantage of the result of rapid growth and turnover of cancer cells subsequently releasing DNA fragments into the circulation.32 Comparison of cfDNA with primary tumor tissue has shown the highest concordance in patients with higher number of metastatic sites, several lines of prior treatment, and lower albumin levels. Patients with gastrointestinal and breast cancers showed a higher concordance than those with head and neck or genitourinary cancers.33 Due to the ease of acquiring blood for cfDNA, serial sampling may be performed and help to elucidate the development of resistance mutations and refine targeting of therapeutic options.

PHARMACOGENOMICS OF CHEMOTHERAPY DRUG TOXICITY A drug’s disposition and pharmacodynamic effects can be influenced by a number of variables, including patient age, diet, concomitant medications, and underlying disease processes. However, an individual’s genetic constitution is an important regulator of variability in drug effect. Differences in drug effects are more pronounced between individuals compared to within an individual. Indeed, studies in monozygotic and dizygotic twins identified that 20% to 80% of the variation in drug disposition is mediated by inheritance.34 Drug-metabolizing enzymes, cellular transporters, and tissue receptors are governed by genetic variation. Advances in the treatment of most common malignancies have resulted in the availability of multiple distinct combination chemotherapy regimens with similar or equal anticancer efficacy. Therefore, differences in systemic toxicity have become a major determinant in the selection of therapy. Optimizing efficacy while minimizing toxicity has also underscored the role of pharmacogenomics to guide agents used in supportive care including voriconazole (metabolized by CYP2C19) and numerous antidepressants (primarily metabolized by CYP2D6 and CYP2C19).35,36 The majority of pharmacogenomic examples affecting adverse events or efficacy involve hepatic metabolizing enzymes that detoxify or biotransform xenobiotics.37,38 The Clinical Pharmacogenetics Implementation Consortium (CPIC) aims to develop peer-reviewed, evidence-based gene/drug practice guidelines focused on providing specific recommendations based on reported genetic test results.39 Numerous CPIC guideline recommendations exist for several drugs used in oncology, infectious disease, psychiatry, and other areas with two discussed in more detail in the following text.

Thiopurine Methyltransferase One of the best-studied pharmacogenetic syndrome involves the metabolism of the thiopurine drugs—6mercaptopurine (6MP), 6-thioguanine, and azathioprine—which have wide applications, including maintenance therapy for childhood ALL and adult leukemias. These prodrugs must be activated to thioguanine nucleotides in order to have antiproliferative effects. However, most of the variability in the formation of active metabolites is mediated by methylation via thiopurine methyltransferase (TPMT).40 TPMT is a cytosolic enzyme that catalyzes S-methylation of thiopurine agents, resulting in an inactive metabolite. Erythrocyte TPMT activity has a trimodal distribution, with 90% of patients having high activity, 10% intermediate activity, and 0.3% with very low or no

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detectable activity. TPMT deficiency results in higher intracellular activation of 6MP to form thioguanine nucleotides, resulting in severe or fatal hematologic toxicity from standard doses of therapy. The variable activity results from polymorphism in the TPMT gene, located on chromosome locus 6p22.3. Genetic variants at codon 238 (TPMT*2), codon 719 (TPMT*3C), or both codons 460 and 719 (TPMT*3A) are the most clinically significant, accounting for 95% of the patients with reduced TPMT activity.40 Heterozygotes (one wild type and one variant allele) are common (10% of patients), have elevated levels of active metabolites (twofold more than homozygous wild type), and required more cumulative dose reductions of 6MP for maintenance ALL chemotherapy compared to homozygous wild-type patients (Fig. 19.3).40 Patients with a homozygous variant TPMT genotype are at a fourfold risk of severe toxicity, compared with wild-type patients.40 TPMT genotype tests are now available commercially in a Clinical Laboratory Improvement Amendments (CLIA)-certified environment. To date, patients homozygous for TPMT variant alleles appear to tolerate 10%, and heterozygotes appear to tolerate 65% of the recommended doses of 6MP, with no apparent decrease in clinical efficacy (see Fig. 19.3).40 This has formed the basis for prospective, TPMT genotype-guided dosing of 6MP to avoid severe toxicity. CPIC guidelines recommend that homozygous wild-type patients be started at the full standard dose. Heterozygous patients should start with reduced doses at 30% to 70% of the full dose with adjustments made after 2 to 4 weeks based on myelosuppression and disease-specific guidelines. Homozygous variant patients should start with 10% of the full dose due to the extremely high levels of the active metabolite and potential for fatal toxicity at standard doses. Adjustments should be made after 4 to 6 weeks based on myelosuppression and disease-specific guidelines.40

Figure 19.3 Relationship between thiopurine methyltransferase (TPMT) genotype and required 6mercaptopurine (6MP) dose. Compared with homozygous wild-type (wt) patients, those heterozygous for a TPMT variant (var) allele generally require at least a 30% dose reduction in 6MP, whereas homozygous variant patients require substantial dose reductions of approximately 90% that of wild-type patients.

Dihydropyrimidine Dehydrogenase Although 5-fluorouracil (5-FU) has been available for over 40 years, it remains the cornerstone of CRC chemotherapy, both in the adjuvant and metastatic settings. Additionally, the oral prodrug capecitabine ultimately undergoes activation to 5-FU and is commonly used in gastrointestinal and breast malignancies. 5-FU is a prodrug that is activated intracellularly to 5-fluoro-2′-deoxyuridine 5′-monophosphate (5-FdUMP), which inhibits thymidylate synthase (TS), among other mechanisms of action. TS inhibition results in impaired de novo pyrimidine synthesis and suppression of DNA synthesis. Approximately 85% of a 5-FU dose is catabolized by

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dihydropyrimidine dehydrogenase (DPD) to inactive metabolites. Therefore, DPD is a primary regulator of 5-FU activity. DPD deficiency has been described, resulting in higher 5-FU blood levels, greater formation of active metabolites, and severe or fatal clinical toxicity, predominately myelosuppression, mucositis, and cerebellar toxicity.41 In theory, this toxicity could be reduced or avoided by screening for DPD activity in surrogate tissues, such as peripheral mononuclear cells. However, the technical requirements for preparation of these samples make it impractical for many practice sites. Understanding the molecular basis for DPD deficiency will provide an approach for prospective identification of patients at high risk for severe 5-FU toxicity. The gene encoding DPD is composed of 23 exons, and at least 23 single nucleotide polymorphisms (SNPs) have been found.42 Studies in DPD-deficient patients have identified several distinct molecular variants associated with low enzyme activity. Many of these are rare, and base substitutions, splicing defects, and frame shift mutations have been described. The prevalent variation is the splice recognition site in intron 14 (DPYD*2A), where a G to A substitution results in the skipping of exon 14, resulting in an inactive enzyme.41 This polymorphism has been associated with severe DPD deficiency in heterozygous patients, with a homozygous genotype associated with a mental retardation syndrome. Patients with severe 5-FU toxicity may harbor one or more variant alleles of DPD, and a recent study showed that 61% of cancer patients experiencing severe 5-FU toxicities had decreased DPD activity in peripheral mononuclear cells, and DPYD*2A was commonly found.43 In the patients with grade 4 neutropenia, 50% harbored at least one DPYD*2A. It is estimated that in the Caucasian population, homozygotes for the variant alleles have an incidence of 0.1% and heterozygotes occur at an incidence of 0.5% to 2%. There are additional DPD mutations that have been associated with impaired enzyme activity, including DPYD *3 and DPYD*13. CPIC guidelines recommend standard dosing for homozygous wild-type patients. Reducing the dose by at least 50% in heterozygous patients (*1/*2A) is recommended, followed by dose adjustment based on toxicity and/or pharmacokinetic testing. The use of an alternative agent is recommended in homozygous-variant patients (*2A/*2A).41 There are many patients with severe 5-FU toxicity that have normal DPD activity. This highlights that many factors, including multiple genes, are potential causes of 5-FU toxicity, and there will not be one simple test to avoid this important clinical problem.

CONCLUSIONS AND FUTURE DIRECTIONS Genomic-driven cancer medicine is being translated into clinical practice through increased understanding of somatic mutations in a specific tumor that can be translated to pathway-directed therapeutics as well as germline mutations that affect the pharmacokinetics and pharmacodynamics of individual medications. For the practicing oncologist, knowledge of pharmacogenomics is necessary because therapeutic decisions of drug selection and dosage are being based on more molecularly and genetically defined variables than the current phenotypic information of tumor type, immunohistochemistry, and body surface area. Health-care policy changes preferring the bundling of care and reimbursement based on diagnosis coding may further drive individualized therapy where the goal is to optimize both treatment responses while minimizing toxicity. However, with advances always come challenges. Reimbursement for multiplex genomic testing is not universal, so deciding who and when to initiate testing is a consideration. Optimizing turnaround time, especially for referral patients who have had biopsies performed elsewhere, will require requesting this archived tissue prior to or during the initial patient visit to facilitate minimizing treatment delays. Although some variants have strong evidence supporting treatment recommendations, many currently do not yet. Multidisciplinary committees charged with reviewing the level of evidence for each genetic result and providing clinically actionable recommendations will be essential for translating these multigene tumor assay results into routine clinical practice. Decision tools and development of treatment guidelines will further assist with routine integration of this technology, especially for oncologists at smaller practice sites. Oncology fellowship training programs will also need to be expanded to ensure competence of new practitioners in the area of genomic-guided therapies. Regardless of these challenges, the treatment paradigm of genomic-driven medicine and individualizing therapy has permitted the field of oncology to move beyond the limitations of nonselective cytotoxic therapy and toward the more optimal selection and dosing of oncology agents.

REFERENCES 1. McLeod HL. Cancer pharmacogenomics: early promise, but concerted effort needed. Science 2013;339(6127):1563–1566.

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2. Garraway LA. Genomics-driven oncology: framework for an emerging paradigm. J Clin Oncol 2013;31(15):1806– 1814. 3. Wang L, McLeod HL, Weinshilboum RM. Genomics and drug response. N Engl J Med 2011;364(12):1144–1153. 4. Nabhan C, Raca G, Wang YL. Predicting prognosis in chronic lymphocytic leukemia in the contemporary era. JAMA Oncol 2015;1(7):965–974. 5. Mandrekar SJ, Sargent DJ. Predictive biomarker validation in practice: lessons from real trials. Clin Trials 2010;7(5):567–573. 6. Pratz KW, Levis M. How I treat FLT3-mutated AML. Blood 2017;129(5):565–571. 7. Druker BJ. Translation of the Philadelphia chromosome into therapy for CML. Blood 2008;112(13):4808–4817. 8. Druker BJ, Guilhot F, O’Brien SG, et al. Five-year follow-up of patients receiving imatinib for chronic myeloid leukemia. N Engl J Med 2006;355(23):2408–2417. 9. Hudis CA. Trastuzumab—mechanism of action and use in clinical practice. N Engl Med 2007;357(1):39–51. 10. Figueroa-Magalhães MC, Jelovac D, Connolly R, et al. Treatment of HER2-positive breast cancer. Breast 2014;23(2):128–136. 11. Bang YJ, Van Cutsem E, Feyereislova A, et al. Trastuzumab in combination with chemotherapy versus chemotherapy alone for treatment of HER2-positive advanced gastric or gastro-oesophageal junction cancer (ToGA): a phase 3, open-label, randomised controlled trial. Lancet 2010;376(9742):687–697. 12. Sleijfer S, Bogaerts J, Siu LL. Designing transformative clinical trials in the cancer genome era. J Clin Oncol 2013;31(15):1834–1841. 13. Hyman DM, Puzanov I, Subbiah V, et al. Vemurafenib in multiple nonmelanoma cancers with BRAF V600 mutations. N Engl J Med 2015;373(8):726–736. 14. Coyne GO, Takebe N, Chen AP. Defining precision: the precision medicine initiative trials NCI-MPACT and NCIMATCH. Curr Probl Cancer 2017;41(3):182–193. 15. Bardelli A, Siena S. Molecular mechanisms of resistance to cetuximab and panitumumab in colorectal cancer. J Clin Oncol 2010;28(7):1254–1261. 16. Jimeno A, Messersmith WA, Hirsch FR, et al. KRAS mutations and sensitivity to epidermal growth factor receptor inhibitors in colorectal cancer: practical application of patient selection. J Clin Oncol 2009;27(7):1130–1136. 17. Roberts PJ, Stinchcombe TE, Der CJ, et al. Personalized medicine in non-small-cell lung cancer: is KRAS a useful marker in selecting patients for epidermal growth factor receptor-targeted therapy? J Clin Oncol 2010;28(31):4769–4777. 18. Chapman PB, Hauschild A, Robert C, et al. Improved survival with vemurafenib in melanoma with BRAF V600E mutation. N Engl J Med 2011;364(26):2507–2516. 19. Dhillon AS, Hagan S, Rath O, et al. MAP kinase signalling pathways in cancer. Oncogene 2007;26(22):3279– 3290. 20. Trunzer K, Pavlick AC, Schuchter L, et al. Pharmacodynamic effects and mechanisms of resistance to vemurafenib in patients with metastatic melanoma. J Clin Oncol 2013;31(14):1767–1774. 21. Flaherty KT, Infante JR, Daud A, et al. Combined BRAF and MEK inhibition in melanoma with BRAF V600 mutations. N Engl J Med 2012;367(18):1694–1703. 22. Lipson D, Capelletti M, Yelensky R, et al. Identification of new ALK and RET gene fusions from colorectal and lung cancer biopsies. Nat Med 2012;18(3):382–384. 23. Snyder A, Makarov V, Merghoub T, et al. Genetic basis for clinical response to CTLA-4 blockade in melanoma. N Engl J Med 2014;371(23):2189–2199. 24. Nishino M, Ramaiya NH, Hatabu H, et al. Monitoring immune-checkpoint blockade: response evaluation and biomarker development. Nat Rev Clin Oncol 2017;14(11):655–668. 25. Rizvi NA, Hellmann MD, Snyder A, et al. Cancer immunology. Mutational landscape determines sensitivity to PD1 blockade in non-small cell lung cancer. Science 2015;348(6230):124–128. 26. Muller PA, Vousden KH. p53 mutations in cancer. Nat Cell Biol 2013;15(1):2–8. 27. Sabapathy K, Lane DP. Therapeutic targeting of p53: all mutants are equal, but some mutants are more equal than others. Nat Rev Clin Oncol 2018;15(1):13–30. 28. Knepper TC, Bell GC, Hicks JK, et al. Key lessons learned from Moffitt’s Molecular Tumor Board: the Clinical Genomics Action Committee experience. Oncologist 2017;22(2):144–151. 29. Walko C, Kiel PJ, Kolesar J. Precision medicine in oncology: new practice models and roles for oncology pharmacists. Am J Health Syst Pharm 2016;73(23):1935–1942. 30. Zehir A, Benayed R, Shah RH, et al. Mutational landscape of metastatic cancer revealed from prospective clinical sequencing of 10,000 patients. Nat Med 2017;23(6):703–713.

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31. Chakravarty D, Gao J, Phillips SM, et al. OncoKB: a precision oncology knowledge base. JCO Precis Oncol 2017;1:6–16. 32. Siravegna G, Marsoni S, Siena S, et al. Integrating liquid biopsies into the management of cancer. Nat Rev Clin Oncol 2017;14(9):531–548. 33. Jovelet C, Ileana E, Le Deley MC, et al. Circulating cell-free tumor DNA analysis of 50 genes by next-generation sequencing in the prospective MOSCATO trial. Clin Cancer Res 2016;22(12):2960–2968. 34. Watters JW, McLeod HL. Cancer pharmacogenomics: current and future applications. Biochim Biophys Acta 2003;1603(2):99–111. 35. Hicks JK, Bishop JR, Sangkuhl K, et al. Clinical Pharmacogenetics Implementation Consortium (CPIC) guideline for CYP2D6 and CYP2C19 genotypes and dosing of selective serotonin reuptake inhibitors. Clin Pharmacol Ther 2015;98(2):127–134. 36. Moriyama B, Obeng AO, Barbarino J, et al. Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines for CYP2C19 and voriconazole therapy. Clin Pharmacol Ther 2018;103(2):349. 37. Evans WE, Relling MV. Pharmacogenomics: translating functional genomics into rational therapeutics. Science 1999;286(5439):487–491. 38. Deenen MJ, Cats A, Beijnen JH, et al. Part 2: pharmacogenetic variability in drug transport and phase I anticancer drug metabolism. Oncologist 2011;16(6):820–834. 39. Relling MV, Klein TE. CPIC: Clinical Pharmacogenetics Implementation Consortium of the Pharmacogenomics Research Network. Clin Pharmacol Ther 2011;89(3):464–467. 40. Relling MV, Gardner EE, Sandborn WJ, et al. Clinical pharmacogenetics implementation consortium guidelines for thiopurine methyltransferase genotype and thiopurine dosing: 2013 update. Clin Pharmacol Ther 2013;93(4):324– 325. 41. Amstutz U, Henricks LM, Offer SM, et al. Clinical Pharmacogenetics Implementation Consortium (CPIC) guideline for dihydropyrimidine dehydrogenase genotype and fluoropyrimidine dosing: 2017 update. Clin Pharmacol Ther 2018;103(2):210–216. 42. McLeod HL, Collie-Duguid ES, Vreken P, et al. Nomenclature for human DPYD alleles. Pharmacogenetics 1998;8(6):455–459. 43. Van Kuilenburg AB, Meinsma R, Zoetekouw L, et al. Increased risk of grade IV neutropenia after administration of 5-fluorouracil due to a dihydropyrimidine dehydrogenase deficiency: high prevalence of the IVS14+1g>a mutation. Int J Cancer 2002;101(3):253–258.

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20

Alkylating Agents Kenneth D. Tew

HISTORICAL PERSPECTIVES The alkylating agents are a diverse group of anticancer agents with the commonality that they react in a manner such that an electrophilic alkyl group or a substituted alkyl group can covalently bind to cellular nucleophilic sites. Electrophilicity is achieved through the formation of carbonium ion intermediates and can result in transition complexes with target molecules. Ultimately, reactions result in the formation of covalent linkages by alkylation with a broad range of nucleophilic groups, including bases in DNA, and these are believed responsible for ultimate cytotoxicity and therapeutic effect. Although the alkylating agents react with cells in all phases of the cell cycle, their efficacy and toxicity result from interference with rapidly proliferating tissues. From a historical perspective, the vesicant properties of mustard gas used during World War I were shown to be accompanied by suppression of lymphoid and hematologic functions in experimental animals1 and led to the development of mechlorethamine as the first alkylating agent used in human cancer management.2 Subsequently, a number of related drugs have been developed, and these have roles in the treatment of a range of leukemias, lymphomas, and solid tumors. Most of the alkylating agents cause dose-limiting toxicities to the bone marrow and to a lesser degree the intestinal mucosa, with other organ systems also affected contingent on the individual drug, dosage, and duration of therapy. Despite the present trend toward targeted therapies, this class of “nonspecific” drugs maintains an essential role in cancer chemotherapy.

CHEMISTRY Alkylating reactions are generally classified through their kinetic properties as SN1 (nucleophilic substitution, first order) or SN2 (nucleophilic substitution, second order) (Fig. 20.1). The first-order kinetics of the SN1 reaction are dependent on the concentration of the original alkylating agent. The rate-limiting step is the initial formation of the reactive intermediate, and the rate is essentially independent of the concentration of the substrate. The SN2 alkylation reaction is a bimolecular nucleophilic displacement with second-order kinetics, where the rate is dependent on the concentration of both alkylating agent and target nucleophile. Reactivity of electrophiles3 suggests that the rates of alkylation of cellular nucleophiles (including thiols, phosphates, amino and imidazole groups of amino acids, and various reactive sites in nucleic acid bases) are most dependent on their potential energy states, which can be defined as “hard” or “soft,” based on the polarizability of their reactive centers.4 Although the metabolism and metabolites of nitrogen mustards and nitrosoureas differ, the active alkylating species of each is the alkyl carbonium ion (see Fig. 20.1), a highly polarized hard electrophile as a consequence of its highly positive charge density at the electrophilic center. Alkyl carbonium ions will react most readily with hard nucleophiles (possessing a highly polarized negative charge density), where the high-energy transition state (a potential energy barrier to the reaction) is most favorable. In specific terms, an active alkylating species from a nitrogen mustard will demonstrate selectivity for cellular nucleophiles in the following order: (1) oxygen in phosphate groups of RNA and DNA, (2) oxygens of purines and pyrimidines, (3) amino groups of purine bases, (4) primary and secondary amino groups of proteins, (5) sulfur atoms of methionine, and (6) thiol groups of cysteinyl residues of protein and glutathione.3 The least favored reactions will still occur but at much slower rates unless they are catalyzed. Alkylation through highly reactive intermediates (e.g., mechlorethamine) would be expected to be less selective in their targets than the less reactive SN2 reagents (e.g., busulfan). However, the therapeutic and toxic effects of alkylating agents do not correlate directly with their chemical reactivity. Clinically useful agents include drugs with SN1 or SN2 characteristics and some with both.5 These differ in their toxicity profiles and antitumor

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activity but more as a consequence of differences in pharmacokinetics, lipid solubility, penetration of the central nervous system (CNS), membrane transport, metabolism and detoxification, and specific enzymatic reactions capable of repairing alkylation sites on DNA.

CLASSIFICATION The major classes of clinically useful alkylating agents are illustrated in Table 20.1 and summarized below. Doses and schedules of the various agents are shown Table 20.2.

Alkyl Sulfonates Busulfan is used for the treatment of chronic myelogenous leukemia. It exhibits SN2 alkylation kinetics and shows nucleophilic selectivity for thiol groups, suggesting that it may exert cytotoxicity through protein alkylation rather than through DNA. In contrast to the nitrogen mustards and nitrosoureas, busulfan has a greater effect on myeloid cells than lymphoid cells, thus its use against chronic myelogenous leukemia.6

Aziridines Aziridines are analogs of ring-closed intermediates of nitrogen mustards and are less chemically reactive, but they have equivalent therapeutic properties. Thiotepa has been used in the treatment of carcinoma of the breast and ovary, for a variety of CNS diseases, and with increasing frequency as a component of high-dose chemotherapy regimens.7 Thiotepa and its primary desulfurated metabolite triethylenethiophosphoramide (TEPA) alkylate through aziridine ring openings, a mechanism similar to the nitrogen mustards.

Triazines Perhaps the newest clinical development in the alkylating agent field is the emergence of temozolomide. This agent acts as a prodrug and is an imidazotetrazine analog that undergoes spontaneous activation in solution to produce 5-(3-methyltriazen-1-yl) imidazole-4-carboxamide (MTIC), a triazine derivative. It crosses the blood– brain barrier with concentrations in the CNS approximating 30% of plasma concentrations.8 Temozolomide provides efficacy in the treatment of gliomas and melanomas.

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Figure 20.1 Comparative decomposition and metabolism of a typical nitrogen mustard compared to a nitrosourea. Although intermediate metabolites are distinct, the active alkylating species is a carbonium ion in each case. This electrophilic moiety reacts with target cellular nucleophiles.

Nitrogen Mustards Bischloroethylamines or nitrogen mustards are extensively administered in the clinic. As an initial step in alkylation, chlorine acts as a leaving group and the β-carbon reacts with the nucleophilic nitrogen atom to form the cyclic, positively charged, reactive aziridinium moiety. Reaction of the aziridinium ring with an electron-rich nucleophile creates an initial alkylation product. The remaining chloroethyl group achieves bifunctionality through formation of a second aziridinium. Melphalan (L-phenylalanine mustard), chlorambucil, cyclophosphamide, and ifosfamide (see Table 20.1) replaced mechlorethamine as primary therapeutic agents. These derivatives have electron-withdrawing groups substituted on the nitrogen atom, reducing the nucleophilicity

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of the nitrogen and rendering them less reactive but enhancing their antitumor efficacy. One distinguishing feature of melphalan is that an amino acid transporter responsible for uptake influences its efficacy across cell membranes.9 Although a number of glutathione (GSH) conjugates of alkylating agents are effluxed through adenosine triphosphate–dependent membrane transporters,10 specific uptake mechanisms are generally rare for cancer drugs. Cyclophosphamide and ifosfamide are prodrugs that require cytochrome p450 metabolism to release active alkylating species. Cyclophosphamide continues to be the most widely used alkylating agent and has activity against a variety of tumors.11 Bendamustine has a nitrogen mustard group at position 5 of a benzimidazole ring (γ-[1-methyl-5-bis(βchloroethyl)-amino-benzimidazolyl-2]-butyric acid hydrochloride) and was initially synthesized over 50 years ago.12 It has structural properties that resemble both an alkylating agent and purine analog. Perhaps because the benzimidazole ring possesses nucleoside-like properties and places it contiguous to DNA, a prolonged half-life seems to be responsible for enhanced drug-induced DNA damage.13 Following drug treatments, DNA damage repair proceeds more slowly than with other nitrogen mustards, and this may relate to the fact that bendamustine demonstrates incomplete cross-resistance with other alkylating agents and essentially no cross-resistance with other cytotoxic drugs.14 Its structure may also provide a greater degree of stability than with other nitrogen mustards, and this may be a contributory factor in the drug’s activity in primary non-Hodgkin lymphoma (NHL) cells resistant to conventional drugs such as cyclophosphamide, doxorubicin, and etoposide.15 Such in vitro and in vivo preclinical studies supported the principle that, unique from the other alkylating agents in common use, bendamustine would find a niche in clinical disease management. TABLE 20.1

Major Classes of Clinically Useful Alkylating Agents Drug

Structure

Main Therapeutic Uses

Clinical Pharmacology

Major Toxicities

Notes

ALKYL SULFONATES Bendamustine



CLL, indolent and aggressive nonHodgkin lymphoma, multiple myeloma

T1/2, 49 min; volume of distribution, 18.3 m2; clearance, 265 mL/min/m2

Typical of alkylating agents

Numerous trials with rituximab in development

Busulfan



Bone marrow transplantation, especially in chronic myelogenous leukemia

Bioavailability, 80%; protein bound, 33%; T1/2, 2.5 h

Pulmonary fibrosis, hyperpigmentation thrombocytopenia, lowered blood platelet count and activity

Oral or parenteral; high dose causes hepatic venoocclusive disease

ETHYLENEIMINES/METHYLMELAMINES Altretamine





Protein bound, 94%; T1/2, 5–10 h

Nausea, vomiting, diarrhea, and neurotoxicity

Not widely used

Thiotepa



Breast, ovarian, and bladder cancer; also bone marrow transplant

T1/2, 2.5 h; urinary excretion at 24 h, 25%; substrate for CYP2B6 and CYP2C11

Myelosuppression

Nadirs of leukopenia, occur 2 wk; thrombocytopenia, 3 wk (correlates with AUC of parent drug)

NITROGEN MUSTARDS Mechlorethamine



Hodgkin lymphoma



Nausea, vomiting, myelosuppression

Precursor for other clinical mustards

Melphalan (Lphenylalanine mustard or L-PAM)



Multiple myeloma and ovarian cancer; occasionally malignant melanoma

Bioavailability, 25%– 90%; T1/2, 1.5 h; urinary excretion at 24 h, 13%; clearance, 9 mL/min/kg

Nausea, vomiting, myelosuppression

Causes less mucosal damage than others in class

Chlorambucil



CLL

T1/2, 1.5 h; urinary excretion at 24 h,

Myelosuppression, gastrointestinal

Oral

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50%

distress, CNS, skin reactions, hepatotoxicity

Cyclophosphamide



Variety of lymphomas, leukemias, and solid tumors

Bioavailability, >75%; protein bound, >60%; T1/2, 3–12 h; urinary excretion at 24 h 50%

Oxaliplatin After oxaliplatin infusion, platinum accumulates into three compartments: plasma-bound platinum, ultrafiltrable platinum, and platinum associated with erythrocytes. When specific and sensitive mass spectrometric techniques are used, oxaliplatin itself is undetectable in plasma, even at end infusion.81 The active forms of the drug have not been extensively characterized. Approximately 85% of the total platinum is bound to plasma protein at 2 to 5 hours after infusion.82 Plasma elimination of total platinum and ultrafiltrates is biphasic. The half-lives for the initial and terminal phases are 26 minutes and 38.7 hours, respectively, for total platinum and 21 minutes and 24.2 hours, respectively, for ultrafiltrable platinum83 (see Table 21.1). Thus, as with carboplatin, substantial differences between total and free platinum kinetics are not observed. As with cisplatin, a prolonged retention of oxaliplatin is observed in red blood cells. However, unlike cisplatin, oxaliplatin does not accumulate to any significant level after multiple courses of treatment.82 This may explain why neurotoxicity associated with oxaliplatin is reversible. Oxaliplatin is eliminated predominantly by the kidneys, with more than 50% of the platinum being excreted in the urine at 48 hours.

Pharmacodynamics Pharmacodynamics relates pharmacokinetic indices of drug exposure to biologic measures of drug effect, usually toxicity to normal tissues or tumor cell kill. Two issues to be addressed in such studies are whether the effectiveness of the drug can be enhanced and whether the toxicity can be attenuated by knowledge of the platinum pharmacokinetics in an individual. These questions are appropriate to the use of cytotoxic agents with relatively narrow therapeutic indices. Toxicity to normal tissues can be quantitated as a continuous variable when the drug causes myelosuppression. Thus, the early studies of carboplatin demonstrated a close relationship of changes in platelet counts to the AUC in the individual. The AUC was itself closely related to renal function, which was determined as creatinine clearance. Based on these observations, Egorin et al.,10 Calvert et al.,9 and Chatelut et al.84 derived formulas based on glomerular filtration rate to predict either the percentage change in platelet count or a target AUC. Application of pharmacodynamically guided dosing algorithms for carboplatin has been widely adopted as a means of avoiding overdosage (by producing acceptable nadir platelet counts) and of maximizing dose intensity in the individual. There is good evidence that this approach can decrease the risk of unacceptable toxicity. Accordingly, a dosing strategy based on renal function is recommended for the use of carboplatin. A key question is whether maximizing carboplatin exposure in an individual can measurably increase the probability of tumor regression or survival. In an analysis by Jodrell et al.,85 carboplatin AUC was a predictor of response, thrombocytopenia, and leukopenia. The likelihood of a tumor response increased with increasing AUC up to a level of 5 to 7 mg × h/mL, after which a plateau was reached. Similar results were obtained with carboplatin in combination with cyclophosphamide, and neither response rate nor survival was determined by the carboplatin AUC in a cohort of ovarian cancer patients.86 As a result, most carboplatin recommended doses are based on an AUC in this range (for every 3- to 4-week schedules), and modifications of these are used for more frequent administration (as in combined chemoradiotherapy regimens). The relationship of pharmacokinetics to response has been sought by investigating the cellular pharmacology of these agents.87 The formation and repair of the platinum-DNA adducts in human cells are not easily measured. Schellens and colleagues88,89 analyzed the pharmacokinetic and pharmacodynamic interactions of cisplatin administered as a single agent. In a series of patients with head and neck cancer, they found that cisplatin exposure (measured as the AUC) closely correlated with both the peak DNA-adduct content in leukocytes and the area under the DNA-adduct-time curve. These measures were important predictors of response, both individually and in logistic regression analysis. However, as an approach to determine who should or should not be treated with platinum drugs, it seems more likely that genomic analyses will continue to provide substantial guidance.

Pharmacogenomics Variability in pharmacokinetics and pharmacodynamics of cytotoxic drugs is an important determinant of therapeutic index. This interindividual variation may be attributed in part to genetic differences among patients. Targeted analyses of germline DNA, and increasingly genomewide association study (GWAS) approaches, have yielded genotypic features associated with results of therapy. Detoxication pathways and DNA repair have emerged as having markers attributable to response of lack of it in response to platinum drugs. Single nucleotide polymorphisms (SNPs) in genes related to GSH metabolism and in several DNA repair genes have been identified

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in lung cancer, breast cancer, and various GI cancers. A concern is that larger trials have not always confirmed early findings. Informative SNPs that could be used to define therapeutic strategies for individual patients have not yet been defined.

REFERENCES 1. Rosenberg B, VanCamp L, Trosko JE, et al. Platinum compounds: a new class of potent antitumor agents. Nature 1969;222(5191):385–386. 2. Rosenberg B. Fundamental studies with cisplatin. Cancer 1985;55(10):2303–2316. 3. Cvitkovic E, Spaulding J, Bethune V, et al. Improvement of cis-dichlorodiammineplatinum (NSC 119875): therapeutic index in an animal model. Cancer 1977;39(4):1357–1361. 4. Hayes DM, Cvitkovic E, Golbey RB, et al. High dose cis-platinum diamine dichloride: amelioration of renal toxicity by mannitol diuresis. Cancer 1977;39(4):1372–1381. 5. Roberts JJ, Thomson AJ. The mechanism of action of antitumor platinum compounds. Prog Nucleic Acids Res Mol Biol 1979;22:71–133. 6. Martin R. Platinum complexes: hydrolysis and binding to N(7) and N(1) of purines. In: Lippert B, ed. Cisplatin: Chemistry and Biochemistry of a Leading Anticancer Drug. Zurich: Verlag Helvetica Chimica Acta; 1999:183. 7. Harrap KR. Preclinical studies identifying carboplatin as a viable cisplatin alternative. Cancer Treat Rev 1985;12(Suppl A):21–33. 8. Calvert AH, Harland SJ, Newell DR, et al. Early clinical studies with cis-diammine-1,1-cyclobutane dicarboxylate platinum II. Cancer Chemother Pharmacol 1982;9(3):140–147. 9. Calvert AH, Newell DR, Gumbrell LA, et al. Carboplatin dosage: prospective evaluation of a simple formula based on renal function. J Clin Oncol 1989;7(11):1748–1756. 10. Egorin MJ, Van Echo DA, Olman EA, et al. Prospective validation of a pharmacologically based dosing scheme for the cis-diamminedichloroplatinum(II) analogue diamminecyclobutanedicarboxylatoplatinum. Cancer Res 1985;45(12 Pt 1):6502–6506. 11. Connors TA, Jones M, Ross WC, et al. New platinum complexes with anti-tumour activity. Chem Biol Interact 1972;5(6):415–424. 12. Burchenal JH, Kalaker K, Dew K, et al. Rationale for development of platinum analogs. Cancer Treat Rep 1979;63(9–10):1493–1498. 13. Kidani Y, Inagaki K, Tsukagoshi S. Examination of antitumor activities of platinum complexes of 1,2diaminocyclohexane isomers and their related complexes. Gan 1976;67(6):921–922. 14. Burchenal JH, Irani G, Kern K, et al. 1,2-Diaminocyclohexane platinum derivatives of potential clinical value. Recent Results Cancer Res 1980;74:146–155. 15. Rixe O, Ortuzar W, Alvarez M, et al. Oxaliplatin, tetraplatin, cisplatin, and carboplatin: spectrum of activity in drug-resistant cell lines and in the cell lines of the National Cancer Institute’s Anticancer Drug Screen panel. Biochem Pharmacol 1996;52(12):1855–1865. 16. Johnstone TC, Suntharalingam K, Lippard SJ. The next generation of platinum drugs: targeted Pt(II) agents, nanoparticle delivery, and Pt(IV) prodrugs. Chem Rev 2016;116(5):3436–3486. 17. Shimada M, Itamochi H, Kigawa J. Nedaplatin: a cisplatin derivative in cancer chemotherapy. Cancer Manag Res 2013;5:67–76. 18. Fojo T, Farrell N, Ortuzar W, et al. Identification of non-cross-resistant platinum compounds with novel cytotoxicity profiles using the NCI anticancer drug screen and clustered image map visualizations. Crit Rev Oncol Hematol 2005;53(1):25–34. 19. Subbiah V, Grilley-Olson JE, Combest AJ, et al. Phase Ib/II trial of NC-6004 (nanoparticle cisplatin) plus gemcitabine in patients with advanced solid tumors. Clin Cancer Res 2018;24(1):43–51. 20. Farrell N, Qu Y, Bierbach U, et al. Structure-activity relationships within di- and trinuclear platinum phase-I clinical anticancer agents. In: Lippert B, ed. Cisplatin: Chemistry and Biochemistry of a Leading Anticancer Drug. Zurich: Verlag Helvetica Chimica Acta; 1999:477–496. 21. Calvert PM, Highley MS, Hughes AN, et al. A phase I study of a novel, trinuclear, platinum analogue, BBR3464, in patients with advanced solid tumors. Clin Cancer Res 1999;5:3796S 22. Holford J, Sharp SY, Murrer BA, et al. In vitro circumvention of cisplatin resistance by the novel sterically hindered platinum complex AMD473. Br J Cancer 1998;77(3):366–373. 23. Flaherty KT, Stevenson JP, Redlinger M, et al. A phase I, dose escalation trial of ZD0473, a novel platinum analogue, in combination with gemcitabine. Cancer Chemother Pharmacol 2004;53(5):404–408.

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24. Park GY, Wilson JJ, Song Y, et al. Phenanthriplatin, a monofunctional DNA-binding platinum anticancer drug candidate with unusual potency and cellular activity profile. Proc Natl Acad Sci U S A 2012;109(30):11987–11992. 25. Eastman A. The formation, isolation and characterization of DNA adducts produced by anticancer platinum complexes. Pharmacol Ther 1987;34(2):155–166. 26. Zhu G, Song L, Lippard SJ. Visualizing inhibition of nucleosome mobility and transcription by cisplatin-DNA interstrand crosslinks in live mammalian cells. Cancer Res 2013;73(14):4451–4460. 27. Martens-de Kemp SR, Dalm SU, Wijnolts FM, et al. DNA-bound platinum is the major determinant of cisplatin sensitivity in head and neck squamous carcinoma cells. PLoS One 2013;8(4):e61555. 28. Blommaert FA, van Dijk-Knijnenburg HC, Dijt FJ, et al. Formation of DNA adducts by the anticancer drug carboplatin: different nucleotide sequence preferences in vitro and in cells. Biochemistry 1995;34(26):8474–8480. 29. Bruno PM, Liu Y, Park GY, et al. A subset of platinum-containing chemotherapeutic agents kills cells by inducing ribosome biogenesis stress. Nat Med 2017;23(4):461–471. 30. Enoiu M, Jiricny J, Schärer OD. Repair of cisplatin-induced DNA interstrand crosslinks by a replicationindependent pathway involving transcription-coupled repair and translesion synthesis. Nucleic Acids Res. 2012;40(18):8953–8964. doi: 10.1093/nar/gks670. 31. Sorenson CM, Eastman A. Mechanism of cis-diamminedichloroplatinum (II)-induced cytotoxicity: role of G2 arrest and DNA double-strand breaks. Cancer Res 1988;48(16):4484–4488. 32. Toney JH, Donahue BA, Kellett PJ, et al. Isolation of cDNAs encoding a human protein that binds selectively to DNA modified by the anticancer drug cis-diamminedichloroplatinum(II). Proc Natl Acad Sci U S A 1989;86(21):8328–8332. 33. Bruhn SL, Pil PM, Essigmann JM, et al. Isolation and characterization of human cDNA clones encoding a high mobility group box protein that recognizes structural distortions to DNA caused by binding of the anticancer agent cisplatin. Proc Natl Acad Sci U S A 1989;89(6):2307–2311. 34. Hughes EN, Engelsberg BN, Billings PC. Purification of nuclear proteins that bind to cisplatin-damaged DNA. Identity with high mobility group proteins 1 and 2. J Biol Chem 1992;267(19):13520–13527. 35. Ramachandran S, Temple BR, Chaney SG, et al. Structural basis for the sequence-dependent effects of platinumDNA adducts. Nucleic Acids Res 2009;37(8):2434–2448. 36. Ramachandran S, Temple B, Alexandrova AN, et al. Recognition of platinum-DNA adducts by HMGB1a. Biochemistry 2012;51(38):7608–7617. 37. Fink D, Zheng H, Nebel S, et al. In vitro and in vivo resistance to cisplatin in cells that have lost DNA mismatch repair. Cancer Res 1997;57(10):1841–1845. 38. Glasspool RM, Brown R, Gore ME, et al. A randomised, phase II trial of the DNA-hypomethylating agent 5-aza-2′deoxycytidine (decitabine) in combination with carboplatin vs carboplatin alone in patients with recurrent, partially platinum-sensitive ovarian cancer. Br J Cancer. 2014;110(8):1923–1929. 39. International Collaborative Ovarian Neoplasm Group. Paclitaxel plus carboplatin versus standard chemotherapy with either single-agent carboplatin or cyclophosphamide, doxorubicin, and cisplatin in women with ovarian cancer: the ICON3 randomised trial. Lancet 2002;360(9332):505–515. 40. Calvert AH, Jackson JC, Hutton C, et al. Evaluation of p53 mutation as a predictive biomarker for outcome to chemotherapy in ovarian cancer. J Clin Oncol 2011;29(15 Suppl):10522. 41. Galluzzi L, Senovilla L, Vitale I, et al. Molecular mechanisms of cisplatin resistance. Oncogene 2012;31(15):1869– 1883. 42. Vasilevskaya IA, Selvakumaran M, O’Dwyer PJ. Disruption of signaling through SEK1 and MKK7 yields differential responses in hypoxic colon cancer cells treated with oxaliplatin. Mol Pharmacol 2008;74(1):246–254. 43. Vasilevskaya IA, Selvakumaran M, Hierro LC, et al. Inhibition of JNK sensitizes hypoxic colon cancer cells to DNA-damaging agents. Clin Cancer Res 2015;21(18):4143–4152. 44. Carrassa L, Damia G. DNA damage response inhibitors: mechanisms and potential applications in cancer therapy. Cancer Treat Rev 2017;60:139–151. 45. Rancoule C, Vallard A, Guy JB, et al. Impairment of DNA damage response and cancer. Bull Cancer 2017;104(11):962–970. 46. Tassone P, Di Martino MT, Ventura M, et al. Loss of BRCA1 function increases the antitumor activity of cisplatin against human breast cancer xenografts in vivo. Cancer Biol Ther 2009;8(7):648–653. 47. Bryant HE, Schultz N, Thomas HD, et al. Specific killing of BRCA2-deficient tumours with inhibitors of poly(ADP-ribose) polymerase. Nature 2005;434(7035):913–917. 48. Sakai W, Swisher EM, Karlan BY, et al. Secondary mutations as a mechanism of cisplatin resistance in BRCA2mutated cancers. Nature 2008;451(7182):1116–1120.

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49. Maestre N, Tritton TR, Laurent G, et al. Cell surface-directed interaction of anthracyclines leads to cytotoxicity and nuclear factor kappaB activation but not apoptosis signaling. Cancer Res 2001;61(6):2558–2561. 50. Roodhart JM, Daenen LG, Stigter EC, et al. Mesenchymal stem cells induce resistance to chemotherapy through the release of platinum-induced fatty acids. Cancer Cell 2011;20(3):370–383. 51. Beatty GL, Chiorean EG, Fishman MP, et al. CD40 regulates cancer inflammation and induces regression of pancreatic carcinoma in mice and humans. Science 2011;331:1612–1616. 52. Galluzzi L, Buqué A, Kepp O, et al. Immunological effects of conventional chemotherapy and targeted anticancer agents. Cancer Cell 2015;28(6):690–714. 53. Mahoney KM, Rennert PD, Freeman GJ. Combination cancer immunotherapy and new immunomodulatory targets. Nat Rev Drug Discov 2015;14(8):561–584. 54. Kelland L. The resurgence of platinum-based cancer chemotherapy. Nat Rev Cancer 2007;7(8):573–584. 55. Lin X, Okuda T, Holzer A, et al. The copper transporter CTR1 regulates cisplatin uptake in Saccharomyces cerevisiae. Mol Pharmacol 2002;62(5):1154–1159. 56. Blair BG, Larson CA, Safaei R, et al. Copper transporter 2 regulates the cellular accumulation and cytotoxicity of cisplatin and carboplatin. Clin Cancer Res 2009;15(13):4312–4321. doi: 10.1158/1078-0432.CCR-09-0311. 57. Samimi G, Varki NM, Wilczynski S, et al. Increase in the expression of the copper transporter ATP7A during platinum drug-based treatment is associated with poor survival in ovarian cancer patients. Clin Cancer Res 2003;9(16 Pt 1):5853–5859. 58. Britten RA, Green JA, Broughton C, et al. The relationship between nuclear glutathione levels and resistance to melphalan in human ovarian tumour cells. Biochem Pharmacol 1991;41(4):647–649. 59. Mistry P, Kelland LR, Abel G, et al. The relationships between glutathione, glutathione-S-transferase and cytotoxicity of platinum drugs and melphalan in eight human ovarian carcinoma cell lines. Br J Cancer 1991;64(2):215–220. 60. Godwin AK, Meister A, O’Dwyer PJ, et al. High resistance to cisplatin in human ovarian cancer cell lines is associated with marked increase in glutathione synthesis. Proc Natl Acad Sci U S A 1992;89(7):3070–3074. 61. Hamilton TC, Winker MA, Louie KG, et al. Augmentation of adriamycin, melphalan, and cisplatin cytotoxicity in drug-resistant and -sensitive human ovarian carcinoma cell lines by buthionine sulfoximine mediated glutathione depletion. Biochem Pharmacol 1985;34(14):2583–2586. 62. Martin LP, Hamilton TC, and Schilder RJ. Platinum resistance: the role of DNA repair pathways. Clin Cancer Res 2008;14(5):1291–1295. 63. Selvakumaran M, Piscarcik DA, Bao R, et al. Enhanced cisplatin cytotoxicity by disturbing the nucleotide excision repair pathway in ovarian cancer cell lines. Cancer Res 2003;63(6):1311–1316. 64. Friboulet L, Olaussen KA, Pignon JP, et al. ERCC1 isoform expression and DNA repair in non-small-cell lung cancer. N Engl J Med 2013;368(12):1101–1110. 65. Lee SM, Falzon M, Blackhall F, et al. Randomized prospective biomarker trial of ERCC1 for comparing platinum and nonplatinum therapy in advanced non-small-cell lung cancer: ERCC1 trial (ET). J Clin Oncol 2017;35(4):402– 411. 66. Edwards SL, Brough R, Lord CJ, et al. Resistance to therapy caused by intragenic deletion in BRCA2. Nature 2008;451(7182):1111–1115. 67. Gelmon KA, Tischkowitz M, Mackay H, et al. Olaparib in patients with recurrent high-grade serous or poorly differentiated ovarian carcinoma or triple-negative breast cancer: a phase 2, multicentre, open-label, nonrandomised study. Lancet Oncol 2011;12(9):852–861. 68. Teschendorff AE, Lee SH, Jones A, et al. HOTAIR and its surrogate DNA methylation signature indicate carboplatin resistance in ovarian cancer. Genome Med 2015;7:108. 69. Rybstein MD, Bravo-San Pedro JM, Kroemer G, et al. The autophagic network and cancer. Nat Cell Biol 2018;20(3):243–251. 70. Delaney JR, Patel CB, Willis KM, et al. Haploinsufficiency networks identify targetable patterns of allelic deficiency in low mutation ovarian cancer. Nat Commun 2017;8:14423. 71. Amaravadi RK, Yu D, Lum JJ, et al. Autophagy inhibition enhances therapy-induced apoptosis in a Myc-induced model of lymphoma. J Clin Invest 2007;117(2):326–336. 72. Yu T, Guo F, Yu Y, et al. Fusobacterium nucleatum promotes chemoresistance to colorectal cancer by modulating autophagy. Cell 2017;170(3):548–563.e16. 73. Vasilevskaya IA, Selvakumaran M, Roberts D, et al. JNK1 inhibition attenuates hypoxia-induced autophagy and sensitizes to chemotherapy. Mol Cancer Res 2016;14(8):753–763. 74. Chen D, Wu M, Li Y, et al. Targeting BMI1+ cancer stem cells overcomes chemoresistance and inhibits metastases

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in squamous cell carcinoma. Cell Stem Cell 2017;20(5):621–634.e6. 75. Brown JA, Schober M. Joining forces: Bmi1 inhibition and cisplatin curb squamous carcinogenesis. Cell Stem Cell 2017;20(5):575–577. 76. Zhao ZL, Zhang L, Huang CF, et al. NOTCH1 inhibition enhances the efficacy of conventional chemotherapeutic agents by targeting head neck cancer stem cell. Sci Rep 2016;6:24704. 77. Su S, Chen J, Yao H, et al. CD10+GPR77+ cancer-associated fibroblasts promote cancer formation and chemoresistance by sustaining cancer stemness. Cell 2018;172(4):841–856.e16. 78. Duffull SB, Robinson BA. Clinical pharmacokinetics and dose optimization of carboplatin. Clin Pharmacokinet 1997;33(3):161–183. 79. Boer H, Proost JH, Nuver J, et al. Long-term exposure to circulating platinum is associated with late effects of treatment in testicular cancer survivors. Ann Oncol 2015;26(11):2305–2310. 80. Harland SJ, Newell DR, Siddik ZH, et al. Pharmacokinetics of cis-diammine-1, 1-cyclobutane dicarboxylate platinum(II) in patients with normal and impaired renal function. Cancer Res 1984;44(4):1693–1697. 81. Graham MA, Lockwood GF, Greenslade D, et al. Clinical pharmacokinetics of oxaliplatin: a critical review. Clin Cancer Res 2000;6(4):1205–1218. 82. Gamelin E, Bouil AL, Boisdron-Celle M, et al. Cumulative pharmacokinetic study of oxaliplatin, administered every three weeks, combined with 5-fluorouracil in colorectal cancer patients. Clin Cancer Res 1997;3(6):891–899. 83. Extra JM, Marty M, Brienza S, et al. Pharmacokinetics and safety profile of oxaliplatin. Semin Oncol 1998;25(2 Suppl 5):13–22. 84. Chatelut E, Canal P, Brunner V, et al. Prediction of carboplatin clearance from standard morphological and biological patient characteristics. J Natl Cancer Inst 1995;87(8):573–580. 85. Jodrell DI, Egorin MJ, Canetta RM, et al. Relationships between carboplatin exposure and tumor response and toxicity in patients with ovarian cancer. J Clin Oncol 1992;10(4):520–528. 86. Reyno LM, Egorin MJ, Canetta RM, et al. Impact of cyclophosphamide on relationships between carboplatin exposure and response or toxicity when used in the treatment of advanced ovarian cancer. J Clin Oncol 1993;11(6):1156–1164. 87. Shen DW, Pouliot LM, Hall MD, et al. Cisplatin resistance: a cellular self-defense mechanism resulting from multiple epigenetic and genetic changes. Pharmacol Rev 2012;64(3):706–721. doi: 10.1124/pr.111.005637. 88. Ma J, Verweij J, Planting AS, et al. Current sample handling methods for measurement of platinum-DNA adducts in leucocytes in man lead to discrepant results in DNA adduct levels and DNA repair. Br J Cancer 1995;71(3):512–517. 89. Schellens JH, Ma J, Planting AS, et al. Relationship between the exposure to cisplatin, DNA-adduct formation in leucocytes and tumour response in patients with solid tumours. Br J Cancer 1996;73(12):1569–1575.

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22

Antimetabolites James J. Lee and Edward Chu

ANTIFOLATES Reduced folates play a central role in one-carbon metabolism, as they are essential for the biosynthesis of purines, thymidylate, and protein (Table 22.1 and Fig. 22.1). Aminopterin was the first antimetabolite with documented clinical activity in the treatment of children with acute leukemia in the 1940s. Methotrexate (MTX), the 4-amino10-methyl analog of folic acid, was subsequently developed, and it remains a widely used antifolate analog, with activity against a broad range of cancers (Table 22.2), including hematologic malignancies (acute lymphoblastic leukemia and non-Hodgkin lymphoma) and many solid tumors (breast cancer, head and neck cancer, osteogenic sarcoma, bladder cancer, and gestational trophoblastic cancer). Pemetrexed is a pyrrolopyrimidine, multitargeted antifolate analog that targets multiple enzymes involved in folate metabolism, including thymidylate synthase (TS), dihydrofolate reductase (DHFR), glycinamide ribonucleotide (GAR) formyltransferase, and aminoimidazole carboxamide (AICAR) formyltransferase (see Fig. 22.1).1,2 This agent has broad-spectrum activity against solid tumors, including malignant mesothelioma and breast, pancreatic, head and neck, non–small-cell lung, colon, gastric, cervical, and bladder cancer.3–5 The third antifolate compound to be used in clinical practice in the United States is pralatrexate (10-propargyl10-deazaaminopterin), and it was rationally designed to bind with higher affinity to the reduced folate carrier (RFC)-1 transport protein, when compared with MTX, leading to enhanced membrane transport into tumor cells. This analog is also an improved substrate for the enzyme folylpolyglutamyl synthase (FPGS), resulting in enhanced formation of cytotoxic polyglutamate metabolites.6,7 When compared with MTX, this analog is a more potent inhibitor of the folate-associated enzymes, including TS, DHFR, and the enzymes involved in de novo purine biosynthesis (see Fig. 22.1). This agent is currently approved for the treatment of relapsed or refractory peripheral T-cell lymphoma.8

Mechanism of Action The antifolate compounds are tight-binding inhibitors of DHFR, a key enzyme in folate metabolism.1 DHFR plays a pivotal role in maintaining the intracellular folate pools in their fully reduced form as tetrahydrofolates, and these compounds serve as one-carbon carriers required for the synthesis of thymidylate, purine nucleotides, and certain amino acids. TABLE 22.1

Antimetabolites: Mechanisms of Action and Resistance Class

Drugs

Mechanism of Action

Mechanism of Resistance

Antifolates

Methotrexate Pemetrexed Pralatrexate

Inhibition of DHFR, TS, and enzymes involved in de novo purine biosynthesis

Alteration in drug transport Reduced levels of polyglutamate metabolites Increased expression of target proteins, such as DHFR and TS Alterations in DHFR and TS with reduced binding affinity

Fluoropyrimidines

5-FU Capecitabine TAS-102

Inhibition of TS Incorporation into RNA Incorporation into DNA Activation of programmed cell death pathways

Increased expression of TS Mutations in TS with reduced binding affinity to FdUMP Decreased expression of DNA mismatch repair enzymes (hMLH1

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and hMSH2) Increased expression of dihydropyrimidine dehydrogenase Deoxycytidine analogs

Purine analogs

Cytarabine

Inhibition of DNA polymerases α, β, and γ DNA chain termination by direct incorporation of ara-CTP into DNA Inhibition of ribonucleotide reductase, reducing the levels of key dNTP pools

Reduced nucleoside transport Reduced expression of deoxycytidine kinase with reduced formation of ara-CMP Increased expression and/or activity of cytidine deaminase and dCMP deaminase

Gemcitabine

DNA chain termination by incorporation of gemcitabine triphosphate into DNA Inhibition of DNA polymerases α, β, and γ Inhibition of ribonucleotide reductase, reducing the levels of key dNTP pools

Reduced expression and/or activity of nucleoside transport protein Reduced expression and/or deficiency in deoxycytidine kinase enzyme activity Increased expression and/or activity of cytidine deaminase and dCMP deaminase Increased biosynthesis of dCTP

6-MP 6-TG

Inhibition of enzymes involved in de novo purine synthesis Incorporation of triphosphate nucleotides into either cellular RNA or DNA

Deficiency of hypoxanthine-guanine phosphoribosyltransferase Increased concentrations of a membrane-bound alkaline phosphatase Increased expression and/or activity of thiopurine methyltransferase Decreased expression of DNA mismatch repair enzymes (hMLH1 and hMSH2)

Fludarabine

DNA chain termination by incorporation of fludarabine triphosphate into DNA Inhibition of DNA polymerases, DNA primase, DNA ligase I, and ribonucleotide reductase Incorporation of fludarabine triphosphate into RNA

Reduced expression of deoxycytidine kinase Reduced nucleoside transport

Cladribine

DNA chain termination due to incorporation of cladribine triphosphate into DNA Inhibition of DNA synthesis and repair due to imbalance in deoxyribonucleotide pools by progressive accumulation of cladribine triphosphate

Reduced expression of deoxycytidine kinase Reduced nucleoside transport Increased activity of cytoplasmic enzyme 5′-nucleotidase

Clofarabine

DNA chain termination by Reduced expression of incorporation of clofarabine deoxycytidine kinase triphosphate into DNA Decreased nucleoside transport Inhibition of DNA polymerases α, β, Increased expression and/or activity and γ of CTP synthetase DHFR, dihydrofolate reductase; TS, thymidylate synthase; 5-FU, 5-fluorouracil; TAS-102, trifluridine/tipiracil; FdUMP, fluorodeoxyuridine monophosphate; hMLH1, human mutL homolog 1; hMLH2, human mutS homolog 2; ara-CTP, cytarabine triphosphate; dNTP, deoxyribonucleotide triphosphate; ara-CMP, cytarabine monophosphate; dCMP, deoxycytidine monophosphate; dCTP, deoxycytidine triphosphate; 6-MP, 6-mercaptopurine; 6-TG, 6-thioguanine; CTP, cytidine triphosphate.

The cytotoxic effects of all of the antifolates are mediated by their respective polyglutamate metabolites, with up to five to seven glutamate groups added in a γ-peptide linkage to the terminal glutamate residue present on the parent molecule. These polyglutamate metabolites exhibit prolonged intracellular half-lives, thereby allowing for prolonged drug action in tumor cells. These polyglutamate metabolites are also potent, direct inhibitors of DHFR, TS, and the enzymes involved in de novo purine biosynthesis (see Table 22.1).1

Mechanisms of Resistance The development of cellular resistance to antifolates remains a major obstacle to their clinical efficacy.9,10 In

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preclinical experimental systems, resistance to antifolates arises from several mechanisms, including alterations in antifolate transport because of a defect in either the reduced folate carrier transport protein or folate receptor systems, decreased polyglutamation of the antifolate parent compound through either decreased expression of FPGS or increased expression of the catabolic enzyme γ-glutamyl hydrolase, and alterations in the target enzymes DHFR and/or TS through increased expression of wild-type protein or overexpression of a mutant protein with reduced binding affinity for the antifolate. Gene amplification resulting in increased gene copy number is a common resistance mechanism observed in various experimental systems, including patient tumor samples. In in vitro, in vivo, and clinical models, the levels of DHFR and/or TS protein acutely increase after exposure to MTX and other antifolate compounds. This acute induction of target proteins in response to drug exposure is mediated, in part, by a translational regulatory mechanism, which represents a clinically relevant mechanism for the development of acute cellular drug resistance.

Figure 22.1 Antifolates and their mechanisms of action. dUMP, deoxyuridine monophosphate; dTTP, deoxythymidine triphosphate; dTDP, deoxyuridine diphosphate; dTMP, deoxythymidine monophosphate; CH2THF, 5,10-methylenetetrahydrofolate; THF, tetrahydrofolate; DHF, dihydrofolate; TK, thymidine kinase.

Clinical Pharmacology The oral bioavailability of MTX is saturable and erratic at doses greater than 25 mg/m2. MTX is completely absorbed from parenteral routes of administration, and peak serum levels are achieved within 30 to 60 minutes of administration. The distribution of this agent into third-space fluid collections, such as pleural effusions and ascites, can substantially alter its pharmacokinetics. The slow release of accumulated drug from these third-space collections over time prolongs the terminal half-life of the drug, leading to potentially increased clinical toxicity. As a result, these fluid collections should be drained prior to initiation of treatment and plasma drug concentrations should be closely monitored. Renal excretion is the main route of drug elimination for all the antifolates. They should, therefore, be used with caution in patients with renal dysfunction. In addition, renal excretion is inhibited in the presence of other agents including probenecid, penicillins, cephalosporins, aspirin, and nonsteroidal anti-inflammatory drugs.

Toxicity The main side effects of MTX are myelosuppression and gastrointestinal (GI) toxicity, and these toxicities are usually completely reversed within 14 days, unless drug-elimination mechanisms are impaired. In the setting of

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compromised renal function, even small doses of the drug may result in serious toxicity. MTX-induced nephrotoxicity results from the intratubular precipitation of parent drug and its metabolites in acidic urine. In addition, MTX may exert a direct toxic effect on the renal tubules. Vigorous hydration and urinary alkalinization have greatly reduced the incidence of renal failure in patients on high-dose regimens. Acute elevations in hepatic enzyme levels and hyperbilirubinemia are often observed during high-dose therapy, but these levels usually return to normal within 10 days. When given concomitantly with radiotherapy, MTX may increase the risk of soft tissue necrosis and osteonecrosis. The original rationale for high-dose MTX therapy was based on the concept of selective rescue of normal tissues by the reduced folate leucovorin. Of note, leucovorin is a racemic mixture with the l-isoform being the active moiety. There is now growing evidence that high-dose MTX may also overcome several key drug resistance mechanisms. The main toxicities of pemetrexed and pralatrexate include myelosuppression, mucositis, and skin rash, usually in the form of the hand-foot syndrome. Other toxicities include reversible transaminasemia, anorexia and fatigue syndrome, and GI toxicity. These side effects are reduced by vitamin supplementation with folic acid (350 μg orally daily) and vitamin B12 (1,000 μg subcutaneously given at least 1 week before starting therapy and then repeated every three cycles). Importantly, vitamin supplementation does not impair the clinical efficacy of pemetrexed or pralatrexate. Premedication with dexamethasone (or an equivalent steroid) has been shown to reduce the incidence and severity of skin rash. TABLE 22.2

Antimetabolites: Indications, Doses and Schedules, and Toxicities Drug

Clinical Indications

Doses and Schedule

Major Toxicities

Methotrexate

NHL Primary CNS lymphoma ALL Breast cancer Bladder cancer Osteogenic sarcoma Gestational trophoblastic cancer

Low dose: 10–50 mg/m2 IV every 3– 4 wk Low dose weekly: 25 mg/m2 IV weekly Moderate dose: 100–500 mg/m2 IV every 2–3 wk High dose: 1–12 g/m2 IV over a 3- to 24-h period every 1–3 wk IT: 10–15 mg IT 2 times weekly until CSF is clear, then weekly dose for 2–6 wk, followed by monthly dose

Mucositis, diarrhea, myelosuppression, acute renal failure, transient elevations in serum transaminases and bilirubin, pneumonitis, neurologic toxicity

Pemetrexed

Mesothelioma NSCLC

500 mg/m2 IV every 3 wk

Myelosuppression, skin rash, mucositis, diarrhea, fatigue

Pralatrexate

Peripheral T-cell lymphoma

30 mg/m2 IV weekly for 6 wk; cycles repeated every 7 wk

Myelosuppression, skin rash, mucositis, diarrhea, elevation of serum transaminases and bilirubin, mild nausea/vomiting

5-FU

Breast cancer CRC Anal cancer Gastroesophageal cancer HCC Pancreatic cancer Head and neck cancer

Bolus monthly schedule: 425–450 mg/m2 IV on days 1–5 every 28 d Bolus weekly schedule: 500–600 mg/m2 IV every week for 6 weeks every 8 wk Infusion schedule: 2,400–3,000 mg/m2 IV over 46 h every 2 wk 120-h infusion: 1,000 mg/m2/d IV on days 1–5 every 21–28 d Protracted continuous infusion: 200– 400 mg/m2/d IV

Nausea/vomiting, diarrhea, mucositis, myelosuppression, neurotoxicity, coronary artery vasospasm, conjunctivitis

Capecitabine

Breast cancer CRC Gastroesophageal cancer HCC Pancreatic cancer

Recommended dose for monotherapy: 1,250 mg/m2 PO bid for 2 wk with 1-wk rest May decrease dose of capecitabine to 850–1,000 mg/m2 bid on days 1– 14 to reduce risk of toxicity without compromising efficacy

Diarrhea, hand-foot syndrome, myelosuppression, mucositis, nausea/vomiting, neurologic toxicity, coronary artery vasospasm

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Alternative dosing schedule for monotherapy: 1,250–1,500 mg/m2 PO bid for 1 wk on and 1 wk off; this schedule appears to be well tolerated, with no compromise in clinical efficacy Combination: capecitabine should be used at lower doses (850–1,000 mg/m2 bid on days 1–14) when used in combination with other cytotoxic agents, such as oxaliplatin, irinotecan, docetaxel, and lapatinib TAS-102

CRC

Recommended dose is 35 mg/m2/dose PO bid on days 1–5 and days 8–12 of each 28-d cycle

Anemia, neutropenia, thrombocytopenia, asthenia/fatigue, nausea, anorexia, diarrhea, nausea/vomiting, and abdominal pain

Cytarabine

Hodgkin lymphoma NHL AML ALL

Standard dose: 100 mg/m2/d IV on days 1–7 as a continuous IV infusion, in combination with an anthracycline, as induction chemotherapy for AML High dose: 1.5–3.0 g/m2 IV every 12 h for 3 d as a high-dose, intensification regimen for AML IT: 10–30 mg IT up to 3 times weekly in the treatment of leptomeningeal carcinomatosis secondary to leukemia or lymphoma

Nausea/vomiting, myelosuppression, cerebellar ataxia, lethargy, confusion, acute pancreatitis, drug infusion reaction, hand-foot syndrome High-dose therapy: noncardiogenic pulmonary edema, acute respiratory distress and Streptococcus viridans pneumonia, conjunctivitis, and keratitis

Gemcitabine

Pancreatic cancer NSCLC Breast cancer Bladder cancer Hodgkin lymphoma Ovarian cancer Soft tissue sarcoma

Pancreatic cancer: 1,000 mg/m2 IV every week for 7 wk with 1-wk rest; treatment then continues weekly for 3 wk followed by 1-wk off Bladder cancer: 1,000 mg/m2 IV on days 1, 8, and 15 every 28 d NSCLC: 1,000–1,200 mg/m2 IV on days 1 and 8 every 21 d

Nausea/vomiting, myelosuppression, flu-like syndrome, elevation of serum transaminases and bilirubin, pneumonitis, infusion reaction, mild proteinuria, and rarely, hemolyticuremic syndrome and thrombotic thrombocytopenic purpura

6-MP

ALL

Induction therapy: 2.5 mg/kg PO daily Maintenance therapy: 1.5–2.5 mg/kg PO daily

Myelosuppression, nausea/vomiting, mucositis and diarrhea, hepatotoxicity, immunosuppression

6-TG

AML ALL

Induction: 100 mg/m2 PO every 12 h on days 1–5, usually in combination with cytarabine Maintenance: 100 mg/m2 PO every 12 h on days 1–5, every 4 wk, usually in combination with other agents Single agent: 1–3 mg/kg PO daily

Myelosuppression, nausea/vomiting, mucositis and diarrhea, hepatotoxicity, immunosuppression

Fludarabine

CLL NHL

25 mg/m2 IV on days 1–5 every 28 d For oral usage, the recommended dose is 40 mg/m2 PO on days 1–5 every 28 d

Myelosuppression, immunosuppression with increased risk of opportunistic infections, mild nausea/vomiting, hypersensitivity reaction

Cladribine

Hairy cell leukemia CLL NHL

0.09 mg/kg/d IV via continuous infusion for 7 d; one course is usually administered

Myelosuppression, immunosuppression, mild nausea/vomiting, fever

Clofarabine

ALL

52 mg/m2 IV daily for 5 d every 2–6 wk

Myelosuppression nausea/vomiting, diarrhea, systemic inflammatory response syndrome, increased risk of opportunistic infections, renal toxicity NHL, non-Hodgkin lymphoma; CNS, central nervous system; ALL, acute lymphoblastic leukemia; IV, intravenous; IT, intrathecal; CSF, cerebrospinal fluid; NSCLC, non–small-cell lung cancer; 5-FU, 5-fluorouracil; CRC, colorectal cancer; HCC, hepatocellular

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cancer; bid, twice daily; TAS-102, trifluridine/tipiracil; AML, acute myelogenous leukemia; 6-MP, 6-mercaptopurine; 6-TG, 6thioguanine; CLL, chronic lymphocytic leukemia.

5-FLUOROPYRIMIDINES The fluoropyrimidine 5-fluorouracil (5-FU) was synthesized by Charles Heidelberger in the mid-1950s. Uracil is a normal component of RNA; as such, the rationale leading to the development of the drug was that cancer cells might be more sensitive to molecules that mimic the natural compound than normal cells. 5-FU and analog compounds are an integral part of treatment for a wide range of solid tumors (see Table 22.2), including GI malignancies (colorectal, esophageal, gastric, pancreatic, anal, and hepatocellular cancers), breast cancer, and head and neck cancer.11 It continues to serve as the main backbone for combination regimens used to treat metastatic colorectal cancer and as adjuvant therapy of early-stage colon cancer.

Mechanism of Action 5-FU enters cells via the facilitated uracil base transport mechanism and is then metabolized via anabolism to various cytotoxic nucleotide forms by several biochemical pathways. It is well-established that 5-FU exerts its cytotoxic effects through various mechanisms, including (1) inhibition of TS, (2) incorporation into RNA, and (3) incorporation into DNA (see Table 22.1 and Fig. 22.1). In addition to these mechanisms, the genotoxic stress resulting from TS inhibition may also activate programmed cell-death pathways in susceptible cells, which leads to the induction of DNA fragmentation.

Mechanisms of Resistance Several resistance mechanisms to 5-FU have been identified in experimental and clinical settings. An alteration in the target enzyme TS with increased expression represents the most commonly described mechanism of resistance. In vitro, in vivo, and clinical studies have documented a strong correlation between the levels of TS enzyme activity/TS protein and chemosensitivity to 5-FU. In this regard, cell lines and tumors with higher levels of TS are relatively more resistant to 5-FU. Mutations in the TS protein have been identified with reduced binding affinity of the cytotoxic 5-FU metabolite fluorodeoxyuridine monophosphate (FdUMP) to the TS protein. Reduced expression and/or diminished activity of key activating enzymes may interfere with the formation of cytotoxic 5-FU metabolites. Decreased expression of DNA mismatch repair enzymes, such as human mutL homolog 1 (hMLH1) and human mutS homolog 2 (hMSH2), and increased expression of the catabolic enzyme dihydropyrimidine dehydrogenase (DPD) are also associated with fluoropyrimidine resistance. Despite being used in the clinic for well over 50 years, the relative contribution of each of these mechanisms in the development of cellular resistance to 5-FU in the clinical setting remains unclear.

Clinical Pharmacology Because of its erratic bioavailability resulting from high levels of the catabolic enzyme DPD present in the gut mucosa, 5-FU is not administered via the oral route. After intravenous (IV) bolus doses, metabolic elimination is rapid, resulting in a short half-life of 8 to 15 minutes. Up to 80% to 85% of an administered dose of 5-FU is inactivated by DPD, the rate-limiting enzyme in the catabolism of 5-FU (Fig. 22.2). A pharmacogenetic syndrome has been identified in which partial or complete deficiency in the DPD enzyme is present in 3% to 5% and 0.1% of the general population, respectively. Because this enzyme catalyzes the ratelimiting step in the catabolic pathway of 5-FU, a deficiency in this enzyme can result in a significant increase in 5FU cytotoxic metabolites. Unfortunately, patients with DPD deficiency do not manifest a phenotype until they are treated with 5-FU. Upon treatment with 5-FU, patients typically develop severe excessive toxicity in the form of mucositis and/or diarrhea, myelosuppression, neurologic toxicity, and in rare cases, death. In patients being treated with 5-FU or any other fluoropyrimidine, it is important to consider DPD deficiency in patients who present with excessive, severe toxicity.12 It is now increasingly appreciated that DPD mutations do not account for all of the observed cases of increased 5-FU toxicity, as up to 40% to 50% of patients who experience 5-FU toxicity will have no documented alterations in the DPD gene. Moreover, individuals with normal DPD enzyme activity may be diagnosed with elevated plasma levels of 5-FU, resulting in increased toxicity. Although DPD enzyme activity can be assayed from peripheral blood mononuclear cells in a specialized laboratory, routine phenotypic and genotypic screenings for DPD deficiency prior to 5-FU therapy are not yet readily available.

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Figure 22.2 5-Fluorouracil (5-FU) metabolism. DPD, dihydropyrimidine dehydrogenase; FUrd, 5fluorouridine; FUMP, 5-fluorouridine-5′-monophosphate; FUDP, fluorouridine diphosphate; FUTP, fluorouridine triphosphate; FUPA, α-fluoro-β-ureidopropionic acid; FUdR, fluorodeoxyuridine; FBAL, α-fluoro-β-alanine; FdUMP, fluorodeoxyuridine monophosphate; FdUDP, fluorodeoxyuridine diphosphate; FdUTP, fluorodeoxyuridine triphosphate; dUMP, deoxyuridine monophosphate; TS, thymidylate synthase; dTMP, deoxythymidine monophosphate; 5,10-CH2THF, 5,10-methylenetetrahydrofolate; DHF, dihydrofolate. 5-FU dosing is typically determined by body surface area. However, dosing of 5-FU by body surface area, as with dosing of most cytotoxic agents, is correlated with significant variation of 5-FU systemic exposure. Pharmacokinetic studies of 5-FU systemic exposure have shown a wide range of inter- and intrapatient variation of 5-FU plasma drug levels, which in some cases may be up to 30- to 100-fold.13 There is growing evidence to show that 5-FU dosing based on plasma 5-FU drug level is feasible and that 5-FU therapeutic drug monitoring can improve clinical outcomes by improving efficacy of 5-FU–based combination regimens and reducing toxicities.13

Biomodulation of 5-FU Significant efforts have focused on enhancing the antitumor activity of 5-FU through biochemical modulation in which 5-FU is combined with various agents, including leucovorin, MTX, N-phosphonacetyl-L-aspartic acid, interferon-α, interferon-γ, and several other agents.14 For the past 30 years, the reduced folate leucovorin has been the main biochemical modulator of 5-FU. An alternative approach has been to alter the schedule of 5-FU administration. Given the S-phase specificity of this agent, prolonged exposure of tumor cells to 5-FU would increase the fraction of cells being exposed to the drug. Overall response rates are significantly higher in patients treated with infusional schedules of 5-FU than in those treated with bolus 5-FU, and this improvement in response rate has translated into an improved progression-free survival. Moreover, the overall safety profile is improved with infusional regimens. A hybrid schedule of bolus and infusional 5-FU was originally developed in France, and this regimen has shown superior clinical activity compared with bolus 5-FU schedules. This hybrid schedule can be simplified by using only the 46-hour infusion of 5-FU and completely eliminating the 5-FU bolus doses. This modification has maintained the clinical activity of 5-FU while reducing some of the associated toxicities, mainly in the form of myelosuppression.

Toxicity

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The spectrum of 5-FU toxicity is dose- and schedule-dependent (see Table 22.2). The main side effects are diarrhea, mucositis, and myelosuppression. Diarrhea and the dermatologic hand-foot syndrome are more commonly observed with infusional 5-FU therapy. Acute neurologic symptoms have also been reported, and they include somnolence, cerebral dysfunction, cerebellar ataxia, and upper motor signs. Treatment with 5-FU can, on rare occasions, cause coronary vasospasm, resulting in a syndrome of chest pain, cardiac enzyme elevations, and electrocardiographic changes. Cardiac toxicity appears to be related more to infusional 5-FU than bolus administration.15

CAPECITABINE Capecitabine is an oral fluoropyrimidine analog that was rationally designed to allow for selective 5-FU activation in tumor tissue.16 This oral agent was initially approved in anthracycline- and taxane-resistant breast cancer and subsequently approved for use in combination with docetaxel as second-line therapy in metastatic breast cancer and in combination with the small molecule lapatinib in women with human epidermal growth factor receptor type 2 (HER2)–positive metastatic breast cancer following progression on trastuzumab-based therapy.17 This agent is also approved by the U.S. Food and Drug Administration (FDA) for the first-line treatment of metastatic colorectal cancer and as adjuvant therapy for stage III colon cancer when fluoropyrimidine therapy alone is preferred.18 In Europe and throughout most of the world, the combination of capecitabine plus oxaliplatin (XELOX) is approved for the treatment of metastatic colorectal cancer and for the adjuvant therapy of stage III colon cancer.19 Recent clinical studies have also documented the equivalence of capecitabine to infusional 5-FU when combined with cisplatin in the treatment of metastatic gastric cancer.

Clinical Pharmacology Given its chemical structure, capecitabine, in contrast to 5-FU, is rapidly and extensively absorbed by the gut mucosa, with nearly 80% oral bioavailability. It is inactive in its parent form and undergoes enzymatic conversion via three successive steps, with the first two reactions occurring mainly in the liver. The third and final step occurs preferentially in tumor tissue and involves the conversion of 5-deoxy-5-fluorouridine to 5-FU by the enzyme thymidine phosphorylase, which is expressed at much higher levels in tumors when compared with corresponding normal tissue. Capecitabine and capecitabine metabolites are primarily excreted by the kidneys, and, in contrast to 5-FU, caution must be taken in the presence of renal dysfunction, with appropriate dose modification. No dose reduction is needed when the creatinine clearance (CrCl) is >50 mL per minute. A 25% dose reduction is recommended when the CrCl is between 30 and 50 mL per minute, and capecitabine is absolutely contraindicated in patients whose CrCl G, c.1236G>A/HapB3, and c.1601G>A as predictors of severe fluoropyrimidine-associated toxicity: a systematic review and meta-analysis of individual patient data. Lancet Oncol 2015;16(16):1639–1650. 13. Lee JJ, Beumer JH, Chu E. Therapeutic drug monitoring of 5-fluorouracil. Cancer Chemother Pharmacol 2016;78(3):447–464. 14. Grem JL. Biochemical modulation of 5-FU in systemic treatment of advanced colorectal cancer. Oncology (Williston Park) 2001;15(1 Suppl 2):13–19. 15. Layoun ME, Wickramasinghe CD, Peralta MV, et al. Fluoropyrimidine-induced cardiotoxicity: manifestations, mechanisms, and management. Curr Oncol Rep 2016;18(6):35. 16. Walko CM, Lindley C. Capecitabine: a review. Clin Ther 2005;27(1):23–44. 17. Geyer CE, Forster J, Lindquist D, et al. Lapatinib plus capecitabine for HER2-positive advanced breast cancer. N Engl J Med 2006;355(26):2733–2743. 18. Mikhail SE, Sun JF, Marshall JL. Safety of capecitabine: a review. Expert Opin Drug Saf 2010;9(5):831–841. 19. Van Custem E, Verslype C, Tejpar S. Oral capecitabine: bridging the Atlantic divide in colon cancer treatment. Semin Oncol 2005;32(1):43–51. 20. Haller DG, Cassidy J, Clarke SJ, et al. Potential regional differences for the tolerability profiles of fluoropyrimidines. J Clin Oncol 2008;26(13):2118–2123. 21. Lee JJ, Chu E. Adherence, dosing, and managing toxicities with trifluridine/tipiracil (TAS-102). Clin Colorectal Cancer 2017;16(2):85–92. 22. Hong DS, Abbruzzese JL, Bogaard K, et al. Phase I study to determine the safety and pharmacokinetics of oral administration of TAS-102 in patients with solid tumors. Cancer 2006;107(6):1383–1390. 23. Overman MJ, Varadhachary G, Kopetz S, et al. Phase 1 study of TAS-102 administered once daily on a 5-day-perweek schedule in patients with solid tumors. Invest New Drugs 2008;26(5):445–454. 24. Lee JJ, Seraj J, Yoshida K, et al. Human mass balance study of TAS-102 using (14)C analyzed by accelerator mass spectrometry. Cancer Chemother Pharmacol 2016;77(3):515–526. 25. Mayer RJ, van Cutsem E, Falcone A, et al. Randomized trial of TAS-102 for refractory metastatic colorectal cancer. N Engl J Med 2015;372(20):1909–1919. 26. Muggia F, Diaz I, Peters GJ. Nucleoside and nucleobase analogs in cancer treatment: not only sapacitabine, but also gemcitabine. Expert Opin Investig Drugs 2012;21(4):403–408. 27. Galmarini CM, Thomas X, Calvo F, et al. In vivo mechanisms of resistance to cytarabine in acute myeloid leukaemia. Br J Haematol 2002;117(4):860–868. 28. Lamba JK. Genetic factors influencing cytarabine therapy. Pharmacogenomics 2009;10(10):1657–1674. 29. Marin JJ, Briz O, Rodríguez-Macias G, et al. Role of drug transport and metabolism in the chemoresistance of acute myeloid leukemia. Blood Rev 2016;30(1):55–64. 30. Löwenberg B. Sense and nonsense of high-dose cytarabine for acute myeloid leukemia. Blood 2013;121(1):26–28. 31. de Sousa Cavalcante L, Monteiro G. Gemcitabine: metabolism and molecular mechanisms of action, sensitivity and chemoresistance in pancreatic cancer. Eur J Pharmacol 2014;741:8–16. 32. Gesto DS, Cerqueira NM, Fernandes PA, et al. Gemcitabine: a critical nucleoside for cancer therapy. Curr Med Chem 2012;19(7):1076–1087. 33. Binenbaum Y, Na’ara S, Gil Z. Gemcitabine resistance in pancreatic ductal adenocarcinoma. Drug Resist Updat

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2015;23:55–68. 34. Nordh S, Ansari D, Andersson R. hENT1 expression is predictive of gemcitabine outcome in pancreatic cancer: a systematic review. World J Gastroenterol 2014;20(26):8482–8490. 35. Zhao S, Chen C, Chang K, et al. CD44 expression level and isoform contributes to pancreatic cancer cell plasticity, invasiveness, and response to therapy. Clin Cancer Res 2016;22(22):5592–5604. 36. Shukla SK, Purohit V, Mehla K, et al. MUC1 and HIF-1 alpha signaling crosstalk induces anabolic glucose metabolism to impart gemcitabine resistance to pancreatic cancer. Cancer Cell 2017;32:71–87. 37. Poplin E, Feng Y, Berlin J, et al. Phase III, randomized study of gemcitabine and oxaliplatin versus gemcitabine (fixed-dose rate infusion) compared with gemcitabine (30-minute infusion) in patients with pancreatic carcinoma E6201: a trial of the Eastern Cooperative Oncology Group. J Clin Oncol 2009;27(30):3778–3785. 38. Hande KR. Purine antimetabolites. In: Chabner BA, Longo DL, eds. Cancer Chemotherapy and Biotherapy: Principles and Practice. 4th ed. Philadelphia: Lippincott-Raven; 2006: 212. 39. Sahasranaman S, Howard D, Roy S. Clinical pharmacology and pharmacogenetics of thiopurines. Eur J Clin Pharmacol 2008;64(8):753–767. 40. Relling MV, Gardner EE, Sandborn WJ, et al. Clinical pharmacogenetics implementation consortium guidelines for thiopurine methyltransferase genotype and thiopurine dosing. Clin Pharmacol Ther 2011;89(3):387–391. 41. Vora A, Mitchell CD, Lennard L, et al. Toxicity and efficacy of 6-thioguanine versus 6-mercaptopurine in childhood lymphoblastic leukaemia: a randomised trial. Lancet 2006;368(9544):1339–1348. 42. Montillo M, Ricci F, Tedeschi A. Role of fludarabine in hematological malignancies. Expert Rev Anticancer Ther 2006;6(9):1141–1161. 43. Pettitt AR. Mechanism of action of purine analogues in chronic lymphocytic leukaemia. Br J Haematol 2003;121(5):692–702 44. Robak T, Robak P. Purine nucleoside analogs in the treatment of rarer chronic lymphoid leukemias. Curr Pharm Des 2012;18(23):3373–3388. 45. Johnston JB. Mechanism of action of pentostatin and cladribine in hairy cell leukemia. Leuk Lymphoma 2011;52(Suppl 2):43–45. 46. Robak P, Robak T. Older and new purine nucleoside analogs for patients with acute leukemias. Cancer Treat Rev 2013;39(8):851–861. 47. Robak T, Lech-Maranda E, Korycka A, et al. Purine nucleoside analogs as immunosuppressive and antineoplastic agents: mechanism of action and clinical activity. Curr Med Chem 2006;13(26):3165–3189. 48. Ghanem H, Jabbour E, Faderl S, et al. Clofarabine in leukemia. Expert Rev Hematol 2010;3(1):15–22. 49. Fozza C. The role of Clofarabine in the treatment of adults with acute myeloid leukemia. Crit Rev Oncol Hematol 2015;93(3):237–245.

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23

Topoisomerase-Interacting Agents Anish Thomas, Khanh Do, Shivaani Kummar, James H. Doroshow, and Yves

Pommier

BIOCHEMICAL AND BIOLOGIC FUNCTIONS OF TOPOISOMERASES Nucleic acids (DNA and RNA) being long polymers, topoisomerases fulfill the need for cellular DNA to be densely packaged in the cell nucleus while being transcribed, replicated, and accurately distributed between daughter cells following replication. Topoisomerases are ubiquitous and essential for all organisms as they prevent and resolve DNA and RNA entanglements and resolve DNA supercoiling during transcription and replication. They are also likely to play a role in chromatin structure and anchoring the DNA to the cellular scaffold. This chapter summarizes the basic elements necessary to understand the mechanism of action of topoisomerases and how their inhibitors interfere with the enzymes. Additional and more detailed information can be found in recent reviews1–3 and books.4,5 The chapter also summarizes the use of topoisomerase inhibitors as anticancer drugs.

Classification of Topoisomerases Human cells contain six topoisomerase genes (Table 23.1),1 which have been numbered historically. The commonly used abbreviations are TOP1 for topoisomerase I (TOP1MT being the mitochondrial topoisomerase whose gene is encoded in the cell nucleus), TOP2 for topoisomerases II, and TOP3 for topoisomerases III. TOP1 was the first eukaryotic topoisomerase discovered by Champoux and Dulbecco.6 Topoisomerases solve DNA topologic problems by cutting the DNA backbone and religating without assistance of any additional ligase. TOP1 and TOP3 act by cleaving/religating a single strand of the DNA duplex, whereas TOP2 enzymes cleave and religate both strands, making a four–base pair reversible staggered cut (Fig. 23.1 and Table 23.1). It is convenient to remember that odd-numbered topoisomerases (TOP1 and TOP3) cleave and religate one strand, whereas the even-numbered topoisomerases (TOP2s) cleave and religate both strands.

Biochemical Characteristics and Cleavage Complexes of the Different Topoisomerases The DNA cutting/religation mechanism is common to all topoisomerases and utilizes an enzyme catalytic tyrosine residue acting as a nucleophile and becoming covalently attached to the end of the broken DNA. These catalytic intermediates are referred to as cleavage complexes (see Fig. 23.1B,E). The reverse religation reaction is carried out by the attack of the ribose hydroxyl ends toward the tyrosyl-DNA bond. TOP1 (and TOP1MT) attaches to the 3′ end of the break, whereas the other topoisomerases (TOP2 and TOP3) have opposite polarity and covalently attach to the 5′ end of the breaks (see Table 23.1 [second column] and Fig. 23.1B,E). Topoisomerases have distinct biochemical requirements. TOP1 and TOP1MT are the simplest, nicking/closing and relaxing DNA as monomers in the absence of cofactor, and even at ice temperature. TOP2 enzymes, on the other hand, are the most complex topoisomerases working as dimers, requiring adenosine triphosphate (ATP) binding and hydrolysis, and a divalent metal (Mg2+) for catalysis. TOP3 enzymes also require Mg2+ for catalysis but function as monomers without ATP requirement. Notably, the DNA substrates differ for TOP3 enzymes. Whereas both TOP1 and TOP2 process double-stranded DNA, the TOP3 substrates need to be single-stranded nucleic acids (DNA for TOP3α and RNA for TOP3β).7–9

Differential Topoisomerization Mechanisms: Swiveling versus Strand Passage,

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DNA versus RNA Topoisomerases Topoisomerases use two main mechanisms to change nucleic acid topology. The first is by “untwisting” the DNA duplex. This mechanism is unique to TOP1, which by an enzyme-associated single-strand break allows the broken strand to rotate around the intact strand (see Fig. 23.1B) until DNA supercoiling is dissipated. At this point, the stacking energy of adjacent DNA bases realigns the broken ends, and the 5′-hydroxyl end attacks the 3′phosphotyrosyl end, thereby religating the DNA. A remarkable feature of this TOP1 untwisting mechanism is its extreme efficiency, with a rotation speed around 6000 rpm and relative independence from torque, thereby allowing full relaxation of DNA supercoiling.10 The second topologic mechanism is by “strand passage.” This mechanism allows the passage of a double- or a single-stranded DNA (or RNA) through the cleavage complexes. TOP2α and TOP2β both act by allowing the passage of an intact DNA duplex through the DNA double-strand break generated by the enzymes, after which TOP2 religates the broken duplex. Such reactions permit DNA decatenation, unknotting, and relaxation of supercoils.1 TOP3 enzymes also act by strand passage but only pass one nucleic acid strand through the singlestrand break generated by the enzymes. In the case of TOP3α, the substrate is a single-stranded DNA segment (such as a double-Holliday junction), whereas in the case of TOP3β, the substrate can be a single-stranded RNA segment, with TOP3β acting as a RNA topoisomerase.7

TOPOISOMERASE INHIBITORS AS INTERFACIAL POISONS Topoisomerase Inhibitors Act as Interfacial Inhibitors by Binding at the Topoisomerase–DNA Interface and Trapping Topoisomerase Cleavage Complexes Religation of the cleavage complexes is dependent on the structure of the ends of the broken DNA (i.e., the realignment of the broken ends). Binding of the drugs at the enzyme–DNA interface misaligns the ends of the DNA and precludes religation, resulting in the stabilization of the topoisomerase cleavage complexes (topoisomerase I cleavage complex [TOP1cc] and topoisomerase II cleavage complex [TOP2cc]). Crystal structures of drug-bound cleavage complexes have firmly established this mechanism for both TOP1- and TOP2targeted drugs.11 TABLE 23.1

Classification of Human Topoisomerases and Topoisomerase Inhibitors Type

Polaritya

Mechanism

Genes

Proteins

Main Functions

Drugsb

IB

3′-PY

Rotation Swiveling

TOP1

TOP1

DNA supercoiling relaxation

TOP1MT

TOP1MT

Replication and transcription

Camptothecins (irinotecan, topotecan) Indenoisoquinolines (LMP400, LMP776, LMP744)

Strand passage ATPase

TOP2A

TOP2α

Decatenation/replication

TOP2B

TOP2β

Transcription

Strand passage

TOP3A

TOP3α

DNA replication with BLM

TOP3B

TOP3β

RNA topoisomerase

IIA

IA

5′-PY

5′-PY

Anthracyclines (doxorubicin, daunorubicin, idarubicin) Mitoxantrone Epipodophyllotoxins (etoposide, teniposide) None

a 3′-PY, covalent linkage of the catalytic tyrosine of the topoisomerase to the 3′ end of the DNA break made by the topoisomerase;

5′-PY, covalent linkage of the catalytic tyrosine of the topoisomerase to the 5′ end of the DNA break made by the topoisomerase. b Drug classes are set in bold. TOP1, topoisomerase I; TOP1MT, mitochondrial topoisomerase I; TOP2α, topoisomerase IIα; TOP2α, topoisomerase IIβ; TOP3α, topoisomerase IIIα; BLM, Bloom syndrome helicase; TOP3α, topoisomerase IIIβ.

It is critical to understand that the cytotoxic mechanism of topoisomerase inhibitors requires the drugs to trap the topoisomerase cleavage complexes rather than block catalytic activity. This sets apart topoisomerase inhibitors from classical enzyme inhibitors such as antifolates. Indeed, knocking out TOP1 renders yeast cells totally

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immune to camptothecin,12,13 and reducing enzyme levels in cancer cells confers drug resistance. Conversely, in breast cancers, amplification of TOP2A, which is on the same locus as HER2, contributes to the efficacy of doxorubicin.14 In addition, cellular mutations of TOP1 and TOP2 that render cells insensitive to the trapping of topoisomerase cleavage complexes produce high resistance to TOP1 or TOP2 inhibitors.2,15 Based on this trapping of cleavage complexes mechanism, we refer to topoisomerase inhibitors as topoisomerase cleavage complex–targeted drugs.

TOP1cc-Targeted Drugs (Camptothecin and Indenoisoquinoline Derivatives) Kill Cancer Cells by Replication Collisions TOP1cc are cytotoxic by their conversion into DNA damage by replication and transcription fork collisions. This explains why cytotoxicity is directly related to drug exposure and why arresting DNA replication protects cells from camptothecin.16,17 The collisions arise because the drugs, by slowing down the nicking-closing activity of TOP1, uncouple the kinetics of TOP1 with the polymerases and helicases, which leads polymerases to collide into TOP1cc (Fig. 23.2A). Such collisions have two consequences. They generate double-strand breaks (replication and transcription runoff) and irreversible TOP1–DNA adducts (Fig. 23.2B). The replication double-strand breaks are repaired by homologous recombination, which explains the hypersensitivity of BRCA-deficient cancer cells to TOP1cc-targeted drugs.18 The TOP1-covalent complexes can be removed by two pathways, the excision pathway centered around tyrosyl-DNA-phosphodiesterase 1 (TDP1)19 and the endonuclease pathway involving 3′-flap endonucleases such as XPF-ERCC1.19,20 It is also possible that drug-trapped TOP1cc directly generate DNA double-strand breaks when they are within 10 base pairs on opposite strands of the DNA duplex, when they occur next to a preexisting single-strand break on the opposite strand, or when TOP1 generates a nick in misincorporated ribonucleotides in the genome (Fig. 23.2C).1,21 Finally, it is not excluded that topologic defects contribute to the cytotoxicity of TOP1cc-targeted drugs (accumulation of supercoils22 and formation of alternative structures such as R-loops) (Fig. 23.2D).23

Figure 23.1 Mechanisms of action of topoisomerases. A–C: Topoisomerases I (TOP1 for nuclear DNA and TOP1MT for mitochondrial DNA) relax supercoiled DNA (A) by reversibly cleaving one DNA strand, forming a covalent bond between the enzyme catalytic tyrosine and the 3′ end of the nicked DNA (the TOP1 cleavage complex [TOP1cc]) (B). This reaction allows the swiveling of the broken strand around the intact strand. Rapid religation allows the dissociation of TOP1. D–F: Topoisomerases II (TOP2α and TOP2β) act on two DNA duplexes (A). They act as homodimers, cleaving both strand, forming a covalent bond between their catalytic tyrosine and the 5′ end of the DNA break (TOP2 cleavage complex [TOP2cc]) (E). This reaction allows the passage of the intact

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duplex through the TOP2 homodimer (red dotted arrow) (E). TOP2 inhibitors trap the TOP2cc and prevent the normal religation (F).

Figure 23.2 Mechanisms of action of topoisomerase inhibitors beyond the trapping of topoisomerase cleavage complexes. A: Stalled or slow cleavage complexes lead to collisions with replication and transcription complexes. B: Collisions of replication complexes with topoisomerase I cleavage complex (TOP1cc) on the leading strand for DNA synthesis generate DNA double-strand breaks (DSBs) by “replication runoff.” C: topoisomerase II cleavage complex (TOP2cc), which are normally held together by TOP2 homodimers, can be converted to free DSBs upon TOP2cc proteolysis or dimer disjunction. TOP1cc can also form DNA DSBs when they occur opposite to another TOP1cc or preexisting nick. D: Topologic defects resulting from functional topoisomerase deficiencies play a minor role in the anticancer activity of topoisomerase cleavage complex– targeted drugs. tyrosyl-DNA-phosphodiesterase 1, TDP1.

Cytotoxic Mechanisms of TOP2cc-Targeted Drugs (Intercalators and Demethylepipodophyllotoxins) Contrary to camptothecins, TOP2 inhibitors kill cancer cells without requiring DNA replication fork collisions. Indeed, even after 30-minute exposure, doxorubicin and other TOP2cc-targeted drugs can kill over 99% of the cells, which is in vast excess of the fraction of S-phase cells in tissue culture (generally less than 50%). The collision mechanism in the case of TOP2cc-targeted drugs (see Fig. 23.2A) appears to involve transcription and proteolysis of both TOP2 and RNA polymerase II.24 Such situation would then lead to DNA double-strand breaks by disruption of the TOP2 dimer interface (see Fig. 23.2C). Alternatively, the TOP2 homodimer interface could be disjoined by mechanical tension (see Fig. 23.2C). Yet, it is important to bear in mind that 90% of TOP2cc trapped by etoposide are not concerted and therefore consist in single-strand breaks,25–27 which is different from doxorubicin, which traps both TOP2 monomers and produces a majority of DNA double-strand breaks.28 Finally, it is not excluded that topologic defects resulting from TOP2 sequestration by the drug-induced cleavage complexes and deficiency at required functional sites could contribute to the cytotoxicity of TOP2cc-targeted drugs (see Fig. 23.2D). Such topologic defect would include persistent DNA knots and catenanes, potentially leading to chromosome breaks during mitosis.

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TOPOISOMERASE I INHIBITORS: CAMPTOTHECINS AND BEYOND Camptothecin is an alkaloid identified in the 1960s by Wall and Wani29 in a screen of plant extracts for antineoplastic drugs. The two water-soluble derivatives of camptothecin containing the active lactone form are topotecan and irinotecan and are approved by the U.S. Food and Drug Administration (FDA) for the treatment of several cancers. In addition, several TOP1cc-targeting drugs are in clinical development, including camptothecin derivatives and formulations (including high-molecular-weight conjugates or liposomal formulations), as well as noncamptothecin compounds that exhibit greater potency or non–cross-resistance to irinotecan and topotecan in preclinical cancer models.26,30,31

Irinotecan Irinotecan, a prodrug containing a bulky dipiperidino side chain at C-10 (Fig. 23.3A), is cleaved by a carboxylesterase-converting enzyme in the liver and other tissues to generate the active metabolite, SN-38. SN-38 is glucuronidated by hepatic uridine diphosphate glucuronosyltransferase-1A1 (UDP-GT 1A1) to SN-38glucuronide (SN-38G). Irinotecan is FDA approved for the treatment of colorectal cancer in the metastatic setting as first-line treatment in combination with 5-fluorouracil (5-FU)/leucovorin (LV) and as a single agent in the second-line treatment of progressive colorectal cancer after 5-FU–based therapy (see Table 23.1).32,33 Newer therapeutic uses of irinotecan include combination with oxaliplatin and 5-FU as first-line treatment in pancreatic cancer.34 Irinotecan is additionally used in combination with cisplatin or carboplatin in extensive-stage small-cell lung cancer35–37 as well as refractory esophageal and esophagogastric junction cancers, gastric cancer, cervical cancer, anaplastic gliomas and glioblastomas, and non–small-cell lung cancer (Table 23.2). Irinotecan is usually administered intravenously at a dose of 125 mg/m2 for 4 weeks with a 2-week rest period in combination with bolus 5-FU/LV, 180 mg/m2 every 2 weeks in combination with infusional 5-FU/LV, or 350 mg/m2 every 3 weeks as a single agent.

Figure 23.3 Structure of topoisomerase inhibitors. A: Camptothecin derivatives are instable at physiologic pH with formation of a carboxylate derivative within minutes. Irinotecan is a prodrug

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and needs to be converted to SN-38 to trap topoisomerase I cleavage complex (TOP1cc). B: Noncamptothecin indenoisoquinoline derivatives in clinical trials. C: Anthracycline derivatives. D: Demethylepipodophyllotoxin derivatives. E: Other intercalating topoisomerase II (TOP2) inhibitors acting by trapping topoisomerase II cleavage complex (TOP2cc). F: Structure of dexrazoxane, which acts as a catalytic inhibitor of TOP2. Diarrhea and myelosuppression are the most common toxicities associated with irinotecan. Two mechanisms explain irinotecan-induced diarrhea. Acute cholinergic effects resulting in abdominal cramping and diarrhea occur within 24 hours of drug administration (“early diarrhea”), are the result of acetylcholinesterase inhibition by the prodrug, and can be treated with atropine. Direct mucosal cytotoxicity from free intestinal luminal SN-38 or SN38G deconjugation (by bacterial β-glucuronidase back to SN-38) underlies diarrhea that occurs after 24 hours of irinotecan administration (“late diarrhea”). SN-38 can induce apoptosis and hypoproliferation in both the small and large intestines and causes colonic damage with changes in goblet cells and mucin secretion.38 Symptoms are managed with loperamide or, if severe, with the addition of diphenoxylate/atropine and opium tincture. Hepatic metabolism and biliary excretion account for >70% of the elimination of the administered dose, with renal excretion accounting for the remainder of the dose. SN-38 is glucuronidated in the liver by UGT1A1, and deficiencies in this pathway increase the risk of diarrhea and myelosuppression. Dose reductions are recommended for patients who are homozygous for the UGT1A1*28 allele, for which an FDA-approved test for detection is available.36,39 In addition, dose reductions of irinotecan are recommended for patients with hepatic dysfunction, with bilirubin greater than 1.5 mg/mL.40

Topotecan Topotecan contains a basic side chain at position C-9 that enhances its water solubility (see Fig. 23.3A). Topotecan is approved for the treatment of ovarian cancer41 and small-cell lung cancer42 as a single agent and in combination with cisplatin for cervical cancer.43 In addition, it is active in acute myeloid leukemia and myelodysplastic syndrome (see Table 23.2). Topotecan is administered intravenously as a single agent at a dose of 1.5 mg/m2 as a 30-minute infusion daily for 5 days followed by a 2-week period of rest for the treatment of solid tumors or at a dose of 0.75 mg/m2 as a 30-minute infusion daily for 3 days in combination with cisplatin on day 1, every 3 weeks, for the treatment of cervical cancer. Oral topotecan (2.3 mg/m2/d orally once daily for 5 consecutive days repeated every 21 days) has shown activity and tolerability similar to the intravenous formulation in small-cell lung cancer patients. TABLE 23.2

U.S. Food and Drug Administration–Approved Camptothecin Analogs Compound

Tumor Type

Clinical Indication

Major Toxicities

Irinotecan (Camptosar)

FDA approved for: Metastatic colorectal cancer Category 2A recommendations: Pancreatic cancer Extensive-stage small-cell lung cancer

First-line therapy in combination with 5-FU/LV Second-line therapy as a single agent First-line therapy in combination with oxaliplatin, 5-FU/LV First-line therapy in combination with cisplatin or carboplatin

Diarrhea (dose reductions are recommended for patients who are homozygous for the UGT1A1*28 allele) Myelosuppression

Category 2B recommendations: esophageal and gastroesophageal junction cancers, gastric cancer, cervical cancer, anaplastic gliomas and glioblastomas, non–small-cell lung cancer, ovarian cancer Topotecan (Hycamtin)

FDA approved for:



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Cervical cancer Ovarian cancer Small-cell lung cancer

Stage IVB, recurrent, or persistent carcinoma of the cervix not amenable to curative treatment with surgery and/or radiation therapy After failure of initial therapy After failure of initial therapy

Myelosuppression

Class 2B recommendations: AML, MDS Category 2A: Recommendations are based on lower level evidence; there is uniform National Comprehensive Cancer Network consensus that the intervention is appropriate. Category 2B: Recommendations are based on lower level evidence; there is National Comprehensive Cancer Network consensus that the intervention is appropriate. FDA, U.S. Food and Drug Administration; 5-FU, 5-fluorouracil; LV, leucovorin; AML, acute myeloid leukemia; MDS, myelodysplastic syndrome.

Myelosuppression is the most common dose-limiting toxicity. Extensive prior radiation or previous bone marrow–suppressive chemotherapy increases the risk of topotecan-induced myelosuppression. Other toxicities include nausea, vomiting, diarrhea, fatigue, alopecia, and transient hepatic transaminitis. Topotecan and its metabolites are primarily cleared by the kidneys, requiring dose reduction in patients with renal dysfunction. A 50% dose reduction is recommended for patients with moderate renal impairment (creatinine clearance 20 to 39 mL/min). Topotecan also penetrates the blood–brain barrier, achieving concentrations in cerebrospinal fluid that are approximately 30% that of plasma levels.44

Camptothecin Conjugates and Analogs New formulations of camptothecin conjugates and analogs are currently in clinical development to improve the therapeutic index (Table 23.3). The development of camptothecin conjugates is based on the notion that the addition of a bulky conjugate would allow for a more consistent delivery and extend the half-life of the molecule. CRLX101, formerly IT-101, a covalent cyclodextrin-polyethylene glycol copolymer camptothecin conjugate, has plasma concentrations and area under the curve (AUC) that are approximately 100-fold higher than camptothecin, with a half-life in the range of 17 to 20 hours compared to 1.3 hours for camptothecin.45 It has demonstrated antitumor activity in preclinical studies in irinotecan-resistant tumors in human non–small-cell lung cancer, Ewing sarcoma, and lymphoma xenograft models.46 Preliminary data from phase I studies indicated that CRLX101 is well tolerated at a dose of 15 mg/m2 administered in a biweekly schedule.47 It is currently in phase II studies as a single agent and in combination with chemotherapeutic agents in lung cancer, renal cell cancer, and gynecologic malignancies. Etirinotecan pegol (NKTR-102), an irinotecan polymer conjugate, has a longer plasma circulation time with lower maximum concentration of SN-38 compared with irinotecan. It was evaluated in a phase II study in platinum-resistant refractory epithelial ovarian cancer at a dose of 145 mg/m2 administered on an every 21-day schedule; median progression-free survival of 5.3 months and median overall survival of 11.7 months were observed.48 Two schedules of administration (145 mg/m2 administered every 14 days versus every 21 days) have been tested in a phase II study of etirinotecan pegol in patients with previously treated metastatic breast cancer.49 Of the 70 patients evaluated in this study, 20 patients achieved an objective response (29%; 95% confidence interval [CI], 18.4% to 40.6%). In both of these studies, the most common adverse events on the 21-day administration schedule were dehydration and diarrhea. However, in a randomized phase III study (BEACON trial), there was no significant difference in overall survival between patients who received etirinotecan pegol versus those who received single-drug treatment of physician’s choice (median overall survival, 12.4 months versus 10.3 months; P = .084).50 In this trial, among patients with brain metastases (n = 67), etirinotecan pegol was associated with a significant reduction in the risk of death (hazard ratio [HR], 0.51; P < .01) compared with single-drug treatment of physician’s choice.51 A phase III trial comparing etirinotecan pegol with treatment of physician’s choice is under way. TABLE 23.3

Topoisomerase I Inhibitors in Development Camptothecin Analogs Camptothecin Conjugates

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Noncamptothecin Agents

CRLX101 NKTR-102

Belotecan

Indenoisoquinoline Indotecan (LMP 400) Indimitecan (LMP 776)



Gimatecan

Dibenzo naphthyridine Genz-644282



Homocamptothecin Elomotecan Diflomotecan



NKTR-102, etirinotecan pegol.

Nanoliposomal irinotecan (Onivyde; MM-398) comprises irinotecan freebase encapsulated in liposome nanoparticles. The liposome is designed to keep irinotecan in the circulation and shelter it from conversion to its active metabolite SN-38 longer than free (unencapsulated) irinotecan.52 This could increase and prolong intratumoral levels of both irinotecan and SN-38 compared with free irinotecan. In the phase III NAPOLI-1 study, 417 patients with progressive pancreatic cancer after gemcitabine-based treatment were randomized to receive nanoliposomal irinotecan plus 5-FU and folinic acid, nanoliposomal irinotecan monotherapy, or 5-FU and folinic acid.52 The median overall survival in patients who received nanoliposomal irinotecan plus 5-FU and folinic acid was 6.1 months versus 4.2 months with 5-FU and folinic acid. Median overall survival did not differ between patients who received nanoliposomal irinotecan monotherapy and those allocated to 5-FU and folinic acid. Nanoliposomal irinotecan in combination with 5-FU and LV is approved for the treatment of patients with metastatic adenocarcinoma of the pancreas after disease progression following gemcitabine-based therapy. The recommended dose of nanoliposomal irinotecan is 70 mg/m2 intravenous infusion over 90 minutes every 2 weeks. As an alternative to macromolecular conjugates, attempts have also been made to alter the camptothecin pentacyclic ring structure with modifications of the A and B ring (see Fig. 23.3A) to improve solubility and enhance antitumor activity. Structure–activity relationship studies have shown that substitutions at the 7, 9, and 10 positions serve to enhance antitumor activity of camptothecin.53 Belotecan has a water-solubilizing group at the 7 position of the B ring of camptothecin (see Fig. 23.3A). Several phase II studies have evaluated belotecan in combination with carboplatin in recurrent ovarian cancer and in combination with cisplatin in extensive-stage small-cell lung cancer,54 demonstrating activity in these cancers; however, these combinations were associated with prominent hematologic toxicities. Phase II studies evaluating belotecan as a single agent in patients with recurrent or progressive carcinoma of the uterine cervix failed to show activity.55 Gimatecan is a lipophilic oral camptothecin analog (see Fig. 23.3A). Pharmacokinetic studies demonstrate that gimatecan is primarily present in plasma as the lactone form (>85%) and has a long half-life of 77.1 ± 29.6 hours, with increase in maximum concentration (Cmax) and AUC of three- to sixfold after multiple dosing.56 Phase II studies show that gimatecan has demonstrated activity in previously treated ovarian cancer, with myelosuppression as the main toxicity.57

Noncamptothecin Topoisomerase I Inhibitors Noncamptothecin TOP1 inhibitors in clinical development are the indenoisoquinolines (see Fig. 23.3B). Three indenoisoquinoline derivatives are currently in clinical development, indotecan (LMP400), imidotecan (LMP776), and LMP744.31,58,59 Early in vitro studies show enhanced potency compared with camptothecins and persistence of TOP1 cleavage complexes.60 A phase I trial established the maximum tolerated dose of indotecan in two different schedules—weekly and daily administration.59 Pharmacokinetics profiles demonstrated a prolonged terminal half-life and tissue accumulation compared to topotecan. Dose-limiting toxicities were nausea and myelosuppression.

TOPOISOMERASE II INHIBITORS: INTERCALATORS AND NONINTERCALATORS TOP2 inhibitors can be classified as DNA intercalators, which encompass different chemical classes (see Fig. 23.3C,E), and nonintercalators represented by the epipodophyllotoxin derivatives (see Fig. 23.3D). Although both act by trapping TOP2 cleavage complexes (TOP2cc) (see Fig. 23.1E), DNA intercalators exhibit a second effect as drug concentrations increase above low micromolar values: They block the formation of TOP2cc by intercalating into DNA and destabilizing the binding of TOP2 to DNA. This explains why anthracyclines (see Fig. 23.3C) trap TOP2α and TOP2β over a relatively narrow concentration range and why intercalators have additional

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effects besides trapping TOP2cc, namely inhibition of a broad range of DNA-processing enzymes including helicases, polymerase, and nucleosome destabilization.61

Doxorubicin Doxorubicin and daunorubicin were the first anthracyclines discovered in the 1960s and remain among the most widely used anticancer agents over a broad spectrum of malignancies. Although doxorubicin only differs by one hydroxyl substitution on position 14 (see Fig. 23.3C), doxorubicin has a much broader anticancer activity than daunorubicin. Anthracyclines are natural products derived from Streptomyces peucetius variation caesius. They were found to target TOP2 well after their clinical approval.62,63 Subsequent searches for less toxic drugs and formulations led to the approval of liposomal doxorubicin, idarubicin, and epirubicin. Anthracyclines are flat, planar, and relatively hydrophobic (see Fig. 23.3C). Their quinone structure enhances the catalysis of oxidation-reduction reactions, thereby promoting the generation of oxygen free radicals, which may be involved in antitumor effects as well as the cardiotoxicity associated with these drugs.64,65 In fact, recent studies have linked the cardiotoxicity of doxorubicin to the poisoning of TOP2β.66,67 Anthracyclines are also substrates for P-glycoprotein (encoded by ABCB1) and Mrp-1 (encoded by ABCC1), and drug efflux is a major drug resistance determinant.68,69 Doxorubicin is available in a standard salt form and as a liposomal formulation. FDA-labeled indications for standard doxorubicin include acute lymphoid leukemia, acute myeloid leukemia, chronic lymphoid leukemia, Hodgkin lymphoma, non-Hodgkin lymphoma, mantle cell lymphoma, multiple myeloma, mycosis fungoides, Kaposi sarcoma, breast cancer (adjuvant therapy and advanced), advanced prostate cancer, advanced gastric cancer, Ewing sarcoma, thyroid cancer, advanced nephroblastoma, advanced neuroblastoma, advanced non–smallcell lung cancer, advanced ovarian cancer, advanced transitional cell bladder cancer, cervical cancer, and Langerhans cell tumors. Doxorubicin has activity in other malignancies as well, including soft tissue sarcoma, osteosarcoma, carcinoid, and liver cancer (Table 23.4). Doxorubicin is typically administered at a recommended dose of 30 to 75 mg/m2 every 3 weeks intravenously. Major acute toxicities of doxorubicin include myelosuppression, mucositis, alopecia, nausea, and vomiting. Myelosuppression is the acute dose-limiting toxicity. Other toxicities, including diarrhea, nausea, vomiting, mucositis, and alopecia, are dose and schedule related. Prophylactic antiemetics are routinely given with bolus doses of doxorubicin, and longer infusions are associated with less nausea and less cardiotoxicity. Patients should also be warned to expect their urine to redden after drug administration. Doxorubicin is a potent vesicant, and extravasation can lead to severe necrosis of skin and local tissues, requiring surgical debridement and skin grafts. Infusions via a central venous catheter are recommended. Other toxicities of doxorubicin include “radiation recall” and the risk of developing secondary leukemia. Radiation recall is an inflammatory reaction at sites of previous radiation and can lead to pericarditis, pleural effusion, and skin rash. Secondary leukemias are thought to be a result of balanced translocations that result from TOP2 poisoning by the anthracyclines, albeit to lesser degree than other TOP2 poisons, such as the epipodophyllotoxins (see the following text).70,71 TABLE 23.4

U.S. Food and Drug Administration–Approved Topoisomerase II Inhibitors in Clinical Use Compound

Tumor Type

Clinical Indication

Major Toxicities

Breast carcinoma ALL AML Wilms tumor Neuroblastoma Sarcomas Ovarian cancer Transitional cell bladder cancer Thyroid cancer

Adjuvant setting with axillary LN involvement following resection of primary breast cancer In combination with other cytotoxic agents

Dose-dependent cardiotoxicity Myelosuppression

I. Anthracyclines Doxorubicin (Adriamycin)

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Gastric cancer Hodgkin lymphoma Non-Hodgkin lymphoma Pegylated liposomal doxorubicin (Doxil)

Ovarian cancer AIDS-related Kaposi sarcoma Multiple myeloma

After failure of platinum-based chemotherapy After failure of prior systemic chemotherapy In combination with bortezomib

Myelosuppression Stomatitis Hand-foot syndrome Dosage reduction recommended with hepatic dysfunction

Daunorubicin (Cerubidine)

ALL AML

Induction therapy

Dose-dependent cardiotoxicity Myelosuppression

Epirubicin (Ellence)

Breast cancer

Adjuvant therapy in patients with evidence of axillary node tumor involvement following primary resection

Dose-dependent cardiotoxicity Myelosuppression

Idarubicin (Idamycin)

AML

Induction therapy

Dose-dependent cardiotoxicity Myelosuppression

Mitoxantrone (Novantrone)

Prostate cancer AML

Hormone-refractory prostate cancer

Myelosuppression

Dactinomycin (Cosmegen)

Wilms tumor Rhabdomyosarcoma Ewing sarcoma Nonseminomatous testicular cancer Gestational trophoblastic neoplasia



Myelosuppression

Small-cell lung cancer Testicular cancer

First line in combination First line in combination

Myelosuppression

II. Anthracenediones

III. Epipodophyllotoxins Etoposide (Vepesid) Teniposide (Vumon)

Pediatric lymphoblastic Refractory setting leukemia LN, lymph node; ALL, acute lymphoblastic leukemia; AML, acute myeloid leukemia.

Myelosuppression

Anthracyclines are cleared mainly by metabolism to less active forms and by biliary excretion. Less than 10% of the administered dose is cleared by the kidneys. Dose reductions should be made in patients with elevated plasma bilirubin. Doxorubicin should be dose reduced by 50% for plasma bilirubin concentrations ranging from 1.2 to 3.0 mg/dL, dose reduced by 75% for values of 3.1 to 5.0 mg/dL, and withheld for values greater than 5 mg/dL.

Liposomal Doxorubicin Doxorubicin is also available in a pegylated liposomal form, which allows for enhancement of drug delivery. Use of liposomal doxorubicin has been associated with less cardiotoxicity even at doses exceeding 500 mg/m2.72 In addition, liposomal doxorubicin produces less nausea and vomiting and relatively mild myelosuppression compared to doxorubicin. Unique to the liposomal formulation is the risk of hand-foot syndrome and an acute infusion reaction manifested by flushing, dyspnea, edema, fever, chills, rash, bronchospasm, and hypertension. These infusion reactions are related to the rate of infusion; therefore, the recommended administration schedule is set at an initial rate of 1 mg per minute for the first 10 to 15 minutes. The rate may be slowly increased to complete infusion over 60 minutes if no reaction occurs. Typical dosing schedules include 50 mg/m2 intravenous infusion every 4 weeks for four courses in ovarian cancer, 20 mg/m2 intravenous infusion every 3 weeks in AIDSrelated Kaposi sarcoma, and 30 mg/m2 intravenous infusion in combination with bortezomib to be given on days 1, 4, 8, and 11 every 3 weeks in multiple myeloma.

Daunorubicin Despite its chemical similarity (see Fig. 23.3C), daunorubicin is considerably less active in solid tumors compared to doxorubicin. It is FDA approved for the treatment of acute lymphoid leukemia and acute myeloid leukemia. Daunorubicin is typically administered via intravenous push over 3 to 5 minutes at a dose of 30 to 45 mg/m2/d on

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3 consecutive days in combination chemotherapy. For induction therapy for pediatric acute lymphoblastic leukemia, daunorubicin is dosed at 25 mg/m2 intravenously in combination with vincristine and prednisone. In children less than 2 years of age or who have a body surface area less than 0.5 m2, current recommendations are based on body mass index of 1 mg/kg rather than body surface area. A higher dose of daunorubicin at 60 to 90 mg/m2/d intravenously for 3 consecutive days is currently recommended as part of the induction combination regimen for the treatment of acute myeloblastic leukemia. Daunorubicin has similar toxicities to doxorubicin, including myelosuppression, cardiac toxicity, nausea, vomiting, and alopecia, and is also a vesicant. Daunorubicin is metabolized by the liver and undergoes substantial elimination by the kidneys, requiring dose reductions for both renal and hepatic dysfunction. A 50% dose reduction is recommended for either serum creatinine or bilirubin greater than 3 mg/dL, and a 25% reduction in dose is recommended for bilirubin concentrations ranging from 1.2 to 3.0 mg/dL.

Epirubicin Epirubicin is an epimer of doxorubicin (see Fig. 23.3C) with increased lipophilicity. It is FDA approved for adjuvant therapy of breast cancer but is also used in combination for the treatment of a variety of malignancies. Epirubicin is administered intravenously at doses ranging from 60 to 120 mg/m2 every 3 to 4 weeks. Epirubicin has a similar toxicity profile to doxorubicin but is overall better tolerated. In addition to being converted to an enol by an aldoreductase, epirubicin has a unique steric orientation of the C-4 hydroxyl group that allows it to serve as a substrate for conjugation reactions mediated by liver glucuronyltransferases and sulfatases. As such, dose adjustments are recommended in the setting of hepatic dysfunction. For patients with serum bilirubin of 1.2 to 3 mg/dL or aspartate aminotransferase of 2 to 4 times the upper limit of normal, a 50% dose reduction is recommended. For patients with bilirubin greater than 3 mg/dL or aspartate aminotransferase greater than 4 times the upper limit of normal, a dose reduction of 75% is recommended. Due to limited data, no specific dose recommendations are currently available for patients with renal impairment, although current recommendations are for consideration of dose adjustments in patients with serum creatinine greater than 5 mg/dL.

Idarubicin Idarubicin is a synthetic derivative of daunorubicin, but lacks the 4-methoxy group (see Fig. 23.3C). It is FDA approved as part of combination chemotherapy regimen for acute myeloid leukemia and is also active in acute lymphoid leukemia. It is given intravenously at a dose of 12 mg/m2 for 3 consecutive days, typically in combination with cytarabine. Idarubicin has similar toxicities as daunorubicin. Its primary active metabolite is idarubicinol, and elimination is mainly through the biliary system and, to a lesser extent, through renal excretion. Fifty percent dose reductions are recommended for serum bilirubin of 2.6 to 5 mg/dL, and idarubicin should not be given if the bilirubin is greater than 5 mg/dL. In addition, dose reductions in renal impairment are advised, but specific guidelines are not available.

Cardiac Toxicity of Anthracyclines Anthracyclines are responsible for cardiac toxicities, and special considerations are necessary to minimize this severe side effect. Acute doxorubicin cardiotoxicity is reversible, and clinical signs include tachycardia, hypotension, electrocardiogram changes, and arrhythmias. It develops during or within days of anthracycline infusion, and its incidence can be significantly reduced by slowing doxorubicin infusion rates. Chronic and delayed cardiotoxicity is more common and more severe because it is irreversible. Chronic cardiotoxicity with congestive heart failure peaks at 1 to 3 months but can occur even years after therapy. The American Society of Clinical Oncology has developed recommendations for prevention and monitoring of cardiac dysfunction in survivors of adult-onset cancers.73 Myocardial damage has been shown to occur by several mechanisms. The classical mechanism is by direct generation of reactive oxygen species (ROS) during electron transfer from the semiquinone to quinone moieties of the anthracycline,64,65 which leads to myocardial damage. ROS can also be generated by mitochondrial damage resulting from drug-mediated inactivation of the oxidative phosphorylation chain, as doxorubicin accumulates not only in chromatin but also in mitochondria.65,74 Recent studies have also related doxorubicin cardiotoxicity to the poisoning of TOP2β cleavage complexes in myocardiocytes67,75 and to defective TOP1MT.67 Because TOP1MT contains multiple single nucleotide polymorphisms (SNPs), which can interfere with TOP1MT activity,76 it could be relevant to determine whether

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delayed cardiac toxicity of doxorubicin or daunorubicin is linked with specific SNPs to identify patients predisposed to cardiotoxicity. Endomyocardial biopsy is characterized by a predominant finding of multifocal areas of patchy and interstitial fibrosis (stellate scars) and occasional vacuolated myocardial cells (Adria cells). Myocyte hypertrophy and degeneration, loss of cross-striations, and absence of myocarditis are also characteristic of this diagnosis.77 The incidence of cardiomyopathy is related to both cumulative dose and schedule of administration, and predisposition to cardiac damage includes a previous history of heart disease, hypertension, radiation to the mediastinum, age greater than 65 years or younger than 4 years, prior use of anthracyclines or other cardiac toxins, and coadministration of other chemotherapy agents (e.g., paclitaxel, cyclophosphamide, or trastuzumab).78,79 Sequential administration of paclitaxel followed by doxorubicin in breast cancer patients is associated with cardiomyopathy at total doxorubicin doses above 340 to 380 mg/m2, whereas the reverse sequence of drug administration did not yield the same systemic toxicities at these doses.80 When doxorubicin is given by a lowdose weekly regimen (10 to 20 mg/m2/wk) or by slow continuous infusion over 96 hours, cumulative doses of more than 500 mg/m2 can be given. Doses of epirubicin below 1,000 mg/m2 and daunorubicin below 550 mg/m2 are considered safe. In addition, liposomal doxorubicin is associated with less cardiac toxicity. Cardiac function can be monitored during treatment with anthracyclines by electrocardiography, echocardiography, or radionuclide scans. Numerous studies have established the danger of embarking on anthracycline therapy in patients with underlying cardiac disease (e.g., a baseline left ventricular ejection fraction of less than 50%) and of continuing therapy after a documented decrease in ejection fraction by more than 10% (if this decrease falls below the lower limit of normal). Because anthracycline-induced cardiotoxicity has been related to the generation of free radicals, efforts have been aimed at attenuating this effect through targeting of redox response and reduction in oxidative stress. Dexrazoxane is a metal chelator that decreases the myocardial toxicity of doxorubicin in breast cancer patients. In two multicenter, double-blind studies, advanced breast cancer patients were randomized to chemotherapy with dexrazoxane or placebo, dexrazoxane was shown to have a cardioprotective effect based on serial noninvasive cardiac testing during the course of the trial and has been approved for this use by the FDA.81 Dexrazoxane chelates iron and copper, thereby interfering with the redox reactions that generate free radicals and damage myocardial lipids. Notably, dexrazoxane is also a TOP2 catalytic inhibitor (see Fig. 23.3F), which potentially might minimize the therapeutic activity of anthracyclines by interfering with the trapping of TOP2 cleavage complexes by anthracyclines.2,82 Other agents currently in use include β-blockers and statins. A meta-analysis of 12 randomized controlled trials and two observational studies involving the use of agents to prevent the cardiotoxicity associated with anthracyclines demonstrated relatively similar efficacy regardless of which prophylactic treatment was used.83

Mitoxantrone Mitoxantrone (see Fig. 23.3E) is currently the only clinically approved anthracenedione. Compared to anthracyclines, mitoxantrone is less cardiotoxic due to decreased ability to undergo oxidation-reduction reactions and form free radicals. Mitoxantrone is FDA approved for the treatment of advanced hormone-refractory prostate cancer84 and acute myeloid leukemia.85 It is typically administered intravenously at a dose of 12 to 14 mg/m2 every 3 weeks in the treatment of prostate cancer and at a dose of 12 mg/m2 in combination with cytarabine for 3 days in the treatment of acute myeloid leukemia. Toxicities are generally less severe compared to doxorubicin, and include myelosuppression, nausea, vomiting, alopecia, and mucositis. Cardiac toxicity can be seen at cumulative doses of greater than 160 mg/m2.86 Mitoxantrone is rapidly cleared from the plasma and is highly concentrated in tissues. Most of the drug is eliminated in the feces with a small amount undergoing renal excretion. Dose adjustments for hepatic dysfunction are recommended, but formal guidelines are currently not available.

Dactinomycin Dactinomycin was the first antibiotic shown to have antitumor activity87 and consists of a planar phenoxazone ring attached to two peptide side chains. This unique structure allows for tight intercalation into DNA between adjacent guanine-cytosine bases, leading to poisoning of TOP2 and TOP1 and transcription inhibition.88 Dactinomycin was one of the first drugs shown to be transported by P-glycoprotein and represents the major mechanism of resistance.89

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Dactinomycin is FDA approved for Ewing sarcoma,90 gestational trophoblastic neoplasm,91 metastatic nonseminomatous testicular cancer,92 nephroblastoma,93 and rhabdomyosarcoma.94 Typically, it is administered intravenously at doses of 15 mcg/kg for 5 days in combination with other chemotherapeutic agents for the treatment of nephroblastoma, rhabdomyosarcoma, and Ewing sarcoma; 12 mcg/kg intravenously as a single agent in the treatment of gestational trophoblastic neoplasias; and 1,000 mcg/m2 intravenously on day 1 as part of a combination regimen with cyclophosphamide, bleomycin, vinblastine, and cisplatin in the treatment of metastatic nonseminomatous testicular cancer. Toxicities include myelosuppression, veno-occlusive disease of the liver, nausea, vomiting, alopecia, erythema, and acne. In addition, similar to doxorubicin, dactinomycin can cause radiation recall and severe tissue necrosis in cases of extravasation. Dactinomycin is largely excreted unchanged in the feces and urine. Guidelines for dosing in patients with impaired renal or liver function are currently not available.

Epipodophyllotoxins Epipodophyllotoxins are glycoside derivatives of podophyllotoxin, an antimicrotubule agent extracted from the mandrake plant. Two derivatives, demethylated on the pendant ring (R1 in Fig. 23.3D), etoposide and teniposide, were shown to primarily function as TOP2 poisons rather than through antimicrotubule mechanisms.27,95 Epipodophyllotoxins poison TOP2 through a mechanism distinct from that of anthracyclines and other DNA intercalators,96 without intercalating into normal DNA in the absence of TOP2. Therefore, they are specific for TOP2 compared to the anthracyclines, anthracenediones, and dactinomycin. Yet, etoposide and teniposide trap TOP2 cleavage complexes by base stacking in a ternary complex at the interface of the DNA and the TOP2 homodimer.11 Mechanisms of resistance include drug efflux, as epipodophyllotoxins are substrates for Pglycoprotein,97 altered localization of TOP2α, decreased cellular expression of TOP2α,98 and impaired phosphorylation of TOP2.99

Etoposide Etoposide (see Fig. 23.3D) is available in intravenous and oral forms. It is FDA approved for treatment of smallcell lung cancer99 and refractory testicular cancer.100 It also has activity in hematologic malignancies and various solid tumors. The intravenous form is generally administered at doses of 35 to 50 mg/m2 for 4 to 5 days every 3 to 4 weeks in combination therapy for small-cell lung cancer, and at 50 to 100 mg/m2 for 5 days every 3 to 4 weeks in combination therapy for refractory testicular cancer. The dose of oral etoposide is usually twice the intravenous dose. Oral bioavailability is highly variable due to dependence upon intestinal P-glycoprotein.101 The dose-limiting toxicity for etoposide is myelosuppression, with white blood cell count nadirs typically occurring on days 10 to 14. Thrombocytopenia is less common than leukopenia. In addition, mild to moderate nausea, vomiting, diarrhea, mucositis, and alopecia are associated with etoposide. Among topoisomerase inhibitors, epipodophyllotoxins have the greatest association with secondary malignancies, with etoposide having the highest risk, with an estimated 4% 6-year cumulative risk.71,102 The majority of etoposide is cleared unchanged by the kidneys and a 25% dose reduction is recommended in patients with a creatinine clearance of 15 to 50 mL per minute. A 50% dose reduction is recommended in patients with a creatinine clearance less than 15 mL per minute. As unbound fraction of etoposide is dependent on albumin and bilirubin concentrations. Dose adjustments for hepatic dysfunction are advised, but consensus guidelines are currently not available.

Teniposide Teniposide contains a thiophene group in place of the methyl group on the glucose moiety of etoposide (see Fig. 23.3D). Teniposide is FDA approved for refractory pediatric acute lymphoid leukemia.103,104 In pediatric acute lymphoblastic leukemia studies, doses ranged from 165 mg/m2 intravenously in combination with cytarabine to 250 mg/m2 intravenously weekly in combination with vincristine and prednisone. Similar to etoposide, the doselimiting toxicity of teniposide is myelosuppression. Additional toxicities include mild to moderate nausea, vomiting, diarrhea, alopecia, and secondary leukemia. Teniposide is associated with greater frequency of hypersensitivity reactions compared to etoposide. Teniposide is 99% bound to albumin and, compared to etoposide, undergoes hepatic metabolism more extensively and renal clearance less extensively. No specific guidelines are currently available on dose adjustments for renal or hepatic dysfunction.

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Therapy-Related Secondary Acute Leukemia One of the major complications of TOP2 inhibitor therapies, especially for etoposide and mitoxantrone, is acute secondary leukemia, which occurs in approximately 5% of patients. Therapy-related acute myelocytic leukemias are characterized by their relatively rapid onset (they can occur only a few months after therapy) and the presence of recurrent balanced translocations involving the mixed lineage leukemia (MLL) locus on 11q23 and over 50 partner genes.105 The molecular mechanism is likely from the disjoining of two drug-trapped TOP2 cleavage complexes on different chromosomes (see Fig. 23.2C) in relationship with transcription collisions and illegitimate religation.71 TOP2β rather than TOP2α has been implicated in the generation of these disjoined cleavage complexes.71,106 TABLE 23.5

Antibody–Drug Conjugates with a Topoisomerase Inhibitor Payload in Clinical Development



Target

Payload

Tumors for Which Drug is in Development

Labetuzumab govitecan (IMMU-130)

CEACAM5

SN-38

Colorectal cancer

I/II

IMMU-140

HLA-DR

SN-38

HLA-DR–expressing tumors

Preclinical

DS-8201a

HER2

DX-8951 derivative

HER2-expressing cancers

II

Sacituzumab govitecan (IMMU-132)

TROP2

SN-38

Phase of Development

Triple-negative breast III cancer, small-cell lung cancer CEACAM5, arcinoembryonic antigen–related cell adhesion molecule 5; HLA-DR, human leukocyte antigen-DR; HER2, human epidermal growth factor receptor 2.

FUTURE DIRECTIONS Current challenges in the development of topoisomerase inhibitors lie in toxicities resulting from lack of tumorspecific activity, inherent chemical instability of current established agents, drug resistance, and limitations in terms of reliable predictors of activity. One approach to overcoming the lack of tissue selectivity (tumor versus normal) and the resulting toxicities is to use antibody–drug conjugates (ADCs), which are monoclonal antibodies specific to tumor cell surface proteins that could achieve tumor specificity and potency not achievable with traditional chemotherapy. ADCs with topoisomerase inhibitor payloads in clinical development include sacituzumab govitecan (IMMU-132), labetuzumab govitecan (IMMU-130), and DS-8201a (Table 23.5). Sacituzumab govitecan is an ADC that targets trophoblast antigen 2 (TROP2), a transmembrane glycoprotein that is usually expressed in trophoblasts and in many epithelial cancers for tumor delivery of SN-38.107 In a phase I trial, the major adverse events were nausea, diarrhea, neutropenia, and fatigue. Sacituzumab govitecan has shown activity in triple-negative breast cancer, platinum-resistant urothelial carcinoma, and non–small-cell and small-cell lung cancers and is being studied in a phase III trial for relapsed triple-negative breast cancer. Labetuzumab govitecan is an ADC targeting carcinoembryonic antigen–related cell adhesion molecule 5 (CEACAM5) for tumor delivery of SN-38.108 In a phase I/II trial of 86 patients, the major toxicities were neutropenia, leukopenia, anemia, and diarrhea. DS-8201a is an HER2-targeting ADC composed of a humanized anti-HER2 antibody, enzymatically cleavable peptide-linker, and a camptothecin TOP1 inhibitor DX-8951 derivative.109 In a phase I study, no dose-limiting toxicities were observed, and the maximum-tolerated dose was not reached. Phase II testing of DS-8201a is ongoing in HER2-positive, unresectable and/or metastatic breast cancer patients who are resistant or refractory to trastuzumab emtansine (T-DM1). In addition to recent developments designed to enhance the stability with semisynthetic analogs and the development of novel delivery systems in an effort to achieve higher intratumoral concentrations, attention is also being focused on targeting other topoisomerase isoenzymes.110 Driving this trend has been the elucidation of the role of TOP2β inhibition in the development of treatment-related cardiotoxicity and secondary acute myeloid

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leukemia. Future rational drug combinations include targeting DNA repair pathways in combination with TOP1 inhibition, although further characterization of the specific DNA repair and stress response pathways invoked in response to DNA damage as a result of TOP1 inhibition is needed. However, one such attempt of combining topotecan with veliparib, a small-molecule inhibitor of poly (ADP-ribose) polymerase, was poorly tolerated due to significant myelosuppression limiting the doses of topotecan that could be safely administered.111 Molecular characterization of tumor to better define patient selection and the development of pharmacodynamic biomarkers to monitor the response to treatment and to optimize the combination dose and schedules is needed for the further clinical development of topoisomerase inhibitors, even when they are tumortargeted. Validated assays are available to evaluate topoisomerase levels and levels of gamma-H2AX, as a marker of DNA damage response to topoisomerase inhibition.112–114 Recent studies have identified Schlafen 11 (SLFN11), a nuclear protein belonging to the Schlafen family of mammalian proteins, as a causal and dominant genomic determinant of response to TOP1 and TOP2 inhibitors.115,116 High expression of SLFN11 in pretreatment tumors is associated with higher likelihood of response to these agents (and a broad spectrum of DNA replication inhibitors) in preclinical and retrospective studies. Further validation is needed in larger and prospective studies for this marker to proceed in clinic.

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65. Doroshow JH, Davies KJ. Redox cycling of anthracyclines by cardiac mitochondria. II. Formation of superoxide anion, hydrogen peroxide, and hydroxyl radical. J Biol Chem 1986;261(7):3068–3074. 66. Lyu YL, Kerrigan JE, Lin CP, et al. Topoisomerase IIbeta mediated DNA double-strand breaks: implications in doxorubicin cardiotoxicity and prevention by dexrazoxane. Cancer Res 2007;67(18):8839–8846. 67. Khiati S, Dalla Rosa I, Sourbier C, et al. Mitochondrial topoisomerase I (TOP1MT) is a novel limiting factor of doxorubicin cardiotoxicity. Clin Cancer Res 2014;20(18):4873–4881. 68. Alvarez M, Paull K, Monks A, et al. Generation of a drug resistance profile by quantitation of mdr-1/Pglycoprotein in the cell lines of the National Cancer Institute Anticancer Drug Screen. J Clin Invest 1995;95(5):2205–2214. 69. Schneider E, Cowan KH, Multiple drug resistance in cancer therapy. Med J Aust 1994;160(6):371–373. 70. Felix CA, Kolaris CP, Osheroff N. Topoisomerase II and the etiology of chromosomal translocations. DNA Repair (Amst) 2006;5(9–10):1093–1108. 71. Cowell IG, Sondka Z, Smith K, et al. Model for MLL translocations in therapy-related leukemia involving topoisomerase IIβ-mediated DNA strand breaks and gene proximity. Proc Natl Acad Sci U S A 2012;109(23):8989–8994. 72. O’Brien ME, Wigler N, Inbar M, et al. Reduced cardiotoxicity and comparable efficacy in a phase III trial of pegylated liposomal doxorubicin HCl (CAELYX/Doxil) versus conventional doxorubicin for first-line treatment of metastatic breast cancer. Ann Oncol 2004;15(3):440–449. 73. Armenian SH, Lacchetti C, Barac A, et al. Prevention and monitoring of cardiac dysfunction in survivors of adult cancers: American Society of Clinical Oncology clinical practice guideline. J Clin Oncol 2017;35(8):893–911. 74. Davies KJ, Doroshow JH. Redox cycling of anthracyclines by cardiac mitochondria. I. Anthracycline radical formation by NADH dehydrogenase. J Biol Chem 1986;261(7):3060–3067. 75. Zhang S, Liu X, Bawa-Khalfe T, et al. Identification of the molecular basis of doxorubicin-induced cardiotoxicity. Nat Med 2012;18(11):1639–1642. 76. Zhang H, Seol Y, Agama K, et al. Distribution bias and biochemical characterization of TOP1MT single nucleotide variants. Sci Rep 2017;7(1):8614. 77. Speyer J, Wasserheit C. Strategies for reduction of anthracycline cardiac toxicity. Semin Oncol 1998;25(5):525– 537. 78. Chanan-Khan A, Srinivasan S, Czuczman MS. Prevention and management of cardiotoxicity from antineoplastic therapy. J Support Oncol 2004;2(3):251–256. 79. Von Hoff DD, Layard MW, Basa P, et al. Risk factors for doxorubicin-induced congestive heart failure. Ann Intern Med 1979;91(5):710–717. 80. Shan K, Lincoff AM, Young JB. Anthracycline-induced cardiotoxicity. Ann Intern Med 1996;125(1):47–58. 81. Swain SM, Whaley FS, Gerber MC, et al. Cardioprotection with dexrazoxane for doxorubicin-containing therapy in advanced breast cancer. J Clin Oncol 1997;15(4):1318–1332. 82. Andoh T, Ishida R. Catalytic inhibitors of DNA topoisomerase II. Biochim Biophys Acta 1998;1400(1–3):155–171. 83. Kalam K, Marwick TH. Role of cardioprotective therapy for prevention of cardiotoxicity with chemotherapy: a systematic review and meta-analysis. Eur J Cancer 2013;49(13):2900–2909. 84. Tannock IF, Osoba D, Stockler ME, et al. Chemotherapy with mitoxantrone plus prednisone or prednisone alone for symptomatic hormone-resistant prostate cancer: a Canadian randomized trial with palliative end points. J Clin Oncol 1996;14(6):1756–1764. 85. Reece DE, Elmongy MB, Barnett MJ, et al. Chemotherapy with high-dose cytosine arabinoside and mitoxantrone for poor-prognosis myeloid leukemias. Cancer Invest 1993;11(5):509–516. 86. Shenkenberg TD, Von Hoff DD. Mitoxantrone: a new anticancer drug with significant clinical activity. Ann Intern Med 1986;105(1):67–81. 87. Hollstein U. Actinomycin. Chemistry and mechanism of action. Chem Rev 1974;74(6):625–652. 88. Wassermann K, Markovits J, Jaxel C, et al. Effects of morpholinyl doxorubicins, doxorubicin, and actinomycin D on mammalian DNA topoisomerases I and II. Mol Pharmacol 1990;38(1);38–45. 89. Biedler JL, Riehm H. Cellular resistance to actinomycin D in Chinese hamster cells in vitro: cross-resistance, radioautographic, and cytogenetic studies. Cancer Res 1970;30(4):1174–1184. 90. Jaffe N, Paed D, Traggis D, et al. Improved outlook for Ewing’s sarcoma with combination chemotherapy (vincristine, actinomycin D and cyclophosphamide) and radiation therapy. Cancer 1976;38(5):1925–1930. 91. Turan T, Karacay O, Tulunay G, et al. Results with EMA/CO (etoposide, methotrexate, actinomycin D, cyclophosphamide, vincristine) chemotherapy in gestational trophoblastic neoplasia. Int J Gynecol Cancer 2006;16(3):1432–1438.

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92. Early KS, Albert DJ. Single agent chemotherapy (actinomycin D) in the treatment of metastatic testicular carcinoma. South Med J 1976;69(8):1017–1021. 93. Fernbach DJ, Martyn DT. Role of dactinomycin in the improved survival of children with Wilms’ tumor. JAMA 1966;195(12):1005–1009. 94. Maurer HM, Moon T, Donaldson M, et al. The intergroup rhabdomyosarcoma study: a preliminary report. Cancer 1977;40(5):2015–2026. 95. Chen GL, Yang L, Rowe TC, et al. Nonintercalative antitumor drugs interfere with the breakage-reunion reaction of mammalian DNA topoisomerase II. J Biol Chem 1984;259(21):13560–13566. 96. Ross W, Rowe T, Glisson B, et al. Role of topoisomerase II in mediating epipodophyllotoxin-induced DNA cleavage. Cancer Res 1984;44(12 Pt 1):5857–5860. 97. Meresse P, Dechaux E, Monneret C, et al. Etoposide: discovery and medicinal chemistry. Curr Med Chem 2004;11(18):2443–2466. 98. Valkov NI, Gump JL, Engel R, et al. Cell density-dependent VP-16 sensitivity of leukaemic cells is accompanied by the translocation of topoisomerase IIalpha from the nucleus to the cytoplasm. J Cell Biochem 2000;108(2):331– 345. 99. Sundstrøm S, Bremnes RM, Kaasa S, et al. Cisplatin and etoposide regimen is superior to cyclophosphamide, epirubicin, and vincristine regimen in small-cell lung cancer: results from a randomized phase III trial with 5 years’ follow-up. J Clin Oncol 2002;20(24):4665–4672. 100. Nichols CR, Catalano PJ, Crawford ED, et al. Randomized comparison of cisplatin and etoposide and either bleomycin or ifosfamide in treatment of advanced disseminated germ cell tumors: an Eastern Cooperative Oncology Group, Southwest Oncology Group, and Cancer and Leukemia Group B Study. J Clin Oncol 1998;16(4):1287–1293. 101. Leu BL, Huang JD. Inhibition of intestinal P-glycoprotein and effects on etoposide absorption. Cancer Chemother Pharmacol 1995;35(5):432–436. 102. Smith MA, Rubinstein L, Anderson JR, et al. Secondary leukemia or myelodysplastic syndrome after treatment with epipodophyllotoxins. J Clin Oncol 1999;17(2):569–577. 103. Maluf PT, Odone Filho V, Cristofani LM, et al. Teniposide plus cytarabine as intensification therapy and in continuation therapy for advanced nonlymphoblastic lymphomas of childhood. J Clin Oncol 1994;12(9):1963– 1968. 104. Rivera G, Bowman WP, Murphy SB, et al. VM-26 with prednisone and vincristine for treatment of refractory acute lymphocytic leukemia. Med Pediatr Oncol 1982;10(5):439–446. 105. Lovett BD, Lo Nigro L, Rappaport EF, et al. Near-precise interchromosomal recombination and functional DNA topoisomerase II cleavage sites at MLL and AF-4 genomic breakpoints in treatment-related acute lymphoblastic leukemia with t(4;11) translocation. Proc Natl Acad Sci U S A 2001;98(17):9802–9807. 106. Azarova AM, Lyu YL, Lin CP, et al. Roles of DNA topoisomerase II isozymes in chemotherapy and secondary malignancies. Proc Natl Acad Sci U S A 2007;104(26):11014–11019. 107. Ocean AJ, Starodub AN, Bardia A, et al. Sacituzumab govitecan (IMMU-132), an anti-Trop-2-SN-38 antibodydrug conjugate for the treatment of diverse epithelial cancers: safety and pharmacokinetics. Cancer 2017;123(19):3843–3854. 108. Dotan E, Cohen SJ, Starodub AN, et al. Phase I/II trial of labetuzumab govitecan (anti-CEACAM5/SN-38 antibody-drug conjugate) in patients with refractory or relapsing metastatic colorectal cancer. J Clin Oncol 2017;35(29):3338–3346. 109. Ogitani Y, Aida T, Hagihara K, et al. DS-8201a, a novel HER2-targeting ADC with a novel DNA topoisomerase I inhibitor, demonstrates a promising antitumor efficacy with differentiation from T-DM1. Clin Cancer Res 2016:22(20):5097–5108. 110. Changela A, DiGate RJ, Mondragón A. Structural studies of E. coli topoisomerase III-DNA complexes reveal a novel type IA topoisomerase-DNA conformational intermediate. J Mol Biol 2007;368(1):105–118. 111. Kummar S, Chen A, Ji J, et al. Phase I study of PARP inhibitor ABT-888 in combination with topotecan in adults with refractory solid tumors and lymphomas. Cancer Res 2011;71(17):5626–5634. 112. Bonner WM, Redon CE, Dickey JS, et al. GammaH2AX and cancer. Nat Rev Cancer 2008;8(12):957–967. 113. Kinders RJ, Hollingshead M, Lawrence S, et al. Development of a validated immunofluorescence assay for γH2AX as a pharmacodynamic marker of topoisomerase I inhibitor activity. Clin Cancer Res 2010;16(22):5447–5557. 114. Pfister TD, Hollingshead M, Kinders RJ, et al. Development and validation of an immunoassay for quantification of topoisomerase I in solid tumor tissues. PLoS One 2012;7(12):e50494. 115. Zoppoli G, Regairaz M, Leo E, et al. Putative DNA/RNA helicase Schlafen-11 (SLFN11) sensitizes cancer cells to

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DNA-damaging agents. Proc Natl Acad Sci U S A 2012;109(37):15030–15035. 116. Barretina J, Caponigro G, Stransky N, et al. The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity. Nature 2012;483(7391):603–307.

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24

Antimicrotubule Agents Christopher J. Hoimes

MICROTUBULES Microtubules are vital and dynamic cytoskeletal polymers that play a critical role in cell division, signaling, vesicle transport, shape, and polarity, which make them attractive targets in anticancer regimens and drug design.1 Microtubules are composed of 13 linear protofilaments of polymerized α/β-tubulin heterodimers arranged in parallel around a cylindrical axis and associated with regulatory proteins such as microtubule-associated proteins (MAPs), tau, and motor proteins kinesin and dynein.2 The specific biologic functions of microtubules are due to their unique polymerization dynamics. Tubulin polymerization is mediated by a nucleation-elongation mechanism. One end of the microtubules, termed the plus end, is kinetically more dynamic than the other end, termed the minus end (Fig. 24.1). Microtubule dynamics are governed by two principal processes driven by guanosine 5′-triphosphate (GTP) hydrolysis: treadmilling or poleward flux is the net growth at one end of the microtubule and the net shortening at the opposite end, and dynamic instability is a process in which the microtubule ends switch spontaneously between states of slow sustained growth and rapid depolymerization. Antimicrotubule agents are tubulin-binding drugs that directly bind tubules, inhibitors of tubulin-associated scaffold kinases, or inhibitors of their associated mitotic motor proteins ultimately to disrupt microtubule dynamics. They are broadly classified as microtubule-stabilizing or microtubule-destabilizing agents according to their effects on tubulin polymerization.

TAXANES Taxanes were the first-in-class microtubule-stabilizing drugs. Ancient medicinal attempts at cardiac pharmacotherapy using material from the toxic coniferous yew tree, Taxus spp., were likely related to the plant’s alkaloid taxine effect on sodium and calcium channels. Taxane compounds are the result of a drug screening of 35,000 plant extracts in 1963 that led to identification of activity from the bark extract of the Pacific yew tree, Taxus brevifolia. Paclitaxel was identified as the active constituent with a report of its activity in carcinoma cell lines in 1971. Motivation to identify taxanes derived from the more abundant and available needles of Taxus baccata led to the development of docetaxel, which is synthesized by the addition of a side chain to 10deacetylbaccatin III, an inactive taxane precursor. The taxane rings of paclitaxel and docetaxel are linked to an ester side chain attached to the C13 position of the ring, which is essential for antimicrotubule and antitumor activity. Nanoparticle albumin-bound paclitaxel (nab-paclitaxel) is a formulation that avoids the solvent-related side effects of non–water-soluble paclitaxel and docetaxel. Overcoming docetaxel and paclitaxel’s susceptibility to the P-glycoprotein efflux pump led to the development of cabazitaxel. Cabazitaxel is synthesized by adding two methyloxy groups to the 10-deacetylbaccatin III, which results in inhibition of the 5′-triphosphate–dependent efflux pump of P-glycoprotein. Paclitaxel initially received regulatory approval in the United States in 1992 for the treatment of patients with ovarian cancer after failure of first-line or subsequent chemotherapy (Table 24.1).1 Subsequently, it has been approved for several other indications, including advanced breast cancer after anthracycline-based regimens, combination chemotherapy of lymph node–positive breast cancer in the adjuvant setting, advanced ovarian cancer in combination with a platinum compound, second-line treatment of AIDS-related Kaposi sarcoma, and first-line treatment of non–small-cell lung cancer in combination with cisplatin (see Table 24.1). In addition to the U.S. Food and Drug Administration (FDA) on-label indications, paclitaxel is widely used for several other tumor types, such as cancer of unknown origin, bladder, esophagus, gastric, head and neck, and cervical cancers. The U.S. patent for paclitaxel expired in 2002, and a generic form of paclitaxel is available. Docetaxel was first approved for use in the United States in 1996 for patients with metastatic breast cancer that

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progressed or relapsed after anthracycline-based chemotherapy, which was later broadened to a general secondline indication (see Table 24.1). Subsequently, it received regulatory approval in adjuvant chemotherapy of stage II breast cancer in combination with Adriamycin and cyclophosphamide (TAC) and first-line treatment for locally advanced or metastatic breast cancer. In addition, docetaxel has indications in nonresectable, locally advanced, or metastatic non–small-cell lung cancer after failure of or in combination with cisplatin therapy; metastatic castration sensitive or castration resistant prostate cancer (CRPC); first-line treatment of gastric adenocarcinoma, including gastroesophageal junction adenocarcinoma in combination with cisplatin and 5-fluorouracil 5 (5-FU); and inoperable locally advanced squamous cell cancer of the head and neck in combination with cisplatin and 5FU (see Table 24.1). Docetaxel came off patent in 2010, and a generic form is available.

Mechanism of Action The unique mechanism of action for paclitaxel was initially defined by Schiff et al. in 1979, who showed that it bound to the interior surface of the microtubule lumen at binding sites completely distinct from those of exchangeable GTP, colchicine, podophyllotoxin, and the vinca alkaloids.3 The taxanes profoundly alter the tubulin dissociation rate constants at both ends of the microtubule, suppressing treadmilling and dynamic instability. Dose-dependent taxane β-tubular binding induces mitotic arrest at the G2/M transition and induces cell death. By stabilizing microtubules they also can stall ligand-dependent intracellular trafficking as shown in sequestration of the androgen receptor to the cytosol in metastatic prostate cancer patients treated with docetaxel and is associated with decreased androgen-regulated gene expression such as prostate-specific antigen (PSA).2 Peripheral neuropathy is a common dose-limiting toxicity across the antimicrotubule agents and likely is a result of their direct effect on microtubules. Studies have shown that they inhibit anterograde and/or retrograde fast axonal transport and can explain the demyelinating “dying back” pattern seen and the vulnerability of sensory neurons with the longest axonal projections.4,5

Figure 24.1 Antimicrotubule agents bind tubulin directly or inhibit its associated proteins. Taxanes and epothilones have distinct binding pockets within the same site. Estramustine has a distinct site on α/β-tubulin though also directly binds microtubule-associated proteins (MAPs). (Adapted from Lieberman M, Marks A. Marks’ Basic Medical Biochemistry: A Clinical Approach. 3rd ed. Baltimore: Lippincott Williams & Wilkins; 2009.) TABLE 24.1

Antimicrotubule Agents: Dosages and Toxicities Chemotherapeutic Agent

Dosage

Indications

Common Toxicities

Paclitaxel

135 to 200 mg/m2 IV over 3 h

Adjuvant therapy of nodepositive breast cancer; metastatic breast, ovarian, non–small-cell lung, bladder, esophagus, cervical, gastric, and head and neck cancer;

Myelosuppression, hypersensitivity, nausea, vomiting, alopecia, arthralgia, myalgia, peripheral neuropathy

or 135 mg/m2 IV over 24 h every 3 wk; or 80 mg/m2 IV over 1 h weekly

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AIDS-related Kaposi sarcoma; cancer of unknown origin Docetaxel

60 to 100 mg/m2 IV over 1 h every 3 wk

Adjuvant therapy of nodepositive breast cancer; metastatic breast, gastric, head and neck, prostate, non– small-cell lung, and ovarian cancer

Myelosuppression, hypersensitivity, edema, alopecia, nail damage, rash, diarrhea, nausea, vomiting, asthenia, neuropathy

Cabazitaxel

25 mg/m2 IV every 3 wk over 1 h

Docetaxel-refractory metastatic castration-resistant prostate cancer

Neutropenia, infections, myelosuppression, diarrhea, nausea, vomiting, constipation, abdominal pain, asthenia

Nab-paclitaxel

260 mg/m2 IV over 30 min every 3 wk; or 125 mg/m2 IV weekly on days 1, 8, and 15 every 28 d

Metastatic breast cancer, non–small-cell lung cancer, pancreatic cancer

Myelosuppression, nausea, vomiting, alopecia, myalgia, peripheral neuropathy

Ixabepilone

40 mg/m2 IV over 3 h every 3 wk

Metastatic and locally advanced breast cancer

Myelosuppression, fatigue/asthenia, myalgia/arthralgia, alopecia, nausea, vomiting, stomatitis/mucositis, diarrhea, musculoskeletal pain

Vincristine

0.5 to 1.4 mg/m2/wk IV (maximum 2 mg per dose); or 0.4 mg/d continuous infusion for 4 d

Lymphoma, acute leukemia, neuroblastoma, rhabdomyosarcoma, AIDSrelated Kaposi sarcoma, multiple myeloma, testicular cancer

Constipation, nausea, vomiting, alopecia, diplopia, myelosuppression

Vinblastine

6 mg/m2 IV on days 1 and 15 as part of the ABVD regimen; 0.15 mg/kg IV on days 1 and 2 as part of the PVB regimen; 3 mg/m2 IV on day 2 of ddMVAC

Hodgkin and non-Hodgkin lymphoma; Kaposi sarcoma; breast, testicular, and bladder cancer

Myelosuppression, constipation, alopecia, malaise, bone pain

Vinorelbine

25 to 30 mg/m2 IV weekly

Non–small-cell lung, breast, cervical, and ovarian cancer

Alopecia, diarrhea, nausea, vomiting, asthenia, neuromyopathy

Estramustine

14 mg/kg PO daily in three or four divided doses

Metastatic prostate cancer

Nausea, vomiting, gynecomastia, fluid retention

Ado-trastuzumab emtansine

3.6 mg/kg IV every 3 wk

HER2-positive metastatic breast cancer

Thrombocytopenia, nausea, constipation or diarrhea, peripheral neuropathy, fatigue, increased AST/ALT

Brentuximab vedotin

1.8 mg/kg every 3 wk, maximum dose 180 mg

Refractory Hodgkin Neutropenia, anemia, lymphoma, refractory systemic thrombocytopenia, fatigue, anaplastic large cell fever, peripheral neuropathy lymphoma IV, intravenously; ABVD, doxorubicin (Adriamycin), bleomycin, vinblastine, dacarbazine; PVB, cisplatin, vinblastine, bleomycin; ddMVAC, dose-dense methotrexate, vinblastine, doxorubicin (Adriamycin), cisplatin; PO, by mouth; HER2, human epidermal growth factor receptor 2 AST, aspartate aminotransferase; ALT, alternative lengthening of telomeres.

Recent evidence suggests that microtubule inhibitors have collateral effects during interphase that lead to cell death. For instance, paclitaxel-stabilized microtubules serve as a scaffold for the binding of the death-effector domain of pro-caspase-8 and thereby enable a caspase-8 downstream proteolytic cascade.4,6,7 This caspase-8– dependent mechanism also serves as an important basis for the understanding of the loss of function and/or low expression of the breast cancer 1, early onset gene (BRCA1) association with resistance to taxane therapy.8 Another mechanism of the anticancer effect of taxanes is attributed to the B-cell lymphoma-2 (Bcl-2) antiapoptosis family of proteins. Paclitaxel has been shown to cause phosphorylation of Bcl-2 and sequestration of Bak and Bim; however, this seemingly cancer-protective phosphorylation needs to be reconciled and likely correlates with Bcl-2 expression levels.9–11 Interestingly, neutralizing the Bcl-2 homology 3 (BH3) domain with compounds such as ABT-737 is synergistic with docetaxel.12

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Host immunologic effects of taxanes on the tumor microenvironment have been explored with docetaxel and paclitaxel. Direct on-target evidence for increased adjuvanticity has been demonstrated with enhanced trastuzumab-mediated antibody-dependent cell-mediated cytotoxicity (ADCC) of human breast carcinoma cell lines as well as human patient serum correlates after treatment with docetaxel. Data showed that activation of natural killer (NK) cells was enhanced after treatment with docetaxel via the NK group 2 member D (NKG2D) receptor with restoration of NK stimulatory ligands MICA, MICB, ULBP1, and/or ULBP2.13 Indirect antitumor immunologic effects of docetaxel and paclitaxel have been shown to occur through depletion of regulatory T cells and suppression of myeloid-derived suppressor cells.14,15 Docetaxel has been shown to induce tolerogenic cell death.

Clinical Pharmacology Paclitaxel With prolonged infusion schedules (6 and 24 hours), drug disposition is a biphasic process with values for alpha and beta half-lives averaging approximately 20 minutes and 6 hours, respectively. When administered as a 3-hour infusion, the pharmacokinetics are nonlinear and may lead to unexpected toxicity with a small dose escalation or a disproportionate decrease in drug exposure and loss of tumor response with a dose reduction. Approximately 70% of an administered dose of paclitaxel is excreted in stool via the enterohepatic circulation over 5 days as either parent compound or metabolites in humans. Renal clearance of paclitaxel and metabolites is minimal, accounting for 14% of the administered dose. In humans, the bulk of drug disposition is metabolized by cytochrome P450 mixed-function oxidases, specifically the isoenzymes CYP2C8 and CYP3A4, which metabolize paclitaxel to hydroxylated 3′-p-hydroxypaclitaxel (minor) and 6α-hydroxypaclitaxel (major), as well as dihydroxylated metabolites.

Nanoparticle Albumin-Bound Paclitaxel Nanoparticle albumin-bound paclitaxel (nab-paclitaxel) is a solvent-free colloidal suspension made by homogenizing paclitaxel with 3% to 4% albumin under high pressure to form nanoparticles of approximately 130 nm that disperse in plasma to approximately 10 nm (see Table 24.1).16 It received regulatory approval in the United States in 2005 based on results in patients with metastatic breast cancer and is now also approved in combination with carboplatin for first-line treatment of locally advanced or metastatic non–small-cell lung cancer and in combination with gemcitabine for first-line treatment of metastatic pancreatic adenocarcinoma.17 The improved responses seen with nab-paclitaxel when compared to solvent-based paclitaxel are not fully understood. Nab-paclitaxel likely capitalizes on several mechanisms that include improved pharmacokinetic profile with larger volume of distribution and higher maximal concentration of circulating unbound free drug, improved tumor accumulation by the enhanced permeability and retention (EPR) effect, and receptor-mediated transcytosis via an albumin-specific receptor (gp60) for endothelial transcytosis and binding of secreted protein acidic and rich in cysteine (SPARC) in the tumor interstitium.18 In contrast to Cremophor–ethanol (CrEL) solvent-based paclitaxel, nab-paclitaxel exhibits extensive extravascular volume of distribution exceeding that of water, indicating extensive tissue and extravascular protein distribution. Some studies show that nab-paclitaxel achieves 33% higher drug concentration over CrEL-paclitaxel.19 Additionally, maximum concentration (Cmax), mean plasma half-life of 15 to 18 hours, area under the curve (AUC), and dose-independent plasma clearance correspond to linear pharmacokinetics over 80 to 300 mg/m2.20 Improved deposition of a nanoparticle such as nab-paclitaxel in a tumor tissue can occur passively through an EPR effect in areas of leaky vasculature and sufficient vascular pore size and decreased lymphatic flow.21 Once in the tissue, the nab-paclitaxel nanovehicle can deliver the drug locally or benefit from further receptor-mediated targeting to SPARC, which has been shown to be overexpressed and correlates with disease progression in many tumor types. High stromal SPARC level was associated with longer survival in patients treated with nab-paclitaxel in phase I/II trials but was not predictive of response in the phase III trial of patients with pancreatic cancer.22

Docetaxel The pharmacokinetics of docetaxel on a 1-hour schedule is triexponential and linear at doses of 115 mg/m2 or less. Terminal half-lives ranging from 11.1 to 18.5 hours have been reported. The most important determinants of docetaxel clearance were the body surface area (BSA), hepatic function, and plasma α1-acid glycoprotein

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concentration. Plasma protein binding is high (>80%), and binding is primarily to α1-acid glycoprotein, albumin, and lipoproteins. The hepatic cytochrome P450 mixed-function oxidases, particularly isoforms CYP3A4 and CYP3A5, are principally involved in biotransformation. The principal pharmacokinetic determinants of toxicity, particularly neutropenia, are drug exposure and the time that plasma concentrations exceed biologically relevant concentrations. The baseline level of α1-acid glycoprotein may be elevated as an acute phase reactant in advanced disease and is an independent predictor of response and a major objective prognostic factor of survival in patients with non–small-cell lung cancer treated with docetaxel chemotherapy.

Cabazitaxel Cabazitaxel is a semisynthetic derivative of the natural taxoid 10-deacetylbaccatin III. It binds to and stabilizes the β-tubulin subunit, resulting in the inhibition of microtubule depolymerization and cell division, cell cycle arrest in the G2/M phase, and the inhibition of tumor cell proliferation.23 It is active against diverse cancer cell lines and tumor models that are sensitive and resistant to docetaxel including prostate, mammary, melanoma, kidney, colon, pancreas, lung, gastric, and head and neck. Cabazitaxel is a poor substrate for the membrane-associated, multidrug resistance P-glycoprotein efflux pump and therefore is useful for treating docetaxel-refractory prostate cancer for which it gained FDA approval in 2010.23 Cabazitaxel has biologic and clinical characteristics that are distinct from docetaxel and include (1) penetration through the blood–brain barrier,24 (2) improved cytostatic and cytotoxic response that is independent of the androgen receptor in CRPC, (3) inducement of molecular actions that are distinct from docetaxel based on gene-expression profiling, and (4) tumors that develop castration resistance via RB loss that show enhanced sensitivity over docetaxel.25 Pharmacokinetics of cabazitaxel is similar to docetaxel; however, cabazitaxel has a larger volume of distribution and longer terminal half-life (mean 77.3 hours versus 11.2 hours for docetaxel).24

Tesetaxel Tesetaxel (DJ-927, XRP6258) is a semisynthetic orally bioavailable taxane in late-stage clinical trials. It has postulated benefits of less hypersensitivity and possibly less neurotoxicity compared to other taxanes. Doselimiting toxicity is neutropenia, and its activity is independent of P-glycoprotein expression.

Drug Interactions Sequence-dependent pharmacokinetic and toxicologic interactions between paclitaxel and several other chemotherapy agents have been noted. The sequence of cisplatin followed by paclitaxel (24-hour schedule) induces more profound neutropenia than the reverse sequence, which is explained by a 33% reduction in the clearance of paclitaxel after cisplatin.26 Treatment with paclitaxel on either a 3- or 24-hour schedule followed by carboplatin has been demonstrated to produce equivalent neutropenia and less thrombocytopenia as compared to carboplatin as a single agent, which is not explained by pharmacokinetic interactions. Neutropenia and mucositis are more severe when paclitaxel is administered on a 24-hour schedule before doxorubicin, compared to the reverse sequence, which is most likely due to an approximately 32% reduction in the clearance rates of doxorubicin and doxorubicinol when doxorubicin is administered after paclitaxel. Several agents that inhibit cytochrome P450 mixed-function oxidases interfere with the metabolism of paclitaxel and docetaxel in human microsomes in vitro; however, the clinical relevance of these findings is not known.26

Toxicity Paclitaxel The micelle-forming CrEL vehicle that is required for suspension and intravenous delivery of paclitaxel causes its nonlinear pharmacokinetics and thereby impacts its therapeutic index. CrEL causes hypersensitivity reactions, with major reactions usually occurring within the first 10 minutes after the first treatment and resolving completely after stopping treatment. All patients should be premedicated with steroids, diphenhydramine, and an H2 antagonist, although up to 3% will still have reactions. Those who have major reactions have been rechallenged successfully after receiving high doses of corticosteroids. Neuropathy is the principal toxicity of paclitaxel. Paclitaxel induces a peripheral neuropathy that presents in a symmetric stocking glove distribution, at first transient and then persistent.27 Neurologic examination reveals

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sensory loss, and neurophysiologic studies reveal axonal degeneration and demyelination.27 Compared with cisplatin, loss of deep tendon reflexes occurs less commonly; however, autonomic and motor changes can occur. Severe neurotoxicity is uncommon when paclitaxel is given alone at doses below 200 mg/m2 on a 3- or 24-hour schedule every 3 weeks or below 100 mg/m2 on a continuous weekly schedule. There is no convincing evidence that any specific measure is effective at ameliorating existing manifestations or preventing the development or worsening of neurotoxicity.27 Neutropenia is also frequent with paclitaxel—the onset is usually on days 8 to 11, and recovery is generally complete by days 15 to 21 with an every-3-week dosing regimen. Neutropenia is noncumulative, and the duration of severe neutropenia, even in heavily pretreated patients, is usually brief. Severity of neutropenia is related to duration of exposure above the biologically relevant levels of 0.05 to 0.10 mM/L, and the nonlinear pharmacokinetics of paclitaxel should be considered whenever adjusting dose. The most common cardiac rhythm disturbance, a transient sinus bradycardia, can be observed in up to 30% of patients. Routine cardiac monitoring during paclitaxel therapy is not necessary but is advisable for patients who may not be able to tolerate bradyarrhythmias. Drug-related gastrointestinal effects, such as vomiting and diarrhea, are uncommon. Severe hepatotoxicity and pancreatitis have also been noted rarely. Pulmonary toxicities, including acute bilateral pneumonitis, have been reported. Extravasation of large volumes can cause moderate soft tissue injury. Paclitaxel also induces reversible alopecia of the scalp in a dose-related fashion. Nail disorders have also been reported with paclitaxel use and include ridging, nail bed pigmentation, onychorrhexis, and onycholysis. These side effects have been reported more commonly with dose-intensified paclitaxel regimens. Recent studies have suggested a role for ABC transporter polymorphisms in the development of neuropathy and neutropenia. Sissung et al.28 reported that patients carrying two reference alleles for the ABCB1 (Pglycoprotein, MDR1) 3435C greater than T polymorphism had a reduced risk to develop neuropathy as compared to patients carrying at least one variant allele (P = .09). Data from a large controlled trial to evaluate these and other candidate polymorphisms failed to detect a significant association between genotype and outcome or toxicity for any of the genes analyzed, although the correlative studies were retrospective and the sample size was inadequate to rule out smaller differences.29 A large randomized trial of the CALGB 40101 using an integrated genomewide associate study found two polymorphisms associated with paclitaxel-induced polyneuropathy with validation in a larger dataset.30,31 Both are involved in nerve development and maintenance including the hereditary peripheral neuropathy Charcot-Marie-Tooth disease gene, FGD4. Further studies are required to adequately assess the role of these variants in predicting toxicity from taxane therapy.

Nab-paclitaxel Hypersensitivity reactions have not been observed during the infusion period, and therefore, steroid premedications are not necessary. The main dose-limiting toxicities are neutropenia and sensory neuropathy. In a trial comparing weekly paclitaxel 90 mg/m2 to nab-paclitaxel 150 mg/m2 to ixabepilone in patients with metastatic breast cancer, although median progression-free survival was not significantly different (at 12-month follow-up), there was more hematologic toxicity and peripheral neuropathy in the nab-paclitaxel arm compared to the paclitaxel arm.32 This led to dose reductions in 45% of patients in the nab-paclitaxel arm compared with 15% for the paclitaxel arm.32 Other toxicities include alopecia, diarrhea, nausea and vomiting, elevations in liver enzymes, arthralgia, myalgia, and asthenia.

Docetaxel Neutropenia is the main toxicity of docetaxel. When docetaxel is administered on an every-3-week schedule, the onset of neutropenia is usually noted on day 8 with complete resolution by days 15 to 21. Neutropenia is significantly less when low doses are administered weekly. FDA black box warnings include increased toxicity in patients with abnormal liver function and in select non–small-cell lung cancer patients that received prior platinum, severe hypersensitivity reactions, and severe fluid retention despite dexamethasone home premedication. Hypersensitivity reactions were noted in 31% of patients who received the drug without premedications in early studies. Symptoms include flushing, rash, chest tightness, back pain, dyspnea, and fever or chills. Severe hypotension, bronchospasm, generalized rash, and erythema may also occur.33 Major reactions usually occur during the first two courses and within minutes after the start of treatment. Signs and symptoms generally resolve within 15 minutes after cessation of treatment, and docetaxel can usually be reinstituted without sequelae after treatment with diphenhydramine and an H2-receptor antagonist. Docetaxel induces a unique fluid retention

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syndrome characterized by edema, weight gain, and third-space fluid collection. Fluid retention is cumulative and is due to increased capillary permeability. Prophylactic treatment with corticosteroids has been demonstrated to reduce the incidence of fluid retention. Aggressive and early treatment with diuretics has been successfully used to manage fluid retention. Skin toxicity may occur in as many as 50% to 75% of patients; however, premedication may reduce the overall incidence of this effect. Other cutaneous effects include palmar-plantar erythrodysesthesia and onychodystrophy. Docetaxel produces neurotoxicity, which is qualitatively similar to that of paclitaxel; however, neurosensory and neuromuscular effects are generally less frequent and less severe than with paclitaxel. Mild to moderate peripheral neurotoxicity occurs in approximately 40% of untreated patients. Asthenia has been a prominent complaint in patients who have been treated with large cumulative doses. Stomatitis appears to occur more frequently with docetaxel than with paclitaxel. Other reported toxicities of note include necrotizing enterocolitis, interstitial pneumonitis, and organizing pneumonia.

Cabazitaxel A phase III multi-institutional study of men with metastatic CRPC who had failed docetaxel improved overall median survival on cabazitaxel compared to mitoxantrone.34 Cabazitaxel was approved by the FDA in June 2010 to treat metastatic CRPC in those who had received prior chemotherapy. This was despite a higher rate of adverse deaths (4.9%), and a third of those were due to neutropenic sepsis. Cabazitaxel was associated with more grade 3 or 4 neutropenia (82%) than mitoxantrone (58%). Side effects reported in more than 20% of patients treated with cabazitaxel included myelosuppression, diarrhea, nausea, vomiting, constipation, abdominal pain, or asthenia. FDA black box warnings are similar to those of docetaxel.

VINCA ALKALOIDS The vinca alkaloids have been some of the most active agents in cancer chemotherapy since their introduction 40 years ago. The naturally occurring members of the family, vinblastine (VBL) and vincristine (VCR), were isolated from the leaves of the periwinkle plant Catharanthus roseus G. Don. In the late 1950s, their antimitotic and, therefore, cancer chemotherapeutic potential was discovered by groups both at Eli Lilly Research Laboratories and at the University of Western Ontario, and they came into widespread use for the single-agent treatment of childhood hematologic and solid malignancies and, shortly after, for adult hematologic malignancies (see Table 24.1).1 Their clinical efficacy in several combination therapies has led to the development of various novel semisynthetic analogues, including vinorelbine (VRL), vindesine (VDS), and vinflunine (VFL).

Mechanism of Action In contrast to the taxanes, the vinca alkaloids depolymerize microtubules and destroy mitotic spindles.1 At low but clinically relevant concentrations, VBL does not depolymerize spindle microtubules; yet, it powerfully blocks mitosis, and this has been suggested to occur as a result of suppression of microtubule dynamics rather than microtubule depolymerization. This group of compounds binds to the β subunit of tubulin dimers at a distinct region called the vinca-binding domain. Importantly, binding of VBL induces a conformational change in tubulin in connection with tubulin self-association. In mitotic spindles, slowing of the growth and shortening or treadmilling dynamics of the microtubules block mitotic progression. Disruption of the normal mitotic spindle assembly leads to delayed cell cycle progress with chromosomes stuck at the spindle poles and unable to pass from metaphase into anaphase and eventually induces to apoptosis. The naturally occurring vinca alkaloids VCR and VBL, the semisynthetic analogue VRL, and a novel bifluorinated analogue VFL have similar mechanisms of action. Tissue and tumor sensitivities to the vinca alkaloids, which relate in part to differences in drug transport and accumulation, also vary. Intracellular or extracellular concentration ratios range from 5- to 500-fold depending on the individual cell type, lipophilicity, tissue-specific factors such as tubulin isotype composition, and tissuespecific MAPs.35–37 Although the vinca alkaloids are retained in cells for long periods of time and thus may have prolonged cellular effects, intracellular retention is markedly different among the various vinca alkaloids. For instance, VBL appears to be retained in lipophilic tissue much more than either VCR or VDS.37 Newer theories of mechanism of action of antimicrotubule agents have emerged, suggesting that the more important target of these drugs may be the tumor vasculature, as reviewed in the next section. Host immunologic effects of vinca alkaloids on the tumor microenvironment have been explored with VRL.

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Indirect antitumor immunologic effects in patients with non–small-cell lung cancer treated with VRL (plus cisplatin) may occur through a depletion of regulatory T cells.38

Clinical Pharmacology The vinca alkaloids are usually administered intravenously as a brief infusion, and their pharmacokinetic behavior in plasma has generally been explained by a three-compartment model. The vinca alkaloids share many pharmacokinetic properties, including large volumes of distribution, high clearance rates, and long terminal halflives that reflect the high magnitude and avidity of drug binding in peripheral tissues. VCR has the longest terminal half-life and the lowest clearance rate, VBL has the shortest terminal half-life and the highest clearance rate, and VDS has intermediate characteristics. Although prolonged infusion schedules may avoid excessively toxic peak concentrations and increase the duration of drug exposure in plasma above biologically relevant threshold concentrations, there is little evidence to support the notion that prolonged infusions are more effective than bolus schedules. The longest half-life and lowest clearance rate of VCR may account for its greater propensity to induce neurotoxicity, but there are many other nonpharmacokinetic determinants of tissue sensitivity, as discussed in the previous section.

Vincristine After conventional doses of VCR (1.4 mg/m2) given as brief infusions, peak plasma levels approach 0.4 μmole. Plasma clearance is slow, and terminal half-lives that range from 23 to 85 hours have been reported. VCR is metabolized and excreted primarily by the hepatobiliary system. The nature of the VCR metabolites identified to date, as well as the results of metabolic studies in vitro, indicate that VCR metabolism is mediated principally by hepatic cytochrome P450 CYP3A5.

Vinblastine The clinical pharmacology of VBL is similar to that of VCR. Binding of VBL to plasma proteins and formed elements of blood is extensive.39,40 Peak plasma drug concentrations are approximately 0.4 mM after rapid intravenous injections of VBL at standard doses. Distribution is rapid, and terminal half-lives range from 20 to 24 hours. Like VCR, VBL disposition is principally through the hepatobiliary system with excretion in feces (approximately 95%); however, fecal excretion of the parent compound is low, indicating that hepatic metabolism is extensive.37

Vinorelbine The pharmacologic behavior of VRL is similar to that of the other vinca alkaloids, and plasma concentrations after rapid intravenous administration have been reported to decline in either a biexponential or triexponential manner.41 After intravenous administration, there is a rapid decay of VRL concentrations followed by a much slower elimination phase (terminal half-life, 18 to 49 hours). Plasma protein binding, principally to α1-acid glycoprotein, albumin, and lipoproteins, has been reported to range from 80% to 91%, and drug binding to platelets is extensive.41 VRL is widely distributed, and high concentrations are found in virtually all tissues, except the central nervous system.41 The wide distribution of VRL reflects its lipophilicity, which is among the highest of the vinca alkaloids. As with other vinca alkaloids, the liver is the principal excretory organ, and up to 80% of VRL is excreted in the feces, whereas urinary excretion represents only 16% to 30% of total drug disposition, the bulk of which is unmetabolized VRL. Studies in humans indicate that 4-O-deacetyl-VRL and 3,6epoxy-VRL are the principal metabolites, and several minor hydroxy-VRL isomer metabolites have been identified. Although most metabolites are inactive, the deacetyl-VRL metabolite may be as active as VRL. The cytochrome P450 CYP3A isoenzyme appears to be principally involved in biotransformation.

Vinflunine VFL is a novel semisynthetic microtubule inhibitor with a fluorinated catharanthine moiety that translates into lower affinity for the vinca binding site on tubulin and therefore different quantitative effects on microtubule dynamics.42 The low affinity for tubulin may be responsible for its reduced clinical neurotoxicity. Despite this lower affinity, it is more active in vivo than other vinca alkaloids and resistance develops more slowly. VFL is a new vinca and still under clinical development. Its volume of distribution is large, and it has a terminal half-life of

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nearly 40 hours.42 The only active metabolite is 4-O-deacetylvinflunine, which has a terminal half-life approximately 5 days longer than that of the parent compound.42

Drug Interactions Methotrexate accumulation in tumor cells is enhanced in vitro by the presence of VCR or VBL, an effect mediated by a vinca alkaloid–induced blockade of drug efflux; however, the minimal concentrations of VCR required to achieve this effect occur only transiently in vivo.43 The vinca alkaloids also inhibit the cellular influx of the epipodophyllotoxins in vitro, resulting in less cytotoxicity, but the clinical implications of this potential interaction are unknown. L-asparaginase may reduce the hepatic clearance of the vinca alkaloids, which may result in increased vinca-related toxicity. To minimize the possibility of this interaction, the vinca alkaloids should be given 12 to 24 hours before L-asparaginase. The combined use of mitomycin C and the vinca alkaloids has been associated with acute dyspnea and bronchospasm. The onset of these pulmonary toxicities has ranged from within minutes to hours after treatment with the vinca alkaloids or up to 2 weeks after mitomycin C. Treatment with the vinca alkaloids has precipitated seizures associated with subtherapeutic plasma phenytoin concentrations.43 Reduced plasma phenytoin levels have been noted from 24 hours to 10 days after treatment with VCR and VBL. Because of the importance of the cytochrome P450 CYP3A isoenzyme in vinca alkaloid metabolism, administration of the vinca alkaloids with erythromycin and other inhibitors of CYP3A may lead to severe toxicity.44 Concomitantly administered drugs, such as pentobarbital and H2-receptor antagonists, may also influence VCR clearance by modulating hepatic cytochrome P450 metabolic processes.44

Toxicity Despite close similarities in structure, the vinca alkaloids differ in their safety profiles. Neutropenia is the principal dose-limiting toxicity of VBL and VRL. Thrombocytopenia and anemia occur less commonly. The onset of neutropenia is usually day 7 to 11, with recovery by days 14 to 21, and can be potentiated by hepatic dysfunction. Gastrointestinal autonomic dysfunction, as manifested by bloating, constipation, ileus, and abdominal pain, occur most commonly with VCR or high doses of the other vinca alkaloids. Mucositis occurs more frequently with VBL than with VRL and is least common with VCR. Nausea, vomiting, diarrhea, and pancreatitis also occur to a lesser extent. VCR principally induces neurotoxicity characterized by a peripheral, symmetric mixed sensorimotor and autonomic polyneuropathy.45 Toxic manifestations include constipation, abdominal cramps, paralytic ileus, urinary retention, orthostatic hypotension, and hypertension. Its primary neuropathologic effects are due to interference with axonal microtubule function. Early symmetric sensory impairment and paresthesias can progress to neuritic pain and loss of deep tendon reflexes with continued treatment, which may be followed by foot drop, wrist drop, motor dysfunction, ataxia, and paralysis. Cranial nerves are rarely affected as the uptake of VCR into the central nervous system is low. Severe neurotoxicity occurs infrequently with VBL and VDS. VRL has been shown to have a lower affinity for axonal microtubules than either VCR or VBL, which seems to be confirmed by clinical observations.46 Mild to moderate peripheral neuropathy, principally characterized by sensory effects, occurs in 7% to 31% of patients, and constipation and other autonomic effects are noted in 30% of patients, whereas severe toxicity occurs in 2% to 3%. In adults, neurotoxicity may occur after treatment with cumulative doses as little as 5 to 6 mg, and manifestations may be profound after cumulative doses of 15 to 20 mg. Patients with delayed biliary excretion or hepatic dysfunction and those with antecedent neurologic disorders, such as Charcot-Marie-Tooth disease, hereditary and sensory neuropathy type 1, and Guillain-Barré, are predisposed to neurotoxicity. The vinca alkaloids are potent vesicants. To decrease risk of phlebitis, the vein should be adequately flushed after treatment. If extravasation is suspected, treatment should be discontinued, aspiration of any residual drug remaining in the tissues should be attempted, and prompt application of heat (and not ice) for 1 hour four times daily for 3 to 5 days can limit tissue damage.47 Hyaluronidase, 150 to 1,500 U (15 U/mL in 6 mL 0.9% sodium chloride solution) subcutaneously, through six clockwise injections in a circumferential manner using a 25-gauge needle (changing the needle with each new injection) into the surrounding tissues may minimize discomfort and latent cellulitis. A surgical consultation to consider early debridement is also recommended. Mild and reversible alopecia occurs in approximately 10% and 20% of patients treated with VLR and VCR, respectively. Acute cardiac ischemia, chest pains without evidence of ischemia, fever, Raynaud syndrome, hand-foot syndrome, and pulmonary and liver toxicity (transaminitis and hyperbilirubinemia) have also been reported with use of the vinca

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alkaloids. All of the vinca alkaloids can cause syndrome of inappropriate secretion of antidiuretic hormone (SIADH), and patients who are receiving intensive hydration are particularly prone to severe hyponatremia secondary to SIADH.

MICROTUBULE ANTAGONISTS Estramustine Phosphate Estramustine is a conjugate of nor-nitrogen mustard linked to 17β-estradiol by a carbamate ester bridge. Estramustine phosphate received regulatory approval in the United States in 1981 for treating patients with CRPC. Estramustine has activity in CRPC and had been used in combination with VBL or docetaxel. Phase III trials in patients with CRPC showed, however, that when combined with docetaxel, there is no added benefit to overall survival compared to docetaxel alone. Estramustine binds to β-tubulin at a site distinct from the colchicine and vinca alkaloid–binding sites. This agent depolymerizes microtubules and microfilaments, binds to and disrupts MAPs, and inhibits cell growth at high concentrations, resulting in mitotic arrest and apoptosis in tumor cells. The selective accumulation and actions of estramustine phosphate and its metabolite, estromustine, in specific tissues appear to be dependent on the expression of the estramustine-binding protein (EMBP). The disposition of estramustine is principally by rapid oxidative metabolism of the parent compound to estromustine. Estromustine concentrations in plasma are maximal within 2 to 4 hours after oral administration, and the mean elimination half-life of estromustine is 14 hours. Estromustine and estramustine are principally excreted in the feces, with only small amounts of conjugated estrone and estradiol detected in the urine (200 nM for aurora B kinase and is in clinical development for neuroendocrine prostate cancer.59,61 Neutropenia is the dose-limiting toxicity.

Kinesin Spindle Protein Inhibitor Kinesin spindle protein (KSP; also known as EG5) is a kinesin motor protein required to establish mitotic-spindle bipolarity. SB-715992 (ispinesib) is a small-molecule inhibitor of KSP adenosine triphosphatase (ATPase); and

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was largely inactive in phase II studies of prostate, renal, and head and neck cancers. Other compounds are still in trials. The lack of efficacy thus far in antimitotic agents may be due to several reasons. However, it’s clear that targeting mitosis to avoid neurotoxicity of microtubule inhibition has tradeoffs where more quiescent cells are spared and may be responsible for eventual recurrence and resistance. Targeting motor proteins responsible for both interphase and mitosis may be essential to realize efficacy with these agents.

MECHANISMS OF RESISTANCE TO MICROTUBULE INHIBITORS Drug resistance is often complex and multifaceted and can involve diverse mechanisms such as (1) factors that reduce the ability of drugs to reach their cellular target (e.g., activation of detoxification pathways and decreased drug accumulation), (2) modifications in the drug target, and (3) events downstream of the target (e.g., decreased sensitivity to, or defective, apoptotic signals). Many tubulin-binding agents are substrates for multidrug transporters such as P-glycoprotein and the multidrug resistance gene (MDR1).62 The MDR1-encoded gene product MDR1 (ABC subfamily B1; ABCB1) and MDR2 (ABC subfamily B4; ABCB4) are the best characterized adenosine triphosphate–binding cassette (ABC) transporters thought to confer drug resistance to taxanes.62,63 MDR-related taxane resistance can be reversed by many classes of drugs, including the calcium channel blockers, cyclosporin A, and antiarrhythmic agents.62,63 However, the clinical utility of this approach has never been proven, despite several clinical trials. The role of ABC transporters in resistance to microtubule inhibitors remains to be determined.64 An increasing number of studies suggest that the expression of individual tubulin polymer or tubulin isotypes are altered in cells resistant to antimicrotubule drugs and may confer drug resistance.65,66 Inherent differences in microtubule dynamics and drug interactions have been observed with some isotypes in vitro and in vivo.67 Several taxane-resistant mutant cell lines that have structurally altered α- and β-tubulin proteins and an impaired ability to polymerize into microtubules have also been identified.68 Mutations of tubulin isotype genes, gene amplifications, and isotype switching have also been reported in taxane-resistant cell lines.68 In patients, levels of class III βtubulin have been shown to correlate with response—those with high RNA levels have poor response—and immunohistochemical stains can correlate and may be predictive. As opposed to taxanes, resistance to vinca alkaloids has been associated with decreased class II β-tubulin expression.65,67 MAPs are important structural and regulatory components of microtubules that act in concert to remodel the microtubule network by stabilizing or destabilizing microtubules during mitosis or cytokinesis. Alterations in the activity and/or balance of stabilizing or destabilizing MAPs can profoundly affect microtubule function. The overexpression of stathmin, a destabilizing protein,69 has been reported to decrease sensitivity to paclitaxel and VBL. An analysis of predictive or prognostic factors in a large phase III study (National Surgical Adjuvant Breast and Bowel Project [NSABP] B28) in patients with node-positive breast cancer showed that MAP-tau, a stabilizing protein, was a prognostic factor; however, it was not predictive for benefit from paclitaxel-based chemotherapy.70 In a separate randomized controlled trial in breast cancer (TAX 307) where the only variable was docetaxel, MAP-tau was also shown to be prognostic but not predictive of taxane benefit.71 Additional studies have shown a correlation with BRCA1 loss measured by gene or protein expression, or gene signatures, with resistance to taxane and sensitivity to DNA-damaging agents (such as cisplatin and anthracyclines).72 BRCA1 is a tumor-suppressor gene with DNA damage response and repair, as well as cell cycle checkpoint activation, which explains why its loss leads to enhanced cisplatin sensitivity.19 BRCA1 also indirectly regulates microtubule dynamics and stability and can favorably control how microtubules respond to paclitaxel treatment via their association with pro-caspase-8. Loss of BRCA1 can lead to impaired taxane- induced activation of apoptosis due to microtubules that are more dynamic and less susceptible to taxane-induced stabilization and proximity induced activation of caspase-8 signaling.8 In addition to resistance, certain tumor subtypes may be sensitive to taxane dosing schedule. In two randomized trials of low-dose weekly paclitaxel, the luminal breast cancer subtype was found to have a better outcome compared with the control arm. This suggests that not only drug but also schedule may influence response to therapy and that genomic approaches may reveal these insights.

SUMMARY

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Antimicrotubule agents can impact mitosis progression, the cell cycle, as well as intracellular trafficking and have broad antineoplastic action including hematologic and solid malignancies. Impacts on the host immune tumor microenvironment are also being elucidated. New agents are currently being developed that can more efficiently target tumor tissue with fewer side effects and ease of administration. Synthetic chemistry, drug design, experimental therapeutics, and improved delivery platforms with ADC and nanoparticle formulations are helping to advance and more precisely target the microtubule. Omics approaches are being developed to define biomarkers of resistance and toxicity of antimicrotubule agents. Opportunities for rational combinations of antimicrotubule agents with immune checkpoint inhibitors are currently being explored.

REFERENCES 1. 2. 3. 4.

Kavallaris M. Microtubules and resistance to tubulin-binding agents. Nat Rev Cancer 2010;10(3):194–204. Nogales E. Structural insight into microtubule function. Annu Rev Biophys Biomol Struct 2001;30:397–420. Schiff PB, Fant J, Horwitz SB. Promotion of microtubule assembly in vitro by taxol. Nature. 1979;277,665-7. Gornstein E, Schwarz TL. The paradox of paclitaxel neurotoxicity: mechanisms and unanswered questions. Neuropharmacology 2014;76 (Pt A):175–183. 5. LaPointe NE, Morfini G, Brady ST, et al. Effects of eribulin, vincristine, paclitaxel and ixabepilone on fast axonal transport and kinesin-1 driven microtubule gliding: implications for chemotherapy-induced peripheral neuropathy. Neurotoxicology 2013;37:231–239. 6. Mielgo A, Torres VA, Clair K, et al. Paclitaxel promotes a caspase 8-mediated apoptosis through death effector domain association with microtubules. Oncogene 2009;28(40):3551–3562. 7. Komlodi-Pasztor E, Sackett D, Wilkerson J, et al. Mitosis is not a key target of microtubule agents in patient tumors. Nat Rev Clin Oncol 2011;8(4):244–250. 8. Sung M, Giannakakou P. BRCA1 regulates microtubule dynamics and taxane-induced apoptotic cell signaling. Oncogene 2014;33(22):1418–1428. 9. Dai H, Ding H, Meng XW, et al. Contribution of Bcl-2 phosphorylation to Bak binding and drug resistance. Cancer Res 2013;73(23):6998–7008. 10. Srivastava RK, Mi QS, Hardwick JM, et al. Deletion of the loop region of Bcl-2 completely blocks paclitaxelinduced apoptosis. Proc Natl Acad Sci U S A 1999;96(7):3775–3780. 11. Strobel T, Kraeft SK, Chen LB, et al. BAX expression is associated with enhanced intracellular accumulation of paclitaxel: a novel role for BAX during chemotherapy-induced cell death. Cancer Res 1998;58(21):4776–4781. 12. Oakes SR, Vaillant F, Lim E, et al. Sensitization of BCL-2-expressing breast tumors to chemotherapy by the BH3 mimetic ABT-737. Proc Natl Acad Sci U S A 2012;109(8):2766–2771. 13. Di Modica M, Sfondrini L, Regondi V, et al. Taxanes enhance trastuzumab-mediated ADCC on tumor cells through NKG2D-mediated NK cell recognition. Oncotarget 2016;7(1):255–265. 14. Li JY, Duan XF, Wang LP, et al. Selective depletion of regulatory T cell subsets by docetaxel treatment in patients with nonsmall cell lung cancer. J Immunol Res 2014;2014:286170. 15. Sevko A, Michels T, Vrohlings M, et al. Antitumor effect of paclitaxel is mediated by inhibition of myeloidderived suppressor cells and chronic inflammation in the spontaneous melanoma model. J Immunol 2013;190(5):2464–2471. 16. Chouhan J, Herrington J. Single premedication dose of dexamethasone 20 mg IV before docetaxel administration. J Oncol Pharm Pract 2011;17(3):155–159. 17. Von Hoff DD, Ervin T, Arena FP, et al. Increased survival in pancreatic cancer with nab-paclitaxel plus gemcitabine. N Engl J Med 2013;369(18):1691–1703. 18. Yardley DA. nab-Paclitaxel mechanisms of action and delivery. J Control Release 2013;170(3):365–372. 19. Desai N, Trieu V, Yao Z, et al. Increased antitumor activity, intratumor paclitaxel concentrations, and endothelial cell transport of cremophor-free, albumin-bound paclitaxel, ABI-007, compared with cremophor-based paclitaxel. Clin Cancer Res 2006;12(4):1317–1324. 20. Sparreboom A, Scripture CD, Trieu V, et al. Comparative preclinical and clinical pharmacokinetics of a cremophor-free, nanoparticle albumin-bound paclitaxel (ABI-007) and paclitaxel formulated in Cremophor (Taxol). Clin Cancer Res 2005;11(11):4136–4143. 21. Cheng CJ, Saltzman WM. Nanomedicine: downsizing tumour therapeutics. Nat Nanotechnol 2012;7(6):346–347. 22. Hidalgo M, Plaza C, Musteanu M, et al. SPARC expression did not predict efficacy of nab-paclitaxel plus gemcitabine or gemcitabine alone for metastatic pancreatic cancer in an exploratory analysis of the phase III MPACT trial. Clin Cancer Res 2015;21(21):4811–4818.

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23. Vrignaud P, Sémiond D, Lejeune P, et al. Preclinical antitumor activity of cabazitaxel, a semisynthetic taxane active in taxane-resistant tumors. Clin Cancer Res 2013;19(11):2973–2983. 24. Mita AC, Denis LJ, Rowinsky EK, et al. Phase I and pharmacokinetic study of XRP6258 (RPR 116258A), a novel taxane, administered as a 1-hour infusion every 3 weeks in patients with advanced solid tumors. Clin Cancer Res 2009;15(2):723–730. 25. de Leeuw R, Berman-Booty LD, Schiewer MJ, et al. Novel actions of next-generation taxanes benefit advanced stages of prostate cancer. Clin Cancer Res 2015;21(4):795–807. 26. Vigano L, Locatelli A, Grasselli G, et al. Drug interactions of paclitaxel and docetaxel and their relevance for the design of combination therapy. Invest New Drugs 2001;19(2):179–196. 27. Kudlowitz D, Muggia F. Defining risks of taxane neuropathy: insights from randomized clinical trials. Clin Cancer Res 2013;19(17):4570–4577. 28. Sissung TM, Mross K, Steinberg SM, et al. Association of ABCB1 genotypes with paclitaxel-mediated peripheral neuropathy and neutropenia. Eur J Cancer 2006;42(17):2893–2896. 29. Marsh S, Paul J, King CR, et al. Pharmacogenetic assessment of toxicity and outcome after platinum plus taxane chemotherapy in ovarian cancer: the Scottish Randomised Trial in Ovarian Cancer. J Clin Oncol 2007;25(29):4528–4535. 30. Abraham JE, Guo Q, Dorling L, et al. Replication of genetic polymorphisms reported to be associated with taxanerelated sensory neuropathy in patients with early breast cancer treated with Paclitaxel. Clin Cancer Res 2014;20(9):2466–2475. 31. Baldwin RM, Owzar K, Zembutsu H, et al. A genome-wide association study identifies novel loci for paclitaxelinduced sensory peripheral neuropathy in CALGB 40101. Clin Cancer Res 2012;18(18):5099–5109. 32. Rugo H, Barry W, Moreno Aspitia A, et al. CALGB 40502/NCCTG N063H: randomized phase III trial of weekly paclitaxel (P) compared to weekly nanoparticle albumin bound nab-paclitaxel (NP) or ixabepilone (Ix) with or without bevacizumab (B) as first-line therapy for locally recurrent or metastatic breast cancer (MBC). J Clin Oncol 2012;30:CRA1002. 33. Baker J, Ajani J, Scotté F, et al. Docetaxel-related side effects and their management. Eur J Oncol Nurs 2009;13(1):49–59. 34. de Bono JS, Oudard S, Ozguroglu M, et al. Prednisone plus cabazitaxel or mitoxantrone for metastatic castrationresistant prostate cancer progressing after docetaxel treatment: a randomised open-label trial. Lancet 2010;376(9747):1147–1154. 35. Jordan MA, Wilson L. Microtubules as a target for anticancer drugs. Nat Rev Cancer 2004;4(4):253–265. 36. Zhou J, Giannakakou P. Targeting microtubules for cancer chemotherapy. Cur Med Chem Anticancer Agents 2005;5(1):65–71. 37. Zhou XJ, Placidi M, Rahmani R. Uptake and metabolism of vinca alkaloids by freshly isolated human hepatocytes in suspension. Anticancer Res 1994;14(3A):1017–1022. 38. Roselli M, Cereda V, di Bari MG, et al. Effects of conventional therapeutic interventions on the number and function of regulatory T cells. Oncoimmunology 2013;2(10):e27025. 39. Bender RA, Castle MC, Margileth DA, et al. The pharmacokinetics of [3H]-vincristine in man. Clin Pharmacol Ther 1977;22(4):430–435. 40. Zhou XJ, Martin M, Placidi M, et al. In-vivo and in-vitro pharmacokinetics and metabolism of vinca alkaloids in rat. II. Vinblastine and vincristine. Eur J Drug Metab Pharmacokinet 1990;15(4):323–332. 41. Rowinsky EK, Noe DA, Trump DL, et al. Pharmacokinetic, bioavailability, and feasibility study of oral vinorelbine in patients with solid tumors. J Clin Oncol 1994;12(9):1754–1763. 42. Bennouna J, Delord JP, Campone M, et al. Vinflunine: a new microtubule inhibitor agent. Clin Cancer Res 2008;14(6):1625–1632. 43. Chan JD. Pharmacokinetic drug interactions of vinca alkaloids: summary of case reports. Pharmacotherapy 1998;18(6):1304–1307. 44. Tobe SW, Siu LL, Jamal SA, et al. Vinblastine and erythromycin: an unrecognized serious drug interaction. Cancer Chemother Pharmacol 1995;35(3):188–190. 45. Quasthoff S, Hartung HP. Chemotherapy-induced peripheral neuropathy. J Neurol 2002;249(1):9–17. 46. Lobert S, Vulevic B, Correia JJ. Interaction of vinca alkaloids with tubulin: a comparison of vinblastine, vincristine, and vinorelbine. Biochemistry 1996;35(21):6806–6814. 47. Schrijvers DL. Extravasation: a dreaded complication of chemotherapy. Ann Oncol 2003;14(Suppl 3):iii26–iii30. 48. Lee JJ, Kelly WK. Epothilones: tubulin polymerization as a novel target for prostate cancer therapy. Nat Clin Pract Oncol 2009;6(2):85–92.

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49. Kelly WK. Epothilones in prostate cancer. Urol Oncol 2011;29(4):358–365. 50. Kelly KR, Zollinger M, Lozac’h F, et al. Metabolism of patupilone in patients with advanced solid tumor malignancies. Invest New Drugs 2013;31(3):605–615. 51. Carter PJ, Senter PD. Antibody-drug conjugates for cancer therapy. Cancer J 2008;14(3):154–169. 52. Trail PA, Willner D, Lasch SJ, et al. Cure of xenografted human carcinomas by BR96-doxorubicin immunoconjugates. Science 1993;261(5118):212–215. 53. Lewis Phillips GD, Li G, Dugger DL, et al. Targeting HER2-positive breast cancer with trastuzumab-DM1, an antibody–cytotoxic drug conjugate. Cancer Res 2008;68(22):9280–9290. 54. Verma S, Miles D, Gianni L, et al. Trastuzumab emtansine for HER2-positive advanced breast cancer. N Engl J Med 2012;367(19):1783–1791. 55. Okeley NM, Miyamoto JB, Zhang X, et al. Intracellular activation of SGN-35, a potent anti-CD30 antibody-drug conjugate. Clin Cancer Res 2010;16(3):888–897. 56. Younes A. Brentuximab vedotin for the treatment of patients with Hodgkin lymphoma. Hematol Oncol Clin North Am 2014;28(1):27–32. 57. Cao AT, Law C-L, Gardai SJ, et al. Abstract 5588: Brentuximab vedotin-driven immunogenic cell death enhances antitumor immune responses, and is potentiated by PD1 inhibition in vivo. Cancer Res 2017;77(13 Suppl):5588. 58. Hoimes CJ, Petrylak DP, Flaig TW, et al. A phase Ib dose-escalation and dose-expansion study of enfortumab vedotin in combination with immune checkpoint inhibitor (CPI) therapy for treatment of patients with locally advanced or metastatic urothelial cancer. J Clin Oncol 2018;36:TPS532. 59. Mosquera JM, Beltran H, Park K, et al. Concurrent AURKA and MYCN gene amplifications are harbingers of lethal treatment-related neuroendocrine prostate cancer. Neoplasia 2013;15(1):1–10. 60. Ujhazy P, Stewart D. DNA repair. J Thorac Oncol 2009;4(11 Suppl 3):S1068–S1070. 61. Green MR, Woolery JE, Mahadevan D. Update on aurora kinase targeted therapeutics in oncology. Expert Opin Drug Discov 2011;6(3):291–307. 62. Gottesman MM, Fojo T, Bates SE. Multidrug resistance in cancer: role of ATP-dependent transporters. Nat Rev Cancer 2002;2(1):48–58. 63. Fojo AT, Menefee M. Microtubule targeting agents: basic mechanisms of multidrug resistance (MDR). Semin Oncol 2005;32(6 Suppl 7):S3–S8. 64. Mozzetti S, Ferlini C, Concolino P, et al. Class III beta-tubulin overexpression is a prominent mechanism of paclitaxel resistance in ovarian cancer patients. Clin Cancer Res 2005;11(1):298–305. 65. Drukman S, Kavallaris M. Microtubule alterations and resistance to tubulin-binding agents (review). Int J Oncol 2002;21(3):621–628. 66. Perez EA. Microtubule inhibitors: differentiating tubulin-inhibiting agents based on mechanisms of action, clinical activity, and resistance. Mol Cancer Ther 2009;8(8):2086–2095. 67. Verrills NM, Kavallaris M. Improving the targeting of tubulin-binding agents: lessons from drug resistance studies. Curr Pharm Des 2005;11(13):1719–1733. 68. Orr GA, Verdier-Pinard P, McDaid H, et al. Mechanisms of taxol resistance related to microtubules. Oncogene 2003;22(47):7280–7295. 69. Baquero MT, Hanna JA, Neumeister V, et al. Stathmin expression and its relationship to microtubule-associated protein tau and outcome in breast cancer. Cancer 2012;118(19):4660–4669. 70. Lee RT, Beekman KE, Hussain M, et al. A University of Chicago consortium phase II trial of SB-715992 in advanced renal cell cancer. Clin Genitourin Cancer 2008;6(1):21–24. 71. Baquero MT, Lostritto K, Gustavson MD, et al. Evaluation of prognostic and predictive value of microtubule associated protein tau in two independent cohorts. Breast Cancer Res 2011;13(5):R85. 72. Peltier AC, Russell JW. Recent advances in drug-induced neuropathies. Curr Opin Neurol 2002;15(5):633–638.

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25

Kinase Inhibitors as Anticancer Drugs Gopa Iyer, Debyani Chakravarty, and David B. Solit

INTRODUCTION Detailed mapping of the signal transduction pathways that regulate normal cellular physiology has revealed that these complex networks are commonly dysregulated in human cancer. Protein and lipid kinases serve as key regulatory nodes within signaling pathways and drugs that selectively inhibit activated kinases are now routinely used to treat a variety of cancers. In many instances, kinase inhibitors have proven to be significantly more active and less toxic than cytotoxic chemotherapies, resulting in their rapid adoption as a component of standard care. Kinases are enzymes that catalyze the transfer of a high-energy phosphate group to an effector protein or lipid substrate in a process known as phosphorylation. Phosporylation can alter the activity of a target substrate through several mechanisms including direct modulation of protein enzymatic activity, creation of docking sites that promote protein–protein interactions, or by altering stability or subcellular localization. The phosphorylation or dephosphorylation of signaling intermediaries play key regulatory roles in the transmission of signals from the cell surface to the nucleus. Dysregulation of these cell signaling networks can lead to uncontrolled cellular proliferation, enhanced cellular survival and motility, and other hallmarks of the cancer phenotype.1 Kinases are subclassified based on whether they phosphorylate proteins or lipids, and protein kinases are further classified based on the specific amino acid phosphorylated (typically serine/threonine or tyrosine in eukaryotic cells). Kinases are also subclassified according to their cellular localization. Receptor tyrosine kinases serve as cell surface receptors for growth factors, cytokines, or hormones. Many nonreceptor tyrosine kinases, such as Src, are localized in the cytoplasm, whereas others are localized in the nucleus. All protein kinases have a kinase domain, the structurally conserved catalytic region responsible for transferring the high-energy phosphate group from an adenosine triphosphate (ATP) molecule to the kinase substrate. As outlined in detail in the following text and in several of the disease-specific chapters, several small molecules and monoclonal antibodies, which inhibit kinases through different mechanisms, have received U.S. Food and Drug Administration (FDA) approval for use in a wide variety of cancer indications. Small-molecule kinase inhibitors often bind to or near the ATP binding site of the target kinase either in its active conformation (type I kinase inhibitors), or in its inactive conformation (type II kinase inhibitors). Notable examples include vemurafenib, a type I RAF kinase inhibitor, and imatinib, a type II inhibitor of the ABL, KIT, and platelet-derived growth factor receptor (PDGFR) kinases. Additionally, monoclonal antibodies that bind to transmembrane receptor tyrosine kinases have proven to be effective cancer therapies in select cancer types. These therapeutic antibodies can induce antitumor effects by blocking ligand binding or receptor dimerization, by inducing receptor internalization, or by immunologic mechanisms. Examples include the epidermal growth factor receptor (EGFR) monoclonal antibody cetuximab and the human epidermal growth factor receptor 2 (HER2)-targeting antibody trastuzumab. This chapter summarizes key landmark events over the past several decades that witnessed the identification of dysregulated kinases as potential therapeutic targets followed by the development of highly selective inhibitors of these mutated oncogenes as anticancer drugs. The chapter has been structured to provide insights into lessons learned during the development of this drug class and how such knowledge is currently being applied to develop more effective and less toxic kinase inhibitors and combinatorial regimens. Figure 25.1 provides an overview of the mitogen-activated protein kinase (MAPK) and phosphatidylinositol 3-kinase (PI3K)/Akt/mammalian target of rapamycin (mTOR) signaling pathways and includes clinically relevant pathway inhibitors. Although patients can exhibit dramatic responses to kinase inhibitors, intrinsic and acquired resistance are major clinical challenges that limit the effectiveness of this drug class. Functional studies have identified a variety of drug resistance mechanisms, and in some cases, bedside-to-bench translational studies have guided the

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development of second-generation inhibitors with enhanced or broader clinical activity. Resistance mechanisms typically fall into one of two general classes: (1) secondary mutations in the kinase that prevent or alter drug binding and (2) co-mutations or adaptive changes involving parallel signaling pathways that reduce dependence on the target kinase (often referred to as “oncogenic bypass”). These resistance mechanisms can exist prior to drug treatment and serve as the mechanistic basis for intrinsic drug resistance or arise during drug treatment and mediate acquired resistance. An example of a secondary mutation resistance mechanism is also the most common mechanism of acquired resistance to erlotinib, an EGFR tyrosine kinase inhibitor FDA-approved for the treatment of patients with non–small-cell lung cancer (NSCLC). Following prolonged exposure to EGFR tyrosine kinase inhibitors, approximately half of patients with EGFR L858R or EGFR exon 19 deletion–mutant NSCLC acquire an EGFR secondary site T790M gatekeeper mutation. Identification of this resistance mechanism in tumors collected at the time of disease progression on the EGFR inhibitors erlotinib and gefitinib led to the development of osimertinib, a third-generation EGFR kinase inhibitor with clinical activity in erlotinib-resistant T790M-mutant lung cancers. Amplification of the mesenchymal-epithelial transition (MET) receptor tyrosine kinase has been shown to be an alternative mechanism of resistance to EGFR kinase inhibitors. MET can activate many of the same downstream signaling cascades as EGFR, and thus, MET activation can function as a “bypass” mechanism, reducing dependence of EGFR-mutant lung cancer cells on EGFR activation. The identification of MET amplification as a recurrent mechanism of EGFR kinase inhibitor resistance is the rationale for clinical trials testing combinations of EGFR and MET inhibitors.

Figure 25.1 The mitogen-activated protein kinase and phosphatidylinositol 3-kinase (PI3K) signaling pathways. Major signaling nodes are shown as well as select kinase inhibitors and antireceptor antibodies. Dotted green lines represent negative regulation of the respective pathways. EGF, Epidermal Growth Factor; EGFR, EGF receptor; SCF, Stem Cell Factor; PIP2, Phosphatidylinositol (4,5)-bisphosphate; PIP3, Phosphatidylinositol (3,4,5)-trisphosphate; IRS1, Insulin Receptor Substrate 1; GDP, Guanosine diphosphate; GTP, Guanosine triphosphate; GRB2, Growth Factor Receptor Bound Protein 2; NF1, Neurofibromin 1; PDK1, 3-phosphoinositidedependent kinase 1; PRAS40, Proline-rich AKT1 substrate; RHEB, Ras homolog enriched in brain; Shc, Shc-transforming protein 1; Sos, Son of Sevenless; p90RSK, p90 ribosomal S6 kinase; 4EBP1, 4E-binding protein 1.

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As kinase inhibitors target signaling pathways that drive malignant transformation, it is not surprising that their activity is often limited to patients in whom activation of the target kinase is required for tumor maintenance and/or cancer progression. Furthermore, as pathway activation is often the result of mutation, translocation, or amplification of the genes that encode kinases, the clinical development of selective kinase inhibitors is often closely tied to the development of a companion diagnostic test that can identify oncogenic alterations that serve as predictive biomarkers of drug response. For example, vemurafenib only inhibits the growth of tumor cells containing codon 600 BRAF mutations. Vemurafenib not only lacks antitumor activity in BRAF wildtype tumors but also accelerates tumor growth in such patients.2 Thus, a key hurdle to the clinical development of vemurafenib as an anticancer drug was the development of diagnostic platforms that could rapidly and with high sensitivity and specificity prospectively identify BRAF V600 mutations in cancer patients. Early companion diagnostic tests were based on polymerase chain reaction (PCR), mass spectrometry, or Sanger sequencing methodologies and were typically limited to the identification of highly recurrent alterations involving a single allele or those within a single exon or gene. Newer next-generation sequencing platforms can now robustly detect mutations and/or translocations in hundreds of cancer-associated genes using readily available formalin-fixed paraffin-embedded tumor tissue. Analysis of circulating DNA in plasma is also emerging as a novel and potentially less invasive method to detect and analyze tumor-derived DNA for mutations and translocations that are predictive biomarkers of kinase inhibitor response. This “liquid biopsy” approach circumvents the need for invasive biopsies in order to collect tumor tissue for molecular analysis. It can also facilitate the identification of emerging resistance mutations through serial sampling of plasma in patients receiving kinase inhibitors, which may allow for the early use of combinatorial therapies that prevent or delay the emergence of drug-resistant cancer cells. With the rapid shift from single analyte tests to larger gene panels, interpreting the clinical significance of the increasing number of mutations identified through prospective, real-time tumor sequencing has become a major challenge for practicing oncologists. Despite extensive efforts over the past 30 years to biologically characterize the most highly recurrent mutations and translocations found in human cancers, only a minority of the somatic and germline alterations identified by whole-genome, whole-exome, or large gene panel next-generation sequencing are likely to be driver mutations and thus possible drug targets.3 Although all highly recurrent mutations are probably functional, most somatic mutations are rare in the population and are likely passenger events with little or no impact on prognosis or response to therapy. Such low-frequency alterations make up the “long-tail” of the plot of mutations distributed by frequency.4 Distinguishing which of these mutations in the long-tail of the frequency distribution are drivers and which are passengers is a major hurdle to the broader adoption of precision medicine paradigms. Currently, there is no comprehensive resource that physicians can use to determine whether individual mutant alleles identified by tumor genomic profiling are clinically actionable, defined as an alteration that is predictive of clinical benefit to an available therapy. As an additional layer of complexity, not all mutant alleles within the same gene are functionally similar and different mutations in the same gene may have different therapeutic implications. For example, EGFR L858R and EGFR exon 19 deletions are both associated with sensitivity of NSCLC patients to the EGFR kinase inhibitor erlotinib. Activating EGFR exon 20 insertions are, however, erlotinib resistant. In this case, the variability in drug sensitivity can be attributed to differences in the binding affinity of erlotinib for different EGFR mutants. Individual mutations may also have different therapeutic implications in different cancer types. As an example, vemurafenib is highly active in melanoma patients with BRAF V600E mutations but is largely ineffective as monotherapy in BRAF V600E–mutant colorectal cancer patients. The rapid expansion in the number of validated kinase targets thus requires that clinicians be familiar with the biologic differences among individual mutant alleles as well as differences in the therapeutic relevance of individual gene mutations in the context of diverse cancer types. Furthermore, oncologists are frequently faced with the dilemma of patients whose tumors contain more than one targetable mutation and thus multiple FDAapproved or investigational drug choices, leading to ambiguity about the optimal treatment regimen. To address this clinical challenge, several knowledge bases have been created, including OncoKB (www.oncokb.org),5 MyCancerGenome (mycancergenome.org), Personalized Cancer Therapy (https://pct.mdanderson.org/), and Clinical Interpretations of Variants in Cancer (CIViC; civic.genome.wustl.edu),6 to aid clinicians in identifying those mutations in tumor-sequencing reports that are of clinical significance and should be used to guide therapeutic decision making. As new laboratory and clinical data regarding FDA-approved and investigational therapies are generated, these databases must be continually updated to reflect practice-changing research findings. As a general rule, these clinical support tools utilize levels of clinical evidence to classify a given mutation as a

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predictive biomarker of drug response. As an example, in the OncoKB database, a level of evidence classification system was developed that incorporates the known biologic and clinical significance of individual mutant alleles as a function of tumor site of origin, recognizing that the effects of targeted inhibitors can vary by tumor lineage (Table 25.1). OncoKB level 1 mutations represent established FDA-recognized biomarkers of response to an FDA-approved drug being used in the FDA-approved cancer indication. Level 2 mutations are those that are considered standard of care biomarkers predictive of response to an FDA-approved drug based on an expert panel recommendation when used off-label in a particular cancer type. In the latter instance, disease expert panels such as those convened by the National Comprehensive Cancer Network (NCCN) may have designated the mutation as a predictive biomarker of drug response that should be used to guide treatment selection, but the drug label does not reflect its adoption as part of standard management. As anticancer drugs initially developed for common cancers such as breast and lung carcinomas are often repurposed for use in rarer cancer types, such off-label use of kinase inhibitors is likely to become more common in the future. Level 3 alterations are those for which there is compelling clinical data demonstrating that the mutation is a predictive biomarker of sensitivity to an FDAapproved or investigational drug; however, the data are not yet sufficiently robust to consider use of the drug in this indication as standard therapy. As level 3 biomarker- therapy associations are not yet considered standard of care, patients with tumors that harbor these alterations may have difficulty obtaining such drugs due to high drug costs and lack of insurance coverage for their cancer type or because the available clinical trial options are not open to or practical for the patient. Finally, level 4 alterations are those for which there are laboratory data but not yet compelling clinical data in cancer patients indicating that the alteration may be a biomarker of drug sensitivity. Level 3 and 4 alterations are often part of the eligibility criteria for actively accruing clinical trials. Finally, mutated oncogenes and tumor suppressors may also serve as biomarkers of drug resistance. As examples, colorectal cancer patients whose tumors harbor KRAS or BRAF mutations do not benefit from EGFR-targeted therapies, and cancers with RB1 mutation/deletion are resistant to cyclin-dependent kinase 4 and 6 (CDK4 and CDK6) inhibitors. In summary, extensive efforts are ongoing to determine the biologic and clinical significance of both recurrent and private mutations identified by prospective and retrospective tumor genomic studies. These clinical and laboratory efforts will need to be coordinated with the development of informatics-based support tools to aid clinicians in interpreting a given patient’s tumor mutational data with the goal of using real-time tumor molecular profiling to guide the selection of the most optimal treatment approach for each patient. As many of the mutations currently identified by tumor genomic profiling may be targetable through the off-label use of FDA-approved or investigational drugs, realizing the full potential of precision medicine in patients with rare cancer types or uncommon mutations in common cancer types will require novel approaches to providing drug access (e.g., basket studies). Moreover, tumor response registries, such as the American Association of Cancer Research Project Genomics Evidence Neoplasia Information Exchange (GENIE) initiative, which seek to pool treatment response data from hundreds of thousands of patients, will serve as powerful tools to explore the clinical relevance of rare mutant alleles in common cancer types and more common mutations in rare cancers (Fig. 25.2).7 TABLE 25.1

OncoKB Level 1 Genes and Alterations Gene

Alteration(s)

Cancer Type(s)

Drug(s)

ABL1

BCR-ABL1 fusion

ALL, CML

Imatinib, nilotinib, dasatinib

ALK

Fusions

NSCLC

Crizotinib, ceritinib, alectinib, brigatinib

BRAF

V600 mutations

Melanoma

Vemurafenib, dabrafenib, trametinib, dabrafenib + trametinib, cobimetinib + vemurafenib

BRCA1

Inactivating mutations

Ovarian cancer

Rucaparib, niraparib

BRCA2

Inactivating mutations

Ovarian cancer

Rucaparib, niraparib

EGFR

Exon 19 deletions, L858R, G719, S768I, Exon 19 insertions, L861Q/R, E709K, L833V, L747P, A763_Y764insFQEA E709_T710delinsD EGFR-KDD

NSCLC

Erlotinib, afatinib, gefitinib

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EGFR

T790M

NSCLC

Osimertinib

ERBB2

Amplification

Breast cancer

Trastuzumab, ado-trastuzumab emtansine, pertuzumab, lapatinib

ERBB2

Amplification

Esophagogastric cancer

Trastuzumab

IDH2

Oncogenic mutations

AML

Enasidenib

KIT

Exon 9, 11, 17 mutations, T670I, V654A

GIST

Imatinib, sunitinib, regorafenib

MMR-d

MSI+

Solid tumors

Pembrolizumab

PDGFRA

FIP1L1-PDGFRA

Leukemia

Imatinib

PDGFRA

Fusions

MDS/MPN

Imatinib

PDGFRB

Fusions

MDS/MPN

Imatinib

PDGFRB

Fusions

DFSP

Imatinib

ROS1 Fusions NSCLC Crizotinib ALL, acute lymphoblastic leukemia; CML, chronic myelogenous leukemia; ALK, anaplastic lymphoma kinase; NSCLC, non–smallcell lung cancer; EGFR, epidermal growth factor receptor; AML, acute myeloid leukemia; GIST, gastrointestinal stromal tumor; MMR-d, mismatch repair-deficient; MSI, microsatellite instability; PDGFR, platelet-derived growth factor receptor; MDS, myelodysplasia; MPN, myeloproliferative neoplasm; DFSP, dermatofibrosarcoma protuberans.

Figure 25.2 Clinical actionability of genetic alterations. Tumor types are shown by decreasing overall frequency of actionability. Actionability was defined by the union of three knowledge bases: My Cancer Genome (http://mycancergenome.org), OncoKB (http://oncokb.org), and the Personalized Cancer Therapy knowledge base (http://pct.mdanderson.org). For each tumor sample, the highest level of actionability of any variant was considered. Only tumor types with 100 or more samples were included in this analysis. CNS, central nervous system. (Reproduced from American Association for Cancer Research Project GENIE Consortium. AACR Project GENIE: powering precision medicine through an international consortium. Cancer Discov 2017;7[8]:818–831.)

VALIDATING MUTATED KINASES AS CANCER DRUG TARGETS—THE DEVELOPMENT OF IMATINIB FOR PATIENTS WITH CHRONIC MYELOGENOUS LEUKEMIA AND GASTROINTESTINAL STROMAL TUMORS

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In 1960, Nowell and Hungerford8 reported the presence of an abnormally small chromosome in the leukemic cells of patients with chronic myelogenous leukemia (CML). Subsequent studies revealed that this abnormal cytogenetic finding, later designated the Philadelphia (Ph) chromosome given its discovery at the University of Pennsylvania, represented a reciprocal translocation between the breakpoint cluster (BCR) located on chromosome 22 and the ABL1 protooncogene on chromosome 9. ABL1 had initially been isolated from the genome of the Abelson murine leukemia virus (A-MuLV), where it was found to encode a transforming protein (p160v-Abl) with tyrosine-specific protein kinase activity. Biochemical studies later confirmed that the p210Bcr-Abl kinase fusion in patients with Ph chromosome–positive CML possessed constitutive Abl kinase activation, and its expression in mice was sufficient to induce a disease resembling CML.9 Importantly, Bcr-Abl kinase activity is required for ongoing cellular proliferation and survival of CML cells, a phenomenon known as “oncogene addiction.” Thus, laboratory and clinical studies exploring the pathogenesis of CML extending over four decades led to the identification of the Bcr-Abl kinase fusion as a therapeutic target and prompted efforts to develop Abl kinase inhibitors for the treatment of Ph chromosome–positive leukemias. The development of imatinib followed a rational drug design paradigm where an initial lead compound was identified through a large compound library screen followed by structure function–based studies to identify a potent, selective, and orally bioavailable drug candidate. The resulting compound developed by scientists at CibaGeigy (later through acquisition Novartis), initially designated as STI571 and subsequently named imatinib, was a selective inhibitor of the ABL, PDGFRα, PDGFRβ, and KIT protein tyrosine kinases. Treatment with imatinib dramatically alters the natural history of CML, converting it from a near universally lethal condition to a chronic disease. Highlighting the clinical impact of imatinib, a retrospective survival analysis of 1,569 CML patients across clinical disease states showed that 8-year survival was 5 years and ongoing) were observed with long-term follow-up of both treatment-naïve and previously chemotherapy-treated patients. A phase II single-arm study of ibrutinib in relapsed/refractory CLL patients with 17p deletion (loss of TP53), a marker of

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significantly worse prognosis, also reported significant responses to ibrutinib monotherapy.86 In summary, the profound clinical activity of ibrutinib in CLL underscores the lineage dependence of CLL cells on B-cell signaling mediated by BTK for survival, a characteristic that can now be exploited therapeutically with a kinase inhibitor. Further work is now being performed to define the efficacy of ibrutinib in combination with other active agents in CLL. In patients with mantle cell lymphoma, a highly aggressive non-Hodgkin’s lymphoma, ibrutinib demonstrated an objective response rate of 68% with a 21% complete response rate, a median duration of response of 17.5 months, and an 18-month median overall survival rate of 58%.87 Although these data led to the FDA approval of ibrutinib for mantle cell lymphoma patients who had progressed on at least one prior treatment, as is observed with other targeted therapies, responses are often short-lived, with over half of patients progressing within a year and up to one-third exhibiting primary resistance.88 Mantle cell lymphomas overexpress cyclin D1 due to a translocation between chromosomes 11 and 14 (t11;14). The CDK4/6 inhibitor palbociclib discussed previously has modest clinical activity as monotherapy in mantle cell lymphoma: a phase I pilot study in 17 heavily pretreated patients demonstrated an 18% overall response rate, including 1 complete and 2 partial responses.89 In laboratory studies, CDK4 inhibition has been shown to resensitize BTK wildtype, ibrutinib-resistant cells to ibrutinib. These data prompted a clinical trial of the palbocilib-ibrutinib combination, which reported a complete response rate of 44% with the combination with an acceptable toxicity profile.90 Further testing of this combination which targets both a lineage dependence vulnerability (BTK) and an oncogenic fusion event (cyclin D1 overexpression due to a t(11;14)) is ongoing.

A POTENTIAL PAN CANCER DRUG TARGET—TRK INHIBITORS The NTRK gene family includes three receptor tyrosine kinases (TRKA, TRKB, and TRKC encoded by the NTRK1, NTRK2, and NTRK3 genes, respectively) which are activated upon binding of distinct neurotrophin ligands. TRK fusions are present at low frequency (typically 10-fold more potent at inducing tumor cell death when cells were exposed to drug for a 1-hour pulse, which mimics the pharmacokinetics of both compounds.32 MLN2238 (the active agent of ixazomib) was active in the same mouse

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models of human tumors as bortezomib but demonstrated greater levels of proteasome inhibition in the tumors.33 Oprozomib is 10-fold less potent than carfilzomib in proteasome activity assays but showed similar antitumor activity in mouse tumor models.34,35 Marizomib displayed greater potency against the non-CT-L–active sites of the proteasome than bortezomib.36 Interestingly, this agent synergized with bortezomib in killing tumor cells in vitro.37 All of the second-generation inhibitors have shown activity in tumor cells made resistant to bortezomib and/or MM cells isolated from patients who experienced relapse after bortezomib-based therapies34,38–41 The inhibition of tumor cells with PIs induces cell death via the induction of apoptosis through caspase activation.10 Although the mechanism underlying the induction of cell death remains to be fully elucidated, extensive research suggests a complex interplay of multiple pathways. PIs have been shown to affect the half-life of the BH3-only members of the Bcl-2 family, specifically BH3-interacting domain death agonist (Bid) and Bcl-2 interacting killer (Bik).42 Moreover the BH3-only protein NOXA is upregulated at the transcription level by PIs.43–47 Proteasome inhibition also upregulates the expression of several key cell-cycle checkpoint proteins that include p53 (an inducer of G0/G1 cell-cycle arrest through accumulation of the cyclin-dependent kinase [CDK] inhibitor p27); the CDK inhibitor p21; mammalian cyclins A, B, D, and E; and transcription factors E2F and Rb.48,49 The transcription factor nuclear factor kappa B (NF-κB), an important regulator of cell survival and cytokine/growth factor production,50 is also affected by proteasome inhibition in multiple ways. The net effect on NF-κB signaling is not consistent across various assays and cell lines, and its relative importance in the antitumor effects of PIs remains unclear. Although it is interesting to note that patients whose myeloma harbors NF-κB– activating mutations (1 line of therapy)

Relapsed myeloma (1–3 lines of therapy)

Relapsed myeloma (1–3 lines of therapy)

TTP

PFS

PFS

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12; placebo days 1, 3, 5, 8, 10, and 12 every 28 d CASTOR trial, Palumbo et al. (2016)66 (phase III, N = 498)

IFM trial, Moreau et al. (2011)61 (phase III, N = 222)

Relapsed myeloma (1–3 lines of therapy)

Relapsed myeloma (1–3 lines of therapy)

PFS

Noninferiority of SC BTZ in terms of ORRa

VD + Dara (251)

Daratumumab 16 mg/kg IV on days 1, 8, and 15 in cycles 1–3; every 3 wk during cycles 4–8; and every 4 wk thereafter; BTZ 1.3 mg/m2 on days 1, 4, 8, and 11 of cycles 1–8; dexamethasone 20 mg on days 1, 2, 4, 5, 8, 9, 11, and 12 every 21 d

82.9% (CR, 46%)

65.4% (1-y PFS)



Thrombocytopenia (45.3%), anemia (14.4%), neutropenia (12.8%), PN (4.5%), fatigue (4.5%), hypertension (6.6%)

VD (247)

BTZ 1.3 mg/m2 on days 1, 4, 8, and 11 of cycles 1–8; dexamethasone 20 mg on days 1, 2, 4, 5, 8, 9, 11, and 12 every 21 d

63.2% (CR, 21%) P < .001

28.8% (1-y PFS) P < .001



Thrombocytopenia (33%), anemia (16%), neutropenia (4.2%), PN (6.8 %), fatigue (3.4%), hypertension (0.8%)

BTZ SC (148)

Bortezomib 1.3 mg/m2 SC on days 1, 4, 8, and 11 of 21-d cycles

42% (CR/nCR, 12%)

10.4

72.6% (1-y OS)

Neutropenia (18%), thrombocytopenia (13%), anemia (12%), PN (5%), pneumonia (5%)

BTZ IV (74)

Bortezomib 1.3 mg/m2 IV on days 1, 4, 8, and 11 of 21-d cycles

42% (CR/nCR, 14%) P = .002a

9.4 P = .387

76.7% (1-y OS) P = .54

Thrombocytopenia (19%), neutropenia (18%), PN (15%), anemia (8%), pneumonia (8%)

Richardson et al. (2010)73 (phase II, N = 68)

Newly diagnosed, transplant eligible



RVD

Bortezomib 1.3 mg/m2 IV on days 1, 4, 8, and 11; lenalidomide 25 mg PO days 1–14; and dexamethasone 20 mg on days 1, 2, 4, 5, 8, and 9 every 21 d

100% (≥VGPR, 67%)

75% (18mo OS)

97% (18-mo OS)

Neutropenia (10%), thrombocytopenia (7%), thrombosis (5%), PN (7%)

IFM 2005-01 trial, Harousseau et al. (2010)78 (phase III, N = 482)

Newly diagnosed, transplant eligible

Postinduction CR/nCR rate

VAD (121)

Vincristine 0.4 mg IV daily; doxorubicin 9 mg/m2 continuous infusion on days 1–4; and dexamethasone 40 mg PO on days 1–4, 9–12, and 17–20 of cycles 1 and 2 of 28-d cycles

62.8% (nCR/CR postinduction, 6.4%)

36

81.4% (3-y OS)

Infections (12.1%), neutropenia (10%), anemia (8.8%), thrombosis (5.4%), thrombocytopenia (1.3%), PN (2.1%)

VAD + DCEP (121)

VAD + dexamethasone 40 mg on days 1– 4 of two 4-wk cycles; cyclophosphamide 400 mg/m2; etoposide 40 mg/m2; and cisplatin 15 mg/m2/d









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continuous infusion on days 1–4 VD (121)

BTZ 1.3 mg/m2 on days 1, 4, 8, and 11 every 21 d and dexamethasone 40 mg on days 1– 4 of all cycles and days 9–12 of cycles 1 and 2

78.5% (nCR/CR postinduction, 14.8%) P < .05

29.7 P = .064

77.4% (3-y OS)

Infections (8.8%), PN (7.1%), neutropenia (5%), anemia (4.2%), thrombocytopenia (2.9%), thrombosis (1.7%)







VD + DCEP (119)

VD + dexamethasone 40 mg on days 1– 4 of two 4-wk cycles; etoposide 40 mg/m2; cyclophosphamide 400 mg/m2; and cisplatin 15 mg/m2/d continuous infusion on days 1–4









GIMEMA trial, Cavo et al. (2010)137 (phase III, N = 480)

Newly diagnosed, transplant eligible

CR rate postinduction

VTD (241)

Thalidomide 100 mg daily × 14 d followed by 200 mg daily after; bortezomib 1.3 mg/m2 on days 1, 4, 8, and 11; and dexamethasone 40 mg daily on 8 out of first 12 d × 3 cycles

93% (CR/nCR, 31%)

68% (3-y PFS)

86% (3y OS)

Skin rash (10%), PN (10%), constipation (4%), thrombosis (3%), infections (3%)

TD (239)

Thalidomide 100 mg daily × 14 d followed by 200 mg daily after and dexamethasone 40 mg daily on 8 out of first 12 d × 3 cycles

79% (CR/nCR, 31%) P < .0001

56% (3-y PFS) P = .005

84% (3y OS) P = .3

Thrombosis (5%), infections (5%), constipation (3%), skin rash (2%), PN (2%)

VBMCP/VBAD/B (129)

VBMCP/VBAD/B: 4 cycles of alternating VBMCP/VBAD followed by 2 cycles bortezomib 1.3 mg/m2 on days 1, 4, 8, and 11 of 21-d cycles

Postinduction → post-ASCT (CR, 21% → 38%)

35.3

70% (4y OS)

Neutropenia (22%), infections (15%), PN (9%), gastrointestinal (8%), thrombocytopenia (6%), thrombosis (4%)

TD (127)

Thalidomide 200 mg daily (escalating doses in first cycle) and dexamethasone 40 mg on days 1– 4 and 9–13 for 24 wk

Postinduction → post-ASCT (CR, 14% → 24%)

28.2

65% (4y OS)

Gastrointestinal (25%), infections (16%), neutropenia (14%), thrombocytopenia (5%), thrombosis (5%), PN (5%)

VTD (130)

BTZ 1.3 mg/m2 on days 1, 4, 8, and 11; thalidomide 200 mg daily (escalating doses in first cycle); and dexamethasone 40 mg on days 1– 4 and 9–13 for 24 wk

Postinduction → post-ASCT (CR, 35% → 46%)

56.2

74% (4y OS)

Infections (21%), PN (14%), thrombosis (12%), neutropenia (10%), thrombocytopenia (8%), gastrointestinal (8%)

PETHEMA trial, Rosiñol et al. (2012)77 (phase III, N = 386)

Newly diagnosed, transplant eligible

CR rate postinduction and postASCT

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HOVON65/GMMGHD4 trial, Sonneveld et al. (2012)79 (phase III, N = 827)

VISTA trial, San Miguel et al. (2008)80,81 (phase III, N = 682)

SWOG S0777 trial, Durie et al. (2016)74 (phase III, N = 525)

Newly diagnosed, transplant eligible

Newly diagnosed, transplant ineligible

Newly diagnosed, transplant ineligible

PFS

TTP

PFS

VAD (414)

Vincristine 0.4 mg IV daily; doxorubicin 9 mg/m2 continuous infusion on days 1–4; and dexamethasone 40 mg on days 1– 4, 9–12, and 17– 20 every 28 d

Postinduction → post-ASCT (CR/nCR, 5% → 15%)

28

55% (5y OS)

Infections (21%), PN (10%), gastrointestinal (7%), anemia (7%), thrombocytopenia (5%), thrombosis (3%)

PAD (413)

BTZ 1.3 mg/m2 on days 1, 4, 8, and 11; doxorubicin 9 mg/m2 continuous infusion on days 1–4; and dexamethasone 40 mg on days 1– 4, 9–12, and 17– 20 every 28 d

Postinduction → post-ASCT (CR/nCR, 11% → 31%) P < .05

35 P < .002

61% (5y OS) P = .11

Infections (26%), PN (24%), gastrointestinal (11%), thrombocytopenia (10%), anemia (8%), thrombosis (4%)

VMP (344)

BTZ 1.3 mg/m2 on days 1, 4, 8, 11, 22, 25, 29, and 32 every 42 d in cycles 1–4 and days 1, 8, 22, and 29 during cycles 5–9; mephalan 9 mg/m2 and prednisone 60 mg/m2 on days 1– 4 every 42 d × 9cycles

71% (CR, 30%)

24

HR 0.61 favoring VMP, P = .008 (median followup, 16.3 mo)

Neutropenia (30%), thrombocytopenia (20%), anemia (16%), PN (13%), diarrhea (7%), fatigue (7%)

MP (338)

Melphalan 9 mg/m2 and prednisone 60 mg/m2 on days 1– 4 every 42 d × 9 cycles

35% (CR, 4%) P < .001

16.6 P < .001



Neutropenia (23%), anemia (20%), PN (5%), thrombocytopenia (16%), fatigue (2%), diarrhea (1%)

VRD (242)

BTZ 1.3 mg/m2 IV on days 1, 4, 8, and 11 of 21-d cycles × 8 cycles; lenalidomide 25 mg PO on days 1– 21; dexamethasone 40 mg on days 1, 8, 15, and 22 every 28 d

81.5% (CR, 15.7%)

43

75

Lymphopenia (23%), PN (23%), neutropenia (19%), thrombosis (8%), SPM (3%)

RD (230)

Lenalidomide 25 mg PO on days 1– 21; dexamethasone 40 mg on days 1, 8, 15, and 22 every 28 d

71.5% (CR, 8.4%) P = .02

31 P < .003

63 P < .025

Lymphopenia (18%), neutropenia (21%), thrombosis (9%), SPM (4%), PN (3%)

CFZ + RD (396)

CFZ IV on days 1, 2, 8, 9, 15, and 16 (starting dose, 20 mg/m2 on days 1 and 2 of cycle 1; 27 mg/m2 thereafter) during cycles 1–12 and on days 1, 2, 15, and 16 during

87.1% (CR, 31.8%)

26.3

73.3% (2-y OS)

Neutropenia (29.6%), thrombocytopenia (16.6%), anemia (17.9%), hypertension (4.3%), dyspnea (2.8%), diarrhea (3.8%), fatigue (7.7%), ARF (3.3%)

Carfilzomib-based Trials ASPIRE trial, Stewart et al. (2015)87 (phase III, N = 792)

Relapsed myeloma (1–3 lines of therapy)

PFS

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cycles 13–18; lenalidomide 25 mg PO on days 1– 21; and dexamethasone 40 mg PO on days 1, 8, 15, and 22 every 28 d





RD (396)

Lenalidomide 25 mg PO on days 1– 21 and dexamethasone 40 mg PO on days 1, 8, 15, and 22 every 28 d

66.7% (CR, 9.3%) P < .001

17.6 P = .0001

65% (2y OS) P = .04

Neutropenia (26.5%), thrombocytopenia (12.3%), anemia (17.2%), hypertension (1.8%), dyspnea (1.8%), diarrhea (4.1%), fatigue (6.4%), ARF (3.1%)

ENDEAVOR trial, Dimopoulos et al. (2016)90 (phase III, N = 929)

Relapsed myeloma (1–3 lines of therapy)

PFS

CFZ + Dex (464)

CFZ IV on days 1, 2, 8, 9, 15, and 16 (starting dose, 20 mg/m2 on days 1 and 2 of cycle 1; 56 mg/m2 thereafter) and dexamethasone 20 mg PO on days 1, 2, 8, 9, 15, 16, 22, and 23 every 28 d

77% (CR, 13%)

18.7

47.6

Neutropenia (29.6%), anemia (16%), hypertension (15%), thrombocytopenia (9%), fatigue (7%), dyspnea (6%), diarrhea (4%), PN (1%)

VD (465)

BTZ 1.3 mg/m2 IV/SC on days 1, 4, 8, and 11 and dexamethasone 20 mg PO on days 1, 2, 4, 5, 8, 9, 11, and 12 every 21 d

63% (CR, 6%) P < .0001

9.4 P < .0001

40 P = .01

Neutropenia (29.6%), anemia (10%), thrombocytopenia (9%), diarrhea (9%), fatigue (8%), PN (6%), hypertension (3%), dyspnea (2%)

CFZ

CFZ IV on days 1, 2, 8, 9, 15, and 16 (starting dose, 20 mg/m2 on days 1 and 2 of cycle 1; 27 mg/m2 thereafter) during cycles 1–9 and on days 1, 2, 15, and 16 during cycles 10+ every 28 d

19.1%

3.7

10.2

Neutropenia (8%), thrombocytopenia (24%), anemia (25%), pneumonia (6%), ARF (8%)

Dex (± cyclophosphamide)

84 mg of dexamethasone or equivalent per cycle with optional cyclophosphamide 50 mg PO daily every 28 d

11.4%

3.3 P = .247

10 P = .417

Neutropenia (12%), thrombocytopenia (22%), anemia (31%), pneumonia (12%), ARF (3%)

Ixa + RD (360)

Ixazomib 4 mg PO on days 1, 8, and 15; lenalidomide PO on days 1–21; and dexamethasone 40 mg PO on days 1, 8, 15, and 22 every 28 d

78.3% (CR, 14%)

20.6



Neutropenia (23%), thrombocytopenia (19%), anemia (9%), rash (7%), diarrhea (6%), fatigue (4%)

Placebo + RD

Placebo PO on

71.5% (CR,

14.7



Neutropenia

FOCUS trial, Hajek et al. (2017)91 (phase III, N = 315)

Relapsed/refractory myeloma

OS

Ixazomib-based Trials TOURMALINEMM1 trial, Moreau et al. (2016)96 (phase III, N = 722)

Relapsed myeloma (1–3 lines of therapy)

PFS

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(362)

days 1, 8, and 15; lenalidomide PO on days 1–21; and dexamethasone 40 mg PO on days 1, 8, 15, and 22 every 28 d

8%) P = .04

(24%), thrombocytopenia (9%), anemia (13%), rash (4%), diarrhea (3%), fatigue (3%)

a

Non-inferiority. ORR, overall response rate; PFS, progression-free survival; TTP, time to progression; OS, overall survival; APEX, Assessment of Proteasome Inhibition for Extending Remissions; BTZ, bortezomib; IV, intravenous; PN, peripheral neuropathy; HiDex, high-dose dexamethasone; PO, orally; PLD, pegylated liposomal doxorubicin; Vori, vorinostat; VD, bortezomib and dexamethasone; Pano, panobinostat; Dara, daratumumab; CR, complete response; IFM, Intergroupe Francophone du Myélome; SC, subcutaneous; RVD, lenalidomide, bortezomib, and dexamethasone; VGPR, very good partial response; IFM 2005-01, Intergroupe Francophone du Myélome 2005-01; VAD, vincristine, doxorubicin, and dexamethasone; DCEP, dexamethasone, cyclophosphamide, etoposide, and cisplatin; VTD, bortezomib, thalidomide, and dexamethasone; TD, thalidomide and dexamethasone; PETHEMA, Programa para el Estudio y la Terapéutica de las Hemopatías Malignas ASCT, autologous stem cell transplantation; VBMCP/VBAD/B, alternating vincristine, carmustine, melphalan, cyclophosphamide, and prednisone with vincristine, carmustine, doxorubicin, and dexamethasone, followed by bortezomib; PAD, bortezomib, doxorubicin, and dexamethasone; VISTA, Velcade as Initial Standard Therapy in Multiple Myeloma: Assessment with Melphalan and Prednisone; VMP, bortezomib, melphalan, and prednisone; HR, hazard ratio; MP, melphalan and prednisone; VRD, bortezomib, lenalidomide, and dexamethasonel; SPM, secondary primary malignancy; RD, lenalidomide and dexamethasone; CFZ, carfilzomib; ARF, acute renal failure; Dex, dexamethasone; Ixa, ixazomib.

Carfilzomib Early-phase trials of carfilzomib targeting B-cell malignancies used two dosing schedules: (1) 20 mg/m2 daily IV boluses for 5 consecutive days, followed by 9 days of rest, or (2) 20 mg/m2 on 2 days a week for 3 consecutive weeks (days 1, 2, 8, 9, 15, and 16), followed by 12 days of recovery. Both approaches resulted in substantial inhibition of proteasome activity.82,83 Hematologic toxicities were the most frequent AEs, observed along with transient, noncumulative elevations in serum creatinine, usually with increases in serum urea nitrogen and consistent with a prerenal etiology. Due to the encouraging safety profile of proteasome inhibition and the potential clinical efficacy of carfilzomib as a single agent in phase I studies, an open-label, single-arm, phase II study of single-agent carfilzomib in RRMM was initiated in 2007.84,85 Carfilzomib administered as an IV bolus of 20 mg/m2 on the twice-weekly dose schedule (PX-171-003-A0) among 39 heavily pretreated patients resulted in 10 patients (26%) with minor response or better, including 5 partial responses, and 16 patients with stable disease.84 Based on new safety information from phase I studies, the protocol was amended, and the carfilzomib dose was escalated to 27 mg/m2 after the first cycle (PX-171-003-A1).85 In this trial, 266 patients were enrolled, and all patients had previously been treated with an immunomodulatory agent and bortezomib and were refractory to their last therapy. An ORR of 23.7% with a median duration of response of 7.8 months was reported. AEs were predominantly hematopoietic (thrombocytopenia, lymphopenia, and anemia), and there was a 90% of dose) under fasting conditions. Food affects oral absorption, reducing area under the concentration-time curve by 20% and maximum concentration by 50%. Maximum plasma concentration is reached 0.625 to 1.5 hours after dosing, with approximately 30% bound to plasma proteins. Biotransformation of lenalidomide in humans includes chiral inversion, trivial hydroxylation, and slow nonenzymatic hydrolysis. Approximately 82% of an oral dose is excreted as lenalidomide in urine within 24 hours. Lenalidomide has a short half-life (3 to 4 hours) and does not accumulate in plasma upon repeated dosing. Its pharmacokinetics profile is consistent across patient populations, regardless of the type of hematologic malignancy. Renal function is the only important factor affecting lenalidomide plasma exposure. Lenalidomide has no QT prolongation risk at approved doses, and higher plasma exposure to lenalidomide is associated with increased risk of neutropenia and thrombocytopenia. Despite being a weak substrate of P-glycoprotein in vitro, lenalidomide does not have clinically significant pharmacokinetic interactions with P-glycoprotein substrates/inhibitors in controlled studies.60 Compared with thalidomide, lenalidomide is associated with less sedation, constipation, and peripheral neuropathy. However, myelosuppression in the form of neutropenia and thrombocytopenia can be dose limiting. As with thalidomide, the incidence of thromboembolic events is significant with the combination of dexamethasone and lenalidomide. A pooled analysis of 691 patients enrolled in two randomized studies reported a

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12% incidence of thrombotic or thromboembolic events with the combination, compared with 4% with dexamethasone alone.

Pomalidomide Pomalidomide (Pomalyst; 4-amino-2-[2,6-dioxopiperidin-3-yl]-2,3-dihydro-1H-isoindole-1,3-dione) is another thalidomide derivative designed to be more potent and less toxic than both parent compounds of thalidomide and lenalidomide. It has clinical activity in lenalidomide-refractory patients.61 Pomalidomide is currently FDA approved (4-mg once-daily dose orally on days 1 to 21 of a 28-day cycle, with or without dexamethasone) for use in patients with progressive multiple myeloma who have received at least two prior therapies, including lenalidomide and bortezomib. In a recent phase II study, addition of daratumumab to pomalidomide resulted in deep and durable responses, including minimal residual disease negativity, in heavily treated patients with relapsed or refractory disease. Aside from increased neutropenia, the safety profile was consistent with that of the individual therapies.62 Further evaluation of daratumumab plus pomalidomide and dexamethasone is under way in the ongoing APOLLO study conducted by the European Myeloma Network. After oral administration, pomalidomide is rapidly absorbed, reaching maximum plasma concentration within 2 to 3 hours. Approximately 12% to 44% of the drug binds proteins, and the half-life of elimination is between 7.5 and 9.5 hours. Pomalidomide is metabolized in the liver via CYP1A2/CYP3A4 (major) and CYP2C19/CYP2D6 (minor), and excretion occurs primarily through the kidneys (73%; 2% as unchanged drug). Like lenalidomide, pomalidomide is better tolerated than thalidomide at approved doses, with less constipation, fatigue, and neuropathy.63 The primary toxicity appreciated in myeloma trials has been myelosuppression, particularly neutropenia, which can be dose limiting. The risk of thromboembolic events is similar to that seen with thalidomide and lenalidomide. Unlike thalidomide or lenalidomide, dermatologic toxicity is rare with pomalidomide. Due to the potential risk of significant teratogenicity, thalidomide, lenalidomide, and pomalidomide can only be prescribed by licensed prescribers who are registered in restricted distribution programs. A summary of the characteristics of the miscellaneous drugs is provided in Table 29.1.

MISCELLANEOUS AGENTS WITH POTENTIAL FOR REPURPOSABLE CHEMOTHERAPEUTIC USE Drug repurposing, the process of finding new uses for existing drugs, makes it possible to bypass years of costly preclinical pharmacology, toxicology, and chemistry work by successfully introducing previously approved noncancer drugs into oncology practice, such as thalidomide, or into oncology clinical trials, such as nelfinavir, propranolol, metformin, statins, and many more. Worldwide, with more than 2,000 approved drugs and, on average, with six relevant targets per drug, the potential for identifying repurposable drugs for cancer therapy is enormous. A PubMed search produced a list of 235 noncancer drugs with at least one peer-reviewed article showing an anticancer effect in vitro, in vivo, or in human clinical trials. In addition to drugs discussed here, there is active and ongoing research on both cancer prevention and cancer therapy settings evaluating many other drugs, such as mebendazole, itraconazole, cimetidine, hydroxychloroquine, diclofenac, and aspirin, in this setting. A summary of the characteristics of the miscellaneous drugs with potential for repurposable anticancer use is provided in Table 29.2.

Nelfinavir Nelfinavir, an HIV protease inhibitor, has been investigated for repurposing as an anticancer agent because of its inhibitory effects on the PI3K/Akt/mTOR pathway and cancer cell proliferation. In preclinical models, nelfinavir has been shown to induce endoplasmic reticulum stress, autophagy, and apoptosis.64 In a phase I study of nelfinavir, the maximum-tolerated dose was established as 3,125 mg twice daily, which is 2.5 times the FDAapproved dose for HIV. One (9%) of 11 evaluable patients in this phase I trial had a confirmed partial response, 3 (27%) of 11 had minor responses (2 with neuroendocrine tumors and 1 with small-cell lung cancer), and 4 (36%) of 11 patients with varying types of cancers had stable disease for more than 6 months. Common adverse events included diarrhea, anemia, and lymphopenia.65 Nelfinavir has also been shown to be safe and effective when used in combination with other chemotherapeutic agents and/or radiation therapy in pancreatic, rectal, and non–small-

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cell lung cancer patients. Preclinical studies of nelfinavir have demonstrated antitumor activity by proteasome inhibition, suggesting potential use in myeloma. In a phase II study, 34 patients with proteasome inhibitor– refractory myeloma who had received a median of five prior regimens were treated with six cycles of nelfinavir in combination with standard doses of bortezomib and dexamethasone. The response rate was 65%, including a 15% rate of very good partial response or better. In patients with high-risk cytogenetics, the response rate was 77%. The most frequent grade 3 or higher adverse events were anemia, thrombocytopenia, lung infections, hypertension, hyperglycemia, hyponatremia, and fatigue, and three cases of sepsis occurred.66

Propranolol First developed in the 1960s, propranolol is a well-known and commonly used nonselective β-adrenergic receptor antagonist (β-blocker), with a range of actions that can be of interest in an oncologic context. There is a significant volume of data ranging from in vitro studies to animal and human studies to indicate that there are multiple clinically relevant anticancer effects associated with propranolol, including effects on cellular proliferation and invasion, immune system, angiogenic cascade, and sensitivity of tumor cells to existing treatments. There is also evidence that propranolol is effective at multiple points in the metastatic cascade and also in the context of the postsurgical wound response. Propranolol is highly lipophilic and undergoes rapid absorption in the gastrointestinal tract, and more than 90% undergoes plasma protein absorption. There is wide distribution into tissues, particularly lungs, liver, kidneys, and heart. Bioavailability after oral dosing is in the range of 25% to 35% due to extensive first-pass hepatic clearance with considerable interpatient variability. Peak plasma concentrations occur 1.5 to 3 hours following oral dosing, with a plasma half-life of around 4 hours following a single dose or around 10 hours for extended-release tablets. Excretion is primarily renal, although 1% to 4% of an oral or IV dose of the drug appears in feces as unchanged drug and metabolites.67 Common side effects include insomnia, fatigue, cold extremities, and Raynaud syndrome. Less common side effects include nausea, vomiting, diarrhea, heart failure, heart block, and hypotension. The earliest human data to suggest a positive effect of propranolol on cancer came from epidemiologic studies comparing cancer incidence in hypertensive and nonhypertensive patients. There is extensive accumulated data supporting anticancer effects of propranolol from prevention to adjuvant and metastatic setting in various cancers.68,69 TABLE 29.1

Miscellaneous Chemotherapeutic Agents

Agent

Other Names

Omacetaxine

Synribo

Protein synthesis inhibitor

Inhibits protein translation by preventing elongation step by interacting with ribosomal A-site

L-

Elspar

Enzyme

Hydrolyzes circulating Lasparagine to aspartic acid and ammonia and results in depletion of essential amino acid L-asparagine leading to the inhibition of protein synthesis

Asparaginase

Drug Class

Mechanism of Action

Dosage and Route of Administration

Common Toxicities

Clinical Pharmacology

Adult patients with chronic or accelerated phase chronic myeloid leukemia with resistance and/or intolerance to two or more tyrosine kinase inhibitors

1.25 mg/m2 subcutaneously bid for 14 d induction followed by 1.25 mg/m2 for 7 d every 28 d

Myelosuppression, impaired glucose tolerance, increased risk of bleeding, diarrhea, nausea, vomiting, headaches

Following subcutaneous administration, maximum drug concentrations are achieved within 30 min; primarily hydrolyzed to 4′DMHHT by plasma esterases; mean half-life is 6 h

Pediatric and adult acute lymphocytic leukemia

6,000–10,000 IU/m2 intramuscularly every 3 d for a total of 9 doses, or 200 IU/kg intravenously for 28 consecutive d

Hypersensitivity reactions, fever, chills, nausea, vomiting, elevation of liver enzymes, increased bleeding and clotting, pancreatitis, lethargy, confusion, agitation, mild elevations in BUN and creatinine

After intramuscular injection, peak plasma levels are reached within 14–24 h; 30% plasma protein binding; half-life is 40–50 h for Escherichia coli derived formulation and 3–5 d for PEG

Clinical Indications

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formulation Bleomycin

Blenoxane

Antitumor antibiotic

Generation of activated oxygen free radical species causing single- and double-strand DNA breaks and cell death

Hodgkin and nonHodgkin lymphoma, germ cell tumors head and neck cancer, squamous cell carcinoma of the skin, cervix, vulva, sclerosing agent for malignant effusions

10 U/m2 intravenously on d 1 and 15 every 28 days for Hodgkin, 30 U/m2 on days 2, 9, and 16 for testicular cancer, 60 U/m2 as sclerosing agent

Erythema, hyperpigmentation, pulmonary toxicity pneumonitis, pulmonary fibrosis, hypersensitivity reaction, vascular events

After intravenous administration, shows a rapid biphasic disappearance from the circulation; terminal half-life is 3 h; rapidly inactivated in tissues by bleomycin hydroxylase; elimination is primarily by kidneys

Procarbazine

Matulane

Nonclassic alkylating agent

Hydrazine analog acts as an alkylating agent; weak monoamine oxidase inhibitor; inhibits DNA, RNA, and protein synthesis

Hodgkin, nonHodgkin lymphoma, brain tumors, cutaneous T-cell lymphoma

100 mg/m2 orally daily for 14 d for Hodgkin lymphoma, 60 mg/m2 orally daily for 14 d for brain tumors

Myelosuppression, nausea and vomiting diarrhea, flu-like symptoms, paresthesias, neuropathies, headache, lethargy, hypersensitivity skin rash, secondary malignancies

Rapid complete absorption from gastrointestinal tract; peak plasma levels within 1 h; extensively metabolized by liver microsomal system; peak CSF levels within 30–90 min after oral intake; elimination halflife 1,900 ng/mL and dose escalation ceased given the lack of a maximum-tolerated dose. Endoxifen clearance was unaffected by CYP2D6 genotype. The overall clinical benefit rate (stable disease >6 months, n = 7; or partial response by Response Evaluation Criteria in Solid Tumors [RECIST] criteria, n = 3) was 26.3% (95% confidence interval, 13.4% to 43.1%), including patients who exhibited prior progression on tamoxifen (n = 3). Based on these early results, subsequent studies are ongoing, including randomized studies comparing endoxifen with tamoxifen.

Toremifene Toremifene is an antiestrogen similar to tamoxifen. It is available in the United States for the treatment of patients with metastatic breast cancer and is approved in other countries for the adjuvant treatment of ER-positive breast cancer. Clinical trials have demonstrated no difference in either disease-free or overall survival when toremifene was compared with tamoxifen for the treatment of ER-positive breast cancer,20 and evidence exists for major cross-resistance between tamoxifen and toremifene.

Pharmacology Toremifene is an antiestrogen with a chemical structure that differs from that of tamoxifen by the substitution of a chlorine for a hydrogen atom that is retained when toremifene undergoes metabolism. Like tamoxifen, toremifene is metabolized by CYP3A, with a secondary metabolism to form hydroxylated metabolites that appear to have similar binding affinities to 4-OH tamoxifen.7 The time to peak plasma concentrations after oral administration ranges from 1.5 to 6.0 hours. The terminal half-life for the major metabolite, N-desmethyltoremifene, is 21 days. The time to reach plasma steady-state concentrations is 1 to 5 weeks. As with tamoxifen, toremifene is present at higher concentrations in tissues compared to plasma with a high apparent volume of distribution (958 L). Seventy percent of the drug is excreted in feces as metabolites.7 Studies in patients with impaired liver function have demonstrated that hepatic dysfunction decreases the clearance of toremifene and N-desmethyltoremifene. Conversely, patients on anticonvulsants known to induce CYP3A had increased clearance. The rates of endometrial cancer in the adjuvant studies are similar to tamoxifen.

Raloxifene Raloxifene is a selective estrogen receptor modulator (SERM) originally developed to treat osteoporosis. Large placebo-controlled randomized trials demonstrated reduced rates of osteoporosis and a reduction in new breast cancers in treated women, leading to the development of a second-generation breast cancer chemoprevention trial (National Surgical Adjuvant Breast and Bowel Project [NSABP] P2) in which raloxifene was compared with tamoxifen in high-risk postmenopausal women. Tamoxifen was superior to raloxifene in terms of both invasive

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and noninvasive cancer events but was associated with a higher risk of thromboembolic events and endometrial cancer.21

Pharmacology Raloxifene is partially estrogenic in bone, antiestrogenic in mammary tissue, and may be less estrogenic in uterine tissue compared to tamoxifen. Pharmacokinetics of raloxifene, studied principally in postmenopausal women, revealed considerable interindividual variation. Raloxifene is rapidly absorbed from the gastrointestinal tract. Because raloxifene undergoes extensive first-pass glucuronidation, oral bioavailability of unchanged drug is low. Although approximately 60% of an oral dose is absorbed, the absolute bioavailability as unchanged raloxifene is only 2%. After the oral administration of a single 120- or 150-mg dose of raloxifene hydrochloride, peak plasma concentrations of raloxifene and its glucuronide conjugates are achieved at 6 hours and 1 hour, respectively. The plasma elimination half-life of raloxifene at steady state averages 27.7 hours. Raloxifene is excreted principally in feces as an unabsorbed drug and via biliary elimination as glucuronide conjugates, which, subsequently, are metabolized by bacteria in the gastrointestinal tract to the parent drug.22 Raloxifene and its monoglucuronide conjugates are more than 95% bound to plasma proteins. Raloxifene binds to albumin and α1-acid glycoprotein. Raloxifene undergoes extensive first-pass metabolism to the glucuronide conjugates raloxifene 4′-glucuronide, 6-glucuronide, and 6,4′-diglucuronide. UGT1A1 and UGT1A8 have been found to catalyze the formation of both the 6-β- and 4′-β-glucuronides, whereas UGT1A10 formed only the 4′-βglucuronide. The metabolism of raloxifene does not appear to be mediated by CYP enzymes.

Fulvestrant Fulvestrant is a considered a selective ER degrader (SERD) that results in ER downregulation without agonist activity.23 Fulvestrant competitively binds to the ER with approximately 100 times greater affinity than tamoxifen. Early studies evaluating inferior dosing regimens (250 mg per month) demonstrated some antitumor activity.24,25 Prospective studies have demonstrated that 500 mg per month (along with an extra loading dose in the first month) is superior to the 250-mg dose in the metastatic setting.26 In endocrine-naïve women with advanced hormone receptor–positive breast cancer, fulvestrant (500-mg dose) was more efficacious than anastrazole.26,27

Side Effects of Fulvestrant Fulvestrant is well tolerated. The most common drug-related events (>10% incidence) from the randomized phase III studies were injection-site reactions and hot flashes. Common events (incidence of 1% to 10%) included asthenia; headache; and gastrointestinal disturbances such as nausea, vomiting, and diarrhea, with minor gastrointestinal disturbances being the most commonly described adverse event.24,27

Pharmacology Fulvestrant is a steroidal molecule derived from estradiol (E2) with an alkylsulfonyl side chain in the 7-α position. The drug is administered via an intramuscular formulation that provides prolonged release of the drug over several weeks. Early studies evaluating three different single doses of fulvestrant (50, 125, and 250 mg) and later studies evaluating the 250- and 500-mg doses have been published.23,28 After single intramuscular injections of fulvestrant, the time of maximal concentration (tmax) ranged from 2 to 19 days, with the median being 7 days for each dose group.23 Fulvestrant is highly protein bound, and the volume of distribution at steady state is 3 to 5 L/kg. Pharmacokinetic modeling of the pooled data from the 250-mg cohort was best described by a twocompartment model in which a longer terminal phase began approximately 3 weeks after administration.23 With monthly dosing of fulvestrant, it takes 3 to 6 months for fulvestrant to reach steady-state plasma level. By adding a loading dose at 14 days, steady-state levels of fulvestrant can be attained within 1 month of treatment.28

AROMATASE INHIBITORS The synthesis of ovarian hormones ceases at menopause. However, estrogen continues to be converted from androgens (produced by the adrenal glands) by aromatase, an enzyme of the cytochrome P450 (CYP) superfamily. Aromatase is the enzyme complex responsible for the final step in estrogen synthesis via the conversion of

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androgens, androstenedione and testosterone, to estrogens, estrone (E1) and E2. This pathway was used to develop the antiaromatase class of compounds. Alterations in aromatase expression have been implicated in the pathogenesis of estrogen-dependent disease, including breast cancer, endometrial cancer, and endometriosis. Aromatase (cytochrome P450 19 [CYP19]) is encoded by the highly polymorphic CYP19 gene. Some of these variants may have clinical significance.29 Aminoglutethimide was the first clinically used aromatase inhibitor. Because of the lack of selectivity for aromatase and the resultant suppression of aldosterone and cortisol, aminoglutethimide is no longer recommended for treating metastatic breast cancer. Aminoglutethimide is also occasionally used to try to reverse excess hormone production by adrenocortical cancers. Aromatase inhibitors have been classified in a number of different ways, including first, second, and third generation; steroidal and nonsteroidal; and reversible (ionic binding) and irreversible (suicide inhibitor, covalent binding). The nonsteroidal aromatase inhibitors include aminoglutethimide (first generation); rogletimide and fadrozole (second generation); and anastrozole, letrozole, and vorozole (third generation). The steroidal aromatase inhibitors include formestane (second generation) and exemestane (third generation). Steroidal and nonsteroidal aromatase inhibitors differ in their modes of interaction and inactivation of the aromatase enzyme. Steroidal inhibitors compete with the endogenous substrates, androstenedione and testosterone, for the active site of the enzyme and are processed into intermediates that irreversibly bind to the active site, causing irreversible enzyme inhibition.30 Nonsteroidal inhibitors also compete with the endogenous substrates for access to the active site, where they then form a reversible bond to the heme iron atom so that enzyme activity can recover if the inhibitor is removed.

Letrozole and Anastrozole Both letrozole and anastrozole have been extensively studied in the metastatic and adjuvant settings. Compared to tamoxifen, both drugs have superior response rates and progression-free survival (PFS) in the metastatic setting.31,32 In the adjuvant setting, a meta-analysis demonstrated their superiority to tamoxifen in terms of relapse-free survival and overall survival.33 In addition, both letrozole and anastrozole have been studied in a sequential approach, and tamoxifen followed by aromatase inhibitor use is superior to 5 years of tamoxifen alone.34,35 In postmenopausal women at high risk for developing breast cancer, anastrozole significantly reduced the incidence of invasive breast cancer.36

Side Effects of Anastrozole and Letrozole The side effects of both anastrozole and letrozole are similar and include arthralgias and myalgias in up to 50% of patients. Both drugs are associated with a higher rate of bone fracture compared with tamoxifen.33 When offering anastrozole for extended periods of time to patients with early breast cancer, attention to bone health is paramount, and bone density should be monitored in all patients. Prospective studies have demonstrated that bisphosphonates prevent aromatase inhibitor–induced bone loss, and a meta-analysis demonstrated that bisphosphonates reduce bone recurrences and prolong overall survival.37 Therefore, bisphosphonates should be considered in aromatase inhibitor–treated patients, both in those with and without an increased risk of bone fractures. A meta-analysis of toxicities comparing aromatase inhibitors with tamoxifen has demonstrated a 30% increase in grade 3 and 4 cardiac events and hypercholesterolemia with aromatase inhibitors.38 However, prospective data demonstrate no differences in myocardial events comparing anastrozole with placebo, although an increase in hypertension was observed.36

Pharmacology Letrozole is a nonsteroidal aromatase inhibitor with a high specificity for the inhibition of estrogen production. In vitro, letrozole inhibits aromatase 180 times more potently than aminoglutethimide. Aldosterone production in vitro is inhibited by concentrations 10,000 times higher than those required for inhibition of estrogen synthesis. After 2 weeks of treatment with letrozole, the blood levels of E2, E1, and estrone sulfate were suppressed 95% or more from baseline.39 In postmenopausal women with advanced breast cancer, the drug did not have any effect on follicle-stimulating hormone (FSH), luteinizing hormone (LH), thyroid-stimulating hormone (TSH), cortisol, 17α-hydroxyprogesterone, androstenedione, or aldosterone blood concentrations.40 Anastrozole is a nonsteroidal aromatase inhibitor that is 200-fold more potent than aminoglutethimide. No effect on the adrenal glands has been detected. In human studies, the tmax is 2 to 3 hours after oral ingestion.

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Elimination is primarily via hepatic metabolism, with 85% excreted by that route and only 10% excreted unchanged in urine. The main circulating metabolite is triazole after cleavage of the two rings in anastrozole by Ndealkylation. The terminal half-life is approximately 50 hours, and steady-state concentrations are achieved in approximately 10 days with once-a-day dosing. Plasma protein binding is approximately 40%.41 In one study, anastrozole 1 and 10 mg daily inhibited in vivo aromatization by 96.7% and 98.1%, respectively, and plasma E1 and E2 levels were suppressed 86.5% and 83.5%, respectively, regardless of dose.42 Thus, 1 mg of anastrozole achieves near-maximal aromatase inhibition and plasma estrogen suppression in breast cancer patients. Large interindividual variations exist in plasma concentrations of anastrozole and its metabolites as well as pretreatment and postdrug plasma E1, E2, and E1 conjugate and estrogen precursor (androstenedione and testosterone) concentrations.43 Further research is needed to determine the basis and clinical relevance of the wide variability in the pharmacokinetics of anastrozole.

Exemestane Exemestane has a steroidal structure and is classified as a type 1 aromatase inhibitor, also known as an aromatase inactivator because it irreversibly binds with and permanently inactivates the enzyme.30 Exemestane has been compared to tamoxifen in both the metastatic and adjuvant settings. In the first-line treatment of hormone receptor–positive metastatic breast cancer, exemestane is superior to tamoxifen, as demonstrated in a phase III trial in which improvements in both median PFS and response rates were observed.44 In the adjuvant setting, exemestane has been compared with the nonsteroidal agent anastrozole in the treatment of ER-positive breast cancer, and there were no differences in disease-free or overall survival.45 Finally, exemestane has been compared to placebo in patients at increased risk of breast cancer, and a significant reduction in the risk of developing invasive breast cancer was observed.46

Side Effects of Exemestane Although preclinical studies have suggested that exemestane prevented bone loss in ovariectomized rats, there were no differences in fracture rates comparing anastrozole with exemestane.45 Side effects, including arthralgias and myalgias, appear to be similar to those of the other aromatase inhibitors. With regard to steroidogenesis, no impact on either cortisol or aldosterone levels was seen in a small study after the administration of exemestane for 7 days.47 Finally, exemestane has weak androgenic properties, and its use at higher doses has been associated with steroidal-like side effects, such as weight gain and acne. However, these side effects have not been observed with the FDA-approved dose (25 mg per day).

Pharmacology Exemestane is administered once daily by mouth, with the recommended daily dose being 25 mg. Exemestane suppresses estrogen concentrations by 52% to 72%. This activity is comparable to that produced by the nonsteroidal aromatase inhibitors anastrozole and letrozole.30 The time needed to reach maximal E2 suppression is 3 days. Exemestane does not appear to affect cortisol or aldosterone levels when evaluated after 7 days of treatment based on dose-ranging studies, including doses from 0.5 to 800 mg.47 Exemestane is metabolized by CYP3A4. Although drug–drug interactions have not been formally reported for exemestane, there is the potential for interactions with drugs that affect CYP3A4.

RESISTANCE TO ENDOCRINE-TARGETED THERAPY IN BREAST CANCER Resistance to SERMs or aromatase inhibitors, whether intrinsic or acquired, inevitably develops over time through multiple mechanisms (Fig. 30.2). An important factor appears to be the level of ER, which is highly predictive for endocrine therapy response. In approximately 10% of cases, resistance may result from a decrease or loss of ER expression.48 Although alterations in estrogen receptor 1 (ESR1, the gene for ERα) are rare in newly diagnosed breast cancer, activating ER point mutations are present in up to 30% of recurrent breast cancers.48 These mutations lead to a conformational change in the ligand-binding domain that mimics the conformation of the activated ligand-bound receptor and generates constitutive, ligand-independent transcriptional activity, resulting in resistance to hormonal therapy. Although preclinical and clinical studies suggest that tumors bearing some of these mutations retain sensitivity to higher dose SERMs19 and fulvestrant,49 new oral SERDs are under clinical

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development, and these drugs have demonstrated substantial antitumor activity against ER-positive cell lines and patient-derived xenograft models harboring ESR1 mutations.50,51 In addition to mutations, ESR1 translocations have been described, several of which yield fusion proteins that render ER-positive cells insensitive to endocrine therapy. ESR1 amplification has been more commonly observed in tumors resistant to aromatase inhibitors.

Figure 30.2 Selected mechanisms of resistance to endocrine therapy in breast cancer. In the standard pathway, estradiol (E1) or estrone (E2) binds to the wild-type estrogen receptor (wtER), resulting in nuclear translocation, DNA binding to estrogen receptor (ER) response elements, and transcriptional activity that promotes growth and survival. Mechanism 1: Loss of wtER expression may lead to estrogen-independent growth. Mechanism 2: Essential components of the ESR1 gene include activation function 1 (AF1), the DNA-binding domain (DBD), hinge, and the ligandbinding domain (LBD). ESR1 activating point mutations have been reported in the LBD (red lightning bolts), resulting in constitutively active mutant ER (mutER). Mechanism 3: Overexpression or amplification of growth factor receptors, including epidermal growth factor receptor (EGFR), human epidermal growth factor receptor 2 (HER2), human epidermal growth factor receptor 3 (HER3), insulin-like growth factor 1 receptor (IGF1R), fibroblast growth factor receptor 1 (FGFR1) contributes to endocrine resistance. Mechanism 4: In the absence of stimulatory signaling, the retinoblastoma (Rb) protein sequesters the transcription factor E2F, preventing progression of the cell cycle. Increased activity of cyclin D1 or cyclin-dependent kinases (CDKs) 4 and 6 or loss of the Rb protein facilitates entry into the cell cycle. C’ter, C-terminal; N’ter, Nterminal; PI3K, phosphoinositide 3-kinase; mTOR, mammalian target of rapamycin.

Figure 30.3 Chemical structures of cyclin-dependent kinase (CDK) 4/6 inhibitors. The chemical structure, code name used in preclinical studies, and molecular formula of each drug are provided. The CDK4/6 structures were drawn using PubChem Sketcher V2.4

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(https://pubchem.ncbi.nlm.nih.gov). Dysregulation in multiple growth factor signaling pathways has been associated with resistance to endocrine therapy. ER-positive breast cancers that overexpress HER2 may be less responsive to tamoxifen and to hormonal therapy in general.52 Overexpression or amplification in multiple growth factor receptors, including epidermal growth factor receptor (EGFR), human epidermal growth factor receptor 2 (HER2), human epidermal growth factor receptor 3 (HER3), insulin-like growth factor 1 receptor (IGF1R), fibroblast growth factor receptor 1 (FGFR1), contributes to endocrine resistance.48,53 These mitogenic pathways converge on the mitogen-activated protein kinase (MAPK) and mammalian target of rapamycin (mTOR) pathways. The expression of AIB1, an estrogen-receptor coactivator, has been associated with tamoxifen resistance in patients whose breast cancers overexpress HER2.48 Finally, mutations in the phosphoinositide 3-kinase (PI3K)/AKT/mTOR pathway are frequently observed in ER-positive breast tumors.54 However, whether these alterations mediate resistance to endocrine therapy is controversial (see Fig. 30.2). Impaired regulation of the cell-cycle progression through abnormalities in key regulatory checkpoints can lead to endocrine insensitivity as well. Abnormalities in the cyclin, cyclin-dependent kinase (CDK) family, or retinoblastoma (Rb) pathways were frequently observed in ER-positive breast cancers.54 Cyclin D1 (CCND1) amplification, gain of CDK4, and loss of negative regulators have been associated with estrogen-independent growth.

Combination and Developing Strategies to Overcome Endocrine Resistance in Breast Cancer mTOR Inhibitors As the downstream mediator of the PI3K/AKT pathway, overcoming endocrine resistance by inhibiting mTOR was evaluated. In patients resistant to anastrozole or letrozole, adding everolimus (an mTOR inhibitor) to the steroidal aromatase inhibitor exemestane improved PFS.55 The benefit of mTOR inhibitors may be confined to patients who exhibit secondary endocrine resistance, as no improvement in PFS was noted when this class of drugs was added to aromatase inhibitors in the first-line setting.56 The side effect profile of everolimus includes stomatitis, hyperglycemia, anemia, and, rarely, drug-related pneumonitis. A feedback loop resulting in increased activation of AKT limits the durability of everolimus responses. Multiple therapeutic strategies targeting the PI3K/AKT/mTOR pathway are in development.

CDK4/6 Inhibitors The cell-cycle progression for multiple growth factor or proliferation signaling pathways is regulated by CDK4 or CDK6. Activation of CDK4 or CDK6 leads to phosphorylation and degradation of the tumor suppressor Rb, representing another mechanism of endocrine resistance. CDK4/6 inhibition activates Rb and inhibits growth in both estrogen-sensitive and estrogen-resistant models. Three highly selective CDK4/6 inhibitors have demonstrated efficacy in ER-positive breast cancer: palbociclib, ribociclib, and abemaciclib (Fig. 30.3). Combinations of palbociclib, ribociclib, or abemaciclib with either letrozole or fulvestrant demonstrated similar and substantial improvement in PFS in premenopausal57 or postmenopausal women58–60 with metastatic hormone receptor–positive breast cancer. Palbociclib and ribociclib share a similar toxicity profile, including myelosuppression, and fatigue. Notably, although neutropenia is commonly observed, episodes of neutropenic fever are infrequent. Prolongation of the QT interval has been reported with ribociclib, and electrocardiogram and electrolyte monitoring are recommended. Abemaciclib more potently inhibits CDK4 compared to CDK6. Unlike other CDK4/6 inhibitors, abemaciclib has significant single-agent activity in hormone-refractory and chemotherapy-refractory metastatic ER-positive breast cancer.61 Although myelosuppression can occur, the most common adverse event with abemaciclib is diarrhea.

GONADOTROPIN-RELEASING HORMONE ANALOGS Gonadotropin-releasing hormone (GnRH) analogs result in a medical orchiectomy in men and are used as a means of providing androgen ablation for hormone-sensitive and castration-refractory metastatic prostate cancer.

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Because the initial agonist activity of GnRH analogs can cause a tumor flare from temporarily increased androgen levels, concomitant use of the antiandrogen flutamide or bicalutamide has been used to prevent this effect. GnRH analogs can also cause tumor regressions in hormonally responsive breast cancers and have received FDA approval for the treatment of metastatic breast cancer in premenopausal women. The benefit of including these drugs in combination with tamoxifen, anastrozole, or exemestane in the adjuvant treatment of premenopausal women with primary breast cancer has been established in multiple large clinical trials.62–64 The primary toxicities of GnRH analogs are secondary to the ablation of sex steroid concentrations and include hot flashes, sweating, and loss of libido. These symptoms can be reversed with low doses of progesterone analogs.4 In men with advanced prostate cancer, an alternate strategy of intermittent GnRH administration may result in improved tolerability and quality of life. However, in men with newly diagnosed metastatic prostate cancer, intermittent androgen-deprivation therapy (ADT) failed to demonstrate noninferiority compared to continuous ADT; thus, continuous GnRH administration remains the standard of care.65

Gonadotropin-Releasing Hormone Analogs GnRH agonists available for clinical use include goserelin and leuprolide. Both are available in depot intramuscular preparations to be given at monthly intervals.66,67 The recommended monthly dose of leuprolide is 7.5 mg and of goserelin is 3.6 mg. There are also longer acting depot preparations to be administered every 3, 4, 6, and 12 months.

Pharmacology Analogs of the decapeptide GnRH have been synthesized by modifications of l-glycine in position 6.66,67 These changes increase the affinity of the analog for the GnRH receptor and decrease the susceptibility to enzymatic degradation. Initial administration of these compounds results in stimulation of gonadotropin release. However, prolonged administration has led to profound inhibition of the pituitary–gonadal axis. Plasma E2 and progesterone are consistently suppressed to postmenopausal or castrate levels after 2 to 4 weeks of treatment. These drugs are administered intramuscularly or subcutaneously in a parenteral sustained-release microcapsule preparation, as parenteral administration is associated with rapid clearance. Leuprolide is approximately 80 to 100 times more potent than endogenous GnRH. It induces castrate levels of testosterone in men with prostate cancer within 3 to 4 weeks of drug administration after an initial sharp increase in LH and FSH. The mechanisms of action include pituitary desensitization after a reduction in pituitary GnRH receptor binding sites and possibly a direct antitumor effect in ER-positive human breast cancer cells.66 The depot form results in a dose rate of 210 μg per day of leuprolide. Peak concentrations of the depot form are achieved approximately 3 hours after drug administration. There appears to be a linear increase in the area under the curve (AUC) for doses of 3.75, 7.5, and 15.0 mg in the depot form. The parenteral bioavailability of subcutaneously injected leuprolide is 94%. In human studies, leuprolide urinary excretion as a metabolite was the primary route of clearance.66 Goserelin is approximately 100 times more potent than naturally occurring GnRH. In women, goserelin inhibits ovarian androgen production, but serum levels of dehydroepiandrosterone sulfate and, to a lesser extent, androstenedione, are preserved. Goserelin is released at a continuous mean rate of 120 μg per day in the depot form, with the terminal half-life occurring approximately 5 hours after subcutaneous injection. It is principally excreted in the urine.

Gonadotropin-Releasing Hormone Antagonists Modification to the structure of GnRH has resulted in the development of GnRH antagonist compounds that are currently being used in the treatment of prostate cancer. Abarelix was approved by the FDA in 2003 as the first depot-injectable GnRH antagonist but was subsequently withdrawn in 2005. Degarelix is a synthetically modified compound with GnRH antagonist activity, with comparable efficacy to leuprolide, that was approved for use by the FDA in 2008 for the management of prostate cancer.68 Degarelix blocks the GnRH receptor, thereby preventing the trigger for LH production that mediates androgen synthesis. In contrast to GnRH analogs, degarelix does not cause tumor flare symptoms secondary to temporary increased androgen production. The most common side effects were hot flashes and pain at the injection site. It is unknown if degarelix will have a similar chronic side effect profile known to be associated with long-term GnRH analog use.

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Pharmacology The recommended loading dose of degarelix is 240 mg, administered as two injections of 120 mg each subcutaneously. Monthly maintenance doses of 80 mg as a 20 mg/mL solution are started 28 days after the loading dose. In 60 healthy males, after a single subcutaneous dose of degarelix, a terminal half-life of 47 days was observed.68 Pharmacokinetic properties of degarelix have been evaluated when administered as a subcutaneous depot of drug as a gel in six different doses to 48 healthy males and when administered intravenously. Using data from several clinical trials, the rate of drug diffusion from subcutaneous administration results in detectable drug up to 60 days after a single dose compared to less than 4 days when the drug is injected intravenously.

ANTIANDROGENS Flutamide The antiandrogen flutamide is used in men with metastatic prostate cancer either as initial therapy, combined with GnRH analog administration, or when the metastatic prostate cancer is unresponsive despite androgen ablation therapy. The recommended dose is 250 mg by mouth three times a day. In patients whose prostate cancer is growing despite flutamide use, stopping flutamide can sometimes cause a flutamide withdrawal response. The most common toxicity seen with flutamide is diarrhea, with or without abdominal discomfort. Gynecomastia, which can be tender, frequently occurs in men who are not receiving concomitant androgen ablation therapy.69 Flutamide can rarely cause hepatotoxicity, a condition that is reversible if detected early, but this toxicity can also be fatal.

Pharmacology Flutamide acts as an androgen receptor antagonist with no intrinsic steroidal activity.69 Binding prevents dihydrotestosterone binding and subsequent translocation of the androgen–receptor complex into the nuclei. Because it is a pure antiandrogen, it acts only at the cellular level. The administration of flutamide alone leads to increased LH and FSH production and a concomitant increase in plasma testosterone and E2 levels. When the drug is administered three times a day, steady-state levels are achieved by day 6. The elimination half-life at steady state is 7.8 hours, and 2-hydroxyflutamide achieves concentrations 50 times higher than the parent drug at steady state and has equal or greater potency than that of flutamide. The elimination half-life for the metabolite is 9.6 hours. The high plasma concentrations of 2-hydroxyflutamide, as compared with flutamide, suggest that the therapeutic benefits of flutamide are mediated primarily through its active metabolite.69

Bicalutamide Bicalutamide is another nonsteroidal antiandrogen that has been approved by the FDA for use in the United States. The recommended dose is one 50-mg tablet per day. One randomized trial reported that bicalutamide compared favorably with flutamide in patients with advanced prostate cancer.70 Bicalutamide appears to be relatively well tolerated and is associated with a lower incidence of diarrhea than is flutamide.

Pharmacology Bicalutamide has a binding affinity to the androgen receptor in the rat prostate that is four times greater than that of 2-hydroxyflutamide.71 In humans, the drug has a long plasma half-life of 5 to 7 days, so it may be administered on a weekly schedule. Pharmacokinetics of the drug showed a dose-dependent increase in mean peak plasma concentrations, and the AUC increased linearly with the dose. The half-life of bicalutamide in humans was approximately 6 days, and the drug clearance was not saturable at plasma concentrations up to 1,000 ng/mL. Daily dosing of the drug led to an approximately 10-fold accumulation after 12 weeks of administration. In contrast to results in rats, serum concentrations of testosterone and LH increased significantly from baseline at all dose levels tested in humans. Whereas serum FSH concentrations remained essentially unchanged, the median serum E2 concentrations increased significantly.71

Nilutamide

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Nilutamide represents the third variation of an antiandrogen available for use in patients with prostate cancer. The observation of unique toxicities, night blindness, and pulmonary toxicity has limited its use.

RESISTANCE TO ANDROGEN THERAPIES IN PROSTATE CANCER Although testosterone depletion remains a standard for advanced-stage, castrate-sensitive disease, evidence indicates that castrate-resistant prostate cancer remains androgen receptor (AR) dependent. Despite undetectable circulating androgens, persistent AR activation occurs through a variety of mechanisms, including AR amplification, activating mutations, or splice variants. Recognition of continued AR activation has led to the development of novel antiandrogens.

Abiraterone Acetate After the failure of initial androgen manipulation, prostate cancer continues to respond to a variety of second- and third-line hormonal interventions. Based on this observation, CYP17, a key enzyme in androgen and estrogen synthesis, was targeted using ketoconazole, which is a weak, reversible, and nonspecific inhibitor of CYP17, resulting in modest antitumor activity of short durability. Abiraterone acetate, a selective, irreversible inhibitor of CYP17 that is 20 times more potent than ketoconazole, prolonged overall survival in castration-resistant prostate cancer.72 In men with newly diagnosed, metastatic, castration-sensitive prostate cancer, combining abiraterone acetate with ADT was superior to ADT alone, as evidenced by a more than doubled radiographic PFS.73 Earlier use of abiraterone acetate was further supported in another phase III study demonstrating that adding abiraterone acetate to androgen deprivation lowered the relative risk of death compared to androgen deprivation alone.74 These two recent studies (LATITUDE and STAMPEDE) add substantial evidence for including abiraterone acetate to ADT in treatment-naïve men with metastatic prostate cancer. Development of primary and secondary resistance to abiraterone acetate and prednisone has been observed in castration-resistant patients. Mechanisms of resistance include both AR-dependent and non-androgen axis– dependent pathways. Regarding the latter, in a study evaluating exome and transcriptome sequencing of metastases in castration-resistant patients, higher expression of genes in cell cycle proliferation pathways and increased mutational frequency in the Wnt/β-catenin pathway were linked to the development of primary resistance to abiraterone acetate and prednisone. Negative regulators of Wnt/β-catenin signaling were also more frequently deleted or displayed reduced mRNA expression in patients with primary resistance.75 Resistance to abiraterone can also be driven by the expression of truncated AR splice variants (AR-Vs). AR-Vs retain the N-terminal domain and DNA-binding domain of full-length AR but lack the C-terminal ligand-binding domain due to splicing of alternative 3′ terminal cryptic exon.76,77 Instead of a ligand-binding domain, these 3′ terminal cryptic exons encode C-terminal extensions of variable length and sequence. One particular AR-V, ARV7, arises from contiguous splicing of AR exons 1, 2, 3, and cryptic exon 3 (CE3) and has been associated with driving resistance by functioning as a ligand-independent transcription factor.78 AR-V9, which shares structural similarities with AR-V7, has also been reported as an independent predictor of primary resistance to abiraterone acetate in castration- resistant patients.79

Pharmacology Abiraterone acetate is a 3-pyridyl steroid pregnenolone-derived compound available as an oral prodrug. Its main toxicity is mineralocorticoid excess (including hypokalemia, hypertension, and fluid overload) because continuous CYP17 blockade raises adrenocorticotrophic hormone (ACTH) levels that increase upstream levels of CYP17, including corticosterone and deoxycorticosterone.80 These adverse effects can be lessened by the coadministration of steroids. The established dose of abiraterone is 1,000 mg per day (four 250-mg tablets). Following oral administration of abiraterone acetate, the median time to maximum plasma abiraterone concentrations is within 1.5 to 4 hours. At the dose of 1,000 mg daily, the following fasting values were found: Cmax, 510 nM/mL; AUC, 3,478 nM/L/h; and half-life, 14.4 hours. Abiraterone is highly bound (>99%), and the apparent steady-state volume of distribution is 19,669 L. Abiraterone is converted into two inactive metabolites, N-oxide abiraterone sulfate and abiraterone sulfate. Abiraterone not only inhibits several CYP enzymes, including CYP2D6, CYP1A2, and CYP3A4, but also inhibits a CYP3A4 substrate.80

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Enzalutamide Enzalutamide is a diarylthiohydantoin compound that binds AR with an affinity that is several-fold greater than the antiandrogens bicalutamide and flutamide. This class of novel AR inhibitor also disrupts the nuclear translocation of AR and impairs DNA binding to androgen response elements and the recruitment of coactivators.81 Enzalutamide is approved for the treatment of metastatic castrate-resistant prostate cancer both before and after chemotherapy.82 Side effects of enzalutamide include hot flashes, fatigue, diarrhea, and rarely, seizures. As is the case for abiraterone acetate, development of resistance after initial response has been observed to enzalutamide with the development of AR variants.78

Pharmacology The standard dose of enzalutamide is 160 mg once daily, and its major active metabolite is N-desmethyl enzalutamide. In the studied dose range between 30 and 480 mg, enzalutamide reached peak concentrations between 30 minutes and 4 hours after administration, and the half-life was approximately 1 week.83 Steady-state plasma levels of enzalutamide are reached after 1 month of daily treatment. Enzalutamide is mainly metabolized by CYP2C8 and CYP3A4.

Androgen-Targeted Therapies in Development Novel, more potent antiandrogens are currently being developed. Apalutamide (ARN-509) is more potent than current inhibitors of the AR. In early clinical studies, apalatuamide was well tolerated, and randomized phase III studies are ongoing.84 Darolutamide (ODM-201) is another high-affinity AR antagonist being evaluated in phase III trials.85 Darolutamide retains the ability to inhibit AR splice variants and may have fewer drug–drug interactions.

OTHER SEX STEROID THERAPIES Fluoxymesterone Fluoxymesterone is an androgen that has been used in women with metastatic breast cancer who have hormonally responsive cancers and who have progressed on other hormonal therapies such as tamoxifen, an aromatase inhibitor, or megestrol acetate. The usual dose is 10 mg given twice daily. Although the overall response rate of fluoxymesterone in this clinical situation is low, some patients have exhibited substantial antitumor responses lasting for months or even years. Toxicities associated with fluoxymesterone are those that would be expected with an androgen, including hirsutism, male-pattern baldness, voice lowering (hoarseness), acne, enhanced libido, and erythrocytosis. Fluoxymesterone can also cause elevated liver function test results in some patients and, rarely, has been associated with hepatic neoplasms. The pharmacology of fluoxymesterone has been described elsewhere.86

Estrogens: Diethylstilbestrol and Estradiol Prior to tamoxifen, diethylstilbestrol (DES) was the primary hormonal therapy used for postmenopausal metastatic breast cancer. Randomized comparative trials comparing DES to tamoxifen showed similar responses rates, but DES was supplanted by tamoxifen given higher rates of toxicity, including nausea, vomiting, breast tenderness, and thromboembolism.87 DES is no longer clinically available in the United States, but similar antitumor effects are seen with estradiol. A prospective clinical trial comparing 30 mg (10 mg three times a day) with 6 mg (2 mg three times a day) in women with metastatic ER-positive breast cancer and acquired resistance to aromatase inhibitors showed similar clinical benefit rates but fewer serious adverse events with the 6-mg dose.88

Medroxyprogesterone and Megestrol Medroxyprogesterone and megestrol are 17-OH-progesterone derivatives differing in a double bond between the C6 and C7 positions in megestrol. Historically, megestrol was used as a hormonal agent for patients with advanced breast cancer or advanced prostate cancer, usually at a total daily dose of 160 mg. It is still used for the treatment of hormonally responsive metastatic endometrial cancer. Megestrol has also been extensively evaluated

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for the treatment of anorexia/cachexia related to cancer or AIDS. Various dosages ranging from 160 to 1,600 mg per day have been used. A prospective study demonstrated a dose–response relationship with doses up to 800 mg per day.89 Low dosages of megestrol (20 to 40 mg per day) have been shown to be an effective means of reducing hot flashes in women with breast cancer and in men who have undergone androgen ablation therapy.90 Although megestrol had historically been administered four times per day, the long terminal half-life supports once-per-day dosing. Megestrol is a relatively well-tolerated medication, with its most prominent side effects being appetite stimulation and resultant weight gain. Although these side effects may be beneficial in patients with anorexia/cachexia, they can be problematic in patients with breast or endometrial cancers. Another side effect of megestrol acetate is the marked suppression of adrenal steroid production by suppression of the pituitary–adrenal axis. Although this appears to be asymptomatic in the majority of patients, reports suggest that this adrenal suppression can cause clinical problems in some patients. There appears to be a slightly increased incidence of thromboembolic phenomena in patients receiving megestrol alone.89 Megestrol can cause menstrual irregularities in women and impotence in men, although these side effects are typically reversible.89,90 Although nausea and vomiting have sometimes been attributed as a toxicity of this drug, there are data to demonstrate that this drug has antiemetic properties. Medroxyprogesterone has many of the same properties, clinical uses, and toxicities as megestrol acetate. It has never been commonly used in the United States for the treatment of breast cancer. Medroxyprogesterone is available in 2.5- and 10-mg tablets and in injectable formulations of 100 and 400 mg/L. Dosing for the treatment of metastatic breast or prostate cancer has commonly been 400 mg per week or more and 1,000 mg per week or more for metastatic endometrial cancer. Injectable or daily oral doses have been used for controlling hot flashes.

Pharmacology The exact mechanism of antitumor effect of medroxyprogesterone and megestrol is unclear. These drugs have been reported to suppress adrenal steroid synthesis, suppress ER levels, alter tumor hormone metabolism, enhance steroid metabolism, directly kill tumor cells, and influence growth factors.91 The oral bioavailability of these progestational agents is unknown, although absorption appears to be poor for medroxyprogesterone relative to megestrol. The terminal half-life for megestrol is approximately 14 hours, with a tmax of 2 to 5 hours after oral ingestion. The AUC for a single megestrol dose of 160 mg is between 2.5- and 8fold higher than that for single-dose medroxyprogesterone at 1,000 mg with a radioactive dose of megestrol; 50% to 78% is found in the urine after oral administration, and 8% to 30% is found in the feces.7 Metabolism of medroxyprogesterone occurs via hydroxylation, reduction, demethylation, and combinations of these reactions. The initial volume of distribution is between 4 and 8 L in humans. The mean terminal half-life is 60 hours. The tmax for medroxyprogesterone occurs 2 to 5 hours after oral administration.7 Progestational agents also may increase plasma warfarin level consistent with CYP3A being the site of interaction.

OTHER HORMONAL THERAPIES Octreotide Octreotide and lanreotide are somatostatin analogs used to treat carcinoid syndrome and other hormonal excess syndromes associated with some pancreatic islet cell cancers and acromegaly. Response rates (measured in terms of a reduction in diarrhea and flushing) are high and can last for several months to years. In enteropancreatic and midgut neuroendocrine tumors, somatostatin analogs improve tumor control.92,93 Octreotide and lanreotide are generally well tolerated overall. More toxicity is observed in acromegalic patients, with such problems as bradycardia, diarrhea, hypoglycemia, hyperglycemia, hypothyroidism, and cholelithiasis.

Pharmacology Octreotide is an 8–amino acid synthetic analog of the 14–amino acid peptide somatostatin. Octreotide has a similar high affinity for somatostatin receptors, with a concentration that inhibits the receptor by 50% in the subnanomolar range. Octreotide can be administered intravenously or subcutaneously. Octreotide inhibits insulin, glucagon, pancreatic polypeptide, gastric inhibitory polypeptide, and gastrin secretion.94 Whereas the half-life of somatostatin is only 2 to 3 minutes, octreotide has a half-life of 90 to 120 minutes, and the pharmacologic duration

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of action lasts up to 12 hours (when administered subcutaneously). It has a much longer duration of action than the parent compound because of its greater resistance to enzymatic degradation. Because of the short half-life of classic octreotide, classic octreotide initial doses of 50 μg are given two to three times on the first day. The dose is titrated upward, with a usual daily dose of 300 to 450 μg per day for most patients. A slow-release form of octreotide, designed for once-per-month administration, controls the symptoms of carcinoid syndrome at least as well as three-times-per-day octreotide. The pharmacokinetic profile of lanreotide is comparable to octreotide.

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44. Paridaens RJ, Dirix LY, Beex LV, et al. Phase III study comparing exemestane with tamoxifen as first-line hormonal treatment of metastatic breast cancer in postmenopausal women: the European Organisation for Research and Treatment of Cancer Breast Cancer Cooperative Group. J Clin Oncol 2008;26(30):4883–4890. 45. Goss PE, Ingle JN, Pritchard KI, et al. Exemestane versus anastrozole in postmenopausal women with early breast cancer: NCIC CTG MA. 27—a randomized controlled phase III trial. J Clin Oncol 2013;31(11):1398–1404. 46. Goss PE, Ingle JN, Alés-Martínez JE, et al. Exemestane for breast-cancer prevention in postmenopausal women. N Engl J Med 2011;364(25):2381–2391. 47. Evans TJ, Di Salle E, Ornati G, et al. Phase I and endocrine study of exemestane (FCE 24304), a new aromatase inhibitor, in postmenopausal women. Cancer Res 1992;52(21):5933–5999. 48. Ma CX, Reinert T, Chmielewska I, et al. Mechanisms of aromatase inhibitor resistance. Nat Rev Cancer 2015;15(5):261. 49. Robinson DR, Wu YM, Vats P, et al. Activating ESR1 mutations in hormone- resistant metastatic breast cancer. Nat Genet 2013;45(12):1446–1451. 50. Bihani T, Patel HK, Arlt H, et al. Elacestrant (RAD1901), a selective estrogen receptor degrader (SERD), has antitumor activity in multiple ER+ breast cancer patient-derived xenograft models. Clin Cancer Res 2017;23(16):4793–4804. 51. Patel HK, Bihani T. Selective estrogen receptor modulators (SERMs) and selective estrogen receptor degraders (SERDs) in cancer. Pharmacol Ther 2017:S0163-7258(17)30310-8. 52. Lipton A, Ali S, Leitzel K, et al. Serum HER-2/neu and response to the aromatase inhibitor letrozole versus tamoxifen. J Clin Oncol 2003;21(10):1967–1972. 53. Formisano L, Stauffer KM, Young CD, et al. Association of FGFR1 with ERα maintains ligand-independent ER transcription and mediates resistance to estrogen deprivation in ER+ breast cancer. Clin Cancer Res 2017;23(20):6138–6150. 54. Cancer Genome Atlas Network. Comprehensive molecular portraits of human breast tumors. Nature 2012;490(7418):61–70. 55. Baselga J, Campone M, Piccart M, et al. Everolimus in postmenopausal hormone-receptor–positive advanced breast cancer. N Engl J Med 2012;366(6):520–529. 56. Wolff AC, Lazar AA, Bondarenko I, et al. Randomized phase III placebo-controlled trial of letrozole plus oral temsirolimus as first-line endocrine therapy in postmenopausal women with locally advanced or metastatic breast cancer. J Clin Oncol 2012;31(2):195–202. 57. Tripathy D, Sohn J, Im SA, et al. First-line ribociclib vs placebo with goserelin and tamoxifen or a non-steroidal aromatase inhibitor in premenopausal women with hormone receptor-positive, HER2-negative advanced breast cancer: results from the randomized phase III MONALEESA-7 trial (Abstract GS2-05). Paper presented at: 40th San Antonio Breast Cancer Symposium; December 6, 2017; San Antonio, TX. 58. Hortobagyi GN, Stemmer SM, Burris HA, et al. Ribociclib as first-line therapy for HR-positive, advanced breast cancer. N Engl J Med 2016;375(18):1738–1748. 59. Finn RS, Martin M, Rugo HS, et al. Palbociclib and letrozole in advanced breast cancer. N Engl J Med 2016;375(20):1925–1936. 60. Goetz MP, Toi M, Campone M, et al. MONARCH 3: abemaciclib as initial therapy for advanced breast cancer. J Clin Oncol 2017;35(32):3638–3646. 61. Dickler MN, Tolaney SM, Rugo HS, et al. MONARCH 1, a phase 2 study of abemaciclib, a CDK4 and CDK6 inhibitor, as a single agent, in patients with refractory HR+/HER2-metastatic breast cancer. Clin Cancer Res 2017;23(17):5218–5224. 62. Pagani O, Regan MM, Walley BA, et al. Adjuvant exemestane with ovarian suppression in premenopausal breast cancer. N Engl J Med 2014;371(2):107–118. 63. Francis PA, Regan MM, Fleming GF, et al. Adjuvant ovarian suppression in premenopausal breast cancer. N Engl J Med 2015;372(5):436–446. 64. Gnant M, Mlineritsch B, Stoeger H, et al. Zoledronic acid combined with adjuvant endocrine therapy of tamoxifen versus anastrozol plus ovarian function suppression in premenopausal early breast cancer: final analysis of the Austrian Breast and Colorectal Cancer Study Group Trial 12. Ann Oncol 2014;26(2):313–320. 65. Hussain M, Tangen CM, Berry DL, et al. Intermittent versus continuous androgen deprivation in prostate cancer. N Engl J Med 2013;368(14):1314–1325. 66. Plosker GL, Brogden RN. Leuprorelin. A review of its pharmacology and therapeutic use in prostatic cancer, endometriosis and other sex hormone-related disorders. Drugs 1994;48(6):930–967. 67. Brogden RN, Faulds D. Goserelin. A review of its pharmacodynamic and pharmacokinetic properties and

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therapeutic efficacy in prostate cancer. Drugs Aging 1995;6(4):324–343. 68. Steinberg M. Degarelix: a gonadotropin-releasing hormone antagonist for the management of prostate cancer. Clin Ther 2009;31(Pt 2):2312–2331. 69. Brogden RN, Chrisp P. Flutamide: a review of its pharmacodynamic and pharmacokinetic properties, and therapeutic use in advanced prostatic cancer. Drugs Aging 1991;1(2):104–115. 70. Schellhammer P, Sharifi R, Block N, et al. A controlled trial of bicalutamide versus flutamide, each in combination with luteinizing hormone-releasing hormone analogue therapy, in patients with advanced prostate cancer. Casodex Combination Study Group. Urology 1995;45(5):745–752. 71. Cockshott ID. Bicalutamide: clinical pharmacokinetics and metabolism. Clin Pharmacokinet 2004;43(13):855– 878. 72. de Bono JS, Logothetis CJ, Molina A, et al. Abiraterone and increased survival in metastatic prostate cancer. N Engl J Med 2011;364(21):1995–2005. 73. Fizazi K, Tran N, Fein L, et al. Abiraterone plus prednisone in metastatic, castration-sensitive prostate cancer. N Engl J Med 2017;377(4):352–360. 74. James ND, de Bono JS, Spears MR, et al. Abiraterone for prostate cancer not previously treated with hormone therapy. N Engl J Med 2017;377(4):338–351. 75. Wang L, Dehm SM, Hillman DW, et al. A prospective genome-wide study of prostate cancer metastases reveals association of wnt pathway activation and increased cell cycle proliferation with primary resistance to abiraterone acetate–prednisone. Ann Oncol 2018;29(2):352–360. 76. Dehm SM, Schmidt LJ, Heemers HV, et al. Splicing of a novel androgen receptor exon generates a constitutively active androgen receptor that mediates prostate cancer therapy resistance. Cancer Res 2008;68(13):5469–5477. 77. Watson PA, Chen YF, Balbas MD, et al. Constitutively active androgen receptor splice variants expressed in castration-resistant prostate cancer require full-length androgen receptor. Proc Natl Acad Sci U S A 2010;107(39):16759–16765. 78. Antonarakis ES, Lu C, Wang H, et al. AR-V7 and resistance to enzalutamide and abiraterone in prostate cancer. N Engl J Med 2014;371(11):1028–1038. 79. Kohli M, Ho Y, Hillman DW, et al. Androgen receptor variant AR-V9 is coexpressed with AR-V7 in prostate cancer metastases and predicts abiraterone resistance. Clin Cancer Res 2017;23(16):4704–4715. 80. Goldberg T, Berrios-Colon E. Abiraterone (Zytiga), a novel agent for the management of castration-resistant prostate cancer. P T 2013;38(1):23–26. 81. Tran C, Ouk S, Clegg NJ, et al. Development of a second-generation antiandrogen for treatment of advanced prostate cancer. Science 2009;324(5928):787–790. 82. Beer TM, Armstrong AJ, Rathkopf DE, et al. Enzalutamide in metastatic prostate cancer before chemotherapy. N Engl J Med 2014;371(5):424–433. 83. Scher HI, Beer TM, Higano CS, et al. Antitumour activity of MDV3100 in castration-resistant prostate cancer: a phase 1–2 study. Lancet 2010;375(9724):1437–1446. 84. Rathkopf DE, Antonarakis ES, Shore ND, et al. Safety and antitumor activity of apalutamide (ARN-509) in metastatic castration-resistant prostate cancer with and without prior abiraterone acetate and prednisone. Clin Cancer Res 2017;23(14):3544–3551. 85. Fizazi K, Massard C, Bono P, et al. Activity and safety of ODM-201 in patients with progressive metastatic castration-resistant prostate cancer (ARADES): an open-label phase 1 dose-escalation and randomised phase 2 dose expansion trial. Lancet Oncol 2014;15(9):975–985. 86. Kammerer RC, Merdink JL, Jagels M, et al. Testing for fluoxymesterone (Halotestin) administration to man: identification of urinary metabolites by gas chromatography-mass spectrometry. J Steroid Biochem 1990;36(6):659–666. 87. Ingle JN, Ahmann DL, Green SJ, et al. Randomized clinical trial of diethylstilbestrol versus tamoxifen in postmenopausal women with advanced breast cancer. N Engl J Med 1981;304(1):16–21. 88. Ellis MJ, Gao F, Dehdashti F, et al. Lower-dose vs high-dose oral estradiol therapy of hormone receptor-positive, aromatase inhibitor-resistant advanced breast cancer: a phase 2 randomized study. JAMA 2009;302(7):774–780. 89. Loprinzi CL, Michalak JC, Schaid DJ, et al. Phase III evaluation of four doses of megestrol acetate as therapy for patients with cancer anorexia and/or cachexia. J Clin Oncol 1993;11(4):762–767. 90. Loprinzi CL, Michalak JC, Quella SK, et al. Megestrol acetate for the prevention of hot flashes. N Engl J Med 1994;331(6):347–352. 91. Lundgren S. Progestins in breast cancer treatment: a review. Acta Oncol 1992;31(7):709–722. 92. Rinke A, Müller HH, Schade-Brittinger C, et al. Placebo-controlled, double-blind, prospective, randomized study

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on the effect of octreotide LAR in the control of tumor growth in patients with metastatic neuroendocrine midgut tumors: a report from the PROMID Study Group. J Clin Oncol 2009;27(28):4656–4663. 93. Caplin ME, Pavel M, C´wikła JB, et al. Lanreotide in metastatic enteropancreatic neuroendocrine tumors. N Engl J Med 2014;371(3):224–233. 94. Harris A. Somatostatin and somatostatin analogues: pharmacokinetics and pharmacodynamic effects. Gut 1994;35(Suppl 3):S1–S4.

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31

Monoclonal Antibodies Hossein Borghaei, Matthew K. Robinson, Gregory P. Adams, and Louis M. Weiner

INTRODUCTION Antibody-based therapeutics are important components of the cancer therapeutic armamentarium. Early antibody therapy studies attempted to explicitly target cancers based on the structural and biologic properties that distinguish neoplastic cells from their normal counterparts. The immunogenicity and inefficient effector functions of the first-generation murine monoclonal antibodies (MAbs) that were evaluated in clinical trials limited their effectiveness.1 Patients developed human antimouse antibody (HAMA) responses against the therapeutic agents that rapidly cleared it from the body and limited the number of times the therapy could be administered. The development of engineered chimeric, humanized, and fully human MAbs has identified a number of important and useful applications for antibody-based cancer therapy. Currently, there are 29 MAbs and MAb-conjugates approved by the U.S. Food and Drug Administration (FDA) for the treatment of cancer (Table 31.1), and many more are under evaluation in late-stage clinical trials.2 Antibodies provide an important means by which to exploit the immune system by specifically recognizing and directing antitumor responses. Antibodies are produced by B cells and arise in response to exposures to a variety of structures, termed antigens, as a result of a series of recombinations of V, D, and J germline genes. Immunoglobulin (Ig) G molecules are most commonly employed as the working backbones of current therapeutic MAbs, although various other isotypes of antibodies have specialized functions (e.g., IgA molecules play important roles in mucosal immunity, IgE molecules are involved in anaphylaxis). The advent of hybridoma technology by Köhler and Milstein3 made it possible to produce large quantities of antibodies with high purity and monospecificity for a single binding region (epitope) on an antigen. The mechanisms that antibody-based therapeutics employ to elicit antitumor effects include focusing components of the patient’s immune system to attack tumor cells4 and methods to alter signal transduction pathways that drive tumor progression.5 Antibody-based conjugates employ the targeting specificity of antibodies to deliver toxic compounds, such as chemotherapeutics, specifically to the tumor sites.

IMMUNOGLOBULIN STRUCTURE Structural and Functional Domains An IgG molecule is typically divided into three domains consisting of two identical antigen-binding (Fab) domains connected to an effector or Fc domain by a flexible hinge sequence. Figure 31.1 shows the structure of an IgG molecule. IgG antibodies are composed of two identical light chains and two identical heavy chains, with the chains joined by disulfide bonds, resulting in a bilaterally symmetrical complex. The Fab domains mediate the binding of IgG molecules to their cognate antigens and are composed of an intact light chain and half of a heavy chain. Each chain in the Fab domain is further divided into variable and constant regions, with the variable region containing hypervariable or complementarity determining regions (CDRs) in which the antigen-contact residues reside. The light and heavy chain variable regions each contain three CDRs (CDR1, CDR2, and CDR3). All six CDRs form the antigen-binding pocket and are collectively defined in immunologic terms as the idiotype of the antibody. In the majority of cases, the variable heavy chain CDR3 plays a dominant role in binding.6 The different isotypes of Igs are defined by the structure and function of their Fc domains. The Fc domain, composed of the CH2 and CH3 regions of the antibody’s heavy chains, is the critical determinant of how an antibody mediates effector functions, transports across cellular barriers, and persists in circulation.7

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MODIFIED ANTIBODY-BASED MOLECULES Advances in antibody engineering and molecular biology have facilitated the development of many novel antibody-based structures with unique physical and pharmacokinetic properties (see Fig. 31.1). These include chimeric human-murine antibodies with human-constant regions and murine-variable regions,8 humanized antibodies in which murine CDR sequences have been grafted into human IgG molecules, and entirely human antibodies derived from human hybridomas and from transgenic mice expressing human immunoglobulin genes.9 The World Health Organization’s International Nonproprietary Names (INN) for pharmaceuticals was updated in 2014 to incorporate the increasing diversity of engineered constructs (Table 31.2). Engineering has also facilitated the development of antibody-based fragments. In addition to the classic, enzymatically derived Fab and F(ab′)2 molecules, a plethora of promising IgG derivatives have been developed that retain antigen-binding properties of intact antibodies (see Fig. 31.1; for review, see Robinson et al.10). The basic building block for these molecules is the 25 kDa, monovalent single-chain Fv (scFv) that is composed of the variable domains (VH and VL) of an antibody fused together with a short peptide linker. Novel, bispecific antibody-based structures can facilitate binding to two tumor antigens or bridge tumor cells with immune effector cells to focus antibody-dependent cellmediated cytotoxicity (ADCC) or killing by T cells. Examples of the latter mechanism include small scFv-based bispecific T-cell engagers (BiTE) such as the anti-CD3/anti-CD19 molecule blinatumomab.11 Both classes of bispecifics endow selectivity and targeting properties that are not obtainable with natural antibody formats.

FACTORS REGULATING ANTIBODY-BASED TUMOR TARGETING Antibody Size Nonuniform distribution of systemically administered antibody is generally observed in biopsied specimens of solid tumors. Heterogeneous tumor blood supply limits uniform antibody delivery to tumors, and elevated interstitial pressures in the center of tumors oppose inward diffusion. This high interstitial pressure slows the diffusion of molecules from their vascular extravasation site in a size-dependent manner. The relatively large transport distances in the tumor interstitium also substantially increase the time required for large IgG macromolecules to reach target cells.12 TABLE 31.1

Antibodies Approved by the U.S. Food and Drug Administration for the Treatment of Cancer Origin

Isotype (Conjugate)

Indication

Target

Initial Approval

Rituximab (Rituxan)

Chimeric

IgG1

NHL

CD20

1997

Trastuzumab (Herceptin)

Humanized

IgG1

BrCa

HER2

1998

Alemtuzumab (Campath-1H)

Humanized

IgG1

CLL

CD52

2001

Cetuximab (Erbitux)

Chimeric

IgG1

CRC, SCCHN

EGFR

2004

Bevacizumab (Avastin)

Humanized

IgG1

CRC, NSCLC, RCC, GBM

VEGF

2004

Panitumumab (Vectibix)

Human (XenoMouse)

IgG2

CRC

EGFR

2006

Ofatumumab (Arzerra)

Human (XenoMouse)

IgG1

CLL

CD20

2009

Denosumab (Prolia/Xgeva)

Human

IgG2

Metastasis-related SREs, ADT/AIassociated osteoporosis, GCT

RANKL

2010

Pertuzumab (Perjeta)

Humanized

IgG1

BrCa

HER2

2012

Obinutuzumab (Gazyva)

Humanized

IgG1

CLL, FL

CD20

2013

Blinatumomab (Blincyto)

Murine

BiTE

ALL

CD3/CD19

2014

Ramucirumab (Cyramza)

Human

IgG1

Gastric, colorectal, lung

VEGFR2

2014–

Generic Name (Trade Name) Unconjugated MAbs

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2015 Daratumumab (Darzalex)

Human

IgG1

MM

CD38

2015

Elotuzumab (Empliciti)

Humanized

IgG1

MM

SLAMF7

2015

Necitumumab (Portrazza)

Human

IgG1

NSCLC

EGFR

2015

Dinutuximab (Unituxin)

Chimeric

IgG1

Neuroblastoma

GD2

2015

Olaratumab (Latruvo)

Human

IgG1

PDGFRα

Sarcoma

2016

Gemtuzumab ozogamicin (Mylotarg)

Humanized

IgG4 (calicheamicin)

AML

CD33

2000a

Ibritumomab tiuxetan (Zevalin)

Murine

IgG1 (90Y)

NHL

CD20

2002

Tositumomab (Bexxar)

Murine

IgG2A (131I)

NHL

CD20

2003

Brentuximab vedotin (Adcetris)

Chimeric

IgG1 (MMAE)

HL, sALCL

CD30

2011

Ado-trastuzumab emtansine (Kadcyla)

Humanized

IgG1 (DM1)

BrCa

HER2

2013

Inotuzumab ozogamicin (Besponsa)

Humanized

IgG4 (calicheamicin)

ALL

CD22

2017

Immunoconjugates

aWithdrawn from the U.S. market in June 2010. Reapproved in 2017.

MAbs, monoclonal antibodies; Ig, immunoglobulin; NHL, non-Hodgkin lymphoma; BrCa, breast cancer; HER2, human epidermal growth factor receptor 2; CLL, chronic lymphocytic leukemia; CRC, colorectal cancer; SCCHN, squamous cell carcinoma of head and neck; EGFR, epidermal growth factor receptor; NSCLC, non–small-cell lung cancer; RCC, renal cell carcinoma; GBM, glioblastoma multiforme; VEGF, vascular endothelial growth factor; SREs, skeletal-related events; ADT, androgen deprivation therapy; AI, aromatase inhibitor; GCT, giant cell tumor; RANKL, RANK ligand; FL, follicular lymphoma; BiTE, bispecific T-cell engagers; ALL, acute lymphoblastic leukemia; VEGFR2, vascular endothelial growth factor receptor 2; MM, multiple myeloma; SLAMF7, signaling lymphocytic activation molecule F7; PDGFRα, platelet-derived growth factor receptor α; AML, acute myelogenous leukemia; 90Y, yttrium-90; 131I, iodine-131; MMAE, monomethyl auristatin E; HL, Hodgkin lymphoma; sALCL, systemic anaplastic large-cell lymphoma.

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Figure 31.1 Structure of an immunoglobulin (Ig) G. C, constant; V, variable; H, heavy chain; L, light chain.

Tumor Antigens Access to the target antigen is undoubtedly a critical determinant of therapeutic effect of antibody-based applications. Such access is regulated by the heterogeneity of antigen expression by tumor cells. Shed antigen in the serum, tumor microenvironment, or both may saturate the antibody’s binding sites and prevent binding to the cell surface. Alternatively, a rapid internalization of an antibody–antigen complex, although critical for antibody– drug conjugates (ADCs), may deplete the quantity of cell surface MAb capable of initiating ADCC or cytotoxic signal transduction events. Finally, target antigens are normally tumor associated rather than tumor specific. Tumor-specific antigens are both highly desirable and rare. Typically, such antigens arise as a result of unique tumor-based genetic recombinations, such as clonal Ig idiotypes expressed on the surface of B-cell lymphomas.13 TABLE 31.2

Rules for Naming Monoclonal Antibodies for the Treatment of Cancer The International Nonproprietary Names (INN) for monoclonal antibodies are composed of “stems” that indicate their origin, specificity, and modifications. The names include a random prefix to provide distinction from other names, a substem indicating the target specificity (-t[u]- for tumor), a substem indicating the species of origin (see the following), and a suffix (-mab) that indicates the presence of an immunoglobulin variable domain. Substem Indication of the Species on Which the Immunoglobulin Sequence Is Based -o-

Mouse

-xi-

Chimeric

-zu-

Humanized

-xizu-

Chimeric/humanized

-u-

Human

Antibody affinity for its target antigen has complex effects on tumor targeting. The binding-site barrier hypothesis postulates that antibodies with extremely high affinity for target antigen would bind irreversibly to the first antigen encountered upon entering the tumor, which would limit the diffusion of the antibody into the tumor and accumulate instead in regions surrounding the tumor vasculature.14,15 Similarly, in tumor spheroids, the in vitro penetration of engineered antibodies is primarily limited by internalization and degradation.16 The valence of an antibody molecule can increase the functional affinity of the antibody through an avidity effect.17

Half-Life/Clearance Rate The concentration of intact IgG in mammalian serum is maintained at constant levels with half-lives of IgGs measured in days. This homeostasis is regulated in part by the major histocompatibility complex (MHC) class I– related Fc receptor, FcRn (n = neonatal), a saturable, pH-dependent salvage mechanism that regulates quality and quantity of IgG in serum. This mechanism can be exploited via mutations in the Fc portion of an IgG to modulate IgG pharmacokinetics.18 Multiple strategies have been developed to increase the serum persistence of antibodybased fragments and other classes of protein therapeutics.

Glycosylation IgGs undergo N-linked glycosylation at the conserved Asn residue at position 297 within the CH2 domain of the constant region. Glycosylation status of the residue has long been known to impact the ability of IgGs to bind effector ligands such as Fcγ receptors (FcγR) and C1q, which, in turn, affects their ability to participate in Fcmediated functions such as ADCC and complement-dependent cytotoxicity (CDC).19–21 The glycosylation of MAbs can be altered to increase ADCC by producing them in a cell line engineered to express β(1,4)-Nacetylglucosaminyltransferase III (GnTIII), the enzyme required to add the bisecting GlcNAc residues. Defucosylation of antibody Fc domains is also associated with enhanced ADCC, and in a recently completed multicenter phase II trial of a defucosylated anti-CC chemokine receptor 4 (CCR4), MAb was associated with meaningful antitumor activity, including complete responses and enhanced progression-free survival (PFS).22

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UNCONJUGATED ANTIBODIES The majority of MAbs approved for clinical use display intrinsic antitumor effects that are mediated by one or more of the following mechanisms.

Cell-Mediated Cytotoxicity As components of the immune system, effector cells such as natural killer (NK) cells and monocytes/macrophages represent natural lines of defense against oncologically transformed cells. These effector cells express FcγR on their cell surfaces, which interact with the Fc domain of IgG molecules. This family is composed of three classes (types I, II, and III) that are further divided into subclasses (IIa/IIb and IIIa/IIIb).23 Recognition of transformed cells by immune effector cells leads to cell-mediated killing through processes such as ADCC and phagocytosis, as shown in Figure 31.2. Clinical results support the idea that ADCC, mediated through recognition of IgGopsonized tumor cells by the low affinity FcγRIIIa, can play a role in the efficacy of antibody-based therapies. Naturally occurring polymorphisms in FcγRs alter their affinity for human IgG1 and have been linked to clinical response.24,25 A polymorphism in the FCGR3A gene results in either a valine or phenylalanine at position 158 of FcγRIIIa. Human IgG1 binds more strongly to FcγRIIIa-158V than FcγRIIIa-158F and likewise to NK cells from individuals that are either homozygous for 158V or heterozygous for this polymorphism.26 Results from a 1,251patient cohort in the NSABP B-31 trial demonstrated that patients either homozygous or heterozygous for the FcγRIIIa-158v polymorphism received greater benefit from the addition of trastuzumab to chemotherapy (hazard ratio, 0.31; 95% confidence interval [CI], 0.22 to 0.43; P < .001) than patients homozygous for the FcγRIIIa-158F polymorphism (hazard ratio, 0.71; 95% CI, 0.51 to 1.01; P =1 .05).27 Antibody engineering has facilitated the development and clinical testing of multiple approaches to enhance antibody-dependent redirection of immune effector cells. One such approach is modifying the Fc domain of IgGs to optimize engagement of FcγR. This is based on the findings of Shields et al.,18 who performed a series of mutagenesis experiments to map the residues required for IgG1-FcγR interaction. Antibodies such as ocrelizmab,28 a humanized version of rituximab, and third-generation anti-CD20 antibodies, such as ocaratuzumab,29 which has been engineered to have increased binding to low-affinity FcγRIIIa variants, have demonstrated clinical activity in patient populations refractory to rituximab treatment. An alternative to modifying the Fc region of MAbs is to create bispecific antibodies (bsAbs) that recognize both a tumor-associated antigen and a trigger antigen present on the surface of an immune effector cell.30 In addition to having flexible choices of cytotoxic trigger molecules, bsAbs can be designed to recruit effector function in the presence of excess IgG, have varied pharmacokinetics, and can be tailored such that the affinity of the bsAb matches effector cell characteristics. Examples include the classic, IgG-like, anti–human epidermal growth factor receptor 2 (HER2)directed bsAbs, 2B1 and MDX-H21,31,32 which have been tested in the clinical setting. BiTE antibodies represent a novel class of bispecific, scFv antibodies.33 The anti-CD19/CD3 BiTE blinatumomab34 represents the first of this class of molecules to obtain FDA approval.

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Figure 31.2 Antibody-dependent cellular cytotoxicity. The antibody engages the tumor antigen, and the Fc domain binds to cellular Fc receptors to bridge effector and target cells. This bridging induces effector cell activation, resulting in natural killer cell cytotoxicity or phagocytosis by neutrophils, monocytes, or macrophages.

Complement-Dependent Cytotoxicity In addition to cell-mediated killing (see previous discussion), MAbs can recruit the complement cascade to kill cells via CDC. Although IgM is the most effective isotype for complement activation, it is not widely used in clinical oncology. Similar to ADCC, the human IgG subclass used to construct a therapeutic MAb dictates its ability to elicit CDC; IgG1 is extremely efficient at fixing complement, in contrast to IgG2 and IgG4. Antibodies activate complement through the classical pathway, by engaging multiple C1q to trigger activation of a cascade of serum proteases, which kill the antibody-bound cells.35 The anti-CD20 MAbs rituximab and ofatumumab have been found to depend in part on CDC for in vivo efficacy.36,37 Antibody engineering approaches have identified residues in the CH2 domain of the Fc region that either suppress or enhance the ability of rituximab to bind C1q and activate CDC. Expansion on this line of investigation led to development of engineered Fc domains capable of fixing complement without engaging FcγRs.38 These Fc domains represent models to directly test the in vivo contribution of CDC to preclinical therapeutic activity. The ability to manipulate complement fixation through engineering approaches warrants further in vivo testing to determine the impact of these changes on the efficacy and toxicity of MAbs in the clinical setting.

ALTERING SIGNAL TRANSDUCTION Growth factor receptors represent a well-established class of targets for therapeutic intervention. Normal signaling through these receptors often leads to mitogenic and prosurvival responses. Unregulated signaling, as seen in a number of common cancers due to receptor overexpression, promotes tumor cell growth and insensitivity to chemotherapeutic agents. Clinically relevant MAbs can modulate signaling through their target receptors to normalize cell growth rates and sensitize tumor cells to cytotoxic agents. Cetuximab and panitumumab bind to the

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epidermal growth factor receptor (EGFR) and physically block ligand binding and prevent the receptor from assuming the extended conformation required for dimerization.39 Pertuzumab binds to the dimerization domain of HER2, thereby sterically inhibiting subsequent receptor heterodimerization with other ligand-bound family members.40 Oligoclonal mixtures of antibodies, which either target multiple epitopes on the same antigen41 or multiple antigens,42 represent approaches to enhance signaling inhibition. Clinical validation of these approaches is ongoing. Alternatively, signaling through growth factor receptors can be indirectly modified by MAbs that bind to activating ligands, as is seen with the anti–vascular endothelial growth factor (VEGF) MAb, bevacizumab.43

IMMUNOCONJUGATES MAbs that are not capable of directly eliciting antitumor effects, either by altering signal transduction or by directing immune system cells, can still be effective against tumors by delivering cytotoxic payloads. MAbs have been employed to deliver a wide variety of agents, including chemotherapy, toxins, radioisotopes, and cytokines (for review, see Adams and Weiner44). In theory, the appropriate combination of toxic agents and MAbs could lead to a synergistic effect. For example, delivery of a therapeutic radioisotope by a MAb would be significantly enhanced if, by binding to its target antigen, the MAb also activated a signaling event that increased the target cell’s sensitivity to ionizing radiation. Catalytic toxins derived from plants catalytic toxins derived from plants (e.g., ricin) and microorganisms (e.g., Pseudomonas) represent two classes of cytotoxic agent that have been investigated for their utility in immunoconjugate strategies.45 Although there are promising preclinical studies, few successful clinical trials have been reported using this approach. In a phase I clinical trial in hairy cell leukemia patients who were resistant to cladribine, 11 of 16 patients exhibited complete remissions with minimal side effects with an anti-CD22 immunotoxin with a truncated form of Pseudomonas exotoxin.46 Clinical trials with other immunotoxins have been associated with unacceptable neurotoxicity47 and life-threatening vascular leak syndrome.48 Immunocytokine fusions have also been investigated as an approach to direct the patient’s immune response to their own tumor.49 A number of cytokines have been incorporated into antibody-based constructs, including interleukin-2 (IL-2), interferon γ (IFN-γ), tumor necrosis factor α (TNF-α), VEGF, and IL-12.50

Antibody–Drug Conjugates The first ADC, gemtuzumab ozogamicin (Mylotarg), was approved by the FDA in 2000 for the treatment of patients with relapsed CD33+ acute myeloid leukemia but was voluntarily withdrawn from the U.S. market by its manufacturer in 2010 after a confirmatory phase III trial (SWOG S0106) recommended, based on results of a planned interim analysis, that Mylotarg randomizations be terminated due to a lack of efficacy in the presence of enhanced toxicity. Although two additional randomized trials suggested that some patient populations may benefit from Mylotarg therapy, the drug was voluntarily withdrawn from the market in 2010 in the United States. However, in 2017, the FDA approved this drug in combination with chemotherapy for adult patients with acute myelogenous leukemia (AML) based on the ALFA-0701 trial. This was an open-label, multicenter phase III trial with 280 patients with newly diagnosed AML between the ages of 50 and 70 years who received standard daunorubicin and cytarabine therapy with or without gemtuzumab at a dose of 3 mg/m2. The group that received gemtuzumab ozogamicin had a 2-year event-free survival of 40.8% versus 17.1% in the chemotherapy-alone group, leading to this approval. Overall survival favored the gemtuzumab arm.51 The indication includes a box warning for hepatotoxicity. The majority of ADCs under development employ potent cytotoxic agents that block the polymerization of tubulin (e.g., auristatins or maytansines) or damage DNA (e.g., calicheamicins or pyrrolobenzodiazepines) by employing a variety of linkers and conjugation strategies.52 A variety of ADCs specific for a wide range of oncology targets are currently in clinical evaluation. The majority of these employ auristatins or maytansines as their payloads. Early observations suggest that cumulative, dose-related peripheral sensory neuropathy can result when auristatins are conjugated to an antibody via a cleavable linker, and dose-limiting thrombocytopenia can result when auristatins and maytansinoids are conjugated to the antibody via an uncleavable linker. Three ADCs are now approved for use in clinical practice. Ado-trastuzumab emtansine (T-DM1, Kadcyla), an ADC composed of the anti-HER2 MAb trastuzumab linked to DM1,53 is now approved for the treatment of patients with refractory HER2/neu-expressing breast cancers. The other, brentuximab vedotin (SGN-35, Adcetris),

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is an ADC consisting of the anti-CD30 chimeric MAb cAC10 that is linked to three to five molecules of the microtubule-disrupting agent monomethyl auristatin E (MMAE). At this point, this drug is approved for use in patients with recurrent systemic anaplastic large cell lymphoma.54 Inotuzumab ozogamicin is another ADC that was recently approved for treatment of patients with acute lymphoblastic leukemia (ALL). This drug is directed against CD22+ B cell found in patients with B-cell ALL. This drug is based on a similar platform as used with another ADC, gemtuzumab ozogamicin. The clinical data associated with these ADCs are discussed in subsequent sections of this chapter. Antibodies also can be used to target liposome-encapsulated drugs55 and other cytotoxic agents, such as antisense RNA or radionuclides to tumors.

Radioimmunoconjugates Two anti-CD20 radioimmunoconjugates have been FDA approved for radioimmunotherapy (RIT) of nonHodgkin lymphoma. Ibritumomab (Zevalin) and tositumomab (Bexxar) are murine MAbs labeled with yttrium-90 (90Y) and iodine-131 (131I), respectively. Both are associated with impressive clinical efficacy.56 Although these radioimmunoconjugates are effective therapeutics, cumbersome logistics surrounding their administration have significantly limited their use. Despite significant preclinical evidence supporting the use of RIT for solid malignancies, clinical results have not demonstrated consistent antitumor activity.

ANTIBODIES APPROVED FOR USE IN SOLID TUMORS Trastuzumab Trastuzumab (Herceptin) is a humanized IgG157 that targets domain IV of the HER2/ErbB2 member of the EGFR/ErbB family of receptor tyrosine kinases. Gene amplification as judged by fluorescence in situ hybridization (FISH) with concomitant overexpression of HER2 protein measured by immunohistochemistry (IHC) is seen in approximately 25% of breast cancers.58,59 HER2 amplification and overexpression is now recognized to be a critical driver in a subset (7% to 34%) of gastric cancers.60 Trastuzumab inhibits tumor cell growth by binding to HER2 and blocking the unregulated HER2 signaling that is associated with high-level overexpression. Trastuzumab became the first FDA-approved MAb for the treatment of solid tumors61,62 and for postsurgical adjuvant therapy.63,64 Myocardial dysfunction, seen with anthracycline therapy, is observed with increased frequency in patients receiving antibody alone65 or with doxorubicin or epirubicin. Recognition of HER2 as a driver in a subset of gastric cancers led to a randomized, phase III trial (ToGA) that investigated the addition of trastuzumab to standard-of-care chemotherapy and showed increased median overall survival with higher levels of HER2 expression.66

Pertuzumab Pertuzumab (Perjeta) is a humanized IgG1 MAb that binds to domain II of HER2 and blocks ligand-dependent dimerization of HER2 with other members of the EGFR family.67 Pertuzumab, in combination with trastuzumab and docetaxel, is approved for use as first-line therapy in HER2-positive metastatic breast cancer patients. Use of the combination is also approved for the treatment of HER2-positive, locally advanced, inflammatory, or high-risk early breast cancer (>2 cm node negative or node positive) in the neoadjuvant setting.68 FDA approval of pertuzumab was based on results of a phase III trial (CLEOPATRA) of 808 patients with locally recurrent, unresectable, or metastatic breast cancer randomized to receive trastuzumab plus docetaxel with or without the addition of pertuzumab. Pertuzumab increased PFS, with an improved overall survival69 and acceptable toxicity. Accelerated approval was granted for use of pertuzumab in combination with trastuzumab and docetaxel for the neoadjuvant treatment of high-risk early-stage breast cancer. This approval was based on results from a four-arm, open-label phase II study of 417 patients randomized to receive trastuzumab plus docetaxel, pertuzumab plus docetaxel, pertuzumab plus trastuzumab, or the triple combination. The triple combination improved the pathologic complete response (pCR) rate by 17.8% over the trastuzumab plus docetaxel arm (39.3% versus 21.5%) in the pertuzumab arm.70

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Cetuximab Cetuximab (Erbitux) targets the EGFR. This chimeric IgG1 binds to domain III of the EGFR, with roughly a 10fold higher affinity than either EGF or transforming growth factor α (TGF-α) ligands and thereby inhibits ligandinduced activation of this tyrosine kinase receptor. Cetuximab may also function to downregulate EGFRdependent signaling by stimulating EGFR internalization. Cetuximab is approved for the treatment of colorectal cancer and, more recently, for the treatment of squamous cell cancer of the head and neck (SCCHN). The efficacy and safety of cetuximab against colorectal cancer was demonstrated alone and in combination with irinotecan in a phase II, multicenter, randomized, and controlled trial of 329 patients.71 The combination of irinotecan plus cetuximab increased both the overall response and the median duration of response as compared to cetuximab alone. Additionally, patients with irinotecan-refractory disease responded to treatment with the combination regimen. Recent studies in patients with colorectal cancers have indicated that patients with KRAS mutations in codon 12 or 13 should not receive anti-EGFR therapy.72 An international, multicenter, phase III trial comparing definitive radiotherapy to radiotherapy plus cetuximab in SCCHN demonstrated that EGFR blockade with radiotherapy significantly reduced the risk of locoregional failure by 32% and the risk of death by 26%. In advanced stage non–small-cell lung cancer (NSCLC) expressing EGFR, the combination of cetuximab and standard doublet chemotherapy (cisplatin plus vinorelbine) was studied in a prospective randomized phase III trial. The addition of cetuximab was associated with a slight, but statistically significant, benefit in overall survival over chemotherapy alone. A similar study using the carboplatin plus paclitaxel backbone in combination with cetuximab did not meet its primary end point of improved PFS, although cetuximab-treated patients exhibited higher objective response rates.73,74 Therefore, the benefit of adding cetuximab to standard chemotherapy for patients with advanced NSCLC is unclear.

Panitumumab Panitumumab (Vectibix) is a fully human IgG2 MAb that binds to EGFR. Similar to cetuximab, panitumumab inhibits EGFR activation by blocking the binding of EGF and TGF-α. However, it does so by binding to EGFR with a higher affinity than cetuximab (5 × 10−11 M versus 1 × 10−10 M). As previously mentioned, the IgG2 class of antibodies does not induce activation of the immune system cell via the Fc-receptor mechanism, so the primary action of panitumumab appears to be interference with EGFR–ligand interactions. A phase III trial of 463 patients with metastatic colorectal cancer compared panitumumab plus best supportive care (BSC) to BSC alone demonstrated a partial-response rate of 8% and a stable-disease rate of 28% compared with a 10% stable-disease rate in the BSC arm of the study.75 As with cetuximab, patients with metastatic colorectal cancers who have KRAS mutations in codons 12 or 13 are not routinely offered therapy with panitumumab.

Necitumumab Necitumumab is a recombinant human IgG1 MAb that binds the EGFR. In combination with cisplatin and gemcitabine, this drug is approved for treatment of squamous NSCLC based on the results of the SQUIRE study. In this randomized phase III study, patients with metastatic squamous cell carcinoma of the lung with no prior therapy were assigned to treatment with a standard platinum doublet chemotherapy versus the same chemotherapy backbone plus necitumumab. A statistically significant 1.6-month improvement in the primary end point of overall survival was observed with the addition of this antibody, with a higher rate of deaths from cardiopulmonary arrest in the necitumumab arm and a higher rate of hypomagnesemia.76 Necitumumab received orphan drug designation by the FDA in November 2015.

Bevacizumab Bevacizumab (Avastin or rhuMAb VEGF) is a humanized MAb targeting VEGF. VEGF is a critical determinant of tumor angiogenesis, a process that is a necessary component of tumor invasion, growth, and metastasis. VEGF expression by invasive tumors has been shown to correlate with vascularity and cellular proliferation and is prognostic for several human cancers. Interestingly, the inhibition of VEGF signaling via bevacizumab treatment may normalize tumor vasculature, promoting a more effective delivery of chemotherapy agents.77 Bevacizumab is approved for use as a first-line therapy for metastatic colorectal cancer and NSCLC when given in combination with appropriate cytotoxic chemotherapy regimens. Phase III clinical trials leading to the approval of

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bevacizumab for the treatment of colorectal cancer demonstrated improved response rates from 35% to 45% compared to fluorouracil (5-FU)-based chemotherapy alone. Enhanced response durations and improved patient survival were seen in patients treated with chemotherapy plus bevacizumab as compared to patients receiving chemotherapy alone.78 A survival benefit was also seen in the setting of NSCLC. A randomized phase III trial (ECOG 4599) of paclitaxel and carboplatin with or without bevacizumab in patients with advanced nonsquamous NSCLC showed a significant improvement in median survival for patients in the bevacizumab arm,79 with significantly higher response rates. A higher incidence of bleeding was associated with bevacizumab therapy. A total of 5 of 10 treatment-related deaths occurred as a result of hemoptysis, all in the bevacizumab arm. Studies in metastatic breast cancer have been less encouraging.80,81 Bevacizumab has not demonstrated activity in the adjuvant colorectal and breast cancer settings,82,83 but it is approved for the management of recurrent glioblastomas based on results of phase II studies.84

Ado-Trastuzumab Emtansine Ado-trastuzumab emtansine (T-DM1, Kadcyla) is an ADC composed of the anti-HER2 MAb trastuzumab linked to DM1, a highly potent derivative of maytansine, through a stable thioether linker. Based on two single-agent phase II trials of T-DM1 that demonstrated single-agent activity in the setting of metastatic breast cancer, two separate phase III studies were conducted. The 991 EMILIA trial demonstrated that T-DM1 significantly prolongs both PFS and overall survival as compared to a regimen of lapatinib plus capecitabine when used in the setting of metastatic breast cancer that had progressed after treatment with trastuzumab plus a taxane,85 with acceptable toxicity. The MARIANNE trial assessed first-line efficacy and safety of T-DM1 alone and with pertuzumab versus trastuzumab plus taxane (NCT01120184) in 1,095 patients with HER2-positive, treatment-naïve, advanced breast cancer. The primary end point of the trial was PFS. T-DM1–based therapy was noninferior but not better than taxane plus trastuzumab.86

Ramucirumab This MAb against the vascular endothelial growth factor receptor 2 (VEGFR2) has received regulatory approval in lung, gastric, and colon cancers all in combination with different chemotherapies. Based on a randomized phase III trial of 1,072 patients with metastatic colorectal cancer (RAISE) who were randomly assigned to receive FOLFIRI with or without ramucirumab, this agent was approved as the addition of ramucirumab to standard chemotherapy improved median overall survival from 11.7 months to 13.3 months with a corresponding improvement in PFS. Patients who were enrolled in this study had previously been treated with chemotherapy with evidence of progression and some had previously been treated with bevacizumab.87 In NSCLC, this drug is approved in combination with docetaxel for treatment of patients with metastatic NSCLC in whom disease has continued to progress after treatment with a platinum-based chemotherapy based on a phase III, randomized, double-blind placebo controlled trial (REVEL) of 1,253 patients with previously treated disease. A statistically significant improvement in overall survival was shown with the addition of ramucirumab to docetaxel (10.5 months versus 9.1 months).88 The most frequent adverse events reported with this combination were neutropenia, fatigue, and stomatitis. In contrast to bevacizumab, which is not indicated for treatment of squamous NSCLC, ramucirumab can be used with this particular histology. This drug also has been approved in combination with paclitaxel for treatment of patients with advanced gastric or gastroesophageal junction adenocarcinoma following progression on first-line paclitaxel chemotherapy.89 Across all these trials common side effects associated with VEGF pathway inhibition were observed. These included hypertension, arterial blood clots, and epistaxis. When combined with chemotherapy, side effects commonly seen with cytotoxic chemotherapy can be exaggerated with the addition of this agent.

Denosumab Denosumab (Xgeva) is a fully human IgG2 RANK ligand (RANKL) neutralizing antibody. Denosumab is FDA approved for use in adults and skeletally mature adolescents who have either surgically unsalvageable giant cell tumors of the bone (GCTB) or where resection is anticipated to result in severe morbidity. Approval was based in part on two open-label, phase II trials examining subcutaneous administration of 120 mg every 4 weeks with additional loading doses on days 8 and 15 of the first cycle.90,91 Of 187 patients, 47 (25%) exhibited partial objective responses based on modified Response Evaluation Criteria in Solid Tumors (RECIST). Two separate formulations and dosing schedules of denosumab are approved for use in two supportive care

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settings based on three randomized, double-blind, placebo-controlled phase III trials evaluating its efficacy versus zoledronic acid92–96 to reduce bone metastasis-related skeletal-related events (SREs) and to increase bone mass in prostate and breast cancer patients at high risk for bone fracture due to hormone-ablation therapies.

ANTIBODIES USED IN HEMATOLOGIC MALIGNANCIES Rituximab Rituximab (Rituxan) is a chimeric anti-CD20 MAb that was the first MAb to be approved by the FDA for use in human malignancy.97,98 There are multiple mechanisms by which anti-CD20 antibodies can lead to cell death.99 The combination of rituximab with cyclophosphamide, doxorubicin, vincristine, and prednisolone (CHOP) resulted in a 95% overall response rate (55% complete response, 40% partial response) among 40 patients with low-grade or follicular B-cell non-Hodgkin lymphoma, with molecular complete remissions observed.100 A longterm study of elderly patients with previously untreated diffuse large-cell lymphoma randomized to either CHOP chemotherapy plus rituximab (R-CHOP) or CHOP alone demonstrated a significant improvement in event-free survival, PFS, disease-free survival, and overall survival for the combination arm.101 No significant differences in long-term toxicity were noted. Low-grade B-cell lymphoma patients possessing the 158V/V polymorphism in FcγRIII experience superior response rates and outcomes when treated with rituximab, as described earlier in this chapter. These findings signify that antibody Fc domain::Fc receptor interactions underlie at least some of the clinical benefit of rituximab and indicate a possible role for ADCC that depends on such interactions. A combination of active agents (such as lenalidomide and thalidomide) that are also immune modulating may be additive with rituximab102 and perhaps synergize by increasing ADCC.103 Cytokines such as IL-2, IL-12, or IL15 and myeloid growth factors may also enhance therapeutic antibody activity as suggested by preclinical data demonstrating that IL-2 can promote NK cell proliferation and activation and can enhance rituximab activity and clinical efficacy.104–106 Myeloid growth factors, in combination with rituximab, may also activate ADCC.107 Alternative approaches to induce effector cell activity by combining Toll-like receptor (TLR) agonists, such as CpG oligonucleotides, have been investigated.108 Altering the balance of proapoptotic and antiapoptotic signals could generate more rituximab-induced cytotoxicity. Bcl2 downregulation by antisense oligonucleotides was found to enhance rituximab efficacy in preclinical testing. However, small molecules that bind to the BH-3 domain common to many members of the Bcl-2 family of proteins may be better therapeutic agents.109–111

Ofatumumab The anti-CD20 ofatumumab112 is a fully human antibody that binds an epitope on CD20 distinct from that bound by rituximab and is engineered for better complement activation, although it induces less ADCC. Ofatumumab has received regulatory approval for the treatment of patients with fludarabine-refractory chronic lymphocytic leukemia (CLL). In a recently reported, planned interim analysis that included 138 CLL patients with treatmentrefractory disease or bulky (>5 cm) lymphadenopathy, treatment with ofatumumab led to an overall response rate (primary end point) of 47% in patients with bulky disease and 5% in patients refractory to both alemtuzumab and fludarabine.113 Additional humanized anti-CD20 antibodies are under development.

Alemtuzumab Alemtuzumab (Campath-1H) targets the CD52 glycopeptide, which is highly expressed on T and B lymphocytes. It has been tested as a therapeutic agent for CLL and promyelocytic leukemias, as well as other non-Hodgkin lymphomas.

Brentuximab Vedotin Brentuximab vedotin (SGN-35, Adcetris) is an ADC consisting of the anti-CD30 chimeric MAb cAC10 that is linked to three to five molecules of the microtubule-disrupting agent MMAE. MMAE is a highly potent derivative of dolastatin. Linkage of MMAE to cAC10 occurs through a protease-cleavable linter.114 Brentuximab vedotin is approved for treating systemic, chemotherapy-refractory anaplastic large-cell lymphomas (sALCL). It is also approved to treat patients with Hodgkin lymphoma who have progressed after an autologous stem cell transplant (ASCT). Patients ineligible for ASCT must have failed two prior multidrug chemotherapy regimens.

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Brentuximab vedotin received accelerated approval in 2011 based in part on the results of two phase II trials. In a multicenter trial,115 58 patients with relapsed or refractory sALCLs received brentuximab vedotin (1.8 mg/kg/week), and 86% of patients achieved objective response, with a 57% complete responses rate, and a 13.2month median duration of response. Most common grade 3 and 4 adverse events were neutropenia (21%), thrombocytopenia (14%), and peripheral sensory neuropathy (12%). A similar trial, in Hodgkin lymphoma, was reported by Younes et al.116 in patients (N = 102) with progression following ASCT. A total of 75% of patients had objective responses, with 34% complete remissions. The median duration of complete responses was 20.5 months, and 31 patients were progression free after a median follow-up of 1.5 years. Phase III trials (e.g., ECHELON-2 or NCT01712490) are ongoing.

Inotuzumab Ozogamicin The approval for this drug came in 2017 based on the results of a randomized open-label trial involving 326 patients with Philadelphia chromosome–negative or Philadelphia chromosome–positive relapsed or refractory Bcell ALL.117 The control arm of the study was investigator’s choice of chemotherapy. The rate of complete remission was 80.7% in the inotuzumab group as compared to 29.4% in the standard chemotherapy group, and this difference was statistically significant. In patients who achieved a complete remission, a higher percentage in the inotuzumab group had no minimal residual disease and had a longer duration of remission, PFS, and overall survival (7.7 versus 6.7 months) compared to the control group. Veno-occlusive liver disease was the most frequent grade 3 or higher nonhematologic adverse event following therapy with inotuzumab ozogamicin.

Obinutuzumab This anti-CD20 MAb received regulatory approval in combination with chemotherapy for treatment of patients with previously untreated follicular lymphoma in 2017. In a randomized, open-label phase III trial (GALLIUM) for patients with previously untreated follicular lymphoma, 1,202 patients were randomly assigned to receive either obinutuzumab plus chemotherapy or rituximab plus chemotherapy followed by either obinutuzumab or rituximab maintenance treatment for up to 2 years in responding patients. The chemotherapy backbone was either bendamustine, CHOP, or cyclophosphamide, vincristine, prednisone. After a median follow-up of 38 months PFS was statistically significantly improved in the obinutuzumab arm with a hazard ratio of 0.72 compared to the rituximab arm. The median PFS had not been reached at the time of the initial reporting. The estimated 3-year rate of PFS was 80% versus 73%. Response rates appeared to be similar in both groups. There were more serious adverse reactions with this antibody compared with rituximab. The most common grade 3 or higher adverse events observed in the obinutuzumab arm was neutropenia, febrile neutropenia, thrombocytopenia, and infusion reactions.118 In a separate study of 396 patients with follicular lymphoma (GADOLIN) who had relapsed after treatment with a rituximab-containing regimen, treatment with obinutuzumab plus bendamustine followed by obinutuzumab monotherapy versus bendamustine alone showed a statistically significant improvement in the median PFS for the combination arm with a hazard ratio of 0.55.119

Blinatumomab Blinatumomab is a bispecific T-cell engager. This drug consists of two single-chain antibody fragments, one targeting CD19 on the B cells and the other targeting the CD3 complex on T cells. This drug initially received accelerated approval in 2014 for the treatment of the Philadelphia chromosome–negative refractory B-cell precursor ALL. Additional studies led to full approval of this agent in 2017 in addition to expansion of the approval to include Philadelphia chromosome–positive relapse or refractory B-cell precursor ALL. In a randomized open-label clinical trial (TOWER), 405 patients with relapsed or refractory B-cell precursor ALL were randomly assigned in a 2:1 fashion to treatment with blinatumomab versus standard-of-care chemotherapy. The study showed that the median overall survival in the group treated with blinatumomab was 7.7 months versus 4 months in the standard-of-care arm (hazard ratio for overall survival of 0.71).120 Adverse events of grade 3 or higher were observed in 87% of the blinatumomab group versus 92% in the chemotherapy group.

Daratumumab This anti-CD38 MAb was first approved as a single agent for treatment of refractory multiple myeloma. Two

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large randomized clinical trials that included different combinations of therapies have led to an expanded approval of this agent. In one phase III trial, 569 patients with multiple myeloma who were previously treated with one or more lines of therapy were randomly assigned to a combination of daratumumab plus lenalidomide and dexamethasone or to the combination of thalidomide and dexamethasone alone (POLLUX). PFS at 12 months was 83% in the daratumumab group as compared with 60% in the control group with a significantly higher overall response rate in the daratumumab group (92.9% versus 76.4%) and more patients in the daratumumab group with minimal residual disease or better. Daratumumab-associated infusion related reactions also occurred in about 47% of patients and were mostly of lower grades.11,121 A second phase III study assigned 498 patients with relapse or refractory multiple myeloma to receive a combination of daratumumab plus bortezomib and dexamethasone versus bortezomib and dexamethasone alone. At interim analysis, the rate of PFS, which was the primary end point of the study, was significantly higher in the daratumumab group than in the control group. At 12 months the rate of PFS was 61% in the daratumumab group versus 27% in the control group, with a correspondingly improved overall response rate and rates of very good partial or complete responses in the daratumumab group.122

Elotuzumab This first-in-class monoclonal immunostimulatory antibody targets signaling lymphocyte activation molecule F7 (SLAMF7), also known as the cell-surface glycoprotein CD2 subset 1 (CS1). This glycoprotein is expressed on myeloma and NK cells but not on normal cells. Following promising results of a single-arm phase II trial, a randomized phase III trial of this agent plus lenalidomide and dexamethasone versus lenalidomide and dexamethasone was conducted in 646 patients with refractory multiple myeloma (ELOQUENT-2). The rate of PFS at 12 months was 68% in the elotuzumab group compared with 57% in the control group. At 2 years, the rates were 41% and 27%, with correspondingly improved median PFS.123 The FDA approved elotuzumab in 2015.

Dinutuximab This MAb targets glycolipid GD2, which is primarily expressed on neuroblastoma cells. There is also some expression of this antigen on peripheral nerves and normal cells of neuroectodermal origin. In a randomized phase III study conducted by the Children’s Oncology Group (COG), investigators evaluated the activity of dinutuximab plus granulocyte macrophage colony-stimulating factor (GM-CSF) and IL-2 versus isotretinoin in patients with high-risk neuroblastoma. All patients had received aggressive multimodality treatment that included induction therapy and stem cell transplantation, and all had shown a response prior to randomization. All eligible patients, 226 in total, were randomly assigned to the two treatment groups. This study met the criteria for early stopping due to efficacy. After a 2.1-year median duration of follow-up, patients assigned to the combination treatment had event-free survival rates of 66% versus 46% in the control group and an overall survival of 86% versus 75% at 2 years. In the experimental group, 52% of patients experienced grades 3 to 5 pain.123 In addition the patients in the combination treatment experienced hypotension, capillary leak syndrome, and hypersensitivity reactions. The FDA approved this drug in combination with IL-2 and GM-CSF in 2015 based on the results of this trial and updated survival data. A randomized trial with this agent plus irinotecan versus irinotecan alone in patients with refractory small-cell lung cancer has been initiated (NCT03098030).

Olaratumab This MAb, which targets the platelet-derived growth factor receptor (PDGFR) α, received accelerated approval for the treatment of patients with soft tissue sarcoma based on the results of a randomized phase II clinical trial. In combination with doxorubicin, 133 patients with unresectable or metastatic soft tissue sarcoma received either the combination treatment or doxorubicin alone. In addition to standard entry criteria for a clinical trial of this nature available tumor samples were required to express PDGFR α by IHC. At the time of the reporting of the study, the median overall survival was 26.5 months with olaratumab plus doxorubicin versus 14.7 months with doxorubicin alone, translating to a hazard ratio of 0.46. The median PFS was also better for the combination, with a hazard ratio of 0.67 (P = .0615). The objective response rate was higher with the combination treatment but did not reach statistical significance when compared to the standard treatment arm of the study. As expected, adverse events were more frequent in the combination group versus doxorubicin alone.124

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CONCLUSION In the 35 years since Köhler and Milstein3 first developed the hybridoma technology that enabled antibody-based therapeutics, the field has made remarkable progress. Numerous antibody-based molecules are currently in clinical trials, and many more are in development. Multiple therapeutic antibodies have a proven clinical benefit and have been licensed by the FDA. The thoughtful application of advances in cancer biology and antibody engineering suggest that this progress will continue.

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32

Immunotherapy Agents Jeffrey A. Sosman and Douglas B. Johnson

INTRODUCTION Cancer immunotherapy, or the leveraging of the immune system against cancer, has been among the “holy grails” of cancer therapy. Conceivably, harnessing the potency, specificity, and precise nature of one’s own immune system could provide powerful tools in treating cancer. More than 100 years without major therapeutic breakthroughs, however, had injected considerable pessimism into the search for cancer immunotherapy. Nevertheless, a few notable, albeit limited, successes provided enough ammunition for several persistent investigators. The last few years have proved a testament to their dedication, with the approval of numerous immunotherapy agents and a multitude of ongoing clinical trials. Since the last edition of this textbook, there has been a major transformation in cancer therapy with the elevation of immunotherapy to a primary pillar of cancer treatment. Now, with the undeniable evidence that cancer immunotherapy can induce durable clinical tumor regression in many different cancers and the remarkable advances in our understanding of the cancer immunity cycle with its interplay of factors that positively or negatively regulate the immune response to cancer, we are now positioned to build on the efficacy of immune checkpoint inhibitors. The previous lack of efficacy for vaccines and cytokine therapy supports the importance of effective antigen presentation; the role of immune checkpoint molecules to modulate T-cell responses; the presence of cells in the tumor microenvironment to suppress effective antitumor responses including regulatory T cells (Tregs); myeloid-derived suppressor cells (MDSCs); type 2 tumor-associated macrophages (TAMs); and tumor-induced soluble suppressive factors such as transforming growth factor β (TGF-β), arginase (ARG), indoleamine 2,3-dioxygenase 1 (IDO1), interleukin (IL)-6, and IL-10. In addition, greater understanding of particular tumor antigens important for the induction of an effective antitumor response and advances in sequencing technology and antibody design have allowed the engineering of antibodies or antibody-like molecules to target agents to the tumor site. This has opened the door to explore approaches to (1) more effectively stimulate responses that target key cancer antigens, (2) further enhance the activating receptors found on T lymphocytes or other antigen-presenting cells (APCs), (3) utilize cytokines or chemokines to activate T cells at the tumor site or enhance T-cell trafficking to the tumor site, (4) block the effects of immune suppressive soluble factors or enzymes, (5) block the inhibitory receptors that weaken or extinguish the immune response to cancer, and (6) inhibit the function of immune suppressive cell populations. Additionally, technologic advances have allowed engineering of T lymphocytes to express receptors specific for either protein antigens (i.e., chimeric antigen receptor [CAR]-T cells) or through T-cell receptor (TCR) sequencing to specifically target peptide–major histocompatibility complex (MHC) tumor antigens. In this chapter, we will provide a limited overview of principles that have guided most of immune-based therapy in development (Tables 32.1and 32.2). We will not review clinical trials that have led to approval of a number of immunotherapy agents. Already, five different anti–programmed cell death protein 1 (anti–PD-1)/anti– programmed cell death protein ligand 1 (anti–PD-L1) molecules for 11 different disease indications have been approved. We will review approaches that will likely be incorporated into the next phase of cancer immunotherapy. The trials will require rational, data-driven incorporation of these and other agents into treatment regimens, in some part driven by the numerous approaches we describe in this chapter.

HUMAN TUMOR ANTIGENS For the past 20+ years following the understanding of antigen processing and the TCR recognition of peptides presented in the context of MHC, the existence of human tumor antigens derived from various proteins that could induce an antitumor response in vitro and in vivo has been firmly established. Intracellular proteins must be

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digested and processed with the resulting peptides transported to the cell surface through the endoplasmic reticulum and presented noncovalently bound to class I or II MHC molecules. A variety of approaches have been used to identify antigens that are naturally processed and presented on tumor cells or on professional APCs.1 These tumor antigens include (1) cancer-testis antigens expressed by embryonic testes and placental tissue but lacking in normal adult tissues, (2) lineage-derived differentiation antigens such as proteins important to melanin synthesis and found on normal melanocytes, (3) overexpressed gene products, (4) mutated gene products, and (5) viral gene products in virally associated cancers (e.g., human papillomavirus [HPV]). Although all of these antigen categories may be of importance to the efficacy and toxicity of immune therapy, the focus has largely turned toward the use of a different category of tumor antigens (mutanome-associated neoantigens) for vaccine development. TABLE 32.1

Approaches to Cancer Immunotherapy Approach

Class

Molecules Targeted

Removal of immune suppressive factors

Immune checkpoint inhibitors

PD-1, PD-L1, CTLA-4, LAG-3, TIM-3, TIGIT, VISTA, B7-H3, CD73, KIR



Soluble factors

IDO, arginase, adenosine, TGF-β



Myeloid targeted

PI3Kγ, CSF1R

Stimulation of effector cells

T-cell agonists

OX40, GITR, 4-1BB, ICOS, CD40, CD27, CD70



Cytokines

IL-2, TNF, IFN, immunocytokines, IL-2 variants



T-cell trafficking

CXCR2, CXCR4, CCR4, CCR5, bispecific antibodies

Direct cell killing, immune stimulation

Oncolytic viruses

HSV1, various other viruses

Innate immunity stimulation

Innate immune modulators

TLR, STING, CD47

Active immunization

Cancer vaccines

Neoantigens

Adoptive immunotherapy

T-cell receptor therapy

Neoantigens, cancer-testes antigens, germline antigens, etc.

Chimeric antigen receptor therapy Note: Molecules in bold text have approved therapies.

CD19, BCMA, many others

PD, programmed death; CTLA, cytotoxic T-lymphocyte antigen; TGF, transforming growth factor; CSF, colony-stimulating factor; IL, interleukin; TNF, tumor necrosis factor; IFN, interferon; HSV, herpes simplex virus; BCMA, B-cell maturation antigen; LAG-3, Lymphocyte-activation gene 3; TIM-3, T-cell immunoglobulin and mucin-domain containing-3; TIGIT, T-cell immunoreceptor with Ig and ITIM domains; KIR, killer cell immunoglobulin-like receptors; VISTA, V-domain Ig suppressor of T cell activation; IDO, Indolamine dioxygenase; PI3K, phosphatidylinositide 3-kinase; F1R, Colony stimulating factor 1 receptor; GITR, glucocorticoidinduced TNFR-related protein; ICOS, inducible T-cell costimulator; CXCR, CXC chemokine receptors; CCR, CC chemokine receptors; TLR, toll-like receptor; STING, stimulator of interferon genes.

Mutanome-Associated Neoantigens Following the success of immune checkpoint inhibition (ICI) and T-cell adoptive therapy, it has been appreciated that for the host immune system to recognize and destroy tumor cells following enhancing T-cell activation, neoantigens must be present and recognizable. Neoantigens are tumor-specific, mutated peptides presented on the surface of cancer cells in the context of MHC molecules. Tumor-specific mutant antigens (neoantigens), arising in large part from carcinogen exposure (ultraviolet [UV] radiation, cigarette smoke), from frameshifts due to small scale insertion and deletion mutations (indels), or from other causes of genomic mutations apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like (APOBEC), represent major class of antigens expressed by cancer cells.2 These are largely single nucleotide variants (SNVs) termed “passenger mutations” that do not individually drive oncogenesis. In murine cancer models, vaccines generated with immunodominant neoantigens are as effective as checkpoint blockade in inducing therapeutic tumor rejection. Neoantigens are the favored targets of T cells reinvigorated by checkpoint blockade therapy. T-cell responses against neoantigens can be enhanced by cytotoxic T-lymphocyte antigen 4 (CTLA-4) and PD-1 blockade. Further, the overall tumor mutation load correlates with response to checkpoint blockade in non–small-cell lung cancer (NSCLC), urothelial carcinoma, melanoma, and tumors with mismatch repair deficiency.3,4 Fitness models for tumors based on immune interactions of neoantigens may help further predict response to

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immunotherapy. Two main factors determine neoantigen fitness: the likelihood of neoantigen presentation by the MHC and subsequent recognition by T cells. The model depends on sequence similarity of neoantigens to known antigens such as infectious pathogen-expressed antigens. Importantly, low-fitness neoantigens identified by these methods may be leveraged to develop novel immunotherapies.

TUMOR VACCINES Personalized Neoantigen Vaccination The steps involved in a personalized neoantigen-based vaccine at present (2018) initially involves whole-exome sequencing (WES) of matched tumor and normal DNA from a single cancer patient, thereby identifying all transcribed somatic mutations.5,6 The expression of MHC alleles of the tumor allows the prediction of which mutated peptides are likely to bind to autologous human leukocyte antigen (HLA) class I peptides/proteins of the patient. Mutations can be ranked according to (1) predicted high-affinity binding to autologous HLA class I and high expression of the mutation-encoding RNA and (2) in some cases if CD4+ T cells are a target for activation, then predicted HLA class II binding. The mutated peptides can be synthesized into long peptides with 10 to 20 neoantigens presently feasible per patient. The mixture of peptides can then be combined with agents acting as nonspecific immune stimulants (adjuvants) such as Toll-like receptor 3 (TLR3), poly-ICLC, or other molecules that activate pathogen-associated molecular patterns (PAMPs) or damage-associated molecular patterns (DAMPs) to compose a vaccine for a specific patient. An alternate approach involves the selection of mutations based on affinity for class I and class II autologous MHC and then engineer them into synthetic RNAs (minigenes), each encoding several linker-connected long peptides. Both processes are time consuming with preparation time lasting 50 to 100 days at present but likely to be abbreviated. The use of long peptides or minigenes provides the ability to activate both CD8+ and CD4+ T cells against a significant proportion of immunizing peptides. One approach for delivery is subcutaneous administration near draining lymph nodes or injected percutaneously into inguinal lymph nodes under ultrasound control. The proportion of neoantigens stimulating class II responses is generally higher than for class I responses even if the selection of the neoepitopes is based on class I binding algorithms. In addition to the licensing of dendritic cells (DCs) and the activation and maintenance of a tumor-directed CD8+ T-cell response, CD4+ T cells can exert direct antitumor effects independently of CD8+ T cells.7 The results in both cases demonstrate that a personal neoantigen vaccine broadens the repertoire of neoantigen-specific T cells even potentially greater than exists from immune checkpoint inhibitors or adoptive cell therapy (ACT). Personal neoantigen vaccine appeared safe, feasible, and capable of eliciting strong T-cell responses in a clinical setting.5,6 The use of a personal neoantigen vaccine is anticipated to help address two major challenges for effective cancer immunotherapy: targeting highly heterogeneous tumors preventing immune escape through antigen loss and selectively targeting tumor relative to healthy tissues, thus limiting toxicity to normal tissues. Future neoantigen vaccine trials will likely use improved techniques to better predict antigen presentation, increasing the percentage of neoantigens inducing tumor-reactive T cells. These trials will likely focus on combinations with immune checkpoint or adoptive cell therapies. TABLE 32.2

Clinical Trials in 2018: Examples of New Immune Agents in Development Date Open

Clinical Trials Identifier

Ability of a Dendritic Cell Vaccine to Immunize Melanoma or Epithelial Cancer Patients Against Defined Mutated Neoantigens Expressed by the Autologous Cancer

March 2018

NCT03300843

Neoepitope-based Personalized Vaccine Approach in Pediatric Patients with Recurrent Brain Tumors

May 2018

NCT03068832

December 2017

NCT03259425

Trial NEOANTIGEN VACCINE

ONCOLYTIC VIRUS VACCINES Neoadjuvant Trial of Nivolumab in Combination with HF10 Oncolytic Viral Therapy in Resectable Stage IIIB, IIIC, IVM1a Melanoma

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A Phase I/II Study of Pexa-Vec Oncolytic Virus in Combination with Immune Checkpoint Inhibition in Refractory Colorectal Cancer

December 2017

NCT03206073

Oncolytic Adenovirus, DNX-2401, for Naive Diffuse Intrinsic Pontine Gliomas

May 2017

NCT03178032

Phase 1b Study PVSRIPO for Recurrent Malignant Glioma in Children

December 2017

NCT03043391

LOAd703 Oncolytic Virus Therapy for Pancreatic Cancer

November 2016

NCT02705196

SBRT and Oncolytic Virus Therapy before Pembrolizumab for Metastatic TNBC and NSCLC (STOMP)

July 2017

NCT03004183

Safety and Pharmacokinetics (PK) of Escalating Doses of MTIG7192A as a Single Agent and in Combination with Atezolizumab in Locally Advanced or Metastatic Tumors

May 2016

NCT0279457

Study of MK-7684 Alone and in Combination with Pembrolizumab in Advanced Solid Tumors (MK-7684-001)

December 2016

NCT02964013

A Study of OMP-313M32 in Subjects with Locally Advanced or Metastatic Solid Tumors

May 2017

NCT03119428

A Phase 1 Study of TSR-022, an Anti-TIM-3 Monoclonal Antibody, in Patients with Advanced Solid Tumors

July 2016

NCT02817633

A Study of LY3321367 Alone or With LY3300054 in Participants with Advanced Relapsed/Refractory Solid Tumors

April 2016

NCT03099109

Safety and Efficacy of MBG453 as Single Agent and in Combination with PDR001 in Patients With Advanced Malignancies

September 2015

NCT02608268

Anti-LAG-3 or Urelumab Alone and in Combination with Nivolumab in Treating Patients with Recurrent Glioblastoma

August 2016

NCT02658981

Study of TSR-033 with an Anti-PD-1

August 2017

NCT03250832

Study of REGN3767 (Anti-LAG-3) with or without REGN2810 (Anti-PD1) in Advanced Cancers

November 2016

NCT03005782

PDR001 Plus LAG525 for Patients with Advanced Solid and Hematologic Malignancies

January 2018

NCT03365791

July 2017

NCT03203876

MEDI9447 Alone and in Combination with MEDI4736 in Adult Subjects With Select Advanced Solid Tumors

July 2015

NCT02503774

Durvalumab, Tremelilumab, MEDI 9447, MEDI 0562: Trial in Patients with Relapsed Ovarian Cancer

March 2018

NCT03267589

Enoblituzumab (MGA271) in Children with B7-H3-expressing Solid Tumors

December 2016

NCT02982941

Safety Study of Enoblituzumab (MGA271) in Combination with Pembrolizumab in Refractory Cancer

July 2015

NCT02475213

Safety Study of Enoblituzumab (MGA271) in Combination with Ipilimumab in Refractory Cancer

March 2015

NCT02381314

Dose Escalation and Expansion Study of GSK3359609 in Subjects with Selected Advanced Solid Tumors (INDUCE-1)

June 2016

NCT02723955

Dose Escalation and Expansion of JTX-2011 Alone or in Combination with Anti-PD-1 in Subjects with Advanced Solid Tumors (ICONIC)

August 2016

NCT02904226

MEDI4736 Or MEDI4736 + Tremelimumab in Surgically Resectable Malignant Pleural Mesothelioma

May 2016

NCT02592551

INHIBITORY IMMUNE CHECKPOINT ANTAGONIST ANTIBODY Anti-TIGIT

Anti-TIM-3

Anti-LAG-3

Anti-KIR A Safety Study of Lirilumab in Combination with Nivolumab or in Combination with Nivolumab and Ipilimumab in Advanced and/or Metastatic Solid Tumors Anti-CD73

Anti-B7H3

ACTIVITY IMMUNE CHECKPOINT AGONIST ANTIBODY Anti-iCOS

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Anti-GITR Phase I/Ib Study of GWN323 Alone and in Combination with PDR001 in Patients with Advanced Malignancies and Lymphomas

July 2016

NCT02740270

A Study of OMP-336B11 in Subjects with Locally Advanced or Metastatic Tumors

October 2017

NCT03295942

INCAGN01876 in Combination with Immune Therapies in Subjects with Advanced or Metastatic Malignancies

November 2017

NCT03277352

Axitinib with or without Anti-OX40 Antibody PF-04518600 in Treating Patients with Metastatic Kidney Cancer

July 2017

NCT03092856

Study of OX40 Agonist PF-04518600 Alone and in Combination with 4-1BB Agonist PF-05082566

April 2015

NCT02315066

A Study to Evaluate MEDI0562 in Combination with Immune Therapeutic Agents in Adult Subjects With Advanced Solid Tumors

March 2016

NCT02705482

GSK3174998 Alone or with Pembrolizumab in Subjects with Advanced Solid Tumors (ENGAGE-1)

September 2015

NCT02528357

A Study Exploring the Safety and Efficacy of INCAGN01949 in Combination with Immune Therapies in Advanced or Metastatic Malignancies

October 2017

NCT03241173

Safety Study of SEA-CD40 in Cancer Patients

February 2015

NCT02376699

CD40 Agonistic Antibody APX005M in Combination with Nivolumab

July 2017

NCT03123783

A Study of CDX-1140 in Patients with Advanced Solid Tumors

December 2017

NCT03329950

A Study of RO7009789 in Combination with Atezolizumab in Participants with Locally Advanced and/or Metastatic Solid Tumors

December 2014

NCT02304393

A Dose Escalation and Cohort Expansion Study of Anti-CD27 (Varlilumab) and Anti-PD-1 (Nivolumab) in Advanced Refractory Solid Tumors

January 2015

NCT02335918

A Study of Varlilumab and IMA950 Vaccine Plus Poly-ICLC in Patients with WHO Grade II Low-Grade Glioma (LGG)

January 2017

NCT02924038

Neoadjuvant Nivolumab with and without Urelumab in Patients with Cisplatin-Ineligible Muscle-Invasive Urothelial Carcinoma of the Bladder

September 2016

NCT02845323

Study of OX40 Agonist PF-04518600 Alone and in Combination with 4-1BB Agonist PF-05082566

April 2015

NCT02315066

Combining PD-1 Blockade, CD137 Agonism and Adoptive Cell Therapy for Metastatic Melanoma

March 2016

NCT02652455

June 2017

NCT03138889

Study of AM0010 with Nivolumab Compared to Nivolumab Alone Secondline Tx in Patients with Metastatic Non-Small Cell Lung Cancer (Cypress 2)

June 1, 2018

NCT03382912

Study of AM0010 with FOLFOX Compared to FOLFOX Alone Second-line Tx in Pts with Metastatic Pancreatic Cancer (Sequoia)

November 1, 2016

NCT02923921

QUILT-3.055: A Study of ALT-803 in Combination with Pembrolizumab or Nivolumab in Patients with Advanced or Metastatic Non-Small Cell Lung Cancer

January 1, 2018

NCT03228667

Interleukin-15 in Combination with Checkpoint Inhibitors Nivolumab and Ipilimumab in Refractory Cancers

February 5, 2018

NCT03388632

March 2017

NCT02983578

Anti-OX40

Anti-CD40

Anti-CD27

CD-137 (4-1BB)

CYTOKINES Interleukin-2variant A Study of a CD122-Biased Cytokine (NKTR-214) with Anti-PD-1 (Pembrolizumab) and of NKTR-214 with Anti-PD-L1 (Atezolizumab) in Patients with Select Advanced or Metastatic Solid Tumors (PROPEL) Interleukin-10

Interleukin-15

SIGNALING MODULATION STAT3 Inhibition AZD9150 with MEDI4736 in Patients with Advanced Pancreatic, Non-Small

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Lung and Colorectal Cancer Trial of WP1066 in Patients with Recurrent Malignant Glioma and Brain Metastasis from Melanoma

March 2018

NCT01904123

AZD9150 Plus Durvalumab Alone or in Combination with Chemotherapy in Patients with Advanced, Solid Tumors and in Patients with Non-Small-Cell Lung Cancer

March 2018

NCT03421353

Pembrolizumab Combined with Itacitinib (INCB039110) and/or Pembrolizumab Combined with INCB050465 in Advanced Solid Tumors

January 2016

NCT02646748

Obinutuzumab with or without PI3K-delta Inhibitor TGR-1202, Lenalidomide, or Combination Chemotherapy in Treating Patients with Relapsed or Refractory Grade I-IIIa Follicular Lymphoma

August 2017

NCT03269669

December 2015

NCT02637531

SX-682 Treatment in Subjects with Metastatic Melanoma Concurrently Treated With Pembrolizumab

May 2018

NCT03161431

Combination Study of AZD5069 and Enzalutamide (ACE)

July 2017

NCT03177187

CXCR4 Inhibitor





Safety of Continuous IV Administration of the CXCR4 Antagonist, Plerixafor at Potentially Active Plasma Concentrations and Assess Its Impact on the Immune Microenvironment in Patients with Advanced Pancreatic, High Grade Serous Ovarian and Colorectal Adenocarcinomas

July 2017

NCT03277209

CX-01 Combined with Azacitidine in the Treatment of Relapsed or Refractory Myelodysplastic Syndrome and Acute Myeloid Leukemia

April 2017

NCT02995655

May 2016

NCT02732938

Mogamulizumab and Pembrolizumab in Treating Patients with Relapsed or Refractory Lymphomas

May 2018

NCT03309878

Study of Pre-operative Combination Therapy with Mogamulizumab and Nivolumab Against Solid Cancer Patients

March 2016

NCT02946671

November 2017

NCT03274804

A Study of Epacadostat in Combination with Pembrolizumab and Chemotherapy in Subjects with Advanced or Metastatic Solid Tumors (ECHO-207/KEYNOTE-723)

May 2017

NCT03085914

A Study of Epacadostat and Nivolumab in Combination with Immune Therapies in Subjects with Advanced or Metastatic Malignancies (ECHO208)

January 2018

NCT03347123

A Trial of HTI-1090 in Subjects with Advanced Solid Tumors

August 2017

NCT03208959

NLG802 Indoleamine 2,3-Dioxygenase (IDO) Inhibitor in Advanced Solid Tumors

July 2017

NCT03164603

A Study of LY3381916 Alone or in Combination with LY3300054 in Participants with Solid Tumors

November 2017

NCT03343613

Study of IDO Inhibitor (Indoximod) and Temozolomide for Adult Patients with Primary Malignant Brain Tumors

March 2014

NCT02052648

A Study to Test Combination Treatments in People with Advanced Renal Cell Carcinoma (FRACTION-RCC) Relatlimab (anti-LAG3), BMS-986016 (IDO Inhibitor)

January, 2017

NCT02996110

PI3Kδ Inhibitor

PI3Kγ Inhibitor A Dose-Escalation Study to Evaluate the Safety, Tolerability, Pharmacokinetics, and Pharmacodynamics of IPI-549 CHEMOKINE MODULATORS CXCR2 Inhibitor

CCR2 Inhibitor Ph1b/2 Study of PF-04136309 in Combination with Gem/Nab-P in First-line Metastatic Pancreatic Patients (CCR2i) CCR4 Inhibitor

CCR5 Inhibitor Combined PD-1 and CCR5 Inhibition (Maraviroc) for the Treatment of Refractory Microsatellite Stable mCRC (PICCASSO) SOLUBLE FACTORS IDO Inhibitors

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TGFβ Inhibition A Study of Galunisertib (LY2157299) in Combination with Nivolumab in Advanced Refractory Solid Tumors and in Recurrent or Refractory NSCLC, or Hepatocellular Carcinoma

October 2015

NCT02423343

Phase I/Ib Study of NIS793 in Combination with PDR001 in Patients with Advanced Malignancies

April 2017

NCT0294716

Study of TGF-β Receptor Inhibitor Galunisertib (LY2157299) and Enzalutamide in Metastatic Castration-resistant Prostate Cancer

April 2016

NCT02452008

Arginase Inhibitor INCB001158 as a Single Agent and in Combination with Immune Checkpoint Therapy in Patients with Advanced/Metastatic Solid Tumors

September 2016

NCT02903914

A Phase 1/2 Study of INCB001158 in Combination with Chemotherapy in Subjects with Solid Tumors

October 2017

NCT03314935

Ipilimumab (Immunotherapy) and MGN1703 (TLR Agonist) in Patients with Advanced Solid Malignancies

May 2016

NCT02668770

TLR9 Agonist SD-101, Anti-OX40 Antibody BMS 986178, and Radiation Therapy in Treating Patients with Low-Grade B-Cell Non-Hodgkin Lymphomas

March 2018

NCT03410901

A Phase 1/2 Study of In Situ Vaccination with Tremelimumab and IV Durvalumab Plus PolyICLC in Subjects with Advanced, Measurable, Biopsyaccessible Cancers

December 2016

NCT02643303

Study of the Safety and Efficacy of MIW815 With PDR001 to Patients with Advanced/Metastatic Solid Tumors or Lymphomas

September 2017

NCT03172936

Study of MK-1454 Alone or in Combination with Pembrolizumab in Participants with Advanced/Metastatic Solid Tumors or Lymphomas (MK1454-001)

February 2017

NCT03010176

Trial of PBF-509 and PDR001 in Patients with Advanced Non-small Cell Lung Cancer (NSCLC) (AdenONCO)

October 2015

NCT02403193

A Phase 2 Study of NIR178 in Combination with PDR001 in Patients with Solid Tumors and Non-Hodgkin Lymphoma

October 2016

NCT03207867

Trial of Hu5F9-G4 in Combination with Cetuximab in Patients With Solid Tumors and Advanced Colorectal Cancer

October 2016

NCT02953782

A Trial of TTI-621 for Patients with Hematologic Malignancies and Selected Solid Tumors

January 2016

NCT02663518

A Study of ALX148 in Patients with Advanced Solid Tumors and Lymphoma

February 2017

NCT03013218

Evaluation of Safety and Activity of an Anti-PDL1 Antibody (DURVALUMAB) Combined With CSF-1R TKI (PEXIDARTINIB) in Patients with Metastatic/Advanced Pancreatic or Colorectal Cancers (MEDIPLEX)

June 2016

NCT02777710

A Combination Clinical Study of PLX3397 and Pembrolizumab to Treat Advanced Melanoma and Other Solid Tumors

June 2015

NCT02452424

A Study of LY3022855 in Combination with Durvalumab or Tremelimumab in Participants with Advanced Solid Tumors

June 2016

NCT02718911

Phase I/II Study of BLZ945 Single Agent or BLZ945 in Combination with PDR001 in Advanced Solid Tumors

October 2016

NCT02829723

A Study of ARRY-382 in Combination with Pembrolizumab for the Treatment of Patients with Advanced Solid Tumors

October 2016

NCT02880371

A Study of MCLA-128 in Patients with Solid Tumors (IgG1 bispecific antibody targeting HER2 and HER3)

January 2015

NCT02912949

A Study of NOV1501 (ABL001) in Subject with Advanced Solid Tumors

September 2017

NCT03292783

Arginase Inhibitor

TLR Agonist

STING Agonist

Adenosine A2a Receptor Antagonist

Anti-CD47

CSF1R Inhibition

BIFUNCTIONAL FUSION PROTEINS Bispecific Antibodies

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(VEGF/DLL4 targeting bispecific antibody) An Open-Label, Multicenter, Dose Escalation Phase Ib Study with Expansion Cohorts to Evaluate the Safety, Pharmacokinetics, Pharmacodynamics, and Therapeutic Activity of RO7009789 (CD40 Agonistic Monoclonal Antibody) in Combination with Vanucizumab (Anti-Ang2 and Anti-VEGF Bi-Specific Monoclonal Antibody) in Patients with Metastatic Solid Tumors

January 2016

NCT02665416

A Phase 1, First-in-Human, Open-Label, Dose Escalation Study of JNJ61186372, a Human Bispecific EGFR and cMet Antibody, in Subjects with Advanced Non-Small Cell Lung Cancer

May 2016

NCT02609776

BATs Treatment for Pancreatic Cancer, Phase Ib/II (anti-CD3 x anti-EGFR bispecific antibody [EGFRBi])

July 2017

NCT03269526

Phase 1 Study of PF-06863135, A BCMA- CD3 Bispecific Ab, in Relapse/Refractory Multiple Myeloma

November 2017

NCT03269136

Phase II Trial of Immune Checkpoint Inhibitor with Anti-CD3 x Anti-HER2 Bispecific Antibody Armed Activated T Cells in Metastatic Castrate Resistant Prostate Cancer

February 2018

NCT03406858

A Phase 1 Dose Escalation and Cohort Expansion Study of ERY974, An Anti-Glypican3 (GPC3)/CD3 Bispecific Antibody, in Patients with Advanced Solid Tumors

August 2016

NCT02748837

Study of ES414 in Metastatic Castration-Resistant Prostate Cancer humanized bispecific antibody CD3xPSMA

January 2015

NCT02262910

Phase 1b/2 Study of the Combination of IMCgp100 with Durvalumab and/or Tremelimumab in Cutaneous Melanoma (soluble gp100-specific T cell receptor with anti-CD3 scFV)

November 2015

NCT02535078

Safety and Efficacy of IMCgp100 Versus Investigator Choice in Advanced Uveal Melanoma

October 2017

NCT03070392

Study to Evaluate the Therapeutic Activity of RO6874281 an Immunocytokine, Consisting of Interleukin-2 Variant (IL-2v) Targeting Fibroblast Activation Protein-a (FAP) as a Combination Therapy in Participants with Advanced and/or Metastatic Solid Tumors

January 2018

NCT03386721

An Open-Label, Multicenter, Dose-Escalation, Phase Ia/Ib Study to Evaluate Safety, Pharmacokinetics, and Therapeutic Activity of RO6874281, an Immunocytokine Consisting of Interleukin 2 Variant (IL-2v) Targeting Fibroblast Activation Protein-a (FAP), as a Single Agent (Part A) or in Combination with Trastuzumab or Cetuximab (Part B or C)

December 2015

NCT02627274

A Phase 1b, Open-Label, Multi-Center, Dose Escalation Study of the Safety, Pharmacokinetics, and Therapeutic Activity of Cergutuzumab Amunaleukin, an Immunocytokine, which Consists of a Variant of Interleukin 2 (IL 2v), That Targets Carcinoembryonic Antigen (CEA), and Atezolizumab, an Antibody That Targets Programmed DeathLigand 1 (PD-L1), Administered Intravenously, in Patients with Locally Advanced and/or Metastatic Solid Tumors

June 2015

NCT02350673

Phase I Clinical Study Combining L19-IL2 With SABR in Patients with Oligometastatic Solid Tumor (L19-IL2) fibronectin containing extra domain B (EDB), scFv fragment directed against EDB, designated L19, interleukin-2 (IL2), immunocytokine L19-IL2. L19-IL2)

December 2015

NCT02086721

August 2015

NCT02517398

April 2018

NCT03440437

BiTEs

ImmTAC

Immunocytokines

Bifunctional Immunostimulatory Antibody MSB0011359C (M7824) (a bifunctional fusion protein targeting PD-L1 and TGF-b) in Metastatic or Locally Advanced Solid Tumors A Phase 1, Open-Label, Dose-Escalation, and Cohort Expansion First-inHuman Study of the Safety, Tolerability, Pharmacokinetics, and Activity of FS118, a LAG-3/PD-L1 Bispecific Antibody, in Patients with Advanced Malignancies That Have Progressed on or After Prior PD-1/PD-L1 Containing Therapy Note: Bolded text denotes names of experimental agents or drug class.

A similar approach can be used to generate a pool of neoantigens that are employed to stimulate autologous T

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cells.2 Clonal TCRs specifically recognizing the neoantigens can then be isolated. These TCRs can be incorporated into chimeric clonal TCR with costimulatory domain to generate clonal T cells specific for the neoepitopes for adoptive T-cell therapy with TCR transfected autologous T cells.

Immune Checkpoint Inhibitors Although it is not the first cancer immunotherapy agents tested, this class of therapeutics has undeniably had the greatest impact. The concept of “immune checkpoints” was initially proposed by Dr. James Allison. TCRs encounter a cognate antigen presented on the cell surface (including APCs, tumor cells, or host cells). For activation, however, a second, costimulatory signal is required. Immune checkpoints oppose these costimulatory signals and repress T-cell function. Thus, these checkpoints functions as negative regulators, or “brakes” on T-cell activation, and pharmacologically inhibiting them would theoretically lead to T-cell activation.8 The first immune checkpoint functionally validated was CTLA-4. For T-cell costimulation to occur, CD28 (on T cells) is required to engage B7 (on APCs). CTLA4 is homologous to CD28 and competes for B7 binding with higher affinity, thus repressing the T cell response. CTLA-4 blockade functions in the early, “immune priming” phase, and activates both T-helper 1 (Th1) subsets of CD4+ T cells as well as CD8+ T cells.9 These cellular populations appear to be stimulated both peripherally and in the tumor microenvironment, where the suppressive Treg population may also be depleted.10 Ipilimumab, a monoclonal antibody to CTLA-4, restored T-cell function and led to long-lasting responses in patients with melanoma (approximately 10% to 15% response rate).11 Importantly, many patients who initially responded to therapy maintained benefit even 5 to 10 years later. This activity led, in 2011, to the first immune checkpoint inhibitor approved by the U.S. Food and Drug Administration (FDA). Despite the success of ipilimumab in melanoma, however, most patients failed to respond to treatment, and single-agent activity was minimal in other cancer types. Nevertheless, the durability of responses in a previously treatment-refractory cancer illustrated the power of cancer immunotherapy and led to interest in developing other immune checkpoint inhibitors. Other laboratory studies have now identified a host of other immune checkpoints, including the critical PD-1/PD-L1 axis (Fig. 32.1).9

Figure 32.1 Selected immune checkpoints, cytokines, and soluble factors in the tumor microenvironment. Green represents stimulatory, and red represents inhibitor factor. PD-L1,

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programmed cell death protein ligand 1; IL, interleukin; IFN-α, interferon α; PD-1, programmed cell death protein 1; PD-L2, programmed cell death protein ligand 2; CTLA-4, cytotoxic Tlymphocyte antigen 4; TIM-3, T-cell immunoglobulin and mucin domain 3; VISTA, V-domain immunoglobulin suppressor of T-cell activation; MHC, major histocompatibility complex; TCR, Tcell receptor; LAG-3, lymphocyte-activation gene 3; TIGIT, T-cell immunoreceptor with immunoglobulin and immunoreceptor tyrosine-based inhibitory motif domains; GITRL, glucocorticoid-induced tumor necrosis factor receptor–related protein ligand; GITR, glucocorticoidinduced tumor necrosis factor receptor–related protein; ICOSL, inducible T-cell costimulator ligand; IDO, indoleamine 2,3-dioxygenase; TGF-β, transforming growth factor β; ICOS, inducible T-cell costimulator. PD-1 and PD-L1 were discovered and characterized by several groups, including those of Drs. Takasu Honjo, Lieping Chen, and Gordon Freeman with Arlene Sharpe. PD-L1 is frequently expressed by tumor cells and tumorinfiltrating myeloid cells (e.g., macrophages). When PD-1 engages PD-L1, particularly in the tumor microenvironment, it suppresses TCR and CD28 signaling through recruitment of phosphatases. Pharmacologic blockade with a PD-1 or PD-L1 blocker restores TCR signaling in a CD28-dependent fashion and primarily affects CD8+ T cells.10,12 Some slight distinctions in the mechanism of action for PD-1 versus PD-L1 inhibitors exist; blocking PD-1 interrupts its interactions with PD-L1 as well as its alternative ligand PD-L2. PD-L1 blockers, by contrast, interrupt the PD-L1/PD-1 and PD-L1/B7 interactions. Despite these distinctions, it remains unclear whether any major differences in clinical activity or toxicities exist between anti–PD-1- and anti–PD-L1targeted agents. Anti–PD-1/PD-L1 therapeutics have demonstrated durable, immune-related responses in numerous cancer types13 and are now approved at the time of this writing in melanoma, NSCLC, urothelial carcinoma, head and neck squamous cell carcinoma (HNSCC), renal cell carcinoma (RCC), hepatocellular carcinoma, gastroesophageal cancer, Hodgkin lymphoma, Merkel cell carcinoma, primary mediastinal B-cell lymphoma and various malignancies demonstrating microsatellite instability (MSI); more approvals are expected in the near future. In addition to approved anti–PD-1 agents (nivolumab and pembrolizumab) and anti–PD-L1 agents (atezolizumab, durvalumab, avelumab), several additional PD-1/PD-L1 antibodies are in clinical development. Toxicities of immune checkpoint inhibitors are related to aberrant activation of autoreactive T cells against host tissues. These toxicities occur idiosyncratically, may affect any organ, and occasionally present in fulminant fashion.14 Most commonly, these toxicities affect the colon, lung, skin, liver, and endocrine glands. It remains unclear why these toxicities occur in some patients but not in others; hypotheses include genetic predisposition to autoimmunity, shared or similar antigens in host and tumor cells, or subclinical inflammation due to environmental causes.15,16 Additional details surrounding the development and clinical utility of these agents are available in Chapter 17.

Other Immune Checkpoint Inhibitors in Development Anti-TIGIT T-cell immunoreceptor with immunoglobulin (Ig) and immunoreceptor tyrosine-based inhibitory motif (ITIM) domains (TIGIT) is a novel coinhibitory immune checkpoint under study in early clinical trials. TIGIT is a member of a recently discovered arm of the Ig superfamily, the poliovirus receptor (PVR)-like proteins. The ligand for TIGIT is CD155 (also known as PVR), but this protein also serves as a ligand for CD226, which, like CD28, is an activating receptor. When CD155 is bound to CD226, it conveys activating signals into the immune cell. Meanwhile, CD155 bound to TIGIT transmits an inhibitory signal by recruiting the SHP1 phosphatase to the membrane through its ITIM domain that deactivates numerous proteins involved in T-cell effector functions. Further members of this family, including CD96 and CD112, also may have a role in TIGIT signaling, adding complexity to this pathway.17 TIGIT is expressed by activated cytotoxic T cells, Tregs, and natural killer (NK) cells. The ligands CD155 and CD112 are found on DCs and macrophages and are also highly expressed in several types of cancer. Several studies have revealed TIGIT as a potentially complementary target to other inhibitory immune checkpoints, including PD-1.18 In addition to directly inhibiting cytotoxic T-cell activity, TIGIT may increase NK-cell activation and dampen Treg function. As such, TIGIT acts as an inhibitory immune checkpoint on both T cells and NK cells. Numerous inhibitors of TIGIT as well as PVR are in early phase development.

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TIM-3 T-cell immunoglobulin and mucin domain 3 (TIM-3) is a Th1hcell–specific surface protein involved in the suppression of macrophage activation (“escape model” following PD-1 inhibition), but it is mainly expressed on activated memory CD8 T cells. TIM-3 stimulation (via its ligand galectin-9 secreted by Tregs) results in a depletion of interferon γ (IFN-γ) production by interrupting CD45 and Lck interaction. Interestingly, although anti–TIM-3 therapy alone had only a modest effect in animal models, the combination of anti–TIM-3 and anti– PD-1 significantly suppressed tumor growth.19 TIM-3 inhibition activates antigen-specific T lymphocytes and enhances cytotoxic T-cell–mediated tumor cell lysis. TIM-3 (and lymphocyte-activation gene 3 [LAG-3]) appear to be upregulated in some models of acquired anti–PD-1 resistance.20 To date, two TIM-3 antagonist monoclonal antibodies are in early clinical development.

LAG-3 LAG-3 is a member of the Ig superfamily, is expressed on various immune cells, and binds to MHC class II molecules. Its expression on tumor-infiltrating lymphocytes (TILs) is associated with negative regulation of cellular proliferation and T-cell activation. LAG-3 and PD-1 receptors are overexpressed and/or coexpressed on TILs following T-cell activation. LAG-3 may contribute to de novo and acquired resistance to anti–PD-1/PDL1.20 Anti–LAG-3 monoclonal antibody BMS-986016 (relatlimab) has shown activity when combined with nivolumab in heavily pretreated patients with melanoma who had progressed during prior anti–PD-1/PD-L1 therapy.21 Responses were more likely in patients with LAG-3 expression ≥1%, whereas PD-L1 expression did not appear to enrich for response. The combination is well tolerated, with a safety profile similar to that of nivolumab monotherapy.

KIR Killer cell Ig-like receptors (KIRs) have importance to both innate and adaptive immunity. NK cells use different innate receptors to sense their environment and respond to alterations induced by malignant cell transformation. In a process termed “licensing,” NK cells use inhibitory KIRs for “self”-MHC-class I molecules to maintain a state of responsiveness and to kill target cells that have lost MHC-I (e.g., tumor cells). In contrast, the recognition of missing or downregulated self-MHC-I molecules on tumor cells by licensed NK cells shifts the receptor balance toward activation. Taken together, the modulation of NK-cell activity is therefore controlled by an array of germline-encoded activating and inhibitory receptors as well as modulating coreceptors (costimulatory KIRs). Several monoclonal antibodies targeting KIRs have been tested in preclinical models and in ongoing clinical trials. Lirilumab (IPH2102/BMS-986015) is a fully human monoclonal antibody that is designed to block the interaction between KIR2DL1, KIR2DL2, and KIR2DL3 inhibitory receptors and their ligands. Blocking these receptors facilitates activation of NK cells and potentially some subsets of T cells. Lirilumab is undergoing phase I/II testing for solid tumors and for hematologic malignancies (i.e., lirilumab plus nivolumab and azacitidine in myelodysplastic syndrome patients).

CD73 CD73 or 5′-nucleotidase, a plasma membrane protein upregulated on many cancer cell types, catalyzes the conversion of extracellular nucleotides, such as AMP, to membrane-permeable nucleosides, such as adenosine. Adenosine mediates lymphocyte suppression and decreases the activity of CD8+ effector cells, and increases both MDSCs and Tregs. Blockade of CD73 leads to clustering and internalization of this molecule and adenosinemediated lymphocyte suppression, and increases the activity of CD8+ effector cells.22 Studies of monoclonal antibodies to CD73 are now underway alone and combination with anti-PD-1.

VISTA V-domain Ig suppressor of T-cell activation (VISTA) is an inhibitory checkpoint predominantly expressed on hematopoietic cells, particularly in tumor-infiltrating myeloid cells. Preclinical studies with VISTA blockade have shown promising improvement in antitumor T-cell responses, even in cases without detectable expression of VISTA on tumor cells, and in the absence of PD-L1 expression.23 Further, VISTA appears to be upregulated following resistance of other immunotherapies.24 Early data from VISTA antagonists have shown preliminary signs of activity and acceptable toxicity.

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B7-H3 B7-H3 (CD276) is an inhibitory member of the B7 protein family. It inhibits APCs and stimulates Tregs, which results in suppression of IL-2 production (termination of the immune response); however, its receptor is still unknown. Recently, a humanized IgG1 monoclonal antibody targeting B7-H3 has been tested (enoblituzumab); an ongoing phase I study showed that enoblituzumab was well tolerated at all dose levels, with initial antitumor activity in a heavily pretreated patient population observed in prostate and bladder cancers and melanoma.25 Currently, enoblituzumab is being evaluated in combination with other checkpoint inhibitors in patients with B7H3–positive melanoma, NSCLC, and HNSCC (phase I trials).

Immune Checkpoint Activators Among the first T-cell activators in clinical trials, the CD28 superagonist TGN1412 provided an extreme cautionary tale. Six healthy young volunteers received simultaneous infusions, and all experienced life-threatening cytokine release syndromes (CRSs).26 Although all survived, this study injected an appropriate degree of caution into future immunotherapy trials, including those of immune checkpoint inhibitors and activators.

4-1BB (CD137) The 4-1BB protein receptor (CD137) is a surface glycoprotein that belongs to the tumor necrosis factor (TNF) receptor superfamily. CD137 is an inducible costimulatory molecule expressed on several immune cells, including activated memory CD4 and CD8 T cells, NK cells, monocytes, and DCs. CD137 functions as a costimulatory receptor induced by TCR stimulation. In this context, ligation of CD137 leads to increased T-cell proliferation, cytokine production, functional maturation, and prolonged memory CD8 T-cell survival. Consistent with the costimulatory function of CD137 on T cells, agonistic monoclonal antibodies against this receptor have been shown to provoke tumor-specific T-cell responses capable of eradicating tumors in several murine tumor models.27 Utomilumab and urelumab are two monoclonal antibodies to CD137 currently under development.28,29

GITR Glucocorticoid-induced TNF receptor–related protein (GITR; CD357, a member of the TNF receptor superfamily) and its ligand (GITRL) can be detected in the steady state on Tregs with further increasing expression upon stimulation. In addition, effector CD4 and CD8 T cells express GITR constitutively at low levels but rapidly upregulate GITR expression on activation. GITR expression in humans has also been described in macrophages and NK cells. Anti-GITR antibody binds to and activates GITRs found on multiple types of T cells induces both the activation and proliferation of tumor antigen–specific T-effector cells, and suppresses the function of activated Tregs. This leads to tumor cell eradication in preclinical models.30 To date, the most advanced monoclonal antibody targeting GITR, TRX518-001, was found to be well tolerated with no dose-limiting toxicities but with limited efficacy. Several other anti-GITR antibodies are also in early development.

ICOS Inducible T-cell costimulator (ICOS; CD278) is expressed on activated T cells, whereas its ligand (B7-H2) is expressed mainly on B cells and DCs. The costimulatory B7-H2/ICOS pathway augments the T-cell effector function, which leads to enhanced cytokine production of both Th1 and Th2 cells. In addition, ICOS stimulates IL-10 production suggesting that this pathway is also involved in the regulation of Treg function.31 Several ICOS agonists are currently being studied in combination with immune checkpoint inhibitors.

CD40 CD40, a cell surface receptor and member of the TNF receptor superfamily, is expressed on various immune cells and cancer cells; it mediates both indirect tumor cell killing through the activation of the immune system and direct tumor cell apoptosis. CD40 agonist monoclonal antibodies bind to CD40 on a variety of immune cell types in a similar fashion to the endogenous CD40 ligand (CD40L or CD154), which triggers the cellular proliferation and activation of APCs, and activates B cells and T cells.

CD27-CD70 CD27, a costimulatory molecule and member of the TNF family overexpressed in certain tumor cell types, is

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constitutively expressed on mature T lymphocytes, memory B cells, and NK cells and plays an important role in NK cell–mediated cytolytic activity and T- and B-lymphocyte proliferation and activation. CD27 supports antigen-specific expansion of naïve T cells (differentiation of CD8 T cells into effector cytotoxic T cells) and is vital for the generation of T-cell memory. The ligand, CD70, is expressed on highly activated lymphocytes and plays an important role in boosting B-cell activation (stimulation of Ig production). CD27 can provide a potent costimulatory signal when engaged by its ligand CD70. Administration of an antibody that binds to CD27 potentiates the immune response by increasing the cytotoxic T-lymphocyte response.32 Binding to CD27expressing tumor cells may lead to growth inhibition of CD27-expressing tumor cells. Several molecules targeting the CD27-CD70 system are currently in clinical development. Recently, data from a phase I trial with MDX-1203 (agonistic monoclonal antibody targeting CD70) showed a best response of stable disease in 18 of 26 patients (69%).33 An agonistic CD27 fully humanized monoclonal antibody (varlilumab) is being developed in hematologic and solid malignancies.

OX40 OX40 (CD134) and its ligand OX40L (secreted by APCs and DCs) are essential for enhancing the activation of CD8 T cells (costimulatory second signal). The expression of OX40 following antigen encounter is largely transient for both CD4 and CD8 T cells (24 to 72 hours). Stimulation of OX40 results in increased IFN-γ secretion and PD-L1 overexpression and regulates Tregs (through suppression or deletion). Preclinical studies have demonstrated that treatment of tumor-bearing mice with OX40 agonistic antibodies resulted in tumor regression, which formed the basis to further evaluate this strategy in clinical trials. Recently, monotherapy with an OX40 agonistic antibody (9B12) was tested in a phase I trial in patients with solid tumors (NCT01644968) with promising results.34 A total of 12 of 30 patients receiving 9B12 had regression of at least one metastatic lesion with only one cycle of treatment, and no significant adverse events were reported. However, the development of murine antibodies precluded continued treatment. Currently, humanized agonistic OX40 monoclonal antibodies are in phase I/II clinical trials as monotherapy or in combination with other immune-modulating agents.

ONCOLYTIC VIRUSES Talimogene Laherparepvec FDA approval of the oncolytic herpesvirus talimogene laherparepvec (TVEC), an in situ vaccine, in advanced melanoma was a major breakthrough for the field. TVEC is an immunostimulatory herpes simplex virus (HSV) that expresses granulocyte-macrophage colony-stimulating factor (GM-CSF). TVEC is derived from a clinical HSV1 strain (JS1) deleted for ICP34.5 and ICP47, which normally acts to block HSV1 MHC class I antigen presentation on the infected cell surface resulting in immune evasion (Fig. 32.2). Its approval was based on a randomized phase III trial using intralesional injections of melanoma metastases; improvement in response rates were observed compared to GM-CSF alone as well as a nearly statistically significant (P = .051) improvement in overall survival.35 Studies of TVEC in combination with immune checkpoint inhibitors have been initiated. A randomized phase II trial evaluated TVEC plus ipilimumab in patients with advanced melanoma compared with ipilimumab alone. The trial showed that the combination induced a higher response rate compared with monotherapy.36 Combined TVEC and pembrolizumab may enhance the activity of each agent, as observed in a small phase II trial where 62% of patients had objective responses.37 This study also showed that response to combination therapy did not appear to be associated with baseline CD8+ T-cell infiltration or IFN-γ signature, as TVEC could induce T-cell infiltration into tumors. These findings suggest that oncolytic virotherapy may improve the efficacy of anti–PD-1 therapy by changing the tumor microenvironment.

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Figure 32.2 Mechanism of action of talimogene laherperpvec. GM-CSF, granulocyte-macrophage colony-stimulating factor; DC, dendritic cell.

Other Oncolytic Viruses In 2017, over 70 clinical trials were recruiting patients, using a range of oncolytic viruses (OVs) in multiple cancer types with many additional trials in the planning stages. In OV clinical trials, many important questions remain, including understanding viral kinetics, toxicity, and predictive biomarkers. As illustrated previously, clinical development of OVs is increasingly focused on their immune stimulatory properties to effectively synergize with immune checkpoint inhibitors. A general understanding of the mechanisms of OV action suggests that it is mediated through a combination of selective tumor cell killing and establishment of antitumor immunity. Immune stimulation is caused by release of cell debris and viral antigens into the tumor microenvironment.38 Tumor selectivity is based on several factors: cellular entry via virus-specific, receptor-mediated mechanisms that can be highly expressed on some tumor cells; rapid cell division in tumor cells with high metabolic and replicative activity that may support increased viral replication compared with normal quiescent cells; driver mutations that may specifically increase the selectivity of virus replication in tumor cells; and deficiencies in antiviral type I IFN signaling that support selective virus replication. Viral replication in the tumor microenvironment leads to innate and ultimately adaptive immune activation. Although viral spread is limited by the immune response, the presence of virus and cell lysis, with its accompanying release of tumor antigens, PAMPs, and DAMPs, promotes antitumor immunity. OVs range in size and complexity from large, double-stranded DNA viruses such as vaccinia (190 kb) and HSV1 (152 kb) to the tiny parvovirus H1 (5-kb linear, single-stranded DNA). Although most OVs are engineered, a few wild-type viruses are in clinical use. These include viruses with low pathogenicity (reovirus) and viruses that have nonhuman hosts, including Newcastle disease virus (avian), parvovirus H1 (rat), and vesicular stomatitis virus (insects, horses, cows, and pigs). Many OVs have been engineered to improve tumor cell selectivity. HSV1 has strong lytic properties, and several variants have been constructed, often via deletion of the ICP34.5 neurovirulence and ICP6 (UL39) (ribonucleotide reductase) genes.38 ICP6 is necessary for generating the nucleotide pool needed for viral replication in normal quiescent cells. Similarly, reovirus has oncolytic selectivity to cells with active RAS signaling. In the case of adenovirus, replication occurs in S phase, and the wild-type virus encodes a protein (E1A) that functions via retinoblastoma signaling to promote S-phase entry because cancer cells typically possess retinoblastoma pathway mutations and enriched S-phase populations. To promote safety and prevent replication in normal cells, the E1A gene has been deleted from oncolytic adenovirus. Tumor selectivity and potency is enhanced by direct intratumoral injection of high viral loads. Currently, trials are underway involving a host of OVs, including herpes virus, adeno virus, vaccinia virus, coxsackie virus, polio virus, retro virus, reo virus, and parvovirus.39

FACTORS TO ACTIVATE IMMUNE EFFECTOR CELLS

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Cytokines Cytokines (ILs) are immunomodulatory proteins that can activate or inhibit the activity of the immune system, depending on their properties and concentration, or the microenvironment in which they operate. Examples of proinflammatory cytokines include IL-2, TNF-α, and IFN-α. IL-2 and IFN have been in the clinic for many years and in some cases approved for therapy of cancer as described in Chapter 17 by Weber and colleagues. However, the systemic administration of these agents is often associated with dose-dependent side effects, as described in the following. Further, insufficient levels of the agents access the tumor microenvironment. These effects, in the case of IL-2, prevent dose escalation to possibly more therapeutically active regimens and schedules.

IL-2 Variant Molecules High-dose (HD) IL-2 administration results in severe hypotension and a capillary leak syndrome, limiting its administration to patients with excellent organ function and performance status, age younger than 70 years, and treatment in specialized centers with specific expertise. HD IL-2 has demonstrated complete cancer regressions in about 5% to 10% of patients treated for metastatic melanoma and renal cancer; most of these have been “cured” as defined by maintaining complete regressions for >10 years. At high doses, IL-2 binds to heterodimeric IL2Rβγ receptor leading to desired expansion of tumor-killing CD8 memory effector T (CD8 T) cells. However, IL-2 also binds to its heterotrimeric receptor IL2Rαβγ with even greater affinity, which expands immunosuppressive CD4+ CD25 (IL2Rα) + Tregs. NKTR-214 is a prodrug consisting of IL-2 bound by polyethylene glycol (PEG) masking the region of IL-2 that interacts with the IL2Rα subunit responsible for activating Tregs. With this approach, PEGylation can alter the immunostimulatory profile of IL-2, releasing active conjugated IL-2 after slow release of PEG chains in vivo, while simultaneously creating an initially inactive prodrug, mitigating rapid systemic immune activation, and improving tolerability. This allows dosing once every 9 days in mice compared with thrice daily for HD IL-2. The PEG reagent and conjugation reaction were optimized to facilitate localization on IL-2 at lysine residues clustered at the IL-2/IL2Rα interface while allowing sustained concentrations of active conjugated IL-2 in the tumor. In total, this molecule NKTR-214 is manufactured to better target IL-2 to the tissue site while limiting the degree of Treg activation. NKTR-214 in combination demonstrated objective response rates of >50% in melanoma, RCC, and NSCLC in very early results.40 Another strategy to improve IL-2 efficacy involves immunocytokines linking antibody-like molecules to IL-2 for targeting the tumor site, as described later in this chapter. IL-10 is generally considered an immunosuppressive cytokine because of its association with multiple regulatory or immunosuppressive immune-cell populations, such as Tregs, MDSCs, and tolerogenic DCs. However, there is also abundant preclinical evidence supporting the antitumor activity of IL-10. Mice lacking IL10 or IL-10 receptor are susceptible to tumor development, and exogenous IL-10 can boost antitumor immunity in mice, likely by stimulation, differentiation, and expansion of CD8+ T cells. AM0010 is a pegylated recombinant IL-10 that allows sustained systemic exposure leading to the expansion and activation of tumor-infiltrating CD8+ T cells. A phase I dose-escalation and expansion clinical trial with daily subcutaneous injections of AM0010 in 51 patients with advanced, treatment-refractory, solid tumors was initiated. AM0010 led to systemic immune activation with elevated immune-stimulatory cytokines, reduced TGF-β, and manageable toxicities.41 Partial responses were observed in 1 patient with uveal melanoma and 4 of 15 evaluable patients with RCC treated at the phase II dose. IL-15 is currently in clinical trials for treatment of advanced cancers. However, the combination of IL-15 with soluble IL-15Rα generates a complex termed IL-15 superagonist (IL-15 SA) that possesses greater biologic activity than IL-15 alone and can selectively expand NK and memory CD8+ T (mCD8+ T) lymphocytes, making it an attractive antitumor and antiviral agent. A novel human IL-15 superagonist variant (IL-15N72D) in a complex with a human IL-15Rα sushi domain-Fc fusion protein is known as ALT-803.42 The IL-15N72D mutation increases IL-2Rβ binding and IL-15 biologic activity. The ALT-803 superagonist complex (IL-15N72D:IL15RαSu/Fc) not only exhibits superior immunostimulatory activity but also has a longer serum half-life and retention in lymphoid organs, with significantly more efficacy against tumors in mouse models compared to IL-15 alone. Currently, ALT-803 is being evaluated in multiple clinical trials, as monotherapy combined with immune checkpoint inhibitors, as a local infusion in the bladder, and in combination with ACT.

SIGNALING MODULATION

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STAT3 Inhibition MDSCs inhibit innate and adaptive immune responses in the tumor microenvironment and constitute a major cellular mediator of immunosuppression. Although signal transducer and activator of transcription (STAT) proteins are induced by cytokines in normal cells, they have additional roles in cells within the tumor microenvironment, including MDSC differentiation, accumulation and activation of tolerogenic DCs and Tregs, and upregulation of immune checkpoint proteins.43 In MDSCs of cancer patients, phosphorylated STAT3 regulates Arg-1 gene expression by binding to its promoter. STAT3 inhibition leads to a decrease in the immunosuppression mediated by MDSCs and their Arg-1 expression. STAT3 inhibitors have the potential to convert MDSCs into fully mature myeloid cells or nonimmune suppressor cells, which may represent a better strategy than simply decreasing MDSC load. Several STAT3 inhibitors are in clinical development.44 These largely orally available agents have demonstrated promising preclinical data alone and in combination with chemotherapy. Effects include growth inhibition of cancer cells as well as proliferation of effector T lymphocytes and upregulation of CD86 and CD80 on APCs.

PI3Kδ Inhibitors Inhibitors against the p110δ isoform of phosphoinositide-3-OH kinase (PI3Kδ) have been active in some human leukemias. However, p110δ inactivation in mice protects against a broad range of cancers, including solid tumors. PI-3065, a PI3Kδ inhibitor, decreased growth and increased survival of breast and pancreatic tumors in wild-type mice compared with vehicle.45 PI3kδ deficiency had a larger impact on Tregs than on the CD8+ T cells, resulting in enhanced antitumor immunity. Numerous small-molecule inhibitors of PI3Kδ are in development; all were initially developed for hematologic malignancies but now are being repurposed due to their immune effects and combined with immune checkpoint inhibitors.

PI3Kγ Inhibitors PI3Kγ is highly expressed in myeloid cells and promotes migration and production of proinflammatory mediators. Mice deficient in p110γ subunit of PI3Kγ show reduced tumor growth with decreased TAM infiltration. Growing evidence suggests that heavy infiltration by immunosuppressive myeloid cells correlates with poor prognosis and immune checkpoint blockade (ICB) resistance. PI3Kγ signaling through Akt and mammalian target of rapamycin (mTOR) inhibits nuclear factor kappa-light-chain- enhancer of activated B cells (NF-κB) activation while stimulating CCAAT/enhancer binding protein β (C/EBPβ) activation, inducing a transcriptional signature of immune suppression, and controlling the switch between type 2 TAMs (suppressive) and type 1 (immune stimulatory).46 PI3Kγ blockade can prolong activation of NF-κB, restore CD8+ T-cell function, and stimulate Tcell recruitment into tumors. CD8+ T-cell content increased in tumors from PI3Kγ−/− mice without significantly altering systemic T-cell content. PI3Kγ inhibitors synergizes with checkpoint inhibitor therapy to promote tumor regression and increased survival in vivo. PI3Kγ targeting is currently being evaluated in a phase I clinical trial (NCT02637531).

Chemokine Inhibitors CXCR2 Inhibitors The C-X-C motif chemokine receptor 2 (CXCR2) is upregulated in the tumor microenvironment and plays a role in tumor cell proliferation and progression and regulation of immune cell attraction. CXCR2 signaling can promote pancreatic tumorigenesis and metastasis, rendering CXCR2 a promising cancer target. Moreover, CXCR2 inhibition is believed to enhance sensitivity to immunotherapies by preventing MDSC attraction.47 CXCR2 inhibitors are currently being investigated in phase Ib/II studies in combination with anti-PD-1/PD-L1.

CCR2 Inhibitors The C-C motif chemokine receptor 2 (CCR2) is mainly expressed on monocytes. Binding of the corresponding ligand (C-C motif chemokine ligand 2 [CCL2]) induces chemotaxis, important for the recruitment of TAMs in solid tumors including pancreatic adenocarcinoma, leading to an immunosuppressive tumor microenvironment. Preclinical models demonstrate that blockade of CCR2 can lead to recovery of antitumor immunity.48 Orally bioavailable CCR2 inhibitors are being investigated in several studies in combination with chemotherapy and in

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the future with anti-PD-1/PD-L1 in patients with pancreatic cancer.

CXCR4 Inhibitors The C-X-C motif chemokine receptor 4 (CXCR4) is often upregulated in tumor cells, involved in metastasis, and associated with increased recurrence risk and poor survival in many cancers. CXCR4 belongs to the seventransmembrane G-protein coupled receptor (GPCR) superfamily. Binding of the corresponding ligand (C-X-C motif chemokine ligand 12 [CXCL12]) (stromal derived factor 1 [SDF1]) stimulates cell proliferation and survival processes, promoting tumor growth. CXCR4 inhibition diminishes proliferation and migration of tumor cells overexpressing CXCR4 as well as recruitment of Tregs and MDSCs to the tumor.49 The CXCR4 inhibitor plerixafor is approved by the FDA for stem cell mobilization for stem cell transplant. Several other CXCR4 inhibitors are being tested in combination with immune checkpoint inhibitors.

CCR4 Antibodies A humanized monoclonal antibody (mogamulizumab) directed against C-C chemokine receptor 4 (CCR4) selectively blocks the activity of CCR4, which inhibits chemokine-mediated cellular migration and proliferation of T cells, and chemokine-mediated angiogenesis.50 This agent may also induce antibody-dependent cell-mediated cytotoxicity against CCR4-positive T cells. CCR4, a G-coupled protein receptor for C-C chemokines such macrophage inflammatory protein 1 (MIP-1), RANTES, thymus and activation-regulated chemokine (TARC), and monocyte chemotactic peptide 1 (MCP-1), is expressed on the surfaces of some types of T cells, endothelial cells, and neurons.

CCR5 Inhibitors The C-C motif chemokine receptor 5 (CCR5) is expressed by tumor cells, lymphocytes, and macrophages. The corresponding ligand (C-C motif chemokine ligand 5 [CCL5]) is produced by T cells at the invasive margin of tumors with tumor-promoting effects. Inhibition of CCR5 is hypothesized to repolarize TAMs and promote antitumor immunity. CCR5 blockade led to clinical responses in colorectal cancer patients accompanied by immune changes in the tumor microenvironment.51 Moreover, a phase I/II study of a dual CCR2/CCR5 antagonist BMS-813160 in combination with nivolumab for patients with advanced solid tumors is planned.

SOLUBLE FACTORS IDO Inhibition IDO1, a porphyrin-containing oxidoreductase, catalyzes the degradation of L-tryptophan to N-formyl kynurenine and therefore controls a major pathway of tryptophan catabolism. IDO1 inhibits T-cell function through local depletion of tryptophan and production of immunosuppressive kynurenine and its downstream metabolites. High IDO1 expression is associated with a decrease in immune cell tumor infiltration and an increase in Tregs.52 IDO1 expression in tumors has also been associated with poor prognosis, increased progression, and reduced survival. Given the potential clinical impact of this pathway, numerous IDO inhibitors are being developed. In addition, anti–PD-1 treatment upregulates IDO1 expression in tumors as a possible mechanism of resistance to anti–PD1/PD-L1. Epacadostat (Incyte) is the most advanced molecule in development and in numerous clinical combination trials with anti-PD-1 agents. Although very little has been published, epacadostat has demonstrated impressive efficacy in early reported results in advanced melanoma (response rate of approximately 55%), squamous cell carcinoma of the head and neck (approximately 25%), urothelial cell carcinoma (approximately 35%), NSCLC (approximately 35%), and RCC (approximately 45%). Recently, a phase III study in advanced melanoma patients failed to show any improvement in outcome (response rate, progression-free survival, or overall survival) in over 700 randomized patients, leaving the role of IDOi to be in question.53 Indoximod, a small molecule that acts directly on immune cells to reverse IDO pathway–mediated suppression, has shown activity in early-phase clinical studies. The addition of indoximod to pembrolizumab led to an overall response rate (ORR) of 52% in patients with advanced melanoma. BMS-986205 is an IDO inhibitor with single-digit nanomolar potency in phase I/II clinical trials. These agents are being extensively explored in later phase studies.

Arginase Inhibitor

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L-arginine depletion profoundly suppresses T-cell immune responses and promotes T-cell anergy/paralysis via downregulation of the TCR-ζ chain. ARG is the key enzyme that catalyzes L-arginine to downstream byproducts L-ornithine and urea. MDSCs and DCs can express ARG, which can be further upregulated by IL-10, GM-CSF, and other cytokines as well as HIF1α, leading to arginine depletion. CB-1158 is an orally active ARG inhibitor that has antitumor effects in immunocompetent syngeneic mice with a rapid increase in the local concentration of arginine, increasing T cells within the tumor.54 ARG inhibitors likely have the most potential for activity in tumor types where ARG-secreting MDSCs play an immunosuppressive role such as RCC and NSCLC.

TGF-β Kinase Inhibitors The TGF-β signaling pathway is complex and results in either tumor suppression or promoting activity depending on the cellular context. In the tumor microenvironment, TGF-β regulates infiltration of immune cells and cancerassociated fibroblasts, and may exclude T cells leading to anti–PD-1/PD-L1 resistance.55 In preclinical models, pharmacologic inhibition of TGF-β drives immune activation and is able to synergize with other immunotherapeutic agents. Galunisertib is an orally available, small-molecule antagonist of TGF-β receptor type 1 (TGFBR1) that targets the kinase domain of TGFBR1, thereby preventing the activation of TGF-β–mediated signaling. Galunisertib is currently in phase II studies with immune checkpoint inhibitors in several solid tumors.

ADENOSINE A2α RECEPTOR AXIS Adenosine Receptor Inhibitors Extracellular adenosine can reach micromolar levels in the tumor microenvironment, blocking the activation of immune cells and increasing the number of Tregs through activation of the A2α and the low-affinity A2β adenosine receptor. These receptors are also expressed on T cells, NK cells, macrophages, and DCs. Early adenosine-A2α receptor antagonists have shown preclinical efficacy in combination with immune checkpoint inhibitors and are now in clinical trials.56 CPI-444 is one small-molecule inhibitor of the adenosine A2α receptor (ADORA2A) with early responses in lung and bladder cancer.

INNATE IMMUNE MODULATION Pathogen-Associated Molecular Patterns, Damage-Associated Molecular Patterns, and Pattern Recognition Receptors The innate immune system recognizes PAMPs through pattern recognition receptors (PRRs) to initiate immune response. These PRRs can also recognize some endogenous DAMPs, including various tumor-derived antigens. Thus, activation of the innate immune system may play a role in initially recognizing and counteracting malignant cells and synergize with other immune therapies.

Toll-Like Receptor Modulators TLRs and stimulator of interferon genes (STING) are both promising innate immune targets in cancer immunotherapy. TLRs are type I transmembrane proteins and consist of numerous members (TLR1 to TLR13). TLRs are expressed by APCs, such as macrophages, B cells, monocytes, neutrophils, and DCs, and can activate these cells when exposed to PAMPs or DAMPs. TLR agonists are being applied in combination with checkpoint inhibitors to trigger a synergistic effect or as therapeutic cancer vaccine adjuvants to activate DCs. These trials mainly focus on the endosomal TLRs that bind nucleic acids such as TLR3, TLR7, TLR8, or TLR9.57 The antitumor activity of TLR7 and TLR8 agonists is mainly based on the activation of DCs and NK cells as well as the suppression of Tregs.58 TLR3 and TLR4 can signal through TIR (Toll/1L-1 receptor) domain-containing adaptor inducing IFN-α (TRIF) pathway to activate type I IFN response. The TLR7 agonist imiquimod is a small molecule approved as a topical treatment of basal cell carcinoma. A structurally similar analog, resiquimod, is a dual TLR7/TLR8 agonist. The compound has been well tolerated as a topical treatment of actinic keratosis and showed promising results in the topical treatment of early-stage cutaneous T-cell lymphoma.59 TLR agonists SD-101 and IMO-2125 have also demonstrated early promising

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results in melanoma when combined with immune checkpoint inhibitors in unpublished results. Low doses of TLR9 (CpG) injected into a tumor induce the expression of OX40 on CD4+ T cells in the tumor microenvironment. An agonistic anti-OX40 antibody can then trigger a T-cell immune response, which is specific to the antigens of the injected tumor. Remarkably, this combination of a TLR ligand and an anti-OX40 antibody can cure multiple types of cancer and prevent spontaneous genetically driven cancers in murine model systems.60 Most TLR agonists are being developed as intratumoral injectables.

STING Agonists A DC detects tumor-derived DNA, which often originates from cancer cells undergoing necrosis. After binding to cyclic GMP synthase (cGAS), cGMP is produced which activates the receptor for STING, resulting in the expression of various interferons, cytokines, and T-cell recruitment factors leading to priming events in the lymph node. STING is expressed in the endoplasmic reticulum in various epithelial and endothelial cells as well as in hematopoietic cells, including T cells, DCs, and macrophages. Synthetic STING agonists are being actively pursued in drug development. Upon intratumoral administration, these agents bind to STING and activate the STING pathway, which activates NF-κB and interferon regulatory factor 3 (IRF3) in the tumor microenvironment, triggering production of proinflammatory cytokines, including IFNs. Specifically, expression of IFN-β enhances the cross-presentation of tumor-associated antigens by CD103+ DCs to cytotoxic T lymphocytes. Early STING agonists have shown excellent promise in preclinical models, alone and in combination with anti-PD-1, and are being developed in numerous clinical trials.61,62 Intratumoral injection is still necessary to activate the STING receptor efficiently.

Anti-CD47 Monoclonal Antibodies CD47, also known as integrin-associated protein, is a cell–surface transmembrane receptor protein found on many leukocytes. CD47 binds with β-3 integrin, thrombospondin-1, signal regulatory protein α (SIRPα), and other signaling proteins to regulate T-cell activation, cell migration, phagocytosis, and other immune cell functions. Specifically, CD47 bound to SIRPα creates an inhibitory signal for phagocytosis often employed in tumor microenvironments. CD47 is expressed in many tumors and, interestingly, in cancer stem cells. Expression of CD47 may allow cancer stem cells to avoid immune clearance, leading to late-cancer recurrences. It also provides a “do not eat” signal by binding to the N-terminus of SIRPα on immune cells and suppresses phagocytosis. Targeting CD47 with monoclonal antibodies in murine models has shown to effectively treat various cancers.63,64 Currently, multiple phase I trials are investigating CD47 inhibition in acute leukemias and several solid tumors.

Colony-Stimulating Factor 1 Receptor Inhibition Colony-stimulating factor 1 receptor (CSF1R) is a cell-surface receptor for its ligands, colony-stimulating factor 1 (CSF1), and IL-34. CSF1R plays an important role in the development, morphology, survival, and functions of tissue and TAMs. CSF1 is involved in the recruitment and survival of macrophages in tumors, and differentiates monocytes/macrophages into the immunosuppressive TAMs (“M2-like”). Increased CSF1 expression is implicated in tumor progression and metastasis and is associated with poor prognosis in some cancers.65 Currently, both small molecules and monoclonal antibodies are in development as monotherapy and in combination with PD-1 inhibition.

BIFUNCTIONAL FUSION PROTEINS Primarily developed throhugh pioneering antibody technology, antibody framework modification allows for fusing multiple protein components leading to a single molecule possessing several complementary functions. Formats vary and include triomabs that are full-sized antibodies generated from the fusion of two hybridomas; Fab2 consists of two full unique antigen-binding fragments, which are physically linked together; diabodies and tandem single chain variable fragments (scFvs) utilize only variable fragments to bind cognate antigens; and diabodies can link heavy and light chains from opposing Fvs, whereas tandem scFvs connect heavy and light chains linearly as a single molecule. These are based on the use of monoclonal antibody modifications that allows: 1. Bispecific antibodies with two different binding sites, each binding a different molecule, either a cell

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surface protein or soluble protein. Bispecific antibody against angiopoietin 2 (Ang-2) and vascular endothelial growth factor (VEGF)-A binds to Ang-2 and VEGF-A are capable of neutralizing two complementary angiogenic factors that lead to superior vessel normalization and potential immunomodulatory effects in preclinical systems. 2. T-cell bispecific where one of the binding sites is an “antibody” directed at CD3ε component of the TCR leading to activation of T cells through TCR complex stimulation and the other binding sites would bring the activated T cell into the proximity of the cancer through its recognition of a tumor-associated antigen. Bispecific T cell engagers (BiTEs) are a new class of immunotherapeutic molecules. These molecules, BiTEs, enhance the patient’s immune response to tumors by retargeting T cells to tumor cells. BiTEs are constructed of two scFvs connected in tandem by a flexible linker. One scFv binds to a T-cell–specific molecule, usually CD3ε, whereas the second scFv binds to a tumor-associated antigen. Tumor antigens include CD19 (blinatumomab, already approved for acute lymphoblastic leukemia [ALL]), epithelial cell adhesion molecule (EpCAM), carcinoembryonic antigen (CEA), and prostate-specific membrane antigen (PSMA). 3. Immune-mobilizing monoclonal TCRs against cancer (ImmTACs) are in many ways a derivation of BiTEs. ImmTACs comprise a distinct tumor-associated epitope-specific monoclonal TCR with extremely high affinity for expressed epitopes presented by MHC at extremely low density, in place of an scFv recognizing a tumor-associated antigen. This molecule redirects and activates T cells to kill cancer cells expressing extremely low surface epitope densities. IMCgp100 (ImmTAC recognizing a peptide derived from the melanoma-specific protein, gp100, presented by HLA-A*0201) efficiently redirects and activates effector and memory CD3+ T cells. CD8+ T cells redirected by IMCgp100 are potent killers of melanoma cells. It has now completed phase I clinical trials and has entered phase II and III trials primarily directed at uveal melanoma. 4. Immunocytokines are the fusion molecule of cytokines linked to an antibody specific for tumor-specific antigens that are capable of selective localization of the cytokine to the tumor, thereby increasing the therapeutic index of the bioactive (cytokine) molecule. 5. Bifunctional immunostimulatory antibody (i.e., anti-PD-1, anti- CTLA-4) fused to a target binding moiety (receptor extracellular domain) acting as a trap for suppressive ligands (TGF-β, IL-6R, VEGF) that limit the efficacy of antibodies targeting immune checkpoint molecules. M7824 (MSB0011359C) is a novel first-in-class bifunctional fusion protein consisting of a fully human IgG1 anti–PD-L1 monoclonal antibody linked to the extracellular domain of two TGF-β receptor 2 (TGF-βR2) molecules serving as a TGF-β trap. Preclinically, M7824 molecule has been shown with the ability to (1) induce antitumor activity in several murine models by inhibiting the binding of PD-1 to PD-L1; (2) reversing the TGF-β1 induction of mesenchymalization of human carcinoma cells, rendering them more chemosensitive; (3) mediate antibody-dependent cell-mediated cytotoxicity of a range of human carcinoma cells; (4) inhibit the TGF-β1 suppression of NK lysis of tumor cells; and (5) inhibit the suppressive activity of human Tregs on CD4+ T cells.66 A phase I study of M7824 has recently been completed. Similar adverse events seen with other anti–PD-1/PD-L1 MAbs were observed, and clear evidence of clinical benefit was seen.67

Immunocytokines In principle, the fusion of cytokines to suitable antibody molecules, specific for antigens preferentially expressed in the tumor is capable of selective tumor localization, should increase the therapeutic index of the bioactive payload. Whereas many cytokine payloads have been considered and tested preclinically, most clinical activities are based on IL-2, TNF, and IL-12. Both the antibody format and properties of the target antigen can have a profound impact on the performance and mechanism of action of immunocytokines. The cytokine component of the immunocytokine should preserve an intact cytokine activity. Favorable tumor–organ ratios have been reported for fragment-based immunocytokine products in various quantitative biodistribution studies performed in mouse models of cancer. IL-2 conjugated to CEA (cergutuzumab amunaleukin) and FAP (RO6874281) are now in clinical trials.68 These agents also lack binding to CD25, thus preventing Treg activation. Antigen loss by tumor cells may represent an escape strategy for the cancer from monoclonal antibodies that recognize the tumor surface antigens, although perhaps less so for those selective for antigens on stromal cells.

Adoptive Cell Therapy Pioneered by Dr. Steven Rosenberg and his group at the National Institutes of Health, ACT was the first form of

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immune therapy to produce a high response rate in cancer. This approach, in brief, consists of surgically resecting melanoma (or other) tumors, separating TILs, expanding with recombinant IL-2, and coculturing them with autologous tumors.69 Interestingly, this approach is agnostic to the immunogenic antigen; rather, it presumes that TILs are present in the tumor because they recognize tumor antigen(s) and that stimulation and expansion will provide clinical responses. When these expanded TILs were then reinfused into patients, up to one-third of patients experienced clinical responses.70 However, initially, most responses were transient. Several modifications were then employed over the next decades, including selecting fragments of resected tumors where TILs had greater tumor recognition and additional stimulation with CD3 and CD28 antibodies (Fig. 32.3). Of particular importance, however, was the use of lymphodepletion prior to treatment to permit engraftment and persistence of these effector T cells. Using these newer methods, higher and more durable rates of response (up to 54%) could be generated.71 Several elegant proof-of-concept studies have also suggested that ACT may have activity in more common, epithelial cancers. This has been enabled, in part, by the availability of relatively inexpensive WES technology. One difficulty of more widespread use of ACT historically was the need to coculture TILs with autologous tumors. However, WES has allowed for rapid-fire evaluation of all mutations in a tumor, and prediction whether these mutations generate an immunogenic neoantigen peptide in the context of a particular patient’s HLA type. This approach now permits selection and expansion of T cells specific for particular mutations. One patient with cholangiocarcinoma received an infusion enriched for TH1 CD4+ T cells that recognized a mutated Erbb2 interacting protein (ERBB2IP E805G) that resulted in a partial response.72 Interestingly, the patients relapsed after 7 months, received a much more enriched treatment (95%), and has maintained an ongoing near-complete response for 2 years.69 A second compelling case recently used CD4 T cells specific for MAGE-A3, a cancer germline antigen following lymphodepletion and IL-2. Of 19 patients, objective responses were noted in patients with cervical, esophageal, and urothelial carcinomas and osteosarcoma, with reasonable toxicity profiles.73 A third intriguing case reported a response in a patient with metastatic colon cancer with a common mutation (KRAS G12D) and a common HLA haplotype (HLA-C*08-02) treated with CD8 T cells specific for KRAS G12D.74 This study suggested that in contrast to most TILs that target rare mutations, these prevalent genetic subtypes could suggest an “off the shelf” TIL product that could be given to patients across cancer types with KRAS G12D mutations (also common in pancreatic and lung cancers). Finally, a patient with metastatic cervical cancer was treated with CD8 TILs specific for HPV proteins E6 and E7, which resulted in a complete response.75 Surprisingly, however, immunodominant T cells in this patient were specific for neoantigen and cancer germline antigens, rather than viral antigens.76 Although each of these individual patient responses are compelling and a likely building block to further progress, most patients with nonmelanoma cancers still fail to respond to ACT. Further, the high technical and logistical hurdles of ACT remain additional roadblocks to widespread dissemination of this therapy.

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Figure 32.3 Diagram of the adoptive cell therapy of patients with metastatic melanoma. Tumors are resected, and individual cultures are grown and tested for antitumor reactivity. Optimal cultures are expanded in vitro and reinfused into the autologous patient who had received a preparative lymphodepleting chemotherapy.

Chimeric Antigen Receptor T-Cell Therapy In many ways, chimeric antigen receptor T-cell (CAR-T) therapy represents a “next-generation” cellular therapy. These cells are the result of sophisticated cellular engineering and have traversed through several iterations. The latest, so-called third- and fourth- generation CARs have the following features: (1) extracellular antibody singlechain variable fragment similar to a B-cell receptor that recognizes the antigen of interest and does not require presentation in an MHC molecule, (2) intracellular TCR-type signaling domain (mimicking the signal of a TCR encountering the antigen), and (3) two to three other costimulatory signaling domains (CD28, 4-1BB, and possibly another signal such as CD27 or CD134) (Fig. 32.4).77 The upshot is that upon encountering the antigen of interest, all necessary costimulation occurs and the T cell can eliminate the encountered cell. Choosing the most appropriate antigen is extremely critical, as CARs will essentially kill any cell expressing its target antigen. The earliest target that has been the most intensively studied preclinically and clinically has been CD19. This B-cell marker is highly expressed on B-cell acute lymphocytic leukemia and other B-cell malignancies. Further, the effects of depleting healthy B cells can be overcome with intravenous immunoglobulin. The clinical results of CD19-directed CAR therapy has been impressive; B-cell lymphomas have reported

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response rates of up to 80%, with responses in >80% of patients with ALL.78 These cells persist for >1 year, suggesting potential long-term uptake. Notably, relapses occurred in a minority of patients, and typically, the resistant leukemia was CD19 nonexpressing. These results led to the FDA approval of tisagenlecleucel for patients up to 25 years of age with refractory B-cell precursor ALL in addition, axicabtagene ciloleucel, a chimeric antigen receptor (CAR) T cell therapy also directed at CD19, is the second gene therapy approved by the FDA and the first for certain types of non-Hodgkin lymphoma (NHL). Although the clinical outcomes observed in B-cell malignancies are clearly impressive, there has now been a major effort to extend these results to other cancers. The most progress has arguably been in multiple myeloma. CARs targeting the cancer-testis antigen NY-ESO-1 or B-cell maturation antigen (a plasma cell marker) have demonstrated extremely high response rates (80% to 100%) in refractory multiple myeloma with seemingly durable responses.79 Developing CARs to myeloid cancers has been a challenge as many of the hallmark antigens of acute myeloid leukemias are shared by bone marrow stem cells, leading to fears of complete bone marrow aplasia. Equally challenging has been the search for safe and targetable solid tumor antigens. This was illustrated by a human epidermal growth factor receptor 2 (HER2)-targeted CAR that caused fatal pulmonary toxicity, potentially due to low levels of HER2 expression in the lungs.80 Other targets are being tested in clinical trials and include MAGE, NY-ESO, melanoma-associated antigens, HPV-associated antigens, and personalized, neoantigen-specific approaches.77 In addition to aberrant antigen targeting on host tissues, CARs have other toxicities and risks. CRS is the most common and serious toxicity and is characterized by fever, flu-like symptoms, hypotension, hypoxia, and possibly multiorgan toxicity. CRS is mediated by the activation of T cells upon target engagement as they release cytokines such as IL-2, IFN-γ, GM-CSF, and perhaps most critically IL-6. These symptoms tend to occur in the first week, and thus, hospitalization is recommended for 7 days following infusion.81 Although corticosteroids can be effective, it is strongly recommended to avoid steroids as they likely compromise CAR T-cell function. Instead, tocilizumab, a monoclonal antibody to IL-6, tends to rapidly resolve CRS. CRS may occasionally progress to hemophagocytic lymphangiohistocytosis. The other serious and frequent toxicity of CARs is encephalitis, characterized by confusion, somnolence, and aphasia, which can progress to seizures, obtundation, and cerebral edema. Encephalitis often occurs in conjunction with CRS but may occur up to 4 weeks after treatment. This toxicity is not only caused initially by release of cytokines but also results from trafficking of CARs into the central nervous system. Tocilizumab may be used for CRS-associated encephalitis, whereas steroids may be used for severe cases not associated with CRS.

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Figure 32.4 Genetic modification of T cells for the treatment of solid cancers. A: In order to genemodify T cells to confer stable tumor-specific reactivity, one can transduce T cells with an exogenous T-cell receptor (TCR) derived from a naturally occurring or murine T-cell clone or a chimeric-antigen receptor (CAR) derived from a tumor-specific monoclonal antibody. The TCR or CAR is synthesized as fusion proteins and inserted into the appropriate gene transfer vector. B: Depending on the transfer vector selected, the T cells are then electroporated (transposon) or transduced (viral vector) to confer tumor specificity. Vα, Vβ, and Cα, Cβ, TCR alpha and beta chain variable and constant regions, respectively; TM, transmembrane domain; VH and VL, immunoglobulin variable regions; 2A and G4S, linker sequences; Exo, extracellular spacer domain; SD, splice donor; SA, splice acceptor; Ψ, packaging signal; LTR, long terminal repeat; U3, unique 3′ region; R, repeat region; U5, unique 5′ region; RRE, rev response element; cPPT, central polypurine tract; ΔU3, truncated unique 3′ region; SIN, self-inactivating.

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5. Ott PA, Hu Z, Keskin DB, et al. An immunogenic personal neoantigen vaccine for patients with melanoma. Nature 2017;547(7662):217–221. 6. Sahin U, Derhovanessian E, Miller M, et al. Personalized RNA mutanome vaccines mobilize poly-specific therapeutic immunity against cancer. Nature 2017;547(7662):222–226. 7. Xie Y, Akpinarli A, Maris C, et al. Naive tumor-specific CD4(+) T cells differentiated in vivo eradicate established melanoma. J Exp Med 2010;207(3):651–667. 8. Sharma P, Allison JP. Immune checkpoint targeting in cancer therapy: toward combination strategies with curative potential. Cell 2015;161(2):205–214. 9. Pardoll DM. The blockade of immune checkpoints in cancer immunotherapy. Nat Rev Cancer 2012;12(4):252– 264. 10. Wei SC, Levine JH, Cogdill AP, et al. Distinct cellular mechanisms underlie anti-CTLA-4 and anti-PD-1 checkpoint blockade. Cell 2017;170(6):1120–1133.e17. 11. Hodi FS, O’Day SJ, McDermott DF, et al. Improved survival with ipilimumab in patients with metastatic melanoma. N Engl J Med 2010;363(8):711–723. 12. Kamphorst AO, Wieland A, Nasti T, et al. Rescue of exhausted CD8 T cells by PD-1-targeted therapies is CD28dependent. Science 2017;355(6332):1423–1427. 13. Wolchok JD. PD-1 Blockers. Cell 2015;162(5):937. 14. Johnson DB, Balko JM, Compton ML, et al. Fulminant myocarditis with combination immune checkpoint blockade. N Engl J Med 2016;375(18):1749–1755. 15. Johnson DB, Sullivan RJ, Ott PA, et al. Ipilimumab therapy in patients with advanced melanoma and preexisting autoimmune disorders. JAMA Oncol 2016;2(2):234–240. 16. Dubin K, Callahan MK, Ren B, et al. Intestinal microbiome analyses identify melanoma patients at risk for checkpoint-blockade-induced colitis. Nat Commun 2016;7:10391. 17. Blake SJ, Stannard K, Liu J, et al. Suppression of metastases using a new lymphocyte checkpoint target for cancer immunotherapy. Cancer Discov 2016;6(4):446–459. 18. Chauvin JM, Pagliano O, Fourcade J, et al. TIGIT and PD-1 impair tumor antigen-specific CD8+ T cells in melanoma patients. J Clin Invest 2015;125(5):2046–2058. 19. Sakuishi K, Apetoh L, Sullivan JM, et al. Targeting Tim-3 and PD-1 pathways to reverse T cell exhaustion and restore anti-tumor immunity. J Exp Med 2010;207(10):2187–2194. 20. Koyama S, Akbay EA, Li YY, et al. Adaptive resistance to therapeutic PD-1 blockade is associated with upregulation of alternative immune checkpoints. Nat Commun 2016;7:10501. 21. Ascierto PA, Melero I, Bhatia S, et al. Initial efficacy of anti-lymphocyte activation gene-3 (anti–LAG-3; BMS986016) in combination with nivolumab (nivo) in pts with melanoma (MEL) previously treated with anti–PD1/PD-L1 therapy. J Clin Oncol 2017;35(15 Suppl):9520. 22. Hay CM, Sult E, Huang Q, et al. Targeting CD73 in the tumor microenvironment with MEDI9447. Oncoimmunology 2016;5(8):e1208875. 23. Liu J, Yuan Y, Chen W, et al. Immune-checkpoint proteins VISTA and PD-1 nonredundantly regulate murine Tcell responses. Proc Natl Acad Sci U S A 2015;112(21):6682–6687. 24. Gao J, Ward JF, Pettaway CA, et al. VISTA is an inhibitory immune checkpoint that is increased after ipilimumab therapy in patients with prostate cancer. Nat Med 2017;23(5):551–555. 25. Rizvi NA, Loo D, Baughman JE, et al. A phase 1 study of enoblituzumab in combination with pembrolizumab in patients with advanced B7-H3-expressing cancers. J Clin Oncol 2016;34(15 Suppl):TPS3104. 26. Suntharalingam G, Perry MR, Ward S, et al. Cytokine storm in a phase 1 trial of the anti-CD28 monoclonal antibody TGN1412. N Engl J Med 2006;355(10):1018–1028. 27. Sanmamed MF, Rodriguez I, Schalper KA, et al. Nivolumab and urelumab enhance antitumor activity of human T lymphocytes engrafted in Rag2-/-IL2Rγnull immunodeficient mice. Cancer Res 2015;75(17):3466–3478. 28. Segal NH, Logan TF, Hodi FS, et al. Results from an integrated safety analysis of urelumab, an agonist anti-CD137 monoclonal antibody. Clin Cancer Res 2017;23(8):1929–1936. 29. Tolcher AW, Sznol M, Hu-Lieskovan S, et al. Phase Ib study of utomilumab (PF-05082566), a 4-1BB/CD137 agonist, in combination with pembrolizumab (MK-3475) in patients with advanced solid tumors. Clin Cancer Res 2017;23(18):5349–5357. 30. Leyland R, Watkins A, Mulgrew KA, et al. A novel murine GITR ligand fusion protein induces antitumor activity as a monotherapy that is further enhanced in combination with an OX40 agonist. Clin Cancer Res 2017;23(13):3416–3427. 31. Fan X, Quezada SA, Sepulveda MA, et al. Engagement of the ICOS pathway markedly enhances efficacy of

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CTLA-4 blockade in cancer immunotherapy. J Exp Med 2014;211(4):715–725. 32. Dong H, Franklin NA, Roberts DJ, et al. CD27 stimulation promotes the frequency of IL-7 receptor-expressing memory precursors and prevents IL-12-mediated loss of CD8(+) T cell memory in the absence of CD4+ T cell help. J Immunol 2012;188(8):3829–3838. 33. Owonikoko TK, Hussain A, Stadler WM, et al. First-in-human multicenter phase I study of BMS-936561 (MDX1203), an antibody-drug conjugate targeting CD70. Cancer Chemother Pharmacol 2016;77(1):155–162. 34. Curti BD, Kovacsovics-Bankowski M, Morris N, et al. OX40 is a potent immune-stimulating target in late-stage cancer patients. Cancer Res 2013;73(24):7189–7198. 35. Andtbacka RH, Kaufman HL, Collichio F, et al. Talimogene laherparepvec improves durable response rate in patients with advanced melanoma. J Clin Oncol 2015;33(25):2780–2788. 36. Chesney J, Puzanov I, Collichio F, et al. Randomized, open-label phase II study evaluating the efficacy and safety of talimogene laherparepvec in combination with ipilimumab versus ipilimumab alone in patients with advanced, unresectable melanoma. J Clin Oncol 2017:JCO2017737379. 37. Ribas A, Dummer R, Puzanov I, et al. Oncolytic virotherapy promotes intratumoral T cell infiltration and improves anti-PD-1 immunotherapy. Cell 2017;170(6):1109–1119.e10. 38. Johnson DB, Puzanov I, Kelley MC. Talimogene laherparepvec (T-VEC) for the treatment of advanced melanoma. Immunotherapy 2015;7(6):611–619. 39. Maroun J, Muñoz-Alía M, Ammayappan A, et al. Designing and building oncolytic viruses. Future Virol 2017;12(4):193–213. 40. 32nd annual meeting and pre-conference programs of the Society for Immunotherapy of Cancer (SITC 2017): part one. J Immunother Cancer 2017;5(Suppl 2):86. 41. Naing A, Papadopoulos KP, Autio KA, et al. Safety, antitumor activity, and immune activation of pegylated recombinant human interleukin-10 (AM0010) in patients with advanced solid tumors. J Clin Oncol 2016;34(29):3562–3569. 42. Liu B, Kong L, Han K, et al. A novel fusion of ALT-803 (interleukin (IL)-15 superagonist) with an antibody demonstrates antigen-specific antitumor responses. J Biol Chem 2016;291(46):23869–23881. 43. Johnson DE, O’Keefe RA, Grandis JR. Targeting the IL-6/JAK/STAT3 signalling axis in cancer. Nat Rev Clin Oncol 2018;15(4):234–248. 44. Wong AL, Soo RA, Tan DS, et al. Phase I and biomarker study of OPB-51602, a novel signal transducer and activator of transcription (STAT) 3 inhibitor, in patients with refractory solid malignancies. Ann Oncol 2015;26(5):998–1005. 45. Ali K, Soond DR, Pineiro R, et al. Inactivation of PI(3)K p110δ breaks regulatory T-cell-mediated immune tolerance to cancer. Nature 2014;510(7505):407–411. 46. De Henau O, Rausch M, Winkler D, et al. Overcoming resistance to checkpoint blockade therapy by targeting PI3Kγ in myeloid cells. Nature 2016;539(7629):443–447. 47. Chao T, Furth EE, Vonderheide RH. CXCR2-dependent accumulation of tumor-associated neutrophils regulates Tcell immunity in pancreatic ductal adenocarcinoma. Cancer Immunol Res 2016;4(11):968–982. 48. Nywening TM, Belt BA, Cullinan DR, et al. Targeting both tumour-associated CXCR2+ neutrophils and CCR2+ macrophages disrupts myeloid recruitment and improves chemotherapeutic responses in pancreatic ductal adenocarcinoma. Gut 2018;67(6):1112–1123. 49. Gil M, Seshadri M, Komorowski MP, et al. Targeting CXCL12/CXCR4 signaling with oncolytic virotherapy disrupts tumor vasculature and inhibits breast cancer metastases. Proc Natl Acad Sci U S A 2013;110(14):E1291– E1300. 50. Kurose K, Ohue Y, Wada H, et al. Phase Ia study of FoxP3+ CD4 Treg depletion by infusion of a humanized antiCCR4 antibody, KW-0761, in cancer patients. Clin Cancer Res 2015;21(19):4327–4336. 51. Halama N, Zoernig I, Berthel A, et al. Tumoral immune cell exploitation in colorectal cancer metastases can be targeted effectively by anti-CCR5 therapy in cancer patients. Cancer Cell 2016;29(4):587–601. 52. Prendergast GC, Malachowski WP, DuHadaway JB, et al. Discovery of IDO1 inhibitors: from bench to bedside. Cancer Res 2017;77(24):6795–6811. 53. Long GV, Dummer R, Hamid O, et al. Epacadostat (E) plus pembrolizumab (P) versus pembrolizumab alone in patients (pts) with unresectable or metastatic melanoma: results of the phase 3 ECHO-301/KEYNOTE-252 study. J Clin Oncol 2018;36(Suppl):108. 54. Steggerda SM, Bennett MK, Chen J, et al. Inhibition of arginase by CB-1158 blocks myeloid cell-mediated immune suppression in the tumor microenvironment. J Immunother Cancer 2017;5(1):101. 55. Mariathasan S, Turley SJ, Nickles D, et al. TGFβ attenuates tumour response to PD-L1 blockade by contributing to

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exclusion of T cells. Nature 2018;554(7693):544–548. 56. Beavis PA, Milenkovski N, Henderson MA, et al. Adenosine receptor 2A blockade increases the efficacy of antiPD-1 through enhanced antitumor T-cell responses. Cancer Immunol Res 2015;3(6):506–517. 57. Iribarren K, Bloy N, Buqué A, et al. Trial watch: immunostimulation with Toll-like receptor agonists in cancer therapy. Oncoimmunology 2015;5(3):e1088631. 58. Tel J, Sittig SP, Blom RA, et al. Targeting uptake receptors on human plasmacytoid dendritic cells triggers antigen cross-presentation and robust type I IFN secretion. J Immunol 2013;191(10):5005–5012. 59. Rook AH, Gelfand JM, Wysocka M, et al. Topical resiquimod can induce disease regression and enhance T-cell effector functions in cutaneous T-cell lymphoma. Blood 2015;126(12):1452–1461. 60. Sagiv-Barfi I, Czerwinski DK, Levy S, et al. Eradication of spontaneous malignancy by local immunotherapy. Sci Transl Med 2018;10(426):eaan4488. 61. Fu J, Kanne DB, Leong M, et al. STING agonist formulated cancer vaccines can cure established tumors resistant to PD-1 blockade. Sci Transl Med 2015;7(283):283ra52. 62. Ager CR, Reilley MJ, Nicholas C, et al. Intratumoral STING activation with T-cell checkpoint modulation generates systemic antitumor immunity. Cancer Immunol Res 2017;5(8):676–684. 63. Weiskopf K, Jahchan NS, Schnorr PJ, et al. CD47-blocking immunotherapies stimulate macrophage-mediated destruction of small-cell lung cancer. J Clin Invest 2016;126(7):2610–2620. 64. Chao MP, Alizadeh AA, Tang C, et al. Anti-CD47 antibody synergizes with rituximab to promote phagocytosis and eradicate non-Hodgkin lymphoma. Cell 2010;142(5):699–713. 65. Holmgaard RB, Brachfeld A, Gasmi B, et al. Timing of CSF-1/CSF-1R signaling blockade is critical to improving responses to CTLA-4 based immunotherapy. Oncoimmunology 2016;5(7):e1151595. 66. Lan Y, Zhang D, Xu C, et al. Enhanced preclinical antitumor activity of M7824, a bifunctional fusion protein simultaneously targeting PD-L1 and TGF-β. Sci Transl Med 2018;10(424):eaan5488. 67. Strauss J, Heery CR, Schlom J, et al. Phase I trial of M7824 (MSB0011359C), a bifunctional fusion protein targeting PD-L1 and TGFβ, in advanced solid tumors. Clin Cancer Res 2018;24(6):1287–1295. 68. Klein C, Waldhauer I, Nicolini VG, et al. Cergutuzumab amunaleukin (CEA-IL2v), a CEA-targeted IL-2 variantbased immunocytokine for combination cancer immunotherapy: overcoming limitations of aldesleukin and conventional IL-2-based immunocytokines. Oncoimmunology 2017;6(3):e1277306. 69. Yang JC, Rosenberg SA. Adoptive T-cell therapy for cancer. Adv Immunol 2016;130:279–294. 70. Rosenberg SA, Packard BS, Aebersold PM, et al. Use of tumor-infiltrating lymphocytes and interleukin-2 in the immunotherapy of patients with metastatic melanoma. A preliminary report. N Engl J Med 1988;319(25):1676– 1680. 71. Rosenberg SA, Yang JC, Sherry RM, et al. Durable complete responses in heavily pretreated patients with metastatic melanoma using T-cell transfer immunotherapy. Clin Cancer Res 2011;17(13):4550–4557. 72. Tran E, Turcotte S, Gros A, et al. Cancer immunotherapy based on mutation-specific CD4+ T cells in a patient with epithelial cancer. Science 2014;344(6184):641–645. 73. Lu YC, Parker LL, Lu T, et al. Treatment of patients with metastatic cancer using a major histocompatibility complex class II-restricted T-cell receptor targeting the cancer germline antigen MAGE-A3. J Clin Oncol 2017;35(29):3322–3329. 74. Tran E, Robbins PF, Lu YC, et al. T-cell transfer therapy targeting mutant KRAS in cancer. N Engl J Med 2016;375(23):2255–2262. 75. Stevanovic´ S, Draper LM, Langhan MM, et al. Complete regression of metastatic cervical cancer after treatment with human papillomavirus-targeted tumor-infiltrating T cells. J Clin Oncol 2015;33(14):1543–1550. 76. Stevanovic´ S, Pasetto A, Helman SR, et al. Landscape of immunogenic tumor antigens in successful immunotherapy of virally induced epithelial cancer. Science 2017;356(6334):200–205. 77. Fesnak AD, June CH, Levine BL. Engineered T cells: the promise and challenges of cancer immunotherapy. Nat Rev Cancer 2016;16(9):566–581. 78. Maude SL, Frey N, Shaw PA, et al. Chimeric antigen receptor T cells for sustained remissions in leukemia. N Engl J Med 2014;371(16):1507–1517. 79. Rapoport AP, Stadtmauer EA, Binder-Scholl GK, et al. NY-ESO-1-specific TCR-engineered T cells mediate sustained antigen-specific antitumor effects in myeloma. Nat Med 2015;21(8):914–921. 80. Morgan RA, Yang JC, Kitano M, et al. Case report of a serious adverse event following the administration of T cells transduced with a chimeric antigen receptor recognizing ERBB2. Mol Ther 2010;18(4):843–851. 81. Neelapu SS, Tummala S, Kebriaei P, et al. Chimeric antigen receptor T-cell therapy—assessment and management of toxicities. Nat Rev Clin Oncol 2018;15(1):47–62.

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PART IV

Cancer Prevention and Screening

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33

Tobacco Use and the Cancer Patient Graham W. Warren and Vani N. Simmons

INTRODUCTION Tobacco use is commonly described as the largest preventable cause of cancer. Over 50 years ago, tobacco was recognized as a causative factor for cancer in the 1964 U.S. Surgeon General’s Report (SGR) on Smoking and Health.1 In the 2014 SGR, tobacco has been identified as a causative agent for multiple diseases and cancers, resulting in over 20 million deaths in the United States between 1965 and 2014.1 Tobacco use is a well-established addictive habit that typically begins in youth and unfortunately continues into adulthood, leading to significant adverse consequences. With respect to cancer, the 2014 SGR provides substantial evidence related to the effects of smoking by cancer patients with the following conclusions: 1. In cancer patients and survivors, the evidence is sufficient to infer a causal relationship between cigarette smoking and adverse health outcomes. Quitting smoking improves the prognosis of cancer patients. 2. In cancer patients and survivors, the evidence is sufficient to infer a causal relationship between cigarette smoking and increased all-cause mortality and cancer-specific mortality. 3. In cancer patients and survivors, the evidence is sufficient to infer a causal relationship between cigarette smoking and increased risk for second primary cancers known to be caused by cigarette smoking, such as lung cancer. 4. In cancer patients and survivors, the evidence is suggestive but not sufficient to infer a causal relationship between cigarette smoking and the risk of recurrence, poorer response to treatment, and increased treatmentrelated toxicity. At the time of the 10th edition of this book,2 there had been relatively little effort to address tobacco use in cancer patients. The critical need to address tobacco use by cancer patients is now recognized, including advocacy and/or guidelines from the American Association for Cancer Research (AACR), American Society for Clinical Oncology (ASCO), National Comprehensive Cancer Network (NCCN), and other cancer organizations.3 The overall objective of this chapter is to discuss tobacco use by cancer patients, the clinical effects of smoking in cancer patients, methods to address tobacco use by cancer patients, and areas of needed research.

TOBACCO USE EPIDEMIOLOGY, ADDICTION, AND TOBACCO PRODUCT EVOLUTION Additional discussion on tobacco use epidemiology and carcinogenesis is presented in Chapter 6. In brief, cigarette smoking is the predominant form of tobacco use in most countries, with an estimated 5.8 trillion cigarettes smoked in 2014.4 An estimated 100 million people died from tobacco-related causes in the 20th century, and an additional estimated 1 billion people will die in the 21st century based on current use projections. Approximately 50% of people who use tobacco will die of a tobacco-related disease. Whereas many developed countries have plateaued or decreased tobacco use in recent years, many undeveloped countries have demonstrated an increase in tobacco use prevalence. Although tobacco is associated with an estimated $1 trillion in economic burden worldwide, less than 1% of tobacco revenues are typically used for tobacco-control activities. Nicotine is the predominant addictive component of tobacco.2 During cigarette smoking, nicotine is delivered within seconds to the brain, leading to stimulation of the dopaminergic system and a rewarding experience that

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can be reinforced by environmental stimuli. For example, an individual who smokes while drinking their morning coffee may associate coffee, or even holding a coffee cup in their hand, with the reward from smoking. Substantial work has been conducted on the addictive nature of tobacco and nicotine, and readers are referred to several comprehensive reviews on this topic.5–7 There have been substantial changes in the landscape of tobacco use over time as a direct consequence of cigarette-centered policies and regulations aimed at reducing the harmful effects and number of deaths caused by smoking.1,4 Under this new landscape, novel and emergent noncigarette tobacco products such as cigars, cigarillos, snuff, chewing tobacco, water pipes (hookahs), electronic cigarettes (e-cigarettes), heat-not-burn products, and other forms of tobacco consumption have been growing in demand as a consequence of aggressive and sophisticated marketing by the tobacco industry. Consumption patterns have also changed due to efforts by the tobacco industry to make cigarettes appear safer, such as low-tar or filtered cigarettes and the addition of flavoring (e.g., menthol, vanilla, fruits).8 Although these efforts may have changed cigarette consumption patterns, they have not reduced cancer risk. The introduction of low-tar and filtered cigarettes actually increased risk by promoting deeper inhalation and higher rates of addiction with no reductions in cancer risk,8,9 resulting in subsequent changes in lung cancer from centrally located squamous cell cancers to peripherally located nonsquamous cell cancers.

ELECTRONIC NICOTINE DELIVERY SYSTEMS, OR ELECTRONIC CIGARETTES The introduction and rapid exponential increase in the use of e-cigarettes (also known as e-cigs, nicotine vaporizers, or electronic nicotine delivery systems [ENDS]) warrants attention. E-cigarettes are relatively new electronic or battery-powered devices that activate a heating element that vaporizes a liquid solution contained in a cartridge, which is then inhaled as vapor into the lungs.10 The liquid solution can have any number of possible chemical compositions with or without nicotine, flavoring, and other additives. Delivery of these chemicals and nicotine can be influenced by liquid contents as well as by the heating element and vaporization process. There are hundreds of brands, spanning self-contained disposable devices to more personalized devices where users can modify the heating and vaporization process as well as select designer liquid compositions from e-cigarette shops. Given the extremely broad availability of brands and constituents, there has been substantial controversy over the potential benefits or harms of e-cigarettes. The primary controversy lies in advocating for or against the safety of e-cigarettes in the context of primary use and use in children (without a history of smoking) versus use in people who smoke cigarettes.11,12 These possible negative outcomes include the fear that e-cigarette use by youth could lead to an increased risk of using of combustible tobacco products. For individuals who smoke, intuition suggests that e-cigarettes could be safer than combustible tobacco given the far fewer chemical constituents as compared with cigarette smoke, but there is potential for e-cigarettes to discourage smokers from quitting by facilitating nicotine addiction.10 A recent study of 533 survey respondents who were current smokers and who had ever used e-cigarettes suggests that higher spending on e-cigarettes was associated with greater health symptoms such as chest pain and shortness of breath.13 Although the authors suggested that e-cigarettes had adverse health effects among cigarette smokers, there was little discussion on whether the onset of adverse health effects was, instead, a driver of ecigarette use. Given the relatively short time frame of widespread use of e-cigarettes, there are limited data on the long-term harms and benefits of e-cigarettes. Literature is rapidly expanding in this field, and the relationship between e-cigarette use and long-term health effects remains unclear. Also uncertain are the potential health effects of e-cigarette use in the context of surgery, chemotherapy, radiotherapy, or targeted agents used in cancer treatment.10 To address the issue of e-cigarette use in cancer patients, AACR and ASCO,10 as well as the International Association for the Study of Lung Cancer (IASLC),14 have issued policy statements that acknowledge the potential benefits and harms of e-cigarettes in cancer patients. To date, e-cigarettes have not been approved by the U.S. Food and Drug Administration (FDA) as therapeutic devices to aid in quitting smoking. E-cigarettes deliver nicotine in a manner that mimics the sensory and behavioral aspects of smoking; thus, smokers report that they confer a desirable behavioral advantage as compared to nicotine replacement therapy (NRT).15 However, recent data suggest that more smokers now report using e-cigarettes to try and quit smoking than use NRT.16 Given the current lack of safety and efficacy data for e-cigarettes in cancer patients, AACR, ASCO, and IASLC recommend

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that health-care providers recommend the use of FDA-approved methods of smoking cessation. This is in contrast to the Royal College of Physicians of the United Kingdom, which has endorsed the use of e-cigarettes for quitting smoking in the general population,17 including authors who have provided a thoughtful approach to the potential risks and benefits.18 In contrast to the rapidly growing literature on e-cigarette use in the general population, few studies have examined e-cigarette use in cancer patients. In an observational study of 1,074 cancer patients who reported current smoking between 2012 and 2013, e-cigarette use appeared to increase from 10.6% to 38.5%.19 E-cigarette users were more likely to be diagnosed with a lung and head or neck cancer, but e-cigarette use did not produce higher smoking cessation rates at follow-up. In a smaller study of 106 patients, self-reported e-cigarette use correlated with lower quit rates,20 although this smaller study demonstrated a remarkably high overall smoking cessation rate. Data are lacking on the safety or health effects of e-cigarettes in cancer patients. Significant research is needed to determine the health effects and potential cessation efficacy of e-cigarettes in cancer patients. The use of ecigarettes is also impacted by a rapidly changing policy landscape.21 In May 2016, the FDA finalized a rule to extend authority to cover all tobacco products, including ENDS, all cigars, hookah tobacco, pipe tobacco, nicotine gels, and dissolvable nicotine products. Three restrictions included in the final rule include a minimum age of purchase of 18 years, required health warnings, and prohibited vending machine sales (unless the retailer can ensure that individuals younger than age 18 years are prohibited from entering). The rule, which went into effect in August 2016, also grants the FDA authority to regulate the manufacture, import, labeling, marketing, promotion, sale, and distribution of ENDS. In July 2017, the FDA extended timelines for certain compliance measures including review of newly regulated noncombustible products, such as ENDS, to August 8, 2022. It is anticipated that regulatory control over e-cigarettes will be dynamic in the coming years.

DEFINING TOBACCO USE BY THE CANCER PATIENT Virtually all studies examining the relationship between tobacco use and cancer treatment outcomes have focused on the effects of combustible cigarette smoking. Few studies report associations between other forms of tobacco use (e.g., smokeless, cigars, cigarillos) and outcomes in cancer patients. Furthermore, the definition of smoking across published studies varies substantially.22,23 In studies of cancer patients, smoking has been defined as current (examples include smoking after diagnosis, at diagnosis, in the weeks before diagnosis, within the past 30 days, within 12 months prior to diagnosis, after diagnosis, within the past 10 years, etc.), former (recent, intermediate-, or long-term quit for 1, 3, 6, or 12 months or 2, 5, or 10 years), never, quitting after diagnosis, and according to exposure (examples include multiple pack-year cutoffs, Brinkman’s index, years of smoking, and years of smoking within a predefined period of time such as the 5 years prior to diagnosis).22 There are four primary categories for smoking status: 1. Never smoking is typically defined as having smoked less than 100 cigarettes in a person’s lifetime and no current cigarette use. These patients are generally considered as a reference group in many studies. Categories 2 to 4 require that a person has smoked at least 100 cigarettes in his or her lifetime. 2. Former smoking is typically defined as no current cigarette use but having quit for usually more than 1 year. 3. Recent smoking (or recent quit) is generally defined as having stopped smoking within the recent past, typically for a period of 1 week to 1 year. 4. Current smoking is typically defined as actively smoking one or more cigarettes per day every day or some days. Ever smoking is a combination of groups 2 to 4 (i.e., former, recent, and current smokers) that has been used to report negative associations between smoking and cancer outcomes in many studies.1 Defining smoking according to ever smoking status limits the ability to interpret the effects of current smoking on a clinical outcome and is not informative for smoking cessation treatment. However, defining exposure according to current smoking status allows for the analysis of potentially reversible effects as well as for the potential implementation of smoking cessation to prevent the adverse outcomes of smoking on cancer patients. Recognizing the deficits in defining tobacco use by cancer patients, the National Cancer Institute and AACR convened a task force in 2013 to develop standard methods to assess tobacco use in clinical trials.24,25 The resultant Cancer Patient Tobacco Use Questionnaire (C-TUQ) consists of core items as well as optional items to

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define tobacco use in a manner that can be translated across clinical trials, thus providing the opportunity to compare the effects of one or more tobacco parameters using a common format. The primary focus for the remainder of this chapter is on current smoking and a discussion of methods to address tobacco use by the cancer patient through accurate assessment and structured tobacco cessation support.

TOBACCO USE AND CESSATION BY THE CANCER PATIENT Approximately 20% to 30% of all cancer patients self-report current smoking at the time of cancer diagnosis, with higher rates in traditionally tobacco-related disease sites such as head and neck or lung cancer and lower rates in traditionally non–tobacco-related disease sites such as breast or prostate cancer.1 However, studies demonstrate that approximately 30% of cancer patients who smoke misrepresent tobacco use by self-report26–28; thus, biochemically confirmed tobacco use patterns are higher than those obtained by self-report. There are few structured evaluations of smoking status at diagnosis and follow-up in cancer patients, but a recent review of 131 head and neck and lung cancer studies demonstrated that approximately 33% of patients reported current smoking and that 53% of patients reporting current tobacco use at diagnosis also reported continued tobacco use at follow-up.29 The prevalence of current smoking among long-term adult cancer survivors appears to be declining and was recently estimated at approximately 9.3%,30 with higher rates in tobacco-related disease sites and higher rates among cancer survivors than in the general population.31 Data from the Childhood Cancer Survivor Study and the 2009 Behavioral Risk Factor Surveillance System indicate that approximately 3% to 8% of cancer survivors use smokeless tobacco products.32,33 A noteworthy limitation in these prevalence rates is that cancer patients who were current smokers at the time of death may not be included. As a result, estimates of smoking rates in cancer survivors may be misleading and may underestimate true tobacco use patterns for cancer patients. Furthermore, patients may be attracted to alternative tobacco products due to less social stigma and the non–evidence-based perception that these products are healthier alternatives compared to cigarette smoking; however, very little data are usually collected on alternative tobacco product use. Continued tobacco use by cancer patients often represents a combined failure by the patient to recognize the need to stop smoking even after a cancer diagnosis and the lack of effort by health-care providers to address tobacco use with evidence-based assessments and tobacco cessation support. In two large surveys of oncologists, approximately 90% asked cancer patients about tobacco use and 80% advised patients to quit smoking.34,35 Although 90% also agreed that smoking negatively affected cancer treatment and that smoking should be a standard part of cancer care, only 30% to 40% discussed the use of cessation of medications or provided assistance with cessation. Although providers may not regularly assist with cessation support for cancer patients, “opt out” approaches to tobacco cessation, where patients are screened for tobacco use and automatically referred to dedicated tobacco treatment programs,36 have been promising. A study of nearly 12,000 cancer patients screened for tobacco use with over 2,700 patients referred to a dedicated phone-based cessation program demonstrated an 81% contact rate by phone and only 3% rate of patients rejecting participation in the cessation program.37 In contrast, only 1.6% of patients receiving a mailing participated in the program, suggesting mailed reactive enrollment is a poor approach to accrue cancer patients to a smoking cessation intervention. Similar results have been demonstrated in a study of 102 head and neck cancer patients referred for cessation support, with 78% accepting referral for treatment and 94% reporting acceptance for the intervention.38 These data highlight that cancer patients are receptive to receiving structured tobacco cessation support. The risk for relapse remains high among cancer patients who quit smoking. Although patients may enroll in a cessation program, clinicians must realize that although relapses in the general population usually occur within 1 week of cessation, relapses in cancer patients may be delayed due to cancer treatment–related variables such as surgical or other posttreatment healing.39 Predictors of relapse have included less confidence in quitting ability, higher risk of depression, greater withdrawal and addiction, greater fears about cancer recurrence, lower cancerrelated risk perceptions, and shorter period of quitting, such as in preparation for surgery.39–43 Unfortunately, many studies have either evaluated predictors of relapse only for a narrow group of patients participating in a cessation trial or for heterogenous groups of patients who do not participate in a structured smoking cessation program. Significant research is needed to identify smoking relapse predictors among a more heterogeneous group of cancer patients with access to structured cessation support so that intervention efforts may be personalized to those at high risk for relapse.

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SMOKING CESSATION IN THE CONTEXT OF LUNG CANCER SCREENING In 2002, the National Lung Screening Trial (NLST) initiated an 8-year multicenter randomized clinical trial to evaluate low-dose computed tomography (LDCT) screening. NLST results demonstrated that LDCT reduced mortality from lung cancer by 20% as compared to chest x-ray.3,44 Based on these findings, the U.S. Preventive Services Task Force (USPSTF) issued a category B recommendation for screening of high-risk individuals (i.e., ages 55 to 80 years, at least a 30-pack-year history of smoking, and current or former smokers who have quit within the past 15 years). The Affordable Care Act and the Centers for Medicare & Medicaid Services (CMS) have approved coverage for LDCT and require that former smokers be counseled on the importance of abstinence, that current smokers receive counseling about the importance of cessation, and that patients should receive information regarding smoking cessation interventions if appropriate. Prominent professional and medical societies, including NCCN, IASLC, and ASCO, support the integration of smoking cessation interventions in the context of lung cancer screening. Simulation work has demonstrated that the addition of a smoking cessation program to an LDCT screening program can substantially improve cost-effectiveness.45 Moreover, 7 years of smoking cessation have been shown to reduce mortality to a level comparable to the benefit of LDCT with longer durations of smoking cessation exceeding the benefit of LDCT screening.46 It is estimated that half of patients who receive a screening test will be current smokers. Motivation to quit smoking among individuals undergoing lung screening is generally high.47 A review of nine cross-sectional, longitudinal, and randomized controlled studies examined the effect of computed tomography screening for lung cancer on smoking behaviors and found quit rates ranging from 6.6% to 42%.48 Although findings have been mixed, some studies suggest that motivation can be impacted by lung screening results. Early studies suggest individuals with abnormal screenings were found to demonstrate greater motivation to quit smoking and a higher likelihood of quitting,49,50 but limited data exist on the efficacy of smoking cessation interventions conducted in the LDCT setting with no significant intervention effects observed to date.51 A recent review noted that promoting smoking cessation with LDCT is a high priority, but only 36% of providers recommend cessation medications and approximately 60% provide counseling or refer patients to a quitline.52 Methods to integrate cessation into LDCT are currently active areas of research.

THE CLINICAL EFFECTS OF SMOKING ON CANCER PATIENTS Cancer treatment is generally defined according to disease site, stage, treatment type (surgery, chemotherapy [CT], radiotherapy [RT], or biologic therapy), and primary treatment objective, such as cure or palliation. A comprehensive discussion of the effects of smoking on cancer patients is beyond the scope of a single chapter, but the 2014 SGR provides an outstanding and overwhelming evidence base concluding that “the evidence is sufficient to infer a causal relationship between cigarette smoking and adverse health outcomes.”1 Overall, approximately 75% to 80% of studies in the SGR demonstrated a negative association between smoking and outcome with approximately 65% to 70% of studies demonstrating statistically significant negative associations. This chapter provides an illustrative review of the adverse effects of tobacco across disease sites and treatment modalities (i.e., surgery, CT, and RT), and effects are discussed across the categories of mortality, recurrence and cancer-related mortality, toxicity, and risk of second primary cancer. Evidence for the benefits of smoking cessation are presented within each section.

The Effect of Smoking and Smoking Cessation on Overall Mortality or Overall Survival Substantial evidence demonstrates that current smoking by cancer patients increases the risk of overall mortality across virtually all cancer disease sites and for all treatment modalities. Evidence from the 2014 SGR demonstrates that in 35 studies evaluating the effects of current smoking on overall mortality, the median risk for increased mortality was 22% higher in former smokers and 51% higher in current smokers.1 In a parallel cohort of 62 studies evaluating the effects of smoking on overall survival, current smoking was associated with decreased overall survival in 77% of studies. Several studies supported a higher risk of mortality with a higher number of cigarettes consumed. The lower risks associated with former smoking supported a benefit for smoking cessation. Collectively, these studies provide significant data associating current smoking with increased overall mortality across most disease sites, tumor stages, treatment modalities, and in both traditionally tobacco-related and non–

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tobacco-related cancers. However, the potential significance of smoking is perhaps best exemplified by Bittner et al.,53 who analyzed causes of death in prostate cancer patients demonstrating that more than 90% died of causes other than prostate cancer but that current smoking increased the risk of non–prostate cancer death between 3- and 5.5-fold. As a result, tobacco use and cessation may be of paramount importance to cancers with high cure rates such as prostate cancer or breast cancer simply because patients may be at most risk of death from non–cancerrelated causes such as heart disease, pulmonary disease, or other diseases related to smoking and tobacco use. There are several studies evaluating the effects of smoking cessation after a cancer diagnosis on overall mortality or survival. In a prospective study of 321 stage I to III lung cancer patients treated with surgery, quitting smoking after diagnosis and before surgery reduced overall mortality as compared with continued smoking (hazard ratio [HR], 0.34; 95% confidence interval [CI], 0.16 to 0.71).54 A retrospective analysis of 284 limitedstage small-cell lung cancer patients demonstrated that quitting at or after diagnosis also significantly reduced mortality as compared with continued smoking (HR, 0.55; 95% CI, 0.38 to 0.79).55 A retrospective analysis of 549 glottic cancer patients treated with RT demonstrated that quitting smoking after RT was associated with increased survival (70%) as compared with continued smoking (36%, P < .001).56 In a study of stereotactic body RT (SBRT) for curative treatment of 119 lung cancer patients who smoked at the time of SBRT, continued smoking after diagnosis significantly increased mortality as compared with patients who quit smoking (HR, 2.07; 95% CI, 1.02 to 4.2).57 In a prospective evaluation of 1,632 male cancer patients from the Shanghai Cohort Study, continued smoking after diagnosis significantly increased mortality as compared with quitting smoking (HR, 1.76; 95% CI, 1.37 to 2.27), with significant benefits noted particularly in patients with lung, colorectal, and bladder cancer, and trends toward improved survival in other cancers.58 Narrowing the effects of smoking and cessation to the time of cancer treatment, Browman et al.59 reported on 148 head and neck cancer patients treated with RT, demonstrating that patients who smoked during RT had a trend toward increased risk of overall mortality (relative risk [RR], 1.17; P = .07) as compared with patients who abstained from smoking or smoked less than one cigarette per day. Although these studies evaluated cessation after diagnosis, there was little discussion about the efficacy of a dedicated smoking cessation effort or program on survival. The potential benefit of using a phone-based smoking cessation program to improve survival has been reported.37,60 Patients identified as current smokers through the electronic medical record were automatically referred to a phone-based smoking cessation program that proactively reached out to patients and provided cessation support. In 224 current smoking lung cancer patients who were treated through the cessation program, continued smoking increased overall mortality by 79% as compared with patients who quit smoking (HR, 1.79; 95% CI, 1.14 to 2.82). These data suggest that relatively minimal interventions structured to increase cessation support can have a meaningful improvement in survival outcomes for cancer patients who smoke. Although several studies support the benefits of cessation after diagnosis, there are other studies that are less conclusive. In three prospective studies of head and neck cancer patients,61 breast cancer patients,62 and colorectal cancer patients,63 the effects of continued smoking or quitting smoking were compared with never smoking. In all three studies, continued smoking significantly increased risk of mortality as compared with never smoking, but quitting smoking was also associated with an increased risk as compared with never smoking. Although the magnitude of risk was lower in patients who quit smoking as compared with those who continued smoking, effects did not appear to be significantly different between the two groups.

The Effect of Smoking on Cancer Recurrence and Cancer-Related Mortality The primary objective of cancer therapy is to cure cancer and prevent recurrence. However, smoking has been shown to increase cancer recurrence and cancer-related mortality. As summarized in the SGR,1 82% of the 51 studies reviewed demonstrated a significant association between smoking and cancer recurrence. In studies evaluating the effects of current and former smoking, recurrence was increased by a median of 42% in current smokers as compared with 15% in former smokers. Regarding cancer-specific mortality or survival, current smoking increased the risk of cancer-related mortality by a median of 61% as compared with 3% in former smokers. Quitting smoking after diagnosis has also been shown to affect recurrence and cancer-related mortality. In 321 lung cancer patients, quitting smoking after diagnosis reduced recurrence and metastasis by 46% (HR, 0.54; 95%, 0.3 to 1.0).54 Similar observations were shown for small-cell lung cancer patients (HR, 0.59; 95% CI, 0.34 to 0.98).55 Quitting smoking in head and neck cancer patients was associated with increased local control as compared with patients who continued smoking (81% versus 94%; P < .001),56 a trend that was also observed in patients who quit smoking or smoked less than one cigarette per day during RT (RR, 0.81; P = .056).59 Garden et

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al.64 evaluated 1,046 advanced oropharyngeal cancer patients treated with RT. Findings demonstrated that continued smoking trended toward decreased local control as compared with quitting smoking (67% versus 78%, P = .08). In a cohort of 4,562 breast cancer patients, continued smoking after diagnosis significantly increased risk for breast cancer mortality (HR, 1.72; 95% CI, 1.13 to 2.60) with no change in risk for patients who quit smoking (HR, 1.15; 95% CI, 0.7 to 1.90).62

The Effect of Smoking and Cessation on Cancer Treatment Toxicity The effects of smoking on cancer treatment toxicity are highly dependent on disease site, treatment modality (e.g., surgery, CT, RT), and timing of toxicity. Across disease sites and treatments, current smoking has been shown to increase complications from surgery, RT, and CT. Toxicity associated with smoking has been related to pulmonary complications, infections, wound healing, scarring and fibrosis, urinary and bowel complications, mucositis, hospitalization, postoperative death, vasomotor symptoms, and non–cancer-related outcomes such as continued risk for heart disease, pulmonary disease, and other outcomes.1 Overall, of 82 studies reporting toxicity from the 2014 SGR, 95% demonstrated an association between smoking and toxicity, including 80% demonstrating a statistically significant association. Of 49 studies evaluating the effects of current smoking, 88% demonstrated a significant effect on toxicity. Smoking cessation has been associated with improvements in cancer treatment toxicity and other aspects of cancer-related quality of life. In a large study of 7,990 lung cancer patients from the Society of Thoracic Surgeons Database, current smoking increased the risk of pulmonary complications by 80% and hospital mortality 3.5fold.65 However, smoking cessation for 2 weeks reduced risks for pulmonary complications, whereas cessation for 1 month reduced risks for hospital mortality. Vaporciyan et al.66 also showed that current smoking increased the risk of pulmonary complications 2.7-fold as compared with smoking cessation for at least 1 month prior to surgery. In 1,335 patients with gastric cancer treated with R0 radical gastrectomy, quitting smoking for 4 to 8 weeks prior to surgery prevented complications associated with continued smoking.67 A similar result was observed in preventing wound healing complications in 188 patients with head and neck or cervical esophageal cancer who underwent free flap reconstructive surgery: quitting smoking for 3 or more weeks prior to surgery reduced complications as compared with continued smoking.68 In 383 glottic cancer patients treated with RT, quitting smoking after RT decreased 10-year complication rates as compared with continued smoking (11% versus 28%, P = .031).69 However, in a striking example of the potentially reversible effects of smoking in 205 head and neck cancer patients treated with RT,70 43% of smoking patients treated in the morning experienced grade 3+ mucositis compared with 72% of smokers treated in the afternoon (P = .04). These data suggest that reducing smoking overnight may yield a clinical benefit in reduced toxicity. Although all toxicity may not be acutely reversed, these encouraging data show that patients can make clinically meaningful improvements in their health and/or cancer treatment within a short time frame by quitting smoking. In 2,442 lung cancer patients evaluated with quality-of-life assessments 6 months after diagnosis, quitting smoking was associated with improved quality of life (32% with poor quality of life in continued smokers versus 23% in patients who quit smoking, P < .001).71 In 915 colorectal cancer survivors, persistent smoking was associated with decreased quality of life, decreased physical function, and fatigue (P < .05); however, quitting smoking was not associated with poor outcomes.72 Similar results were observed in a prospective trial of 134 head and neck or lung cancer patients with repeated assessments at 2, 4, 6, and 12 months after surgery.73 Patients who quit smoking after diagnosis have also been found to have higher performance status, even after controlling for disease stage, age, cancer therapy type, and comorbidities.74 In a prospective study of head and neck cancer patients after cancer treatment, higher quality of life was observed among those who had quit in the prior 12 months as compared to current smokers.75 Smoking cessation has also been associated with improved sexual function after surgery for prostate cancer.76 Collectively, these studies support an important benefit of quitting smoking on improved quality of life.

The Effect of Smoking and Cessation on Risk of Second Primary Cancer Continued smoking by cancer patients causes an increase in developing a second primary cancer.1 In 26 studies reviewed by the 2014 SGR, smoking increased the risk of developing second cancers by a median of 2.2-fold for current smokers versus 1.2-fold for former smokers. Although an increase in tobacco-related cancers was more prominent, other studies have demonstrated that smoking also increases risk for second primary cancers in traditionally non–tobacco-related disease sites. For example, Ford et al.77 found that breast cancer patients who

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were former smokers had a 3-fold increased risk of developing lung cancer, but current smokers had a 13-fold increased risk. In nearly 1,100 estrogen receptor (ER)-positive breast cancer patients, current smokers had a 1.8fold increased risk of developing a second contralateral breast cancer, and current smokers at most recent followup had a 2.2-fold increased risk; however, former smokers at diagnosis or most recent follow-up had no increased risk.78 In 2,700 5-year survivors of testicular cancer, current smokers had a 1.8-fold increased risk of developing a second primary cancer as compared with all other survivors.79 Smoking cessation after diagnosis has been shown to reduce the risk of developing a second primary cancer. In a study of 1,050 glottic cancer patients, stopping smoking during or after radiotherapy reduced risk of second primary cancer from 21% to 13% (P = .032).80 Combining smoking with cytotoxic cancer treatment (RT or CT) has also been observed to further exacerbate risk beyond the effects of smoking alone. In ER-positive breast cancer patients, treatment with RT had no significant effect on the risk of developing a contralateral breast cancer, but RT combined with current smoking increased the risk of contralateral cancer by 9-fold.77 In an examination of Hodgkin disease patients, non–heavy smokers (defined as never smoker, former smoker, or smoking less than one pack per day) had a relative risk of a second primary cancer of between 4- and 7-fold when treated with CT or RT as compared with patients who received no RT or CT.81 However, heavy smokers had a 6-fold increased risk in the absence of RT and CT and a 17- to 49-fold increased risk when combined with RT and/or CT. These observations suggest that smoking combined with cytotoxic cancer therapy may increase risk of developing a second primary cancer, perhaps through promotion of mutations induced by CT and RT in the presence of tobacco smoke.

Human Papillomavirus, Epidermal Growth Factor Receptor, Anaplastic Lymphoma Kinase, Programmed Cell Death Protein 1, and Smoking Data over the past decade have shown that head and neck cancer patients who are human papillomavirus (HPV) positive are known to have an improved prognosis as compared with patients with HPV-negative tumors.82 Patients who have HPV-positive tumors typically have increased p16 expression and often respond better to conventional cancer therapy including RT and CT. Many HPV-positive patients are never smokers or have a lighter smoking history. However, smoking was an independent adverse risk factor for both overall and cancerrelated mortality, with a 1% increase in risk per pack-year smoked.82 Current smoking increased cancer mortality approximately five-fold even in p16-positive patients treated with surgery.83 Smoking also increased the risk of developing a second primary cancer among both HPV-positive and HPV-negative patients.84 As a consequence, the presence of HPV does not appear to negate the adverse effects of smoking. A similar effect is noted in lung cancer patients with EGFR-mutated and ALK-mutated tumors. As with HPVpositive head and neck cancer patients, lung cancer patients who are light or never smokers have a higher rate of epidermal growth factor receptor (EGFR)-positive tumors that may respond to biologic therapy using EGFR tyrosine kinase inhibitors. At this time, most information regarding EGFR-based therapy for lung cancer reports on the effects of ever smoking, demonstrating that ever smokers have a decreased response to EGFR therapy. Early large randomized trials demonstrate that erlotinib and gefitinib provide survival and tumor control benefit specifically in never smokers.85,86 A very similar pattern is noted for ALK-positive patients, with a much higher incidence in never smokers and high response rate to the anaplastic lymphoma kinase (ALK) kinase inhibitor crizotinib.87 Paik et al.88 have described the importance of driver mutations in EGFR, ALK, and KRAS, demonstrating that smokers have a higher preponderance for KRAS driver mutations, whereas nonsmokers tend to have EGFR or ALK driver mutations. Given the overall decreased response from biologic therapies, patients who are smokers may be best served with conventional cancer treatments; however, randomized controlled trials supporting this notion are lacking at this time. Early observations suggested that anti-programmed cell death protein 1 (PD-1)–based therapies may have a better response rate in smokers.89 A 2015 review of studies supported that former or currently smoking patients had a higher overall response rate to PD-1 or programmed cell death protein ligand 1 (PD-L1) therapies as compared with never smokers.90 In a study of 114 KRAS-mutated lung cancer patients, PD-L1 expression was higher in current smokers (44%) as compared with former smokers (20%) and never smokers (13%, P = .03), suggesting PDL1 expression may be affected by active exposure to cigarette smoke.91 Data are increasingly well established that the benefits of PD-1- or PD-L1–based therapies are related to higher mutational burden and molecular signatures from smoking.92 These data are increasingly exciting because immunotherapy may represent the first targeted approach to improve therapeutic response and outcomes in cancer patients who smoke.

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Summarizing the Clinical Effects of Smoking and Cessation in Cancer Patients There are three important conclusions, and a fourth implied conclusion, based on the evidence presented earlier: 1. One or more adverse effects of smoking affect all cancer disease sites and cancer treatment modalities. 2. The effects of current smoking are distinct from an ever or former smoking history. 3. Several lines of evidence demonstrate that many of the effects of smoking are reversible, supporting the benefit of smoking cessation to improve cancer treatment outcomes. Although substantial data demonstrate that smoking by cancer patients increases the risk for one or more adverse outcomes, the largest limitations are the lack of standard tobacco use definitions, failure to assess tobacco use in cancer patients at follow-up, lack of structured tobacco cessation for cancer patients, and misrepresentation of smoking status by cancer patients.23–29 Marin et al.93 exemplify the importance of accurate assessment by demonstrating that among patients who self-reported their smoking status, there was no significant risk associated with surgical complications; however, with biochemical confirmation of smoking status, the significant relationship between smoking and an increased risk of surgical wound complications was evident. Given the discrepancy between self-reported versus biochemically confirmed assessments, the fourth implied conclusion is that the adverse effects of smoking and the benefits of cessation may be more pronounced than currently reported in the literature.

ADDRESSING TOBACCO USE BY THE CANCER PATIENT Professional societies are taking leadership roles in recognizing the need to assess patients’ tobacco use and examine the effects of tobacco use in medical treatment, including the important role of tobacco cessation and general policy statements addressing tobacco use in cancer patients detailing that clinicians have a responsibility to address tobacco use, that all patients should be screened, that all patients who use tobacco should receive evidence-based tobacco cessation support, and that tobacco use should be included in clinical practice and research.2 In 2016, the National Cancer Institute (NCI) partnered with AACR to release recommendations to include structured tobacco use assessments for cancer patients enrolled on clinical trials, emphasizing the need to address tobacco use not only in clinical practice but also in clinical trials design.24,25 These recommendations provide clear guidance on how to address tobacco use in the general population as well as in cancer patients. In 2015, the NCCN released guidelines for smoking cessation for all cancer patients.94 The broad framework for intervention consists of evaluating smoking status and performing a more thorough tobacco use assessment including nicotine dependence and history of quit attempts for patients who report using tobacco within the past 30 days. Currently, guidelines divide patients into those ready to quit within the next 4 weeks versus those who are not ready to quit. The overarching goal is to emphasize quitting smoking as soon as possible using proven methods of behavioral therapy and cessation medications. In patients who are not ready to quit, the goal is to reduce tobacco use immediately with the objective of setting a quit date. For patients who do not report using tobacco within the past 30 days, risk for relapse should be evaluated, with an emphasis on preventing relapse with behavioral therapy and pharmacotherapy. Over the past 5 years, the 2014 SGR and development of NCCN guidelines for addressing tobacco use by cancer patients represent landmark activities. The SGR provides unequivocal evidence of the adverse effects of tobacco, and the NCCN guidelines provide the cohesive clinical support to address tobacco use in all cancer patients. Clinicians can rely on these documents and guidelines to facilitate development of structured cessation treatments for cancer patients.

Smoking Cessation Guidelines Overall, the approach to tobacco cessation for the cancer patient is very similar to the approach in the general population. However, there are a few specific details that are important to consider when approaching the cancer patient who smokes.2,3,8,10,23,95–99 It is important to recognize that virtually all newly diagnosed cancer patients are faced with a life-changing diagnosis that will require intensive treatment approaches. Treatments, toxicity, and survival outcomes differ according to disease site and treatment modality. Whereas some cancer patients may have a curable cancer, others may have incurable cancer. Smoking in cancer patients is also often associated with comorbid psychiatric diseases such as depression that may affect dependence. The urgency of cessation is also

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important to consider. If smoking decreases the efficacy of cancer treatment, then every effort should be made to stop tobacco use as soon as possible rather than choosing a quit date several weeks or months after a cancer diagnosis. Patients may also be burdened with a “stigma” associated with certain tobacco-related cancers where they may be viewed by others, or themselves, as causing their cancer due to tobacco use. As a result, the rationale and motivation for quitting tobacco use likely differ among cancer patients, but there is a consistent theme that exists: (1) All patients should be asked about tobacco use with structured assessments; (2) all patients who use tobacco or are at risk for relapse should be offered evidence-based cessation support; and (3) tobacco assessment and cessation support should occur at the time of diagnosis, during treatment, and during follow-up for all cancer patients. Evidence-based treatment of tobacco use is fundamentally supported by Public Health Service (PHS) Guidelines and NCCN Smoking Cessation Guidelines.94,100 The basic recommendation states that clinicians should consistently identify, document, and treat every tobacco user seen in a health-care setting. Although cessation support may range from brief to intensive intervention, it is important to note that consistent repeated cessation support and even brief counseling are effective methods to assist patients with stopping tobacco use. It is also noteworthy that physician-delivered interventions significantly increase long-term abstinence rates. Included are newer effective medication options and strong support for counseling and use of quitlines as effective intervention strategies. As described in the PHS Guidelines, the principal steps in conducting effective smoking cessation interventions are referred to as the 5 A’s (Fig. 33.1): 1. Ask about tobacco use for every patient. 2. Advise every tobacco user to quit. 3. Assess the willingness of patients to quit. 4. Assist patients with quitting through counseling and pharmacotherapy. 5. Arrange follow-up cessation support, preferably within the first week after the quit date. There is a strong evidence base for these interventions as documented in the clinical practice guideline.100 A common alternative to the 5 A’s model is the Ask-Advise-Refer (AAR) or Ask-Advise-Connect (AAC) model (see Fig. 33.1). The fundamental difference is that patients are still asked about tobacco use and advised to quit by clinicians, but patients are then either referred to dedicated tobacco cessation resources or connected directly to the tobacco cessation service. This method has been highly effective in reaching patients and in patients accepting cessation support.37 Facilitating connection to dedicated tobacco treatment resources can reduce strain on existing clinical oncology services as well as increase emphasis on the importance and focus of quitting smoking without being deemphasized by discussions of other important aspects of cancer care.95–99

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Figure 33.1 Incorporating the 5 A’s, Ask-Advise-Refer (AAR), or Ask-Advise-Connect (AAC) into clinical cancer care. The 5A’s model (blue shading) is typically delivered by the provider, whereas the AAR or AAC model (yellow shading) is delivered using dedicated tobacco treatment program resources such as an institutional program or state quitlines. Common elements associated with tobacco use assessments and advice are shaded in gray. All patients who report current tobacco use should be advised to quit and offered cessation support at any time during cancer treatment or follow-up.

Implementing Smoking Cessation into Clinical Practice An algorithm is provided to guide clinicians in implementing the 5 A’s, AAR, or AAC models into clinical cancer

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care (see Fig. 33.1).2,37,94–100 Included in the algorithm are questions that are useful to accurately assess tobacco use by cancer patients where patients can generally be divided into current, former, or never smokers. The first step (ask) is to inquire about and document tobacco use behaviors for every patient at repeated visits, including follow-up visits. Whereas a more comprehensive evaluation is necessary at first consult, only updates to current tobacco use are needed at follow-up. Including smoking status assessments as a “vital sign” for all patients significantly increases the identification and treatment of patients.101 Tobacco-use status stickers on paper charts or an automated reminder system for electronic records can increase compliance with tobacco assessments.23,36,37,95–99 With the recent “Meaningful Use” standards that were implemented in 2011, hospitals using an electronic medical record (EMR) are essentially required to document tobacco use.102 A recent study used the EMR to implement mandatory tobacco assessments in cancer patients and demonstrated that just a few questions at initial evaluation and follow-up could yield high referral and that less than 1% of referrals were delayed when assessments were repeated on a monthly basis rather than at every clinic visit.37 These findings reduce the clinical burden and patient fatigue associated with repeated assessments as frequently as every day such as in patients who are treated with daily RT or CT. At the time of this writing, there were no national guidelines for implementation of specific questions to assess tobacco use for clinical cancer patients, but recent papers from AACR and NCI have provided questions that were cognitively tested and useful in clinical settings.24,25 Figure 33.1 provides useful structured questions for assessing tobacco use in cancer patients that facilitate identification of current, former, and never smokers. Patients who use tobacco within the past 30 days should have structured support to quit tobacco use, maintain abstinence, and prevent relapse. Although not explicitly stated by any specific guidelines, asking about tobacco use in family members of cancer patients may also be important because family members often support cancer patients during and following treatment, and continued smoking by family members can make quitting much more difficult.2,95–100 Advising is the second step in promoting effective tobacco cessation and involves giving clear, strong, and personalized advice to stop tobacco use.2,3,8,10,23,94–100 This advice should include the importance of quitting smoking such as explicit information on the risks of continued smoking and benefits of cessation for cancer treatment outcomes and overall health regardless of cancer diagnosis. Advising should also include a discussion of how it is not “too late” to quit and will in fact benefit the patient’s cancer treatment efficacy and cancer prognosis. Many of the benefits of cessation were described previously for mortality, recurrence, toxicity, and quality of life. Clinicians must be particularly sensitive to avoid contributing to any perceived blame for the patient’s illness. Clinicians must remember that most patients started smoking in adolescence and did not completely understand the risks associated with tobacco use. At the same time, the severe addiction associated with chronic tobacco use makes it difficult to stop. Given the particularly high costs associated with cancer treatment overall, patients can also consider the cost savings of stopping a smoking habit. After advising, clinicians can then refer or connect a patient to treatment and assess dependence and willingness to quit.2,3,8,10,23,94–100 Asking “How soon after waking do you smoke your first cigarette?” assesses nicotine dependence, with high dependence associated with a shorter interval between waking and first cigarette. Nicotine dependence is predictive of smoking cessation outcomes and can be used as a good indicator of the intensity of cessation treatment needed such as the need for pharmacotherapy. Determining the patient’s motivation and interest in quitting is a critical parameter that influences the types of intervention strategies to be employed. Unique intervention messages and strategies are needed to optimally promote smoking cessation based on a patient’s readiness to quit smoking. In the general population, recommendations encourage that clinicians set a target quit date within 30 days. However, for cancer patients, clinicians must consider an urgent need to stop smoking immediately. If patients are unable to quit immediately, then patients should be encouraged to immediately reduce tobacco use and set a quit date as soon as possible based on the common need to start cancer treatment in the immediate future. “Assisting” patients with smoking cessation involves clinicians helping the patient design and implement a specific quit plan or broadly enhancing the motivation to quit tobacco.2,3,8,10,23,94–100 Promoting an effective quit strategy for cancer patients should consist of (1) setting a quit date (immediately or as soon as possible), (2) removing all tobacco-related products from the environment (e.g., cigarettes, ashtrays, lighters), (3) requesting support from family and friends, (4) discussing challenges to the quit attempt, and (5) discussing or prescribing pharmacotherapy where appropriate. Patients should also be provided information on cessation support services. In the cancer setting, patients can also be informed that smoking cessation is a critical component of cancer care over which they have complete control, thereby empowering patients to have personal control over their cancer care.

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Patients who are unwilling to quit should continue to receive repeated assessments and counseling to help motivate them to quit smoking.2,3,8,10,23,94–100 These patients should be encouraged to make immediate reductions in tobacco use and work toward abstinence as soon as possible. Clinician education, reassurance, and gentle encouragement can help them to consider changing their smoking behaviors. Specific strategies include discussing the personal relevance of smoking and benefits to cessation, providing support and acknowledging the difficulty of quitting, educating patients about the positive consequences of quitting smoking, and discussing available pharmacologic methods to assist quitting. Emphasis should be placed on patient autonomy to quit. Motivational strategies for patients unwilling to quit can be employed (e.g., asking open-ended questions, providing affirmations, reflective listening, and summarizing). Table 33.1 provides suggested methods to help clinicians promote tobacco cessation. The final step in the 5 A’s model of clinician-delivered smoking cessation intervention is arranging follow-up contact with the patient.2,3,8,10,23,94–100 Ideally, cancer patients will follow an immediate quit strategy, and followup should occur preferably within 1 to 2 weeks. However, short-term follow-up may also benefit patients who are reluctant to quit smoking. Some patients may require more support and closer follow-up. The clinician must remember that a new cancer diagnosis is stressful and patients may rely on continued smoking to relieve stress, but after absorbing the psychological effects of a new cancer diagnosis, patients may be more receptive to smoking cessation. During follow-up, clinicians should congratulate patients on successful cessation efforts, discuss accomplishments and setbacks, and assess pharmacotherapy use and problems. Patients should not be criticized for returning to smoking; rather, it is critical to create a supportive environment for patients to communicate progress, failure, and personal needs. Framing relapses as a learning experience can be helpful, and patients should be encouraged to set another quit date. Referrals to a psychologist or professionally trained smoking cessation counselor should be considered for patients with numerous unsuccessful quit attempts, comorbid depression, anxiety, additional substance abuse disorders, or inadequate social support. TABLE 33.1

Select Treatment Strategies Used for Tobacco Cessation Treatments Provide and monitor the use of nicotine replacement or other pharmacotherapy. Provide education regarding the health effects of tobacco use and its addictive and relapsing nature. Identify and change environmental and psychological cues for tobacco use. Generate alternative behaviors for tobacco use. Assist in optimization of social support for cessation efforts and address tobacco use in family members. Prevent relapse including the identification of future high-risk situations and plans for specific behaviors in those situations. Provide motivational interventions as needed throughout treatment. Identify relaxation techniques such as guided imagery and progressive muscle relaxation. Provide behavioral strategies to address depressed mood (e.g., increasing pleasurable activities). Provide crisis intervention including appropriate referrals and emergency intervention if indicated. Recognize and congratulate patients on success to reduce and/or quit smoking.

Clinicians who are not well versed in tobacco cessation should realize that smoking is an extremely difficult addiction to overcome and recognize the clinical pattern associated with cessation. As patients stop smoking, many will experience symptoms of withdrawal including dry or sore throat, constipation, cravings to smoke, irritability, anxiety, trouble concentrating, restlessness, increased appetite, depression, and insomnia. In the first few weeks, patients may also report an increase in mucous secretions from the airways, a cough, and other upper respiratory tract symptoms. Patients and clinicians should realize that tobacco cessation requires a concerted effort and may require repeated attempts and that symptoms will not resolve immediately. Clinicians should counsel patients on a repeated basis, recognize success, and provided repeated assistance if patients relapse.

Pharmacologic Treatment for Smoking Cessation

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The use of pharmacotherapy to help patients quit smoking is based on reducing the craving associated with nicotine withdrawal and significantly increases cessation success.2,3,8,10,23,94–100,103 NRT (in the form of patches, lozenges, inhalers, sprays, and gum), varenicline (Chantix), and bupropion (Zyban) are the three principal firstline pharmacotherapies recommended for use either alone or in combination according to PHS Guidelines. Table 33.2 presents information on these first-line agents. The clinical practice guideline also identifies two non– nicotine-based medications—clonidine and nortriptyline—as second-line pharmacotherapies for tobacco dependence typically used when a smoker cannot use first-line medications due to either contraindications or lack of effectiveness. Nicotine is the primary addictive substance in tobacco, and NRT facilitates smoking cessation by reducing craving and withdrawal that smokers experience during abstinence. NRT also weans smokers off nicotine by providing a lower level and slower infusion of nicotine than smoking. Strong evidence from randomized clinical trials support the use of NRT to increase the odds of quitting approximately two-fold as compared with placebo. Recent evidence further shows that combination therapy, or “dual NRT” (such as a nicotine patch and lozenge), is a very effective smoking cessation therapy producing high quit rates.104 Preclinical data suggest that although activation of the nicotinic acetylcholine receptor (nAChR) using high doses of nicotine promotes tumor development in preclinical evaluations,105 the negative aspects of smoking outweigh these concerns.1,2,95,98 Furthermore, there are no clinical trials reporting negative clinical outcomes for NRT in cancer patients related to mortality or recurrence. NRT use is not associated with an increased risk of carcinogenesis in the general population and should be used as an evidence-based method to help cancer patients stop smoking. TABLE 33.2

First-Line Pharmacotherapy Agents for Treatment of Nicotine Dependence Agent

Dose

Mechanism

Use

Nicotine Replacement Transdermal (patches)

16 h or 24 h 7, 14, or 21 mg 1 patch/d

Steady-state NRT to reduce craving and withdrawal

6–10 CPD: 14 mg daily × 8 wk, then 7 mg daily × 2 wk >10 CPD: 21 mg daily × 6 wk, then 14 mg × 2 wk, then 7 mg × 2 wk

Gum

2 or 4 mg Max: 24 pieces/d

Short-term NRT to reduce craving and withdrawal

First cigarette >30 min after waking: 2 mg PO every 1–2 h First cigarette 30 min after waking: 2 mg PO every 1–2 h First cigarette 20% lifetime risk of developing breast cancer defined by a risk assessment tool, or (3) those who have tested positive for a deleterious genetic mutation. A detailed history of common risk factors for breast cancer (e.g., age, reproductive history, family history) or a personal history of abnormal biopsies provides the most individualized information regarding breast cancer risk. Commonly used risk models, including the GAIL/National Cancer Institute (NCI) risk assessment tool, Tyrer-Cuzick, Claus, and BRCAPRO, can help quantify risk to determine if high-risk management is appropriate. Each model takes into account different risk factors and thus provides a slightly different risk estimate. The GAIL/NCI model measures age, family history in first-degree relatives, and a personal history of atypia. In addition to evaluating common risk factors (e.g., age of menarche and menopause, parity, age at first live birth, and history of abnormal breast biopsies), the Tyrer-Cuzick model includes the most comprehensive inventory regarding family history of all the risk models.1,2 The Claus model takes into account the number of first- and second-degree relatives with breast or ovarian cancer as well at the age of onset of cancer. The BRCAPRO model predicts the probability of carrying a BRCA1/2 mutation and developing breast or ovarian cancer. It takes into account age, family history, and Ashkenazi ethnic background.1 The Tyrer-Cuzick and Claus models predict the risk of developing either ductal carcinoma in situ (DCIS) or invasive cancer, whereas

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BRCAPRO only predicts the risk of invasive cancer. Although these models are useful in quantifying clinical risk, each have their limitations. The GAIL/NCI model is the quickest to use in a clinical setting, but it does not take into account non–first-degree family history and is less frequently used in high-risk patients.1,3 The GAIL model was generated from a general screening population but underestimates the risk in African American patients.1,4 Claus, Tyrer-Cuzick, and BRCAPRO have been incompletely validated, and they all underestimate risk in nonwhite populations.1 Despite their limitations, risk assessment models are an important adjunct in identifying patients who can benefit from high-risk screening and other risk-reducing interventions. Patients with certain deleterious gene mutations are considered to be at a high risk for developing breast cancer (Table 34.1). Hereditary breast cancers only account for approximately 5% to 10% of all diagnosed breast cancers, with BRCA1/2 mutations being the most common and well studied of all of the high-penetrance cancer genes. The EMBRACE study was one of the largest prospective studies to estimate the risk of developing breast, ovarian, and contralateral breast cancer (CBC) in BRCA1/2 mutation carriers. The authors found the risk of breast, ovarian, and CBC to be 60%, 59%, and 83%, respectively, by age 70 years in BRCA1 carriers. Similar risk estimates for BRCA2 carriers were 55%, 16.5%, and 62%.5 Other rare high-penetrance genes (e.g., PTEN, TP53, STK11, CDH1) account for 20% lifetime risk for breast cancer. Patients with these mutations can also benefit from risk-reducing strategies. With the widespread use of multigene panel testing, more moderate-penetrance genes (e.g., CHEK2, BRIP, BARD) and variants of unknown significance are reported with increasing frequency and pose a diagnostic challenge. High-risk management for these patients, in the absence of other risk factors, is not recommended.1 TABLE 34.1

Genes Associated with Hereditary Breast Cancer

Gene

Syndrome

Relative Risk of Breast Cancer Relative Risk (Age Range)

Breast Cancer Risk by Age 70 Years (%)

High-Penetrance Genes BRCA1

Hereditary breast and ovarian cancer syndrome

17 (20–29 y) 32 (40–49 y) 14 (60–69 y)

39–87

BRCA2

Hereditary breast and ovarian cancer syndrome

19 (20–29 y) 10 (40–49 y) 11 (60–69 y)

26–91

p53

Li-Fraumeni syndrome

1.46 overall

56 at 45 y; >90 at 70 y

PTEN

Cowden disease

2–4

25–50

STK11

Peutz-Jeghers syndrome

15

45–54

CDH1

Hereditary diffuse gastric carcinoma

3.25

39

Low- to Moderate-Penetrance Genes ATM

Ataxia-telangiectasia

3–4

NA

CHEK2

Li-Fraumeni variant

2 for women; 10 for men

NA

BRIP1

Fanconi anemia

2

NA

PALB2

None

2.3

NA

Excerpt from Robson M, Offit K. Management of an inherited predisposition to breast cancer. N Engl J Med 2007;357:154–162.

In patients who do not have a strong family history or a deleterious gene mutation but do have other clinical risk factors, high-risk assessment may still be warranted. Young women treated for Hodgkin lymphoma with mantle radiation between the ages of 10 and 30 years have an increased lifetime risk of developing breast cancer,

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as do patients with a previous breast biopsy of lobular carcinoma in situ (LCIS).4,6 LCIS is associated with a 10% to 20% lifetime risk of developing ipsilateral or CBC, whereas a history of mantle radiation can confer between a 20% and 25% lifetime risk of developing breast cancer.

Management Options for High-Risk Patients Management options for high-risk patients include (1) high-risk surveillance, (2) chemoprevention, and (3) riskreducing surgeries (RRSs).

Noninvasive Options In patients who do not want to pursue or want to delay RRS, high-risk surveillance is a reasonable option. The 2007 American Cancer Society (ACS) guidelines for breast screening with magnetic resonance imaging (MRI) suggest that compared to average-risk women, high-risk women can benefit from earlier and more frequent screening with MRI as an adjunct to conventional mammography.3 Studies show higher sensitivity rates of 71% to 100% with MRI compared to 16% to 40% with mammography in high-risk populations.3,4 The specificity of MRI, however, is substantially lower than that of mammogram, resulting in higher recall and biopsy rates. The American College of Radiology (ACR) recommends that high-risk surveillance include an annual MRI in addition to, and not instead of, an annual mammogram, as the combination of both modalities together has better sensitivity than either screening modality alone. In BRCA1/2 mutation carriers, the ACR recommends that screening with MRI begin by age 30 years but not before age 25 years.7 For patients with a >20% lifetime risk of breast cancer, screening with MRI is recommended to begin at age 30 years. In patients with Hodgkin lymphoma who were treated for cancer before age 30 years with ≥20 Gy of chest irradiation, guidelines suggest that screening with annual mammography and breast MRI start at age 25 years or 8 years after radiation treatment.6 The use of MRI screening remains controversial in patients with LCIS. Although the ACS reports insufficient evidence to recommend for or against the use of MRI screening, the ACR guidelines suggest MRI should be considered in women with LCIS, especially if other risk factors such as a family history of breast cancer or a previous abnormal breast biopsy are present.7 Routine screening of patients with a 1.66%. Participants were randomly assigned to receive either tamoxifen (20 mg/dL) or raloxifene (60 mg/dL) for 5 years. In a recent update of the study, compared to placebo, raloxifene and tamoxifen were found to decrease invasive cancer risk by 38% and 50%, respectively.8 In a 2013 update, the American Society of Clinical Oncology (ASCO) suggested that in women with a high risk of developing breast cancer, tamoxifen (in premenopausal women) and tamoxifen, raloxifene, or exemestane (in postmenopausal women) be considered for risk reduction of hormone-sensitive breast cancers.9 Although screening recommendations for patients with LCIS are mixed, the benefits of chemoprevention have been well described. In a single-institutional study over 29 years, King et al.10 found the 10-year cumulative breast cancer incidence to be 7% in patients with LCIS who used chemoprevention, compared to 21% in those that did not. In a multivariable analysis, including mammographic breast density and family history, only the use of chemoprevention was significantly associated with a lower risk of developing breast cancer.10

Invasive Options Invasive options, including risk-reducing mastectomy (RRM) and risk-reducing salpingo-oophorectomy (RRSO), provide the largest breast cancer risk reduction. The Prevention and Observation Surgical End Points (PROSE) study group showed that RRM reduced the risk of breast cancer by 99% in BRCA1/2 patients with prior oophorectomy and 90% in women with intact ovaries.11 The magnitude of breast cancer risk reduction with RRSO for BRCA1 versus BRCA2 mutation carriers remains controversial. RRSO was shown to have a protective effect in the development of breast cancer and decreased breast cancer risk by 37% to 56% in BRCA1 carriers and 46% to 64% in BRCA2 mutation carriers.12,13 Conversely, Kauff et al.14 reported a 72% reduction in BRCA2-associated

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breast cancers with RRSO, whereas the reduction for BRCA1-associated cancers did not meet statistical significance. The PROSE study found a protective benefit for both mutation carriers, and RRSO continues to be an appropriate choice for risk reduction in patients with both BRCA1 and BRCA2 mutations.11 Surgical options for RRM include simple or total mastectomy (TM), skin-sparing mastectomy (SSM), or nipple-sparing mastectomy (NSM). The long-term oncologic safety of NSM has been questioned, but several single-institution studies have indicated that the risk of local recurrence with NSM is similar to that of TM or SSM, making NSM a good oncologic and cosmetic option for risk reduction.15,16 In a multi-institutional study of BRCA1/2 mutation carriers, Jakub et al.17 reported on 346 patients who underwent NSM. At a mean follow-up of 56 months, no ipsilateral breast cancer events were seen after prophylactic NSM. The study also showed that the use of NSM was increasing in the BRCA1/2 population, with approximately a doubling of the number of NSM performed per year from 2009 to 2013.17 Smith et al.16 studied recurrence rates in breast cancer patients undergoing NSM. At a median follow-up of 51 months, 5.4% of patients developed a recurrence and none were at the nipple-areolar complex. In addition, the disease-free survival at 3 and 5 years was 95.7% and 92.3%, respectively.16 Data supporting the oncologic safety of NSM in primary breast cancer patients continues to grow and further supports its use in the risk-reduction setting. Timing of prophylactic surgeries is highly individualized, and several factors play a role in when and if these invasive procedures are undertaken. For those contemplating RRS, it is recommended that these procedures be completed as close to the completion of childbearing as possible in order to provide the greatest lifetime risk reduction. Chai et al.18 studied the use of RRSs in 1,499 BRCA1/2 mutation carriers. RRM usage was 70% by age 70 years. By age 40 years, RRSO use ranged from 34% to 45%, and increased to 71% to 86% by age 50 years, suggesting that delaying childbirth may account for less uptake of RRSO by age 40 years.18 Eisen et al.13 showed that breast cancer risk reduction after oophorectomy was greatest if the oophorectomy was performed prior to age 40 years than after age 40 years. This finding has important implications for counseling in patients contemplating RRSO. Although RRS can be performed at any age, it is important to underscore that the greatest reduction in breast cancer risk is conferred if RRM and RRSO are performed at a younger age, and the relative benefit decreases if performed at an older age. Chen et al.19 published important data predicting age-specific breast and ovarian cancer risks in unaffected BRCA1/2 patients. The study showed that the cumulative risk of developing breast cancer was higher in younger patients compared to those diagnosed later. According to their study, a 30year-old BRCA1 mutation carrier was estimated to have a cumulative risk of developing breast cancer of 10% by age 40 years, 37% by age 50 years, and 42% by age 70 years. A 50-year-old BRCA1 mutation carrier, however, was estimated to have a cumulative risk of developing breast cancer of 17% by age 60 years and 24% by age 70 years. Breast cancer risk estimates were even lower in patients who had a prior oophorectomy, suggesting that in older patients with a prior bilateral oophorectomy, the absolute benefit conferred by RRM is much less than that for a younger patient without oophorectomy. Important treatment decisions can be made from these findings, as recommendations for risk-reducing strategies may differ based on the age of presentation. Several risk-reducing strategies exist to decrease breast cancer risk. The first step in management is to identify high-risk patients by taking a detailed history or with the help of a risk assessment tool. High-risk surveillance with MRI as an adjunct to mammography, chemoprevention, and RRSs are all options that require a nuanced conversation regarding management between patients and their clinicians.

HEREDITARY DIFFUSE GASTRIC CANCER Gastric cancer is the fourth most common cause of cancer worldwide and is the second leading cause of cancer mortality.20 Although environmental agents, including Helicobacter pylori and diet, are the primary risk factors for this disease, approximately 10% of gastric cancers are a result of familial clustering.21,22 Histologically, gastric cancers may be classified as either intestinal or diffuse types. The intestinal type histopathology is linked to environmental factors and advanced age. The diffuse type occurs in younger patients and is associated with a familial predisposition. Because of a decrease in intestinal-type gastric cancers, the overall incidence of gastric cancer has declined significantly in the past 50 years. However, the incidence of diffuse gastric cancer (DGC), which is also called signet ring cell or linitis plastica, has remained stable and, by some reports, is increasing. Hereditary DGC (HDGC) is a genetic cancer susceptibility syndrome defined by one of the following: (1) two or more documented cases of DGC in first- or second-degree relatives, with at least one diagnosed before the age of 50 years; (2) three or more cases of documented DGC in first- or second-degree relatives, independent of age of onset; (3) families with one DGC before the age of 40 years; and (4) families with a history of DGC and lobular

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breast cancer with one diagnosed before the age of 50 years.23 The average age of onset of HDGC is 38 years, and the pattern of inheritance is autosomal dominant.23 Figure 34.1 shows a pedigree with HDGC. In 1998, inactivating germline mutations in the E-cadherin gene CDH1 were identified in three Maori families, each with multiple cases of poorly differentiated DGC.24 The CDH1 mutations in these families were inherited in an autosomal dominant pattern, with incomplete but high penetrance. Onset of clinically apparent cancer was early, with the youngest affected individual dying of DGC at the age of 14 years.24 Since then, germline mutations of CDH1 have been identified in 30% to 50% of all patients with HDGC.22,25 More than 50 mutations have been recognized across diverse ethnic backgrounds, including European, African American, Pakistani, Japanese, Korean, and others.22 In addition to gastric cancers, germline CDH1 mutations are associated with increased risk of lobular carcinoma of the breast, and this was the first manifestation of a CDH1 mutation in one series.26 CDH1 is, to date, the only gene implicated in HDGC. Penetrance of DGC in patients carrying a CDH1 mutation is estimated at 70% to 85%.27 Systematic study of specimens is necessary, and detailed sectioning and analysis has shown invasive carcinoma missed by some pathologists.

Figure 34.1 A family pedigree showing autosomal dominant inheritance of gastric cancer. Individual mutation testing results for the codon 1003 CDH1 mutation are indicated by + or −. Individuals affected with gastric cancer are shaded. (From Norton JA, Ham CM, Van Dam J, et al. CDH1 truncating mutations in the E-cadherin gene: an indication for total gastrectomy to treat hereditary diffuse gastric cancer. Ann Surg 2007;245[6]:873–879.) CDH1 is localized on chromosome 16q22.1 and encodes the calcium-dependent cell adhesion glycoprotein Ecadherin. Functionally, E-cadherin impacts maintenance of normal tissue morphology and cellular differentiation. It is hypothesized that CDH1 acts as a tumor suppressor gene in HDGC, with loss of function leading to loss of cell adhesion and subsequently to proliferation, invasion, and metastases. Figure 34.2 shows the CDH1 mutation for the pedigree depicted in Figure 34.1. The germline CDH1 mutation is most frequently a truncating mutation. Germline missense mutations are not clinically significant.25 Within the gastric mucosa, the “second hit” leading to complete loss of E-cadherin function results from CDH1 promoter methylation, as has been described in sporadic gastric cancer.28 It remains unclear whether specific CDH1 mutations are associated with distinctive phenotypic characteristics or rates of penetrance, although this may become apparent as more recurrent mutations are recognized. To date, most mutations identified have been novel and distributed throughout CDH1. Recognition of recurrent mutations has usually resulted from independent events; however, there is evidence for the role of founder effects in certain kindreds.25 At present, it is also unclear whether patients with HDGC without detectable CDH1 mutations have mutation of a different gene or merely a CDH1 mutation that has gone unrecognized. New recommended screening criteria for CDH1 mutations are as follows: 1. Families with one or more cases of DGC

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2. Individuals with DGC before the age of 40 years without a family history 3. Families or individuals with cases of DGC (one case below the age of 50 years) and lobular breast cancer 4. Cases where pathologists detect in situ signet ring cells or pagetoid spread of signet ring cells adjacent to DGC21,29 As in other familial cancer syndromes, genetic counseling should take place prior to genetic testing so that the family understands the potential impact of the results. After obtaining informed consent, a team comprising a geneticist, gastroenterologist, surgeon, and oncologist should discuss the possible outcomes of testing and the management options associated with each. Genetic testing should first be performed on a family member with HDGC or on a tissue sample if no affected relative is living. In addition to direct sequencing, multiplex ligationdependent probe amplification is recommended to test for large genomic rearrangements. If a CDH1 mutation is identified, asymptomatic family members may proceed with genetic testing, preferably by the age of 20 years.22 If no mutation is identified in the family member with DGC, the value of testing asymptomatic relatives is low. Among individuals found to carry a germline CDH1 mutation, clinical screening is problematic. Histologically, DGC is characterized by multiple infiltrates of malignant signet ring cells, which may underlie normal mucosa.30 Because these malignant foci are small in size and widely distributed, they are difficult to identify via random endoscopic biopsy. Chromoendoscopy and positron emission tomography have reportedly been used, but the clinical utility of these tools in early detection remains unproven.31 Lack of a sensitive screening test for HDGC makes early diagnosis extremely challenging. By the time patients are symptomatic and present for treatment, many have diffuse involvement of the stomach or linitis plastica, and rates of mortality are high. Published case reports describe patients who have presented with extensive DGC despite recent normal endoscopy and negative biopsies. The 5-year survival rate for individuals who develop clinically apparent DGC is only 10%, with the majority dying before age 40 years.

Figure 34.2 The mutation in this kindred is located in the central region of the E-cadherin gene that codes for the extracellular cadherin domains of the protein containing calcium-binding motifs important in the adhesion process. The C → T transition in exon 7 of nucleotide 1003 results in a premature stop codon (R335X), producing truncated peptides that lack the transmembrane and cytoplasmic β-catenin–binding domains essential for tight cell–cell adhesion. Black area indicates truncated portion of peptide. N, N-terminus; C, S, signal peptide; PRE, precursor sequence; TM, transmembrane domain; CP, cytoplasmic domain; C, C-terminus. (From Norton JA, Ham CM, Van Dam J, et al. CDH1 truncating mutations in the E-cadherin gene: an indication for total gastrectomy to treat hereditary diffuse gastric cancer. Ann Surg 2007;245[6]:873–879.) Because of high cancer penetrance (85% in recent series), poor outcome of clinically diagnosed cancer, and inadequacy of clinical screening tools for HDGC, prophylactic total gastrectomy is recommended as a management option for asymptomatic carriers of CDH1 mutations.32 Although total gastrectomy is performed with prophylactic intent in these cases, most specimens have been found to contain multiple foci of diffuse signet ring cell cancer.25,27,31,33 Foci of DGC have been identified even in patients who have undergone extensive negative screening, including high-resolution computed tomography, positron emission tomography scan, chromoendoscopy-guided biopsies, and endoscopic ultrasonography.25 However, HGDC in asymptomatic CDH1 carriers is usually completely resected by prophylactic gastrectomy, as pathologic analyses of resected specimens have repeatedly shown only T1N0 disease. Because these signet ring cell cancers are multifocal and distributed throughout the entire stomach, especially in the cardia,34 prophylactic gastrectomy must include the entire stomach, and the surgeon must transect the esophagus and not the proximal stomach. Total gastrectomy has been done laparoscopically, but the reported leak rate is unacceptably high.34 Furthermore, it should be performed by a surgeon experienced in the technical aspects of the procedure and familiar with HDGC. In asymptomatic patients, lymph node metastases have not been

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observed; therefore, complete D2 lymph node resection is not necessary. The optimal timing of prophylactic gastrectomy in individuals with CDH1 mutations is unknown, but recent consensus recommendations indicate age 5 years younger than the youngest family member who developed DGC.21 Although it is a potentially lifesaving procedure, prophylactic gastrectomy for CDH1 mutation carries significant risks that must be considered. Overall mortality for total gastrectomy is estimated to be as high as 2% to 4%, although it is estimated to be 1% when performed prophylactically. Patients must also be aware that there is a nearly 100% risk of long-term morbidity associated with this procedure, including diarrhea, dumping, weight loss, and difficulty eating.22 A recent study of the effects of prophylactic gastrectomy for CDH1 mutation demonstrated that physical and mental function were normal at 12 months, but a significant proportion of patients had bile reflux and dumping.35 Because the penetrance of CDH1 mutations is incomplete, 15% to 20% of patients who undergo prophylactic gastrectomy will have no evidence of gastric cancer on pathology.33 This fact must be carefully discussed with the individual patient. Some individuals with CDH1 mutations choose not to pursue prophylactic gastrectomy. These individuals should undergo careful surveillance, including biannual endoscopy with multiple biopsies according to the method developed at Cambridge,25 beginning when they are at least 10 years younger than the youngest family member with DGC at time of diagnosis. It is recommended that any endoscopically visible lesion is targeted and that six each random biopsies are taken from the following regions: antrum, transitional zone, body, fundus, and cardia. Careful white-light examination with targeted and random biopsies combined with detailed histopathology can identify early lesions and help to inform decision making with regard to gastrectomy.25 Additionally, because women with CDH1 mutations have a nearly 40% lifetime risk of developing lobular breast carcinoma, they should be carefully screened with annual mammography and biannual breast MRI starting at age 35 years.26 They should also do monthly self-examinations and have a breast examination by a physician every 6 months. The same surveillance recommendations are probably appropriate for HDGC families without identifiable CDH1 mutations, although no current guidelines for this exist. The emergence of gene-directed gastrectomy as a treatment strategy for patients with HDGC represents the culmination of a successful collaboration between molecular biologists, geneticists, oncologists, gastroenterologists, and surgeons. It is anticipated that the recognition of similar molecular markers in other familial cancer syndromes will transform the approach to the early diagnosis and treatment of a variety of tumors.

SURGICAL PROPHYLAXIS OF HEREDITARY OVARIAN AND ENDOMETRIAL CANCER Hereditary Ovarian Cancer (BRCA1, BRCA2) Inherited mutations in BRCA1 and BRCA2 strongly predispose women to high-grade epithelial cancers of the ovary, fallopian tube, and peritoneum.5,36 It is now believed that most of these cancers arise from epithelial cells that originate in the fimbria of the fallopian tube. BRCA1 mutations are about twice as common as BRCA2 mutations, and together they account for about 15% to 20% of these cancers.36 Lifetime risk of ovarian cancer is about 1.5% in the general population and increases to 15% to 25% in BRCA2 carriers and 30% to 50% in BRCA1 carriers.5,36 Inherited BRCA1/2 mutations are relatively rare in the general population (1 in 300 to 800), but the frequency is higher in some ancestral groups founded by a relatively small number of individuals. Most notably, three common BRCA1/2 founder mutations occur in about 2.5% of Ashkenazi Jews, and some have advocated universal screening of this population for these mutations.37 Hereditary ovarian cancers occur earlier on average, with risk rising around ages 35 to 40 years for BRCA1 and 45 to 50 years for BRCA2.36 Germline mutations in several other genes in the homologous recombination DNA repair pathway (RAD51C, RAD51D, BRIP1) also confer a high risk of ovarian cancer (5% to 15%).38 Panel tests that include all of these genes are increasingly being used to identify women who are candidates for cancer prevention with RRSO. Genetic risk assessment and testing for inherited mutations in BRCA1/2 and other genes should be discussed with women who have a significant personal and/or family history of breast, ovarian, fallopian tube, or peritoneal cancer.36,39 A number of expert guidelines have been developed that provide detailed guidance,36,39 and several risk prediction tools are available online. It is best for patients to see a genetic counselor who can construct a complete family pedigree and discuss the potential benefits and harms of genetic testing, including the potential for inconclusive results, reproductive and familial implications, anxiety, and employment and insurance

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discrimination. However, the shortage of cancer genetic counselors presents a challenge, and physicians can order genetic testing directly. Generally, testing should be focused on those in a family affected by cancer. Sometimes, this is not possible, and testing is performed on unaffected individuals. However, negative test results in an unaffected individual are uninformative for the rest of the family because these autosomal dominant mutations are only transmitted on average to half of offspring. If a disease-causing mutation is identified, “cascade testing” for that single mutation can be performed at less expense in other family members. Most BRCA1/2 mutations involve base deletions or insertions in the coding sequence or splice sites that encode truncated protein products that are clearly dysfunctional.5,36 Genomic rearrangements that disrupt these genes may also occur, and identification requires molecular testing beyond sequencing. Not infrequently, disease-causing mutations may occur that alter a single amino acid, but most of these represent innocent variants. The clinical significance of these missense mutations can sometimes be elucidated by assessing their predicted functional consequences and by whether they segregate with cancer risk in the family being tested or in large databases of previously tested individuals. Variants initially reported as benign occasionally are later reclassified as deleterious, and genetic testing companies will then issue amended reports. Newer tests that use next-generation sequencing to assess large panels of genes implicated in hereditary cancer syndromes increase the likelihood of finding variants of uncertain significance for which there are little risk data to guide clinical management. Because about 20% to 25% of women with high-grade serous ovarian cancer have germline or somatic BRCA1/2 mutations, it is recommended that all ovarian cancer cases undergo genetic testing.36,40 The availability of poly (ADP-ribose) polymerase (PARP) inhibitor therapy for cancers with germline or sporadic mutations in BRCA1/2 and other genes in the homologous recombination DNA repair pathway provides additional rationale for this practice.41 BRCA1/2 testing is now often performed after surgery using DNA from the cancer to allow detection of both germline mutations (10% to 20% of cases) and somatic mutations (5% of cases) that predict sensitivity to PARP inhibitors. Reflex blood testing is done if a mutation is found to determine whether it is a germline change and predisposes the patient and other family members to additional cancers. RRSO is strongly recommended in women who carry BRCA1/2 mutations because of the high mortality rate of ovarian/fallopian tube cancers and the lack of effective screening and prevention approaches.36,39 Management of women with a strong family history in whom a deleterious germline mutation is not found, or those with variants of uncertain significance, should be determined on a case-by-case basis. RRSO may be deemed appropriate in some cases despite the absence of a clearly deleterious mutation. Screening with CA125 and transvaginal ultrasound was recommended in the past but is no longer recommended because it has not been proven to reduce ovarian cancer mortality.36 There is also concern that screening can provide a false sense of security that causes some women to avoid RRS. Oral contraceptives reduce the risk of ovarian cancer in the general population by 30% to 60% and appear to have a similar effect in BRCA1/2 carriers.42 This preventive approach is one that should be discussed prior to the age at which RRSO is recommenced. Despite concerns that oral contraceptives may increase breast cancer risk, a meta-analysis of published studies is reassuring.43 Ovarian cancer is rare before the age of 40 years in women with BRCA1 mutations, occurring in 50 pg/mL), contralateral lateral neck nodes (basal calcitonin >200 pg/mL), and mediastinal nodes (basal calcitonin >500 pg/mL). Based on these findings, this group (who also wrote the European guidelines) recommends thyroidectomy only if basal calcitonin is 20 cm or rapidly growing, and/or need for parenteral nutrition is only 53%.129 Therefore, desmoid resection is evaluated on an individualized case-by-case basis with surgery reserved for highly select cases. Desmoids that involve the small bowel mesentery may preclude the formation of an IPAA secondary to foreshortening of the small bowel mesentery, especially in patients undergoing proctectomy after an initial IRA.132 Surgery for intra-abdominal and abdominal wall desmoids should be reserved for limited disease where the likelihood of clear margins is high. In symptomatic cases where resection of an intra-abdominal desmoid may not be feasible, intestinal bypass or ureteral stenting may be necessary to alleviate bowel or urinary obstruction secondary to mass effect. In addition to surgical intervention, several medical options with variable efficacy are available for the management of desmoid disease and include nonsteroidal anti-inflammatory drugs (e.g., sulindac), selective estrogen receptor modulators (e.g., tamoxifen), immunomodulators (e.g., imatinib, sorafenib, interferon), doxorubin-based cytotoxic chemotherapy, and radiation.

MUTYH-Associated Polyposis MAP is an autosomal recessive disorder caused by biallelic mutation in the MUTYH gene with the number of polyps being highly variable, ranging from a few adenomas to hundreds of adenomas, making it sometimes difficult to distinguish between AFAP and classic FAP. MAP has been diagnosed in over 7% of patients with polyposis (>100 adenomas) and lack of an APC mutation, and therefore, patients with polyposis and negative APC should be tested for an MUTYH mutation.106,133 Polyps may be found throughout the colon, but, as in AFAP, there is a slight propensity to CRC proximal to the splenic flexure.134 It has been suggested that approximately 30% of MAP patients with CRC do not develop polyposis.135 The mean age at CRC diagnosis is between the late 40s and early 50s, which is later than classic FAP but similar to AFAP.136 The estimated cumulative risk of CRC in biallelic MUTYH mutation carriers is 80% by age 80 years (19% by age 50 years, 43% by age 60 years).137 Additionally, there is a 2.5 increased risk of CRC for heterozygous carriers of MUTYH mutations compared with the general population, and an even higher risk if they have a first-degree relative diagnosed with CRC.138 Synchronous cancers occur in up to 24% of MAP patients. The genotype of MUTYH mutations can predict phenotype. Patients with a compound heterozygous mutation (G396D/Y179C) are diagnosed with CRC at a mean age of 52 years, whereas those with a homozygous G396D mutation were diagnosed at 58 years, and 46 years with a Y179C mutation. This information is important when counseling patients with known mutations.97 The diagnosis of MAP is confirmed by MUTYH gene testing.97,105 Patients with a personal history of between 10 to 20 adenomas or if they meet criteria for serrated polyposis syndrome with at least some adenomas should also be considered for testing. When polyposis is present in a patient with no family history, testing for de novo APC mutation should be undertaken, and if negative, testing for MUTYH should follow. Patients who have polyposis but a negative test for MUTYH should be managed as FAP patients.106 Extracolonic manifestations of MAP are similar to FAP and include osteomas, desmoids, congenital hypertrophy of the retinal pigment epithelium, and cancers of the thyroid, ovary, bladder, sebaceous gland, and breast. In addition, patients with MAP are also at a 4% lifetime risk of developing duodenal cancer. Once a patient is identified as having MAP, genetic counseling and surveillance colonoscopies should be initiated given the increased risk of CRC. Colonoscopy should begin at ages 25 to 30 years and should be repeated every 2 to 3 years should no adenomas be discovered. Patients younger than 21 years with small adenoma burden should be followed with colonoscopy and polypectomy every 1 to 2 years with surgical counseling for TAC/IRA as the patient ages or if polyposis becomes unable to be managed endoscopically. In general, long-term endoscopic management of the whole colon is not successful. Most MAP patients present with an attenuated phenotype and relative sparing of the rectum.134 If surgery is necessary, and the rectum is spared, TAC/IRA is recommended. If rectal polyposis is severe, then TPC with IPAA is indicated. The rectal stump should be surveilled every 6 to 12 months postoperatively as rectal polyps are frequently found after surgery (1.52 adenomas per year per patient).139 There are currently no recommendations for chemoprevention of polyps postoperatively. Monoallelic MUTYH carriers require special CRC screening with colonoscopy every 5 years beginning at age 40 years, or 10 years prior to the first-degree relative with CRC. It is unclear whether special screening is needed

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if no first-degree family members have CRC. Should CRC be discovered in an MUTYH carrier, postsurgical surveillance is the same as for sporadic CRC.106 Given the risk of duodenal cancer, upper gastrointestinal endoscopy is advised starting from between 30 to 35 years of age. The recommended screening interval is the same as FAP and determined by the Spigelman classification.106

Lynch Syndrome Due to the discordance associated with the term hereditary nonpolyposis CRC, the use of this term has largely been abandoned with reversion back to the eponym LS, which refers to individuals with a predisposition to CRC and other malignancies as a result of a germline MMR mutation.140 Overall, CRC occurs in up to 80% of patients with LS by their mid-40s.93,99 Endometrial cancer occurs in 40% to 60%, gastric cancer in 11% to 19%, urinary tract cancer in 1% to 4%, and ovarian cancer in 9% to 15% of affected individuals.93,99,104 Several clinical criteria are available to identify patients at risk of LS who require further testing. These include the Amsterdam II criteria, the revised Bethesda guidelines, and online statistical models (MMRpro, MMRPredict, PREMM5).141–143 The Amsterdam II criteria require that there be: Three relatives (one a first-degree relative of the other two) with colorectal, endometrial, stomach, ovary, small bowel, ureteral/renal pelvis, brain, hepatobiliary, and/or sebaceous cancer In two or more successive generations With at least one case of cancer diagnosed before the age of 50 years FAP as a diagnosis is excluded142 Although the Amsterdam criteria can be used clinically to identify potential patients with LS, using it alone will result in identification of only 42% of LS mutation carriers.144 This led to the development of the Bethesda guidelines, now revised, which broaden the clinical criteria (Table 34.3). Patients with CRC who belong to pedigrees suspicious for LS should be offered screening by IHC for loss of MMR protein expression or by MSI analysis. As the sensitivity of IHC testing for loss of MMR protein expression is comparable to MSI testing, either approach can be pursued.140 However, IHC testing is less expensive and can also identify a specific MMR protein loss, which can help target subsequent germline testing. Routine IHC testing, or universal screening, for loss of MMR protein in individuals younger than 50 years at the time of CRC diagnosis is feasible and has led to the identification of patients with LS who might otherwise have been missed.145,146 This has been successfully implemented at some institutions, has been demonstrated to be cost effective, and is an accepted practice by the Evaluation of Genomic Applications in Practice and Prevention (EGAPP) working group, the U.S. Multi-Society Task Force on Colorectal Cancer, and the National Comprehensive Cancer Network (NCCN).106,140,147,148 However, a majority of cancer programs nationwide currently do not have a protocol for reflex testing for LS, citing lack of institutional protocols as well as fear of nonreimbursement.149 TABLE 34.3

The Revised Bethesda Guidelines for Testing Colorectal Tumors for Microsatellite Instability Tumors from individuals should be tested for MSI in the following situations: 1. Colorectal cancer diagnosed in a patient who is aged 10 years) of 325 mg of aspirin twice weekly or more reduces colorectal cancer risk (RR, 0.77; 95% CI, 0.67 to 0.88, from the Nurse’s Health Study). Daily NSAID intake is associated with a 40% (OR, 0.56; 95% CI, 0.43 to 0.73) reduction in risk of esophageal adenocarcinoma.137

Evidence in Preclinical In Vivo Carcinogenesis Models NSAIDs, including aspirin, indomethacin, piroxicam, sulindac, ibuprofen, and ketoprofen, suppress colonic tumorigenesis induced chemically (1,2-dimethylhydrazine or its metabolites) or transgenically (Min+).138,139 The selective COX-2 inhibitors were the most efficacious colon tumorigenesis inhibitors in both chemical and transgenic rodent models.140,141 In preclinical models, NSAIDs affect the onset and progression of cancers in stomach, skin, breast, lung, prostate, and urinary bladder, although the evidence is more limited than for colon cancers.142

Clinical Trials Key clinical trials of NSAIDs for the prevention of colorectal cancer are summarized in Table 35.8. Sulindac reduced the size and number of preexisting adenomas in patients with familial adenomatous polyposis but did not suppress the development of new adenomas.143 The selective COX-2 inhibitor, celecoxib, suppressed the development of new adenomatous polyps in patients with familial adenomatous polyposis.144 Although these results are promising, reports of invasive neoplasms developing in familial adenomatous polyposis patients being treated with sulindac145 raise the question of whether NSAIDs preferentially alter the formation or regression of those adenomas less likely to progress to invasive adenocarcinomas, as compared to those more likely to progress. Randomized, double-blinded, placebo-controlled trials of NSAIDs as cancer risk–reducing agents for colorectal adenocarcinoma (see Table 35.8) have confirmed that aspirin suppresses adenoma recurrence in patients previously treated for adenomas or for cancer. Neither sulindac nor piroxicam alone suppressed adenoma formation in high-risk, sporadic populations at tolerable doses.146,147 Sulindac in combination with difluoromethylornithine (DFMO) has potent colorectal anticarcinogenesis effects.148 Selective COX-2 inhibitors (celecoxib, rofecoxib) reduce the recurrence of adenomas by one-third in all patients previously treated for adenomas and by one-half in patients with previously resected large (≥1 cm) adenomas,149–151 but they are too toxic as cancer risk–reducing agents due to their cardiovascular toxicity.152 Although most NSAIDs (piroxicam, indomethacin) have sufficient gastrointestinal (GI) toxicity to reduce their acceptability as cancer risk–reducing agents,153,154 long-term administration of low-dose aspirin in vascular prevention trials demonstrates acceptable GI toxicity.155 Published meta-analyses confirm NSAID risk-reductive efficacy in preventing adenoma recurrence in prospective, randomized trials (nonaspirin NSAIDs [OR, 0.37; 95% CI, 0.24 to 0.53]; low-dose aspirin [OR, 0.71; 95% CI, 0.41 to 1.23]).156,157 The safety profile of low-dose aspirin exceeds that of nonaspirin NSAIDs. TABLE 35.8

Nonsteroidal Anti-inflammatory Drugs as Colorectal Cancer Risk–Reducing Agents

Population

Drug (Dose), Duration

Phase

End Point

Outcome

Citations

IIb

Adenoma regression

Colorectal and duodenal polyps regressed in

272–274

GENE-ASSOCIATED FAP

Sulindac (300– 400 mg/d, divided doses)

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2 years reduced the risk first colorectal cancer event in Lynch syndrome (HR, 0.41; 95% CI, 0.19 to 0.8),158 whereas selective COX-2 inhibition with celecoxib or nonselective COX inhibition with sulindac, and low-dose aspirin reduce adenoma recurrence, size, and frequency in patients with familial polyposis syndrome.143,144,159 Up to 40% of individuals screened for colorectal neoplasms will have an adenomatous polyp detected and removed; yet, only 10% of these lesions will progress to invasive neoplasms. Prospective NSAID trials to date of only 2 to 5 years cannot substitute for cancer incidence or mortality end points. Given the 10-year latency between adenoma formation and a cancer event, prospective trials sufficiently powered to detect colorectal cancer incidence end points are unlikely in the future.160 Alternatively, follow-up of patients randomized on trials of aspirin in prevention of vascular events in the 1980s and 1990s offers secondary analysis opportunities. In a pooled analysis of three prospective vascular end point cohort studies, 20-year low-dose aspirin treatment reduced cancer deaths from all solid tumors (OR, 0.69; 95% CI, 0.54 to 0.88) and from lung and esophageal adenocarcinomas (OR, 0.66; 95% CI, 0.56 to 0.77).155 The U.S. Preventive Services Task Force recommends use of a low dose of aspirin 75 to 100 mg daily (in the United States, 81 mg daily is commonly used) for the primary prevention of cardiovascular disease and for prevention of colorectal neoplasia in adults aged 50 to 59 years who have a 10% or greater 10-year cardiovascular disease risk and no increased risk for bleeding. For adults aged 60 to 69 years, the U.S. Preventive Services Task Force recommends that the decision be individualized to persons who place a higher value on the potential benefits rather than the potential harms.161 Minimal prospective clinical cancer risk reduction data are available at other epithelial organ sites. Ketorolac, given as a 1% rinse solution, did not reduce the size or histology of leukoplakia lesions.162 Celecoxib reduces the Ki67 labeling index and increases the expression of nuclear survivin without significantly changing the cytoplasmic survivin in bronchial biopsies of smokers.163 Cancer prevention trials of aspirin as interventions for delaying progression from intra-epithelial neoplasias in other epithelial sites remain ongoing for lower esophagus.137 No prospective, randomized trials or data are available for breast, prostate, or gynecologic cancer prevention.

POSTTRANSLATIONAL PATHWAY TARGETS Selective Estrogen Receptor Modulators Mechanism Selective ER modulators (SERMs) function as ER agonists and antagonists depending on the SERM structure and target tissue. Predominant ERα receptors occur in human uterus, cortical bone, and liver, whereas predominant ERβ receptors occur in blood vessels, cancellous bone, whole brain, and immune cells.164,165 During carcinogenesis, the amount of ERα increases, whereas the amount of ERβ decreases in breast tissues.166 Ideally, a desirable SERM for cancer prevention will function as an antiestrogen in the breast and uterus, but a partial estrogen agonist in skeletal, cardiovascular, central nervous system (CNS), GI tract, and vaginal tissues. The ideal SERM will not have procoagulant effects and will not cause perimenopausal symptoms such as hot flashes.166

Formulations Tamoxifen. Tamoxifen is a triphenylethylene compound developed for the treatment of ER-positive breast cancer in the 1960s and 1970s. Tamoxifen inhibits the initiation and promotion phases of breast carcinogenesis in the dimethylbenzanthracene chemical carcinogenesis model.167 When tamoxifen binds to ERβ, which then binds to an AP1 type gene promoter, it functions as an estrogen agonist. When bound to ERα, which binds to an ERE target gene promoter, tamoxifen functions as an estrogen antagonist.166,167 Tamoxifen has estrogen antagonist effects in the human breast; partial estrogen agonist effects in bone, the cardiovascular system, and CNS; and predominant estrogen agonist effects in the uterus, liver, and vagina. The estrogen agonist effects in the liver and uterus result in tamoxifen’s toxicities of thromboembolism and endometrial cancer, respectively. The clinical finding that tamoxifen reduces the incidence of contralateral second primary breast cancers during adjuvant treatment

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regimens catalyzed the push for its development as a cancer risk–reducing agent.168 Raloxifene. The benzothiophene structure of raloxifene confers a different tissue-specific ER binding profile than the triphenylethylene tamoxifen. Raloxifene has greater estrogen agonist activity in bone but reduced estrogen agonist activity in the uterus. Raloxifene was studied for treatment and prevention of osteoporosis in a large, pivotal trial (Multiple Outcomes of Raloxifene Evaluation [MORE]) and found to reduce the rate of vertebral fracture as compared to placebo in postmenopausal women.169 Lasofoxifene and Arzoxifene. Lasofoxifene and arzoxifene are third-generation SERMs developed as more potent blockers of bone resorption with the goals of reducing the risk of fractures, breast cancer, and heart disease while minimizing the SERM-induced risk of endometrial hyperplasia in postmenopausal women. Both agents proved potent in vitro and in preliminary clinical trials for bone fracture prevention.170–173

Efficacy Table 35.9 summarizes the phase III data for SERM-based breast cancer risk reduction. In a systematic review of MEDLINE and Cochrane databases through December 2012, the U.S. Preventive Services Task Force identified seven trials of tamoxifen or raloxifene that showed a reduced incidence of invasive breast cancer by seven to nine cases in 1,000 women over 5 years compared to placebo.174 Tamoxifen is more effective than raloxifene; it reduces breast cancer incidence more than raloxifene by five cases in 1,000 women. Both drugs reduce the incidence of ER-positive breast cancer; neither reduces the risk of ER-negative breast cancer. Neither drug reduced breast cancer–specific or all-cause mortality rates. Based on benefit–risk models, women with an estimated 5-year risk of breast cancer of 3% or greater are likely to benefit from treatment.175 Tamoxifen reduces risk of in situ (preinvasive) breast neoplasms (lobular carcinoma in situ, ductal carcinoma in situ) by 50%.176,177 The reduction during treatment persists for at least 5 years after treatment.176,177 Raloxifene does not reduce the risk of in situ breast neoplasms. Data from two trials designed to evaluate the safety and efficacy of lasofoxifene (PEARL)170,171 and arzoxifene (GENERATIONS)172,173 as bone fracture preventives have been analyzed for breast cancer risk reduction. Their effect in reducing breast cancer incidence was captured in secondary analyses (see Table 35.9). Neither lasofoxifene nor arzoxifene have been evaluated in phase III randomized controlled breast cancer prevention trials. Arzoxifene development has been discontinued in the United States.

Toxicity Tamoxifen causes a twofold increase in risk of endometrial adenocarcinoma (RR, 2.13; 95% CI, 1.36 to 3.32) and is related to more benign gynecologic conditions, uterine bleeding, and surgical procedures than the placebo controls, whereas raloxifene did not increase the risk for endometrial cancer or uterine bleeding.174 Tamoxifen causes a twofold increase in thromboembolic events (RR, 1.93; 95% CI, 1.41 to 2.64), whereas raloxifene causes a 60% increase in risk of venous thromboembolism (RR, 1.60; 95% CI, 1.15 to 2.23).174 Raloxifene does not differ from tamoxifen in risk of fractures, other cancers, or cardiovascular events.176 Raloxifene’s lower risk of endometrial adenocarcinomas compared to tamoxifen needs to be weighed against the increased risk of stroke seen in in the MORE/CORE trials (see Table 35.8).178 Raloxifene’s effectiveness in the community may also be compromised by its poor bioavailability (2%) due to rapid phase II enzyme metabolism in the gut and liver,179 whereas tamoxifen is more bioavailable and has active metabolites that permit prolonged drug effect. Missed raloxifene doses may potentially compromise efficacy and prevention outcomes in widespread, community use. TABLE 35.9

SERMs for the Prevention of Breast Cancer

Study

Drug and Daily Dose

N

Treatment Duration (y)

Entry Criteria

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Overall Outcome Hazard Ratio (95% Confidence Interval)

Citations

NSABP P-1

Tamoxifen 20 mg Placebo

13,388

5

Gail model: 5-y predicted risk of ≥1.66%

0.52 (0.42– 0.64)

28, 281

IBIS-I

Tamoxifen 20 mg Placebo

7,139

5

>twofold relative risk

0.72 (0.58– 0.90)

282

Marsden

Tamoxifen 20 mg Placebo

2,471

8

Family history

0.87 (0.63– 1.21)

283

Italian

Tamoxifen 20 mg Placebo

5,408

5

Normal risk, hysterectomy

0.67 (0.59– 0.76)

284

NSABP P-2 (STAR)

Raloxifene 60 mg Tamoxifen 20 mg

19,747

5

Gail model: 5-y predicted risk of ≥1.66%

Risk ratio raloxifene vs. tamofen 1.02 (0.81– 1.28)

29

MORE/CORE

Raloxifene 60 mg Placebo Raloxifene 120 mg Placebo

7,705 6,511

5

Normal risk, postmenopausal with osteoporosis

0.42 (0.29– 0.60)

285, 286

RUTH

Raloxifene 60 mg Placebo

10,101

5

Normal risk, postmenopausal with risk of coronary heart disease

0.67 (0.47– 0.96)

178

PEARL

Lasofoxifene 0.5 mg Lasofoxifene 0.25 mg Placebo

8,856

5

Normal risk, postmenopausal, with osteoporosis

0.25 mg: 0.82 (0.45– 1.49) 0.5 mg: 0.21 (0.05–0.55)

170

GENERATIONS

Arzoxifene 20 mg Placebo

9,354

4

Normal risk, postmenopausal, with osteoporosis

0.42 (0.25– 0.68)

171

Table and data adapted from Cuzick J, Sestak I, Bonanni B, et al. Selective oestrogen receptor modulators in prevention of breast cancer: an updated meta-analysis of individual participant data. Lancet 2013;381(9880):1827–1834.

Aromatase Inhibitors Mechanism Aromatase converts adrenal androgens (testosterone and androstene dione) to estrone and estradiol. Pharmacologically inhibiting aromatase reduces the peripheral estrone and estradiol conversion from androgenic sources, thus depriving neoplastic hormonally dependent cells of necessary estrogens.180

Formulations Anastrozole. Anastrozole, a selective nonsteroidal aromatase inhibitor, is 1,3-benzenediacetonitrile, a triazol synthetic small molecule. A 1-mg dose of anastrozole suppresses human serum estradiol concentrations by 70% within 24 hours and by 80% after 14 days of daily dosing. Estradiol suppression remains for up to 6 days after cessation of daily dosing. Anastrozole has no effect on cortisole or aldosterone secretion, nor does it have effects on thyroid-stimulating hormone, progesterone, or androgens. It is metabolized via N-dealkylation, hydroxylation,

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and glucuronidation. Triazole, the major metabolite, has no pharmacologic activity. Anastrozole inhibits reactions catalyzed by CYP 1A2, 2C8/9, and 3A4.181 Exemestane. Exemestane, a steroidal, irreversible aromatase inactivator, is 6-methylenandrosta-1,4-diene-3,17dione. It is extensively metabolized, primarily by oxidation via CYP 3A4 of the methylene group in position 6 and reduction via aldo-keto reductases of the 17-keto group with subsequent formation of many therapeutically inactive secondary metabolites. Exemestane suppresses human plasma estrogens (estradiol, estrone, and estrone sulfate) at a low dose (5-mg daily) with maximal suppression of 85% to 95% achieved with 25 mg once daily. Maximal suppression of circulating estrogens occurs 2 to 3 days after dosing and persists for 4 to 5 days. Exemestane has aeffect on cortisol or aldosterone secretion. Exemestane does not bind to steroid receptors with the exception of weak binding to androgen receptors.180 Letrozole. Letrozole, a nonsteroidal, irreversible aromatase inactivator, is 4,4′-((1h-1,2,4-triazole-1yl)methylene)dibenzanitrile. Doses as low as 0.1 mg daily reduce circulating estradiol and estrone concentration with dose response. Doses 0.5 mg and higher reduce circulating estrogens by 75% to 95% from baseline with maximal suppression achieved within 3 days of daily dosing. As with other selective aromatase inhibitors, letrozole has no effect on other steroid synthesis pathways. It has no effect on androgen synthesis. Letrozole is a substrate for CYP3A4 metabolism to an inactive carbinol metabolite, which is further conjugated and renally excreted.180

Efficacy In a phase I cancer risk–reducing agent trial, letrozole reduces the Ki-67 proliferation index of breast epithelial cells aspirated from high-risk women.181 In phase III trials (Table 35.10), exemestane reduces the overall risk of ER-positive invasive breast cancer. It does not reduce the risk of noninvasive breast neoplasms or ER-negative breast cancer.182 The results of the International Breast Cancer Intervention Study II (IBIS-II) comparing anastrozole with placebo are similar to those reported for exemestane.183 Compared to exemestane, anastrozole decreases the incidence of ductal carcinoma in situ, whereas exemestane does not. Neither aromatase inhibitor increased survival compared to placebo controls. The American Society of Clinical Oncology (ASCO) recommends exemestane for breast cancer prevention in addition to tamoxifen and raloxifene.184 TABLE 35.10

Aromatase Inhibitors for the Prevention of Breast Cancer

Study

Drug and Daily Dose

N

Treatment Duration (y)

Entry Criteria

Overall Outcome Hazard Ratio (95% Confidence Interval)

Citations

MAP.3

Exemestane 25 mg Placebo

4,560

5

Gail model: 5-y predicted risk of ≥2.3%

0.35 (0.18– 0.70)

182

IBIS-II

Anastrozole 1 mg Placebo

3,851

5

Relative risk twofold higher than general population or TyrerCuzick 10-y risk >5%

0.47 (0.32– 0.68)

183

Toxicity Aromatase inhibitors have no increased risk of venous thromboembolism, endometrial cancer, fracture, or cataract, but losses in bone mineral density and cortical thickness of distal tibia and radius occurred after 2 years of treatment despite calcium and vitamin D supplementation. Severe and persistent vasomotor symptoms can be disabling and require drug withdrawal. Other common toxicities include carpal tunnel syndrome, vaginal dryness,

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dyspareunia, and libido loss.182,185

Breast Cancer Risk Reductive Use Counseling Despite the widespread evidence of breast cancer preventive efficacy for tamoxifen and raloxifene, only 3% to 20% of eligible high-risk women agree to take tamoxifen for primary prevention.186 The low willingness of eligible women to take tamoxifen for 5 years demonstrates the issue of risk benefit for cancer risk–reducing agents. Women >35 years of age with high short-term risk (5-year Gail risk of >3%) (e.g., those with ER-positive atypical hyperplasia, lobular carcinoma in situ, and the majority of non–high-grade ductal carcinoma in situ lesions) have an acceptable risk–benefit ratio and are the most likely to benefit from a 5-year cancer risk–reducing agent intervention with a SERM.175,184 The toxicity profile of aromatase inhibitors differs from SERMs. Current ASCO guidelines state “tamoxifen (20 mg per day for 5 years) should be discussed as an option to reduce the risk of ER-positive BC [breast cancer]. In postmenopausal women, raloxifene (60 mg per day for 5 years) and exemestane (25 mg per day for 5 years) should also be discussed as options for BC risk reduction…. Use of other selective ER modulators or other aromatase inhibitors to lower BC risk is not recommended outside of a clinical trial.”184 The U.S. Preventive Services Task Force updated recommendations are expected in 2018. In the National Surgical Adjuvant Breast and Bowel Project, a small subset of tamoxifen-treated women with a BRCA2 (11 carriers) mutation but not a BRCA1 mutation (8 carriers) had reduced cancer incidence.187 Subsequent data from other groups have found approximately 50% reduced cancer risk in contralateral breasts in women with both BRCA mutations.188,189 Guidelines from the National Comprehensive Cancer Network (NCCN) and from the American College of Obstetricians and Gynecologists (ACOG) recommend tamoxifen for BRCA carriers.

5α-Steroid Reductase Inhibitors Mechanism Prostate cancers require androgens to proliferate and to evade apoptosis. The primary nuclear androgen responsible for maintenance of epithelial function is dihydrotestosterone. The testes and adrenal gland synthesize dihydrotestosterone by the conversion of testosterone by 5α-steroid reductase types 1 and 2 isozymes. Dihydrotestosterone binds to intracellular androgen receptors to form a complex that binds to DNA hormone response elements controlling cellular proliferation and apoptosis. Finasteride, a selective, competitive inhibitor of type 2 5α-steroid reductase,190 inhibits proliferation in the transformed prostate cell. In the 3,2′-dimethyl-4aminobiphenyl, methylnitrosourea (MNU), and testosterone chemical carcinogenesis models in rats, finasteride reduces prostate tumor incidence by close to sixfold. Finasteride appears to be more effective in the promotion phase of prostate carcinogenesis.191 Dutasteride inhibits both 5α-steroid reductase inhibitor191 types 1 and 2 isoforms and has similar anticarcinogenesis activity in preclinical models to finasteride.

Cancer Risk–Reducing Agent Activity Randomized, placebo-controlled cancer incidence end point risk-reducing agent clinical trials demonstrated that finasteride and dutasteride reduced the incidence of prostate cancer by approximately 22% (Table 35.11).30,192 Patients who are treated with either drug yet progress to transformed neoplasms develop more tumors of high Gleason grade (7 to 10) compared to the placebo arm (22%). After 18 years of follow-up, no significant differences in overall survival or survival after prostate cancer diagnosis were found in the finasteride-treated group compared to the placebo-treated group.193 Sexual function side effects (erectile dysfunction, loss of libido, gynecomastia) were more common in the finasteride- or dutasteride-treated groups.30,192 TABLE 35.11

5α-Steroid Reductase Inhibitors for the Prevention of Prostate Cancer

Study PCPT

Drug and Daily Dose Finasteride 5 mg Placebo

N

Treatment Duration (y)

Entry Criteria

Overall Outcome

18,880

7

Age ≥55 y, PSA ≤3 ng/mL

HR for prostate cancer,

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Citations 30, 193

0.70; 95% CI, 0.65– 0.76 REDUCE

Dutasteride 0.5 mg Placebo

6,729

4

Age 50–75 y, PSA 2.5 to 10.0 ng/mL, core biopsies within 6 mo

RR for prostate cancer, 0.77; 95% CI, 0.70– 0.85

192

PSA, prostate-specific antigen; HR, hazard ratio; CI, confidence interval; RR, relative risk.

The 5α-steroid reductase inhibitors finasteride and dutasteride prevent or delay carcinogenesis progression in the prostate; yet, progression of high-grade lesions is unaffected. Use of finasteride for a period of 7 years reduced the incidence of prostate cancer but did not significantly affect mortality.193 Increasing the diagnosis of low-grade prostate cancer through prostate-specific antigen (PSA) testing or intervention with a drug with minimal toxicity profile without reducing mortality is of no benefit and “all forms of therapy cause considerable burden to the patient and to society.”193

Difluoromethylornithine Mechanism Polyamines (spermidine, spermine, and the diamine, putrescine) are required to maintain cellular growth and function.194 In mammalian cells, polyamine inhibition by genetic mutation or pharmaceutical agents is associated with virtual cessation in cellular growth. DFMO is an enzyme-activated irreversible inhibitor of ornithine decarboxylase (which is transactivated by the c-MYC oncogene and cooperates with the Ras oncogene in malignant transformation).195 DFMO reduces single carbon transfer through inhibiting S-adenosylmethionine (SAM) and reducing available tetrahydrofolate for the synthesis of thymidine.196

Evidence in Preclinical In Vivo Carcinogenesis Models Extensive preclinical data has found that DFMO prevents tumor promotion in a variety of systems: skin, mammary, colon, cervical, and bladder carcinogenesis models. Synergistic or additive activity with retinoids, butylated hydroxyanisole, tamoxifen, piroxicam, and fish oil has been demonstrated with low concentrations of DFMO.194

Clinical Trials In phase I prevention trials, DFMO at a dose of 0.5 mg/m2/day reduces tissue polyamines in colon and skin,197,198 and causes regression of cervical intraepithelial neoplasia when used topically, topically.199 DFMO does not reduce tissue polyamines or other biomarkers of cellular proliferation in the human breast.200 As a single agent, DFMO has anticarcinogenic activity for nonmelanoma skin cancers, primarily basal cell carcinoma. In combination with an NSAID (sulindac), DFMO reduced adenoma recurrences suggesting synergistic reduction of colorectal cancer risk (Table 35.12). The ornithine decarboxylase 1 GG polymorphism at +316 position identifies a group of individuals more likely to have a colorectal neoplasia risk reductive benefit from DFMO intervention.201 A phase II 24-month randomized trial of DFMO + sulindac versus either drug as monotherapy for reduction of colonic neoplastic progression in patients with familial adenomatous polyposis is ongoing as of 2017.202 Preliminary data suggest some cancer risk–reducing agent activity for the lower esophagus and the prostate (see Table 35.12).203

Statins Mechanism Statins or hydroxyl-3-methylglutaryl coenzyme A (HMG-CoA) reductase inhibitors inhibit conversion of HMGCoA to mevalonate, a cholesterol precursor. The statins are a class of medications with similar structures but with variable moieties that can result in hydrophilic (pravastatin, rosuvastatin) and lipophilic (lovastatin, simvastatin,

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fluvastatin, atorvastatin) forms.204 Statins decrease risk of cancer in preclinical studies by inhibiting Ras- and Rho-mediated cell proliferation, upregulating cell cycle inhibitors (e.g., p21 and p27), inducing apoptosis of transformed cells, and inhibition of angiogenesis.205

Evidence in Preclinical In Vivo Carcinogenesis Models Lipophilic statins delay progression of pancreatic intraepithelial neoplasias and growth of pancreatic carcinoma xenografts. Atorvastatin alone and in combination with NSAIDs reduced colonic adenoma and adenocarcinoma incidence and multiplicity by half in rodent transgenic and chemical carcinogenesis models. Lovostatin reduced lung adenoma multiplicity but not incidence.204 TABLE 35.12

Difluoromethylornithine as a Cancer Risk–Reducing Agent

Population

Dose per Day, Duration

Phase

End Point

Outcome

Citations

Low-risk bladder cancer (Ta. T1. Grades 1 or 2)

1 g vs. placebo × 1 year

III

Bladder cancer recurrence

Did not prevent or delay recurrence

287

Prostate risk—men with family history prostate cancer, age 35–70 y

500 mg vs. placebo × 1 y

IIb

Prostate volume, polyamines, PSA

10-fold reduction of prostate size increase over 1 y compared to placebo, PSA reduction nonsignificant

288

Nonmelanoma skin cancer

500 mg/m2 vs. placebo × 4–5 y

III

New nonmelanoma skin cancers

Lower rate of basal cell carcinomas per year (0.28 vs. 0.40); persistent reduction in nonmelanoma skin cancers, not statistically significant

289, 290

Colon adenomas

DFMO: 500 mg Sulindac: 150 mg vs. placebo × 3 y

IIb

Adenoma recurrence

Risk ratio for adenoma recurrence for DFMO-sulindac treatment = 0.30; 95% CI, 0.18–0.49

148

PSA, prostate-specific antigen; DFMO, difluoromethylornithine; CI, confidence interval.

Epidemiology Several case control studies evaluating statin effects have shown a significant association with lower risk of colorectal adenocarcinoma with odds ratios ranging from 0.53 to 0.91 for arzoxifene. Secondary analysis of a celecoxib prevention trial demonstrated no statin protection against colorectal neoplasms.206 The WHI (prospective longitudinal cohort of 159,319 women) found that lovastatin was associated with a lower risk of developing colorectal cancer (HR, 0.62; 95% CI, 0.39 to 0.99).207 Prospective longitudinal studies have shown mixed results. The Physician’s Health Study reported statin use was inversely associated with prostate cancer (adjusted RR, 0.51),208 whereas the Nurse’s Health Study showed no association with risk of breast cancer.209

Clinical Trials Several large trials of pravastatin or simvastatin on cardiovascular disease risk with cancer as secondary end points have shown no benefit for reducing cancer risk with follow-ups between 18 months to 4 years. These trials were not adequately powered to examine cancer end points.204 Interventional trials to determine statin preventive efficacy for colon, hepatocellular, and breast cancers are ongoing.204 Statins may be effective risk-reducing agents

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in individuals with the A/A variant of the predominant T/T genotype of rs12654264 of the HMG-CoA reductase gene.210

Metformin Mechanism Metformin, an oral antidiabetic drug in the biguanide class, is the first-line drug of choice for the treatment of type 2 diabetes. Cancers are more common in diabetics and obese individuals than their normal weight and normoglycemic counterparts, leading to the hypothesis that elevated serum insulin concentrations promote cancer risk.211 Insulin and insulin-like growth factors (IGF1 and 2) stimulate cellular DNA synthesis, proliferation, and tumor growth through phosphoinositide 3-kinase (PI3K), mammalian target of rapamycin (mTOR), and the RasMAPK signaling pathways.211 Metformin activates the adenosine monophosphate–activated protein kinase (AMPK) via liver kinase B1 (LKB1), a protein-threonine kinase that has tumor suppressor activity.204 Metformin anticarcinogenesis activity appears to be broad and includes downregulation of ErbB2 and epidermal growth factor receptor (EGFR) expression, inhibiting the phosphorylation of ErbB family members, IGF1R, AKT, mTOR, and STAT3 in vivo. Low doses of metformin inhibit the self-renewal/proliferation of cancer stem cells in breast, colon, and pancreatic models.212

Evidence in Preclinical In Vivo Carcinogenesis Models Metformin reduces tobacco carcinogen–induced tumors in mice, and pancreatic premalignant and malignant tumors in hamsters.204 However, metformin’s anticarcinogenic activity appears dependent on dose and induced carcinogenesis process. Metformin promoted carcinogenesis in MNU-induced rat breast cancers, MMTV-Neu ER-negative breast cancers, OH-BBN-induced bladder, and Min+ mouse intestinal tumors using nonobese rodents.213 Metformin cancer risk–reducing agent effects may be limited to obesity- and diabetes-associated carcinogenesis mechanisms.

Epidemiology Multiple case control and cohort analyses of metformin use with subsequent meta-analyses report a decrease in overall cancer incidence of 10% to 40%. In meta-analyses as reviewed by Heckman-Stoddard et al.,214 metformin is associated with reduced risk of colon, liver, pancreas, head and neck, breast, endometrial, and lung cancers. Biases such as the effect of tobacco use in the case of lung cancer; obesity in the case of pancreatic, endometrial, and breast cancer; and publication bias toward positive studies have reduced the impact of population-based data and justified prospective interventional trials.

Clinical Trials Metformin reduces colonic adenoma recurrence and an early pathologic surrogate, aberrant crypt foci.215,216 Tissue biomarker studies, primarily assessing proliferation using Ki67 have demonstrated modest reduction in neoplastic cellular proliferation using phase IIa window of opportunity prospective clinical trials in patients undergoing surgical resection of breast, prostate, head and neck, and endometrial carcinomas (Table 35.13). Metformin’s proapoptotic activity using terminal deoxynucleotidyl transferase (TdT) dUTP nick-end labeling appears stronger than its antiproliferative effects than proliferation end points.

DIET-DERIVED NATURAL PRODUCTS Mechanism Polyphenolic phytochemicals such as curcumin, resveratrol, epigallocatechin gallate (EGCG), genistein, and ginger are attractive as cancer risk–reducing agents for their low toxicity and multimechanism anticarcinogenic properties. They have anti-inflammatory activity in part through scavenging of reactive oxygen species, modulation of protein kinase signal transduction pathways (e.g., STAT3, HER2/neu, MAPK, and AKT), and downstream inhibition of eicosanoid synthesis potentially due to upstream inhibition of NF-κB and PPAR or direct inhibition of eicosanoid-metabolizing enzymes.217–219 Curcumin and presumably other polyphenolics

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downregulate stem cell driver signaling systems Wnt, Hedgehog, and Notch with subsequent reductions of breast, pancreatic, and colonic stem cell self-renewal.220,221 Omega-3 fatty acids (i.e., derived from marine products) compete with omega-6 fatty acid substrates for eicosanoid-metabolizing enzymes with subsequent tissue reduction of these inflammatory mediators.222 These fatty acids have other diverse anticarcinogenic mechanisms (e.g., G protein inhibition, changes in membrane physical characteristics that alter transmembrane signaling protein dynamics) that make them attractive as cancer risk–reduction agents.223 Whole berries, black raspberries, and strawberries contain mixtures of multiple anticarcinogenic compounds such as ellagic acid, anthocyanins, and tocopherols. Research-grade berries are grown in a standardized cultivation environment and assayed for key components to ensure year-to-year reproducibility despite yearly climatologic variation. Berries have potent stabilization of methylation properties in addition to the expected anti-inflammatory and antioxidative properties associated with the prominent components.224

Preclinical and Clinical Anticarcinogenesis Efficacy Diverse diet-derived natural products have moderate to strong anticarcinogenic effects in both chemical and transgenic rodent carcinogenesis models; yet, early-phase clinical trials have failed to demonstrate sufficient systemic bioavailability to support further biomarker-based efficacy trials (Table 35.14). For example, in the case of curcumin, no free curcumin or minute quantities (0.002% ± 0.012%) of an oral dose are recovered from the 24hour collected urine.225 Little curcumin has been detected in plasma or tissues, raising the possibility of biologically active conjugates or deconjugation at the target site.226 Resveratrol’s plasma bioavailability exceeds that of curcumin and partitions into human colon tissue at 10-fold concentrations compared to plasma227; yet, maximum tissue concentrations remain lower than those considered necessary for pharmacologic activity.228 TABLE 35.13

Metformin as a Cancer Risk–Reducing Agent

Population

Dose per Day, Duration

Phase

End Point

Outcome

Citations

Colon

250 mg/d × 1 y vs. placebo

IIb

ACF

Metformin arm reduced ACF from 8.78 to 5.11; P = .007

216

Colon

250 mg/d × 1 y vs. placebo

IIb

Adenoma recurrence

Adenoma recurrence RR, 0.60; 95% CI, 0.39–0.92, metformin vs. placebo

215

Endometrial (carcinoma or hyperplasia)

Preoperative window; 850 mg twice daily 1–4 wk preoperative; IBC

IIa

Ki67 (proliferation index)

17.2% decrease, P = .002, metformin vs. control

291

Breast

Preoperative window; 850 mg daily × 3 d, then 850 mg twice daily × 28 d preoperatively; IBC

IIa

Ki67

No change; decrease Ki67 in insulin resistance

292

Breast

Preoperative window; 500 mg three times daily × 2–3 wk; IBC

IIa

TUNEL, Ki67

3% decrease Ki67 (P = .016); 50% increase TUNEL staining (P = .004)

293

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Breast

Preoperative window; 500 mg once daily × 1 wk; 500 mg twice daily × 1 wk, metformin vs. placebo; IBC

IIa

Ki67; Affymetrix GeneChip analysis

3.4% decrease Ki67 (P = .027)

294

Breast

Preoperative window; 500 mg twice daily × 2 wk; IBC + DCIS; BMI >25

IIa

Ki67

No change in Ki67

295

Barrett esophagus

Dose escalation 500 mg to 2,000 mg for 12 wk, metformin vs. placebo

IIa

pS6K (mTOR pathway); Ki67; caspase 3

No change in pS6K, Ki67, or caspase 3

296

Head and neck

Preoperative window: 500 mg/d × 3 d, then 500 mg twice daily × 3 d, then 1,000 mg twice daily × 21 d

IIa

Ki67, TUNEL, CAV1, GALB, MCT4

Increase: TUNEL, CAV1, GALB; no change: Ki67, MCT4

297

Prostate

Preoperative window; 500 mg three times/d × 4– 12 wk

IIa

Ki67, pAMPK

29.5% decrease Ki67; no change pAMPK

298

ACF, aberrant crypt foci; RR, relative risk; CI, confidence interval; preoperative window, neoadjuvant treatment prior to surgery; IBC, invasive breast cancer; TUNEL, terminal deoxynucleotidyl transferase dUTP nick end labeling; BMI, body mass index; mTOR, mammalian target of rapamycin; pS6K, ribosomal protein S6 kinase beta-1 (S6K1), also known as p70S6 kinase; CAV1, caveolin-1; GALB, B-galactosidase; MCT4, monocarboxylate transporter 4; pAMPK, 5′ adenosine monophosphate–activated protein kinase. Adapted from Higurashi T, Hosono K, Takahashi H, et al. Metformin for chemoprevention of metachronous colorectal adenoma or polyps in post-polypectomy patients without diabetes: a multicentre double-blind, placebo-controlled, randomised phase 3 trial. Lancet Oncol 2016;17(4):475–483.

Pharmacologic versus Dietary Equivalent Dosing Diet-derived cancer risk reductives are often identified by population-based associations with food types and intake. Despite extensive preclinical data indicating that diet-derived natural products reduce risk from multiple epithelial cancers, purified formulations have failed to improve risk in randomized controlled trials. In the majority of in vitro studies of mechanism, concentrations often exceed those attainable in human target tissues.228 The chronic low concentrations of active anticarcinogens in a complex diet have not been accounted for in contemporary studies or risk reductive recommendations. Using ApcMin mice, Cai et al.228 found that a mouse dietary equivalent reserveratrol low dose reduced the adenoma number by approximately 40% and the overall tumor burden by approximately 52% compared to the 2,000-fold higher pharmacologic dose. In humans, a 5-mg resveratrol dose, consistent with the dose of resveratrol in the diet or with wine, enhanced activation of AMPK, neoplastic cellular autophagy, and increased expression of the cytoprotective NAD(P)H dehydrogenase, quinone 1 (NQO1) compared to a 2,000-fold higher 1-g dose. Maximal activation of AMPK and autophagy are achieved at submicromolar resveratrol concentrations.228 Using intraepithelial biomarker end points in human phase II trials, berry formulations reduce esophageal dysplasia and oral leukoplakia.224 Curcumin at doses that are not detected pharmacokinetically reduces the number of colon aberrant crypt foci in human smokers.229 A bell-shaped dose response for resveratrol and potentially other diet-derived natural products suggest that dietarily achievable doses may be the most efficacious future strategy to deliver natural product–based cancer risk reductives.

ANTI-INFECTIVES

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Many infectious agents are known causes of human cancers including the human hepatitis viruses, hepatitis B virus (HBV) and hepatitis C virus (HCV), for hepatocellular carcinoma230; Helicobacter pylori for gastric adenocarcinoma231; human papillomaviruses (HPVs) for cervical, anal, vulva, penis, oral cavity, and pharynx232; herpes virus-8 for Kaposi sarcoma233; Epstein-Barr virus for Burkitt and other lymphomas234; liver flukes for cholangiocarcinoma235; and schistosomes for bladder carcinoma.236 The success of HPV vaccine in reducing the incidence of intraepithelial neoplasia of the cervix (reviewed in Chapter 74) is one example that demonstrates the potential of immune based cancer risk reducing therapies immune based cancer risk reducing therapies (immunochemoprevention) for epithelial targets for which an etiologic agent can be identified. TABLE 35.14

Selected Diet-Derived Natural Products with Cancer Risk–Reducing Activity

Nutritional Extract

Source

Mechanisms

Curcumin ((1E,6E)-1,7-bis-(4hydroxy-3methoxyphenyl)-1,6heptadiene-3,5dione or diferuloylmethane)

Turmeric, rhizome of Curcuma longa

Inhibits PGE2 synthesis via direct binding to COX-2 and through inhibition of NF-κB; angiogenesis. ErbB2 transduction; PI3KAkt transduction; inhibits stem cell self-renewal Agonist: vitamin D receptor

Resveratrol (3,5,4′-trihydroxytrans-stilbene)

Grapes, mulberries, peanuts, and Cassia quinquangulata plants

Ginger (gingerols, paradols, shagaols)

Rhizome of Zingiber officinale

In Vivo Anticarcinogenesis Efficacy

Human Trials

Citations

Colon, breast, skin

Phase I: Poor bioavailability due to biotransformation in gut, enterohepatic cycling of metabolites Phase IIa: reduces aberrant crypt foci

225, 229

Inhibits carcinogen activation via inhibition of phase I isozyme, eicosanoids via direct binding; NFκB; Nrf2. Acts as a caloric restriction mimetic, activates the histodeacetylase SIRT1 and AMPK

Colorectal, breast, pancreas, skin, and prostate

Physiologic doses achieved in diet 2,000-fold below pharmacologic doses more potent anticarcinogenic effect than high pharmacologic doses. Phase I: 1-g dose generates peak concentration 45 y (OR, 1.92; 95% CI, 1.18– 3.11), alcohol use (OR, 1.67; 95% CI, 1.07–2.62)

304

Gastric precancerous lesion (Shandong Intervention Trial)

3,365

H. pylori eradication: amoxicillin and omeprazole × 2 wk Vitamin supplement: vitamin C, vitamin E, and selenium × 7.3 y Garlic supplement: aged garlic extract

4, 8, 15 y

Histologic progression

H. pylori eradication: reduced combined prevalence of severe chronic atrophic gastritis, intestinal metaplasia, dysplasia, or gastric cancer in 1999 OR, 0.77;

305– 307

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and steam-distilled garlic oil × 7.3 y Placebo

H. pylori infection (China Gastric Cancer Study Group)

1,630

H. pylori eradication: omeprazole, amoxicillin + clavulanate, metronidazole × 2 wk vs. placebo

95% CI, 0.62– 0.95; 2003 OR, 0.60; 95% CI, 0.47–0.75; 2010 OR; 2010: Reduced gastric cancer incidence OR, 0.61; 95% CI, 0.38–0.96; P = .032. No effect on dysplasia + gastric cancer prevalence Vitamin, garlic: No effect 7.5 y

Gastric cancer

No overall reduction in gastric cancer; subgroup of H. pylori carriers without precancerous lesions, eradication significantly decreases gastric cancer development

308

RR, relative risk; CI, confidence interval; IM, intestinal metaplasia; OR, odds ratio.

Helicobacter pylori Eradication and Reduction in Gastric Cancer Risk Treatment of H. pylori with a short 2-week course of antibiotics induces regression of nonmetaplastic gastric atrophy and intestinal metaplasia in geographically diverse regions. Eradication of the H. pylori infection improves pathologic regression rate (Table 35.15). A pooled analysis of clinical trials and cohort studies of H. pylori eradication therapy finds lower incidence of gastric cancer than those treated compared to those who were not treated (pooled incidence rate ratio, 0.53; 95% CI, 0.44 to 0.64).238 Because H. pylori infection is so widespread, mass eradication campaigns in high-risk regions are being considered.242 However, complicating this strategy are data associating reduced risk of both esophageal adenocarcinoma and gastric cardia carcinoma with H. Pylori infection.243

Multiagent Approaches to Cancer Risk Reduction In the transition to molecularly targeted interventions, combinations of targets that logically address critical carcinogenic pathways may have greater efficacy than single agents. For example, previously demonstrated interactive signaling of epidermal growth factor receptors and cyclooxygenase-2, experiments in Min+ mice244 demonstrates cancer-preventive synergism. Combining atorvastatin with selective or nonselective cyclooxygenase inhibitors enhanced the inhibition of azoxymethane-induced colon carcinogenesis in F344 rats and reduced the dose of the combined drugs required to achieve reduction of colon carcinogenesis.245 DFMO plus sulindac inhibited adenoma formation in a phase IIb trial of 375 patients with prior history of adenomas followed for 36 months (see Table 35.12).148 As more data accumulates from in vivo models, combined drugs aimed at specific targets in coordinated signaling pathways will enter clinical biomarker-based trials.

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36

Prophylactic Cancer Vaccines John T. Schiller and Olivera J. Finn

INTRODUCTION Vaccines to prevent cancer can be divided into two classes. The first class seeks to prevent persistent infection by microbes that are the central cause of many human cancers. Similar to the strategy used in many successful vaccines against other infectious agents, these vaccines are primarily based on the generation of antibodies that interfere with the infectious process. Vaccines of this class targeting hepatitis B virus (HBV) and human papillomaviruses (HPVs) will have a major impact on cancer cases and deaths in the coming years. The first half of this chapter discusses the development and implementation status of these vaccines and the prospects for developing similar vaccines against other oncogenic microbes. The second class of vaccines seeks to prevent the progression of premalignant neoplasia to invasive cancers. Although antibody effectors may function in some instances, most of these vaccines are designed to generate cellmediated immune responses, mostly T cells that would eliminate or control the premalignant disease. Premalignant neoplasia can have either an infectious agent or noninfectious etiology, and the vaccines can target microbial or self-antigens. Although targeting microbial antigens in a precancer would be considered prophylactic from the point of view of cancer, it is therapeutic from the point of view of infectious disease. There has been considerable effort to develop therapeutic vaccines to eliminate persistent infections by cancer-causing microbes, but, to date, none have resulted in a commercial vaccine, and they are not further discussed in this chapter. Therefore, second half of the chapter focuses on the theoretical underpinnings, impediments to the development, and promising advances for prophylactic cancer vaccines targeting various forms of self-antigens.

OVERVIEW OF INFECTIOUS AGENTS IN CANCER Infectious agents are important causes of cancer, causing an estimated 15% of all cancer. The International Agency for Research on Cancer (IARC) has designated as carcinogenic agents eight viruses, three parasites, and one bacterium.1 The viruses are HBV; hepatitis C virus (HCV); HPV (types 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, and 59); Epstein-Barr virus (EBV); Kaposi sarcoma–associated herpesvirus (KSHV), also known as human herpes virus type 8 (HHV-8); human T-cell lymphotropic virus type 1 (HTLV-1); and human immunodeficiency virus type 1 (HIV-1). The three parasites are Schistosoma haematobium, Opisthorchis viverrini, and Clonorchis sinensis. In addition, Merkel cell polyomavirus (MCPyV), designated as a probable carcinogen by the IARC, is widely acknowledged as a major cause of a rare skin cancer, Merkel cell carcinoma.2 The only carcinogenic bacterium identified to date is Helicobacter pylori. All of these agents are considered to be direct carcinogens, with the exception of HIV-1, whose immunosuppressive activities indirectly potentiate carcinogenesis by promoting persistent infections of other oncogenic microbes. Some carcinogenic microbes express specific oncogenes that influence proliferative or antiapoptotic activities via interaction with cellular gene products (e.g., HPV E6 and E7, EBV LMP1, MCPyV T antigen, and HTLV-1 Tax). Other agents, such as HBV, HCV, and H. pylori, primarily induce cancer more indirectly, as a result of chronic tissue injury and the inflammatory response to the infection. A discussion of specific carcinogenic mechanisms is beyond the scope of this review. However, a common feature of microbial-induced cancers is that carcinogenesis is an aberration of the microbe’s life cycle and an uncommon outcome of infection that persists for years. Estimates of the global burden of infection-attributable cancers are periodically generated by the IARC, with the most recent update for the year 2012 published in 2016.1 It was estimated that worldwide, 2.2 million cancers (15.4%) annually are caused by infections. However, the attributable fraction of infectious agent–associated cancer varies widely by region, from 31.3% in sub-Saharan Africa to 4.0% in North America. This disparity largely reflects differences in economic development, with a microbial attributable fraction of 23.4% in less

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developed regions versus 9.2% in more developed regions. More than 20 distinct cancer types are associated with infectious agents (Table 36.1), but 3 types (i.e., noncardia gastric, liver, and cervical cancers) account for 83% of cases. Not surprisingly, the agents that cause these cancers (H. pylori, HBV/HCV, and HPV, respectively) are responsible for the vast majority of infection-associated cancers (92% overall; Table 36.2). The fraction of the individual cancers attributable to a specific infection varies widely, from 100% for cervical cancer and adult T-cell leukemia/lymphoma to less than 5% for bladder, laryngeal, and oral cavity cancers (see Table 36.1). TABLE 36.1

Cancer Types Associated with Infectious Agents and Attributable Percentage No. of New Cases by Infectious Agent(s)

Attributable Percentage

Cancer Type

Infectious Agent

Noncardia gastric

Helicobacter pylori

730,000

89.0%

Liver

Hepatitis B virus; hepatitis C virus

570,000

73.4%

Cervix uteri

Human papillomavirus

530,000

100.0%

Nasopharynx

Epstein-Barr virus

83,000

95.5%

Kaposi sarcoma

Kaposi sarcoma virus

44,000

100.0%

Anus

Human papillomavirus

35,000

88.0%

Hodgkin lymphoma

Epstein-Barr virus

32,000

49.1%

Oropharynx

Human papillomavirus

29,000

30.8%

Cardia gastric

H. pylori

23,000

17.8%

Penis

Human papillomavirus

13,000

51.0%

Gastric non-Hodgkin lymphoma

H. pylori

13,000

74.1%

Non-Hodgkin lymphoma

Hepatitis C virus

13,000

3.6%

Vagina

Human papillomavirus

12,000

78.0%

Oral cavity

Human papillomavirus

8,700

4.3%

Vulvar

Human papillomavirus

8,500

24.9%

Larynx

Human papillomavirus

7,200

4.6%

Bladder

Schistosoma haematobium

7,000

4.6%

Burkitt lymphoma

Epstein-Barr virus

4,700

52.2%

Adult T-cell leukemia and lymphoma

Human T-cell lymphotropic virus 1

3,000

100.0%

Bile duct

Opisthorchis viverrini; Clonorchis sinensis

1,300

NA

Merkel cell carcinoma

Merkel cell polyomavirus

NA

80.0%

NA, not available. Data adapted from Plummer M, de Martel C, Vignat J, et al. Global burden of cancers attributable to infections in 2012: a synthetic analysis. Lancet Glob Health 2016;4(9):e609–e616.

TABLE 36.2

Estimated Number of New Cancer Cases in 2012 Caused by Individual Infectious Agents in

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Males and Females

Infectious Agent

Percentage of Infectious Disease–Associated Cancers

No. of New Cases in Females

No. of New Cases in Males

Helicobacter pylori

35.4%

270,000

500,000

Human papillomavirus

29.5%

570,000

66,000

Hepatitis B virus

19.2%

120,000

300,000

Hepatitis C virus

7.8%

55,000

110,000

Epstein-Barr virus

5.5%

40,000

80,000

Kaposi sarcoma virus

2.0%

15,000

29,000

Schistosoma haematobium

0.3%

2,200

4,900

Human T-cell lymphotropic virus 1

0.1%

1,200

1,700

Opisthorchis viverrini or Clonorchis sinensis

0.1%

470

820

100.0%

1,100,000

1,100,000

All infectious agents

Data adapted from Plummer M, de Martel C, Vignat J, et al. Global burden of cancers attributable to infections in 2012: a synthetic analysis. Lancet Glob Health 2016;4(9):e609–e616.

The identification of an infectious agent as a cause of a cancer provides an exceptional opportunity to prevent that cancer by preventing the initiating infection, especially by the development and deployment of prophylactic vaccines, which have had a dramatic worldwide impact on many infectious diseases, even in low-resource settings, and have very favorable safety profiles. In this section, we consider the development of prophylactic vaccines against cancer-causing infectious agents, specifically the notable success against two agents, HBV and HPV, and the prospects for development of commercial vaccines for other infectious agents.

HEPATITIS B VACCINES HBV is a major cause of hepatocellular cancer (HCC), with over 400,000 attributable cases per year (see Table 36.1), with the highest incidences in East Asia and sub-Saharan Africa.1 In addition, it is a major cause of infant deaths due to fulminant hepatitis and adult deaths from cirrhosis. The prospect of prevention of these diseases, in addition to HCC, was an important incentive for development and subsequent worldwide deployment of HBV vaccines. In lower income countries, HBV transmission is primarily from mother to infant and from child to child. In developed countries, transmission is more often transmitted percutaneously or sexually.3 HBV vaccines were the first licensed prophylactic vaccines against an infectious cause of cancer. Commercial vaccines became available in 1982 and were based on subvirion 22-nm HBV surface antigen (HBsAg) particles purified from the blood of chronically infected individuals.4 Vaccines based on these particles were considered safe because they were stringently inactivated and lacked the viral DNA that is contained in the infectious 42-nm virions. However, concerns about transmission of unrecognized bloodborne pathogens led to the development of second-generation vaccines, the first licensed vaccines generated by recombinant DNA technology. Multiple companies, including many developing country manufacturers, now produce HBsAg vaccines at low cost in genetically engineered yeast (mostly Saccharomyces cerevisiae).5 They contain HBs protein spikes embedded in 22-nm lipid particles that closely resemble the HBsAg particles produced during human infections.6 Most are formulated with an aluminum phosphate or aluminum hydroxide adjuvant and are generally delivered in a threedose series by intramuscular injection at 0, 1 or 2, and 6 months. However, an HBsAg vaccine containing a proprietary CpG adjuvant (a Toll-like receptor 9 [TLR9] agonist) was recently approved in the United States for a two-dose regimen in adults.7 Combination vaccines including an HBsAg component are now widely available. HBsAg vaccines are recognized as safe by the World Health Organization (WHO), with mild pain, erythema, and swelling at the site of injection being the most common side effects. With the exception of a one per million rate

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of anaphylaxis, no serious adverse events have been causally linked to the vaccines.8 The HBV vaccines were initially recommended only for high-risk groups (e.g., babies of infected mothers, health-care professionals, and intravenous drug users). However, this approach did little to reduce the overall prevalence of HBV infection. Consequently, in 1992, the WHO recommended universal vaccination programs targeting infants, with the first dose optimally delivered within 24 hours of birth.9 It is especially important to prevent infant infections because early age of acquisition is a strong risk factor for establishment of chronic infection, the prerequisite for cirrhosis and HCC. Over 180 countries have introduced infant HBV vaccination programs, with the three-dose coverage estimated to be approximately 75%.3 A reduction in chronic HBV infection rates of greater than 90% has been seen in countries with high-coverage infant vaccination programs.4 Given that development of HCC from incident infection usually takes many decades, the impact of the vaccines on HCC rates has only recently begun to emerge, mostly from countries with early adoption of universal infant immunization and a historically high prevalence of HBV infection, such as Taiwan. In Taiwan, which began universal infant vaccination in 1984, the observed incidences of HCC in 6- to 26-year-old cohorts born before and after initiation of their vaccination program were 9.2 and 2.3 cases per 106 person-years, respectively (relative risk [RR], 0.24; 95% confidence interval [CI], 0.21 to 0.29).10 The vaccines are thought to protect primarily by the induction of HBs antibodies that bind the virus and prevent infection of hepatocytes. Consistent with this conjecture, passive transfer of purified immunoglobulins containing high concentrations of HBs antibodies can protect against hepatitis (e.g., in the setting of postexposure prophylaxis).5 A serum anti-HBs concentrations of 10 mIU measured 1 to 3 months after the last immunization is considered a reliable marker for protection. This level is reached in approximately 90% of young people after three doses but less often in older adults. Antibody responses decline over time, often becoming undetectable. Nevertheless, vaccinees who initially achieve the 10 mIU level remain protected from HBV-induced hepatitis, presumably due to the ability of their HBs-specific memory B cells, and perhaps T cells, to mount a protective anamnestic response. Protection has been observed for 20 to 30 years in a number of settings. Therefore, booster vaccinations are not generally recommended.11 Importantly, the vaccines provide protection against all eight HBV genotypes. Because the virus has high replication and mutations rates (due to replication via an RNA intermediate), there were concerns that escape mutants with changes in their HBs protein would rapidly develop and spread in vaccinated populations. Fortunately, although these types of mutants have been documented, they do not appear to pose a major threat to vaccine effectiveness, perhaps because they are substantially less fit than the vaccine-sensitive strains.4 HBV has no animal reservoir; thus, elimination of HBV infection in a population is an achievable goal. Again, the Taiwanese experience provides a useful illustration of what can be accomplished. The HBV seroprevalence in those younger than age 15 year decreased from 9.8% in 1984 to 0.3% in 2009.3 Based on the relatively high efficacy of the vaccines and herd immunity effects protecting the minority of individuals who are poor responders, the prospects for virtual elimination HBV-induced HCC worldwide are high, provided coverage rates, particularly in lower resource setting, continue to increase. However, this goal will take many decades, given the long interval between infection and cancer detection and the large number of individuals who are already chronically infected.

HUMAN PAPILLOMAVIRUS VACCINES HPV infections cause over 600,00 cancers annually. Approximately 80% occur in women, due to the dominance of cervical cancer (see Table 36.2). Essentially all cervical cancers are attributable to HPV infection, and 85% occur in lower income countries, in large measure due to the absence of effective screening programs. Two types of HPV, HPV16 and HPV18, cause approximately 70% of cervical cancers worldwide. An additional five types, HPV31, HPV33, HPV35, HPV45, HPV52, and HPV58, together cause another 20% of these cancers. The HPVattributable fractions for anal, vaginal, penile, oropharyngeal, and vulvar cancers are smaller, varying from 88% to 25% (see Table 36.1). However, HPV16 and HPV18 are associated with a large fraction of the HPV-positive cases (approximately 90%). There is strong epidemiologic evidence that the HPV infections that cause all of these cancers are predominantly sexually transmitted. Two other types, HPV6 and HPV11, cause 90% of genital warts but are almost never implicated in cancer. The HPV prophylactic vaccines are based on nonenveloped virus-like particles (VLPs) composed of 360 copies of the L1 major virion protein that assemble into an ordered icosahedron that mimics the outer shell of the authentic virus. Three vaccines that differ in composition are currently licensed for use in many countries worldwide. Cervarix (GlaxoSmithKline, Brentford, United Kingdom) is a bivalent vaccine containing VLPs of

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types 16 and 18. It is produced in recombinant baculovirus-infected insect cells and contains a proprietary adjuvant, AS04, consisting of an aluminum salt plus the TLR4 agonist monophosphoryl lipid A, a detoxified form of lipopolysaccharide (LPS). Gardasil (Merck, Kenilworth, NJ) is a quadrivalent vaccine containing VLPs of types of types 6, 11, 16, and 18. It contains a standard aluminum salt adjuvant and is produced in S. cerevisiae. Gardasil-9 is similar to Gardasil, but with the addition VLPs of oncogenic types 31, 33, 35, 45, 52, and 58.12 The clinical efficacy trials for licensure of Cervarix and Gardasil in young women had as their primary end point protection against cervical intraepithelial neoplasia (CIN) grades 2 and 3 caused by incident infection by the vaccine-targeted types. Remarkably, protection was virtually 100% at the end of the 4-year trials and has remained so in longer term follow-up, now up to a decade. Strong protection against vulvar and vaginal intraepithelial neoplasia and genital warts was also demonstrated in the Gardasil trials. Based on the ages of the efficacy trial cohorts and immunobridging to pre- and early adolescents, the U.S. Food and Drug Administration (FDA) approved Gardasil for females aged 9 to 26 years in 2006 and Cervarix for females aged 9 to 25 years in 2009. An efficacy trial in young men led to FDA approval of Gardasil for prevention of genital warts and anal cancer (based on prevention of anal intraepithelial neoplasia) in males in 2009. The current age recommendation is 9 to 26 years. Gardasil was simultaneously licensed for prevention of anal cancer in women under the assumption that HPV-induced anal carcinogenesis in men and women is biologically indistinguishable.12 High levels of protection from persistent anogenital infection, as measured by the presence of HPV DNA, by the vaccine-targeted types were also observed in the efficacy trials. However, protection from infection by other HPV types was limited to a few closely related types (i.e., HPV31, HPV33, and HPV45) and was partial at best. In addition, the vaccines had no detectable effect on infections present at the time of vaccination, both with regard to time to clearance or rate of progression to a higher grade neoplasia. For this reason, routine vaccination prior to initiation of sexual activity is strongly encouraged. The efficacy of Garasil-9 was clinically evaluated after the licensure of Cervarix and Gardasil, and thus, a placebo-controlled trial was considered unethical. Therefore, Gardasil-9 was approved in 2014 based on immunologic noninferiority for the HPV types shared with Gardasil and an efficacy of 97% in prevention of CIN2/CIN3 attributable to the five additional HPV types in Gardasil-9 compared with Gardasil.12 All three vaccines were initially approved for a series of three intramuscular injections over a 6-month period. Subsequently, it was found that the antibody responses to two doses, at 0 and 6 months, in girls and boys younger than age 15 years were noninferior to the responses to three doses in the individuals aged 15 to 26 years evaluated in the efficacy trials. These findings led to a WHO recommendation of a two-dose regimen for those aged 9 to 14 years in 2014 and its subsequent adoption in the United States and elsewhere. Surprisingly, post hoc analyses from three trials indicated that young women who happened to receive only one dose of vaccine were equally protected against infection by the vaccine-targeted types, in one trial even after 7 years.13 A randomized trial to formally compare the protection afforded by one versus two doses of Cervarix and Gardasil-9 in 10- to 16-yearold girls is now under way. None of the vaccines are approved for prevention of HPV- associated oropharyngeal cancer (OPC). The primary reason for this situation is the difficulty in conducting efficacy trials for this indication.14 The precursor lesions of OPC have not been definitively identified, precluding a disease end point short of cancer. Infection end points are also problematic. A large trial size would be necessary because the prevalence of oral infection by oncogenic HPV types is generally much lower than anogenital prevalence. Post hoc data from one trial indicate that vaccination prevents acquisition of oral HPV16/HPV18 infections.15 Despite the limited efficacy data, it is highly likely that the vaccines will have a major impact on HPV-associated OPC, at least secondarily because epidemiologic evidence indicates that it is predominantly caused by sexually transmitted HPV16/HPV18 infections, and the vaccines work exceptionally well at preventing anogenital infections by these types. Similar to the HBV vaccines, the HPV vaccines are thought to protect by the induction of type-restricted antibodies that prevent infection. The vaccines induce remarkably consistent, high-level, and durable antibody responses in humans.16 Seroconversion rates are virtually 100%, even after a single dose. Serum antibody levels peak several orders of magnitude higher than the levels induced after natural infection. After an initial 10-fold decline over the first 2 years, serum antibody titers stabilize or decline very slowly indefinitely, regardless of number of doses. The plateau levels of antibodies have now been observed for 10 years after three doses and 7 years after a single dose.13 The general expectations are that booster doses will not be required to maintain these protective antibody levels long term. The oligomerization of the B-cell receptors on naïve B cells by engagement with the ordered repetitive epitopes on the VLP surface and subsequent induction of strong downstream activation and survival signals are believed to be critical for the induction of the exceptionally strong and persistent antibody responses by the vaccines. The

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systemic antibodies, predominantly immunoglobulin G (IgG), induced by the vaccine after intramuscular vaccination can reach the cervicovaginal mucosal site of infection by a process of transudation via the neonatal Fc receptor in the tissue. Perhaps more importantly, systemic antibodies are exudated at the sites of epithelial trauma that are thought to be required for initiating HPV infections in the relevant tissues.17 As of 2018, 82 countries have introduced the HPV vaccines into their national immunization programs. There is increasing evidence that the vaccines are very effective at preventing cervicovaginal infection, cervical dysplasia, and genital warts in females and genital warts in males (even in female-only vaccination programs).18 The impact is most clearly evident in countries with high coverage rates, such as Scotland, where approximately 80% of adolescent girls receive the complete three dose series of Cervarix and approximately 90% receive at least one dose. In Scotland, the rates of CIN3, regardless of HPV type, in 20- to 21-year-olds at their first cervical screening decreased from 11.9 per 100,000 in the 1988 birth cohort, who were not vaccinated in the national program, to 2.9 per 100,000 in the vaccinated 1994 birth cohort.19 Decreases in rates of CIN in vaccinated cohorts have also been observed in Australia, United States, Canada, and Sweden. Preliminary evidence for a reduction in cervical cancer incidence in vaccinated cohorts in Finland was recently published.20 The biggest issue, by far, that limits the potential impact of the HPV vaccines is global vaccination rates. It was estimated that, as of 2014, approximately 400,000 cases of cervical cancer have been prevented worldwide, but only 10% are in less developed regions of the world.21 This situation arises because only 3% of young women in lower and lower-middle income countries have been vaccinated, compared to 34% in higher income countries. Even in some highly developed countries, such as the United States and France, less than 50% of girls and young women complete the vaccination series. Multiple factors contribute to low rates of uptake. In less developed regions, the primary issue is vaccine accessibility, due to the relatively high cost of both the vaccine and multidose vaccination programs for adolescents. Vaccine production by manufacturers in developing countries and, hopefully, an eventual transition to single-dose vaccination programs could address these limitations. In some more developed countries, such as the United States, the primary issues are insufficient vaccine advocacy by health-care providers and parental hesitancy.22

PROSPECTS FOR PROPHYLACTIC VACCINES AGAINST OTHER ONCOGENIC MICROBES Helicobacter pylori There is no commercial H. pylori vaccine despite the fact that the bacterium is the cause of more cancers, primarily gastric adenocarcinoma, than any other infectious agent (see Table 36.1) and is also the principal cause of peptic ulcers. An estimated 50% of the world population is infected. Infection is typically acquired in childhood and persists for life. The lack of a vaccine is only partially compensated by the availability of antibiotic treatments. Although they can be effective at treating peptic ulcers, the regimens are complex, so compliance can be poor, and their use has led to the emergence of drug-resistant H. pylori strains, limiting their effectiveness. Importantly, gastric cancers are usually diagnosed at a late stage, and therapeutic use of antibiotics has had little effect on the progression of H. pylori–induced cancers. Widespread use of antibiotics in cancer prophylactic programs in young children would be expected to exacerbate the resistance problem. In addition, such programs would not prevent reinfection. Programs involving repeated administration would repeatedly subject individuals to the adverse side effects of antibiotic treatments (e.g., diarrhea and nausea) and would be prohibitively expensive. Therefore, there appears to be a clear public health argument for development of a prophylactic H. pylori vaccine to prevent stomach cancers and peptic ulcers.23 However, there is epidemiologic evidence that H. pylori infection is associated with reduced risk of esophageal adenocarcinoma and allergic asthma. Decisions to implement widespread prophylactic vaccination programs would have to consider the potential for increases in these diseases. There has been limited commercial investment in the development of H. pylori vaccines, despite their potential impact and estimates that they would be cost-effective in the United States.24 Factors limiting investments may include (1) the perception that antibiotics are a sufficient alternative, (2) the declining prevalence of infection in developed countries, (3) the limited attractiveness of current vaccine candidates, (4) the expense of phase III efficacy trials, and (5) the decades between vaccination administration and meaningful reduction in H. pylori– induced diseases.25 A number of vaccines have been evaluated in animal and human challenge models involving various antigens (whole bacteria, urease, catalase, vacA, and Hsp60), adjuvants (alum, Escherichia coli heat-labile toxin, and

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cholera toxin), and routes of administration (oral, nasal, sublingual, parenteral, and live recombinant bacteria). However, basic questions such as those regarding the critical immune effector (antibodies or T cells) and preferable route of administration (mucosal or parenteral) remain unresolved.23,25 Encouragingly, the results of a recently published phase III trial are the first demonstration of vaccine efficacy against natural acquisition of H. pylori.26 The vaccine consisted of a fusion protein of H. pylori urease B and the B subunit of E. coli heat-labile toxin. It was delivered orally in three doses to 2,200 H. pylori–negative children aged 6 to 14 years at a single center in Jiangsu, China. Compared to the placebo control group, H. pylori acquisition was reduced by 72% in the first year, but efficacy was reduced to 55% by year 3. Although the study represents an important proof of concept, it is unclear whether it will lead to commercialization of this candidate or expand commercial interest in the development of others.

Epstein-Bar Virus The overall burden of EBV-associated cancer is sufficient to warrant vaccine development (see Table 36.1), and EBV infection is also associated with autoimmune diseases, including multiple sclerosis. Antiviral drugs have had limited impact on primary EBV infection or EBV-associated cancers. However, the cancer burden is spread over a diverse set of cancer types (see Table 36.2), and vaccine trials with a specific cancer end point would be very challenging. A possible exception might be Burkitt lymphoma, an aggressive B-cell malignancy, which has a relatively rapid onset and relatively high prevalence in children in equatorial regions of Africa and Papua New Guinea. However, its predominance in these lower resource locales provides little incentive for commercial development. If commercial vaccines are developed, it is likely that they will be licensed for the prevention of infectious mononucleosis (IM), a debilitating disease of young adults with relatively high frequency in many higher income countries.27 Trials in military recruits or college freshmen, for example, are feasible. The primary limiting factor has been the availability of sufficiently promising vaccine candidates to attract sustained industry investments. Contributing to this situation are the limitations of animal models for EBV and incomplete understanding of the clinical immune correlates of protection.28 Prophylactic vaccine development has focused primarily on the virion surface glycoprotein gp350 because antibodies to it can block infection of B cells. However, other surface glycoproteins are responsible for infection of epithelial cells and presumably would also need to be targeted to prevent nasopharyngeal carcinoma, an epithelial malignancy. The most promising clinical trial to date involved a vaccine consisting of recombinant gp350 protein in AS04, the adjuvant used in the licensed HPV vaccine Cervarix.29 It reduced the incidence of IM by 78% but did not prevent asymptomatic infection. Therefore, the potential impact of this vaccine on subsequent development of cancer is uncertain. Development of alternative vaccination candidates is continuing. Particularly encouraging are the virus-like display vaccines for gp350, which can generate 10- to 100-fold higher neutralizing antibody titers than the monomeric candidates previously evaluated.30

Hepatitis C Virus There is a high burden of HCV disease. An estimated 130 to 200 million people are infected worldwide. Despite improved screening and awareness, viral transmission, primarily percutaneously, is increasing in some developed and developing countries. Approximately 60% to 80% of individuals who are acutely infected develop lifelong chronic infection, and one-third of chronic infections lead to liver cirrhosis and/or HCC, resulting in 165,000 annual worldwide cases of HCC.31 This burden of disease is probably sufficient to warrant development of a prophylactic vaccine for high-risk individuals and perhaps the general population in high-incidence areas. The development of direct-acting antiviral drugs targeting three essential viral proteins has revolutionized treatment of chronic HCV infection, with a cure rate of greater than 90%.31 However, the potential of these antivirals to have global impact on HCC is limited by their high cost and potential for generation of resistant mutants that could limit their effectiveness, even when used correctly in dual- or triple-drug combinations. In addition, infection is often not diagnosed and treatment is often not started until an advanced stage of liver disease is reached, at which time elimination of the virus might not prevent cancer development. Several factors have limited the development of HCV prophylactic vaccines.32 Foremost, the exceptional genetic diversity and high mutation rate of the virus hinder development of broadly protective vaccines and promote rapid immune escape. There are seven major genotypes that vary by as much as 30%, and the virus replicates as a swarm of genetic variants within an individual, much like HIV. In addition, the immune mechanism(s) that would prevent initial infection and/or the establishment of chronic infection have not been

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definitively established, in large part because the only challenge model, in chimpanzees, was costly and is no longer available. Nevertheless, there continues to be substantial interest in the development of HCV vaccines. These activities have been promoted by the availability of the deep sequencing data that have identified conserved viral protein epitopes and the development of robust in vitro neutralizing assays to evaluate potentially protect antibody responses. Spontaneous resolution of acute infections, which are mostly asymptomatic, often generates a complete cure and immunity to reinfection. The primary goal of most vaccine developers is to generate a similar outcome, and thereby prevention of the establishment of chronic infection, the prerequisite for liver cirrhosis and HCC, and not to generate sterilizing immunity. However, it is unclear whether humoral or cell-mediated immunity is primarily responsible for resolution of acute infections or protection from reinfection. Consequently, vaccines designed to generate antibody responses against the envelope glycoproteins (E1 and E2), T-cell responses against nonstructural viral proteins (NS3, NS4a, NS4b, NS5a, and NS5b), or both are under active development.33 A leading candidate of each type is discussed in the following text. An E1/E2 protein subunit vaccine formulated in an oil-in-water adjuvant elicited serum antibodies in chimpanzees that were able to neutralize most HCV genotypes in an in vitro neutralizing assay. Sterilizing immunity to experimental challenge was observed in a subset of the vaccinated animals. This vaccine also generated strong cross-type neutralizing antibody responses in HCV-naïve humans.33 Display of the virion glycoproteins in the context of a VLP is an attractive strategy for increasing the magnitude and durability of neutralizing antibody responses. Several approaches for virus-like display of E1/E2 have generated promising immunogenicity results in small animal models, but none have been evaluated in a humans.34 The observations that some HCV infections resolve in the absence of an antiviral antibody response and that Tcell depletion exacerbates HCV infections in experimentally challenged chimpanzees support the hypothesis that vaccines that generate cell- mediated immunity might be protective. A prime/boost strategy involving recombinant adenovirus and naked plasmid DNA vectors expressing nonstructural viral proteins elicited strong CD4+ and CD8+ T-cell responses in naïve chimpanzees and suppressed acute-phase viremia upon challenge with a heterologous HCV genotype. Similar vaccines involving prime/boost with two adenovirus serotypes or an adenovirus/modified vaccinia virus Ankara prime/boost protocol generated T-cell responses in HCV-naïve humans. The latter vaccine is now being evaluated in HCV-naïve individuals who are at high risk for HCV infection (intravenous drug users) for protection against virus persistence (NCT01436357).33

Kaposi Sarcoma Virus KSHV is the main cause of Kaposi sarcoma (KS) and two rare B-cell malignancies, Castleman disease and primary effusion lymphoma. However, compared with the oncogenic microbes discussed earlier, there has been relatively modest investment in developing a KSHV vaccine.35 In part, this may be because these cancer account for only 2% of the infectious disease–associated cancer burden. In addition, the incidence of AIDS-associated KS has decline markedly in countries with effective anti-HIV drug treatment programs. Nevertheless, there remains an unmet need to prevent endemic and HIV-associated KS, particularly in sub-Saharan Africa, where KS is a leading cancer in adults. Disincentives for commercial development include the predominance of KSHV-induced cancer occurring in low-resource settings and the fact that there is no premalignant disease, in contrast to EBV and HCV, that could serve as an alternative disease end point for licensure. In addition, the failure to develop prophylactic vaccines against other herpesviruses, despite more extensive efforts, no doubt discourages investment in KSHV vaccines. However, KSHV belongs to the same γ-herpesvirus family as EBV; thus, successful development of a vaccine against EBV could serve as a roadmap for developing a KSHV vaccine. A marmoset model for KSHV has been developed, but no small animal infection model exists. Therefore, most vaccine studies have centered on mouse infection of the related γ-herpesvirus MHV-68. Vaccines based on purified MHV-68 lytic phase proteins, heat-inactivated virus, or replication-defective virus showed varying efficacy in reducing lytic replication but did not prevent establishment of long-term latency. Only replicationcompetent MHV-68 mutants were able to prevent latency establishment.35 A live attenuated virus vaccine that acts therapeutically is licensed for the human herpesvirus varicella-zoster virus. However, prophylactic vaccination with replication-competent derivatives of an oncogenic virus such as KSHV would raise substantial safety concerns for human use.

Other Infectious Agents The relatively low incidences of the cancers associated with MCV, HTLV-1, and the eukaryotic parasites make it

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unlikely that they will be vigorously targeted for commercial vaccine development as cancer preventative vaccines. Based on the HPV vaccine paradigm, it seems quite possible that an effective VLP-based vaccine to prevent MCV infection could be developed because MCV VLPs have a similar icosahedral structure and induce similarly high titers of neutralizing antibodies. However, asymptomatic MCV infections are highly prevalent in human populations, and there are no disease end points short of MCC on which to base clinical trials, making phase III efficacy trials impractical. There has been little investment in HTLV-1 vaccinations. However, relatively extensive vaccine trials for bovine leukemia virus, a delta-retrovirus related to HTLV-1 that is of economic concern to the cattle industry, suggest that development of a practical HTLV-1 vaccine would be challenging.36 Prevention efforts have centered on interrupting mother-to-infant transmission by discouraging breastfeeding by HTLV-1–infected women. Schistosomiasis is an important parasitic disease globally, perhaps second only to malaria. Consequently, there have been substantial efforts to develop vaccines to prevent Schistosoma infections,37 although no licensed vaccine is currently available. Most efforts have centered on Schistosoma mansoni and Schistosoma japonicum, which cause intestinal and hepatic schistosomiasis, and not S. haematobium, which primarily causes urogenital disease that can progress to bladder carcinoma. Successful development of a vaccine against the former would likely spur interest in developing a vaccine against the latter. C. sinensis is a fish-borne liver fluke and the cause clonorchiasis, a major foodborne hepatobiliary disease, particularly in East Asia, that can progress to cholangiocarcinoma. Protein subunit vaccines are under development and have demonstrated some reduction in worm burden in a rat model.38 However, a commercial vaccine does not seem imminent and would have little effect on global cancer rates in any event. Vaccine development for O. viverrini, another liver fluke that can cause cholangiocarcinoma, has been very limited.

VACCINES FOR CANCERS OF NONINFECTIOUS ETIOLOGY: TUMORSPECIFIC AND TUMOR-ASSOCIATED TARGET ANTIGENS Many of the most common human cancers, such as breast, prostate, lung, colon, and pancreatic cancers, have not been shown to be associated with any particular infectious agent and thus cannot benefit from prophylactic or therapeutic vaccines based on pathogen-derived antigens. The search for candidate antigens to incorporate into vaccines against these types of tumors focused instead on molecules produced by tumor cells that are significantly different between tumors and normal cells to not be subject to self-tolerance and thereby elicit effective antitumor immunity. Many such molecules were initially identified by immunizing mice with human tumor cells and deriving monoclonal antibodies that recognized the tumor cells and not their normal tissue counterparts. Although many candidate tumor antigens were discovered this way, there remained a question whether those same apparently tumor-specific molecules would be recognized by human antibodies and, even more importantly, human T cells. Technologic and conceptual advances in immunology, such as the discovery of interleukin-2 (IL2),39 the T-cell growth factor that enables expansion and cloning of tumor-specific human T cells in vitro, and the new appreciation of the importance of dendritic cells for endocytosing and cross-presentation of tumor antigens for priming of T cells, combined with learning how to generate and expand human dendritic cells in vitro,40 showed unambiguously that the human immune system could recognize molecules differentially expressed by tumor cells compared to normal cells and use them as targets to kill tumor cells.41 A concerted tumor antigen discovery effort that started in the late 1980s and intensified greatly over the next decade yielded many different types and categories of antigens; representative ones are listed in Table 36.3. Finding some of these antigens as targets of human tumor immunity was predictable based on the known mutations in oncogenes such as HRAS and KRAS or tumor suppressor genes such as p53, which not only drive tumorigenesis but also encode mutated peptides that can be presented in human leukocyte antigen (HLA) class I molecules on tumor cells to serve as targets for tumor-specific T cells or cross-presented by dendritic cells in both HLA class I and class II to prime both cytotoxic and helper T cells. Other predictably identified antigens were products of known oncogenic gene translocations and gene fusions, such as BCR/ABL in all acute lymphoblastic leukemias. Based on the results of mouse experiments that showed that the focus of the mouse immune response against carcinogen-induced tumors was the unique mutations in each tumor,42 antibodies and T cells were expected to be generated in cancer patients against unique mutations in their own tumors. It was not until recently, when sequencing of mouse and human tumors became possible and indeed practical, that these mutations were shown to be bona fide tumor antigens.43,44 All of these mutated antigens, some unique and some shared, belong to a category of tumor-specific antigens. This category also includes antibody idiotypes that are not random

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mutations but are nevertheless unique sequences clonally expressed on B-cell immunoglobulins. Inasmuch as Bcell lymphomas are clonal in origin, idiotypes represent highly tumor-specific unique antigens that could be targeted by the immune system.45 TABLE 36.3

Human Nonviral Tumor Antigens Recognized by Antibodies and T Cells Category

Example Antigens

Antibody Target

T-Cell Target

KRAS

No

Yes

HRAS

No

Yes

p53

Yes

Yes

Somatic mutations

No

Yes

BCR/ABL

Yes

Yes

BCR idiotypes

Yes

Yes

TCR idiotypes

Yes

Yes

HER2/neu

Yes

Yes

MUC1

Yes

Yes

Cyclin B1

Yes

Yes

WT1

Yes

Yes

PSA

Yes

Yes

Survivin

Yes

Yes

hTERT

Yes

Yes

Mesothelin

Yes

Yes

Tyrosinase

Yes

Yes

Glycopeptides

Yes

Yes

Phosphopeptides

Yes

Yes

Citrullinated peptides

Yes

Yes

MART-1/melan-A

Yes

Yes

PSMA

Yes

Yes

CD19

Yes

Yes

CD20

Yes

Yes

CD22

Yes

Yes

α-Fetoprotein

Yes

Yes

CEA

Yes

Yes

NY-ESO-1

Yes

Yes

MAGE family

Yes

Yes

GAGE family

Yes

Yes

Tumor-Specific Antigens Mutated and other oncogenic proteins

Nonmutated clonal antigens

Tumor-Associated Antigens Overexpressed proteins

Tumor-specific posttranslational modifications

Tissue differentiation antigens

Oncofetal antigens

Cancer-testis (CT) antigens

BCR, B-cell receptor; TCR, T-cell receptor; HER2, human epidermal growth factor receptor 2; MUC1, mucin 1; WT1, Wilms tumor 1; PSA, prostate-specific antigen; hTERT, human telomerase reverse transcriptase; MART-1, melanoma antigen recognized by T cells

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1; PSMA, prostate-specific membrane antigen; CEA, carcinoembryonic antigen.

The tumor antigen category that was not predicted and yet turned out to be most frequently identified, first by mouse monoclonal antibodies and later by antibodies and T cells from cancer patients, included nonmutated proteins that were nevertheless in some way differentially expressed between tumors and normal cells.41 The most commonly identified were proteins that were overexpressed in cancer cells compared to normal cells. Some of the most extensively studied are human epidermal growth factor receptor 2 (HER2)/neu, mucin 1 (MUC1), survivin, human telomerase reverse transcriptase (hTERT), Wilms tumor 1 (WT1), mesothelin, cyclin B1 and other cyclins, and p53. Overexpression could be due to overproduction of the protein by cancer cells or its accumulation due to changes in its stability. Antibodies and T cells against these molecules preferentially or solely recognize tumor cells versus normal cells that carry these same antigens but presumably below the threshold levels required for recognition. In addition to overexpression, many of these antigens are also posttranslationally modified differently in tumor cells compared to normal cells. This can include differences in glycosylation (e.g., the hypoglycosylated tumor form of MUC146), phosphorylation (e.g., numerous tumor-specific phosphopeptides identified through tandem mass spectrometry,47 including those derived from the insulin receptor substrate-248), and citrullination (e.g., citrullinated vimentin49). Inasmuch as cleavage of proteins to short peptides is dependent on where the carbohydrates, phosphate groups, or citrullines are located, even the repertoire of unmodified peptides is different if they derive from differentially modified proteins in tumor cells compared to normal cells. The next surprising category included differentiation- or tissue- specific antigens that are not different between tumors and their tissues of origin and should be subject to self-tolerance. This tolerance is apparently mediated by mechanisms other than deletion of self-reactive T cells because, in the setting of tumor growth, immune responses against these molecules appear. The most studied were melanoma antigens, such as tyrosinase and MelanA/melanoma antigen recognized by T cells 1 (MART-1), that are also expressed on melanocytes. Not surprisingly, induction of high levels of antibodies and T cells directed to these antigens can destroy not only melanoma cells but also normal melanocytes, causing autoimmunity that manifests as vitiligo.50 More recently, antitumor antibodies and T cells that target B-cell differentiation antigens CD19, CD20, CD22, and several others have been used therapeutically against B-cell lymphomas that carry these normal B-cell differentiation antigens.51 Targeting these antigens results in the elimination of not only malignant B cells but also normal B cells. In the case of melanoma and B-cell lymphomas, autoimmunity caused by the immune response against tissue differentiation antigens that are not significantly different between these tumors and their normal cell counterparts can be tolerated if the life of a cancer patient can be comfortably extended.52 There are many other antigens in this category, however, that would be unacceptable to target with a vaccine or other forms of immunotherapy for fear of inducing lifelong organ-specific autoimmunity. Two categories of nonmutated antigens that are safe to target with immunotherapy and use in vaccines are oncofetal antigens and cancer-testis (CT) antigens. Oncofetal antigens, as their name implies, are molecules that are expressed on various tissues during fetal development, but their expression is turned off in fully developed adult tissues. Malignant transformation of adult tissues can lead to their reexpression. The best-known examples are α-fetoprotein expressed by HCCs53 and carcinoembryonic antigen (CEA) found in colon cancer and several other tumors.54 CT antigens, best represented by NY-ESO-1 and the MAGE family of molecules, are highly expressed in many tumors but not in any normal tissues with the exception of germ cells.55

THERAPEUTIC CANCER VACCINES HAVE SET THE STAGE FOR PREVENTATIVE CANCER VACCINES Various tumor antigen categories and the majority of the individual antigens that belong to them were discovered and elucidated at least two decades ago, with several new antigens added in intervening years. Almost every one of them has been considered a vaccine candidate, and a large number of these vaccines have made it as far as clinical testing in phase I and II clinical trials. Because most tumor-bearing patients were found to possess antibodies and T cells specific for these antigens, it was assumed that in the course of tumor development, the immune system did mount an antigen-specific defense that might have, for an extended period of time, prevented the tumor from becoming a clinical disease, but eventually, the tumor was somehow able to eventually evade this defense. Contemporaneous studies in mouse models showed that cancer immune surveillance could have at least three different outcomes: elimination, equilibrium, and escape.56 There has been a lot of new evidence that having tumor antigen–specific immunity is beneficial even after tumor escape. Patients with antitumor immunity at the

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time of diagnosis have a longer time to recurrence compared to patients without such immunity, and, in rare instances, tumors do not recur at all. Evidence of an immune infiltrate into the primary tumor, in particular activated T cells, has been associated with increased time to recurrence and longer survival.57 These important observations gave rise to the idea that the apparently failed immune defense could be strengthened with a therapeutic vaccine targeting tumor antigens in order to more frequently and reproducibly achieve lack of recurrence or prolonged survival. With the exception of varicella-zoster vaccines, therapeutic vaccines had not been successfully developed against an ongoing pathogen infection. Other licensed infectious disease vaccines are administered to prevent initial infection or disease. The reason therapeutic vaccines were even considered in the setting of cancer was the perceived “window of opportunity” that is created by the surgical removal of the primary tumor and a certain period of time, often months to years, that it takes for the cancer to recur. It was thought that this postsurgical period of minimal residual disease would be an opportune time to administer vaccines and, through the best possible choice of antigens, adjuvants, and delivery systems, assure stimulation of the most effective antitumor responses that would destroy the remaining tumor cells. The tumor immunology field had collectively decided that effective antitumor immunity required highly activated CD8+ cytotoxic T cells, and thus, short peptides that bound most common HLA molecules on antigenpresenting cells and were again presented on those molecules on target tumor cells were the first choice for vaccine antigens to stimulate T cells. This was followed by a great variety of vaccine designs, including soluble peptides and proteins that were administered with a variety of adjuvants or loaded on dendritic cells, viral and bacterial vectors encoding tumor antigens, and VLPs containing such antigens. Hundreds of phase I clinical trials supported by data from numerous preclinical mouse models were run, and some showed encouraging enough results to proceed to phase II. Unfortunately, few therapeutic vaccines showed sufficient immunogenicity and efficacy to warrant testing in a randomized phase III trial.58,59 Those that did, failed to reach the required end points for FDA approval. Only one therapeutic cancer vaccine, sipuleucel-T (Provenge), was FDA approved in 2010 for use in prostate cancer patients. This was based on a statistically significant but nevertheless small difference in median overall survival, with vaccinated patients surviving, on average, 4 months longer than placebo controls.60 Immune responses induced by therapeutic cancer vaccines were much lower than what was expected based on the experience with infectious disease vaccines, the only available reference point. This was erroneously attributed to, among other things, the nature of the tumor antigens used in therapeutic cancer vaccines and tolerance to them as a result of their high similarity to self-molecules on normal cells. Although, in the case of a few ill-chosen antigens, this might have been the reason, the critical factor that limited the immunogenicity and antitumor efficacy of most therapeutic cancer vaccines was the less than optimal condition of the patient’s own immune system. Evidence of immune suppression in cancer patients started to accumulate in the early 1990s, just as the first cancer vaccines were being tested.61,62 The main culprits were considered to be the known immunosuppressive effects of standard therapies, chemotherapy, and radiation. Vaccines were usually administered after enough time had passed from the end of standard therapy to allow immune system recovery. Accumulation of new knowledge that came from detailed analyses of the many failed therapeutic cancer vaccine trials revealed that it was not only the acute immunosuppressive effect of standard therapy that was preventing better efficacy of the vaccines but also the chronic and likely long-term presence of the tumor and its highly organized microenvironment capable of suppressing antitumor effector functions.63 The immune system remained in the state of immune suppression even after the removal of the primary tumor, in part because it had established its own regulatory networks and in part due to the continued presence of tumor metastases. This new information effectively eliminated the predicted “window of opportunity” for therapeutic cancer vaccines. The new awareness of the immunosuppressive tumor microenvironment stimulated several lines of investigation, the primary one being to understand the specific immunosuppressive mechanisms. Many mechanisms were found, some mediated by the tumor via the production of soluble immunosuppressive molecules such as indoleamine-2,3-dioxygenase (IDO) or proinflammatory and immunosuppressive cytokines such as tumor necrosis factor α (TNF-α) and transforming growth factor β (TGF-β) or expression of specific ligands for receptors on antitumor T cells that send inhibitory signals (programmed cell death protein 1 [PD1]/programmed cell death protein ligand 1 [PD-L1]). Other suppressive mechanisms could be ascribed directly to the accumulation and propagation of immunosuppressive immune cells, such as regulatory T cells (Tregs)64 and myeloid-derived suppressor cells (MDSC),65 at the tumor site and in circulation, and tumor-associated macrophages (TAM)66 in tumors. Parallel lines of investigation centered on targeting these negative regulators in the tumor microenvironment

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with specific drugs. By far, the most successful were antibodies that could block specific receptor-ligand interactions (checkpoints) that led to T-cell inhibition. These checkpoint inhibitors included antibodies against cytotoxic T-lymphocyte antigen 4 (CTLA-4), PD-1, PDL-1, and several other inhibitory ligands. By blocking their interaction, they reverse T-cell suppression and allow effective antitumor responses. Several of these antibodies have received FDA approval and are now standard of care for many types of cancer.67 For the first time in immunotherapy and most cancer therapies, there is high frequency of durable tumor regressions, the large percentage of which can already be considered cures. The importance of checkpoint immunotherapy for therapeutic cancer vaccines is the possibility for a combination therapy that is currently successful in animal models and beginning to be explored in the clinic. Therapeutic vaccines that showed little efficacy as monotherapy might help improve patient outcomes when added to checkpoint blockade therapy as a result of the greatly expanded number of antigen-specific T cells that are again responsive to antigen stimulation and thus to a vaccine due to checkpoint blockade.

PROPHYLACTIC VACCINES FOR CANCERS OF NONINFECTIOUS ETIOLOGY Cancer vaccines have always been considered different from infections disease vaccines, and this perceived difference relegated them to the arena of cancer therapy rather than prevention. In part, this was due to the lack of deeper understanding of how antigens are recognized by the immune system, especially by T cells. As long as the term antigen referred to a whole protein or a glycoprotein, only molecules entirely foreign made by a virus or a bacterium were considered safe to use in prophylactic vaccines. Molecules made by a tumor cell were not considered acceptable as they were mostly self. Eliciting effective immunity to such molecules was expected to be difficult due to self-tolerance. If a superior vaccine design were able to break that tolerance, the result was expected to be lifelong autoimmunity. This created the long-held perception that there would be no antigens in cancers without microbial etiology suitable for prophylactic vaccines. However, as soon as it became clear that an antigen referred only to a small piece of a large protein, a short peptide bound in MHC class I or class II molecules presented to T cells by antigen-presenting cells and recognized by T cells on tumor cells, a large universe of potential candidate antigens opened up. As soon as the focus changed from molecules to antigenic peptide epitopes derived from these molecules, the difference between cancer vaccines and pathogen vaccines was erased. If an epitope, a string of 8 to 10 amino acids, is seen for the first time by CD8+ T cells, it should make no difference to that T cell if the peptide was made by a pathogen or by a tumor. Identification of a large number of tumor antigens that contained epitopes recognized by tumor-specific T cells and antibodies showed that even the number of such epitopes on tumor cells would not be that different from the numbers of viral epitopes on infected cells. Extensive characterization of differences between epitopes in normal cells and in tumor cells put forward a large number of candidate antigens that could be used to create safe tumor-specific vaccines.41 Once tumor specificity and safety are shown in vitro and in vivo in genetically engineered animal models, the remaining requirements for an antigen to be considered for a cancer prevention vaccine are its expression at the earliest points in tumor development, tumor dependence on its expression for sustained growth, and low likelihood of outgrowth of antigen-negative variants that can avoid the vaccine-elicited immunity. The last two are also important requirements for therapeutic cancer vaccines, and thus, many of the antigens used in those vaccines have already successfully met these criteria. Increased emphasis is also beginning to be placed on molecules expressed on precancerous lesions.68,69 Shared mutated antigens such as KRAS, which drives development of many human tumors and is mutated very early, even in premalignant lesions, are attractive tumor-specific antigens. KRAS has not performed well as a therapeutic vaccine, but it may be the perfect antigen for including in a preventative vaccine. In addition to the immunosuppressive tumor microenvironment affecting the KRAS therapeutic vaccines, another problem was the very low level of expression of the mutated peptides on the tumor cell surface, which was too low to be recognized by KRAS-specific T cells to activate them to kill the tumor. However, in the setting of prevention where a strong immune response and immune memory can be generated, even low levels of mutated KRAS peptides on the first few premalignant cells might be enough to trigger memory T cells that require less antigen to be activated and allow them to eliminate abnormal cells to prevent tumor development. The expectation would be that prophylactic vaccine- elicited KRAS immunity would be completely safe and directed in the future only to cells harboring an oncogenic mutation. Other shared mutations or gene translocations that predictably drive various tumor types are also good candidates for safe prophylactic vaccines.

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Next in line as prophylactic vaccine antigen candidates are the shared tumor-associated antigens that contain well-known epitopes expressed differently on tumor cells compared to normal cells. Good examples are the extensively studied overexpressed antigens such as HER2/neu, MUC1, hTERT, survivin, WT1, and others listed in Table 36.3. Several of these have already been shown to be abnormally expressed not only on mature tumors but also on the earliest premalignant lesions. Moreover, immune responses to these antigens are found in individuals with premalignant lesions, suggesting that they have already been seen as foreign by the immune system and that boosting this immunity before these lesions progress to cancer may lead to their elimination and de facto cancer prevention. HER2 vaccines have been very effective in preventing spontaneous breast cancer development in HER2 transgenic mice.70 There is also evidence from clinical trials that therapeutic HER2 vaccines have increased immunogenicity and efficacy in very early stages of breast cancer and even more convincing efficacy in the setting of ductal carcinoma in situ (DCIS) where they were able to completely eliminate precancerous lesions.71,72 Similarly, a MUC1 vaccine that has had very low immunogenicity in advanced breast, pancreas, prostate, and colon cancer elicited high levels of immunity and long-term immune memory in patients with a history of premalignant colonic polyps.73 Importantly, this increase in immunogenicity and efficacy is not accompanied by any toxicities that might signal potential autoimmunity. CT antigens and oncofetal antigens have the same potential to be more immunogenic in the absence of cancer and safe. Due to the unique patterns of expression of CT antigens, vaccine-elicited immunity would be presented with its target only if a tumor starts to develop. Considerable effort has been expended in testing many different CT antigens in therapeutic vaccines, but most of them have yet to be tested for expression on precancerous lesions or in preventative vaccines. Limited reports show expression of the flagship CT antigen, NY-ESO-1, on premalignant lesions in the oral cavity, squamous dysplasia, and DCIS. This might very well be the first of the CT antigens to be tested in the clinic for cancer prevention.

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16. Stanley M, Pinto LA, Trimble C. Human papillomavirus vaccines: immune responses. Vaccine 2012;30(Suppl 5):F83–F87. 17. Schiller JT, Lowy DR. Understanding and learning from the success of prophylactic human papillomavirus vaccines. Nat Rev Microbiol 2012;10(10):681–692. 18. Brotherton JML, Bloem PN. Population-based HPV vaccination programmes are safe and effective: 2017 update and the impetus for achieving better global coverage. Best Pract Res Clin Obstet Gynaecol 2018;47:42–58. 19. Cameron RL, Kavanagh K, Cameron Watt D, et al. The impact of bivalent HPV vaccine on cervical intraepithelial neoplasia by deprivation in Scotland: reducing the gap. J Epidemiol Community Health 2017;71(10):954–960. 20. Luostarinen T, Apter D, Dillner J, et al. Vaccination protects against invasive HPV-associated cancers. Int J Cancer 2018;142(10):2186–2187. 21. Bruni L, Diaz M, Barrionuevo-Rosas L, et al. Global estimates of human papillomavirus vaccination coverage by region and income level: a pooled analysis. Lancet Glob Health 2016;4(7):e453–e463. 22. National Vaccine Advisory Committee. Overcoming barriers to low HPV vaccine uptake in the United States: recommendations from the National Vaccine Advisory Committee: Approved by the National Vaccine Advisory Committee on June 9, 2015. Public Health Rep 2016;131(1):17–25. 23. Blanchard TG, Czinn SJ. Identification of Helicobacter pylori and the evolution of an efficacious childhood vaccine to protect against gastritis and peptic ulcer disease. Pediatr Res 2017;81(1–2):170–176. 24. Rupnow MF, Chang AH, Shachter RD, et al. Cost-effectiveness of a potential prophylactic Helicobacter pylori vaccine in the United States. J Infect Dis 2009;200(8):1311–1317. 25. Del Giudice G, Malfertheiner P, Rappuoli R. Development of vaccines against Helicobacter pylori. Expert Rev Vaccines 2009;8(8):1037–1049. 26. Zeng M, Mao XH, Li JX, et al. Efficacy, safety, and immunogenicity of an oral recombinant Helicobacter pylori vaccine in children in China: a randomised, double-blind, placebo-controlled, phase 3 trial. Lancet 2015;386(10002):1457–1464. 27. Cohen JI. Epstein-barr virus vaccines. Clin Transl Immunol 2015;4(1):e32. 28. Dasari V, Bhatt KH, Smith C, et al. Designing an effective vaccine to prevent Epstein-Barr virus-associated diseases: challenges and opportunities. Expert Rev Vaccines 2017;16(4):377–390. 29. Sokal EM, Hoppenbrouwers K, Vandermeulen C, et al. Recombinant gp350 vaccine for infectious mononucleosis: a phase 2, randomized, double-blind, placebo-controlled trial to evaluate the safety, immunogenicity, and efficacy of an Epstein-Barr virus vaccine in healthy young adults. J Infect Dis 2007;196(12):1749–1753. 30. Kanekiyo M, Bu W, Joyce MG, et al. Rational design of an Epstein-Barr virus vaccine targeting the receptorbinding site. Cell 2015;162(5):1090–1100. 31. Hayes CN, Chayama K. Why highly effective drugs are not enough: the need for an affordable solution to eliminating HCV. Expert Rev Clin Pharmacol 2017;10(6):583–594. 32. Pierce BG, Keck ZY, Foung SK. Viral evasion and challenges of hepatitis C virus vaccine development. Curr Opin Virol 2016;20:55–63. 33. Walker CM. Designing an HCV vaccine: a unique convergence of prevention and therapy? Curr Opin Virol 2017;23:113–119. 34. Masavuli MG, Wijesundara DK, Torresi J, et al. Preclinical development and production of virus-like particles as vaccine candidates for hepatitis C. Front Microbiol 2017;8:2413. 35. Wu TT, Qian J, Ang J, et al. Vaccine prospect of Kaposi sarcoma-associated herpesvirus. Curr Opin Virol 2012;2(4):482–488. 36. Gutiérrez G, Rodríguez SM, de Brogniez A, et al. Vaccination against δ-retroviruses: the bovine leukemia virus paradigm. Viruses 2014;6(6):2416–2427. 37. Tebeje BM, Harvie M, You H, et al. Schistosomiasis vaccines: where do we stand? Parasit Vectors 2016;9(1):528. 38. Tang ZL, Huang Y, Yu XB. Current status and perspectives of Clonorchis sinensis and clonorchiasis: epidemiology, pathogenesis, omics, prevention and control. Infect Dis Poverty 2016;5(1):71. 39. Smith KA. Interleukin 2. Annu Rev Immunol 1984;2:319–333. 40. Caux C, Massacrier C, Dezutter-Dambuyant C, et al. Human dendritic Langerhans cells generated in vitro from CD34+ progenitors can prime naive CD4+ T cells and process soluble antigen. J Immunol 1995;155(11):5427– 5435. 41. Finn OJ. Human tumor antigens yesterday, today, and tomorrow. Cancer Immunol Res 2017;5(5):347–354. 42. Srivastava PK, DeLeo AB, Old LJ. Tumor rejection antigens of chemically induced sarcomas of inbred mice. Proc Natl Acad Sci U S A 1986;83(10):3407–3411. 43. Srivastava PK. Neoepitopes of cancers: looking back, looking ahead. Cancer Immunol Res 2015;3(9):969–977.

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44. Tran E, Ahmadzadeh M, Lu YC, et al. Immunogenicity of somatic mutations in human gastrointestinal cancers. Science 2015;350(6266):1387–1390. 45. Levy S, Kon S, Levy R. Somatic mutations in the Ig VH genes of human B cell lymphoma. Acta Paediatr Jpn 1987;29(4):561–565. 46. Finn OJ, Jerome KR, Henderson RA, et al. MUC-1 epithelial tumor mucin-based immunity and cancer vaccines. Immunol Rev 1995;145:61–89. 47. Zarling AL, Polefrone JM, Evans AM, et al. Identification of class I MHC-associated phosphopeptides as targets for cancer immunotherapy. Proc Natl Acad Sci U S A 2006;103(40):14889–14894. 48. Zarling AL, Obeng RC, Desch AN, et al. MHC-restricted phosphopeptides from insulin receptor substrate-2 and CDC25b offer broad-based immunotherapeutic agents for cancer. Cancer Res 2014;74(23):6784–6795. 49. Brentville VA, Metheringham RL, Gunn B, et al. Citrullinated vimentin presented on MHC-II in tumor cells is a target for CD4+ T-cell-mediated antitumor immunity. Cancer Res 2016;76(3):548–560. 50. Dudley ME, Wunderlich JR, Robbins PF, et al. Cancer regression and autoimmunity in patients after clonal repopulation with antitumor lymphocytes. Science 2002;298(5594):850–854. 51. Le Jeune C, Thomas X. Antibody-based therapies in B-cell lineage acute lymphoblastic leukaemia. Eur J Haematol 2015;94(2):99–108. 52. Pardoll DM. Inducing autoimmune disease to treat cancer. Proc Natl Acad Sci U S A 1999;96(10):5340–5342. 53. Evdokimova VN, Butterfield LH. Alpha-fetoprotein and other tumour-associated antigens for immunotherapy of hepatocellular cancer. Expert Opin Biol Ther 2008;8(3):325–336. 54. Hammarström S. The carcinoembryonic antigen (CEA) family: structures, suggested functions and expression in normal and malignant tissues. Semin Cancer Biol 1999;9(2):67–81. 55. Simpson AJ, Caballero OL, Jungbluth A, et al. Cancer/testis antigens, gametogenesis and cancer. Nat Rev Cancer 2005;5(8):615–625. 56. Dunn GP, Old LJ, Schreiber RD. The three Es of cancer immunoediting. Annu Rev Immunol 2004;22:329–360. 57. Galon J, Costes A, Sanchez-Cabo F, et al. Type, density, and location of immune cells within human colorectal tumors predict clinical outcome. Science 2006;313(5795):1960–1964. 58. Finn OJ. Cancer vaccines: between the idea and the reality. Nat Rev Immunol 2003;3(8):630–641. 59. Tan AC, Goubier A, Kohrt HE. A quantitative analysis of therapeutic cancer vaccines in phase 2 or phase 3 trial. J Immunother Cancer 2015;3:48. 60. Kantoff PW, Higano CS, Shore ND, et al. Sipuleucel-T immunotherapy for castration-resistant prostate cancer. N Engl J Med 2010;363(5):411–422. 61. Lai P, Rabinowich H, Crowley-Nowick PA, et al. Alterations in expression and function of signal-transducing proteins in tumor-associated T and natural killer cells in patients with ovarian carcinoma. Clin Cancer Res 1996;2(1):161–173. 62. Schmielau J, Finn OJ. Activated granulocytes and granulocyte-derived hydrogen peroxide are the underlying mechanism of suppression of t-cell function in advanced cancer patients. Cancer Res 2001;61(12):4756–4760. 63. Joyce JA, Fearon DT. T cell exclusion, immune privilege, and the tumor microenvironment. Science 2015;348(6230):74–80. 64. Kitagawa Y, Sakaguchi S. Molecular control of regulatory T cell development and function. Curr Opin Immunol 2017;49:64–70. 65. Gabrilovich DI. Myeloid-derived suppressor cells. Cancer Immunol Res 2017;5(1):3–8. 66. Mantovani A, Marchesi F, Malesci A, et al. Tumour-associated macrophages as treatment targets in oncology. Nat Rev Clin Oncol 2017;14(7):399–416. 67. Topalian SL, Drake CG, Pardoll DM. Immune checkpoint blockade: a common denominator approach to cancer therapy. Cancer Cell 2015;27(4):450–461. 68. Finn OJ. Premalignant lesions as targets for cancer vaccines. J Exp Med 2003;198(11):1623–1626. 69. Spira A, Disis ML, Schiller JT, et al. Leveraging premalignant biology for immune-based cancer prevention. Proc Natl Acad Sci U S A 2016;113(39):10750–10758. 70. Quaglino E, Iezzi M, Mastini C, et al. Electroporated DNA vaccine clears away multifocal mammary carcinomas in her-2/neu transgenic mice. Cancer Res 2004;64(8):2858–2864. 71. Czerniecki BJ, Koski GK, Koldovsky U, et al. Targeting HER-2/neu in early breast cancer development using dendritic cells with staged interleukin-12 burst secretion. Cancer Res 2007;67(4):1842–1852. 72. Sharma A, Koldovsky U, Xu S, et al. HER-2 pulsed dendritic cell vaccine can eliminate HER-2 expression and impact ductal carcinoma in situ. Cancer 2012;118(17):4354–4362. 73. Kimura T, McKolanis JR, Dzubinski LA, et al. MUC1 vaccine for individuals with advanced adenoma of the

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colon: a cancer immunoprevention feasibility study. Cancer Prev Res (Phila) 2013;6(1):18–26.

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37

Cancer Screening Otis W. Brawley and Howard L. Parnes

INTRODUCTION Cancer screening refers to performing a test or examination on an asymptomatic individual. The goal of cancer screening is to prevent death and suffering from the disease in question through early therapeutic intervention. At least four requirements must be met for screening to be efficacious: 1. The disease burden is significant. 2. The natural history of the disease is such that a detectable preclinical phase exists. 3. A test or procedure must detect cancers earlier than if the cancers were detected as a result of the development of symptoms. 4. Treatment initiated earlier as a consequence of screening results in an improved outcome. These requirements are necessary but not sufficient for the test or procedure to be efficacious. A screening test is efficacious when it leads to a decrease in cause-specific mortality. The assumption that early detection improves outcomes can be traced back to the concept that cancer inexorably progresses in a linear fashion from a small, localized, primary tumor to locoregional spread, to distant metastases, and to death. Cancer screening was an element of the “periodic physical examination,” as espoused by the American Medical Association in the 1920s.1 It consisted of palpation to find a mass or enlarged lymph nodes and auscultation to find a rub or abnormal sound. Today, screening has grown to include radiologic testing, measurement of serum markers, and even molecular testing. A positive screening test triggers further diagnostic testing, which might lead to a cancer diagnosis. The intuitive appeal of early detection accounts for the emphasis that has long been placed on screening. However, it is not widely understood that screening tests are always associated with some harm (e.g., anxiety, financial costs), and invasive diagnostic or therapeutic procedures caused by a positive screening test can actually cause substantial harm. Because screening is, by definition, done in healthy people, all early detection tests should be carefully studied and their risk–benefit ratio determined before they are adopted for widespread use. Screening is a public health intervention. However, some do draw a distinction between screening an individual within the doctor–patient relationship and mass screening, a program aimed at screening a large population. The latter may involve advertising campaigns to encourage people to be screened for a particular cancer at a shopping mall, a community center, or a public event such as state fair. Screening can be “opportunistic” or “programmatic.” When screening is opportunistic, a patient sees a healthcare provider who chooses to screen or not to screen. Programmatic screening refers to a standardized approach with algorithms for screening and follow-up as well as recall of patients for regular routine screening with quality control measures. In the United States, programmatic screening is most commonly seen in health maintenance organizations. Programmatic screening is usually more effective.

PERFORMANCE CHARACTERISTICS OF A SCREENING TEST The degree to which a screening test can accurately discriminate between individuals with and without a particular disease is described by its performance characteristics. These include the test’s sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) (Table 37.1). It should be noted that these measures relate to the accuracy of a screening test; they do not provide any information regarding a test’s efficacy or effectiveness.

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Sensitivity and specificity are usually inversely related. For example, as one lowers the threshold for considering a serum prostate- specific antigen level to represent a “positive” screen, the sensitivity of the test increases and more cancers will be detected. This increased sensitivity comes at the cost of decreased specificity (i.e., more men without cancer will have “positive” screenings tests and, therefore, will be subjected to unnecessary diagnostic procedures). Some screening tests, such as mammograms, are more subjective and operator dependent than others. For this reason, the sensitivity and specificity of screening mammography vary among radiologists. For a given radiologist, the lower his or her threshold for considering a mammogram to be suspicious, the higher the sensitivity and lower the specificity will be for that radiologist. However, mammography can have both a higher sensitivity and higher specificity in the hands of a more experienced versus a less experienced radiologist. As opposed to sensitivity and specificity, the PPV and NPV of a screening test are dependent on disease prevalence. PPV is also highly responsive to small increases in specificity. As shown in Table 37.2, given a disease prevalence of 5 cases per 1,000 (0.005), the PPV of a hypothetical screening test increases dramatically as specificity goes from 95% to 99.9% but only marginally as sensitivity goes from 80% to 95%. Given a disease prevalence of only 1 per 10,000 (0.0001), the PPV of the same test is poor even at high sensitivity and specificity. Screening mammography is a better test (higher PPV) for women aged 50 to 59 years than for women aged 40 to 49 years because the prevalence of breast cancer increases with age. TABLE 37.1

Measures of Screening Performance

Disease Status

Screen Test Results

Yes

No

Total

Positive

TP

FP

TP + FP

Negative

FN

TN

FN + TN

Total

TP + FN

FP + TN



TP, true-positive result; FP, false-positive result; FN, false-negative result; TN, true-negative result. Sensitivity is the proportion of persons designated positive by the screening test among all individuals who have the disease.

Specificity is the proportion of persons designated negative by the screening test among all individuals who do not have the disease.

Positive predictive value is the proportion of individuals with a positive screening test who have the disease.

Negative predictive value is the proportion of individuals with a negative screening test who do not have the disease.

TABLE 37.2

Positive Predictive Value Given Varying Sensitivity and Specificity and Prevalence

Sensitivity %

Prevalence 0.005

80

90

95

Specificity %

95

7

8

9



99

29

31

32

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99.9

80

82

83



Sensitivity %

Prevalence 0.0001

80

90

95

Specificity %

95

0.2

0.2

2.0



99

0.8

0.9

0.9



99.9

0.7

8.0

9.0

Positive predictive value (PPV) improves dramatically in response to small changes in specificity. Changes in specificity influence PPV much more than changes in sensitivity. Note the influence of prevalence on PPV. Screening tests do not perform as well in populations with a low prevalence of disease.

ASSESSING A SCREENING TEST Screening is subject to a number of biases that can make it appear efficacious when it really is not. In some instances, the biases can make screening appear efficacious when it actually causes harm. A prospective randomized clinical trial is needed to negate the biases and adequately assess a screening intervention. Lead time bias occurs when screening results in an earlier diagnosis than would have occurred in the absence of screening. As survival is measured from the time of diagnosis, earlier diagnosis, by definition, increases survival. Unless an effective intervention is available, lead time bias has no impact on the natural history of a disease and death will occur at the same time it would have in the absence of early detection (Fig. 37.1).

Figure 37.1 Survival is the time from cancer diagnosis to death. A: Lead time bias occurs when

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screening results in an earlier diagnosis. Without screening, a patient is diagnosed with cancer due to symptoms. B: With screening, the patient is often diagnosed earlier. When screening and treatment do not prolong life, the screened patient can have a longer survival solely due to the earlier diagnosis. The survival increase is pure lead time bias. C: When screening and treatment are beneficial, the patient is diagnosed before the onset of symptoms and the patient lives beyond the point in which death would have occurred without screening.

Figure 37.2 Length bias and cancer screening. The red line is indicative of a fast-growing tumor that is not amenable to regular screening. The blue line is indicative of a fast-growing tumor that can be diagnosed by screening or later by symptoms; death may possibly be prevented by treatment. The green line is a slower growing but potentially deadly cancer that can be detected by symptoms or several screenings and treated, possibly preventing death. The orange line is indicative of a very slow growing tumor that would never cause death and would never need treatment despite being screen detected. This is classic overdiagnosis. Length bias is a function of the biologic behavior of a cancer. Slower growing, less aggressive cancers are more likely to be detected by a screening test compared to faster growing cancers, which are more likely to be diagnosed due to the onset of symptoms between scheduled screenings (interval cancers). Length bias has an even greater effect on survival statistics than lead time bias (Fig. 37.2). Overdiagnosis is an extreme form of length bias and represents pure harm. It refers to the detection of tumors, often through highly sensitive modern imaging modalities and other diagnostic tests, that fulfill the histologic criteria for malignancy but are not biologically destined to harm the patient (see Fig. 37.2). There are two categories of overdiagnosis: the detection of histologically defined “cancers” not destined to metastasize or harm the patient and the detection of cancers not destined to metastasize or cause harm in the life span of the specific patient. The importance of this second category is illustrated by the widespread practice in the United States of screening elderly patients with limited life expectancies and who are thus unlikely to benefit from early cancer diagnosis. Virtually every screening test is a balance between known harms and potential benefits. The most important risk of screening is the detection and subsequent treatment of a cancer that would never have come to clinical detection or harmed the patient in the absence of screening (i.e., overdiagnosis). This can lead to unnecessary treatment. Overdiagnosis occurs with many malignancies, including lung, breast, prostate, renal cell, and thyroid cancer and melanoma.2 Neuroblastoma provides one of the most striking examples of overdiagnosis.3 Urine vanillylmandelic acid (VMA) testing is a highly sensitive screening test for detection of this pediatric disease. After screening programs in Germany, Japan, and Canada showed marked increases in the incidence of this disease without a concomitant decline in mortality, it was noticed that nearby areas that did not screen had similar death rates with lower

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incidence.3,4 It is now appreciated that screen-detected neuroblastoma has a very good prognosis with minimal or no treatment. Many actually regress spontaneously. Overdiagnosis of thyroid cancer is also common. A thyroid screening program using ultrasound was implemented in South Korea in the mid 1990s. By 2011, the rate of thyroid cancer diagnosis was 15 times that observed in 1993. Thyroid cancer mortality rates continued to remain stable. The overwhelming majority of these tumors were less than 20 mm in size. Stage shift (i.e., cancer diagnosis at an earlier stage than would have occurred in the absence of screening) is necessary, but not sufficient, for a screening test to be efficacious in terms of reducing mortality. Both lead time bias and length bias contribute to this phenomenon. Although it is tempting to speculate that diagnosis at an earlier stage must confer benefit, it is not necessarily the case. For example, a substantial proportion of men treated with radical prostatectomy for what appears to be localized prostate cancer relapse after undergoing surgery due to unrecognized micrometastatic disease. Conversely, some men who are treated with definitive therapy would never have gone on to develop metastatic disease in the absence of treatment. Selection bias occurs when enrollees on a clinical study differ from the general population. In fact, people who voluntarily participate in clinical trials tend to be healthier than the general population, perhaps due to a greater interest in health and health-care research. Screening studies also tend to enroll individuals who are healthier than the general population. This so-called healthy volunteer effect5,6 can introduce a powerful bias if not adequately controlled for by randomization procedures.

Assessing Screening Outcomes The primary goal of cancer screening is to reduce mortality from the disease in question (a reduction in diseasespecific mortality). Screening studies generally do not have sufficient statistical power to assess the impact of screening for a specific malignancy on overall mortality. Lung cancer screening provides an exception to this rule (as discussed later in this chapter). As discussed earlier, the fact that a screening test increases the percentage of people diagnosed with early-stage cancer and decreases the percentage of patients diagnosed with late-stage cancer (stage shift) is not equivalent to proof of mortality reduction. Further, due to the healthy volunteer effect, case-control and cohort studies cannot provide definitive evidence of mortality benefit. Prospective randomized clinical trials are required to address this issue. In such trials, volunteers are randomized to be screened or not and are then followed over time to determine if there is a difference in disease-specific or overall mortality. A reduction in mortality rate or in the risk of death is often stated in terms of relative risk. However, this method of reporting can be misleading. It is preferable to report both the relative and absolute reduction in mortality. For example, the European Randomized Study of Screening for Prostate Cancer (ERSPC) found that screening reduced the relative risk of prostate cancer death by 20%. However, this translates into one prostate cancer death averted per 1,000 men screened (5 prostate cancer deaths per 1,000 men not screened versus 4 prostate cancer deaths per 1,000 men screened) and a relatively modest lifetime reduction in the absolute risk of prostate cancer death of only 0.6% (i.e., from 3.0% to 2.4%).7 A reduction in mortality as demonstrated in a prospective randomized clinical trial is the gold standard for demonstrating efficacy of a screening intervention. Even prospective, randomized trials can have serious methodologic shortcomings. For example, imbalances caused by flaws in the randomization scheme can prejudice the outcome of a trial. Other flaws include so-called drop-in, also known as contamination, in which some participants on the control arm get the intervention. Patients on the intervention arm may also drop out of the study. Both drop-ins and drop-outs reduce the statistical power of a clinical trial. Statistical power is an estimate of a trial’s ability to find the true answer. In the United States, it is now considered standard to obtain informed consent before randomization takes place. However, there are widely cited European studies in breast and prostate cancer screening that randomized participants from rosters of eligible subjects such as census lists. In these trials, informed consent is obtained after randomization and only among those randomized to the screening arm of the study. Those randomized to the control arm are not contacted and, indeed, do not know they are in a clinical trial. They are followed through national death registries. Although these studies are analyzed on an intent-to-screen basis, this method can still introduce bias. For example, only patients on the intervention arm have access to the screening facility and staff for counseling and treatment if diagnosed, and those in the control group are more likely to be treated in the community as opposed to high-volume centers of excellence. In the prostate cancer studies, men in the control arm were less likely to be treated with surgery and more likely to be treated with hormones alone compared to those on the screened arm. The study arms also tend to differ in their knowledge of the disease, which may

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contribute to an overestimate of the benefits of a screening test.8 Even when screening has a net mortality benefit, there can be considerable harm. Treatment can cause emotional and physical morbidity and even death.9 For example, in a randomized trial of spiral lung computed tomography (CT), approximately 27,000 current smokers and former smokers were given three annual low-dose CT scans. Nearly 40% had a “positive” screening CT necessitating further testing. Approximately 1,000 subsequently underwent invasive diagnostic procedures, and 16 deaths were reported within 60 days of the invasive procedure.10 It is not known how many of these deaths were directly related to the screening. Efficacy is best thought of as “Can the test lead to interventions that prevent deaths?” Effectiveness is best thought of in terms of “How well does the test work when looking at large groups in the real world?” The lung screening study cited earlier shows that screening is efficacious when done in 30 of the finest hospitals in the United States. Participants volunteered for the trial. Screening might not be as effective when disseminated to a larger population and clinics in the broader community. It can be dangerous to extrapolate estimates of benefit from one population to another. In particular, studies showing that a radiographic test is beneficial to average-risk individuals may not mean that it is beneficial to a population at high risk and vice versa. For example, women at high risk for breast cancer due to an inherited mutation of a DNA repair gene such as BRCA1 or BRCA2 may be at higher risk for radiation-induced cancer from mammography compared to the general population, and a screening test (e.g., spiral lung CT) shown to be efficacious in a high-risk population of heavy smokers may result in net harm if applied to a low- or average-risk population.

SCREENING GUIDELINES AND RECOMMENDATIONS A number of organizations develop cancer screening recommendations or guidelines. These organizations use varying methods. The National Academy of Medicine (formerly known as the Institute of Medicine) has released two reports to establish standards for developing trustworthy clinical practice guidelines and conducting systematic evidence reviews that serve as their basis.11,12 The U.S. Preventive Services Task Force (USPSTF) and the American Cancer Society (ACS) are two organizations that issue widely used cancer guidelines. Both use methods that comply with National Academy of Medicine standards. The USPSTF is a panel of experts in prevention and evidence- based medicine.13 They are primary care providers specializing in internal medicine, pediatrics, family practice, gynecology and obstetrics, nursing, and health behavior. The task force process begins by conducting an extensive structured scientific evidence review. The task force then develops recommendations for primary care clinicians and health-care systems. They adhere to some of the highest standards for recommending a screening test. They are very much concerned with the question, “Does the evidence supporting a screening test demonstrate that the benefits outweigh its harms?” The ACS guidelines date back to the 1970s. The current process for making guidelines involves commissioning academics to do an independent systematic evidence review. A single generalist group digests the evidence review, listens to public input, and writes the guidelines. The ACS panel tries to clearly articulate the benefits, limitations, and harms associated with a screening test.14

BREAST CANCER SCREENING Mammography, clinical breast examination (CBE) by a health-care provider, and breast self-examination have long been advocated for the early detection of breast cancer.15 In recent years, ultrasound, magnetic resonance imaging (MRI), and other technologies have been added to the list of proposed screening modalities. Mammographic screening was first advocated in the 1950s. The Health Insurance Plan (HIP) study was the first prospective, randomized clinical trial to formally assess its value in reducing death from breast cancer. In this study, started in 1963, approximately 61,000 women were randomized to three annual mammograms with CBE versus no screening, the standard practice at that time. HIP first reported that the three mammograms reduced breast cancer mortality by 30% at about 10 years after study entry. With 18 years of follow-up, those in the screening arm had a 25% lower breast cancer mortality rate.15 Nine additional prospective randomized studies have been published (Table 37.3). These studies provide the basis for the current consensus that screening women 40 to 75 years of age reduces the relative risk of breast cancer death by 10% to 25%. Collectively, the studies do demonstrate that the risk–benefit ratio is more favorable

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for women aged 60 to 69 years versus those aged 50 to 59 years. Mammography has also been shown to be operator dependent, with better performance characteristics (higher sensitivity and specificity and lower falsepositive rates) reported by high-volume centers. It is important to note that each of these studies has some flaws and limitations. They vary in the questions asked and their findings. In some, randomization methods were suboptimal, others reported varying numbers of participants over the years, and still others had substantial contamination (drop-ins). Perhaps more importantly, most trials were started and concluded before the widespread use of more advanced mammographic technology, before the modern era of adjuvant therapy, and before the advent of targeted therapy. To date, no study has shown that breast self-examination (BSE) decreases mortality. BSE has been studied in two large randomized trials. In one, approximately 266,000 Chinese women were randomized to receive intensive BSE instruction with reinforcements and reminders compared to a control group receiving no instruction on BSE. At 10 years of follow-up, there was no difference in mortality, but the intervention arm had a significantly higher numbers of diagnosed benign breast lesions and breast biopsies preformed. In the second study, 124,000 Russian women were randomized to monthly BSE versus no BSE. There was no difference in mortality rates, despite the BSE group having a higher proportion of early-stage tumors and a significant increase in the proportion of cancer patients surviving 15 years after diagnosis. TABLE 37.3

The Prospective Randomized Controlled Trials of Breast Cancer Screening



Breast Cancer Death (n)

Person-Years (n)

Followup (years)

Screen

Control

Screen

Control

RR

Trial

Year

Age Group

95% CI

HIP15,167

1963

40–60

18

180

236

483,275

487,164

0.77

0.63– 0.93

MMST1168

1976

45–69

19

161

198

360,000

362,000

0.82

0.66– 1.01

Two county25,169,170,171

1977

40–49

29

351

367

1,632,492

1,200,887

0.70

0.61– 0.81

Edinburgh172

1979

45–64

14

156

167

301,155

276,363

0.86

0.69– 1.07

CNBSS-1 and CNBSS-224,173

1980

40–59

25

180

171

968,676

968,432

1.05

0.85– 1.30

Stockholm174

1981

40–64

11

66

45

473,153

239,460

0.74

0.51– 1.08

Gothenburg175

1982

39–59

10

63

112

237,963

324,895

0.77

0.56– 1.05

United Kingdom Age Trial176,177

1991

40–41

17

83

219

532,747

1,058,322

0.75

0.58– 0.97

HIP, Health Insurance Plan; MMST1, Malmö Mammographic Screening Trial 1; CNBSS, Canadian National Breast Screening Study.

There is little evidence to support the use of ultrasound as an initial screening test. Ultrasonography is used in the diagnostic evaluation of a breast mass identified by palpation or mammography.16 MRI is used for screening women with elevated breast cancer risk due to BRCA1 and BRCA2 mutations, LiFraumeni syndrome, Cowden disease, or a very strong family history. MRI is more sensitive, but less specific, than mammography, leading to a high false-positive rate and more unnecessary biopsies, especially among young women.17 The impact of MRI breast screening on breast cancer mortality has not yet been determined.

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Effectiveness of Breast Cancer Screening Breast cancer screening was associated with a dramatic increase in the incidence of invasive breast cancer and ductal carcinoma in situ. At the same time, there has been a dramatic decrease in breast cancer mortality rates. However, in the United States and Europe, incidence-by-stage data show a dramatic increase in the proportion of early-stage cancers without a concomitant decrease in the incidence of regional and metastatic cancers.8 These findings are at odds with the clinical trials data and raise questions regarding the extent to which early diagnosis is responsible for declining breast cancer mortality rates.18 The discrepancy between the magnitude of the increase of early disease and the decrease of late-stage cancer and cancer mortality suggests that a proportion of invasive breast cancers diagnosed by screening represents overdiagnosis. Some estimate that up to 50% of breast cancers detected by screening mammography are overdiagnosed cancers. In an exhaustive review of the screening literature, a panel of experts concluded that overdiagnosis does exist and estimated it to be 11% to 19% of invasive breast cancers diagnosed by screening.19 The risk of overdiagnosis is greatest at the first screen and varies with patient age, tumor type, and grade of disease.2 Although randomized clinical trials remain the gold standard for assessing the benefits of a clinical intervention, they cannot take into account the improvements in both treatment and patient awareness that have occurred over time. A confounding factor with regard to the mortality benefits of breast cancer screening is the improvement that has occurred in breast cancer treatment over time. Observational and modeling studies can provide important, complementary information. The Cancer Intervention and Surveillance Modeling Network (CISNET) supported by the National Cancer Institute (NCI) has estimated that two-thirds of the observed breast cancer mortality reduction is attributable to modern therapy, and about a third is due to screening.20,21 Mammography, like all screening tests, is more efficient (higher PPV) for detection of disease in populations with higher disease prevalence (see Table 37.2). Experts agree that large-scale screening is inappropriate among women younger than 40 years because of its low prevalence. Experts disagree about the utility of screening women in their 40s, even though most conclude that regular mammography reduces breast cancer mortality in women aged 40 to 74 years, with the benefits being most significant for women aged 50 to 74 years.22 Mammography is less optimal in women aged 40 to 49 years compared to older women because: Younger women have a lower incidence of the disease, meaning they are less likely to have breast cancer compared to older women. A larger proportion have increased breast density, which can obscure lesions (lower sensitivity). Younger women are more likely to develop aggressive, fast-growing breast cancers that are diagnosed due to symptoms between regular screening visits.23 In the HIP randomized controlled trial, women who entered at aged 40 to 49 years had a mortality benefit at 18 years of follow-up. However, to a large extent, the mortality benefit was driven by breast cancers diagnosed after they reached age 50 years.15 The Canadian screening trial suggests mammography and CBE do not decrease risk of death for women aged 40 to 49 years and mammography adds nothing to CBE for women aged 50 to 59 years.24 On the other extreme, the Kopparberg Sweden study suggests that mammography is associated with a 32% reduction in risk of death for women aged 40 to 74 years.25 A USPSTF meta-analysis of eight large randomized trials suggested a 15% relative reduction in mortality (relative risk [RR], 0.85; 95% confidence interval [CI], 0.75 to 0.96) as a result of mammography screening in women aged 40 to 49 years after 11 to 20 years of follow-up. This is equivalent to a number needed to invite to screening of 1,904 over 10 years to prevent one breast cancer death.26 The decision to participate in a mammography screening program should involve a balancing of the benefits and harms. The disadvantages of mammography screening include overdiagnosis, false-positive tests, falsenegative tests, and the possibility of radiation-induced breast cancer. False-positive screening tests lead to substantial inconvenience and anxiety in addition to unnecessary invasive biopsies with their attendant complications. In the United States, approximately 10% of all women screened for breast cancer are called back for additional testing, and less than half will be diagnosed with breast cancer. The risk of a false-positive mammogram is greater for women younger than 50 years.27 Indeed, among women aged 40 years starting annual mammography, more than half will have a false-positive exam by age 49 years. In an effort to decrease the false-positive rate, some have suggested screening every 2 years rather than yearly. Comparing biennial with annual screening, the CISNET model consistently shows that biennial screening of women aged 40 to 70 years only marginally decreases the number of lives saved while halving the false-positive

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rate.23 Notably, the Swedish two-county trial, which had a planned 24-month screening interval (the actual average interval was 33 months), reported one of the greatest reductions in breast cancer mortality among the randomized clinical trials conducted to date. False-negative tests delay diagnosis and provide false reassurance. They are more common in younger women and in women with dense breasts.28,29 Certain histologic subtypes are also more difficult to see on mammogram. Mucinous and lobular tumors and rapidly growing tumors tend to blend in with normal breast architecture.30 A typical screening mammogram provides approximately 4 mSv of radiation. It has been estimated that annual mammography will cause up to one breast cancer per 1,000 women screened from age 40 to 80 years. Radiation exposure at younger ages causes a greater risk of breast cancer.31 There is also concern that ionizing radiation from mammography might disproportionately increase the breast cancer risk for women with certain BRCA1 or BRCA2 mutations, as these mutations are related to DNA repair.32

Screening Women at Higher Risk There is interest in creating risk profiles as a way of reducing the inconveniences and harms of screening. It might be possible to identify women who are at greater risk of breast cancer and refocus screening efforts on those most likely to benefit. Risk factors for breast cancer include the following: Extremely dense breasts on mammography or a first-degree relative with breast cancer are each associated with at least a twofold increase in breast cancer risk. Prior benign breast biopsy, second-degree relatives with breast cancer, and heterogeneously dense breasts are each associated with a 1.5- to 2.0-fold increase in risk. Current oral contraceptive use, nulliparity older than age 30 years, or age at first birth of 30 years or older is associated with a 1- to 1.5-fold increase in risk.33 Importantly, these are risk factors for breast cancer diagnosis, not breast cancer mortality. Few studies have assessed the association between these factors and death from breast cancer; indeed, reproductive factors and breast density have been shown to have limited influence on breast cancer mortality.34,35 Genetic screening for BRCA1 and BRCA2 mutations and other markers has identified a group of women at high risk for breast cancer. Unfortunately, when to begin and the optimal frequency of screening have not been defined. Mammography is less sensitive at detecting breast cancers in women carrying BRCA1 and BRCA2 mutations, possibly because such cancers occur in younger women, in whom mammography is known to be less sensitive. MRI screening is more sensitive than mammography in women at high risk, but specificity is lower. As noted earlier, MRI is associated with both an increase in false-positive results and an increase in the detection of smaller cancers, which are more likely to be biologically indolent. The impact of MRI on breast cancer mortality with or without concomitant use of mammography has not been evaluated in a randomized controlled trial. It is well established that mammogram sensitivity is lower in women with heterogeneously dense or very dense breasts.23,34 Density obscures the interpretation of the x-ray. At this time, there are no clear guidelines regarding whether or how screening algorithms should take breast density into account. It has yet to be determined whether supplemental imaging reduces breast cancer mortality in women with increased breast density. Although it continues to be strongly advocated by some, systematic reviews have concluded that the evidence is insufficient to recommend for or against this approach.36 There are also a number of barriers to supplemental imaging, including inconsistent insurance coverage, lack of availability in many communities, concerns about cost-effectiveness, particularly regarding MRI, and the increased false-positive rate associated with supplemental imaging leading to unnecessary biopsies.37 The American College of Radiology Imaging Network (ACRIN)/NCI 666 trial assessed mammography and breast ultrasound screening women with increased breast density, and if either test was positive, the patient was referred for breast biopsy.38 The radiologists performing the ultrasounds were not aware of the mammographic findings. Mammography detected 7.6 cancers per 1,000 women screened; ultrasound increased the cancer detection rate to 11.8 per 1,000. However, the PPV for mammography alone was 22.6%, whereas the PPV for mammography with ultrasound was only 11.2%.

Newer Screening Technologies Newer technologies may improve screening accuracy for women with dense breasts. Full-field digital

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mammography (FFDM) produces a flat two-dimensional image. It appears to result in less false positives compared to conventional mammography. This could reduce the number of women needing supplemental imaging and biopsies.27 Digital breast tomosynthesis (DBT) uses x-rays and a digital detector to generate crosssectional images of the breasts. Data are limited, but compared to mammogram, DBT appears to offer increased sensitivity and a reduction in the recall rates.39 The Tomosynthesis Mammographic Imaging Screening Trial is an ongoing NCI-sponsored randomized prospective screening trial comparing the diagnostic accuracy of screening for breast cancer with threedimensional DBT plus two-dimensional FFDM versus FFDM alone. It is powered to determine if DBT is superior to FFDM in reducing the rate of advanced cancer. Molecular breast imaging is a technique approved by the U.S. Food and Drug Administration (FDA) but not in widespread use.40 It uses intravenous 99mTc-sestamibi and gamma cameras to image the breast. It is very promising as an adjunct to mammography and could be a replacement. It may be better for screening dense breasts. Note that because it is a nuclear medicine image, it shows cellular metabolism as opposed to structure, which is shown by x-ray and MRI imaging. Abbreviated (fast) MRI takes 3 to 5 minutes to image the breast.41 It is more feasible, less costly, and more accessible than conventional MRI of the breast.

Ductal Carcinoma In Situ The incidence of noninvasive ductal carcinoma in situ (DCIS) has increased more than fivefold since 1970 as a direct consequence of widespread screening mammography.42 DCIS is a heterogeneous condition with low- and intermediate-grade lesions taking decades to progress if they progress at all. Clinical trials are using genomic analysis in an attempt to predict those that can be observed versus those that need aggressive treatment. Outside of a clinical trial, women with DCIS are uniformly subjected to treatment, even though there is little evidence that early detection and aggressive treatment of low- and intermediate-grade DCIS reduces breast cancer mortality. The standard of care for all grades of DCIS is lumpectomy with radiation or mastectomy, followed by tamoxifen for 5 years. Interestingly, patterns of care studies indicate that mastectomy rates are increasing and that women are more often choosing double mastectomy for treatment of DCIS.43,44 Genomic characterization will hopefully lead to the identification of a subset of noninvasive cancers that can be treated less aggressively or even observed.

Breast Screening Recommendations The ACS breast cancer screening guideline for women at average risk states the following: Women should undergo regular screening mammography starting at age 45 years. Women aged 45 to 54 years should be screened annually. Women should have the opportunity to begin annual screening between the ages of 40 and 44 years. Women aged 55 years and older should transition to biennial screening or have the opportunity to continue screening annually. Women should continue screening mammography as long as their overall health is good and they have a life expectancy of 10 years. The ACS does not recommend CBE or BSE because of the paucity of data supporting them. The USPSTF, the American College of Physicians, and the Canadian Task Force on Periodic Health Examination recommend routine biennial screening beginning at age 50 years.26,45,46 For women aged 40 to 49 years, these groups advise physicians enter into a discussion with the patient. The physician and patient should take into account individual risks and concerns before deciding to screen. The USPSTF statement specifically states the following: “The decision to start screening mammography in women prior to age 50 years should be an individual one. Women who place a higher value on the potential benefit compared to potential harms may choose to begin biennial screening between the ages of 40 and 49 years.” Screening is best offered in an organized screening program with quality assurance.47 Women should be informed of the benefits, limitations, and harms associated with breast cancer screening. Mammography will not detect all breast cancers; some breast cancers detected with mammography may still have poor prognosis. The harms associated with breast cancer screening also include the potential for false-positive results, causing substantial anxiety. When abnormal findings cannot be resolved with additional imaging, a biopsy is required to

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rule out the possibility of breast cancer. The majority of biopsies are benign. Finally, some breast cancers detected by mammography may be biologically indolent, meaning they would not have caused a problem or have been detected in a woman’s lifetime had she not undergone mammography. The ACS has issued guidelines for women at high risk. Annual screening with mammography and MRI starting at age 30 years is recommended for women who Are known or likely carriers of a BRCA mutation Have another high-risk genetic syndrome (e.g., Cowden syndrome, Li-Fraumeni syndrome, Peutz-Jeghers syndrome, ataxia-telangiectasia) Have been treated with radiation to the chest for Hodgkin disease Have an approximately 20% to 25% or greater lifetime risk of breast cancer based on specialized breast cancer risk estimation models48

GASTROINTESTINAL TRACT CANCERS Colon Cancer Screening Colorectal cancer screening involves either stool testing for blood or DNA associated with polyps or cancer or structural examinations looking for polyps or early cancers. Screening with the rigid sigmoidoscope dates back to the late 1960s. The desire to examine the entire colon led to the use of barium enema and development of fecal occult blood tests (FOBTs). With the development of fiber optics, flexible sigmoidoscopy and, later, colonoscopy were employed. Today, FOBT, stool DNA testing, flexible sigmoidoscopy, colonoscopy, and CT colonography and occasionally barium enema are all used in colorectal cancer screening.49 MRI colonoscopy is in development. Screening examination of the colon and rectum can not only find cancer early but can also find precancerous polyps. Randomized trials have demonstrated that endoscopic polypectomy reduces the incidence of colorectal cancer by about 20%.50–52 FOBT was the first colorectal screening test studied in a prospective randomized clinical trial. The Minnesota Colon Cancer Control Study randomized 46,551 adults to one of three arms: annual FOBT, biennial screening, or usual care. A rehydrated guaiac test was used. With 13 years of follow-up, the annual screened arm had a 33% relative reduction in colorectal cancer mortality compared to the usual care group.53 At 18 years of follow-up, the biennially screened group had a 21% reduction in colorectal cancer mortality.54 This study would subsequently show that annual stool blood testing was associated with a 20% reduction in colon cancer incidence.50 These results were confirmed by two other randomized trials.55,56 A reduction in colon cancer–specific mortality persisted in the Minnesota trial through 30 years of follow-up. Overall mortality was not affected. Rehydration increases the sensitivity of FOBT at the expense of lowering specificity.57 Indeed, rehydrated specimens have a very high false-positive rate. Overall, 1% to 5% of FOBTs are positive, but only 2% to 10% of patients with positive tests have cancer. Fecal immunochemical tests (FIT) are stool tests that react to human hemoglobin and do not react to hemoglobin in dietary products. They appear to have higher sensitivity and specificity for colorectal cancer when compared to nonrehydrated FOBT tests.58 Fecal DNA testing is an emerging modality. These tests look for DNA sequences specific to colorectal polyps and colorectal cancer. They may have increased sensitivity and specificity compared to FOBT. The one currently marketed stool DNA test incorporates FIT. Flexible sigmoidoscopy is, of course, limited to examination of the rectum and sigmoid colon. It is estimated that flexible sigmoidoscopy can find 60% to 80% of cancers and polyps found by colonoscopy. A prospective randomized trial of once-only flexible sigmoidoscopy demonstrated a 23% reduction in colorectal cancer incidence and a 31% reduction in colorectal cancer mortality after a median follow-up of 11.2 years.59 In the NCI’s Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO), there was a 21% reduction in colorectal cancer incidence and a 26% reduction in colorectal cancer mortality with two sigmoidoscopies done 3 to 5 years apart compared with the usual care group after a median follow-up of 11.9 years.52 In both studies, there was no effect on proximal (i.e., right and transverse colon) lesions due to the limited reach of the scope.60 In two meta-analyses of five randomized controlled trials of sigmoidoscopy, there was an 18% relative reduction in colorectal cancer incidence and a 28% relative reduction in colorectal cancer mortality.61,62 Participants ranged in age from 50 to 74 years. Follow-up ranged from 6 to 13 years.

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Colonoscopy has become the preferred screening method in the United States, although there have been no prospective, randomized trials of colonoscopy screening. One can also make the argument that the sigmoidoscopy studies indirectly support the efficacy of colonoscopy screening, although it can also be argued that embryologic and epidemiologic evidence indicates that the right and left colon are biologically distinct and, therefore, the mortality benefits from sigmoidoscopy do not constitute proof that colonoscopy would similarly reduce mortality from proximal colon lesions. A positive FOBT, FIT, fecal DNA test, or sigmoidoscopy warrants a follow-up diagnostic colonoscopy. Perhaps, the best support for colonoscopy screening is indirect evidence from the Minnesota Colon Cancer Control Study, which required that all participants with a positive stool blood test have diagnostic imaging of the entire colon. In the Minnesota study, more than 40% of those screened annually eventually received a colonoscopy. Quality of the colonoscopic examination is an issue. In studies involving repeat colonoscopy by a second physician, 21% of all adenomas were missed, including 26% of 1- to 5-mm adenomas and 2% of adenomas 10 mm or more in length.63 Other limitations of colonoscopy include the inconvenience of the bowel preparation and the risk of bowel perforation (approximately three in 1,000 procedures, overall, with nearly all of the risk among patients who undergo colonoscopic polypectomy). The cost of the procedure and limited number of physicians who can do the procedure are also of concern. CT colonography or virtual colonoscopy allows a physician to visually reproduce the endoscopic examination on a computer screen. CT colonography involves the same preparation as a colonoscopy but is less invasive. It might have a higher compliance rate. In experienced hands, the sensitivity of CT colonography for the detection of polyps ≥ 6 mm appears to be comparable to that of colonoscopy. Compared to optical colonoscopy, quality is easier to measure as the images are saved and can be reviewed. In a meta-analysis of 30 studies, two-dimensional and three-dimensional CT colonography performed equally well.64 The disadvantages of CT colonography include the fact that it does require a colonic prep and a finding on CT requires a follow-up diagnostic colonoscopy. The rate of extracolonic findings of uncertain significance is high (100 cancer predisposition genes, mutations in which cause moderate to high cancer risk, and most of which are not presently associated with named syndromes. The number of cancer syndromes, cancer predisposition genes, and approaches to genetic testing is growing rapidly. Additionally, the use of tumor (somatic) genetic testing to guide treatment of an individual tumor is becoming mainstream as a result of the precision medicine initiative.4 The opportunities and challenges that have arisen due to these developments are discussed in this chapter. Advertisements by genetic testing companies bill genetic testing as a simple process that can be carried out by health-care professionals with no training in this area; however, there are many genes involved in cancer, the interpretation of the test results is often complicated, the risk of result misinterpretation is great and associated with potential liability, and the emotional and psychological ramifications for the patient and family can be powerful.5–7 It is because of these complexities that multiple professional guidelines recommend that multigene panel testing takes place in the context of pre- and posttest counseling by a genetics expert.8–11 A few hours of training by a company generating a profit from the sale of these tests does not adequately prepare providers to offer their own genetic counseling and testing services.9 Furthermore, the delegation of genetic testing responsibilities to office staff, mammography technicians, and other providers is alarming and likely presents a huge liability for these ordering physicians, their practices, and their institutions.13–15 Providers should proceed with caution before taking on the role of primary genetic counselor for their patients. Counseling about hereditary cancers differs from traditional genetic counseling in several ways. Clients seeking cancer genetic counseling are rarely concerned with reproductive decisions, which are often the primary focus in traditional genetic counseling, but are instead seeking information about their own and other relatives’ chances of developing cancer.2 Additionally, the risks given are not absolute but change over time as the family and personal history changes and the patient ages. The risk reduction options available are often radical (e.g., chemoprevention or prophylactic surgery) and are not appropriate for every patient at every age. The surveillance and management plan must be tailored to the patient’s age, childbearing status, menopausal status, risk category, ease of screening, and personal preferences and will likely change over time with the patient. In most instances, the typical nondirective approach often associated with genetic counseling in the prenatal setting is replaced with

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tailored recommendations for the patient and his or her family. The ultimate goal of cancer genetic counseling is to help the patient reach the decision best suited to his or her personal situation, needs, and circumstances. There are now a significant number of referral centers and individual counselors across the country specializing in cancer genetic counseling, and the numbers are growing. However, some experts insist that the only way to keep up with the overwhelming demand for counseling will be to educate more physicians and nurses in cancer genetics. The feasibility of adding another specialized and time-consuming task to the clinical burden of these professionals is questionable, particularly with average patient encounters of 19.5 and 21.6 minutes for general practitioners and gynecologists, respectively.16,17 A more practical goal is to better educate clinicians in the area of risk assessment so that they can screen their patient populations for individuals at high risk for hereditary cancer and refer them on to comprehensive counseling and testing programs. Access to genetic counseling has improved significantly because there are now Internet, phone, and satellite-based telemedicine services available (Table 38.1), with many major health insurance companies now covering these services18–20 and several requiring them.21 TABLE 38.1

How to Find a Genetic Counselor for Your Patient American Board of Genetic Counselors https://abgcmember.goamp.com/Net/ABGCWcm/Find_Counselor/ABGCWcm/PublicDir.aspx? hkey=0ad511c0-d9e9-4714-bd4b-0d73a59ee175 http://bit.ly/1kzTbk9 Directory of board-certified genetic counselors InformedDNA www.informeddna.com (800) 975-4819 A nationwide network of independent genetic counselors that use telephone and Internet technology to bring genetic counseling to patients and providers. Covered by many insurance companies Gene Matters Genematters.com 1-866-741-5331 A telehealth genetic counseling company providing one-on-one telephone counseling for genetic conditions, including DTC testing. Covered by many insurance companies National Society of Genetic Counselors www.nsgc.org (312) 321-6834 Click “Find a Genetic Counselor” button for a listing of genetic counselors in your area who specialize in cancer and DTC testing. National Cancer Institute Cancer Genetics Services Directory www.cancer.gov/cancertopics/genetics/directory (800) 4-CANCER A free service designed to locate providers of cancer risk counseling and testing services DTC, direct-to-consumer.

WHO IS A CANDIDATE FOR CANCER GENETIC COUNSELING? Only 5% to 10% of most cancer types are thought to be caused by single pathogenic variants within autosomal dominantly inherited cancer predisposition genes.22 Several hereditary cancer syndromes are autosomal recessive, and considerations of these syndromes in risk assessment, counseling, and informed consent are discussed further.23 The key for clinicians is to determine which patients are at greatest risk to carry a hereditary pathogenic variant. There are several critical indications that signal a cancer may be hereditary (Table 38.2). The first is early age of cancer onset. This indication, even in the absence of a family history, is associated with an increased frequency of germline pathogenic variants in many types of cancers.24 The second indication is the presence of the

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same cancer in multiple affected relatives on the same side of the pedigree. These cancers do not need to be of similar histologic type in order to be caused by a single pathogenic variant. The third indication is the constellation of specific cancers known to be caused by pathogenic variants in a single gene in one family (e.g., breast/ovarian/pancreatic/prostate [Gleason score ≥7 or metastatic] cancer or colon/uterine/ovarian cancers). The fourth indication is the occurrence of multiple primary cancers in one individual. This includes multiple primary breast or colon cancers as well as a single individual with separate cancers known to be caused by pathogenic variants in a single gene (e.g., breast and ovarian cancer in a single individual). Ethnicity also plays a role in determining who is at greatest risk to carry a pathogenic variant in a cancer predisposition gene. Individuals of Jewish ancestry are at increased risk to carry three specific pathogenic BRCA1/BRCA2 variants.25 The presence of specific types of tumors—in this case, ovarian, fallopian tube, primary peritoneal cancer, retinoblastoma, breast cancer in a male, or metastatic prostate cancer—represents a sixth indication and is important even when the only indication present. Pathology must also be considered. Certain types of cancer are overrepresented in hereditary cancer families. For example, medullary and triple- negative breast cancers (where the estrogen, progesterone, and Her2 receptors are all negative, often abbreviated ER/PR/Her2) are overrepresented in BRCA1 families,26,27 and the National Comprehensive Cancer Network (NCCN) BRCA testing guidelines include individuals aged 60 and younger years diagnosed with a triple-negative breast cancer.8 However, breast cancer patients without these pathologic findings are not necessarily at lower risk to carry a pathogenic variant. In contrast, patients with a borderline or mucinous ovarian carcinoma are at lower risk to carry a BRCA1 or BRCA2 pathogenic variant28 and may instead carry a pathogenic variant in a different gene. It is already well-established that medullary thyroid carcinoma (MTC), sebaceous adenoma or carcinoma, and adrenocortical carcinoma are each associated with other hereditary cancer syndromes.3 Recently, the results from tumor genomic profiling that may reveal germline findings have been added as an indication for genetic counseling. For instance, BRCA testing is appropriate when a pathogenic BRCA variant is identified in any tumor type during somatic testing.8 This subject is discussed further in this chapter. Finally, the ninth indication is a known family history of a pathogenic variant in a cancer predisposition gene. TABLE 38.2

Indications that Warrant Genetic Counseling for Hereditary Cancer Syndromes 1. Early age of onset (e.g., younger than 50 y for breast, colon, and uterine cancer) 2. Multiple family members on the same side of the pedigree with the same cancer 3. Clustering of cancers/benign findings in the family known to be caused by pathogenic variants in a single gene (e.g., breast/ovarian/pancreatic/prostate cancer [Gleason score ≥7 or metastatic]; colon/uterine/ovarian; colon cancer/polyps/desmoid tumors/osteomas) 4. Multiple primary cancers in one individual (e.g., breast/ovarian cancer; colon/uterine; synchronous/metachronous colon cancers; >15 gastrointestinal polyps; >10 adenomas; >5 hamartomatous or ≥3 juvenile polyps) 5. Ethnicity (e.g., Jewish ancestry for BRCA-related breast/ovarian cancer syndrome) 6. Presence of a tumor that, by itself, indicates a need for genetics evaluation (e.g., ovarian, fallopian tube, primary peritoneal, male breast, or metastatic prostate cancer; retinoblastoma; even one sebaceous carcinoma or adenoma at any age) 7. Pathology (e.g., triple negative [ER/PR/Her-2] breast cancer 60 y and younger; medullary thyroid cancer; a colon/endometrial cancer with an abnormal microsatellite instability or immunohistochemistry result) 8. Tumor profiling results with possible germline implications (e.g., pathogenic BRCA1/BRCA2 variant detected by tumor profiling in any tumor type) 9. Family history of a known pathogenic variant in a cancer predisposition gene (e.g., BRCA1, MSH2, PTEN, CHEK2) ER, estrogen; PR, progesterone.

These indications should be viewed in the context of the entire family history and must be weighed in proportion to the number of individuals who have not developed cancer. Risk assessment is often limited in families that are small or have few female relatives, in families with several early deaths for other reasons, in families in which individuals have undergone prophylactic surgeries that may mask risk (e.g., hysterectomy and

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ovary removal when a syndrome that predisposes to gynecologic cancer is being considered), and in cases that patients have little/no information about their family histories. In such families, a single indication may carry more weight, and the lack of family history of cancer should not discount risk to a family member.29 Furthermore, some hereditary cancer syndromes have a significant de novo (new mutation) rate, which could explain lack of suspicious family history in an individual who has been diagnosed with such a condition. A less common, but extremely important, finding is the presence of characteristic benign features or birth defects that are known to be associated with hereditary cancer syndromes. For instance, significant polyp burden or polyps with specific pathology, such as multiple adenomatous, hamartomatous, or juvenile colon polyps,3,30 can be suggestive of familial adenomatous polyposis, Cowden syndrome, or juvenile polyposis syndrome, respectively. Characteristic benign skin findings, autism, large head circumference,31,32 and thyroid lesions are commonly seen in Cowden syndrome; odontogenic keratocysts in nevoid basal cell carcinoma (Gorlin) syndrome33; and desmoid tumors or dental abnormalities in familial adenomatous polyposis.30 These findings, especially in combination with suspicious cancer history, should prompt further investigation of the patient’s family history and consideration of a referral to genetic counseling.

COMPONENTS OF THE CANCER GENETIC COUNSELING SESSION Cancer genetic counseling may be appropriate for adult men and women, and sometimes children, with a personal and/or family history of cancer. Given this, the appropriate elements to include, and challenges and nuances to address, vary from patient to patient. In this chapter, the breast/ovarian cancer counseling session with a female patient serves as a paradigm by which all other sessions may broadly follow.

Precounseling Information Before coming in for genetic counseling, the counselee should be informed about what to expect at each visit and what information he or she should collect ahead of time. The counselee can then begin to collect medical and family history information and pathology reports that will be essential for the genetic counseling session.

Family History An accurate family history is undoubtedly one of the most essential components of the cancer genetic counseling session. Many clinics collect this information electronically, which has both pros and cons. Optimally, a family history should include at least four generations; however, patients do not always have this information. For each individual affected with cancer, it is important to document the exact diagnosis, age at diagnosis, treatment strategies, and environmental exposures (i.e., occupational exposures, cigarettes, other agents) whenever possible.34 The current age of the individual, laterality, and occurrence of any other cancer should also be documented. Cancer diagnoses should be confirmed with pathology reports whenever possible. A study by Love et al.35 revealed that individuals accurately reported the primary site of cancer only 83% of the time in their firstdegree relatives with cancer, and 67% and 60% of the time in second- and third-degree relatives, respectively. It is common for patients to report a uterine cancer as an ovarian cancer, a colon polyp as an invasive colorectal cancer, or a metastasis as an additional primary cancer. These differences, although seemingly subtle to the patient, can have a significant impact on risk assessment. Individuals should be asked if there are any consanguineous relationships (partnerships between biologically related individuals) in the family; if any relatives were born with autism, birth defects, or intellectual disability; and whether genetic diseases run in the family (e.g., Fanconi anemia, Cowden syndrome) because these pieces of information could prove to be important in reaching a diagnosis. A common misconception in family history taking is that a maternal family history of breast, ovarian, or uterine cancer is somehow more significant than a paternal history. Conversely, many still believe that a paternal history of prostate cancer is more significant than a maternal history. None of the cancer predisposition genes discovered thus far are located on the sex chromosomes; therefore, both maternal and paternal histories are significant and must be explored thoroughly. It is also necessary to elicit the spouse’s personal and family history of cancer. This has bearing on the cancer status of common children and may also suggest whether children are at increased risk for a serious recessive genetic disease, a point that is discussed further in this chapter. Patients should be encouraged to report changes in their family history over time (e.g., new cancer diagnoses, genetic testing results in relatives) because this may change their risk assessment and counseling.

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A detailed family history should also include genetic diseases, birth defects, intellectual disability, multiple miscarriages, stillbirths, and infant deaths. A history of certain recessive genetic diseases (e.g., ataxia telangiectasia, Fanconi anemia) can indicate that healthy family members who carry a pathogenic variant in one copy of the gene in question may be at increased risk to develop cancer.23 Other genetic disorders, such as hereditary hemorrhagic telangiectasia, can be associated with a hereditary cancer syndrome caused by a pathogenic variant in the same gene—in this case, juvenile polyposis.36

Dysmorphology Screening Congenital anomalies, benign tumors, and unusual dermatologic features occur in a large number of hereditary cancer predisposition syndromes. Examples include osteomas of the jaw in familial adenomatous polyposis, palmar pits in nevoid basal cell carcinoma (Gorlin) syndrome, and papillomas of the lips and mucous membranes in Cowden syndrome. Obtaining an accurate past medical history of benign lesions and birth defects, and screening for such dysmorphology, can greatly impact risk assessment, diagnosis, counseling, and testing. For example, BRCA1/BRCA2 testing alone is inappropriate in a patient with breast cancer who has a family history of thyroid cancer and the orocutaneous manifestations of Cowden syndrome.

Risk Assessment Risk assessment is one of the most complicated components of the genetic counseling session. It is crucial to remember that risk assessment changes over time as the person ages and as the health statuses of his or her family members change. Risk assessment can be broken down into three separate components. What is the chance that the counselee will develop the cancer observed in his or her family (or a genetically related cancer such as ovarian cancer due to a family history of breast cancer)? What is the chance that the cancers in this family are caused by a pathogenic variant in a cancer predisposition gene, or more rarely, pathogenic variants in multiple genes? What is the chance that we can identify the pathogenic variant in this patient with our current knowledge and laboratory techniques? Cancer clustering in a family may be due to genetic and/or environmental factors or may be coincidental because some cancers are very common in the general population.37 Although inherited factors may be the primary cause of cancers in some families, in others, cancer may develop because an inherited factor increases the individual’s susceptibility to environmental carcinogens. It is also possible that members of the same family may be exposed to similar environmental exposures due to shared geography or patterns in behavior and diet that may increase the risk of cancer.38 Therefore, it is important to distinguish the difference between a familial pattern of cancer (due to environmental factors or chance) and a hereditary pattern of cancer (due to a shared pathogenic variant). Emerging research is also evaluating the role and clinical utility of more common low-penetrance susceptibility genes and single nucleotide polymorphisms that may account for a proportion of familial cancers.38,39 Several models, some web-based, are available to calculate the chance that a woman will develop breast cancer, including the Gail, Claus, BRCAPro, BOADICEA, Tyrer-Cuzick, and PENNII models.40 At first glance, many of these models appear simple and easy to use, and it may be tempting to exclusively rely on these models to assess cancer/pathogenic variant risk. However, each model has its strengths and weaknesses, and the counselor needs to understand the limitations well and know which are validated, which are considered problematic, when a model will not work for a particular patient, or when another genetic syndrome should be considered. For example, none of the existing models are able to factor in other risks that may be essential in hereditary risk calculation (e.g., a sister who was diagnosed with breast cancer after radiation treatment for Hodgkin disease). The risk of a detectable pathogenic variant will also vary based on cancer history and the degree of relationship to an affected family member. For example, family members with early-onset breast cancer have a higher likelihood of testing positive than unaffected family members. Therefore, the risk assessment process should include a discussion of which family member is the best candidate for testing.

Genetic Testing Testing for dozens of cancer predisposition genes is now available via DNA testing. However, germline cancer genetic testing is currently only appropriate for a relatively small percentage of individuals with cancer.

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Importantly, testing should begin in an affected family member whenever possible to maximize the likelihood of finding a hereditary cause for cancer, when it exists. DNA testing offers the important advantage of presenting clients with actual risks instead of the empiric risks derived from risk calculation models. The cost of DNA testing has dropped dramatically since the 2013 Supreme Court Case decision on gene patents.41 BRCA1/BRCA2 testing cost $4,400 before this decision, $2,200 by most competitor labs within 24 hours of the decision, and is now offered for less than $150 by several laboratories.42 Most insurance companies cover cancer genetic testing in families in which the test is medically indicated. Many consumers are now having genetic testing through companies like 23andMe and Ancestry.com for under $100 and have the option of receiving their raw data. Interpreting these data is discussed later in this chapter. One of the most crucial aspects of DNA testing is accurate result ordering and interpretation. Unfortunately, errors in ordering and interpretation are the greatest risk of genetic testing and are common.5–7,15,43,44 Emerging data reveal that between 30% to 50% of genetic tests are ordered inappropriately, which is problematic for patients, clinicians, and insurers.45–47 Recent data demonstrate that many medical providers have difficulty interpreting even basic pedigrees and genetic test results with 85% of providers reporting that they do not feel prepared to answer questions pertaining to these.48–50 Additional studies have demonstrated that inaccurate interpretation of genetic testing has resulted in inappropriate medical management recommendations, unnecessary prophylactic surgeries (e.g., removal of breasts, ovaries, colon), late diagnoses of advanced cancers, a massive waste of health-care dollars, psychosocial distress, and false reassurance for patients.5–7,43 A recent case in which a patient alleged that she had her uterus and breasts removed because her clinicians misinterpreted her genetic test results has received much attention.51 Similar gross errors, including pregnancy termination for unfounded medical reasons, occur in all areas of genetics.44 Interpretations are becoming increasingly complicated as more tests and gene panels become available. For example, one study demonstrated that approximately 25% of high-risk families that were BRCA1 and BRCA2 negative by commercially available sequencing were found to carry a deletion or duplication in one of these genes, or a pathogenic variant in another gene.52 This is particularly concerning in an era in which many providers are performing their own counseling and testing. It is also crucial that the person ordering the test understand the efficacy of testing techniques utilized by the laboratory. The potential impact of test results on the patient and his or her family is great and, therefore, accurate interpretation of the results is paramount. Numerous professional groups have recognized this and have adopted standards recommending pre- and postgenetic counseling by a certified provider to ensure proper ordering and interpretation of genetic tests.8–12 In an effort to reduce errors, many insurance companies are requiring genetic counseling by a certified genetic counselor before testing for hereditary breast or colon cancer syndromes.21 Results can fall into a few broad categories. It is important to note that a negative test result can actually be interpreted in three different ways, detailed in points 2, 3, and 4, which follow. 1. Pathogenic variant “positive.” When a pathogenic variant in a well-known cancer predisposition gene is discovered, the cancer risks for the patient and her family are relatively straightforward. The NCCN publishes revised management guidelines approximately once a year. Guidelines exist for hereditary cancer syndromes, whereas management for other syndromes and pathogenic variants in other cancer predisposition genes is based on expert opinion and consensus guidelines when available. These nuances are discussed further. Even for well-known genes, the risks are not precise and should be presented to patients as risk ranges.53,54 When a true pathogenic variant is found, it is critical to test both parents (whenever possible) to determine from which side of the family the pathogenic variant is originating, even when the answer appears obvious. 2. True negative. An individual does not carry the pathogenic variant found in her family, which ideally has been proven to segregate with the cancer family history. Outside of other risk factors, the patient’s cancer risks are usually reduced to population risk in this case. 3. Negative. A pathogenic variant was not detected, and the cancers in the family are not likely to be hereditary based on the personal and family history assessment. For example, a patient is diagnosed with breast cancer at age 38 years and comes from a large family with no other cancer diagnoses and relatives who died at old ages of other causes. However, the testing this patient had should be examined with care, as new panels of cancer predisposition genes include many rare, lower penetrance genes that may be associated with less striking family histories. 4. Uninformative. A pathogenic variant cannot be found in affected family members of a family in which the cancer pattern appears to be hereditary; there is likely an undetectable pathogenic variant within the gene, or

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the family carries a pathogenic variant in a different gene. If, for example, the patient developed breast cancer at age 38 years, has a father with breast cancer, and has a paternal aunt who developed breast and ovarian cancers before age 50 years, a negative test result would be almost meaningless. It would simply mean that the family likely has a pathogenic variant that could not be identified with our current testing methods or a pathogenic variant in another cancer predisposition gene. The entire family should be followed as high risk. 5. Variant of uncertain significance (VUS). A genetic variant (difference) is identified, the significance of which is unknown. It is possible that this variant is deleterious or completely benign. Of concern, a recent study demonstrated that up to half of breast surgeons surveyed treated VUS findings the same as pathogenic variants in terms of surgical decision making for patients, especially those surgeons who less commonly treated patients with breast cancer. A VUS finding requires further investigation by the person providing the counseling and interpretation, such as enrolling the patient in a formal variant reclassification program, and should not be mistakenly treated as a positive result.93 It may be helpful to test other affected family members to see if the variant segregates with disease in the family. If it does not segregate, the variant is less likely to be significant. If it does, the variant is more likely to be significant. However, it is very possible for multiple close family members to carry the same variant (pathogenic or benign) given that family members share a significant proportion of hereditary information, so it is important not to make assumptions in this case. Other tools, including a splice site predictor, in conjunction with data on species conservation and amino acid difference scores, can also be helpful in determining the likelihood that a variant is significant. It is rarely helpful (and can be detrimental) to test unaffected family members for such variants or affected family members outside of a formal variant reclassification study with clear guidance on the implications (or lack thereof) of identifying a variant that has not been confirmed to be pathogenic. Guidance on the classification of variants from the American College of Medical Genetics and Genomics and the Association for Molecular Pathology have improved the consistency of variant reporting across laboratories; however, further collaborations are still needed. Several studies, including the Prospective Registry of MultiPlex Testing (PROMPT), aim to tackle this issue. In addition, creation of open databases such as ClinVar and nationwide movements such as Free the Data will likely improve variant reporting for all laboratories. In order to pinpoint the pathogenic variant in a family, an affected individual most likely to carry the pathogenic variant should be tested first, whenever possible. This is most often a person affected with the cancer in question at the earliest age. Test subjects should be selected with care because it is possible for a person to develop sporadic cancer in a hereditary cancer family. For example, in an early-onset breast cancer family, it would not be ideal to first test a woman diagnosed with breast cancer at age 65 years because she may represent a sporadic case. If a pathogenic variant is detected in an affected relative, other family members can be tested for the same pathogenic variant with a greater degree of accuracy. Family members who do not carry the pathogenic variant found in their family are deemed true negative. Those who are found to carry the pathogenic variant in their family will have more definitive information about their risks to develop cancer. This information can be crucial in assisting patients in decision making regarding surveillance and risk reduction. If a pathogenic variant is not identified in the affected relative, it generally means that either the cancers in the family are (1) not hereditary or (2) caused by an undetectable pathogenic variant or a pathogenic variant(s) in a different gene. A careful review of the family history and the risk factors will help to decipher whether interpretation 1 or 2 is more likely. Additional genetic testing may need to be ordered at this point or over time as analysis of additional cancer predisposition genes becomes available. In cases in which the cancers appear hereditary and no pathogenic variant is found, DNA banking should be offered to the proband for a time in the future when improved testing may become available. A letter indicating exactly who in the family has access to the DNA should accompany the banked sample. The genetic counseling result disclosure session should also include a detailed discussion of which other family members would benefit from genetic counseling and testing as well as referral information. This may not only apply to families who have been found to carry a pathogenic variant but may also prove useful in other families (e.g., test a higher risk relative or determine segregation of a variant within a family). Even in absence of a positive test result, increased screening may be appropriate for family members, and these considerations should be discussed during result disclosure. The penetrance of pathogenic variants in cancer susceptibility genes is also difficult to interpret. Initial estimates derived from high-risk families provided very high cancer risks for BRCA1 and BRCA2 pathogenic variant carriers.55 More recent studies done on populations that were not selected for family history have revealed

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lower penetrance.29 Risks based on location of the variant within the gene or on family history can be discussed, but this should be done with great caution. Family structure and size can have major bearing on these estimates, and the counselor must review the test result and the pedigree thoroughly before providing altered risk estimates to a patient. Because exact penetrance rates cannot be determined for individual families at this time, and because precise genotype/phenotype correlations remain unclear, it is prudent to provide patients with a range of cancer risk and to explain that their risk probably falls somewhere within this spectrum. This can prove challenging for genes that lack published long-term data on cancer associations and risks. Female carriers of BRCA1 and BRCA2 pathogenic variants have a 50% to 85% lifetime risk to develop breast cancer and between a 15% to 60% lifetime risk to develop ovarian cancer.25,54,55 It is important to note that the classification “ovarian cancer” also includes cancer of the fallopian tubes and primary peritoneal carcinoma.56 BRCA carriers also have an increased lifetime risk of male breast cancer, pancreatic cancer, and melanoma, especially in the case of pathogenic BRCA2 variant carriers.57,58

Options for Surveillance, Risk Reduction, and Tailored Treatment The cancer risk counseling session is a forum to provide counselees with information, support, options, and hope. Pathogenic variant carriers can be offered: tailored cancer treatment, earlier and more aggressive surveillance, chemoprevention, and/or prophylactic surgery. Detailed management options for BRCA carriers are discussed in this chapter and summarized in Table 38.3. Surveillance recommendations are evolving with newer techniques and additional data. At this time, it is recommended that women who carry a pathogenic BRCA variant begin breast surveillance at age 25 years.8 This includes a clinical breast exams every 6 to 12 months and annual breast magnetic resonance imaging (MRI) with contrast. It may be necessary to begin earlier if a patient has a family history of breast cancer diagnosed prior to age 30 years. If breast MRI is unavailable, mammogram may be considered. Ideally, breast MRI should be performed days 7 to 15 of the menstrual cycle. At age 30 years, clinical breast exams should continue every 6 to 12 months, along with annual mammogram in addition to annual breast MRI with contrast. It is suggested that the mammogram and MRI be spaced out around the calendar year so that some intervention is planned every 6 months. After age 75 years, breast imaging should be individualized. TABLE 38.3

BRCA Screening and Risk Reduction Options BRCA Carriers Breast cancer: Women screening: Age 18 y: Breast awareness Age 25 y: Annual breast MRI with contrast. If not available, mammography with tomosynthesis can be considered. Age 30 y: Continue annual MRI. Additional mammogram (with consideration of tomosynthesis), with consideration of spacing out around the calendar year so that some intervention is planned every 6 mo. Age 75 y: Breast imaging should be individualized. Risk reduction: Risk-reduction agents: Limited retrospective data suggest that tamoxifen and raloxifene reduce the risk of breast cancer in women who are BRCA carriers. Prophylactic surgery: Bilateral prophylactic mastectomy has been shown to reduce a BRCA carrier’s risk of a future breast cancer by >90%. Men screening: Age 35 y: Breast self-exam training and education, annual clinical breast exams Ovarian cancer: Screening: Ages 30–35 y: Transvaginal Doppler ultrasound and CA 125 blood marker may be considered. However, the effectiveness of this screening has not been established, and this should be

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considered a short-term plan until risk-reducing salpingo-oophorectomy (RRSO). Risk reduction: Risk-reduction agents: Several studies suggest that oral contraceptives reduce ovarian cancer risk in carriers of BRCA pathogenic variants. Prophylactic surgery: RRSO should typically be considered by ages 35–40 y and upon completion of childbearing. Given that BRCA2-associated ovarian cancers occur later, it is reasonable to consider RRSO by ages 40–45 y in BRCA2 carriers. Prostate: Screening: Age 45 y: Yearly digital rectal exam and PSA blood test is recommended for men with a BRCA2 pathogenic variant and should be considered for men with a BRCA1 pathogenic variant. Melanoma: Screening: Consider annual dermatologic and eye exams. The recommended ages in this table do not account for family history, which may indicate that screening or risk reduction should be considered at an earlier age. In addition, medical management for individuals with a hereditary cancer predisposition is nuanced, and not all options are presented here. Discussions should take into account several considerations not addressed by professional guidelines. A genetic counselor’s input in managing these patients can help address these concerns. MRI, magnetic resonance imaging; PSA, prostate-specific antigen.

BRCA carriers may take a selective estrogen-receptor modulator or aromatase inhibitor in hopes of reducing their risks of developing breast cancer. These medications have been proven effective in women at increased risk due to a positive family history of breast cancer.59,60 There are limited data on the effectiveness of such medications in unaffected BRCA carriers61,62; however, there are some data to suggest that BRCA carriers taking tamoxifen as treatment for a breast cancer reduce their risk of a contralateral breast cancer.63 Additionally, the majority of BRCA2 carriers who develop breast cancer develop an estrogen-positive form of the disease,64 and it is hoped that this population will respond especially well to chemoprevention. Further studies in this area are necessary before drawing conclusions about the efficacy of chemoprevention in this population. Prophylactic bilateral mastectomy reduces the risk of breast cancer by >90% in women at high risk for the disease.65 Before genetic testing was available, it was not uncommon for entire generations of cancer families to have at-risk tissues removed without knowing if they were personally at increased risk for their familial cancer. Fifty percent of unaffected individuals in hereditary cancer families will not carry the inherited predisposition gene and can be spared prophylactic surgery or invasive high-risk surveillance regimens. Therefore, it is clearly not appropriate to offer prophylactic surgery until a patient is referred for genetic counseling and, if possible, testing.66 Women who carry BRCA1/BRCA2 pathogenic variants are also at increased risk to develop second contralateral and ipsilateral primaries of the breast.67 These data bring into question the option of breastconserving surgery in women at high risk to develop a second primary within the same breast. For this reason, the BRCA1/BRCA2 carrier status can have a profound impact on surgical decision making,68 and many patients have genetic counseling and testing immediately after diagnosis and before surgery or radiation therapy. Those patients who test positive and opt for prophylactic mastectomy can often be spared radiation and the resulting side effects that can complicate reconstruction. Approximately 30% to 60% of previously irradiated patients who later opt for mastectomy with reconstruction report significant complications or unfavorable cosmetic results.68,69 Women who carry pathogenic BRCA1/BRCA2 variants are also at increased risk to develop ovarian, fallopian tube, and primary peritoneal cancer, even if no one in their family has developed these cancers. Surveillance for ovarian cancer includes transvaginal ultrasounds and CA 125 testing; however, the effectiveness of such surveillance in detecting ovarian cancers at early, more treatable stages has not been proven in any population. Furthermore, these screening measures are insufficiently specific or sensitive. In September 2016, the U.S. Food and Drug Administration (FDA) issued the following warning: “The FDA believes that women at high risk for developing ovarian cancer should not use any currently offered test that claims to screen for ovarian cancer.”70 Oral contraceptives reduce the risk of ovarian cancer in all women, including BRCA carriers.71 Recent data indicate that the impact of this intervention on increasing breast cancer risk, if any, is low.72,73 Given the difficulties in screening and in the treatment of ovarian cancer, the risk/benefit analysis likely favors the use of oral contraceptives in young carriers of BRCA1/BRCA2 pathogenic variants who are not yet ready to have their

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ovaries removed. Risk-reducing salpingo-oophorectomy (RRSO) is currently the most effective means to reduce the risk of ovarian cancer and is typically recommended to BRCA1/BRCA2 carriers by the age of 35 to 40 years or when childbearing is complete.8,73 Emerging data indicate that most ovarian cancers begin in the fallopian tube and that salpingectomy may someday be sufficient in reducing ovarian cancer risk in young women; however, more data are needed before this option is offered to patients outside of clinical trials.77 For women 15 to 20 percentage points usually are considered unrealistic. Establishing a sample size that provides good statistical power for detecting realistically expected treatment improvements is important. Many published “negative” results are actually uninterpretable because the sample sizes are too small. TABLE 39.6

Number of Events Needed for Comparing Survival Curves Percentage Reduction in Hazard of Death

Ratio of Median Survival for Exponential Distributions

Number of Total Deaths to Observea

25

1.33

508

30

1.43

330

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33

1.50

257

40

1.67

162

50

2.0

88

aTotal number of deaths in both groups to have power = .90 for detecting ratio of median survival. Type I error α = .05 (two-sided).

TABLE 39.7

Number of Patients in Each of Two Treatment Groups to Compare Proportions (One-Sided Test) Larger Minus Smaller Success Rate Smaller Success Rate

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

a

512

172

94

62

45

35

28

23

19

16

381b

129

72

48

35

27

22

18

15

13

0.10

786

236

121

76

54

40

31

25

21

17

579

176

91

58

41

31

24

20

16

14

0.15

1,026

292

144

88

60

44

34

27

22

18

752

216

108

66

46

34

26

21

17

14

0.20

1,231

339

163

98

66

48

36

29

23

19

900

250

121

73

50

37

28

22

18

15

0.25

1,402

377

178

105

70

50

38

29

23

19

1,024

278

132

79

53

38

29

23

18

15

1,539

407

189

111

73

52

38

30

23

19

1,122

300

141

83

55

39

30

23

18

15

1,642

429

197

114

74

52

38

29

23

18

1,196

315

146

85

56

40

30

23

18

14

1,711

441

201

115

74

52

38

29

22

17

1,246

324

149

86

56

39

29

22

17

14

1,745

446

201

114

73

50

36

27

21

16

1,271

327

149

85

55

38

28

21

16

13

1,745

441

197

111

70

48

34

25

19

15

1,271

324

146

83

53

37

26

20

15

12

0.05

0.30 0.35 0.40 0.45 0.50 a

Upper figure: significance level = .05, power = .90.

bLower figure: significance level = .05, power = .80.

TABLE 39.8

Number of Patients in Each of Two Treatment Groups to Compare Proportions (Two-Sided Test) Larger Minus Smaller Success Rate Smaller Success Rate 0.05

0.10 0.15 0.20 0.25

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

620a

206

113

74

54

42

33

27

23

19

473b

159

88

58

43

33

27

22

18

16

956

285

146

92

64

48

38

30

25

21

724

218

112

71

50

38

30

24

20

17

1,250

354

174

106

73

53

41

33

26

22

944

269

133

82

57

42

32

26

21

18

1,502

411

197

118

79

57

44

34

27

22

1,132

313

151

91

62

45

34

27

22

18

1,712

459

216

127

84

60

45

35

28

23

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0.30 0.35 0.40 0.45 0.50

1,289

348

165

98

65

47

36

28

22

18

1,880

495

230

134

88

62

46

36

28

22

1,414

375

175

103

68

48

36

28

22

18

2,006

522

239

138

89

63

46

35

27

22

1,509

395

182

106

69

49

36

28

22

18

2,090

537

244

139

89

62

45

34

26

21

1,571

407

186

107

69

48

36

27

21

17

2,132

543

244

138

88

60

44

33

25

19

1,603

411

186

106

68

47

34

26

20

16

2,132

537

239

134

84

57

41

30

23

17

1,603

407

182

103

65

45

32

24

18

14

aUpper figure: significance level = .05, power = .90. bLower figure: significance level = .05, power = .80.

FACTORIAL DESIGNS The factorial design is one approach to improving the efficiency of phase III clinical trials by using the same patients to answer more than one therapeutic question. For example, consider a two-by-two factorial design involving factor A, whether drug A1 or A2 is used for induction, and factor B, whether drug B1 or B2 is used for consolidation. There are four treatment groups: A1B1, A1B2, A2B1, and A2B2. Although there are four treatment groups, the average effect of each treatment factor can be evaluated using all of the patients. To compare A1 to A2, you ignore factor B or average the factor A treatment effect over the two factor B strata. Usually, the sample size for a two-by-two factorial trial is computed assuming that there is no interaction between the effects of the two drugs. The sample size is approximately the same as for a simple two-arm trial. The factorial design offers the possibility of answering two questions for the cost of one, but there is a risk of ambiguity in the interpretation of results. For situations in which negative interactions are unlikely or in which it is unlikely that both factors will have substantial effects, the factorial design can provide a substantial improvement in the efficiency of clinical trials. Simon and Freedman75 developed a Bayesian method for the design and analysis of factorial trials. Their approach avoids the need to dichotomize one’s assumptions that interactions either do or do not exist and provides a flexible approach to the design and analysis of such clinical trials. The Bayesian approach also avoids a preliminary test of interaction; such tests have poor power, and basing the analysis on such tests is problematic. The Bayesian model suggests that in planning a factorial trial in which interactions are unlikely but cannot be excluded, the sample size should be increased by approximately 30%, as compared to a simple two-arm clinical trial for detecting the same size of treatment effect. The 30% figure allows for a 5% prior probability of a medically important, qualitative interaction between the treatment effects.

Noninferiority Trials Noninferiority trials often compare a standard treatment to a less invasive or more convenient therapy that is not expected to be superior to the standard treatment with regard to the primary end point. For such trials, the secondary benefits of the new regimen, although important, is not worth reductions in effectiveness in the primary end point. Unfortunately, it is not possible to establish that the two treatments are completely equivalent with regard to the primary end point. The usual approach is to plan the trial to have high statistical power for detecting small reductions in effectiveness, and this requires a large sample size. Because failure to reject the standard null hypothesis of no treatment difference results in adoption of a new, and potentially inferior, regimen, misinterpretation of the results of noninferiority trials can result in serious problems. For the analysis of such trials, confidence intervals rather than statistical significance tests should be emphasized.76 The confidence interval for the true difference of effectiveness gives a much clearer picture of which differences are consistent with the data. Makuch and Simon77 and Durrleman and Simon78 discuss this approach for planning and monitoring therapeutic equivalence trials. Noninferiority trials are generally planned to distinguish the null hypothesis that the treatments are equivalent from the alternative that the new treatment is inferior by an amount δ. One of the key problems in designing a

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noninferiority trial is specification of δ. A small value of δ leads to a large trial. A large value of δ can lead to a small but meaningless trial. The reduction in effectiveness that the trial will be able to detect should be some fraction of the effectiveness of the standard treatment. For example, suppose the standard treatment is 12 months of a chemotherapy regimen that increases 5-year survival by 10 percentage points relative to no chemotherapy and the new regimen of interest is use of the same regimen for only 6 months. If we want to have high power for detecting a reduction in effectiveness by half, then δ should represent a difference of 5 percentage points in 5-year survival. If we want high power for detecting a reduction in effectiveness by one-quarter, then δ should represent a difference of 2.5 percentage points in 5-year survival. An appropriate value of δ can only be determined based on a careful review of the studies that established the effectiveness of the standard treatment. If those studies do not exist or are not adequate, a noninferiority trial may not be appropriate. Another problem in the design of noninferiority trials is the lack of internal validation of the assumption that the control treatment is actually effective for the patient population at hand. If the effectiveness of the standard treatment is highly variable among studies, there is the risk that a new regimen will be found noninferior to the standard because the standard is not effective in the current study. Consequently, noninferiority trials are only appropriate when the standard regimen is highly and reproducibly effective. None of the conventional frequentist approaches to the design and analysis of therapeutic equivalence trials satisfactorily account for the uncertainty in estimation of the effectiveness of the standard treatment. Simon79 developed a Bayesian approach that addresses this problem. Simon79 also shows how the sample size of the therapeutic equivalence trial may be planned and how the size depends critically on the strength and consistency of the evidence that the active control C is superior to P and on the size of that difference in effectiveness.

Bayesian Methods Conventional statistical methods (i.e., frequentist method) regard the data collected in an experiment as being random; they test hypotheses about parameters that represent fixed but unknown treatment effects. For example, frequentist methods derive probability statements about differences in observed response rates under an assumed null hypothesis that the true response probabilities are equal. Bayesian statistical methods consider the parameters, as well as the data, as being random and selected from prior distributions. What does the assumption that the true treatment effect is a random draw from a prior distribution mean? One interpretation is that we regard the prior distribution as expressing our subjective beliefs about the value of the treatment effect based on previous experience with this treatment and other similar treatments. Such subjective prior distributions would vary among individuals based on their experience, biases, circumstances, and perhaps economic interests. Bayesian methods use Bayes’ theorem to update the prior distributions of the parameters based on data from the study to produce the posterior distributions of the parameters. Using the posterior distributions, hypotheses about whether the treatments are equivalent can be tested. Consequently, Bayesian methods can derive direct probability statements about the parameters, such as “the probability that the treatment effect is .04.” The probability statements about the parameters seem to tell us what we want to know, but the results may depend as much on our prior distributions as on the data. Many Bayesian statisticians use “noninformative” prior distributions. For example, a noninformative prior distribution for the difference in response probabilities might be constant for all differences between −1 and +1. That noninformative prior represents the belief that huge differences are just as likely as small differences, positive differences as likely as negative differences. Consequently, methods based on apparently innocuous noninformative prior distributions may not be appropriate for inference based on small sample sizes for real-world studies. Spiegelhalter et al.80 have suggested analysis of a clinical trial with regard to both an “enthusiastic” prior and a “skeptical” prior. The former might be held by a developer of the treatment and the later by a regulator. Robust conclusions are obtained when the data is so extensive and strong that the posterior distributions are little changed regardless of whether you use an enthusiastic or skeptical prior. Unfortunately, such robustness generally requires a very large sample size, much larger than indicated by use of standard frequentist methods. For some parameters, there may be a consensus prior distribution. For example, for evaluating cytotoxics there is often broad consensus that large treatment effect by patient–subset interactions were unlikely, and Simon81 used this in a Bayesian approach to subset analysis. There are several important misconceptions about the use of Bayesian methods for clinical trials. First, some people believe that Bayesian methods provide an adequate alternative to randomized treatment assignment. In fact, however, randomization is just as important for the validity of Bayesian methods as for frequentist methods.82 Second, some people mistakenly believe that Bayesian clinical trials require fewer patients than

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frequentist trials. Bayesian sample size calculations depend on the prior distribution used. Using skeptical priors, the sample size needed with Bayesian methods may be much larger than the conventional sample size. Third, some statisticians believe that the main impediment to use of Bayesian methods in clinical trials has been the difficulty of computing posterior distributions. The main limitation has, however, been the fact that subjectivity of analysis is problematic for phase III clinical trials. Randomized clinical trials are done because the opinions of experts are often wrong. Bayesian methods can be very useful for phase I and II trials. For such trials, the prior distribution need only be appropriate for the investigator or sponsor. For phase III trials, the situation is more complex. Although subjective opinion of the investigator or sponsor should have no role in testing the primary hypothesis of no treatment effect, once the basic effectiveness of the treatment is established, however, there are many other analyses that can help physicians decide how to use the new treatment. Those analyses generally cannot be answered as precisely or with as little chance of error as the testing of the primary null hypothesis and Bayesian methods may play a useful role.83 Different physicians may have varying prior beliefs about the treatment and how its effectiveness might vary among patients; Bayesian methods may be useful for physicians in determining how to implement the results in the context of the patients they see. One must recognize, however, that Bayesian models can be overfit to data like any other models and can produce poor predictions.

ANALYSIS OF PHASE III CLINICAL TRIALS Intention-to-Treat Analysis The intention-to-treat principle indicates that all randomized patients should be included in the primary analysis of the trial. For cancer trials, this has often been interpreted to mean all “eligible” randomized patients. Excluding patients from analysis because of treatment deviations, early death, or patient withdrawal can severely distort the results.84–86 Often, excluded patients have poorer outcomes than do those who are not excluded. Investigators frequently rationalize that the poor outcome experienced by a patient was due to lack of compliance to treatment, but the direction of causality may be the reverse. For example, in the Coronary Drug Project, the 5-year mortality for poor adherents to the placebo regimen was 28.3%, significantly greater than the 15.1% experienced by good adherents to the placebo regimen.87 In randomized trials, there may be poorer compliance in one treatment group than the other, or the reasons for poor compliance may differ. Excluding patients, or analyzing them separately (which is equivalent to excluding them), for reasons other than eligibility is generally considered unacceptable. The intention-to-treat analysis with all eligible randomized patients should be the primary analysis. If the conclusions of a study depend on exclusions, these conclusions are suspect. The treatment plan should be viewed as a policy to be evaluated. The treatment intended cannot be delivered uniformly to all patients, but all eligible patients should generally be evaluable in phase III trials.

Interim Analyses If statistical significance tests are performed repeatedly, the probability that the difference in outcomes will be found to be statistically significant (at the .05 level) at some point may be considerably >5%. This probability is called the type I error of the analysis plan. Fleming et al.88 have shown that the type I error can be as great as 26% if a statistical significance test is performed every 3 months of a 3-year trial that compares two identical treatments. Some trials are published without stating the target sample size, without indicating whether a target sample size was stated in the protocol, and without describing whether the published analysis represented a planned final analysis or was one of multiple analyses performed during the course of the trial. In such cases, one must suspect that the investigators were not aware of good statistical practices and of the dangers of informal multiple analyses. Interim analyses can be misleading and interfere with a physician’s attempt to state honestly to the patient that there is no reliable evidence indicating that one treatment option or the other is preferable. Consequently, it has become standard in phase III multicenter clinical trials to have a data-monitoring committee review interim results, rather than having the monitoring done by participating physicians. This approach helps protect patients by having interim results carefully evaluated by an experienced group of individuals and helps protect the study from damage that ensues from misinterpretation of interim results.89,90 Generally, interim outcome information is available to only the data-monitoring committee. The study leaders are not part of the data-monitoring committee because they may have a perceived conflict of interest in continuing the trial. The data-monitoring committee

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determines when results are mature and should be released. These procedures are used only for phase III trials. A number of useful statistical designs have been developed for monitoring interim results. The simplest is due to Haybittle.91 Interim differences are discounted unless the difference is statistically significant at the two-sided P < .0025 level. If the interim differences are not significant at that level, the trial continues until its originally intended size. The final analysis is performed without regard to the interim analyses, and the type I error is almost unaffected by the monitoring. Many others have developed group-sequential methods for interim monitoring based on a prespecified number of planned interim analyses. One of the most commonly used methods is that of O’Brien and Fleming.92 The critical P value for determining whether an interim difference should be judged statistically significant depends on the number of analyses that will be performed during the trial. For a five-stage trial—four interim analyses and one final analysis—the critical P values are shown in Table 39.9.93 The experience of the U.S. cancer cooperative groups with interim analysis of phase III clinical trials was reviewed by Korn et al.94 Extreme treatment differences at an interim analysis are less usual in cancer clinical trials than finding that interim results do not support the hypothesis that the experimental treatment is substantially better than the control. Futility analyses are important in order to avoid exposing patients to a more toxic and debilitating new treatment E once the essential outcome of the trial is well assured.95 Data-monitoring committees are charged with helping to make these difficult judgments. A variety of statistical approaches to “futility monitoring” have been developed.96 Futility analyses based on intermediate end points like disease-free survival can be particularly effective even in trials where the primary end point is survival.41 TABLE 39.9

Nominal Two-Sided Significance Levels for Early Stopping in Interim Monitoring Methods that Maintain an Overall Type I Error Level of .05 Pocock113

Haybittle91

1

.016

.0027

.00001

.0051

2

.016

.0027

.0013

.0061

3

.016

.0027

.008

.0073

4

.016

.0027

.023

.0089

Final

.016

.049

.041

.0402

Analysis Number

O’Brien and Fleming92

Fleming et al.93

The method of stochastic curtailment97 is widely used for “futility analyses.” At any interim analysis, the probability of rejecting the null hypothesis at the end of the trial is computed. This probability is calculated as being conditional on the data already obtained and on the assumption that the alternative hypothesis of superiority of the experimental treatment used initially in planning the sample size for the trial is true. If this conditional power is less than approximately .20, then the trial may be terminated with acceptance of the null hypothesis. The .20 cutoff can be raised substantially to at least .40 if this type of interim analysis is performed only a few times during the course of the trial. With stochastic curtailment, interim analyses need not be equally spaced, and the number of interim analyses need not be specified in advance.

Significance Levels, Hypothesis Tests, and Confidence Intervals The concept of prespecification of hypotheses is important for medical experimentation. However, the accept– reject nomenclature of the Neyman-Pearson theory provides an oversimplified and sometimes misleading interpretation of the data. Significance levels can serve as useful aids to interpretation of results, but quibbling about whether a one-sided P = .04 is significant makes little sense. Significance levels are influenced by sample sizes, and failure to reject the null hypothesis does not mean that the treatments are equivalent. There is no simple index of truth for interpreting results. Some attempt to use the notion of statistical significance in this way, but thorough presentation, skeptical evaluation, and cautious interpretation of results always are required. Confidence intervals are generally much more informative than are significance levels. A confidence interval for the size of the treatment difference provides a range of effects consistent with the data. The significance level tells nothing about the size of the treatment effect because it depends on the sample size. However, it is the size of the treatment effect, as communicated by a confidence interval, that should be used in weighing the costs and

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benefits of clinical decision making. Many so-called negative results are actually noninformative, and confidence intervals help to determine when this is the case. Simon76 has presented a nontechnical discussion of how to calculate confidence intervals for treatment differences with the types of end points commonly used in cancer clinical trials.

Calculation of Survival Curves Most cancer clinical trials display results by showing survival curves or disease-free survival curves. Survival curves display the probability of surviving beyond any specified time, with time shown on the horizontal axis. In disease-free survival curves, it is the time until recurrence or death that is shown. The usual statistical methods are not appropriate for analyzing survival because they ignore the fact that at the time of analysis some patients have died while others continue alive (i.e., their ultimate survival times are “censored”). The most satisfactory way of representing such data is to estimate the survival function S(t). This function represents the probability of surviving more than t time units. Time t is measured from diagnosis, start of treatment, or some other meaningful time point. For randomized studies, it is best to measure time from the date of randomization. There are basically two satisfactory methods for estimating S(t). The first is the life table or actuarial method98,99 and is appropriate when the number of patients is large. The other method is the product limit method of Kaplan and Meier,100 which is described here. The first step is the calculation of survival time for all patients. Survival is the duration from the chosen baseline (e.g., date of randomization) until death or date last known to be alive for patients who are not known to have died. With the Kaplan-Meier approach, the intervals are defined by the actual survival times of patients who have died. Suppose, for example, that the survivals are 3, 3, 3+, 5, 6, 8+, 8+, 10, 10, and 12+ months, where a plus sign follows survivals for patients still alive. Then the intervals are 0 to 3, 3 to 5, 5 to 6, and 6 to 10 months, as shown in Table 39.10. The probability of surviving beyond 3 months is S(3) = 8/10, as indicated for the first interval of Table 39.10. The probability of surviving beyond 5 months is taken as the product of two factors: S(3) and the probability of surviving through the interval (3,5). We do not know whether the patient with survival time 3+ survives through the interval (3,5) because of the censoring. There are seven patients alive and followed at the start of this interval who we do know about and all but one (the one with survival time 5) survive through the interval. So we estimate S(5) = (8/10)(6/7) = 0.6857. This way of estimating S(5) represents an optimal use of the censored data and is based only on the assumption that censoring is not prognostic or “informative.” Similarly, we estimate S(6) as the product of S(5) and the probability of surviving through the end of the interval (5,6), which is 5/6. Thus, S(6) is estimated as (0.6857)(5/6) = 0.571. Similarly, S(10) = S(6)(1/3), where 1/3 is the estimated probability of surviving through the interval (6,10) given that the patient is alive at the start of the period. Because two patients are censored at 8 months, there are only three patients alive at the start of this period for whom we know definitively whether they survive through the entire period. Once the values Sx have been calculated for the Kaplan-Meier method, they may be graphed with time on the horizontal axis. The graph is a step function that starts at time zero and ordinate 1.0. It drops to value Sx at time x, where x is the time at the right end of an interval. Tic marks would be placed on the curve at 3, 8, and 12 months to represent the follow-up times of living patients. The step function can be extended horizontally out to 12 months to represent follow-up of the last patient, but the right-hand end of the curve usually is very imprecisely estimated, and concluding that a plateau exists at the level shown on the curve is often erroneous. TABLE 39.10

Kaplan-Meier Method for Estimating a Survival Distribution Censored During Interval wx

Died During Interval dx

Number at Risk Through Interval lx − wx

Proportion Dying dx / (lx − wx)

Proportion Surviving Interval px

Cumulative Proportion Surviving

Interval

Alive at Beginning of Interval lx

0–3

10

0

2

10

0.2

0.8

0.8

3–5

8

1

1

7

0.14

0.86

0.68

5–6

6

0

1

6

0.17

0.83

0.57

6–10

5

2

2

3

0.67

0.33

0.19

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For any time t, the Kaplan-Meier curve is an estimator of the true unknown value of S(t). The estimator is approximately normally distributed in large samples. If m patients remain alive at time x, the standard error of the estimate can be estimated44 as Ŝ(t)

, where Ŝ(t) denotes the Kaplan-Meier estimate at time t

and n(t) denotes the number of patients at risk for failure just before the failure at time t. The Kaplan-Meier estimate is based on the assumption that censoring is noninformative, which means that the censoring time is independent of the prognosis of the patient. Most censoring in a randomized clinical trial is “administrative censoring,” meaning that some patients are alive and still being followed at the time of analysis. This is noninformative censoring. However, if patients are lost to follow-up—if they fail to return to clinic when they are too sick to travel—then the censoring is informative and all the usual methods of survival analysis are invalidated. Consequently, it is essential to obtain follow-up information as completely as possible before analysis. If some patients have not been contacted for many months and their status is unknown, that information should be obtained before any analysis is performed. Examining the distribution of time since the last contact for patients not known to have died is a good way to examine the adequacy of follow-up. The issue of informative censoring also arises in considering end points other than death. For example, one may be attempting to estimate the distribution of time until tumor recurrence in the central nervous system (CNS) in a pediatric leukemia trial. How should one handle patients whose disease recurs in the marrow without evidence of CNS recurrence? One may be tempted to censor the time to CNS recurrence of such patients at their time of marrow recurrence, but that implicitly assumes that the censoring is noninformative. Because CNS and marrow recurrence may be biologically linked, the assumption of noninformative censoring may not be valid. Other issues of informative censoring can be similarly problematic. Clearly, one should not censor patients because of lack of compliance with therapy, as this can bias results.

Multiple Comparisons Table 39.11 shows the probability of obtaining one statistically significant (P < .05) difference by chance alone as a function of the number of independent comparisons of two equivalent treatments. With only five comparisons, the chance of at least one false-positive conclusion is 22.6%. When the number of end points, interim analyses, and patient subsets are considered in the analysis of clinical trials, these results are disturbing.101 The comparisons performed in clinical trials are not entirely independent, but this does not have much effect on ameliorating the problem. Fleming and Watelet102 performed a computer simulation to determine the chance of obtaining a statistically significant treatment difference when two equivalent treatments in six subsets determined by three dichotomous variables are compared. The chance of a statistically significant difference between treatments in at least one subset was 20% at the final analysis and 39% in the final or one of the three interim analyses. The primary end point should be defined in the protocol. Subset analyses and analyses with regard to secondary end points should be specified in advance, and statistical significance should be declared only for reduced significance levels defined in advance to limit the study-wise type I error to 5%. TABLE 39.11

Probability of Obtaining at Least One Statistically Significant (P, .05) Difference by Chance Along in Multiple Comparisons of Two Equivalent Treatments Percentage of Simulated Trials with at Least One “Significant” Difference (%)

Comparisons 1

5

2

9.7

3

14.3

4

18.5

5

22.6

10

40

20

64.1

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Approaches to subset analysis and multiple end point analysis using Bayesian methods have been described by Dixon and Simon103 and methods based on cross-validation are described by Freidlin et al.67 Qualitative interaction tests are described by Gail and Simon.104

REPORTING RESULTS OF CLINICAL TRIALS Effective reporting of results is an integral part of good research. Unfortunately, numerous reviews have indicated that the quality of reporting of clinical trial results is poor105,106; “often biased toward an exaggeration of treatment differences.” The guidelines summarized in Table 39.12 are adapted from those proposed by Simon and Wittes.107

FALSE-POSITIVE REPORTS IN THE LITERATURE Many of the positive results reported in the literature for small clinical trials are probably false-positive results.108–110 In 100 trials, suppose that there are 10 in which the experimental treatment is sufficiently better than the control such that there is a 90% chance of the difference being detected in a small or moderate-sized clinical trial. Of these 10 trials, obtaining a statistically significant difference is expected in 9. Of the remaining 90 trials, we assume that the treatments are approximately equivalent to the control. A statistically significant difference could be expected in 5% (4.5) of these. Hence, of the 13.5 (9 + 4.5) trials that yield statistically significant results, the finding is false positive in 4.5 or 33% of the cases. The 33% false discovery rate is striking but it depends on the assumption that only 10% of the trials study new treatments with large treatment effects. The Eastern Cooperative Oncology Group reported that about one-third of their phase III clinical trials resulted in statistically significant results.110 Assuming that most of these trials are conducted with 90% power and a 5% statistical significance level, the false-positive discovery rate is about 9%. An additional factor to consider is that of publication bias,111 which denotes the preference of journals to publish positive rather than negative results. A negative result may not be published at all, particularly from a small trial. If it is published, it is likely to appear in a less widely read journal than it would if the result were positive. TABLE 39.12

Summary of Guidelines for Reporting Clinical Trials107 Quality control of data and response evaluations should be discussed. All patients registered on study should be accounted for. Inevaluability rate for major end points should not exceed 15%. No exclusions of eligible patients in comparing outcomes by treatment group. The sample size should be large enough to establish or conclusively rule out effects of clinically important magnitude. Confidence limits for size of treatment versus control effectiveness should be given. Publication should provide protocol-specified sample size and interim analysis plan as well as actual timing of analyses. Claims of therapeutic effectiveness should not be based on phase II trials. Generalizability of conclusions should be carefully discussed. Subset-specific claims should be justified based on prospective planning and statistical control of study-wise type I error.

These observations emphasize that results in the medical literature often cannot always be accepted at face value. It is important to recognize that “positive” results need confirmation, particularly positive results of small studies, before they can be believed and applied to the general population.

META-ANALYSIS A meta-analysis is a quantitative summary of research on a topic. It is distinguished from the traditional literature review by its emphasis on quantifying results of individual studies and combining results across studies. Key components of this approach for therapeutics are to include only randomized clinical trials, to include all relevant randomized clinical trials that have been initiated (regardless of whether they have been published), to exclude no randomized patients from the analysis, and to assess therapeutic effectiveness based on the average results pooled

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across trials.112 Attention is restricted to randomized trials because the bias from nonrandomized comparisons may be larger than the small to moderate therapeutic effects likely to be present. Including all relevant randomized trials that have been initiated in a geographic area (e.g., the world, or the Americas and Europe) represents an attempt to avoid publication bias. Avoiding exclusion of any randomized patients also functions to avoid bias. Assessing therapeutic effectiveness based on average pooled results is an attempt to make the evaluation on the totality of evidence rather than on extreme isolated reports. In calculating average treatment effects, a measure of difference in outcome between treatments is calculated separately for each trial. For example, an estimate of the logarithm of the hazard ratio can be computed for each trial. A weighted average of these study-specific differences is then computed, and the statistical significance of this average is evaluated. This approach to meta-analysis requires access to individual patient data for all randomized patients in each trial. It also requires collaboration of the leaders of all the relevant trials and is very labor intensive. Nevertheless, it represents the gold standard for metaanalysis methodology. A major issue of concern in meta-analyses is whether the individual trials are sufficiently similar to make calculation of average effects medically meaningful. If the therapeutic interventions or control treatments differ too greatly or if the patient populations are too different, the results may not be medically meaningful as a basis for making treatment decisions for individual patients. Often in cancer therapeutics, the studies will not be identical in their treatment regimens or their patient populations, but they will not be so different as to make the results meaningless. In this case, the meta-analysis may be useful for answering important questions about a class of treatments that the individual trials cannot address reliably. For example, trials evaluating adjuvant treatment of primary breast cancer often are designed to detect differences in disease-free survival, and a meta-analysis is often required to evaluate survival. Similarly, subset analysis can usually be meaningfully evaluated only in the context of a meta-analysis because individual trials are not sized for this objective. Meta-analysis is not an alternative to properly designed and sized randomized clinical trials. Some have suggested that one need not be concerned about computing sample size in the traditional ways, as small, randomized trials can be pooled for meta-analysis. Because most investigators would prefer to “do their own thing,” this would lead to a proliferation of diverse trials of inconsequential individual size that may be too heterogeneous to permit a meaningful meta-analysis. Given that sufficient large, randomized clinical trials of very similar treatment regimens have been conducted, meta-analysis can provide supplemental information about a given class of treatments that is not available from the individual trials.

REFERENCES 1. Subramanian J, Simon R. Gene expression-based prognostic signatures in lung cancer: ready for clinical use? J Natl Cancer Inst 2010;102(7):464–474. 2. Green S, Benedetti J, Crowley J. Clinical Trials in Oncology. 2nd ed. London: Chapman & Hall/CRC Press; 2003. 3. Leventhal BG, Wittes RE. Research Methods in Clinical Oncology. New York: Raven Press; 1988. 4. Eisenhauer EA, O’Dwyer PJ, Christian M, et al. Phase I clinical trial design in cancer drug development. J Clin Oncol 2000;18(3):684–692. 5. Simon R, Freidlin B, Rubinstein L, et al. Accelerated titration designs for phase I clinical trials in oncology. J Natl Cancer Inst 1997;89(15):1138–1147. 6. Dancey J, Freidlin B, Rubinstein LV. Accelerated titration designs. In: Chevret S, ed. Statistical Methods in DoseFinding Experiments. New York: Wiley; 2006:91–114. 7. Heath EI, LaRusso PM, Ivy SP, et al. Theoretical and practical application of traditional and accelerated titration phase I clinical trial designs: the Wayne State Experience. J Biopharm Stat 2009;19(3):414–423. 8. O’Quigley J, Pepe M, Fisher L. Continual reassessment method: a practical design for Phase I clinical trials. Biometrics 1990;46(1):33–48. 9. Babb J, Rogatko A, Zacks S. Cancer phase I clinical trials: efficient dose escalation with overdose control. Stat Med 1998;17(10):1103–1120. 10. Goodman SN, Zahurak ML, Piantadosi S. Some practical improvements in the continual reassessment method for phase I studies. Stat Med 1995;14(11):1149–1161. 11. Moller S. An extension of the continual reassessment methods using a preliminary up-and-down design in a dose finding study in cancer patients, in order to investigate a greater range of doses. Stat Med 1995;14(9–10):911–922. 12. Rahma OE, Gammoh E, Simon RM, et al. Is the “3+3” dose escalation phase 1 clinical trial design suitable for therapeutic cancer vaccine development? A recommendation for an alternative design. Cancer Res

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2014;20(18):4758–4767. 13. Korn EL, Rubinstein LV, Hunsberger SA, et al. Clinical trial designs for cytostatic agents and agents directed at novel molecular targets. In: Adei AA, Buolamwini JK, eds. Strategies for Discovery and Clinical Testing of Novel Anticancer Agents. Amsterdam: Elsevier; 2004:366–380. 14. Kummar S, Kinders R, Rubinstein L, et al. Compressing drug development timelines in oncology using phase “0” trials. Nat Rev Cancer 2007;7(2):131–139. 15. Rubinstein LV, Steinberg SM, Kummar S, et al. The statistics of phase 0 trials. Stat Med 2010;29(10):1072–1076. 16. Karapetis CS, Khambata-Ford S, Jonker DJ, et al. K-ras mutations and benefit from cetuximab in advanced colorectal cancer. N Engl J Med 2008;359(17):1757–1765. 17. Pusztai L, Anderson K, Hess KR. Pharmacogenomic predictor discovery in phase II clinical trials for breast cancer. Clin Cancer Res 2007;13(20):6080–6086. 18. LeBlanc M, Rankin C, Crowley J. Multiple histology phase II trials. Clin Cancer Res 2009;15(13):4256–4262. 19. Dobbin KK, Zhao Y, Simon RM. How large a training set is needed to develop a classifier for microarray data? Clin Cancer Res 2008;14(1):108–114. 20. Eisenhauer EA, Therasse P, Bogaerts J, et al. New response evaluation criteria in solid tumors: revised RECIST guideline (version 1.1). Eur J Cancer 2009;45(2):228–247. 21. Simon R. Optimal two-stage designs for phase II clinical trials. Control Clin Trials 1989;10(1):1–10. 22. Simon R. Genomic driven clinical trials in oncology. Annals of Internal Medicine 2016;165(4):270–278. 23. Cunanan KM, Iasonos A, Shen R, et al. An efficient basket trial design. Statistics in Medicine 2017;36(10):1568– 1579. 24. Simon R, Geyer S, Subramanian J, et al. The Bayesian basket design for genomic variant driven phase II trials. Semin Oncology 2016;43(1):13–18. 25. Seymour L, Ivy SP, Sargent D, et al. The design of phase II clinical trials testing cancer therapeutics: consensus recommendations from the clinical trial design task force of the National Cancer Institute investigational drug steering committee. Clin Cancer Res 2010;16(6):1764–1769. 26. Vidauurre T, Wilkerson J, Simon R, et al. Stable disease is not preferentially observed with targeted therapies and as currently defined has limited value in drug development. Cancer J 2009;15(5):366–373. 27. El-Maraghi RH, Eisenhauer EA. Review of phase II trial designs used in studies of molecular targeted agents: outcomes and predictors of success in phase III. J Clin Oncol 2008;26(8):1346–1354. 28. Korn EL, Freidlin B. Conditional power calculations for clinical trials with historical controls. Stat Med 2006;25(17):2922–2931. 29. Thall PF, Simon R, Estey E. New statistical strategy for monitoring safety and efficacy in single-arm clinical trials. J Clin Oncol 1996;14(1):296–303. 30. Estey EH, Thall PF. New designs for phase 2 clinical trials. Blood 2003;102(2):442–448. 31. Korn EL, Liu PY, Lee SJ, et al. Meta-analysis of phase II cooperative group trials in metastatic stage IV melanoma to determine progression-free and overall survival benchmarks for future phase II trials. J Clin Oncol 2008;26(4):527–534. 32. Mick R, Crowley JJ, Carroll RJ. Phase II clinical trial design for nontoxic anticancer agents for which time to disease progression is the primary endpoint. Control Clin Trials 2000;21(4):343–359. 33. Seymour L. The design of clinical trials for new molecularly targeted compounds: progress and new initiatives. Curr Pharm Des 2002;8(25):2279–2284. 34. Korn EL, Arbuck SG, Pluda JM, et al. Clinical trial designs for cytostatic agents: are new approaches needed? J Clin Oncol 2001;19(1):265–272. 35. Rubinstein LV, Korn EL, Freidlin B, et al. Design issues of randomized phase 2 trials and a proposal for phase 2 screening trials. J Clin Oncol 2005;23(28):7199–7206. 36. Rosner G, Stadler W, Ratain M. Randomized discontinuation design: application to cytostatic antineoplastic agents. J Clin Oncol 2002;20(22):4478–4484. 37. Freidlin B, Simon R. An evaluation of the randomized discontinuation design. J Clin Oncol 2005;23:1–5. 38. Hong F, Simon R. Run-in phase III trial designs with pharmacodynamic predictive biomarkers. J Natl Cancer Inst 2013;105(21):1628–1633. 39. Temple RJ. Special study designs: early escape, enrichment, studies in non-responders. Commun Stat Theory Methods 1994;23:499–531. 40. Hunsberger S, Zhao Y, Simon R. A comparison of phase II study strategies. Clin Cancer Res 2009;15(19):5950– 5955. 41. Goldman B, LeBlanc M, Crowley J. Interim futility analysis with intermediate endpoints. Clin Trials

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2008;5(1):14–22. 42. Thall PF. A review of phase 2-3 clinical trial designs. Lifetime Data Anal 2008;14(1):37–53. 43. Sher HI, Heller G. Picking the winners in a sea of plenty. Clin Cancer Res 2002;8(2):400–404. 44. Thall PF, Simon R, Ellenberg SS. Two-stage selection and testing designs for comparative clinical trials. Biometrika 1988;75:303–310. 45. Parmar MK, Barthel FM, Sydes M, et al. Speeding up the evaluation of new agents in cancer. J Natl Cancer Inst 2008;100(17):1204–1214. 46. Berry SM, Connor JD, Lewis RJ. The platform trial: an efficient strategy for evaluating multiple treatments. JAMA 2015;313:1619–1620. 47. Freidlin B, Korn EL, Gray R, et al. Multi-arm clinical trials of new agents: some design considerations. Clin Cancer Res 2008;14(14):4368–4371. 48. Freidlin B, McShane LM, Polley MY, et al. Randomized phase II trial designs with biomarkers. J Clin Oncol 2012;30(26):3304–3309. 49. Simon R. Randomized clinical trials. Principles and obstacles. Cancer 1994;74(9 Suppl):2614–2619. 50. Torri V, Simon R, Russek-Cohen E, et al. Relationship of response and survival in advanced ovarian cancer patients treated with chemotherapy. J Natl Cancer Inst 1992;84(6):407–414. 51. Buyse M, Molensberghs G, Burzykowski T, et al. The validation of surrogate endpoints in meta-analyses of randomized experiments. Biostatistics 2000;1(1):49–67. 52. Daniels MJ, Hughes MD. Meta-analysis for the evaluation of potential surrogate markers. Stat Med 1997;16(17):1965–1982. 53. Korn EL, Albert PS, McShane LM. Assessing surrogates as trial endpoints using mixed models. Stat Med 2004;24(2):163–182. 54. Buyse M, Sargent DJ, Grothey A, et al. Biomarkers and surrogate endpoints—the challenge of statistical validation. Nat Rev Clin Oncol 2010;7(6):309–317. 55. Simon R. An agenda for clinical trials: clinical trials in the genomic era. Clin Trials 2004;1(5):468–470. 56. Simon R. A roadmap for developing and validating therapeutically relevant genomic classifiers. J Clin Oncol 2005;23(29):7332–7341. 57. Simon R. New challenges for 21st century clinical trials. Clin Trials 2007;4(2):167–169, 173–177. 58. Simon R, Maitournam A. Evaluating the efficiency of targeted designs for randomized clinical trials. Clin Cancer Res 2005;10:6759–6763. 59. Simon R, Maitournam A. Evaluating the efficiency of targeted designs for randomized clinical trials. Erratum. Clin Cancer Res 2006;12:3229. 60. Hoering A, LeBlanc M, Crowley J. Randomized phase III clinical trial designs for targeted agents. Clin Cancer Res 2008;14(14):4358–4367. 61. Mandrekar SJ, Sargent DJ. Clinical trial designs for predictive biomarker validation: theoretical considerations and practical challenges. J Clin Oncol 2009;27(24):4027–4034. 62. Simon RM. Genomic Clinical Trials and Predictive Medicine. Cambridge, United Kingdom: Cambridge University Press; 2013. 63. Freidlin B, Sun Z, Gray R, et al. Phase III clinical trials that integrate treatment and biomarker evaluation. J Clin Oncol 2013;31(25):3158–3161. 64. Freidlin B, McShane LM, Korn EL. Randomized clinical trials with biomarkers: design issues. J Natl Cancer Inst 2010;102(3):152–160. 65. Jiang W, Freidlin B, Simon R. Biomarker adaptive threshold design: a procedure for evaluating treatment with possible biomarker-defined subset effect. J Natl Cancer Inst 2007;99(13):1036–1043. 66. Freidlin B, Simon R. Adaptive signature design: an adaptive clinical trial design for generating and prospectively testing a gene expression signature for sensitive patients. Clin Cancer Res 2005;11(21):7872–7878. 67. Freidlin B, Jiang W, Simon R. The cross-validated adaptive signature design for predictive analysis of clinical trials. Clin Cancer Res 2010;16(2):691–698. 68. Simon R, Simon N. Adaptive enrichment designs for clinical trials. Biostatistics 2013;14(4):613–625. 69. Simon RM, Paik S, Hayes DF. Use of archived specimens in evaluation of prognostic and predictive biomarkers. J Natl Cancer Inst 2009;101(21):1–7. 70. Simon R. Stratification and partial ascertainment of biomarker value in biomarker driven clinical trials. J Biopharm Stat 2014;24(5):1011–1021. 71. Pocock S, Simon R. Sequential treatment assignment with balancing for prognostic factors in the controlled clinical trial. Biometrics 1975;31(1):103–115.

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72. Kalish LA, Begg CB. Treatment allocation methods in clinical trials: a review. Stat Med 1985;4(2):129–144. 73. Simon R, Simon N. Using randomization tests to preserve type I error with response-adaptive and covariateadaptive randomization. Stat Probab Lett 2011;81(7):767–772. 74. Rubinstein L, Gail M, Santner T. Planning the duration of a comparative clinical trial with loss to follow-up and a period of continued observation. J Chronic Dis 1981;34(9–10):469–479. 75. Simon R, Freedman LS. Bayesian design and analysis of 2 by 2 factorial clinical trials. Biometrics 1997;53(2):456– 464. 76. Simon R. Confidence intervals for reporting results from clinical trials. Ann Intern Med 1986;105(3):429–435. 77. Makuch R, Simon R. Sample size requirements for evaluating a conservative therapy. Cancer Treat Rep 1978;62(7):1037–1040. 78. Durrlemann S, Simon R. Planning and monitoring of equivalence studies. Biometrics 1990;46:329–336. 79. Simon R. Bayesian design and analysis of active control clinical trials. Biometrics 1999;55(2):484–487. 80. Spiegelhalter DJ, Freedman LS, Parmar MK. Bayesian approaches to randomized trials. J R Stat Soc Series A General 1994;157:357–387. 81. Simon R. Bayesian subset analysis: application to studying treatment-by-gender interactions. Stat Med 2002;21(19):2909–2916. 82. Rubin DB. Bayesian inference for causal effects: the role of randomization. Ann Stat 1978;6:34–58. 83. Simon N, Simon R. Using Bayesian modeling in frequentist adaptive enrichment designs. Biostatistics 2018;19(1):27–41. 84. Peto R, Pike MC, Armitage P, et al. Design and analysis of randomized clinical trials requiring prolonged observation of each patient. II. Analysis and examples. Br J Cancer 1977;35(1):1–39. 85. Barr J, Tannock I. Analyzing the same data two ways: a demonstration model illustrate the reporting and misreporting of clinical trials. J Clin Oncol 1989;7(7):969–978. 86. Tannock I, Murphy K. Reflections on medical oncology: an appeal for better clinical trials and improved reporting of their results. J Clin Oncol 1983;1(1):66–70. 87. Randomised trial of IV streptokinase, oral aspirin, both or neither among 17187 cases of suspected acute myocardial infarction: ISIS-2. ISIS-2 (Second International Study of Infarct Survival) Collaborative Group. Lancet 1988;2(8607):349–360. 88. Fleming TR, Green SJ, Harrington DP. Considerations of monitoring and evaluation treatment effects in clinical trials. Control Clin Trials 1984;5(1):55–66. 89. Ellenberg S, Fleming TR, DeMets D. Data Monitoring Committees in Clinical Trials: A Practical Perspective. Hoboken, NJ: Wiley; 2002. 90. Smith M, Ungerleider R, Korn E, et al. The role of independent data monitoring committees in randomized clinical trials sponsored by the National Cancer Institute. J Clin Oncol 1997;15(7):2736–2743. 91. Haybittle JL. Repeated assessment of results in clinical trials of cancer treatment. J Radiol 1971;44(526):793–797. 92. O’Brien PC, Fleming TR. A multiple testing procedure for clinical trials. Biometrics 1979;35(3):549–556. 93. Fleming TR, Harrington DP, O’Brien PC. Designs for group sequential tests. Control Clin Trials 1984;5(4):348– 361. 94. Korn EL, Freidlin B, Mooney M. Stopping or reporting early for positive results in randomized clinical trials: the National Cancer Institute Cooperative Group experience from 1990 to 2005. J Clin Oncol 2009;27(10):1712–1721. 95. Freidlin B, Korn EL. Monitoring for lack of benefit: a critical component of a randomized clinical trial. J Clin Oncol 2009;27(4):629–633. 96. DeMets DL. Futility approaches to interim monitoring by data monitoring committees. Clin Trials 2006;3(6):522– 529. 97. Lan KKG, Simon R, Halperin M. Stochastically curtailed test in long-term clinical trials. Commun Stat Seqen Anal 1982;1:207–219. 98. Berkson J, Gage RP. Calculation of survival rates for cancer. Proc Staff Meet Mayo Clin 1950;25(11):270–286. 99. Cutler SJ, Ederer F. Maximum utilization of the life table method in analyzing survival. J Chronic Dis 1958;8(6):699–712. 100. Kaplan EI, Meier P. Nonparametric estimation from incomplete observations. J Am Stat Assoc 1958;53:457–481. 101. Tannock IF. False-positive results in clinical trials: multiple significance tests and the problem of unreported comparisons. J Natl Cancer Inst 1996;88(3–4):206–207. 102. Fleming TR, Watelet L. Approaches to monitoring clinical trials. J Natl Cancer Inst 1989;81(3):188–193. 103. Dixon DO, Simon R. Bayesian subset analysis. Biometrics 1991;47(3):871–881. 104. Gail M, Simon R. Testing for qualitative interactions between treatment effects and patient subsets. Biometrics

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1985;41:361–372. 105. Begg CB. Quality of clinical trials. Ann Oncol 1990;1(5):319–320. 106. Pocock SJ, Hughes MD, Lee RJ. Statistical problems in the reporting of clinical trials: a survey of three medical journals. N Engl J Med 1987;317(7):426–432. 107. Simon R, Wittes RE. Methodologic guidelines for reports of clinical trials. Cancer Treat Rep 1985;69(1):1–3. 108. Simon R. Randomized clinical trials and research strategy. Cancer Treat Rep 1982;66(5):1083–1087. 109. Simon R. Commentary on “Clinical trials and sample size considerations: another perspective.’ ’ Stat Sci 2000;15:95–110. 110. Ioannidis JP. Why most published research findings are false. PLoS Med 2005;2:696–701. 111. Begg CB, Berlin JA. Publication bias and dissemination of clinical research. J Natl Cancer Inst 1989;81(2):107– 115. 112. Collins R, Gray R, Godwin J, et al. Avoidance of large biases and large random errors in the assessment of moderate treatment effects: the need for systematic overviews. Stat Med 1987;6(3):245–254. 113. Pocock SJ. Group sequential methods in the design and analysis of clinical trials. Biometrika 1977;64:191–999.

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40

Assessment of Clinical Response Susan Bates and Tito Fojo

INTRODUCTION The modern era of drug development began in 1976 when 16 experienced oncologists treating lymphoma gathered to decide what would be considered a reliable measure of response to a therapy.1 Using calipers or rulers, the oncologists measured spheres and decided that a 50% size difference in the product of the perpendicular diameters was required to reduce the error rate in detection to approximately 5%. It was from this auspicious beginning that our current methodologies of response assessment evolved. A key principle in drug development is that the benefit sought in oncology is first and foremost increased overall survival (OS). It is thus important to note that the decision to use a 50% reduction in the product of the perpendicular diameters as a measure of response was made to reduce error and not because it represented a value that conferred benefit. But as we discuss in the following text, that value and those derived from it are often barometers of benefit.

From Calipers and Rulers in Lymphoma to Diagnostic Imaging and the Bidimensional World Health Organization Criteria and the One-Dimensional Response Evaluation Criteria in Solid Tumors In 1981, 5 years after the rationale for accepting a 50% decrease in the product of the perpendicular diameters as a measure of response was published,1 Miller et al.2 reported the recommendations from a World Health Organization (WHO) initiative to develop standardized approaches for the “reporting of response, recurrence and disease-free interval.” In concordance with the 1976 recommendations, the WHO criteria recommended malignant disease be “measured in two dimensions by ruler or caliper with surface area determined by multiplying the longest diameter by the greatest perpendicular diameter.” Furthermore, complete response (CR) was defined as the disappearance of all known disease, determined by two observations not less than 4 weeks apart, whereas a designation of a partial response (PR) was assigned if there occurred a “50% decrease in the sum of the products of the perpendicular diameters of the multiple lesions” by “two observations not less than four weeks apart.” Thus, the 50% reduction initially chosen as an “operationally” reliable value became institutionalized as the threshold for declaring efficacy in the majority of cancers. This measure of efficacy was perpetuated when in 2000 a recommendation was made to replace the WHO criteria with the now widely used Response Evaluation Criteria in Solid Tumors (RECIST).3 The authors noted, “The definition of a partial response, in particular, is an arbitrary convention—there is no inherent meaning for an individual patient of a 50% decrease in overall tumor load.” Nevertheless, the threshold chosen, a 30% reduction in one dimension, was comparable, indeed almost indistinguishable, to the 50% decrease in the sum of the products of the perpendicular diameters and thus perpetuated the 1976 standard. Table 40.1 compares the WHO criteria2 with those of RECIST 1.03 and RECIST 1.1,4 whereas Figure 40.1 provides a visual presentation of the RECIST thresholds required to qualify as response or progression. Whereas the response threshold in RECIST was similar to that in the WHO criteria, the threshold for progression in RECIST allowed for more progression before treatment failure is declared.

ASSESSING RESPONSE Response Evaluation Criteria in Solid Tumors 1.1

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A decade of experience with WHO and RECIST 1.0 prompted an update in 2009, known as RECIST 1.1, with differences highlighted in Table 40.1. Specific RECIST 1.1 changes include establishment of a 1-cm lesion as the minimum measurable, reduction in the required number of lesions to be measured to a total of five (two lesions per organ), and clarification that lymph nodes 30% or appearance of new FDG-avid lesions

CA 125, cancer antigen 125; GCIG, Gynecologic Cancer Intergroup; ULN, upper limit of normal; PSA, prostate-specific antigen; PCWG3, Prostate Cancer Working Group 3; DT, doubling time; hCG, human chorionic gonadotropin; AFP, α-fetoprotein; CT, computed tomography; GIST, gastrointestinal stromal tumor; PR, partial response; FDG, fluorodeoxyglucose; PET, positron emission tomography; EORTC, European Organization for the Research and Treatment of Cancer; SUV, standardized uptake value; CMR, complete metabolic response; PMR, partial metabolic response; SMD, stable metabolic disease; PMD, progressive metabolic disease; PERCIST, PET Response Criteria in Solid Tumors; SUL, SUV normalized to lean body mass.

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GIST and hepatocellular carcinoma (HCC) can have a biologic response but minimal tumor shrinkage and thus present challenges when assessed using RECIST. GIST may remain unchanged in size after treatment while the center of the tumor mass undergoes necrosis, with progression occurring in the rim.25 An alternate assessment approach, the Choi criteria, defines a response in GIST as either a decrease in the sum of longest diameters of ≥10% or a decrease in tumor density of ≥15% (see Table 40.2).26 These thresholds, although validated by others, have been critiqued for scoring as “responders” tumors that would be considered to be stable by conventional RECIST and for defining progression too early at a 10% increase.27 Although valuable, the technical complexity of and difficulty in reproducing the Choi criteria have precluded its widespread acceptance.28,29 HCCs are often treated with locoregional therapy with the goal of producing tumor necrosis, and treatment failure often occurs in surviving viable tumor.30 In HCC, discrimination of response can be obtained by Choi criteria or by measurement of the arterially enhancing regions of tumor.30,31 Ultimately, volumetric measurements may overtake tumor assessment strategies for difficult tumors such as GIST and HCC.29

Fluorodeoxyglucose Positron Emission Tomography Regulatory approvals of new agents have focused on response assessments by WHO, RECIST, or IWG criteria, with FDG-PET used at most as an adjunct to those standardized criteria. Although FDG uptake is a powerful diagnostic tool and is strongly correlated with tumor activity, it has limitations, including variable FDG avidity in tumors; variation due to patient activity, carbohydrate intake, blood glucose, and timing; and benign sources of uptake, including inflammatory and postsurgical sites (see Table 40.2). Two main methods of quantitating FDGPET uptake and assessing response have been proposed, the European Organization for Research and Treatment of Cancer (EORTC) criteria and PET Response Criteria in Solid Tumors (PERCIST).32,33 Both define four response categories. PERCIST uses standardized uptake values (SUV) corrected for lean body mass (SUL), and studies have suggested excellent concordance.34

Pathologic Complete Response in Breast Cancer One unique response end point is the assessment of breast cancer treated in the neoadjuvant setting. The purpose of neoadjuvant therapy is to improve survival, render locally advanced cancer amenable to surgery, or aid in breast conservation. In that setting, the absence of cancer cells in resected breast tissue has been used to define a pathologic complete response (pCR). The pCR rate has been proposed as a surrogate end point for event-free survival (EFS) or OS to support approval of new agents or combinations of agents tested in clinical trials.35 In a pooled analysis of 11,955 patients enrolled on 12 neoadjuvant trials, individual patients with pCR had improved EFS and OS.36 However, at the trial level, pCR rates did not correlate with EFS or OS, a problem likely due to heterogeneity of breast cancer subtypes among the trials. Despite this, pCR rates were used to support the approval of pertuzumab and trastuzumab in the neoadjuvant setting.36,37

Serum Biomarker Levels Biomarkers have been developed for multiple purposes, including assessment of prognosis, early detection of recurrence, and monitoring response to therapy (see Table 40.2). Although widely used in oncology, they are not thought to have the precision of tumor measurements.38 In addition to issues regarding sensitivity and specificity, their impact is limited by the quality of available therapies, so that biomarkers are of little value without highly effective primary and salvage therapies. For example, in asymptomatic patients with ovarian cancer whose only evidence of disease progression is an isolated rise in cancer antigen 125 (CA 125), nothing is gained by instituting treatment before there is other evidence of progression.39 As noted by Karam and Karlan,40 the results highlight “the need for improved salvage therapies for recurrent ovarian cancer.” CA 125: Despite its recognized limitations, CA 125 is used widely. For example, the Gynecologic Cancer Intergroup criteria have evolved to help determine whether a patient’s tumor has responded to therapy.41,42 Consistently, the fraction of patients scored as having a tumor response using CA 125 criteria, defined as a 50% decline from baseline, is higher than the response defined by RECIST—a not surprising finding because a 30% decrease in RECIST represents a 65% decrease in tumor volume and is thus a more stringent response threshold. Progression is defined as an increase in CA 125 to more than two times the nadir value on two occasions, in this case a higher and more generous threshold than RECIST, where a 73% increase in volume qualifies as progression. PSA: PSA has been extensively studied for its ability to report patient outcomes. As noted earlier, PSA has

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been incorporated into PCWG guidelines, with a 25% increase confirmed in a second measurement indicative of disease progression.24 PSA doubling times correlate with OS in the absence of therapy but are not used in response assessment.43 Human chorionic gonadotropin (hCG) and α-fetoprotein (AFP): Because testicular cancer is a highly curable disease with validated biomarkers, outcome assessment has focused on the rapid identification of patients whose tumors have a poor response to therapy. Because both markers have relatively short half-lives (1 to 2 days for hCG and 5 to 7 days for AFP), the rate of decline can be calculated and correlated with outcome.44,45 Nonetheless, the 2010 American Society of Clinical Oncology (ASCO) guidelines on serum tumor markers concluded there was still insufficient evidence to recommend changing therapy solely based on a slow marker decline.46 Increasing levels after two cycles (early increases can be due to tumor lysis) may indicate a need to change therapy. The markers are used in staging, prognosis, and surveillance after surgical resection.44 Carcinoembryonic antigen (CEA): Since its discovery in 1965, CEA has been extensively studied for its ability to detect recurrence after curative resection and to monitor treatment. In general, an increasing CEA indicates disease progression.47,48 Carbohydrate antigen 19-9 (CA 19-9): This marker is used primarily in the clinical management of pancreatic cancer. Although very sensitive to changes in tumor burden, ductal obstruction can cause falsepositive elevation. There are no guidelines on use in clinical trial assessment.48,49

Circulating Tumor DNA and Circulating Tumor Cells CTCs, which compose about one in a billion blood cells, are understood as the mechanism whereby tumors metastasize, and high levels or clusters of cells portend a poor outcome. Multiple different methodologies are in development for CTC detection, and the CellSearch assay (Menarini Silicon Biosystems, Huntington Valley, PA) was cleared by the FDA for assessment of prognosis in patients with breast, colorectal, and prostate cancer.50,51 Although CTC levels ≥5 per 7.5 mL portend a poor prognosis, changing therapy based on CTC levels has not been shown to improve outcome. The PCWG3 noted that changes in CTC number from unfavorable (five or more cells) to favorable could be used as a clinical trial end point.24 Originally described in 1948, the presence of DNA within the noncellular fraction of peripheral blood, termed cell-free DNA (cfDNA),52 was followed 30 to 35 years later by reports of elevated cfDNA within the serum of cancer patients,53,54 with a fraction derived from the tumor. Definitive proof that tumor cells were contributing to cfDNA came with detection of DNA harboring mutated KRAS and NRAS in the plasma of patients with pancreatic cancer55 and acute myeloid leukemia,56 respectively. This led to coinage of the term circulating tumor DNA (ctDNA) to describe cfDNA fragments released into the bloodstream from tumor cells and raised hopes that a simple blood test could define success or failure of a cancer treatment. ctDNA retains single nucleotide variants (SNVs), insertions, deletions, large chromosomal alterations, and aberrant epigenetic changes observed in tumors. Depending on factors including tumor burden and biology, the fraction of cfDNA derived from a tumor varies from 0.1% to 90%,57 with the fraction from residual disease as low as 0.001% of cfDNA. The latter makes the lower limit of detection (LLOD) a critical feature of ctDNA detection methods to be used for tumor surveillance. ctDNA quantification by polymerase chain reaction (PCR) is ideal when investigating known or recurrent mutations, but PCR approaches underperform with infrequent or unknown mutations. For the latter, whole-genome sequencing of plasma cfDNA is possible but lacks sufficient sensitivity at practical costs and is thus prohibitive for routine clinical use. These limitations have led to a focus on the ubiquitously altered epigenetic landscape of tumors. Hypermethylation of CpG islands (CGIs) and global hypomethylation commonly occur, are quite stable, and are potentially quantifiable.58 Rigorously validated, prospective clinical studies assessing ctDNA-based disease surveillance should eventually lead to regulatory approvals and their adaptation in the community.

DETERMINING OUTCOME The response measures described earlier quantitate tumor burden. What happens after those data are obtained varies depending on the clinical setting. In the community, less emphasis is placed on strict criteria. In the setting of a clinical trial, tumor size is measured and the response categorized. For FDA submission, these are but factors in the risk–benefit equation needed for drug approvals. The FDA conveys full approval to new agents based on

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true clinical benefit, such as an improvement in a survival end point or symptom relief.59 Depending on the setting, surrogates for clinical benefit such as response rate may support either regular or accelerated approval.

Overall Response Rate and Stable Disease Overall response rate (ORR) is the fraction of patients with a tumor size reduction of a predefined amount for a minimum time period. The FDA has generally defined ORR as the sum of PRs and CRs. Although OS remains the gold standard, ORR and its allied end points (duration of response [DOR] and PFS) have been advocated as surrogates of antitumor efficacy. Although standardized definitions of response evolved from the original exercise on tumor measurements, studies have shown that ORR (often) correlates with OS, although ORR usually explains only a fraction of the variability of the survival benefits.60–62 Equally important is the duration of response, a value that is measured from the time of initial response until documented tumor progression. What has been more difficult is the significance of stable disease (SD), which is defined as shrinkage that qualifies as neither response nor progression. The FDA has not been willing to include SD as part of the ORR because it is often indicative of the underlying disease biology rather than a drug’s therapeutic effect.59,63 Nevertheless, investigators increasingly use the term clinical benefit rate (CBR) to include CR + PR + SD. This represents a misuse of the term clinical benefit because CR, PR, and SD are objective tumor findings that do not address the true clinical benefit of a therapy. Although it is tempting to assign a clinical benefit to a reduction in tumor size or SD, in fact, there is no evidence of such. Clinical benefit was originally delineated to assess the benefit of gemcitabine in pancreatic cancer, using a composite of measurements of pain (analgesic consumption and pain intensity), Karnofsky performance status, and weight.64 Clinical benefit in pancreatic cancer required a sustained (≥4 weeks) improvement in at least one parameter without worsening in any others. CBR and its twin, disease control rate (DCR), have exaggerated efficacy in many settings. In more than 140 phase II clinical trials with either cytotoxic or targeted therapies, SD rates did not correlate with either PFS or OS.56 In addition, SD was not defined in nearly 80% of these trials. Failing the “clear communication between investigators” test for clinical trial end points,65 SD should not be used as a response end point in the absence of standardized definitions that are shown to effect meaningful changes in clinical outcome. Indeed, the FDA assesses new drug applications for demonstration of “benefit,” generally defined as OS or, in some cases, PFS, reduced by a quantitative assessment of toxicity.59,66,67

Progression-Free Survival, Time to Progression, and Time to Treatment Failure In cancer drug development, one usually finds ORR assessed as an indicator of activity in phase II trials, whereas randomized phase III trials rely on other end points such as PFS and time to progression (TTP) (Table 40.3). Although PFS and TTP attempt to assess efficacy in close proximity to a therapy, they score outcomes differently and are not interchangeable. TTP is defined as the time from randomization to the time of disease progression.59 In TTP analyses, deaths are censored either at the time of death or at an earlier visit. In contrast, PFS is defined from the time of randomization to the time of disease progression or death. Although both analyses censor patients discontinuing trial participation for adverse events, patients dying on study are censored only in TTP analyses. Those favoring PFS argue that in some cases, death might be an adverse effect of the therapy and that a proper assessment of efficacy should consider such severe toxicities. Although many have argued that PFS and TTP should be acceptable end points for cancer clinical trials, in the majority of tumors, there is no convincing evidence that PFS is a surrogate for OS, and in those in whom there is some evidence, its value is arguable.68 The lack of a reliable definition of progression, investigator bias, ascertainment bias, and censoring, depicted in Figure 40.2, can also impact outcomes. An alternate end point is time to treatment failure (TTF), a composite end point measuring time from randomization to discontinuation of treatment for any reason, including disease progression, treatment toxicity, or death. Although the FDA has not recommended TTF as a regulatory end point for drug approval, the high rates of censoring due to toxicity seen in phase III clinical trails should lead to a reassessment of this position, given that most can agree that efficacy and tolerability are important and TTF captures both of these attributes.

Overall Survival Defined as the time from randomization to death, OS has been considered the gold standard of clinical trial end points, in part because it is unambiguous and does not suffer from interpretation bias (see Table 40.3). An additional advantage of the survival end point is that it can balance the effect of therapies with high treatment-

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related mortality even if tumor control is substantially better with the new treatment. However, some worry the results may be confounded by subsequent therapies. The latter concern is often cited as the reason for why an advantage in PFS or TTP “disappears” when one looks at OS. However, as a review of clinical trials confirms,69 the magnitude of the difference does not disappear, only the statistical validity. A clear example is seen in the use of ixabepilone plus capecitabine in metastatic breast cancer where a 1.6-month PFS advantage “disappeared” as a 1.8-month OS advantage.70 When evaluating a randomized controlled trial, it is important that the OS and PFS analyses are always by intention to treat (ITT). In an ITT analysis, often described as “once randomized, always analyzed,” all patients assigned to a group at the time of randomization are analyzed regardless of what occurred subsequently.71 An ITT analysis avoids the bias introduced by omitting dropouts and noncompliant patients, which can negate randomization and overestimate clinical effectiveness.

Kaplan-Meier Plots In a typical clinical trial, data are often presented as a Kaplan-Meier plot. In discrete time intervals, the number of patients in each group who are progression free and alive (PFS analysis) or alive (OS analysis) at the end of the interval are counted and divided by the total number of patients in that group at the beginning of the time interval. One excludes from this calculation patients censored for a reason other than PD or death during the same interval. This has the advantage that it allows one to include censored patients in estimates of the probability of PFS or OS up to the point when they were censored; they are excluded only beyond the point of censoring. In constructing the Kaplan-Meier plot, probabilities are calculated for each interval of time. The probability of surviving “progression free” or being counted as a “survivor” to the end of any interval of assessment is the product of the probabilities of surviving in all the preceding assessment intervals multiplied by the probability for the interval of interest. One might ask to what extent the two curves in each study differ. One measure that is of value is the median PFS or OS, a value calculated in most studies from a Kaplan-Meier plot. TABLE 40.3

A Comparison of Important Cancer Approval End Points Regulatory Evidence

End Points

Clinical benefit used for regular approvals

Overall survival (OS)

Universally accepted direct measure of clinical benefit Easily measured Includes treatment-related mortality that can obscure benefit in a subset Precisely measured; unambiguous Not dependent on assessment intervals

May require a larger sample size May require longer follow-up May be affected by crossover and/or sequential therapies Includes noncancer deaths Requires randomized controlled trials

Symptom end points (patient-reported outcomes)

Patient perspective of direct clinical benefit

Blinding is often difficult Data are often missing or incomplete Clinical significance of small changes is unknown Multiple analyses Lack of validated instruments

Disease-free survival (DFS)

Smaller sample size and shorter follow-up necessary compared with survival end point

Not statistically validated as surrogate for survival in all settings Not precisely measured; subject to assessment bias, particularly in openlabel studies Definitions vary among studies

Objective response rate (ORR)

Can be assessed in single-arm studies Assessed earlier and in smaller studies compared with survival end point

Not a direct measure of benefit in all cases; uncertain correlation between response and clinical benefit Not a comprehensive measure of drug activity

Surrogates used for accelerated approvals or regular approvals

Advantages

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Disadvantages

Effect attributable to drug, not inherent tumor biology Early end point, often reached within months of initiating treatment Definition of progressive disease identifies uniform time to end treatment and capture data Complete response (CR)

Durable complete responses can represent clinical benefit

Progression-free survival (PFS) or time to progression (TTP)a

Smaller sample size and shorter follow-up necessary compared with OS end point Measurement of stable disease included Not confounded by crossover or subsequent therapies Generally based on objective and quantitative assessment

Only a subset of patients who benefit Short-lived responses rarely clinically meaningful Requires prospective consistent definition; meaningful response duration not standardized Definition of PD is arbitrary, without evidence it actually represents end of benefit period Statistically validated as surrogate for survival only in some settings Not precisely measured; subject to assessment bias, particularly in openlabel studies Definitions vary among studies; little agreement on magnitude of difference that constitutes clinical benefit Requires randomized clinical trial design to provide control group Requires frequent and constant radiologic or other assessments Involves balancing timing of assessments among treatment arms

aProgression-free survival includes all deaths; time to progression censors deaths that occur before progression.

Adapted from U.S. Department of Health and Human Services, U.S. Food and Drug Administration, Center for Drug Evaluation and Research, Center for Biologics Evaluation and Research. Guidance for industry. Clinical trial endpoints for the approval of cancer drugs and biologics https://www.fda.gov/downloads/Drugs/Guidances/ucm071590.pdf. Accessed June 8, 2018.

Hazard Ratios Increasingly, hazard ratios are incorrectly being cited in preference to more traditional measures of efficacy such as median PFS and OS. Because a hazard ratio is a value that has no dimensions, it has limited value and primarily provides a measure of relative efficacy. It does not quantify the magnitude of the benefit. Physicians and especially patients want to know the magnitude of the benefit—the extent to which a life will be prolonged—in a measure they can comprehend, not as a dimensionless ratio. By definition, the hazard ratio is a ratio of the hazard rates. The hazard rate quantifies the likelihood that a patient will experience a “hazardous event” or a “hazard” during a defined interval of observation, expressed as a rate (or percentage). This period of observation may be 1 day, 1 month, 1 year, or longer. Specifically, the hazard rate represents the conditional probability that a patient will continue to be alive without progression of their disease or death in any upcoming period of time. A hazard ratio of 0.8 does not mean the occurrence of a hazardous event (progression or death) will be reduced by 20%. It only indicates that the rate at which the hazardous event will occur is reduced by 20% compared to the rate of the control arm, but eventually, death or progression will occur. The hazard rate can be easily obtained from the data used to generate a Kaplan-Meier plot, and this is shown schematically in Figure 40.3. As commonly presented, the lower the hazard ratio, the better is the experimental therapy. To determine whether the hazard ratio has statistical significance, one can (1) use a log-rank test to show that the null hypothesis that the two treatments lead to the same survival probabilities is wrong or (2) use a parametric approach writing a regression model and fitting the data to the model so that one can establish the hazard ratio for the whole trial and its statistical significance. In many cases, the Cox proportional hazard model is used. Although the ideal hazard ratio would capture the differential benefit throughout the period of study, in practice, the entire time depicted in a Kaplan-Meier plot may not be analyzed. As time progresses, the number of patients who have not yet died or experienced progression of their disease declines, and any such event generates a disproportionate effect on the hazard rate and, in turn, the hazard ratio. Consequently, these areas of the Kaplan-Meier plot are often not used in calculating the overall hazard ratio. Although intuitively reasonable, this has the effect of ignoring portions of the Kaplan-Meier curve that are less beneficial for the superior arm of the study, and this enhances the hazard ratio.

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Figure 40.2 Ideally, as depicted at the top, response assessment will be conducted at a prespecified time. However, the date at which progression is scored may suffer from either ascertainment or censoring bias. Ascertainment bias can occur if either an evaluation occurs before the prespecified date or if it is delayed. For example, a clinician concerned about a patient who is not experiencing side effects and has likely been randomized to placebo may be more inclined to investigate symptoms early and document progression before the prespecified time, while delaying the evaluation of a patient randomized to the experimental arm who experiences some toxicity. Similarly, censoring—an increasing problem in randomized trials—may impact the outcome of a given study arm by either censoring patients who would experience early progression (beneficial impact) or censoring those who would have remained progression free for a long time (detrimental impact). Finally, informative censoring can occur when independent radiologic review cannot concur with an investigator’s assessment of progression and censors the patient. This outcome is usually beneficial because a patient who is very close to experiencing progression is censored. PFS, progression-free survival; TTP, time to progression. (Adapted from Villaruz LC, Socinski MA. The clinical viewpoint: definitions, limitations of RECIST, practical considerations of measurement. Clin Cancer Res 2013;19:2629–2636.)

Forest Plots Interest in determining the extent of heterogeneity in a treatment effect has led to the use of forest plots to display treatment effects across subgroups.72 Although simple in concept, these plots are subject to error because subgroups are composed of smaller numbers and the confidence intervals are therefore wider than those for the entire group. The most common presentation includes a vertical line at the “no effect point” (e.g., a hazard ratio of 1.0), with symbol size usually proportional to the size of the subgroup each with its confidence interval depicted by a line that stretches outward from the symbol to both sides. If the confidence interval for a subgroup crosses the “no effect point,” this is commonly interpreted, not necessarily correctly, as a lack of effect in the subgroup.

Beyond Dichotomized Data

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Waterfall Plots, Spider Plots, and Swimmer Plots The arbitrary nature of the initial 50% cutoff discussed earlier and its evolution to the current RECIST threshold of 30% reduction in the size of the maximum diameter raises valid queries as to why 30% is valuable and not 29% or 25%. On this background, waterfall plots, such as the one shown in Figure 40.4,73 have become increasingly popular because they depict the benefit or lack thereof in all patients as a continuum of response, rather than a dichotomized response rate. The correlations observed between ORR and PFS and OS60–62 would most likely be higher if the threshold for response required an even greater magnitude than 30% shrinkage. Similarly one could envision that if SD were more narrowly defined, such as encompassing the range from −20% to −29%, then SD might be seen to correlate with PFS and OS. The reason the value chosen as an operational optimum in lymphoma over 30 years ago has endured is that 30% shrinkage in one dimension (RECIST definition of response) represents a volumetric decrease of over 65%, a magnitude of tumor regression that not surprisingly impacts OS in the majority of cancers. Because a 20% decrease represents a 50% decrease in volume, it would not be surprising to find that some responses we currently score as SD could nevertheless impact PFS and OS.

Figure 40.3 Kaplan-Meier plots are used to estimate hazard ratios (HRs). Although Kaplan-Meir plots depict the percentage of patients who are event free at any point in time, the HR leverages the opposite value—the percentage of patients who have suffered the hazardous event. The figure is presented to provide an understanding of how HRs are estimated. At the bottom of the graph, for the intervals noted in the x-axis, the percentages of patients who are event free (in this case, event indicates progression or death) are shown (for the 6-month time point, 78% versus 44%). This allows one to know the fraction of patients who have suffered the hazardous event (100 minus the percentage event free). The ratio of these latter two values at any point in time gives you an HR at that point that one can see in this example is initially “low” (0.25) but gradually increases over time (0.86 at 24 months). This trend is commonly seen in clinical trials with high rates of early censoring that can impact interpretations. In calculating the HR for the trial, one can imagine doing this analysis at an infinite number of points and, in effect, averaging this over time. Two additional approaches for displaying clinical data are the swimmer plot and spider plot, shown in Figure 40.4. The swimmer plot graphs horizontally the duration of time individual patients remain on study and most often depicts the subset of patients experiencing a response. In the spider plot, the percent change over baseline for each patient is reported at defined intervals, whereas the waterfall plot describes only the largest decrease or,

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in the case of those with only tumor growth, the smallest increase or “best response.” All three of these approaches provide a visualization of the data but lack a statistical framework for analysis; further, each is missing critical aspects of the data.74 The waterfall plot lacks information on duration, the swimmer plot lacks information on depth of response, and neither the spider nor the swimmer plot accurately portrays fractional response rate. The spider plot has been particularly useful in describing outcomes in immunotherapy trials in which some patients have demonstrated initial progression events followed by regression (pseudoprogression), whereas others have demonstrated marked early disease progression, termed hyperprogression.75,76

Quality of Life The assessment of cancer patients enrolled on a clinical trial can be said to consist of two sets of end points— cancer outcomes and patient outcomes. Cancer outcomes measure the response of the tumor to treatment, the duration of the response, the symptom-free period, and the early recognition of relapse. In contrast, patient outcomes assess the benefit achieved with a given therapy by measuring the increase in survival and quality of life (QOL) before and after therapy. Unfortunately, physicians tend to concentrate on cancer-related outcomes, often neglecting assessments of QOL. Although QOL assessment in clinical settings is possible with currently available instruments, these must be refined. Such refinement must focus not only on extracting valuable information in an unbiased manner but also, equally importantly, on developing an instrument that is user friendly and will be completed in a high percentage of encounters.

Novel End Points Growth Rate Constant. Although RECIST outcomes represent the net result of tumor growth and regression, its algorithms do not describe tumor kinetics and thus provide incomplete information about drug activity. To remedy this, an increasing number of studies are describing the results of kinetic measurements77–79 (Fig. 40.5). Using data gathered while a patient is receiving therapy and a novel but simple two-phase mathematical equation, one can estimate the concomitant rates of tumor regression and growth.79 A high correlation has been observed between OS and the growth rate constant, although not the regression rate constant. Indeed, the response of a tumor to a therapy as exemplified by the nadir, the time to the nadir, and the PFS are all surrogates of the growth rate constant. Beside providing a measure that is highly correlated with OS, estimating the growth rate constant allows one to (1) compare efficacy across trials, (2) predict the outcome if therapy were continued longer, (3) provide accurate measures of efficacy less affected by ascertainment bias and censoring, and (4) assess the outcomes in small studies by benchmarking those outcomes to data from registration studies. The utility of this approach awaits further validation.

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Figure 40.4 Examples of a waterfall plot, a swimmer plot, and a spider plot. A: The waterfall plot demonstrates for each patient the maximum benefit obtained with the study therapy. Bars to the left represent patients whose tumors increased, whereas bars on the right patients whose tumors regressed. Those with increase in tumor size have the “best result” depicted, and this explains why

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not every patient has a value above 20%, as would be expected for scoring progressive disease. In some patients, the initial reassessment was higher than baseline but not above 20%, and this first reassessment is what is depicted. Ideally, all responses should be confirmed after a period of at least 4 weeks. B: The swimmer plot depicts the time on study for the patients represented on the graph, with the values on the x-axis indicating the number of weeks during which patients received therapy. In this plot, all treated patients are shown, whereas most swimmer plots often depict only patients who have achieved a response or have stable disease. The legend describes the symbols used. C: Finally, the spider plot depicts the extent of tumor shrinkage for each individual patient over time. HPV, human papillomavirus. Adapted from Seiwert TY, Burtness B, Mehra R, et al.73

Real-World Assessments Two final points deserve discussion. One is that the response assessment methodologies discussed earlier have been created for drug development, for assessing clinical trial outcomes. They are not methods used by clinicians in routine care of patients. When caring for patients, a physician uses a clinical heuristic, informed by parameters including imaging, markers, performance status, pain, and adverse effects, to decide when to continue and when to stop treatment. Learning how well drugs work in that setting, or outcomes research, is an important area of postapproval investigation. Real-world efficacy, with some exceptions, is seldom as promising as that noted in the clinical trial.80–82 This is why it is so important during clinical trials to get the clinical assessments right.

Figure 40.5 Regression and growth of tumors. The purple line is what is usually observed in the clinic in the overwhelming majority of patients with a solid tumor—an initial regression of tumor, unfortunately followed by progression and growth. However, this is actually a result of two simultaneous processes that are occurring in a tumor as a patient is treated. These two simultaneous processes are the exponential regression of the sensitive fraction of the tumor, depicted by the red dotted line, and the simultaneous exponential growth of the resistant or relatively resistant fraction of the tumor, depicted by the green dotted line. The fraction that is regressing will not cause any long-term harm because it will die and never recur, whereas the growing fraction is responsible for disease progression and ultimately death. Although this is happening simultaneously, one can mathematically estimate both a regression rate constant and a growth rate constant. The regression rate represents the rate at which the sensitive fraction of the tumor disappears. The growth rate is the rate at which the resistant or relatively resistant fraction is growing. Importantly, as can be seen, even as the total tumor quantity is decreasing, these two processes are occurring simultaneously, although it appears to the clinician that the tumor is decreasing.

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49. Bünger S, Laubert T, Roblick UJ, et al. Serum biomarkers for improved diagnostic of pancreatic cancer: a current overview. J Cancer Res Clin Oncol 2011;137(3):375–389. 50. Beije N, Jager A, Sleijfer S. Circulating tumor cell enumeration by the CellSearch system: the clinician’s guide to breast cancer treatment? Cancer Treat Rev 2015;41(2):144–150. 51. Jackson JM, Witek MA, Kamande JW, et al. Materials and microfluidics: enabling the efficient isolation and analysis of circulating tumour cells. Chem Soc Rev 2017;46(14):4245–4280. 52. Mandel P, Metais P. Les acides nucléiques du plasma sanguin chez l’homme. C R Seances Soc Biol Fil 1948;142(3–4):241–243. 53. Leon SA, Shapiro B, Sklaroff DM, et al. Free DNA in the serum of cancer patients and the effect of therapy. Cancer Res 1977;37:646–650. 54. Shapiro B, Chakrabarty M, Cohn EM, et al. Determination of circulating DNA levels in patients with benign or malignant gastrointestinal disease. Cancer 1983;51(11):2116–2120. 55. Sorenson GD, Pribish DM, Valone FH, et al. Soluble normal and mutated DNA sequences from single-copy genes in human blood. Cancer Epidemiol Biomarkers Prev 1994;3(1):67–71. 56. Vasioukhin V, Anker P, Maurice P, et al. Point mutations of the N-ras gene in the blood plasma DNA of patients with myelodysplastic syndrome or acute myelogenous leukaemia. Br J Haematol 1994;86(4):774–779. 57. Burgener JM, Rostami A, De Carvalho DD, et al. Cell-free DNA as a post- treatment surveillance strategy: current status. Semin Oncol 2017;44(5):330–346. 58. Warton K, Mahon KL, Samimi G. Methylated circulating tumor DNA in blood: power in cancer prognosis and response. Endocr Relat Cancer 2016;23(3):R157–R171. 59. Pazdur R. Endpoints for assessing drug activity in clinical trials. Oncologist 2008;13(Suppl 2):19–21. 60. Buyse M, Thirion P, Carlson RW, et al. Relation between tumour response to first-line chemotherapy and survival in advanced colorectal cancer: a meta- analysis. Meta-Analysis Group in Cancer. Lancet 2000;356(9227):373–378. 61. Bruzzi P, Del Mastro L, Sormani MP, et al. Objective response to chemotherapy as a potential surrogate end point of survival in metastatic breast cancer patients. J Clin Oncol 2005;23(22):5117–5125. 62. Vidaurre T, Wilkerson J, Simon R, et al. Stable disease is not preferentially observed with targeted therapies and as currently defined has limited value in drug development. Cancer J 2009;15(5):366–373 63. McKee AE, Farrell AT, Pazdur R, et al. The role of the U.S. Food and Drug Administration review process: clinical trial endpoints in oncology. Oncologist 2010;15(Suppl 1):13–18. 64. Burris HA 3rd, Moore MJ, Andersen J, et al. Improvements in survival and clinical benefit with gemcitabine as first-line therapy for patients with advanced pancreas cancer: a randomized trial. J Clin Oncol 1997;15(6):2403– 2413. 65. Ohorodnyk P, Eisenhauer EA, Booth CM. Clinical benefit in oncology trials: is this a patient-centred or tumourcentred end-point? Eur J Cancer 2009;45(13):2249–2252. 66. Raju GK, Gurumurthi K, Domike R, et al. A benefit-risk analysis approach to capture regulatory decision-making: non-small cell lung cancer. Clin Pharmacol Ther 2016;100(6):672–684. 67. Raju GK, Gurumurthi K, Domike R, et al. A benefit-risk analysis approach to capture regulatory decision-making: multiple myeloma. Clin Pharmacol Ther 2018;103(1):67–76. 68. Buyse M. Use of meta-analysis for the validation of surrogate endpoints and biomarkers in cancer trials. Cancer J 2009;15(5):421–425. 69. Wilkerson J, Fojo T. Progression-free survival is simply a measure of a drug’s effect while administered and is not a surrogate for overall survival. Cancer J 2009;15(5):379–385. 70. Hortobagyi GN, Gomez HL, Li RK, et al. Analysis of overall survival from a phase III study of ixabepilone plus capecitabine versus capecitabine in patients with MBC resistant to anthracyclines and taxanes. Breast Cancer Res Treat 2010;122(2):409–418. 71. Hennekens C, Buring J. Epidemiology in Medicine. Boston, MA: Little, Brown and Co.; 1987. 72. Cuzick J. Forest plots and the interpretation of subgroups. Lancet 2005;365(9467):1308. 73. Seiwert TY, Burtness B, Mehra R, et al. Safety and clinical activity of pembrolizumab for treatment of recurrent or metastatic squamous cell carcinoma of the head and neck (KEYNOTE-012): an open-label, multicentre, phase 1b trial. Lancet Oncol 2016;17(7):956–965. 74. Shen Y, Anderson A, Sinha R, et al. Joint modeling tumor burden and time to event data in oncology trials. Pharm Stat 2014;13(5):286–293. 75. Champiat S, Dercle L, Ammari S, et al. Hyperprogressive disease is a new pattern of progression in cancer patients treated by anti-PD-1/PD-L1. Clin Cancer Res 2017;23(8):1920–1928. 76. Le DT, Durham JN, Smith KN, et al. Mismatch repair deficiency predicts response of solid tumors to PD-1

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blockade. Science 2017;357(6349):409–413. 77. Ferté C, Fernandez M, Hollebecque A, et al. Tumor growth rate is an early indicator of antitumor drug activity in phase I clinical trials. Clin Cancer Res 2014;20(1):246–252. 78. Li CH, Bies RR, Wang Y, et al. Comparative effects of CT imaging measurement on RECIST end points and tumor growth kinetics modeling. Clin Transl Sci 2016;9(1):43–50. 79. Wilkerson J, Abdallah K, Hugh-Jones C, et al. Estimation of tumour regression and growth rates during treatment in patients with advanced prostate cancer: a retrospective analysis. Lancet Oncol 2017;18(1):143–154. 80. Westgeest HM, Uyl-de Groot CA, van Moorselaar RJA, et al. Differences in trial and real-world populations in the Dutch Castration-Resistant Prostate Cancer Registry. Eur Urol Focus 2016;[Epub ahead of print]. 81. Gore ME, Szczylik C, Porta C, et al. Final results from the large sunitinib global expanded-access trial in metastatic renal cell carcinoma. Br J Cancer 2015;113(1):12–19. 82. D’Angelo S, Germano D, Zolfino T, et al. Therapeutic decisions and treatment with sorafenib in hepatocellular carcinoma: final analysis of GIDEON study in Italy. Recent Prog Med 2015;106(5):217–226.

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41

Vascular Access Mohammad S. Jafferji and Stephanie L. Goff

INTRODUCTION Comprehensive multimodal cancer treatment has led to the need for reliable intravascular access. Modern intravascular access techniques and catheter systems allow for the delivery of chemotherapies, parenteral nutrition, and convenient access of blood sampling for laboratory tests. Long-term, durable intravenous access is often the first step in cancer treatment algorithms. Multiple devices have been developed to allow for effective treatment delivery based on appropriate clinical indications. Understanding the indications, commercially available options, and array of complications is critical to clinical oncologists. This chapter discusses the available catheters, their indications, placement techniques, proper maintenance, and common complications.

CATHETER TYPES There are many commercially available intravascular catheters that provide access with a range of specifications and indications. Most catheters are placed in the central venous system, and this chapter mainly focuses on the typical array of available central venous catheters. In selecting the appropriate catheter for treatment, there are several considerations including the type of regimen, length, and frequency of treatment. In addition, patient comfort, convenience, and the risk-to-benefit ratio should be considered (Table 41.1). In assessing catheter type, the first practical branch point is catheters that have an external access apparatus versus those that have implanted ones. There are other implantable intra-arterial devices such as hepatic arterial infusion pumps, which are discussed separately.

EXTERNAL CATHETERS External catheters contain an external hub that is directly accessible for intravenous delivery or blood sampling. Among these, are two basic systems: nontunneled and tunneled external devices.

Nontunneled Catheters Nontunneled intravenous catheters are most commonly used for acute central venous access such as in the need for delivery of vasopressors, resuscitation, antibiotics, urgent induction chemotherapy, or when there is poor peripheral access. These are typically placed in the inpatient setting and are the simplest and fastest to place. They often can be placed using anatomic landmarks or, more frequently, with the use of ultrasonography and fixed at the site of insertion. Based on the clinical indication, the external diameter and number of lumens may be selected. Nontunneled catheters are typically used in the short term and are safe for up to 14 days of use. Given its direct entrance through the skin, external nontunneled lines have an increased rate of local and catheter-based infections. A general principle is to use the least number of lumens as the incidence of catheter-related infections increases with lumen number.1 These catheters should be removed as soon as they are no longer indicated. There are many commercially available kits such as the Arrow (Teleflex, Morrisville, NC), which provide multiple minor alterations, sizes, lengths, and lumen number based on the patient and the clinical scenario.

Tunneled Catheters Tunneled catheters are similar to nontunneled catheters but have several key features that allow for longer use.

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First is the creation of a subcutaneous tunnel, which the proximal portion of the catheter traverses from the insertion site to the venipuncture. This limits movement of the catheter and decreases catheter infection by increasing the natural barrier distance from skin entry site and the vein. Additionally, tunneled catheters have a Dacron cuff affixed to the catheter located near the skin entry site. This cuff allows further fixation of the catheter by promoting tissue ingrowth in the subcutaneous tract (Fig. 41.1A). There are multiple commercially available tunneled central catheters including Hickman, Broviac, Leonard, and Groshong (Bard Access Systems, Salt Lake City, UT) that have minor differences based on the indication and clinician preference. In addition, there have been several attempts at making these lines bacteriostatic to decrease the rate of catheter-related infection. These include cuffs that are impregnated with bacteriostatic agents such as silver or antibiotics as well as catheters that have treated with these agents. There have been mixed data in terms of decreasing catheter-based infections as large randomized trials demonstrate no advantage/noninferiority of untreated catheters.2 Other methods have used two-way valves that function to reduce reflux of blood into the lumen. Without flow, the valve is in a neutral closed position. When blood is either drawn or the catheter is infused, the valve opens. Again, this design has not demonstrated clear benefit in well-designed trials.3 These catheters are placed with the aid of ultrasonography and fluoroscopy in either the interventional radiology suite or in the operating room. Similar to nontunneled catheters, the smallest number of lumens should be selected to meet the needs of care. Once the patient no longer requires central venous access the catheter should be removed, and this can typically be done at bedside or in the clinic with a simple instrument tray. With the recent approval by the U.S. Food and Drug Administration (FDA) of gene-engineered cellular therapies such as chimeric-antigen receptor T cells, large-bore tunneled catheters are needed to rapidly deliver a large dose of cellular product with low resistance.4

Peripherally Inserted Central Catheter Another option of central venous access and catheter placement is through the peripheral veins. First described in 1975, a long silastic catheter can be inserted from the peripheral upper extremity veins and terminate at the superior vena cava (SVC).5 Venipuncture can be accessed through different veins with the basilic vein being the most preferred site as it is relatively superficial and has the largest diameter, the straightest route to the SVC, and the greatest blood flow of the peripheral arm veins.6 However, the cephalic, medial cubital, and brachial are also options for access. Ideally, peripherally inserted central catheters (PICCs) should be placed above the antecubital fossa to limit mechanical issues related to movement at the joint. PICCs are typically placed by an interventional radiologist or more commonly by specialized nursing teams trained in this technique. Ultrasonography is used to identify a suitable vein, and a chest x-ray is used to assess correct central positioning. PICC lines provide several advantages including avoiding the risk of a pneumothorax or vascular injury as well not requiring interventional radiology or surgery.7 However, these lines have similar rates of catheter-based infections, and several studies have shown that they have increased thrombotic complications compared to centrally placed catheters.8 Additionally, due to their longer course to the SVC, PICCs have increased resistance and are less suitable for rapid infusions. TABLE 41.1

Catheter-Specific Advantages and Disadvantages Catheter Type

Advantages

Disadvantages

Central indwelling catheter (tunneled catheter)

Low device profile Durable Lower maintenance than external catheter

Increased insertion-associated risks (pneumothorax, arterial injury) compared to PICC

Central externalized catheter

Large bore lumen (i.e., Cordis) allows rapid infusions and/or resuscitation vs. smaller-bore multilumen for administration of multiple agents Can be placed emergently Does not require IR/OR suite

Shorter catheter life vs. indwelling Higher routine maintenance required when compared to indwelling catheters Increase of arterial and insertion related injury compared to PICC

Implantable port

Low device profile Durable Convenient

Requires IR/OR placement If infected, may require surgical removal

PICC line

Can be placed by trained nursing staff under local anesthesia

Higher risk of thrombosis

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Lower risk of insertion related injury (pneumothorax, arterial injury)

Decreased durability Higher routine maintenance required when compared to indwelling catheters PICC, peripherally inserted central catheter; IR, interventional radiology; OR, operating room.

Another option of peripherally inserted catheters are midline catheters. They are placed similarly to PICC lines with access through the upper extremity veins. They are shorter in length and typically range from 8 to 20 cm and terminate no further than the proximal axillary vein. These catheters can infuse many of the same products that PICC lines can; however, they should not be used for longer than 30 days. Short- to moderate-term use of total parenteral nutrition, antibiotics, and chemotherapies can be safely administered via a midline catheter and have become an increasingly popular approach in the short-term outpatient setting.9 They do not typically require a postprocedure x-ray.

IMPLANTABLE DEVICES Implantable systems expand on the concept of limiting external exposure to the intravascular circulation. Whereas nontunneled, tunneled, and PICC lines allow for an external hub for drug delivery or blood sampling, implanted devices are completely contained subcutaneously, and access is obtained percutaneously. There are two main systems utilized: medical access ports and continuous infusion pumps. This section first discusses implantable ports and then addresses implantable continuous infusion pumps.

Figure 41.1 A: A dual lumen 10 Fr Hickman catheter showing the Dacron cuff. B: Implantable venous device. A noncoring Huber needle is also shown. The housing of the port can be made of titanium (shown) or plastic.

Implantable Ports Implantable ports have become a cornerstone in the management of patients with a number of malignancies that require long-term access. The catheter portion of the device is the same as external devices and terminates in the distal SVC. The difference is the access port, surgically implanted in a subcutaneous pocket and connected to the catheter. This port is then accessed by percutaneous puncture. The port has many unique technical features that allow for repetitive and durable access. It is designed with either nonferrous metal or plastic housing also called the “portal” and a central silicone diaphragm (Fig. 41.1B). The port is oriented such that the self-sealing silicone apposes the underlying skin. The self-sealing silicone allows for puncture via a specialized Huber needle that is noncoring.10 The needle is punctured through the overlying skin and into the diaphragm after disinfecting the skin. The needle tip should be pushed until it makes contact with the back wall of the diaphragm. The port should then be flushed and blood withdrawn. Once patency has been confirmed, the port is ready for infusion or further blood sampling. Small volumes of heparinized saline are required to preserve patency of the reservoir and prevent clotting while the port is not in use. Deaccessing the port involves injecting a small volume of heparinized saline to refill the reservoir before the Huber needle is removed. The silicone diaphragm can be accessed this way for hundreds of uses.10 Placement of a port involves two major steps. These are placed in the operating room or in interventional

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radiology with local anesthetic and moderate sedation. Much like external catheters, percutaneous access of the central veins is the first step, via the internal jugular or subclavian vein. Modified Seldinger technique, described later in this chapter, is used to cannulate the venous system. Fluoroscopic guidance to ensure correct tip positioning at the atriocaval junction is essential. The port incision is typically placed about two fingerbreadths below the clavicle. A horizontal incision is made, and a subcutaneous pocket is developed inferiorly.11 The port should be sutured to the pectoralis fascia to prevent twisting or migration. The catheter is then tunneled from the port site to the venipuncture site. It is important that the port incision is not situated directly above the access diaphragm to prevent puncture through healing tissue or surgical scar during use. Access and use of the port can start immediately after placement. Ports are typically placed as an outpatient procedure. There are multiple adaptations and commercial brands, such as Port-A-Cath, BardPort, PasPort, Medi-port, and Infusaport, that use variations of the above technology. Some offer multiple lumens, materials, and specifications regarding infusion rate. An important consideration is the ability for rapid infusion for contrast-enhanced computed tomography (CT) scans. Given the standard use of high-resolution helical CT scans for staging and routine evaluation, selection of a “power” port affords convenient and reliable access. Ports such as PowerPort (Bard Access Systems, Salt Lake City, UT; Fig. 41.2) allow for rapid infusion rates of up to 5 mL per second via the port and eliminates the need for peripheral access.12 Institutional policies may vary, and it is important to confirm suitability to facilitate informed patient consent and expectations. Multilumen catheters are also available and should be selected if incompatible infusates are routinely needed. The main advantage of an implantable port is its long-term durable access. Well-maintained ports can remain safely implanted for several years.13 In addition, the port is low maintenance, is low profile, and affords good cosmesis and functionality. Subcutaneous placement allows for a natural skin barrier and prevents exposure of hardware. Although placement is a simple procedure, it still carries risks of infection, pneumothorax, and thrombosis similar to external devices. Multiple studies have shown a comparable risk profile between the two with durability of implanted ports being the key difference.14 Clinically significant catheter or port infections require surgical explantation of the device, whereas external lines can be removed at bedside. Complication rates remain low, and short-term complications occur in 3% of patients and with long-term complications occurring in 1.6%.15

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Figure 41.2 A dual reservoir PowerPort (Bard Access Systems, Salt Lake City, UT) implantable venous device compatible with magnetic resonance imaging technology. Inset: Silicone diaphragm and locking connector.

Implantable Infusion Pumps Although the majority of patients with malignancies receive intravenous chemotherapies in intermittent scheduled cycles, another approach is continuous infusion. Continuous infusion implantable pumps allow for self-contained mobile delivery of treatment. This frees a patient from cumbersome external pumps. Much like a port, a central venous catheter is connected to a sealed chamber. This chamber is also implanted in a subcutaneous pocket,

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although this is typically placed in the abdominal subcutaneous tissue. These devices also contain a silicone diaphragm that is accessed through a Huber needle. However, it leads to a larger reservoir where a volume of the infusate can be filled. Surrounding the reservoir is chamber filled with gas-phase fluorocarbon. When the reservoir is filled, the gas is compressed and transitions to its liquid state. The pressure of the compressed gas exerts a constant measurable force as its slowly transitions back to a gas state. These pumps can be attached to other catheters and are useful for other application such as intrathecal analgesia, insulin, parenteral nutrition, or intraarterial chemotherapy.16 In addition to these pumps, on-demand, motor-driven implantable pumps offer the advantage of changes to delivery rate. In the case of continuous arterial chemotherapeutic infusion, surgical cannulation of the gastroduodenal artery connected to an implanted pump allows higher concentrations of chemotherapies into the hepatic arterial circulation. This has been used mainly in unresectable isolated colorectal liver metastasis in an effort to decrease hepatic tumor burden and allow for resection.17

CATHETER SELECTION With multiple options for obtaining intravenous access, it is important to select the most appropriate device to meet the treatment needs and minimize exposure to risks. Several factors should be considered: the anticipated length of treatment; treatment regimen and its compatibility; need for blood sampling; need for routine intravenous contrast; as well as patient comfort, anatomy, and comorbidities. In addition, it is always important to ask if effective treatment can be safely administered either with peripheral access or orally. Nontunneled central lines are the choice for acute resuscitation, administration of vasopressors, transfusions, central venous pressure monitoring, or those undergoing major surgical procedures. In addition, they are suitable for infusion of short-term parenteral nutrition, antibiotics, or chemotherapeutic agents. They can also be used for plasmapheresis when peripheral access is not suitable. The duration of the expected treatment should be 4 cm for T3, and T4 tumors involve major invasion or encasement of surrounding structures (e.g., bone, carotid artery, deep musculature). For the other primary sites, further staging is less easily generalized because the anatomic extent of spread, histology (e.g., p16 status for oropharyngeal SCC for which a new staging system reflecting the better prognosis for these patients has been proposed),33 and/or functional criteria (e.g., vocal cord mobility) are used and, for certain sites, are combined with tumor size (e.g., hypopharynx, major salivary glands) and are given in the discussion of each respective primary site.32 Neck staging is common to all head and neck sites, except the nasopharynx (Table 45.1).32 Lesions may be clinically or pathologically staged. Clinical staging is more commonly used for treatment planning and the reporting of results. The format for combining T and N stages into an overall stage is depicted in Table 45.2 and is common to all sites except the nasopharynx and p16 positive oropharynx or unknown primary.32 Overall stage for p16 positive oropharynx or unknown primary is further stratified based on whether the stage is clinical or pathologic.32 TABLE 45.1

2017 American Joint Committee on Cancer Stages of Regional Lymph Node Involvement NX

Regional lymph nodes cannot be assessed

N0

No regional lymph node metastasis

N1

Metastasis in a single ipsilateral lymph node, 3 cm or smaller in greatest dimension and ENE(−)

N2

Metastasis in a single ipsilateral lymph node larger than 3 cm but no larger than 6 cm in greatest dimension and ENE(−); or metastases in multiple ipsilateral lymph nodes, none more than 6 cm in greatest dimension and ENE(−); or in bilateral or contralateral lymph nodes, none larger than 6 cm in greatest dimension and ENE(−)

N2a

Metastasis in single ipsilateral or contralateral lymph node larger than 3 cm but not larger than 6 cm in greatest dimension and ENE(−)

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N2b

Metastasis in multiple ipsilateral lymph nodes, none larger than 6 cm in greatest dimension and ENE(−)

N2c

Metastasis in bilateral or contralateral lymph nodes, none larger than 6 cm in greatest dimension and ENE(−)

N3

Metastasis in a lymph node larger than 6 cm in greatest dimension and ENE(−); or metastases in a single ipsilateral nose ENE(+); or multiple ipsilateral, contralateral, or bilateral nodes, any with ENE(+)

N3a

Metastasis in a lymph node larger than 6 cm in greatest dimension and ENE(−)

N3b Metastasis in a single ipsilateral ENE(+); or multiple ipsilateral, contralateral, or bilateral nodes, any with ENE(+) Note: A designation of “U” or “L” may be used for any N category to indicate metastasis above the lower border of the cricoid (U) or below the border of the cricoid (L). Similarly, clinical and pathologic ENE should be recorded as ENE(−) or ENE(+). ENE, extranodal extension. Used with the permission of the American College of Surgeons. The original source for this material is the AJCC Cancer Staging Manual, Eighth Edition (2017) published by Springer International Publishing AG.

TABLE 45.2

2017 American Joint Committee on Cancer Overall Stage Grouping When T Is …

And N Is …

And M Is …

Then the Stage Group Is …

T1

N0

M0

I

T2

N0

M0

II

T3

N0

M0

III

T1, T2, T3

N1

M0

III

T4a

N0, N1

M0

IVA

T1, T2, T3, T4a

N2

M0

IVAt

Any T

N3

M0

IVB

T4b

Any N

M0

IVB

Any T Any N M1 IVC Used with the permission of the American College of Surgeons. The original source for this material is the AJCC Cancer Staging Manual, Eighth Edition (2017) published by Springer International Publishing AG.

Stage IV represents a wide spectrum of disease. One patient may have a T1, T2, or T3 lesion with low-volume N2 neck disease and a high probability of cure (stage IVA), whereas another may have a T4b primary cancer and/or N3 neck disease and a relatively poor prognosis (stage IVB)34; distant metastases indicate stage IVC disease, and the treatment intent is typically palliative.

PRINCIPLES OF TREATMENT FOR SQUAMOUS CELL CARCINOMA General Principles for Selection of Treatment Surgery and RT are the only curative treatments for head and neck carcinomas. Although chemotherapy alone is not curative, it enhances the effects of RT and thus is routinely used as part of combined modality treatment in patients with stage III or IV disease. The advantages of surgery compared with RT, assuming similar cure rates, may include the following: (1) a limited amount of tissue is exposed to treatment; (2) the treatment time is shorter; (3) the risk of immediate and late RT toxicity is avoided; and (4) RT is reserved for a head and neck SPT, which may not be suitable for surgery. The advantages of RT may include (1) the risk of a major postoperative complication is avoided, (2) no tissues are removed so that the probability of a functional or cosmetic defect may be reduced, (3) elective neck RT can be included with relatively low morbidity, and (4) the surgical salvage of an RT failure is probably more likely than the RT salvage of a surgical failure.

Transoral Robotic Surgery In recent years, transoral robotic surgery (TORS) has been popularized. This technology uses robotic arms operated remotely by the surgeon. It overcomes difficulties in exposing tumors, especially OPCs, allowing a better access and no need to split the mandible. The functional results of TORS are excellent in relatively small tumors,

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with similar survival rates as RT or combined chemoRT (CRT). The functional results, notably dysphagia, may be adversely affected if patients require postoperative RT or CRT.35 Salvage of a surgical failure may be attempted by repeat surgery, RT, or both if possible. Surgical recurrences usually develop at the resection margins, in or near the suture line. It is difficult to distinguish the normal surgical scarring from recurrent disease, and the diagnosis of recurrence is often delayed. Tumor response to RT under these circumstances is poor. Surgery, RT, or both, however, may salvage small mucosal recurrences and some neck recurrences. For bulkier recurrences treated with RT, concurrent chemotherapy is often incorporated.

Survival Benefits of Head and Neck Cancer Patients Receiving Treatment at Centers with Expertise The National Comprehensive Cancer Network (NCCN) guidelines recommend that patients with HNC receive treatment at centers with expertise. A recent analysis of institutions with high accrual or low accrual of patients in cooperative group studies found that patients treated in high-volume RT centers had better survival compared with patients treated at low-volume institutions, after accounting for RT protocol deviations.36 The same has been shown for surgically treated patients for whom survival is nearly doubled at high-volume centers.37

MANAGEMENT Primary Site The management of the primary cancer is considered separately for each anatomic site. Patients who are in poor nutritional condition may require a nasogastric tube or a percutaneous gastrostomy (PEG) before initiating surgery or RT, particularly if concomitant chemotherapy is used. Opinions vary regarding the role of prophylactic nasogastric or PEG placement in anticipation of RT-based local toxicity in patients without significant baseline dysphagia or weight loss; a reactive strategy is preferred by many and may facilitate swallowing recovery.38 If external-beam RT (EBRT) is selected, it may be given with either conventional once-daily fractionation, 66 to 70 Gy at 2 Gy per fraction, 5 days a week in a continuous course, or with an altered fractionation schedule. Whether an altered fractionation schedule is better than conventional fractionation when used as a single modality depends on the altered fractionation technique that is selected. Two altered fractionation schedules that have been shown to result in improved local–regional control rates are the University of Florida hyperfractionation and the MD Anderson Cancer Center concomitant boost techniques.39 The results of a prospective randomized Radiation Therapy Oncology Group (RTOG) trial comparing these schedules with conventional fractionation and the Massachusetts General Hospital accelerated split-course schedule are shown in Table 45.3. Acute toxicity is increased with altered fractionation; late toxicity is comparable with conventional fractionation.40 Hyperfractionation resulted in improved overall survival, whereas the concomitant boost schedule did not. Of note, when concurrent chemotherapy is added, there does not appear to be a tumor control advantage for use of altered fractionated compared to standard fractionation RT.9,41 However, there are no randomized trials comparing hyperfractionation and concomitant chemotherapy with once-daily fractionation and concomitant chemotherapy. TABLE 45.3

Altered Fractionation: 5-Year Outcomes from the Radiation Therapy Oncology Group 90-03 Trial Fractionation Schedule Conventional (70 Gy/35 Fx/7 wk)

Hyperfractionation (81.6 Gy/68 Fx/7 wk)

Accelerated Split Course (67.2 Gy/42 Fx/6 wk)

Accelerated Concomitant Boost (72 Gy/42 Fx/6 wk)

Number of patients

268

263

274

268

Local– regional failure

59.1%

51.2% (P = .037)

57.8%

51.7% (P = .042)

Disease-free

21.2%

30.7% (P = .013)

26.6%

28.9% (P = .042)

Parameter

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survival Overall survival

29.5%

37.1% (P = .063)

30.8%

33.5%

Causespecific survival

42.9%

45.5%

40.9%

43.4%

Grade 3 late 25.2% 27.4% 26.8% 33.3% (P = .066) toxicity Note: P values reflect comparison of the experimental arms with standard fractionation. Fx, fractions. From Trotti A, Fu KK, Pajak TF, et al. Long term outcomes of RTOG 90-03: a comparison of hyperfractionation and two variants of accelerated fractionation to standard fractionation radiotherapy for head and neck squamous cell carcinoma. Int J Radiat Oncol Biol Phys 2005;63:S70–S71.

Conventional EBRT techniques and/or brachytherapy are discussed in the subsequent site-specific sections. EBRT may also be delivered with intensity-modulated RT (IMRT) to produce a more conformal dose distribution and to reduce the dose to the normal tissues.42–44 The disadvantages of IMRT are that it is more time consuming to plan and treat the patient, the dose distribution is often less homogenous so that “hot spots” may increase the risk of late complications, the risk of a marginal miss may be increased because the fields are more conformal, the total body RT dose is higher because of increased “beam on” time and scatter irradiation, and it is more costly. Therefore, a clear reason for using IMRT versus conventional RT should be identified. The usual indication for IMRT is to reduce the dose to the contralateral parotid gland and thus limit long-term xerostomia.45 Another indication is to reduce the CNS dose in patients with NPC. Finally, it may be used to avoid a difficult low neck match in patients with laryngeal or hypopharyngeal cancers and a low-lying larynx. Proton therapy, which offers potential targeting and dosing advantages for selected tumors,46 is useful for reducing the dose to the brain and the visual apparatus for patients with nasal cavity and paranasal sinus malignancies.47 It may also be advantageous for some patients with oropharyngeal SCCs where the dose to the oral cavity may be reduced, thus decreasing the need for a PEG during treatment.48

NECK In 1906, Dr. Crile described the radical neck dissection (currently also known as comprehensive neck dissection), which became the standard of care for lymph node metastases. The superficial and deep cervical fascia with its enclosed lymph nodes (levels I to V) were removed in continuity with the sternocleidomastoid muscle, the omohyoid muscle, the internal and external jugular veins, cranial nerve XI, and the submandibular gland. Over time, neck dissections became less morbid, moving toward the modified radical neck dissection (MRND; currently also known as modified comprehensive neck dissection), or functional neck dissection, and selective neck dissections (SNDs). The principle tenet of these dissections is to preserve structures not involved with cancer and additionally to remove only fat, fascia, and lymph nodes. There are three types of MRND: type I, cranial nerve (CN) XI is spared; type II, CN XI and the internal jugular vein are spared; and type III (functional), CN XI, the internal jugular vein, and the sternocleidomastoid muscle are spared. SNDs are more limited and include removal of lymph node levels that are at greatest risk for nodal metastatic spread. The type of SND is denoted by the lymph node levels removed (e.g., SND II to IV). An SND is recommended for the cN0 neck, for selected clinically positive necks (mobile, 1- to 3-cm lymph nodes), and for removing residual disease after RT when there has been excellent regression of N2 or N3 disease.49,50 The more extensive the neck dissection, the higher the risk of complications. Complications after neck dissection include hematoma; seroma; lymphedema; wound infections and dehiscence; damage to the 7th, 10th, 11th, and 12th cranial nerves; phrenic nerve injury; brachial plexus injury; chyle leak; and vascular injury. The main long-term complication of neck dissection is caused by injury to the spinal accessory nerve, which can result in shoulder and neck pain, weakness, loss of range of motion, and decreased shoulder-related quality of life (QOL). Physical therapy and anti-inflammatory medication are initiated days following surgery and continued for several weeks to maximize recovery. Progressive resistance exercise therapy has been shown to drastically improve shoulder function and related QOL with most participants reaching near-baseline measures.51 Acupuncture has also demonstrated an additional benefit compared to the usual care in one randomized study.52

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CLINICALLY NEGATIVE NECK The estimated incidence of subclinical disease in the regional lymphatics when the neck is cN0 is presented in Table 45.4.53 The likelihood of subclinical disease is also related to the thickness of the primary lesion where lesions 2 to 4 mm thick or less are unlikely to have regional metastases.54 Both RT and neck dissection are approximately 90% efficient at eradicating subclinical regional disease.49 Although a policy of close observation may be adopted for the cN0 neck to avoid unnecessary treatment, the salvage rate for patients developing clinically positive lymph nodes with the primary lesion controlled is 50% to 60%,53 such that candidates for observation should be carefully selected. Elective neck irradiation (ENI) and elective neck dissection (END) are equally effective in the management of the N0 neck, with control rates exceeding 90%.53,55 Treatment of the entire neck is advised for primary lesions with a high rate of subclinical disease, such as the base of tongue, soft palate, supraglottis, and hypopharynx. Patients with lateralized T1 to T2 tonsillar cancers do not require elective treatment for the contralateral N0 neck56; T3 or T4 cancers or those with significant extension into the tongue and/or soft palate should receive bilateral neck treatment to the entire neck.57 TABLE 45.4

Definition of Risk Groups for the Clinically N0 Neck Group

Estimated Risk of Subclinical Neck Disease

T Stage

I: Low risk

30%

Site

T1– Nasopharynx, pyriform sinus, base of tongue T4 Soft palate, pharyngeal wall, supraglottic larynx, tonsil T2– Floor of mouth, oral tongue, retromolar trigone, gingiva, hard T4 palate, buccal mucosa T3– T4 Reprinted with permission from Mendenhall WM, Million RR. Elective neck irradiation for squamous cell carcinoma of the head and neck: analysis of time-dose factors and causes of failure. Int J Radiat Oncol Biol Phys 1986;12(5):741–746.

TABLE 45.5

Failure of Initial Neck Treatment (596 Patients with Carcinoma of the Tonsillar Fossa, Base of Tongue, Supraglottic Larynx, or Hypopharynx at MD Anderson Cancer Center 1948–1967) Stage N0 Treatment

No Treatment

N1

N2a

N2b

N3a

N3b

Radiation



Partial 15%

Complete 2%

15%

27%

27%

38%

34%

Surgery

55% (16/29)

35%

7%

11%

8%

23%

42%

41%

Combined 1/5 0/6 0 0 0 23% 25% Adapted from Barkley HT Jr, Fletcher GH, Jesse RH, et al. Management of cervical lymph node metastases in squamous cell carcinoma of the tonsillar fossa, base of tongue supraglottic larynx, and hypopharynx. Am J Surg 1972;124(4):462–467.

When the primary tumor is to be treated surgically, an END should be performed when the risk of regional lymph node metastasis is 10% to 15% or greater. SND has an excellent rate of disease control; patients who are found to have multiple positive nodes or extracapsular extension (ECE) are then referred for postoperative RT,58 and concurrent chemotherapy is recommended in the latter circumstance.59–62 A recent large randomized study in patients with oral cancer and clinically negative nodes compared neck dissection during surgery to observation of the neck and salvage neck dissection if nodal metastases appear at

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follow-up. END resulted in higher rates of overall and disease-free survival compared to therapeutic dissection at recurrence.63 If the primary lesion is to be treated with EBRT, ENI adds relatively little cost and modest morbidity.

CLINICALLY POSITIVE NECK LYMPH NODES The rates of neck failure by N stage and treatment group reported from the MD Anderson Cancer Center and the University of Florida are shown in Tables 45.5and 45.6, respectively.55,64 In general, RT precedes surgery if the primary site is to be treated by RT or if the node is fixed. The operation precedes RT if the primary site is to be treated surgically. MRND is sufficient treatment for the ipsilateral neck for patients with N0 or N1 disease without ECE. RT, often combined with concurrent chemotherapy, is added for those with more advanced neck disease.58 When the primary lesion is to be managed by RT or CRT, then RT-based therapy alone is sufficient for patients in whom the node(s) regress completely as documented on CT obtained 4 weeks post-RT.50,65 RT is followed by a neck dissection for patients with residual nodes that are 1.5 cm or larger, as well as those that demonstrate focal defects, enhancement, and/or calcification on imaging.65 A PET scan done 3 months after RT is completed as an alternative to CT to assess whether there is persistent disease.66 However, if performed earlier than 3 months after treatment, the PET-CT will have a high false-positive rate. Of note, in a randomized trial of patients with N2 or N3 disease, a PET-CT surveillance strategy did not adversely affect survival compared to planned neck dissection.67 McGuirt and McCabe68 compared results of definitive surgery with and without a prior open neck biopsy and concluded the risks of neck failure, distant metastases, and complications were all increased. Ellis et al.69 studied the results of therapy following open biopsy of a lymph node before treatment. Patients received definitive RT to the primary site and neck; a subset of patients underwent a neck dissection after RT. Open biopsy had no adverse impact on these patients compared with those who did not undergo an open biopsy.69 Therefore, after open biopsy of the neck, RT-based therapy is recommended as the initial treatment, particularly if the primary tumor is to be managed by RT or CRT. Under these circumstances, no further neck treatment is needed if the neck node was removed; if there is residual gross tumor in the neck after open biopsy a definitive neck dissection should be performed if surgery is to be the primary treatment, or definitive RT with chemotherapy added if indicated, if therapy is to be radiation centric.65

CHEMOTHERAPY Drug therapy may be administered to palliate symptoms in patients with incurable disease, to improve the odds of cure or organ preservation when combined with definitive local–regional therapy, or to decrease treatment toxicity. TABLE 45.6

Five-Year Rate of Neck Control According to the 1983 American Joint Committee on Cancer Stage and Treatment (459 Patients, 593 Heminecksa) RT Alone Stage

No. of Heminecks

RT + Neck Dissection Control

No. of Heminecks

Control

N1

215

86%

38

93%

Significance P = .28

N2a

29

79%

24

68%

P = .60

N2b

138

70%

80

91%

P 8 weeks, (3) use of the gastric pull-up for reconstruction, (4) open biopsy of a positive neck node, and (5) soft tissue sarcomas.

Postoperative Radiation Therapy Postoperative RT is considered when the risk of recurrence above the clavicles exceeds 20%. The operative procedure should be one stage and of such magnitude that RT is started no later than 6 to 8 weeks after surgery. The operation should be undertaken only if it is believed to be highly likely that all gross disease will be removed and margins will be negative. Although no definitive randomized trials have addressed the efficacy of postoperative RT in the treatment of HNC, excellent data that has bearing on this issue is available from the Medical College of Virginia. Two groups of surgeons operated on patients with HNC: general surgical oncologists who used surgery alone and reserved RT for treatment of recurrent disease, and otolaryngologists, or head-and-neck surgeons, who routinely sent patients with locally advanced disease for postoperative RT.129 Of 441 patients, 125 were treated surgically between 1982 and 1988 and had ECE and/or positive margins, 71 were treated with surgery alone, and 54 received postoperative RT. Local control rates at 3 years after surgery alone compared with surgery and RT were for ECE, 31% and 66% (P = .03); positive margins, 41% and 49% (P = .04); and ECE and positive margins, 0% and 68% (P = .001). A multivariate analysis of local control revealed that the use of postoperative RT (P = .0001), macroscopic ECE (P = .0001), and margin status (P = .09) were of independent significance. Cause-specific survival rates at 3 years were 41% for surgery alone and 72% for surgery and postoperative RT (P = .0003). A multivariate analysis of causespecific survival showed that postoperative RT (P = .0001) and the number of nodes with ECE (P = .0001)

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significantly influenced this end point. Indications for postoperative RT include close (5 mm of subglottic invasion.58 There are also data showing that patients with initially positive margins converted to negative margins have a significantly higher risk of a local–regional recurrence after surgery.130 The authors currently recommend 60 Gy in 6 weeks to 66 Gy in 6.5 weeks for patients with negative margins and fewer than three indications for RT. For patients with close (10 pack-years) and the extent of nodal disease (N2b to N3) both adversely affect the prognosis associated with HPV-positive tumors.9

Induction Chemotherapy In untreated patients with local or regionally advanced M0 HNSCC, treatment with cisplatin-based combination chemotherapy will yield major response rates approximating 90%, with clinical complete response rates in the 30% range.135 Yet, in the original report of the MACH-NC analysis, which included 31 induction studies, all but 2 suggested no survival benefit.133 However, a more careful look at these and other data do provide grounds for continued interest in this approach. Many of the included studies had significant methodologic limitations by more contemporary trial standards. A subset analysis, limited to the 15 trials that used cisplatin and infusional 5-fluorouracil, suggested survival benefit (hazard ratio [HR], 0.88; 95% confidence interval [CI], 0.79 to 0.97).133 Even in the absence of survival improvement, there seemed to be a correlation between response to chemotherapy and subsequent response to RT, which provided a basis for subsequent organ preservation initiatives.136,137 Finally, patterns of failure were affected with less distant metastases in certain studies when induction chemotherapy was incorporated. As local–regional control improves, the rate of clinically apparent distant metastases is increasing,138 and induction chemotherapy is, on average, better tolerated than maintenance therapy as a way to give additional systemic therapy. Although historically there was no established role for induction chemotherapy prior to planned surgery and postoperative RT, and only in selected settings prior to RT, with the incorporation of taxanes into induction regimens containing cisplatin and 5-fluorouracil, newer data suggest that the indications for induction chemotherapy may further evolve. Randomized trials have compared the relative efficacies of induction chemotherapy with standard cisplatin and 5-fluorouracil versus a triplet including a taxane and these same two drugs with one or both being dose adjusted.139–141 All three studies randomized patients with advanced M0 HNC to either cisplatin and 5-

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fluorouracil or a triplet, followed by the same RT-based treatment. In one study, this was RT alone, whereas, in the other two, concurrent therapy with carboplatin and cisplatin, respectively, were employed. In general, the taxane-containing triplet was associated with a higher response rate to induction chemotherapy, and improved both progression-free and overall survival. More neutropenia was observed with triplet therapy but, overall, it was as well tolerated as standard cisplatin and 5-fluorouracil. These studies were designed to determine which induction chemotherapy was more efficacious and provide convincing evidence that the triplet of a taxane with cisplatin and 5-fluorouracil is superior to standard cisplatin and 5-fluorouracil alone as induction therapy. However, an alternative design is necessary to define the role of induction with such triplets in standard practice. For this population, as discussed in the next section, concurrent chemotherapy and RT alone without induction chemotherapy is the more established standard therapy. Randomized studies are necessary to determine whether a sequential approach using induction with a triplet followed by RT-based treatment (typically with concurrent chemotherapy) is superior to concurrent chemotherapy and RT alone such that the added duration of treatment and potential toxicity is justified. To date, available randomized trials have failed to demonstrate a clear overall survival benefit with the incorporation of induction chemotherapy. In a European study, 439 patients with unresectable, locally advanced HNC were randomized to one of three arms: induction with docetaxel, cisplatin, and 5-fluorouracil followed by concurrent cisplatin RT; induction with cisplatin and 5-fluorouracil followed by concurrent cisplatin RT; or concurrent cisplatin RT alone. No statistically significant difference in progression-free or overall survival was demonstrated.142 In the PARADIGM study, 145 patients with local or regionally advanced SCC were randomized to induction docetaxel, cisplatin, and 5-fluorouracil followed by carboplatin or docetaxel concurrent with RT versus concurrent cisplatin with concomitant boost radiation. Patients could have unresectable disease or be resectable, with the intent of therapy being organ preservation. The study was closed early because of slower than expected accrual, so it was somewhat underpowered. There was no difference in overall or progression-free survival between the arms with a median follow-up of 49 months; the 3-year overall survival rates were 73% in the induction arm and 78% in the concurrent arm (P = .77); and the 3-year progression-free survival rates were 67% and 69%, respectively (P = .82).143 The DECIDE trial used a similar design, but only patients with N2/N3 were eligible, and, for the concurrent therapy, hydroxyurea and 5-fluorouracil was used. Among 285 patients accrued with minimum of 30 months of follow-up, there was no significant difference between the sequential and concurrent arms with regard to overall survival (P = .68 log rank), relapse-free survival (P = .16 log rank), nor distant metastatic-free survival (P = .37 log rank). Serious adverse events were more common with induction chemotherapy (47% versus 28%, P = .002).144 In 256 enrolled patients with stage III or IVA oral cavity cancer, induction with docetaxel, cisplatin, and 5-fluorouracil prior to surgery and postoperative radiation failed to improve overall survival (P = .918) or disease-free survival (P = .897) compared to proceeding directly to surgery and postoperative radiation alone.145 A more recent large randomized study from Germany randomized 1,060 patients with advanced HNC to receive either Docetaxel, Cisplatin, Fluorouracil (TPF) induction chemotherapy followed by CRT or CRT alone, demonstrating no significant differences in outcomes.146 The optimal role of induction chemotherapy is currently controversial. A review of the NCCN guidelines highlights this reality because concurrent CRT alone and induction followed by RT-based therapy are both listed as treatment options for certain disease scenarios.147

Concurrent Chemotherapy and Radiation for Gross Disease Concurrent CRT programs vary in many ways, of which the type of chemotherapy (i.e., specific agents, single, combination) and RT schedule (i.e., dose, fractionation) are the most apparent variables. In general, three main approaches can be discerned: single-agent or combination chemotherapy with continuous-course RT; combination chemotherapy with split-course RT, often with altered fractionation; and chemotherapy alternating with RT.148 Although continuous-course RT may be desirable and more attractive from a radiobiologic perspective, local toxicities may preclude it depending on the concurrent agents used. The first two approaches are the most common. A variety of drugs and combinations have been utilized concurrently with RT. When only one drug is used, the MACH-NC indicates that the impact is largest with a platin, of which cisplatin is the predominant one studied, a conclusion shared in another meta-analysis reported by Browman and colleagues.149 Of interest, platin plus 5fluorouracil (HR, 0.75) offered no clear advantage compared to platin alone (HR, 0.74).150 The results of a threearm randomized study comparing concurrent cisplatin and RT, concurrent cisplatin, 5-fluorouracil and splitcourse RT (with possible resection depending on response), and definitive RT alone in patients with unresectable

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disease reported by Adelstein et al.,151 in the E1392 study, are consistent with this assessment. Although daily,152 weekly,62,153 and every-3-week schedules of cisplatin intravenously concurrent with RT have been applied, the last schedule is the one most studied and is a widely accepted standard. If weekly dosing is used, 20 mg/m2 weekly appears too low because it did not significantly improve overall survival or failure-free survival in one randomized study.153 Attempts to improve the efficacy of concurrent cisplatin through intra-arterial administration154,155 did not prove more efficacious in a randomized trial when compared to intravenously delivered cisplatin, although toxicity profiles differed.156 In absence of a proven efficacy advantage with intraarterial delivery, intravenous cisplatin is preferred because it is logistically easier to administer. Most randomized trials to date have compared CRT to RT alone. As such, studies evaluating the efficacy of different CRT programs are limited. For example, for purposes of the MACH-NC analysis, “platin” included both cisplatin and carboplatin. Yet, the relative efficacy of these agents, when given concurrently, is not well studied. The RTOG reported a randomized phase II study comparing three different chemotherapy regimens, all delivered concurrently with 70 Gy in 2-Gy fractions: arm 1, cisplatin 10 mg/m2/day and 5-fluorouracil 400 mg/m2/day continuous infusion for the final 10 days of treatment; arm 2, hydroxyurea 1 g every 12 hours and 5-fluorouracil 800 mg/m2/day continuous infusion every other week; or arm 3, weekly paclitaxel 30 mg/m2 and cisplatin 20 mg/m2. Among 231 analyzable patients, 2-year disease-free and overall survival rates were 38.2% and 57.4% for arm 1, 48.6% and 69.4% for arm 2, and 51.3% and 66.6% for arm 3, respectively.157 Because anemia may adversely affect the efficacy of RT, the integration of an appropriate hematopoietic growth factor has been investigated. In a multicenter, double-blind, randomized, placebo- controlled trial, the addition of erythropoietin 300 IU/kg three times weekly during postoperative RT was evaluated in 351 patients with HNSCC.158 Although target hemoglobulin levels were reached in 82% of patients receiving erythropoietin compared to 15% receiving placebo, local–regional progression-free survival (adjusted relative risk [RR], 1.62; 95% CI, 1.22 to 2.14; P = .0008), local–regional progression (RR, 1.69; 95% CI, 1.16 to 2.47; P = .007), and survival (RR, 1.39; 95% CI, 1.05 to 1.84; P = .02) were all inferior on the erythropoietin arm. Consistent with the FDA alert, an erythropoietin-stimulation agent is contraindicated during curative-intent RT-based therapy.159 Transfusion, then, is the preferred approach to address potential radiation resistance attributed to anemia, but a recent analysis of two randomized trials failed to demonstrate that prophylactic transfusion improved overall survival or other disease control end points.160 Use of a hypoxic radiosensitizer represents another strategy to potentially address tumor hypoxia. The results of one meta-analysis were consistent with potential benefit161; randomized trials, however, have not been convincing in terms of improved disease control with such a strategy.162,163 An important question is whether the use of newer, more efficacious, and altered fractionated RT programs164 obviates the benefits accrued with the addition of chemotherapy. However, the MACH-NC analysis, which demonstrated significant HRs, that are consistent with benefits among patients receiving postoperative RT (HR, 0.79), conventional RT (HR, 0.83), or altered fractionated RT (HR, 0.73), suggesting a benefit for adding concomitant chemotherapy regardless of the type of RT schedule.150 Of note, the converse—once concurrent chemotherapy is added, does an altered fractionation RT schedule further improve outcome compared to that seen with standard fractionation—has not been established in randomized trials. Neither RTOG 0129 (standard versus concomitant boost RT both with concurrent high-dose cisplatin)9 nor GORTEC 99-02 (accelerated RT with or without concurrent carboplatin and 5-fluorouracil, standard fractionated RT with concurrent carboplatin and 5-fluorouracil)41 demonstrated improved overall survival with the incorporation of altered fractionated RT with concurrent chemotherapy versus standard fractionation with concurrent chemotherapy to justify the added logistical complexity and potential added toxicity. That said, there are no prospective randomized trials comparing concomitant chemotherapy with hyperfractionated RT with concomitant chemotherapy and daily RT. For patients who are not cisplatin candidates, using a carboplatin-based program (e.g., carboplatin/5fluorouracil)131 or other concurrent programs that have different side effect profiles and that withstood the scrutiny of a randomized trial is recommended. There has been great interest in cetuximab and concurrent RT in this regard.165 In a randomized study reported by Bonner et al.,166 patients with local–regionally advanced HNC were randomized to RT alone (213 patients) or combined with weekly cetuximab dosed in a standard fashion (211 patients); median follow-up was 54 months. The median duration of survival was 49 months after combined therapy compared with 29 months after RT alone (P = .03). Other than an acneiform rash and infusion reactions, grade 3 or greater complications were similar in the two groups of patients. The results of this trial have been confirmed with longer follow-ups.166 Patients with oropharynx cancer appeared to derive the largest benefit with

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the integration of cetuximab, suggesting that HPV-related disease may have an improved outcome with the use of this agent; other studies, however, suggest greater activity of EGFR-directed antibody therapy in HPV-negative disease.91,94 Randomized data comparing cetuximab and RT to other CRT programs are limited. The RTOG did a large randomized trial (RTOG 0522, n = 891 analyzable patients) intended to assess the efficacy and safety of this regimen compared to concurrent cisplatin and RT. The incorporation of cetuximab failed to significantly improve 3-year progression-free survival (61.2% versus 58.9%, P = .76) or overall survival (72.9% versus 75.8%, P = .32), but mucosal and skin toxicity were increased.167 In the NCCN guidelines,147 concurrent cisplatin with RT is the preferred CRT choice. It is important to emphasize that concurrent CRT may be associated with significant toxicity; treatment-related mortality (6 mL are treated with a partial or total laryngectomy.316,317 The anatomic constraints include no extension inferior to the apex of the ventricle, minimal or no involvement of the medial wall of the pyriform sinus, mobile cords, no cartilage invasion, and limited lateralized extension to the tongue base. TLM and TORS offer excellent survival and functional outcomes without the morbidity of an open partial laryngectomy and are increasingly used for suitable candidates.318 Patients who are not candidates for the supraglottic laryngectomy are treated with RT; concomitant chemotherapy is added for those with stage III to IV disease. When a patient presents with an early-stage primary lesion and N2b to N3 neck disease, a combined treatment approach may be necessary to produce a high rate of neck control. Thus, the primary lesion is preferably treated with CRT, with neck dissection(s) added to the involved side(s) of the neck if necessary. If the patient has N1 or N2a neck disease and surgery is elected for the primary site, postoperative RT or CRT is only added because of

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unexpected findings (e.g., positive margins, multiple positive nodes, ECE). The probability of a good functional result is improved if the dose to the remaining larynx is limited to 55 Gy at 1.8 Gy per once-daily fraction. The involved neck may be boosted to a higher dose without irradiating the larynx. Selected unfavorable T3 and T4 lesions that are mainly exophytic can be treated by CRT. Lesions unsuitable for RT are endophytic, high-volume cancers often associated with vocal cord fixation, which are managed by a total laryngectomy.

Surgical Treatment Supraglottic Laryngectomy The traditional supraglottic laryngectomy requires an apron incision with neck dissection left attached to the thyrohyoid membrane. The perichondrium of the larynx is elevated in continuity with the strap muscles and used to close the surgical defect. Saw cuts are made through the thyroid cartilage, and the pharynx is entered above the hyoid bone through the vallecula so the preepiglottic space is included in the specimen. The arytenoids and true vocal cords are preserved. If one arytenoid is sacrificed, the vocal cord is fixed in the midline to prevent aspiration. Suturing the perichondrium and muscle to the base of tongue closes the defect. The extended supraglottic laryngectomy may include resection of the base of tongue to the level of the circumvallate papillae as long as one lingual artery is spared. TORS and TLM may accomplish the same resection transorally with the aid of endoscopic cameras. Incisions are made around the lesions with the goal to remove the supraglottic structure en bloc. Margins are obtained up to the thyroid cartilage and down to the ventricles as well as around the arytenoids.318

Total Laryngectomy The entire larynx and the preepiglottic space are resected en bloc and a permanent tracheostoma is fashioned. This can be done in an open approach or in some cases transorally with the use of a robot.319 A portion of the thyroid gland is also removed if there is extralaryngeal or subglottic extension. The pharyngeal defect is closed with or without a flap, reestablishing a conduit from the pharynx into the esophagus.

Irradiation Technique The primary lesion and both sides of the neck are included with opposed lateral portals. The inferior border of the portals depends on the inferior extent of the primary tumor; it is usually at the inferior border of the cricoid. The dose is 74.4 Gy in 62 twice-daily fractions; the lower neck nodes are irradiated through a separate anterior portal. Patients with ipsilateral positive nodes may be treated with IMRT to reduce the dose to the contralateral parotid and/or to avoid a difficult low neck match. An alternative is 70 Gy in 35 fractions over 30 treatment days. Patients develop a sore throat, loss of taste, and moderate dryness during RT. Arytenoid edema may occur and produce the sensation of a lump in the throat. A tracheostomy is seldom necessary before the start of RT. Laryngeal edema may persist for up to a year. Neck dissection increases the degree of lymphedema; a bilateral neck dissection should be avoided, if possible.320

Combined Treatment Policies If a total laryngectomy is required and the lesion is resectable, postoperative RT or CRT, depending on the pathology, is preferred. The high-risk areas are usually the base of tongue and neck. The stoma is at risk when subglottic extension is present or if there is tumor in the low neck lymph nodes.

Management of Recurrence Failures after supraglottic laryngectomy or RT frequently can be salvaged by further treatment. The salvage of recurrences that develop after total laryngectomy and adjuvant RT is uncommon.

TREATMENT: SUBGLOTTIC LARYNX CARCINOMA Early lesions are treated with RT; advanced lesions are usually managed by a total laryngectomy and

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postoperative RT or CRT.

Results of Treatment Vocal Cord Cancer Surgical Results. Garcia-Serra et al.306 reviewed 10 series containing 269 patients with CIS of the vocal cord treated with stripping; the weighted average 5-year local control and ultimate local control rates were 71.9% and 92.4%, respectively. Similarly, 10 series containing 177 patients treated with carbon dioxide laser revealed the following weighted average 5-year local control and ultimate local control rates: 82.5% and 98.1%, respectively.306 Early vocal cord cancers treated with TLM have very high control rates. The 5-year disease-free and overall survival rates have been reported as 87.9% and 92.2%, respectively.321 These results are comparable to primary RT results reported at the University of Florida.302 Advanced laryngeal cancers (T3 and T4a) require multimodality treatment, as found in the landmark VA Laryngeal Cancer Study.132,136 Most advanced laryngeal cancers were treated with primary CRT starting in the mid-1990s; however, various population-based studies from 2000 to 2015 have questioned whether survival rates are preserved in patients with advanced tumors treated without primary surgery. Studies have shown that T4a cancers may have superior survival outcomes when treated with primary total laryngectomy plus adjuvant RT or CRT versus nonsurgical organ preservation.322–325 The NCCN guidelines advise primary surgical management as the preferred approach for treatment of T4a disease.147 For T3 laryngeal cancers the lines are more blurred.325–330 Reported differences in resection versus organ preservation surgery and nonsurgical organ preservation results may reflect in part center-specific expertise and differences in patient selection. Another way of selecting T3 cancers for organ preservation is through tumor volume. At the University of Florida, the multidisciplinary head and neck tumor board uses a cutoff tumor volume of 3.5 cm3. Patients with tumors ≤3.5 cm3 are offered organ preservation, whereas those with larger tumors are recommended to undergo total laryngectomy. This protocol has been supported through several studies.331 Radiation Therapy Results. The results of RT for 585 patients with T1 and T2N0 SCC of the glottis treated by RT are presented in Table 45.16. The 5-year rates of neck control for the overall groups and for the subsets of patients who remained continuously disease free at the primary site were as follows: for T1a, 98% and 100%; for T1b, 99% and 100%; for T2a, 96% and 98%; and for T2b, 88% and 94%, respectively.302 The 5-year outcomes after RT alone (53 patients) versus surgery alone or combined with RT (65 patients) in a series of 118 patients with T3 fixed-cord glottic carcinomas treated at the University of Florida were as follows: for local–regional control, 62% versus 75% (P = .10); for ultimate local–regional control, 84% versus 82% (P = .95); for cause-specific survival, 75% versus 71% (P = .26); for overall survival, 55% versus 45% (P = .119); and for severe complications, 16% versus 15% (P = .558), respectively.309 Hinerman et al.332 recently updated the University of Florida experience and reported a 5-year local control rate of 63% for 87 patients with T3 fixed-cord glottic carcinomas. The likelihood of local control after RT is related to primary tumor volume and cartilage sclerosis.333 The probability of cure after treatment for T4 glottic carcinomas after surgery with or without adjuvant RT or definitive RT varies from 30% to 50% depending on patient selection.332–338

TREATMENT: SUPRAGLOTTIC LARYNX CANCER The 5-year local control rates after definitive RT in a series of 274 patients treated between 1964 and 1998 at the University of Florida were as follows: for T1, 100% (n = 22); for T2, 86% (n = 125); for T3, 62% (n = 99); and for T4, 62% (n = 28).339 The likelihood of local control and local control with a functional larynx is related to tumor volume; those with tumors ≤6 mL have a more favorable outcome than those with larger primary tumors.317 The 5-year rates of local–regional control and cause-specific survival were as follows: stage I, 100% and 100%; stage II, 86% and 93%; stage III, 64% and 81%; stage IVA, 61% and 50%; and stage IVB, 28% and 13%, respectively.339 Of 274 patients, 12 (4%) experienced a severe acute or late complication, and 2 patients (1%) died as a consequence.

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Lee and coworkers340 reported on 60 patients who underwent a supraglottic laryngectomy and modified neck dissection at the MD Anderson Cancer Center between 1974 and 1987, of which 50 patients (83%) received postoperative RT. Local control was 100%, and local–regional control was obtained in 56 of 60 patients (93%). The 5-year disease-free survival rate was 91%. A total of 3 of 60 patients (5%) required a complete laryngectomy for intractable aspiration. Ambrosch and colleagues341 reported on 48 patients treated with transoral laser resection for T1N0 (12 patients) and T2N0 (36 patients) supraglottic carcinoma. A total of 26 patients underwent a unilateral (11 patients) or bilateral (15 patients) neck dissection. Postoperative RT was administered to 2 patients (4%). The 5-year local control rates were 100% for pT1 cancers and 89% for pT2 malignancies. The 5-year recurrence-free survival and overall survival rates were 83% and 76%, respectively. No patient developed severe aspiration.

Complications of Treatment Surgical Treatment Repeated laser excision of the cord may result in vocal cord fibrosis and hoarseness. Chiesa Estomba et al.342 reported a 2% intraoperative, 6% early, and 13% late complication rate in TLM for laryngeal cancers. Intraoperative complications include airway fire and loss of a tooth. Early postoperative complications include aspiration, pneumonia, bleeding, wound complications, and airway obstruction requiring a tracheotomy. Late complications include chondritis, laryngeal stenosis/web, and recurrent aspiration. The complication rate following supraglottic laryngectomy is about 10%, including fistula formation, aspiration, chondritis, dysphagia, dyspnea, and rare carotid rupture.339 The common postoperative complications of a total laryngectomy may include infection/abscess, fistula, bleeding, hypocalcemia, and pharyngoesophageal stenosis. TABLE 45.16

T1 to T2N0 Glottic Larynx: 5-Year Outcomes After Radiotherapy in 585 Patients No. of Patients

Local Control

T1a

253

94%

98%

95%

97%

82%

T1b

72

93%

97%

94%

99%

83%

T2a

165

80%

96%

81%

94%

76%

Stage

Ultimate Local Control

Local Control with Larynx Preservation

Cause-Specific Survival

Survival

T2b 95 70% 93% 74% 90% 78% Data from Chera BS, Amdur R, Morris CG, et al. T1N0 to T2N0 squamous cell carcinoma of the glottic larynx treated with definitive radiotherapy. Int J Radiat Oncol Biol Phys 2010;78(2):461–466.

Radiation Therapy Soft tissue necrosis leading to chondritis occurs in about 1% of patients. Soft tissue and cartilage necroses mimic recurrence with hoarseness, pain, and edema; a laryngectomy may be recommended for fear of recurrent cancer, even though biopsies show only necrosis. Chera et al.302 recorded severe complications after definitive RT in 10 of 585 (1.7%) patients treated for T1 to T2N0 glottic SCCs.

Combined Treatment The major late effects of combined treatment are an increased fibrosis of soft tissues, stomal stenosis, and pharyngeal stricture.

HYPOPHARYNX: PHARYNGEAL WALLS, PYRIFORM SINUS, AND POSTCRICOID PHARYNX Both the lower oropharyngeal and hypopharyngeal walls are considered together because there is no distinct difference in the presentation or treatment. The majority of hypopharyngeal lesions originate in the pyriform sinus. Postcricoid carcinomas are uncommon.

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ANATOMY The epithelium of the pharyngeal mucous membrane is squamous. The dividing point between the nasopharynx and posterior pharyngeal wall is Passavant ridge, a muscular ring that contracts to close the nasopharynx during swallowing. Between the constrictor muscles and the prevertebral fascia covering the longitudinal prevertebral muscles is a thin layer of loose areolar tissue, the retropharyngeal space. The entire thickness of the posterior pharyngeal wall from the mucous membrane to the anterior vertebral body is no more than 5 to 10 mm in the midline. Lateral to the pharyngeal wall are the great vessels, nerves, and muscles of the parapharyngeal space. The constrictor muscles are relatively thin and do not present much of an obstacle to tumor penetration; however, if they have not been invaded by tumor, they act as a barrier to spread into the parapharyngeal space. There is a variable weak spot in the lateral pharyngeal wall just below the hyoid where the middle and the inferior constrictor muscles fail to overlap. The lateral wall in this area is composed of the thin thyrohyoid membrane, which is penetrated by the vessels, nerves, and lymphatics of the laryngopharynx. The pharyngeal walls are continuous with the cervical esophagus below; the transition to cervical esophagus is below the arytenoids (C4). The transition zone, which is 3 to 4 cm in length, is the postcricoid hypopharynx. The lateral pharyngeal wall is a narrow strip of mucosa that lies behind the posterior tonsillar pillar in the oropharynx, is partially interrupted by the pharyngoepiglottic fold, and then continues into the hypopharynx, where it becomes the lateral wall of the pyriform sinus. The posterior pharyngeal wall is 4 cm to 5 cm wide and 6 cm to 7 cm in height. The superior margin of the pyriform sinus is the pharyngoepiglottic fold and the free margin of the aryepiglottic fold. The superolateral margin of the pyriform sinus is an oblique line along the lateral pharyngeal wall opposite the aryepiglottic fold. Thus, the pyriform sinus has three walls: the anterior, lateral, and medial (there is no posterior wall). The pyriform sinus tapers inferiorly to the apex and terminates variably at a level between the superior and inferior borders of the cricoid cartilage. The superior limit of the pyriform sinus is opposite the hyoid. The thyrohyoid membrane is lateral to the upper portion of the pyriform sinus, and the thyroid cartilage, cricothyroid membrane, and cricoid cartilage are lateral to the lower portion. The internal branch of the superior laryngeal nerve, a branch of the vagus, lies under the mucous membrane on the anterolateral wall of the pyriform sinus. The auricular branch is sensory to the skin of the back of the pinna and the posterior wall of the external auditory canal. The postcricoid pharynx is funnel shaped to direct food into the esophagus. The superior margin begins just below the arytenoids. The anterior wall lies behind the cricoid cartilage and is the posterior wall of the lower larynx. The posterior wall is a continuation of the hypopharyngeal walls. The recurrent laryngeal nerve ascends in the tracheoesophageal groove, entering the larynx posterior to the cricothyroid articulation at the junction of the hypopharynx and esophagus. Internal branches of the superior laryngeal nerve extend inferiorly anterior to the mucosa of the pyriform sinuses.

PATHOLOGY More than 95% of malignant tumors are SCCs. CIS is commonly seen at the edge of pharyngeal wall SCCs; multifocal skip areas of CIS may make it difficult to obtain clear margins if excision is done. Minor salivary gland tumors are rare.

PATTERNS OF SPREAD Posterior Pharyngeal Wall SCCs of the posterior wall have a tendency to remain on the posterior wall, grow up or down the wall, and infiltrate posteriorly; they seldom spread circumferentially to the lateral walls. Early lesions are red and ulcerate as they progress. The tumor may spread up the pillars, eventually reaching the palate and nasopharynx. Advanced lesions tend to terminate inferiorly at the level of the arytenoids. Direct invasion of the cervical vertebrae or skull base is uncommon.

Lateral Pharyngeal Wall

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Early tumors may be well-defined exophytic lesions. As they advance, they tend to penetrate laterally through the constrictor muscle, thus entering the lateral pharyngeal space or the soft tissues of the neck.

Pyriform Sinus Early lesions usually appear as nodular mucosal irregularities. Medial wall lesions may grow superficially along the aryepiglottic fold and arytenoids or invade directly into the false cord and aryepiglottic fold. Medial wall lesions also extend posteriorly to the postcricoid region, to the cricoid cartilage, and to the opposite pyriform sinus. Extensive submucosal spread is characteristic. There is frequently an area of central ulceration. The vocal cord becomes fixed because of infiltration of the intrinsic muscles of the larynx, the cricoarytenoid joint or muscle, or, less commonly, the recurrent laryngeal nerve. Spread into the cervical esophagus is a late event. Lesions arising on the lateral wall tend toward early invasion of the posterior thyroid cartilage and the posterior superior cricoid cartilage and, eventually, invade the thyroid gland. Involvement of the pyriform sinus apex is associated with an increased risk of thyroid cartilage invasion.343 Lesions of the lateral walls tend to spread submucosally to the posterior pharyngeal wall.

Postcricoid Pharynx Early postcricoid lesions are rare. Lesions arising from the posterior wall tend to remain on the posterior wall. Lesions arising from the anterior wall tend to invade the posterior cricoarytenoid muscle and the cricoid and arytenoid cartilages. Advanced tumors eventually encircle the lumen.

Lymphatic Pharyngeal Walls The lymphatics of the pharyngeal walls terminate primarily in the jugular chain and secondarily in the level V nodes. The level II nodes are most often involved. Lindberg22 reported 59% clinically positive nodes at diagnosis; 17% were bilateral. Retropharyngeal lymph node involvement is frequent.

Pyriform Sinus The drainage is mainly to the jugular chain with a relatively small proportion to the level V nodes. The level II nodes are most commonly involved, but level III involvement occurs without level II metastases. At diagnosis, 75% of patients have clinically positive nodes, and at least 10% have bilateral nodes. There is no difference in the risk of lymph node metastases by T stage. The incidence of subclinical neck disease probably exceeds 50%.344

CLINICAL PICTURE Tumors that are lateralized to the lateral pharyngeal wall or pyriform sinus produce a unilateral sore throat. Dysphagia, ear pain, and voice changes occur later. A neck mass may be the presenting complaint. Lesions of the apex of the pyriform sinus or postcricoid area produce a pooling of secretions, indicating obstruction of the gullet. Arytenoid edema and an inability to see into the apex of the pyriform sinus may be observed.

STAGING The staging system for the primary tumor is depicted in Table 45.17. TABLE 45.17

Hypopharynx: 2017 American Joint Committee on Cancer Staging System for the Primary Tumor TX

Primary tumor cannot be assessed

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Tis

Carcinoma in situ

T1

Tumor limited to one subsite of hypopharynx and/or 2 cm or smaller in greatest dimension

T2

Tumor invades more than one subsite of hypopharynx or an adjacent site, or measures larger than 2 cm but not larger than 4 cm in greatest dimension without fixation or hemilarynx

T3

Tumor larger than 4 cm in greatest dimension or with fixation of hemilarynx or extension to esophagus

T4

Moderately advanced and very advanced local disease T4a

Moderately advanced local disease Tumor invades thyroid/cricoid cartilage, hyoid bone, thyroid gland, or central compartment soft tissuea

T4b

Very advanced local disease Tumor invades prevertebral fascia, encases carotid artery, or involves mediastinal structures

aNote: Central compartment soft tissue includes prelaryngeal strap muscles and subcutaneous fat.

Used with the permission of the American College of Surgeons. The original source for this material is the AJCC Cancer Staging Manual, Eighth Edition (2017) published by Springer International Publishing AG.

TREATMENT Selection of Treatment Modality Posterior Pharyngeal Wall RT has produced similar cure rates to surgery and has historically been less morbid. However, with the recent use of robotic surgery, TORS resections of T1 and T2 posterior pharyngeal wall tumors has led to excellent survival and functional outcomes.345

Lateral Pharyngeal Wall The preferred treatment for early-stage lesions is TLM or definitive RT.

Pyriform Sinus T1 and low-volume (≤6 mL), exophytic T2 cancers with normal cord mobility can be treated either by RT or partial laryngopharyngectomy.346 RT has been preferred because it has historically resulted in less morbidity; however, novel transoral approaches such as TORS and TLM are producing encouraging oncologic and functional results in selected patients.318,347 Selected high-volume endophytic T2 and T3 lesions with normal or reduced mobility may be suitable for CRT. The swallowing outcomes after concurrent CRT may be less optimal than those seen in the oropharynx and larynx.348 The remainder are best treated with a total laryngopharyngectomy, neck dissection, and postoperative RT or CRT.

Surgical Treatment Posterior Pharyngeal Wall If the lesion is high on the posterior wall, a transoral approach can be used. Lower lesions were traditionally accessed via a transhyoid approach, a lateral pharyngotomy, or a midline mandibulolabial glossotomy. More recently, TLM and TORS resection has been employed to reduce the morbidity associated with open approaches. Dissection extends deep to the tumor down to the prevertebral fascia; smaller defects heal by secondary intention without a skin graft, whereas larger defects may require a free flap.318

Pyriform Sinus Partial Laryngopharyngectomy. A partial laryngopharyngectomy removes the false cords, epiglottis, aryepiglottic fold, and pyriform sinus; one arytenoid may be removed when necessary. The vocal cords are preserved. The following findings contraindicate a partial laryngopharyngectomy: extension to the apex of the pyriform sinus; a fixed cord; extension to contralateral arytenoid; poor pulmonary function; and large, fixed lymph nodes. Unfortunately, functional outcomes are unpredictable using traditional open approaches, and

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resections of smaller hypopharyngeal lesions are more likely to be cured with good function using TLM.349 Total Laryngopharyngectomy. Due to the mucosal extent and high risk of submucosal spread, a total laryngopharyngectomy is often needed to resect hypopharyngeal cancers. This operation removes the larynx and a large amount, if not all, of the pharyngeal mucosa. It is not uncommon to have a circumferential pharyngeal defect from base of tongue to esophagus. Reconstruction with a free flap is often needed.

Postcricoid Pharynx A total laryngopharyngectomy with reconstruction, generally using a free flap, is performed. If the lesion extends beyond the cervical esophagus, a gastric pull-up may be needed.

Irradiation Technique Posterior Pharyngeal Wall The RT technique is opposed lateral fields to include the primary lesion and the regional nodes. Because these lesions tend to “skip” areas, the entire posterior pharyngeal wall is included initially. If the lesion extends near the arytenoids, the postcricoid pharynx, pyriform sinuses, and upper cervical esophagus are included. The retropharyngeal nodes are included even if the neck is N0. When the field is reduced at 45 Gy to avoid the spinal cord, the posterior border of the portal is placed just anterior to the spinal cord.350 The dose is 74.4 to 76.8 Gy, at 1.2 Gy per fraction twice daily, in a continuous course. Another option is 70 Gy in 35 fractions over 30 treatment days. IMRT is useful to reduce the dose to one or both parotids. Concomitant chemotherapy should be included for stage III to IV cancers.

Pyriform Sinus Parallel-opposed lateral portals are used to encompass the primary lesion and regional nodes on both sides. The superior border is placed 2 cm above the tip of the mastoid to cover the most superior jugular chain and the retropharyngeal lymph nodes. The posterior border encompasses the level V nodes. Clinically positive nodes behind the plane of the spinal cord require an electron boost. The anterior border is usually placed about 0.5 to 1 cm behind the anterior skin edge if it is possible to do so and adequately encompass the tumor. The inferior border is 2 cm below the inferior border of the cricoid. The remaining lower neck lymph nodes are treated through an en face portal. The doses are the same as for the posterior pharyngeal wall. IMRT is an option if the tumor can be adequately encompassed while sparing the contralateral salivary gland(s) and/or to avoid a difficult low neck match.

Combined Treatment Policies Posterior Pharyngeal Wall An operation should usually precede RT when a combination is selected, unless a gastric pull-up is planned.

Pyriform Sinus Following a total laryngopharyngectomy, RT is usually recommended for indications previously outlined. RT, CRT, or induction chemotherapy is used prior to operation for patients with nodal disease encasing the common or internal carotid. The dose to the primary tumor ranges from 45 to 50 Gy; the fixed nodes are boosted to 60 to 75 Gy.

Management of Recurrence Posterior Pharyngeal Wall Recurrence after RT may be limited to the posterior pharyngeal wall and may be suitable for surgical excision, with occasional salvage. There is frequently a persistent ulcer after RT for advanced lesions; it should be considered evidence of persistent disease if it does not heal. Surgical excision is limited posteriorly by the prevertebral fascia. RT salvage of a surgical failure is unusual.

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Pyriform Sinus The hallmark of local recurrence after RT is persistent edema, pain, and fixation of laryngeal structures. A direct laryngoscopy is required, but the biopsy may be negative. A CT and/or PET scan is often helpful for distinguishing local recurrence from necrosis. It may be necessary to recommend a total laryngopharyngectomy for salvage without a positive biopsy. Recurrence after a total laryngopharyngectomy is usually in the soft tissues of the neck, the untreated opposite neck, the base of tongue, or stoma. Surgical failures after a partial laryngopharyngectomy for early lesions may be salvaged by a total laryngopharyngectomy. Failures after a total laryngopharyngectomy are rarely salvaged.

RESULTS OF TREATMENT Pharyngeal Wall The 5-year local control rates and ultimate local control rates after RT at the University of Florida for 170 patients were as follows: T1 (n = 14), 93% and 93%; T2 (n = 51), 84% and 91%; T3 (n = 75), 60% and 62%; and T4 (n = 30), 44% and 44%, respectively.350 The 5-year local–regional control and cause-specific survival rates were 88% and 88% for stage I, 85% and 89% for stage II, 49% and 44% for stage III, and 44% and 35% for stage IV, respectively.350 For advanced-stage tumors, CRT is advised.

Pyriform Sinus The results of treatment for 80 patients with carcinoma of the pyriform sinus treated at Washington University by preoperative RT followed by a partial laryngopharyngectomy are shown in Table 45.18.351 A total of 70 patients had the equivalent of AJCC T1 lesions (disease limited to the pyriform sinus), 10 patients had disease extending beyond the pyriform sinus, and none had invasion of the apex of the pyriform sinus. The cause of death was cancer in 26%, complications of treatment in 14%, and intercurrent disease in 20%. The 5-year absolute survival was 25 of 66 patients (38%) (JE Marks, personal communication, 1979). The results of treatment for 57 patients from the same institution who were treated by preoperative RT followed by total laryngectomy and partial pharyngectomy are depicted in Table 45.18.351 A total of 35 patients had lesions confined to the pyriform sinus (AJCC T1), and the remainder had extension beyond the pyriform sinus (AJCC T2 to T4). The cause of death was cancer in 56% of patients, complications of treatment in 11% of patients, and intercurrent disease in 18% of patients. The 5-year local control rates for 123 patients treated with definitive RT for T1 (23 patients) and T2 (100 patients) pyriform sinus SCCs were 85% for T1 and 85% for T2, respectively.348 The 5-year rates of local– regional control and cause-specific survival were as follows: stages I to II, 86% and 85%; stage III, 65% and 73%; stage IVA, 83% and 62%; and stage IVB, 24% and 22%, respectively.348 The 5-year distant metastasis–free survival rates were 96% for N0, 88% for N1, 68% for N2, and 55% for N3. For advanced-stage tumors, CRT is advised. TABLE 45.18

Carcinoma of the Pyriform Sinus: Results of Treatment by Low-Dose Radiation Therapy plus Partial Laryngopharyngectomy or Total Laryngectomy and Partial Pharyngectomy (Washington University, St. Louis, 1964–1974) PLP (80 Patients)a

Result

TLP (57 Patients)b

14%c

14%

Neck recurrence ± distant metastases (primary controlled)

9%

23%

Distant metastases alone

11%

21%

Five-year actuarial survival (no evidence of disease)

40%

22%

Local recurrence ± neck recurrence

aT1, 70 patients; T2–T4, 10 patients (American Joint Committee on Cancer staging). bT1, 35 patients; T2–T4, 22 patients (American Joint Committee on Cancer staging). c

Four patients salvaged. PLP, partial laryngopharyngectomy; TLP, total laryngopharyngectomy.

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Data from Marks JE, Kurnik B, Powers WE, et al. Carcinoma of the pyriform sinus. An analysis of treatment results and patterns of failure. Cancer 1978;41(3):1008–1015.

Surgically treated advanced hypopharyngeal cancers carry a 5-year overall survival rate of 60% to 70% and disease-free survival of 50% to 60%. Similarly matched patients treated with primary RT-based treatments had rates of 41% and 35%, respectively.352 Survival is significantly improved with the addition of postoperative RT/CRT. A randomized trial done by the EORTC revealed no difference in survival between primary surgery and postoperative RT versus a CRT approach using induction chemotherapy with surgery reserved for salvage.137

COMPLICATIONS OF TREATMENT Posterior Pharyngeal Wall Surgical Treatment Complications Complications of surgery are the same as listed for laryngeal cancers previously.

Radiation Therapy Complications Mendenhall and coworkers350 observed nine fatal complications (5%) in 170 patients who were treated at the University of Florida. A total of 25 patients (15%) experienced nonfatal severe complications including permanent feeding tube (17 patients), soft tissue and/or bone necrosis (7 patients), and permanent tracheostomy (1 patient).

Pyriform Sinus Surgical Treatment Complications The complications of a partial laryngopharyngectomy included a 12% operative mortality, fistula, aspiration, and dysphagia.351 The complications of total laryngopharyngectomy included a treatment-related mortality of 11%, fistula, and pharyngeal stenosis.351 The complication rate is increased by the addition of RT.

Radiation Therapy Complications The major RT complication is laryngeal necrosis. Rabbani et al.348 reported the following rates of moderate-tosevere complications in 123 patients: acute (2%), late (9%), and postoperative (5%).

Complications of Salvage Treatment Attempted surgical salvage of RT failures has a significant operative morbidity and mortality; few patients are cured.

NASOPHARYNX NPCs are uncommon in the United States. The Chinese have a high frequency; American-born second-generation Chinese maintain the risk of NPC. NPCs have been shown to have an association with elevated titers of EBV, which is independent of geography.353 There is a 3:1 ratio of predominance in men. The age distribution for NPC is younger than for other head and neck sites; about 20% of patients are younger than 30 years of age.

ANATOMY The nasopharynx is roughly cuboidal in shape. It is contiguous with the nasal cavity, inferior with the oropharynx, and lateral with the middle ears by way of the eustachian tubes. The mucosa of the roof and posterior wall is often irregular because of the pharyngeal bursa, adenoids, and pharyngeal hypophysis; it tends to become smooth with age. The lateral walls include the eustachian tube openings with the fossa of Rosenmüller, located behind the torus tubarius. The superolateral muscular wall of the nasopharynx is incomplete. The floor of the nasopharynx is

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incomplete and consists of the upper surface of the soft palate.

Lymphatic There is an extensive submucosal lymphatic capillary plexus. The tumor spreads along three different pathways: the jugular chain, the spinal accessory chain, and the retropharyngeal pathway.354 The lateral retropharyngeal nodes lie in the retropharyngeal space medial to the carotid artery. Directly behind the nodes are the lateral masses of C1 and C2. Inconstant lymphatic vessels may drain directly to the level III and V nodes.15

PATHOLOGY Carcinomas compose about 85% and lymphomas about 10% of the malignant lesions. NPCs are classified as follows: keratinizing SCC (WHO type I), nonkeratinizing carcinoma (WHO type II), and undifferentiated (WHO type III) basaloid SCC. Lymphoepithelioma is included in the WHO type II and III categories. A miscellaneous group of malignant tumors includes melanoma, plasmacytoma,268 juvenile angiofibroma,16 carcinosarcoma, sarcomas, nonchromaffin paragangliomas, and minor salivary gland tumors.

PATTERNS OF SPREAD Primary Inferior extension along the lateral pharyngeal walls and tonsillar pillars occurs in almost one-third of patients. Extension into the posterior nasal cavity is frequent but is usually limited to 60 mL was associated with a lower likelihood of local control after RT. Teo and colleagues362 evaluated a series of 903 patients treated at the Prince of Wales Hospital, Hong Kong, and observed that local control was adversely affected by advanced patient age, skull base invasion, and CN involvement. Prognostic factors associated with an increased rate of distant metastases and poor survival were

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male sex, skull base and CN(s) involvement, advanced neck stage, nodal fixation, and bilateral neck nodes.362 The 5-year outcomes for 82 patients treated at the University of Florida were 78% for local control, 90% for regional control, 76% for local–regional control, 80% for distant metastasis–free survival, 66% for cause-specific survival, and 57% for survival.363 Table 45.9 summarizes the results of selected randomized trials comparing CRT versus RT alone.

FOLLOW-UP The follow-up includes careful observation and laboratory testing for possible thyroid and/or pituitary hypofunction. Dental care must be closely monitored because of xerostomia.

COMPLICATIONS OF TREATMENT Primary or secondary hypopituitarism (from a hypothalamic lesion) has been reported. Brain necrosis is rare. Hypothyroidism may result from either a direct effect on the thyroid gland or an indirect effect on the pituitary. A transient CNS syndrome may appear 2 to 3 months after RT and would require several months to resolve. General weakness and extreme fatigue may be symptoms of low serum cortisol levels. Radiation myelitis of the cervical cord or brain stem is the most severe CNS complication. IMRT may be used to reduce the dose to the CNS, particularly the temporal lobes. Trismus may occur because of fibrosis of the pterygoid muscles. Palsy of CNs IX to XII may occur several years after RT and is related to nerve entrapment in the lateral pharyngeal space. Eye complications (e.g., retrobulbar optic neuritis) may develop owing to RT of the optic nerve.364 RT of the posterior eyeball to high doses may produce a retinopathy.365

NASAL VESTIBULE, NASAL CAVITY, AND PARANASAL SINUSES Tumors of the nasal vestibule are considered separately from nasal cavity tumors because they are essentially skin cancers and have a different natural history. Primary tumors arising from the nasal cavity and paranasal sinuses are considered together because the lesions are frequently advanced when first seen and it is not always possible to determine the site of origin. Cancer of the nasal cavity or paranasal sinuses is a relatively rare problem, with a yearly risk factor estimated at approximately one case for every 100,000 people. They occur more often in men and usually appear after the age of 40 years except for minor salivary gland tumors and esthesioneuroblastomas, which may appear before the age of 20 years.366 Nasal cavity and ethmoid sinus adenocarcinomas have been linked to occupations associated with wood dust, such as the furniture industry, sawmill work, and carpentry. Other occupations with dust-filled work environments, such as shoemaking, baking, and the flour milling industry, also have been implicated.14 Carcinomas of the sphenoid and frontal sinuses are rare.

ANATOMY The nasal vestibule is the entrance to the nasal cavity. It is lined by skin in which there are numerous hair follicles and sebaceous glands. The vestibule is a three-sided, pear-shaped cavity about 1.5 cm in diameter that ends posteriorly at the limen nasi. The alar cartilages form the anterolateral wall. The medial wall is the columella, formed by the medial wing of the alar cartilage and the anterior portion of the cartilaginous septum. The floor is the maxilla. The nasal cavity begins at the limen nasi and ends at the posterior nares, where it communicates with the nasopharynx. The lateral walls are composed of thin bony folds that project into the nasal cavity: the inferior, medial, and superior turbinates. The nasolacrimal duct enters the nasal cavity beneath the inferior turbinate. The frontal sinus and ethmoid bullae connect to the nasal cavity with openings in the middle meatus. The sphenoid sinus communicates with the nasal cavity by an opening on the anterior wall of the sinus. Approximately 20 branches of the olfactory nerves enter the nasal cavity through the cribriform plate; nerve fibers are distributed over the upper one-third of the septum and the superior nasal turbinate. The epithelium is nonciliated columnar.

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The lower half of the nasal cavity is the respiratory portion, and the epithelium is ciliated columnar. There are numerous collections of lymphoid tissue and mucous glands beneath the epithelium. The maxillary sinuses are single pyramidal cavities. The medial wall is the lateral wall of the nasal cavity and has one or two openings communicating with the middle meatus under the medial turbinate. The inferior wall is the hard palate. The posterolateral wall is related to the zygomatic process and the pterygomaxillary space. The superior wall is the orbital floor. The frontal sinuses are two irregular, asymmetrical air cavities separated by a thin bony septum. They connect to the middle meatus of the nasal cavity by the frontonasal duct. They are separated from the anterior ethmoid cells by thin bony walls. The posterior wall separating the frontal sinus from the anterior cranial fossa is relatively thick. The ethmoid sinuses consist of a number of air cells lying between the medial walls of the orbits and the lateral wall of the nasal cavity. The lateral wall is the thin porous lamina papyracea. Medially, the ethmoid air cells bulge into the lateral wall of the nasal cavity. The ethmoid cells communicate with the nasal cavity in the middle meatus. These bony walls are thin and easily traversed by the tumor. The basal lamella of the middle turbinate separates anterior and posterior ethmoid air cells. The sphenoid sinus is a midline structure in the body of the sphenoid bone. The pituitary lies above, the cavernous sinuses laterally, the nasal cavity and ethmoid sinuses in front, and the nasopharynx beneath. The clivus and brain stem lie posteriorly. The pneumatization is variable and can extend into all portions of the sphenoid bone. The sphenoid sinus connects anteriorly with the nasal cavity in the sphenoethmoidal recess.

Lymphatic Nasal Vestibule The lymphatic trunks run to the level IB nodes. There is a small risk for involvement of the intercalated facial nodes just behind the commissure of the lip along the course of the facial neurovascular bundle.

Nasal Cavity and Paranasal Sinuses The lymphatics of the nasal cavity are separated into the olfactory group and the respiratory group. According to Rouvière,15 they do not communicate with each other. There is a connection between the lymphatic network of the olfactory region and the subarachnoid spaces, which allows some absorption of cerebrospinal fluid (CSF) into the lymphatic system. The lymphatics of the olfactory region of the nasal cavity run posteriorly to terminate in lymph nodes alongside the jugular vein at the skull base in the lateral pharyngeal space. The lymphatics of the respiratory nasal cavity terminate in the lateral retropharyngeal nodes or the level II nodes. The capillary lymphatic plexus of the nasal mucosa is probably not very profuse, judging by the relatively low incidence of metastatic nodes. The mucosa of the paranasal sinuses has either no or very sparse capillary lymphatics.

PATHOLOGY Benign Tumors Inflammatory polyps, giant cell reparative granulomas, benign odontogenic tumors, and necrotizing sialometaplasia may appear in this area. Inverted papilloma is a benign, aggressive neoplasm that is associated with carcinoma in 5% to 15% of cases.367

Malignant Tumors Nasal Vestibule Almost all malignant tumors are SCCs; basal cell carcinomas and adnexal carcinomas are also reported.

Nasal Cavity and Paranasal Sinuses SCC or one of its variants is the most common neoplasm. Minor salivary gland tumors account for about 10% to 15% of neoplasms in this region. Lymphoma and melanoma account for approximately 5% and 1% of cases,

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respectively. Esthesioneuroblastoma is a neuroendocrine carcinoma that originates from the olfactory mucosa. Sinonasal undifferentiated carcinoma—a more aggressive neuroendocrine malignancy—is sometimes encountered.368 Soft tissue and bone sarcomas may occur in the nasal cavity and paranasal sinuses, including chondrosarcoma, osteosarcoma, and Ewing sarcoma.369 Midline lethal granuloma is a nonkiller nasal T-cell lymphoma. Unchecked, the disease is fatal. Death results from extension to the CNS, hemorrhage, sepsis, or inanition. Treatment is usually RT, which is often combined with chemotherapy.370

PATTERNS OF SPREAD Nasal Vestibule Primary Lesions of the nasal vestibule invade the nasal mucosa, alar, and septal cartilages and may extend to the nasal skin. The upper lip is frequently invaded. Posterior growth into the nasal cavity is frequent. Early cancers originating on the columella and anterior septum are often superficial lesions that ulcerate and produce a crust or scab and often present with septal perforation.

Lymphatic Lymph node spread is usually to a solitary ipsilateral level IB node but may be bilateral. The facial, preauricular, and submental nodes are at low risk. Wallace et al.371 reported only 4 of 79 patients (5%) with clinically positive lymph nodes at diagnosis, but 9 patients (11%) later developed positive lymph nodes.

Nasal Cavity and Paranasal Sinuses Nasal Cavity Routes of spread are essentially the same for various histologies, with the exception of esthesioneuroblastoma and minor salivary gland tumors. The latter have a greater propensity for PNI. Lesions arising in the olfactory region invade the ethmoids and the orbit, spread through the cribriform plate to the anterior cranial fossa, and spread between bone and dura. Eventually, they penetrate the dura and invade the frontal lobes. These lesions also tend to destroy the septum and may invade through the nasal bone to the skin. Lesions arising on the lateral wall of the nasal cavity invade the maxillary sinus, ethmoids, and orbit. Esthesioneuroblastomas may show submucosal spread and may grow along olfactory nerves and penetrate through an intact dura to the frontal lobes. The nasopharynx and sphenoid sinus are secondarily invaded in advanced lesions. The tumor may follow nerves posteriorly and superiorly toward the sphenopalatine ganglion near the skull base or along V2.

Maxillary Sinus All walls of the sinus may be penetrated by the tumor; the pattern of spread and bone destruction is dependent on the site of origin within the sinus. Lesions arising in the anterolateral infrastructure tend to invade through the lateral inferior wall or grow through dental sockets, causing loosening of the teeth or improper seating of a denture. Ulceration follows, with the development of an oral–antral fistula. Lesions arising on the medial infrastructure readily extend into the nasal cavity. Posterior infrastructure lesions erode through the posterolateral wall and into the infratemporal fossa and extend superiorly to the skull base. Orbital extension occurs either through the roof of the maxillary sinus, through the ethmoids and lamina papyracea, or by way of the infratemporal fossa and then through the infraorbital fissure. Tumors arising in the suprastructure of the antrum have two general patterns of development. One group extends laterally, invades the malar bone, and produces a mass below the lateral floor of the orbit that may ulcerate through to the skin. The orbit is invaded laterally and displaces the eye superomedially. The temporal fossa is often involved, as is the zygomatic bone in advanced lesions. Suprastructure cancers that extend medially invade the nasal cavity, the ethmoid and frontal sinuses, the lacrimal apparatus, and the medial inferior orbit.

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Ethmoid Sinuses Depending on the location of the tumor, it may invade the medial orbit through the lamina papyracea, the inner canthus, and the nasal cavity. More advanced lesions invade the maxillary antrum, nasopharynx, sphenoid sinus, and anterior cranial fossa.

Sphenoid Sinus The sphenoid sinus is closely related to the CNs in the cavernous sinus: III, IV, V1, V2, and VI (Fig. 45.2). CN palsies and headaches are frequently the first clinical evidence of a sphenoid sinus tumor. A diagnosis is usually made, however, when the tumor eventually breaks through into the nasopharynx or nasal cavity where it can be seen.

Inverted Papilloma A report of 223 cases of inverted papillomas showed the lateral nasal wall was the most commonly involved site (68%), with ethmoid and maxillary sinus involvement also being common (57%), as was involvement of the septum (28%). However, ethmoid and maxillary sinus involvement without a tumor of the lateral nasal wall occurred in 4%. Intracranial extension was usually associated with a carcinoma. The tumor occurred bilaterally when there was spread through the nasal septum; multicentric sites of origin were observed.372

Figure 45.2 Coronal section of the cavernous sinus. (Mendenhall WM, Million RR, Mancuso AA, et al. Nasopharynx. In: Million RR, Cassisi NJ, eds. Management of Head and Neck Cancer: A Multidisciplinary Approach. 2nd ed. Philadelphia: J. B. Lippincott Company; 1994:606, Fig. 23.10.)

Lymphatic The incidence of lymphatic metastases at diagnosis is 10% to 15% for nasal cavity and ethmoid sinus SCCs and probably lower for antral and sphenoid tumors. Maxillary sinus tumors that invade the oral cavity and involve the buccal mucosa, maxillary gingiva, or hard palate may spread to the level IB and II nodes. Lesions that invade the

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nasal cavity or nasopharynx spread posteriorly to the parapharyngeal nodes and then to the level II nodes. The risk of cervical node involvement for esthesioneuroblastoma is approximately 20%.366

CLINICAL PICTURE Nasal Vestibule These lesions present with symptoms of a slow-growing mass with attendant crusting and occasional, minor bleeding. Pain out of proportion to examination is not uncommon.

Nasal Cavity and Paranasal Sinuses Nasal Cavity The earliest symptoms are a low-grade chronic infection with discharge, obstruction, and minor, intermittent bleeding. Lesions arising in the olfactory region may cause unilateral or bilateral nasal expansion of the bridge of the nose; a mass may appear near the inner canthus and eventually ulcerate. Obstruction of the nasolacrimal system may be a presenting complaint. Extension through the cribriform plate or into the ethmoid sinuses is accompanied by a frontal headache. The aberration of smell is rare. Invasion of the medial orbit produces proptosis and diplopia; a mass may be palpated in the orbit.

Maxillary Sinus These cancers develop silently when they are confined to the sinus and produce symptoms after extension through the walls. Many do not present until the lesion is T4. If the tumor invades toward the oral cavity, the presenting symptoms include pain and loosening or loss of teeth. Palpation and observation of the face may show a mass. A posterior invasion of the orbit will produce proptosis, diplopia, and conjunctival edema. Invasion of V2 in the floor of the orbit may cause paresthesia. Nasal obstruction and bleeding are common, and trismus and headaches are associated with invasion posteriorly into the pterygopalatine fossa, pterygoid muscles, infratemporal fossa, and skull base. Cancers developing in the medial suprastructure of the antrum present with nasal symptoms of discharge or bleeding, mild infraorbital pain, an infected lacrimal sac, and displacement of the eye superolaterally with proptosis, diplopia, and conjunctival edema. Cancer developing in the lateral suprastructure produces a mass below the lateral canthus with associated pain. The eye may be deviated medially and upward when orbital invasion occurs, producing diplopia and proptosis. The tumor may extend to the temporal fossa, producing a diffuse fullness.

Ethmoid Sinuses Mild-to-moderate sinus pain referred to the frontal-nasal area is an early symptom. A painless mass may present near the inner canthus. Diplopia and proptosis develop with invasion of the medial orbit. Nasal discharge, epistaxis, and obstruction are frequent. Paresthesia may occur over the distribution of sensory nerves.

STAGING The AJCC staging system for the nasal cavity and paranasal sinuses is depicted in Table 45.20. Nasal vestibule tumors are staged according to the AJCC staging system for skin cancers. TABLE 45.20

2017 American Joint Committee on Cancer Staging System for Nasal Cavity and Paranasal Sinus Cancers MAXILLARY SINUS TX

Primary tumor cannot be assessed

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T0

No evidence of primary tumor

Tis

Carcinoma in situ

T1

Tumor limited to the maxillary sinus mucosa with no erosion or destruction of bone

T2

Tumor causing bone erosion or destruction including extension into the hard palate and/or middle nasal meatus, except extension to posterior wall of maxillary sinus and pterygoid plates

T3

Tumor invades any of the following: bone of the posterior wall of maxillary sinus, subcutaneous tissues, floor or medial wall of orbit, pterygoid fossa, ethmoid sinuses

T4a

Tumor invades anterior orbital contents, skin of cheek, pterygoid plates, infratemporal fossa, cribriform plate, sphenoid or frontal sinuses

T4b

Tumor invades any of the following: orbital apex, dura, brain, middle cranial fossa, cranial nerves other than maxillary division of trigeminal nerve (V2), nasopharynx, or clivus

NASAL CAVITY AND ETHMOID SINUS TX

Primary tumor cannot be assessed

T0

No evidence of primary tumor

Tis

Carcinoma in situ

T1

Tumor restricted to any one subsite, with or without bony invasion

T2

Tumor invading two subsites in a single region or extending to involve an adjacent region within the nasoethmoid complex, with or without bony invasion

T3

Tumor extends to invade the medial wall or floor of the orbit, maxillary sinus, palate, or cribriform plate

T4a

Tumor invades any of the following: anterior orbital contents, skin of nose or cheek, minimal extension to anterior cranial fossa, pterygoid plates, sphenoid or frontal sinuses

T4b

Tumor invades any of the following: orbital apex, dura, brain, middle cranial fossa, cranial nerves other than V2, nasopharynx, or clivus Used with the permission of the American College of Surgeons. The original source for this material is the AJCC Cancer Staging Manual, Eighth Edition (2017) published by Springer International Publishing AG.

TREATMENT Nasal Vestibule Selection of Treatment Modality RT is usually the preferred treatment because of the deformity produced by excision.371 However, salvage surgery often results in a defect that is not well reconstructed. A nasal prosthesis is often needed. Surgery alone is preferred for the occasional very small lesion, the removal of which will not produce cosmetic deformity or require reconstruction. A subset of patients best treated by surgery and adjuvant RT or CRT are those with invasion of the premaxilla.

Surgical Treatment Excision of lesions in the nasal vestibule usually involves removal of cartilage as well as skin. Depending on the site of the lesion, the columella, the septum, or the alar cartilages will have to be removed, with a resulting cosmetic deformity that is difficult to reconstruct. If the alar cartilage has been sacrificed, a three-layered reconstruction consisting of nasal mucosa, ear cartilage, and a regional skin flap (nasolabial or paramedian forehead) is needed. If the entire external nose is resected, free flap reconstruction or a nasal prosthesis are needed.

Irradiation Technique EBRT, brachytherapy, or a combination of both may be used. EBRT is usually administered with a single anterior portal technique, which uses a combination of photons and electrons; a wax bolus ensures a homogenous dose. The dose ranges from 66 to 70 Gy at 2 Gy per fraction, once daily in a continuous course. Interstitial brachytherapy of the nasal vestibule and nasal cavity is highly individualized and employs afterloaded 192Ir needles. The implant is usually composed of two, three, or four planes of sources inserted perpendicularly through the skin surface of the external nose with crossing needles placed in the dorsum of the nose, the floor of the nasal cavity, and the upper lip. The dose varies depending on the size of the lesion.371

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Inverted Papilloma An inverted papilloma is treated initially by surgery. This typically consists of an endoscopic medial maxillectomy or an endonasal endoscopic WLE. When the lesion begins to act aggressively with rapid recurrences and invasion of the sinuses, orbit, and anterior cranial fossa, it should be considered a low-grade cancer and treated by a more radical removal. RT is recommended for lesions that are incompletely resected, for multiple recurrences, and for those in whom carcinoma is found.367

Nasal Cavity Selection of Treatment Modality Surgery is the preferred treatment if a gross total resection is likely; postoperative RT or CRT is usually indicated.373 Definitive RT or CRT is used for tumors that cannot be completely resected.

Surgical Treatment Traditionally, sinonasal cancers were approached through a lateral rhinotomy or Weber-Furgussen incision. A bifrontal craniotomy was used to resect lesions extending to or though the skull base. In the last 20 years, endoscopic endonasal approaches along with image guidance have minimized the need for external incisions and craniotomies.374 These approaches have shown equivalent disease control with improved functional and QOL outcomes.375–379 Reconstruction of the skull base can often be achieved with a pericranial flap or nasoseptal flap and/or free flap if needed.380

Irradiation Technique The traditional EBRT technique emphasized an anterior portal with one or two lateral portals. Contiguous structures such as the maxillary sinus, ethmoid sinus, medial orbit, nasopharynx, skull base, and sphenoid sinus are generally included in the initial treatment volume as required. The treatment volume is reduced after 50 Gy to include the original gross disease with a margin. IMRT is usually employed and usually produces a more conformal dose distribution. Advanced lesions may require inclusion of an entire orbit and loss of vision usually occurs, but an operation would require visual loss in any case. Treatment planning should protect the opposite eye and optic nerve.

Combined Treatment Policies If a combined treatment is planned, we prefer surgery first. RT or CRT is started 4 to 6 weeks afterward. The dose is usually 60 to 65 Gy for clear margins; patients with positive margins or gross residual tumor after operation receive 74.4 Gy at 1.2 Gy per twice-daily fraction.

Management of Recurrence Once the patient has had surgery or RT, it is difficult to determine the extent of recurrent disease because of changes from the previous therapy. The most common situation for salvage is RT or surgical failure that can be treated successfully by a craniofacial resection. Tumor extension to the sphenopalatine fossa with definite destruction of a pterygoid plate is a relative contraindication to craniofacial resection. CN involvement, posterior invasion near the optic chiasm, and sphenoid sinus or cavernous sinus invasion are contraindications to resection. An MRI can distinguish between exudate and a gross tumor in a sinus. The anterior wall of the sphenoid sinus may be removed, but the sinus itself cannot be completely resected. Postoperative RT should be considered whether or not margins are positive.

Maxillary Sinus Selection of Treatment Modality Surgery gives the best oncologic and functional results. Early infrastructure lesions may be cured by surgery alone, but, for most other cases, RT is given postoperatively even if margins are clear. CRT should be considered for a positive or close margin. The extension of cancer to the skull base, nasopharynx, or sphenoid sinus

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contraindicates excision. The pterygoid process below the foramen rotundum may be removed along with the attached pterygoid muscles, but destruction of the sphenoid bone above this point is a contraindication to operation. Procedures to resect portions of the skull base are described for special situations.

Surgical Treatment Surgery for maxillary sinus carcinoma depends on which walls are involved. If the floor of the orbit is free of disease, then the eye and orbital rim may be left undisturbed. If, however, there is involvement through the periorbita, then a maxillectomy with resection of the orbital floor with or without an orbital exenteration must be performed. If the posterior wall or the pterygoid plates are involved, they too must be included in the resection. The reconstructive ladder begins with a skin graft to line the nasal cavity. An obturator/prosthesis is then used to provide nasal/oral separation and dentition. The next step involves a soft tissue–only free flap, which permanently separates the nasal and oral cavities and may accept an obturator once healed. The most sophisticated reconstruction involves a bone-containing free flap (fibula, iliac crest, or scapula) into which dental implants can be installed. This provides a full oral reconstruction and rehabilitation.381,382

Irradiation Technique RT treatment planning includes the entire maxilla, the adjacent nasal cavity, the ethmoid sinus, the nasopharynx, and the pterygopalatine fossa. All or part of the orbit is included in patients with extension into or near the orbit. Target volume definition is aided by the use of treatment planning CT combined with image-fusion MRI. The prescribed dose is 74.4 Gy at 1.2 Gy per fraction twice daily for RT alone. The dose for preoperative RT varies from 50 to 60 Gy, and the dose for postoperative RT varies from 60 to 74.4 Gy.

Ethmoid Sinus Selection of Treatment Modality Surgery is preferred if a gross total resection is likely. Postoperative RT or CRT is usually indicated. Unresectable tumors are treated with CRT.

Surgical Treatment Most ethmoid cancers can be resected with the endoscopic endonasal approach technique as mentioned previously.

Irradiation Technique IMRT is usually employed because a more conformal dose distribution can typically be achieved compared with traditional three-field techniques.

Management of Recurrence Recurrent disease is heralded by recurrent pain and CN palsies. Localized recurrence after surgery only may be managed by CRT or craniofacial resection and postoperative RT or CRT. RT failures may be suitable for maxillectomy or craniofacial resection.

Sphenoid Sinus The treatment is with RT, and the technique is similar to that used for advanced NPC.

RESULTS OF TREATMENT Nasal Vestibule Goepfert and coworkers383 reviewed the MD Anderson Cancer Center experience of 26 patients with nasal vestibule SCCs. The absolute 5-year survival was 78%. A total of 10 patients were treated initially by surgery; 1 developed a local recurrence and was salvaged by RT. In total, 16 patients were treated by RT; 3 developed local

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recurrence, and 2 were salvaged by an operation. Wallace et al.371 reviewed 71 patients treated by RT at the University of Florida for SCC of the nasal vestibule. The 5-year local control and cause-specific survival rates were as follows: T1 to T2 (n = 43), 95% and 95%; for T4 (n = 28), 71% and no data; and overall, 86% and 91%, respectively.371 A total of 8 additional patients with unfavorable T4 cancers were treated with resection and adjuvant RT. All 8 patients treated with surgery and RT were locally controlled; 3 of 8 experienced severe complications.

Nasal Cavity and Ethmoid Sinus Inverted Papilloma Weissler and coworkers372 reported 233 cases of inverting papilloma seen over a 35-year period. A total of 134 patients had at least 1 year of follow-up. The risk of recurrence was 71% in patients who had an intranasal procedure and 56% for those having a Caldwell-Luc approach. Patients having a lateral rhinotomy had the lowest incidence of recurrence (29%). Weissler and coworkers372 also reported 6 patients who received RT for benign inverting papilloma and 9 for inverting papilloma associated with malignant disease. A total of 11 of the 15 patients had a complete response to RT and were free of disease for long periods of follow-up. Rutenberg et al.367 reported 13 patients with advanced and/or recurrent inverting papillomas who were treated with definitive or adjuvant RT and followed for a median of 16.2 years. Of the 13, 6 patients had concomitant carcinoma at the time of treatment. The 5-year outcomes were as follows: local control, 45%; cause-specific survival, 82%; and overall control, 62%.

Carcinoma Mendenhall et al.373 reviewed 109 patients treated at the University of Florida for carcinomas of the nasal cavity (69 patients), ethmoid sinus (33 patients), sphenoid sinus (6 patients), and frontal sinus (1 patient). In total, 56 patients were treated with definitive RT, 45 with surgery and postoperative RT, and 8 with preoperative RT and surgery. The 5-year local control rates were as follows: T1 to T3, 82%; T4, 50%; and overall, 63%. Local control at 5 years was 43% after definitive RT and 84% after surgery and adjuvant RT (P < .0001). A multivariate analysis revealed that both overall stage and treatment group (definitive RT versus surgery and adjuvant RT) impacted this end point. Cause-specific survival rates at 5 years were 81% for stages I to III, 54% for stage IV, and 62% overall. A multivariate analysis of cause-specific survival revealed that T stage, N stage, and treatment group significantly impacted this end point. Of 109 patients, 31 (20%) sustained severe complications: 17 of 56 (16%) patients after definitive RT, and 14 of 53 (25%) patients after surgery and adjuvant RT. Some rare carcinomas such as sinonasal undifferentiated carcinoma have very poor outcomes no matter which treatment approach is used with a 12.7-month median disease-free survival.384 Management varies by center. Trimodality therapy is a common strategy.

Esthesioneuroblastoma Elkon and coworkers385 reviewed the literature on esthesioneuroblastoma and compiled the results of 78 cases. They concluded that either RT or surgery was sufficient treatment for early-stage disease but that combined treatment might be advantageous for late-stage presentations. The 5-year absolute survival rate was 75% for lesions confined to the nasal cavity, 60% for those involving the nasal cavity and paranasal sinuses, and 41% for tumors extending beyond the nasal cavity and paranasal sinuses. Monroe and coworkers366 reported on 22 patients treated with curative intent at the University of Florida and observed the following 5-year outcomes: local control, 59%; cause-specific survival, 54%; and survival, 48%. The 5-year cause-specific survival rate was lower after definitive RT (17%) compared with craniofacial resection and postoperative RT (56%). Cervical metastases occurred in 6 of 22 patients (27%). Recurrence in the neck was observed in 4 of 9 patients, who were initially N0 and who did not receive elective neck RT compared with zero of 11 patients who were electively treated (P = .02).

Maxillary Sinus Waldron and coworkers386 reported on 110 patients treated with curative intent at the Princess Margaret Hospital with definitive RT (83 patients) or surgery and adjuvant RT (27 patients). The 5-year rates of local control and cause-specific survival were 42% and 43%, respectively. A total of 63 patients developed a local recurrence, and

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25 of 63 underwent salvage surgery with a subsequent 5-year cause-specific survival of 31%.

COMPLICATIONS OF TREATMENT Surgery Complications of a maxillectomy include infection, poor wound healing, midface numbness/weakness, trismus, CSF leak, epiphora, and hemorrhage. Complications of ethmoid sinus surgery include hemorrhage, meningitis, CSF leak, cellulitis and pansinusitis, brain abscess, and stroke. Complications of craniofacial resection include meningitis, subdural abscess, CSF leak, diplopia, and hemorrhage.

Radiation Therapy The most frequent and significant complications of RT involve the eye.373,387,388 When only a portion of the ipsilateral eye is irradiated (the medial one-third), it is possible to preserve vision in the majority of patients. When there is extensive disease in the orbit, the entire eye is irradiated to a high dose with almost certain loss of vision; however, these same patients would require orbital exenteration if treated by surgery. The risk for bilateral blindness can be reduced by the use of CT and MRI scans for improved treatment planning and knowledge of the tolerance of the optic nerve. A few patients will experience a transient CNS syndrome that includes vertigo, headaches, decreased cerebration, and lethargy. This syndrome usually appears 2 to 3 months after the completion of treatment and lasts 1 to 2 months. Aseptic meningitis, chronic sinusitis, or serous otitis media can occur. High-dose RT of the nasal cavity can cause narrowing and synechiae of the nasal cavity. Douching with salt water and daily self-dilations with petrolatum-coated cotton swabs will reduce the problem. Septal perforations occur when tumor has destroyed part of the septum; these do not usually require treatment. Destruction of the nasal bone and septum by the tumor may result in cosmetic deformity. Maxillary necrosis may develop, particularly if teeth are extracted.

PARAGANGLIOMAS Paragangliomas are an uncommon group of neoplasms that may originate anywhere glomus bodies are found. The lesions are rare before the age of 20 years; they may occur in multiple sites in about 10% to 20% of cases, especially in patients with familial history.

ANATOMY The normal glomus bodies in the head and neck vary from 0.1 to 0.5 mm in diameter. Tumors arising in glomus bodies (i.e., paragangliomas) arise most often from the carotid and temporal bone glomus bodies. At least one-half of the glomus bodies are found in the general region of the jugular fossa; the remaining are distributed along the course of the nerve of Jacobson (a branch of CN X). The carotid bodies are located adjacent to the bifurcation of the common carotid. Vagal bodies are adjacent to the ganglion nodosum of the vagus nerve.

PATHOLOGY Paragangliomas are histologically benign tumors resembling the parent tissue and consist of nests of epithelioid cells within stroma-containing, thin-walled blood vessels and nonmyelinated nerve fibers. Although the tumor is well circumscribed, a true capsule is not seen. The criterion of malignancy is based on the development of metastases rather than the histologic appearance.

PATTERNS OF SPREAD These lesions usually grow slowly; it is usual to have a history of symptoms for a few years and, occasionally, for 20 years or longer.

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Lymphatic metastases occur in about 5% of carotid body tumors but are very rare for temporal bone tumors. An upper neck mass may be an inferior extension of a jugular fossa or vagal tumor rather than a lymph node metastasis. Distant metastases have rarely been reported for temporal bone tumors; carotid body tumors have a low risk for distant metastases, usually to lung and bone, probably in the range of 5% or less.

STAGING There is no one accepted staging system for paragangliomas.

TREATMENT Selection of Treatment Modality Temporal Bone Tumors Excision is satisfactory for small lesions that can be removed without a risk of operative death or damage to normal structures. Stereotactic radiosurgery is an option for early lesions. Early lesions of the tympanic cavity are managed successfully by excision without a loss of hearing or vestibular function. The remainder of the lesions are managed best by IMRT to 45 Gy in 25 fractions over 5 weeks, with a very high success rate and minimal morbidity with current techniques. Partial removal of the tumor prior to RT does not improve the results and only increases the overall morbidity. Local control after RT is defined as stable disease or partial regression with no evidence of growth.

Carotid Body Tumors Small lesions (1 to 5 cm) may be successfully removed with little risk to the patient. However, if resection of the carotid vessels is anticipated or if a large lesion is fixed or unresectable because of size, RT is the preferred initial treatment.

Management of Recurrence Patients have follow-up with annual CT or MRI scans. Recurrence after surgery usually is treated by RT. Recurrence after RT should be treated by operation if feasible; if surgery is not possible, re-RT may be considered.

RESULTS OF TREATMENT Woods and coworkers389 observed a local control rate of 89% in 71 patients with temporal bone paragangliomas who were treated surgically and followed from 1 to 22 years. Green and coworkers390 reported a local control rate of 89% after surgery for 18 patients who had a mean follow-up of 8 years. Gilbo et al.31 reported on 131 patients with 156 paragangliomas who were treated with RT and followed for a median of 8.7 years. The 10-year actuarial local control and cause-specific survival rates were 96% and 97%, respectively.

COMPLICATIONS OF TREATMENT Surgery The major risks during operation are hemorrhage and injury to the CNs. Other complications include hemiparesis, spinal fluid leak, and hearing loss.

Irradiation

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Complications include cholesteatoma and sequestrum of the mastoid and otitis media. Detectable damage to the hearing mechanism and vestibular apparatus is unlikely after 45 Gy in 25 fractions.391

MAJOR SALIVARY GLANDS Tumors of the major salivary glands account for 3% to 4% of all head and neck neoplasms. The average age of patients is 55 years for malignant neoplasms and about 40 years for benign tumors. Approximately 25% of parotid tumors and 50% of submandibular tumors are malignant.

ANATOMY The parotid gland is formed by the muscles, bones, vessels, and nerves that come in contact with the gland. The bulk of the parotid gland is superficial, extending superiorly to the zygomatic arch and anterior aspect of the external auditory canal. The anterior border extends to the opening of the parotid duct into the oral cavity opposite the second molar. Inferiorly, the gland extends between the mastoid and the angle of the mandible. The gland lies in front of and below the external auditory canal. A deep lobe extends into the parapharyngeal area, where it is in relationship to the lateral process of C1, the styloid process, and the parapharyngeal space. The parotid gland is encompassed by fascia that is sufficient to contain most parotid infections in addition to benign tumors and low-grade malignancies. However, the fascia between the parotid gland and the conchal and tragal cartilages is thin and quickly penetrated by tumor. The cartilage of the external auditory canal has fissures of Santorini and a foramen of Huschke through which tumors may extend. The fascia separating the deep lobe from the parapharyngeal space (stylomandibular fascial membrane) may be sufficiently thin to allow the tumor or infection to access the parapharyngeal space and pharynx. The sensory nerve supply to the parotid area and part of the pinna is from the greater auricular nerve (C2, C3) and the auriculotemporal nerve (V3). The facial nerve (VII) penetrates the parotid gland almost immediately upon leaving the stylomastoid canal and forms an extensive anatomic network within the gland and gives off branches to the muscles of facial expression. The parotid gland is richly supplied from several arteries that freely anastomose. The external carotid, internal maxillary, and superficial temporal arteries as well as the retromandibular vein lie deep to CN VII. The superficial preauricular nodes lie outside the fascia of the parotid gland and immediately in front of the tragus and drain the skin of the anterior ear, temple, and upper face, including the eye and nose. They are involved most frequently by metastatic skin cancer and lymphoma but not usually by parotid neoplasms. The preauricular nodes empty into the external jugular chain nodes, or they may communicate with the internal jugular chain nodes. There are two nodal groups within the parotid fascia. Within the substance of the parotid gland are numerous lymph follicles and 4 to 10 small lymph nodes scattered along the posterior facial and external jugular veins. Thus, they may lie deep to CN VII. Outside the gland but within the fascia are subparotid nodes that lie in front of the tragus and between the inferior aspect of the parotid tail and the anterior border of the sternocleidomastoid muscle.

PATHOLOGY Benign Tumors Benign Mixed Tumors Also called pleomorphic adenoma, these slow-growing neoplasms are surrounded by an imperfect pseudocapsule traversed by fingers of tumor. The age of appearance begins in the early 20s with a mean age of 40 years.

Papillary Cystadenoma Lymphomatosum (Warthin Tumor) It is encased by a thin, complete capsule and occurs predominantly in older men who are smokers. It is bilateral in approximately 10% of cases and may be multifocal on one side.

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Benign Lymphoepithelial Lesions Benign lymphoepithelial lesions account for about 5% of benign lesions. The tumor may be bilateral and is more common in women. It is more common in HIV-positive patients.

Oncocytoma Oncocytoma is a benign, slow-growing tumor found mostly in the older age group. The encapsulated tumor has a dark appearance and behave similarly to a Warthin tumor.

Basal Cell Adenoma The basal cell adenoma is an uncommon benign lesion, usually appearing in older people. It is cured by a simple excision. Basal cell adenoma must be distinguished from basal cell carcinoma of the skin metastatic to parotid lymph nodes.

Malignant Tumors Low-Grade Malignancy Acinic Cell Carcinoma. Acinic cell carcinomas typically are indolent low-grade neoplasms appearing in all age groups and are most common in women. Metastases occur in a small percentage of cases and cannot be predicted by the histologic picture. Mucoepidermoid Carcinoma, Low and Intermediate Grade. Most mucoepidermoid carcinomas are indolent lesions readily cured by adequate excision. They may appear in any age group and grow slowly; there is little or no capsule. They are usually well circumscribed, but they may widely infiltrate the normal gland or become fixed to skin. Low- and intermediate-grade lesions have similar recurrence and survival rates.392

High-Grade Malignancy Mucoepidermoid Carcinoma, High Grade. High-grade mucoepidermoid carcinomas behave aggressively, widely infiltrating the salivary gland and producing lymph node and distant metastases. They may be difficult to distinguish from SCCs. Adenocarcinoma, Poorly Differentiated Carcinoma, Anaplastic Carcinoma, and SCC. These histologies tend to appear late in life and behave aggressively. Almost all of the so-called SCCs of the parotid are metastatic from skin cancer, especially from the temple area.393 Malignant Mixed Tumor. A small percentage of benign mixed tumors may develop into a frank malignancy (carcinoma ex pleomorphic adenoma). Adenoid Cystic Carcinoma. This is uncommon in the major salivary glands. Its growth rate is variable. Metastases to regional lymph nodes and distant sites occur, PNI is characteristic, and recurrences may appear many years after initial treatment. Lymphoepithelioma (Malignant Lymphoepithelial Lesion, “Eskimoma”). Lymphoepithelioma occurs rarely in the parotid and submandibular gland. The histologic picture is that of lymphoepithelioma with varying degrees of nonmalignant lymphoid stroma.

PATTERNS OF SPREAD Benign Mixed Tumors Benign mixed tumors of the parotid gland grow by expansion and local infiltration. Most tumors begin in the superficial lobe. Because of their slow growth, they rarely cause CN VII palsy. When incompletely excised, multiple tumor nodules develop within the tumor bed. Skin invasion may occur in recurrent lesions; bone invasion

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does not occur.

Malignant Tumors Malignant neoplasms infiltrate the parotid gland, invade CN VII and the auriculotemporal nerve, and spread along nerve sheaths. The tumor may invade the adjacent skin, muscles, and bone. Deep lobe lesions invade the parapharyngeal space, the infratemporal fossa, and the skull base and compromise additional CNs. Malignant tumors of the submandibular gland invade the gland, fix the tumor to the adjacent mandible, and invade the mylohyoid muscle and hypoglossal nerve. Sublingual gland neoplasms usually present as a submucosal mass in the floor of the mouth. The advanced lesions show an ulcerated mass in the floor of the mouth with extension to the tongue, the mandible, and the submental soft tissues.

Lymphatic Spread Lymph node metastases may occur from all of the malignant neoplasms. Approximately 20% to 25% of patients with malignant tumors will have clinically positive or occult metastases in lymph nodes at the time of diagnosis. Low-grade mucoepidermoid carcinoma and acinic cell adenocarcinoma have a low rate of lymph node metastasis, as do adenoid cystic cancers. The risk for lymph node metastasis increases with recurrent disease and an increased size of the primary lesion.

CLINICAL PICTURE Parotid Gland Most patients with either benign or malignant parotid tumors present with a mass. Mild, intermittent pain is occasionally present but does not distinguish between benign and malignant tumors. Facial nerve palsy is an infrequent presenting complaint and indicates malignancy. Deep lobe tumors may produce dysphagia. Fixation or reduced mobility may occur in both benign and malignant neoplasms. Tumors presenting in the deep lobe may cause bulging of the palate and tonsil. Advanced malignant lesions may rarely affect CNs IX to XII and the sympathetic chain if the parapharyngeal space is invaded. CN V3 may be involved when tumor tracks along the auriculotemporal nerve to the skull base; pain is an associated finding.

Submandibular Gland Both benign and malignant neoplasms present as a mass usually associated with mild pain. Nerve palsy is rarely present. The skin may be infiltrated in advanced lesions. The tumor mass usually is partially fixed to the mandible unless quite small. Loss of mobility occurs with both benign and malignant lesions.

Sublingual Gland Sublingual gland lesions are clinically similar to floor-of-mouth SCCs. They produce a mass, which is submucosal at first, that may be felt by the tongue. There is mild discomfort, if any, in the early stages.

DIFFERENTIAL DIAGNOSIS Parotid Gland Gallia and Johnson394 reviewed 140 patients who eventually underwent a parotidectomy for diagnosis. Only 11% had malignant masses; the remainder had benign neoplasms (62%) or nonneoplastic conditions (27%). Conditions that may be confused with a parotid tumor include (1) metastatic cancer, lymphoma, or leukemia involving parotid-area lymph nodes; (2) fatty replacement, tail of parotid; (3) chronic parotitis; (4) a Boeck sarcoid; (5) a stone in the duct; (6) cysts (branchial cleft, dermoid); (7) hypertrophy associated with diabetes or alcoholism; (8) hypertrophy of masseter muscle; (9) mandibular neoplasms; (10) prominent transverse process of C1; (11) penetrating foreign bodies; (12) hemangiomas/lymphangioma; and (13) a lipoma.

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Submandibular Gland The differential diagnosis of a submandibular mass includes inflammatory disease, SCC metastatic to a lymph node, and a primary neoplasm of the submandibular gland. Gallia and Johnson394 reviewed 110 submandibular lesions in patients who underwent biopsy. A total of 93 lesions (85%) were nonneoplastic, usually inflamed glands, and 9 lesions (8%) were benign tumors. Eight patients (7%) had malignant lesions, of which 3 lesions were lymphoma, 3 were metastatic carcinoma, and 2 were primary submandibular gland carcinoma.

Biopsy Technique Parotid Gland An FNA biopsy is useful to determine the extent of treatment needed. A negative FNA does not necessarily mean that there is no tumor; therefore, surgical decisions often rely heavily on clinical and radiographic findings. An FNA can also be used in the inoperable or recurrent lesions when RT is the initial treatment. Benign lesions may be treated with extracapsular dissection or a superficial parotidectomy. In experienced hands, extracapsular dissection has low recurrence rates and morbidity and requires less operating time, thus saving health-care costs.395 Cancers or large lesions require superficial or total parotidecromt.

Submandibular Gland Much like parotid lesions, an FNA biopsy is useful for surgical planning. Surgery involves removing the submandibular gland and possibly the remaining contents of level IB (with or without comprehensive neck dissection) if malignancy is suspected.

STAGING The AJCC staging system is depicted in Table 45.21.

TREATMENT Selection of Treatment Modality Parotid Gland The initial management of resectable masses is an en bloc superficial lobectomy. The tumor usually can be dissected free of the facial nerve. If the tumor involves the deep portion of the gland, the nerve is retracted and the deep portion excised (i.e., total parotidectomy). Skin, bone, and muscle may also be resected as needed. Low-grade malignant neoplasms are usually managed by operation only. RT is given postoperatively for nearly all high-grade lesions. RT is advised for low-grade malignant lesions that are recurrent and those with close or positive margins on the facial nerve. Postoperative RT is advised for selected benign mixed tumors when there is microscopic residual disease after operation, and for nearly all patients after surgery for recurrent disease. RT alone is unlikely to control gross disease, and if possible, resection of any gross residual benign mixed tumor should be performed prior to RT. Inoperable malignancies are treated by definitive RT or CRT as an extrapolation of other data. TABLE 45.21

American Joint Committee on Cancer Staging for Major Salivary Gland Primary Tumors (T) T Category

T Criteria

TX

Primary tumor cannot be assessed

T0

No evidence of primary tumor

Tis

Carcinoma in situ

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T1

Tumor 2 cm or smaller in greatest dimension without extraparenchymal extension*

T2

Tumor larger than 2 cm but not larger than 4 cm in greatest dimension without extraparenchymal extension*

T3

Tumor larger than 4 cm and/or having extraparenchymal extension*

T4

Moderately advanced or very advanced disease

T4a

Moderately advanced disease Tumor invades skin, mandible, ear canal, and/or facial nerve

T4b

Very advanced disease Tumor invades skull base and/or pterygoid plates and/or encases carotid artery *Extraparenchymal extension is clinical or macroscopic evidence of invasion of soft tissues. Microscopic evidence alone does not constitute extraparenchymal extension for classification purposes. Used with the permission of the American College of Surgeons. The original source for this material is the AJCC Cancer Staging Manual, Eighth Edition (2017) published by Springer International Publishing AG.

Submandibular Gland Benign lesions require only a submandibular gland excision. Malignant lesions will need a WLE, submandibular gland excision en bloc with level IB, and a neck dissection (if the lesion is high grade). If there is PNI, bone invasion, clinically positive node, or extension to contiguous soft tissues, resection is enlarged to encompass the necessary areas. Postoperative RT is added in nearly all cases; CRT is considered in selected patients with poorrisk features.

Surgical Treatment Superficial Parotidectomy The incision is made in the preauricular crease and then curves under the earlobe posteriorly and extends into the neck. The facial nerve is identified, and the dissection is carried out between the mass and the facial nerve. Ideally, a 1-cm circumferential cuff of “normal” parotid tissue should be resected along with the tumor. However, close margins of 60% of NSCLCs, resulting in constitutive activation of downstream signaling pathways.44 EGFR mutations are present in 10% to 40% of NSCLCs (10% to 15% Caucasians, 30% to 40% East Asians) and particularly prevalent in adenocarcinoma, women, never smokers, and East Asian ethnicity.44 Exon 19 deletion and exon 21 L858R mutation in the tyrosine kinase domain each account for approximately 45% of EGFR mutations, with preferential activation of the PI3K/AKT/mTOR and STAT3/STAT5 pathways. EGFR-targeted inhibitors include monoclonal antibodies (e.g., cetuximab) that target the extracellular domain and small molecule TKIs (e.g., erlotinib and afatinib) that inhibit the intracellular tyrosine kinase activity. Exon 19 and 21 mutations strongly correlate with sensitivity to EGFR TKIs,10,11 an example of oncogene addiction where tumors driven by mutant EGFR rely on continued epidermal growth factor signaling. Mutations in exons 18 and 20 comprise the remaining 10% of EGFR mutations. They do not confer sensitivity to EGFR TKIs but, in the case of exon 20 T790M, are associated with EGFR TKI resistance as it results in a conformational change that inhibits binding of first generation EGFR TKIs.44 Despite an initial response, patients treated with EGFR TKIs eventually develop resistance. In addition to EGFR T790M (accounting for approximately 60% of cases), resistance can occur through EGFR exon 20 insertions, KRAS mutation, MET amplification or activation, HER2 amplification, and occasionally, a switch to a SCLC-like phenotype.44 Second-generation EGFR TKIs (e.g., dacomitinib and afatinib) bind irreversibly to EGFR tyrosine

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kinase and induce much less therapeutic resistance. However, they have failed to demonstrate significant singleagent activity in T790M disease and have considerable toxicity due to concurrent inhibition of wild-type EGFR.45 Third-generation EGFR TKIs (e.g., osimertinib), however, demonstrate T790M activity with limited wild-type EGFR inhibition.45 TABLE 47.3

Targeted Therapies Approved or in Clinical Trials for Lung Cancer Target

Approved for Lung Cancera

In Clinical Trials for Lung Cancer

Multikinase inhibitors



Axitinib, BMS-690514, dasatinib, foretinib, imatinib, lenvatinib, linifanib, motesanib, pazopanib, regorafenib, sorafenib, sunitinib, tesevatinib, vatalanib, vandetanib

AKT



MK-2206, nelfinavir, perifosine

ALK

Alectinib, brigatinib, ceritinib, crizotinib



AURKA



Alisertib, tozasertib

BCL2



ABT-737, gossypol, navitoclax, obatoclax, oblimersen

BRAF

Dabrafenib (V600E), trametinib

Vemurafenib (V600E)

CDK4/6



Abemaciclib, palbociclib

COX-2



Celecoxib

CTLA-4



Ipilimumab, tremelimumab

DDR2



Dasatinib

EGFR

Afatinib, cetuximab, erlotinib, gefitinib, osimertinib (T790M), necitumumab

AP32788, canertinib, icotinib, lapatinib, matuzumab, neratinib, nimotuzumab, panitumumab, pelitinib, zalutumumab

FGFR

Nintedanib

AZD4547, BGJ398, brivanib alaninate, dovitinib, erdafitinib, FP-1039, lucitanib, nintedanib, ponatinib

FLT3



CDX-301, dovitinib, XL999

HDACs



Belinostat, CXD101, entinostat, mocetinostat, panobinostat, romidepsin, vorinostat

HER2

Afatinib

Adotrastuzumab emtansine, AP32788, canertinib, dacomitinib, lapatinib, neratinib, pertuzumab, trastuzumab

HER3/4

Afatinib



HGF



Ficlatuzumab, rilotumumab

HH (SMO)



BMS-833923, LY2940680, sonidegib, taladegib, vismodegib

HSP90



Ganetespib, retaspimycin, tanespimycin

IGF-1R



BIIB022, cixutumumab, dalotuzumab, figitumumab, ganitumab, linsitinib

KIT



Cediranib, dasatinib, dovitinib, imatinib

LSD1



GSK2879552

MEK



PD325901, selumetinib, trametinib

MET (amplification, exon 14 skipping)

Crizotinib

Cabozantinib, capmatinib, glesatinib, merestinib, onartuzumab, savolitinib, tepotinib, tivantinib

mTOR



BEZ235, everolimus, LY3023414, ridaforolimus, sirolimus, temsirolimus, vistusertib

NTRK1/2/3



Altiratinib, cabozantinib, DS6051b, entrectinib, larotrectinib, merestinib, PLX7486, sitravatinib

p53



INGN-225

PARP



Iniparib, olaparib, talazoparib, veliparib

PD-1

Nivolumab, pembrolizumab



PDGFR

Nintedanib

Cediranib, dasatinib, dovitinib, IMC-3G3, pazopanib

PD-L1

Atezolizumab, durvalumab

Avelumab

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PI3K



BEZ235, buparlisib, LY3023414, pictilisib, PX-866, taselisib

RANKL



Denosumab

RAS



Tipifarnib

RET



Alectinib, apatinib, cabozantinib, capmatinib, glesatinib, merestinib, ponatinib, savolitinib, tepotinib

ROS

Ceritinib, crizotinib



SRC/BCR-ABL



Bosutinib, ponatinib, saracatinib

TRAIL



Conatumumab, dulanermin, mapatumumab

VEGF

Bevacizumab, ramucirumab

Aflibercept, neovastat

VEGFR

Nintedanib, ramucirumab (VEGFR2)

Brivanib alaninate, cabozantinib, cediranib, dovitinib, tivozanib

aApproved for use by either the U.S. Food and Drug Administration, National Comprehensive Cancer Network, or the European

Medicines Agency. Data summarized from Shum E, Wang F, Kim S, et al. Investigational therapies for squamous cell lung cancer: from animal studies to phase II trials. Expert Opin Investig Drugs 2017;26(4):415–426; Silva AP, Coelho PV, Anazetti M, et al. Targeted therapies for the treatment of non-small-cell lung cancer: monoclonal antibodies and biological inhibitors. Hum Vaccin Immunother 2017;13(4):843– 853; Jones PA, Issa JP, Baylin S. Targeting the cancer epigenome for therapy. Nat Rev Genet 2016;17(10):630–641; Romanidou O, Imbimbo M, Mountzios G, et al. Therapies in the pipeline for small-cell lung cancer. Br Med Bull 2016;119(1):37–48; Santarpia M, Daffina MG, Karachaliou N, et al. Targeted drugs in small-cell lung cancer. Transl Lung Cancer Res 2016;5(1):51–70; and Reck M, Rabe KF. Precision diagnosis and treatment for advanced non-small-cell lung cancer. N Engl J Med 2017;377(9):849–861.

ERBB2 (HER2) Human epidermal growth factor receptor 2 (HER2) is overexpressed in 6% to 35% and amplified in 10% to 20% of NSCLC. Unlike breast and gastric cancers, HER2 amplification or overexpression does not confer sensitivity to HER2 antibodies or TKIs in NSCLC.46 Exon 20 mutations in HER2 (2% to 4% of NSCLC)47 may, however, be predictive of HER2-targeting therapies. HER2 mutations confer resistance to EGFR TKIs regardless of EGFR mutation status as HER2 replaces EGFR in driving growth signals.

MET MET amplification is being targeted in clinical trials with a variety of antibodies and small molecule inhibitors, including crizotinib.48 MET amplification also mediates resistance to EGFR TKIs, independent of T790M, by activating the PI3K/AKT/mTOR pathway.46

RAS/RAF/MAPK Pathway RAS In lung cancer, KRAS is the most commonly mutated RAS family member (90% of mutations) with 80% occurring in codon 12 and the remainder in codons 13 and 61.46 Nearly always occurring in smoking LUACs, KRAS mutations are mutually exclusive with EGFR mutations, independent of EGFR signaling and resistant to EGFR TKIs. The prevalence and impact of mutant KRAS in lung cancer makes it an attractive, but so far unsuccessful, therapeutic target, but recent approaches are identifying genetic dependencies and harnessing the immune system.49

RAF BRAF is a known oncogene in lung cancer with an activating mutation in approximately 3% of cases, about 50% of which are V600E. It is predominantly found in LUAC of current/former smokers, and mutually exclusive to EGFR and KRAS mutations.46 Inhibition of kinase activity with small molecule kinase inhibitors has been successful and dabrafenib, in combination with the MEK inhibitor trametinib, is approved for use in V600E metastatic lung cancers. Recurrent mutations in ARAF and RAF1 have now been described in LUAC, which are oncogenic in vitro, and may predict response to targeted therapies such as sorafenib and MEK inhibitors.50

MEK (MAP2K1 or MEK1) Point mutations occur in 1% of NSCLC, more commonly LUAC. These mutations tend to be mutually exclusive with other driver mutations, occur outside the kinase domain, and induce constitutive extracellular signal-

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regulated kinase phosphorylation and cell proliferation in vitro. It remains to be determined if these mutations are predictive of anti-MEK therapies.46

MYC One of the major downstream effectors of the RAS/RAF/MAPK pathway is the MYC protooncogene and its family members (MYC, MYCN, and MYCL), which interact with a network of proteins including MAX.51 MYC activation can occur through gene overexpression and amplification in both NSCLC (frequently MYC) and SCLC (all three MYC members).18 Recurrent mutations have also been found in a MAX-interacting protein (MGA) in the MYC pathway.12 Deregulated MYC transcriptionally reprograms cell metabolism to promote neoplasia. It can also sensitize cells to apoptosis through activation of the mitochondrial apoptosis pathway where it often requires coexpression of antiapoptotic BCL2 proteins.52 In preclinical cancer models, MYC can be targeted directly by gene knockdown or using the dominant negative Omomyc inhibitor, which disrupts MYC interacting with its binding partner MAX,53 and indirectly through a variety of small molecule inhibitors that interrupt MYC-MAX binding.54 However, there are no MYC targeted drugs in early phase clinical trials nor biomarkers to predict which lung cancers would be most sensitive to MYC targeting.

Pl3K/AKT/mTOR Pathway In lung cancer, activation of the PI3K/AKT/mTOR pathway occurs early in pathogenesis, through the binding of growth factors to their respective RTK, amplification or mutation of PIK3CA or AKT1 (as well as EGFR or KRAS), or loss of function of the TSGs PTEN, TSC1, TSC2 and STK11 (LKB1).46 PIK3CA mutations are observed in 1% to 4% of LUAC and 16% of LUSC, and often co-occur with other lung cancer driver mutations. AKT is the downstream mediator of PI3K and is mutated in approximately 1% of LUAC. PTEN antagonizes the PI3K/AKT/mTOR pathway by dephosphorylating phosphatidylinositol 3,4,5-trisphosphate (PIP3), a product of PI3K, to PIP2, and is commonly inactivated in lung cancer.46 Currently, despite multiple clinical trials, there is no targeted therapy for this pathway that has shown clinical benefit in lung cancer.

STK11 (LKB1) Somatic inactivation of STK11 through point mutation and deletion occurs in approximately 30% of LUAC18 with low or absent expression in approximately 66% of SCLC. Loss of function is less frequent, however, in LUSC and large cell carcinoma.46 STK11 mutations often correlate with KRAS activation and confer increased in vitro sensitivity to MEK inhibition compared with either mutation alone.46 The combination of STK11 and KRAS mutations in LUAC confer a poor prognosis and impaired immune system engagement.55 Metformin, an oral hypoglycemic drug, activates AMPK and has antineoplastic preclinical activity in NSCLC, with clinical trials ongoing.

Insulin Growth Factor Pathway Overexpression of insulin-like growth factor 1 receptor (IGF1R) is observed in up to 70% of NSCLC, particularly LUSC, where increased signaling results in tumor growth and drug resistance. Increased plasma levels of insulin growth factor 1 ligand are associated with increased risk of lung cancer.56 Despite significant efforts to therapeutically target IGFR1, clinical studies of anti-IGFR1 agents in lung and other cancers have halted due to excessive toxicities and the need to identify biomarkers indicating which patients would respond.57

Fibroblast Growth Factor Pathway FGFR1 amplification occurs in approximately 20% of LUSC and has been associated with cigarette smoking and worse survival.46 Activating mutations in FGFR1 and FGFR3 have been detected in approximately 5% of NSCLC and 3% of LUSC, respectively. Anti-FGFR inhibitors have shown in vitro activity in FGFR mutant cell lines, and nintedanib is approved for use in advanced LUAC in Europe.

The p53 Pathway The most commonly altered gene in lung cancer is TP53, in approximately 90% of SCLC and >50% of NSCLC, more frequently in LUSC (81%) than LUAC (approximately 50%).46 Alteration usually involves a hemizygous

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deletion at its 17p13 locus and a mutation, mostly missense mutations, in the remaining allele. Mutations can be in the DNA binding domain, which prevents p53 binding target DNA, and oncogenic, dominant negative mutations in the homo-oligomerization domain, which can bind wild-type p53 and abrogate its ability to inhibit cellular transformation.46 Other components of the p53 pathway frequently altered in lung cancer include MDM2 and the tumor suppressors ATM and p14ARF. MDM2, commonly amplified in lung cancer, regulates p53 levels through ubiquitination degradation and can be induced by p53 or inhibited by ATM and p14ARF.46 ATM activates cell cycle checkpoints in response to DNA damage, ultimately activating and stabilizing p53. Deleterious ATM mutations occur in approximately 7% of LUAC, usually mutually exclusive to TP53 mutations.18 In the clinic, TP53 mutations are routinely determined using CLIA-certified tests; however, they cannot yet be therapeutically targeted. Efforts toward restoring normal p53 function or inhibiting the mutant protein58,59 include inhibiting negative regulators of p53 (such as MDM2 small molecule inhibitors, in clinical trial), p53 vaccination, gene therapy to reintroduce wild-type p53, p53 oncolytic viruses, and miRNA-based therapies; or small molecules targeting the mutant protein (e.g., APR-246, in clinical trial), proteosomal depletion, and targeting the inhibitory and oncogenic effects of mutant p53.58,59

The p16INK4a-RB Pathway The p16INK4a-RB pathway is commonly altered in lung cancer through mutation (CDK4 and CDKN2A), deletion (RB1 and CDKN2A), amplification (CDK4 and CCDN1), methylation (CDKN2A and RB1), and phosphorylation (RB).46 Mutant or absent protein expression of RB occurs in approximately 90% of SCLC compared with 10% to 15% of NSCLC, where p16INK4a abnormalities are more common (approximately 40%). These abnormalities cannot yet be therapeutically targeted.

Fusion Proteins Oncogenic fusion proteins from gene rearrangements are routinely detected in patient tumors using CLIA-certified tests, with targeted therapies available for most cases.

ALK The ALK fusion protein is an activating oncogenic driver occurring in 2% to 8% of NSCLC.60 ALK rearrangements, which result in persistent mitogenic signaling and malignant transformation, most commonly occur with not only EML4 but also TFG, KIF5B, PTPN3, and KLC1.46 NSCLC ALK fusions are almost always exclusive of EGFR and KRAS mutations, and occur predominantly in LUAC, never/light smokers, younger age, and male gender. Tumors with ALK fusions respond to ALK targeted therapy, approved for first- (crizotinib and ceritinib) and second-line (alectinib and brigatinib) therapy. Although resistance to crizotinib usually occurs, second- and third-generation TKIs (e.g., lorlatinib, in clinical trial) are effective in crizotinib-resistant tumors.61

ROS1 ROS1 is an RTK in the insulin receptor family not normally expressed in the lung. Rearrangement occurs in 1% to 2% of NSCLC patients: mostly LUAC, younger patients, and never smokers.46 ROS1 fusions induce autophosphorylation and downstream activation of common growth and survival pathways like MAPK, STAT3, and PI3K/AKT/mTOR. Select ALK inhibitors (e.g., crizotinib and lorlatinib) are active in these tumors. Although crizotinib resistance usually occurs through ROS1 G2032R, the new generation TKI lorlatinib shows promise.61

RET RET rearrangements (with KIF5B, CCD6, NCOA4, EPHA5, and PICALM)62 occur in approximately 1% to 2% of NSCLC, mostly LUAC and never smokers, and are mutually exclusive with ALK or ROS1 rearrangements, and EGFR mutations. Similar to ALK, RET fusion partners act as dimerization units, leading to ligand-independent homodimerization and constitutive kinase activity. Whereas toxicities are common for many multitargeted kinase inhibitors, selective inhibitors (e.g., RXDX-105 and alectinib) exhibit fewer toxicities and are under clinical evaluation.62

NTRK NTRK1, NTRK2, and NTRK3 encode the tropomyosin receptor kinases (TRK): TRKA, TRKB, and TRKC,

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respectively. Fusion partners include MPRIP and CD74 and leave the TK domain of NTRK1 intact.62 NTRK fusions are estimated to occur in 3% of NSCLC with no other identified driver mutation.62 TRK inhibitors are being clinically assessed, but tumors develop resistance.

BRAF BRAF gene fusions are extremely rare (0.2% of NSCLC) and have been detected in LUAC, but not in LUSC or SCLC,62 and tend to be mutually exclusive of other activating mutations in the MAPK pathway. The fusion leaves an intact BRAF kinase domain and dimerization motif, but the RAS-binding domain is replaced by the fusion partner, which can include EPS15, NUP214, ARMC10, BTF3L4, AGK, GHR, ZC3HAV, and TRIM24. BRAF fusions are activating and certain BRAF fusion variants can homodimerize with one another. Unlike BRAF V600E, which functions as a monomer, BRAF fusions function as dimers. As such, BRAF inhibitors, such as vemurafenib and dabrafenib that only bind one site of the RAF dimer, are ineffective in BRAF fusion–driven malignancies and may paradoxically promote cancer growth.62

EGFR EGFR gene fusions are also rare, occurring in about 0.05% of lung cancers, and involve a breakpoint in EGFR (between exon 23 and intron 25) fused with either RAD51 or PURB. The fusions both activate EGFR and sensitize tumors to EGFR TKIs.62

Epigenetic Changes in Lung Carcinogenesis Epigenetic events can lead to changes in gene expression without changes in DNA sequence and are therefore potentially pharmacologically reversible. Epigenetic silencing of gene expression by DNA methylation and chromatin remodeling is essential for the initiation and progression of lung cancer, affecting all major cell regulatory pathways.63 Being almost universal in lung cancer, epigenetic dysregulation is an attractive target for clinical intervention and biomarkers for lung cancer risk, early diagnosis, classification, prognosis, and prediction. Epigenetic targeting drugs in combination with existing therapies are being intensively investigated.63

Methylation and Chromatin Remodeling Aberrant promoter hypermethylation (transcriptional silencing from the addition of a methyl group to CpG islands in a gene promoter) is a common method for TSG inactivation and occurs early in lung tumorigenesis. Epigenetic disruption can occur through DNA methylation by DNA methyltransferases, enzymes that transfer the methyl group, or chromatin remodeling and histone modification, where nucleosome position and histone modification can result in a compacted chromatin environment and transcriptionally inactive DNA.63 This can be facilitated by mutation or overexpression of epigenetic modifiers, histone methyltransferases, histone acetyltransferase coactivators, and the histone lysine demethylase KDM2A.63 Mutations have been reported in the epigenetic modifiers CREBBP and EP300 as well as in SMARCA4 (encoding BRG1), SETD2, and ARID1A, which encode proteins in the SWI/SNF complex, a predicted tumor suppressor important in chromatin remodeling.12,17,18,63 In lung cancer, aberrant methylation of MGMT and p16INK4a have been reported as biomarkers for early detection, and APC, CDH1, CDH13, DAPK1, DLEC1, MLH1, p16INK4a, PTEN, and RASSF1A for prognosis.63 Initial trials using inhibitors of DNA methyltransferases, histone deacetylases, and histone methyltransferases had disappointing results, with low activity and toxicity. Benefit has been shown in more recent approaches, however, by using lower doses to promote reversal of DNA methylation rather than cytotoxicity, and combining epigenomic-targeted drugs (“epidrugs”) with conventional chemotherapy, TKIs (such as erlotinib), or immunotherapy,63 where it is hypothesized that epidrugs “prime” the tumor to better respond to other treatments.

Noncoding RNAs Noncoding RNAs such as miRNAs and lncRNAs do not encode proteins and represent >80% of the transcribed human genome. miRNAS. miRNAs are a class of highly conserved, small (20 to 24 nucleotides) RNAs capable of regulating gene expression, most commonly by direct cleavage of target mRNA or by inhibition of translation through interaction with the 3′ untranslated region. It is estimated miRNAs may regulate up to 60% of the human genome where

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miRNA expression and function is driven by chromosomal aberrations, epigenetic changes, miRNA or target polymorphisms, environmental stimuli (e.g., cigarette smoke), and TSGs or oncogenes.64 miRNAs regulate biologic processes fundamental to cancer initiation and progression. In lung cancer, there are miRNA profiles for histologic and prognostic classification, and miRNAs have been detected in peripheral blood and sputum.64 Some key oncogenic miRNAs (“oncomiRs”) in lung cancer include miR-21, miR-31, miR-155, miR-17-92 cluster, and miR-221/222, whereas let-7, miR34a, miR-126, miR-195, and the miR-200 family are key tumor-suppressive miRNAs.64 Restoration of aberrantly expressed miRNAs can be achieved in vitro and in vivo using miRNA mimics or miRNA inhibitors (antagomirs and small interfering RNA [siRNA]) delivered systemically or through local injection. Concurrent manipulation of miRNA expression with conventional therapies increases response to EGFR TKIs, radiotherapy, and chemotherapy.63 Translation of preclinical findings has, however, been limited by inefficient delivery, pharmacokinetics, and toxicity, such as with the miR-34 mimic MRX34 in SCLC.63 miR-16 TargomiR (an miRNA mimic delivered by targeted bacterial minicells), however, showed efficacy in malignant mesothelioma patients,65 and although open to advanced NSCLC, none were recruited. lncRNAs. lncRNAs (200 nucleotides or longer) control gene expression via transcriptional and epigenetic regulation, imprinting, splicing, and subcellular transport. Although largely regulating nearby genes, they can also serve as scaffolds for protein-protein interactions and regulate kinase functions. lncRNA dysregulation contributes to lung cancer development, progression, and metastasis,64 and can serve as minimally invasive molecular markers for screening and diagnosis. Like miRNAs, lncRNAs can function as oncogenes or TSGs, with some key oncogenic lncRNAs being CCAT2, MALAT1, and HOTAIR, and tumor-suppressive lncRNAs being BANCR, GAS6-AS1, MEG3, and PANDAR.64 Currently there are no therapies targeting lncRNA alterations.

NFIB, a Metastasis-Inducing Transcription Factor NFIB was recently found to increase chromatin accessibility to many intergenic regions and promote a prometastatic neuronal gene expression program driving SCLC metastases.66 Identification of widespread chromatin changes during SCLC progression reveals an unexpected global epigenomic reprogramming during metastatic progression that needs to be explored in NSCLC and for targeted therapy approaches.

KDM Lysine Demethylases (JumonjiC) as an Epigenomic Drug Resistance Mechanism A recent study found NSCLCs selected for platin-taxane resistance progressively increased the expression of many KDM (JumonjiC) lysine-demethylases, had altered histone methylation, and, importantly, showed hypersensitivity to JumonjiC inhibitors.67 These inhibitors also prevented the emergence of drug-tolerant colonies from chemo-naive cells, and synergized with standard chemotherapy in vitro and in vivo, making them promising therapeutics for targeting taxane-platin-chemoresistant NSCLC, preventing the outgrowth of primary resistant tumor cells, and indicating responsive tumors with increased expression of selected KDM demethylases.

METASTASIS AND THE TUMOR MICROENVIRONMENT Cells that comprise the tumor microenvironment interact both with each other and with tumor cells, and as a consequence, they can affect tumor growth, invasion, and metastasis.68 Molecular alterations in lung cancer affect the tumor microenvironment and how they respond to microenvironmental signals. Thus, modulation of critical signals from the tumor to the microenvironment or vice versa could improve lung cancer treatment.

Epithelial-to-Mesenchymal Transition Epithelial-to-mesenchymal transition (EMT) describes a loss of cell polarity and has been implicated in lung tumor progression and metastasis.69 A variety of candidate genes are involved, including cell adhesion molecules such as the cadherins, integrins, and CD44. The E-cadherin–catenin complex is critical for intercellular adhesiveness and the maintenance of normal and malignant tissue architecture, and EMT is typically due to loss of E-cadherin expression. Conversion of epithelial tumor cells to a mesenchymal state promotes motility and invasiveness but at a secondary site, tumor cells undergo a mesenchymal-to-epithelial transition (MET) to revert to the more proliferative epithelial state. EMT is also associated with early carcinogenic events, stem cell–like

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properties, and resistance to cell death, senescence, and conventional chemotherapies.69 In lung cancer, tumors expressing mesenchymal markers and EMT inducers (e.g., Vimentin, Twist and Snail) have poorer prognosis and resistance to EGFR TKIs.69 The miR-200 family is an important negative regulator of EMT, and its expression is frequently lost in lung cancer.69

Angiogenesis Angiogenesis is a hallmark of cancer, being essential for a microscopic tumor to expand into a macroscopic, clinically relevant tumor. A number of angiogenic proteins are dysregulated in lung cancer, including vascular endothelial growth factor (VEGF), platelet-derived growth factor (PDGF), fibroblast growth factor (FGF), interleukin-8, and angiopoietins 1 and 2. VEGF signaling, stimulated by tumor hypoxia, growth factors and cytokines, and oncogenic activation; promotes proliferation, migration, and survival, inhibits apoptosis, and regulates endothelial cell permeability.70 It is highly active in both NSCLC and SCLC and is associated with poor prognosis in NSCLC.70 Anti-VEGF therapy approaches include blocking VEGF from binding extracellularly to its receptors using VEGF-specific antibodies and recombinant fusion proteins, or using small molecule TKIs that bind to the intracellular region of vascular endothelial growth factor (VEGFR). The humanized monoclonal antibody bevacizumab blocks binding of VEGF-A to VEGFR1 and VEGFR1 and is approved for use in lung cancer.70 Interestingly, VEGF expression does not always correlate with response to bevacizumab, possibly due to single nucleotide polymorphisms in VEGF.70

Immune Checkpoint Inhibition Accumulating evidence suggests T cells that target tumor neoantigens arising from cancer mutations are the main mediators of effective cancer immunotherapy in humans.71 To date, the major approach used in lung cancer is monoclonal antibody immune checkpoint inhibitors, likely efficacious in NSCLC and SCLC because lung cancer induces an immunocompromised microenvironment. Monoclonal antibodies to cytotoxic T-lymphocyte– associated antigen 4 (CTLA-4), programmed cell death protein 1 (PD-1), and programmed cell death protein ligand 1 (PD-L1) are currently approved by the U.S. Food and Drug Administration (FDA) for use in patients (see Table 47.3). PD-L1 is expressed on tumor cells and suppresses immune activity by binding to PD-1 on T cells. Nivolumab and pembrolizumab prevent this interaction by binding to PD-1, whereas atezolizumab binds to PDL1. All three inhibitors are approved for use in lung cancer. CTLA-4 is expressed on T cells and suppresses T-cell signaling. Ipilimumab is a monoclonal antibody that inhibits CTLA-4 and is approved for use in melanoma. These inhibitors have become standard of care in relapsed or metastatic lung cancer, demonstrating higher and longer responses compared to standard chemotherapy. However, only approximately 20% of all lung cancers will respond to immune checkpoint inhibitors, and specific biomarkers are needed to guide and monitor therapy. PDL1 expression, mutational load, mutation heterogeneity, production of mutation-associated neoantigens, oncogenic driver mutations, immune cell populations, gut microbiota, and tumor microenvironment metabolomics have all been associated with response.72

Exosomes as a Source of Information on Tumor Molecular Alterations Exosomes are small (30 to 150 nm), extracellular, membrane vesicles that can act as key mediators of intercellular communication within the tumor microenvironment. Containing various molecules, such as nucleic acids (DNA, mRNA, and noncoding RNAs), lipids, and proteins, exosomes can modify the phenotype of recipient cells. In lung cancer, exosomes have been shown to carry mutated DNA reflective of the tumor and promote tumorigenesis and metastatic dissemination and resistance to chemotherapy and targeted therapy.73 Exosomes have excellent clinical potential as they can be isolated from blood in a minimally invasive manner.73

LUNG CANCERS STEM CELLS The cancer stem cell (CSC) is defined as a cell within a tumor with the capacity to self-renew and generate heterogeneous lineages of cancer cells that comprise the bulk of the tumor. The CSC hypothesis proposes it is this rare population of CSCs that drives primary tumor growth, metastasis, and resistance to cytotoxic therapies where residual viable stem cells can repopulate the tumor after treatment. Although evidence for lung CSCs (also called “tumor-initiating cells”) is increasing, the identification and isolation of lung CSCs has been technically

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challenging, and few methods or markers have validated.74 They include the side population assay and cell surface expression of CD44, CD87, CD90, CD133, CD166, and aldehyde dehydrogenases.74 As almost all deposited molecular analyses of lung cancer analyze the bulk of tumor cells, molecular analyses of lung CSC subpopulations are urgently needed. Stem cell signaling pathways important in normal lung development, such as the Hedgehog (Hh), Wnt, and Notch pathways, are likely to be involved in the regulation of lung CSCs, and pathway members are often dysregulated or mutated in SCLC and NSCLC.75 Distinct subsets of epithelial cells (basal cells, secretory cells, ciliated cells, and pulmonary neuroendocrine cells) and potential stem cell niches have been identified in the normal lung epithelium. Basal cells are the stem cells of the airway epithelium, capable of self-renewal and mucociliary differentiation to give rise to secretory and ciliated cells. There is also a distinct bronchioalveolar stem cell population that can self-renew and differentiate into Clara cells and AT-II cells.74 Notch signaling plays a major role in the differentiation to either a secretory or ciliated lineage, and aldehyde dehydrogenase activity, a putative CSC marker in LUAC, is dependent on Notch activity.74 Current chemotherapy and radiotherapy fail to specifically target CSCs. FDA-approved disulfiram (Antabuse), previously used to treat alcoholism, is a potential pan–aldehyde dehydrogenase inhibitor with anticancer properties in lung cancer.75 Specific inhibitors of Wnt, Hh, and Notch signaling have shown efficacy in lung cancer preclinically and some are now in clinical trial.75

TELOMERASE-MEDIATED CELLULAR IMMORTALITY IN LUNG CANCER During normal cell division, telomere shortening leads to cell senescence, thereby governing normal cell mortality. Telomerase is an enzyme that maintains telomere length and prevents loss of telomere ends beyond critical points, thereby essential for cell immortality. The human telomerase reverse transcriptase catalytic subunit is the major determinant of telomerase activity. Although silenced in normal cells (except stem cells), telomerase is activated in >80% of NSCLCs and almost all SCLCs.56 Preclinically, telomerase and telomerase-associated protein inhibitors have shown activity in lung cancer.76 Clinical testing of imetelstat suggests NSCLCs with the shortest telomeres respond best,77 but it is also possible that certain oncogenotypes (e.g., KRAS mutant) are more sensitive to telomerase inhibition.78

CLINICAL TRANSLATION OF MOLECULAR DATA This chapter outlines some of the significant molecular alterations involved in the initiation and/or progression of lung cancer, which have translated into significant advancements in targeted therapy (see Table 47.3), but we have yet to move any biomarkers for lung cancer risk or early detection into clinical use.79 The recent rapid progress in genomics and bioinformatics now gives researchers the tools to correlate patient subsets with augmented sensitivity to conventional or targeted therapeutics, distinguish driver versus passenger mutations, and better focus the design of novel therapeutic targets. To achieve these goals, we continue to need large numbers of samples from lung cancer patients, incorporation of genomic studies into clinical trials of molecularly targeted agents, and timely mutation testing of clinical materials (such as FFPE specimens) using clinical laboratory practices (CLIAcertified laboratory methods). Identifying and unraveling the intricate and interlinked pathways will lead to improved detection, diagnosis, treatment, and prognosis of lung cancer by achieving “precision medicine”; the selection of the best treatment for each patient based on tumor associated biomarkers.

Current Translation of Rationale-based Targeted Therapy Improved detection and sampling of clinical samples using fluorescent bronchoscopy, endobronchial ultrasounds, and laser capture microdissection techniques now enables precise analysis of abnormal epithelial cells. The National Comprehensive Cancer Network (NCCN) guidelines for NSCLC outline recommended molecular analyses. Predictive biomarkers, indicative of therapeutic efficacy, include ALK fusions, ROS1 gene rearrangements, sensitizing EGFR mutations, BRAF V600E mutations, and PD-L1 expression. Emerging biomarkers include HER2 mutations, RET gene rearrangements, and MET amplification or exon 14 skipping mutations. The only current prognostic biomarker, indicative of innate tumor aggressiveness, is KRAS mutations. Table 47.3 outlines targeted therapies that are currently approved for use or in clinical trial for lung cancer, with a significant number of compounds also undergoing preclinical testing. Importantly, the NCCN guidelines

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recommend retesting a tumor that is actively progressing on targeted therapy, as it can inform on the next appropriate therapeutic step. The NCCN currently has no recommendations for the molecular analysis of SCLC. Identifying patient subsets that will most benefit from these therapies remains a considerable task, including clinical guidelines that explicitly describe if, when, and how molecular testing should be performed to identify known responders. To address the latter, the College of American Pathologists, the International Association for the Study of Lung Cancer, and the Association for Molecular Pathology jointly published a guideline on molecular testing for the selection of lung cancer patients for EGFR and ALK TKIs,80 which are currently being updated to incorporate emerging clinical standards and recent breakthroughs. DNA sequencing advances mean it is now feasible to prospectively molecularly analyze tumors for mutations in hundreds of cancer-associated genes using assays requiring only small quantities of FFPE tissue. As a followup to the LCMC study that molecularly analyzed LUACs then treated those with actionable mutations,81 a prospective study in 860 LUACs stratified patients by potentially actionable genetic events from a panel of >300 cancer-associated genes.82 Approximately 37% of patients received a therapy guided by their tumor molecular profile, and they found early prospective tumor sequencing, including of non–standard-of-care predictive biomarkers, can guide therapy and improve clinical outcomes.

Potential for Future Clinical Translation The variety of clinically translatable approaches for molecular analyses of human lung cancer is summarized in Table 47.4. In addition, other issues are the need to identify and understand the importance of co-occurring mutations, the development and use of “liquid biopsies,” and the use of this information for the chemoprevention of lung cancer. TABLE 47.4

Important Areas for Clinical Translation of Findings from the Molecular Analyses of Lung Cancer Molecular changes in the field at risk of developing lung cancer for early cancer detection and evaluating chemoprevention efforts Molecular changes indicating exposure to different carcinogen types Interactions of molecular changes with germline polymorphisms impacting tumor clinical behavior and response to therapies Molecular analyses of cancer stem cell and related tumor subpopulations Molecular biomarkers providing prognostic information Molecular biomarkers providing histologic typing information Molecular changes detected in circulating tumor cell DNA for early lung cancer diagnoses, monitoring of response to therapy, and selection of targeted therapy Molecular biomarkers identifying lung cancer acquired vulnerabilities Molecular biomarkers predicting response to chemotherapy and targeted therapies Molecular biomarkers predicting response to immuno-oncology therapies Molecular analyses of epigenomic changes in cancer to determine epigenomic targeted therapy

Co-occurring oncogenic mutations. Increasing molecular data on increasing numbers of lung tumors will identify new therapeutic targets, particularly rare driver events. This data will also identify co-occurring mutations that represent tumor vulnerabilities for known but currently untargetable driver mutations, such as mutant KRAS, or tumors with acquired resistance. For instance, tumors with co-occurring KEAP1 and KRAS mutations are vulnerable to glutamate supply,83 whereas those with co-occurring KRAS and STK11 mutations are addicted to COPI31 and have a metabolic vulnerability related to a dependence on pyrimidine metabolism.84 Liquid biopsies to analyze circulating tumor DNA have great potential to provide a dynamic and comprehensive genomic profile of NSCLC in a minimally invasive manner.85 When integrated with nextgeneration sequencing, liquid biopsies could be applied to NSCLC diagnosis and treatment by screening for earlystage lung cancer, identifying actionable genomic alterations, tracking spatiotemporal tumor evolution, and dynamically monitoring response and resistance to targeted therapies. Challenges include defining a clinically relevant threshold of detection for genomic alterations and early screening. Nevertheless, CLIA-certified tests are now available to match advanced cancer patients to approved targeted therapies, such as Guardant Health’s 73gene panel. Chemoprevention of lung cancer. The National Lung Screening Trial found annual screening with low-dose

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computed tomography in a high-risk population was associated with a 20% reduction in lung cancer–specific mortality, compared with conventional chest radiography.86 In addition to screening, lung cancer prevention and outcomes could be enhanced by reducing inflammation. The Canakinumab Anti-inflammatory Thrombosis Outcomes Study found anti-inflammatory therapy using canakinumab, an interleukin-1β inhibitor, significantly reduced lung cancer incidence (by 67%) and mortality (by 77%).87 Supported by NCI P50CA70907.

REFERENCES 1. 2. 3. 4.

Siegel RL, Miller KD, Jemal A. Cancer statistics, 2017. CA Cancer J Clin 2017;67(1):7–30. Wistuba II, Gazdar AF. Lung cancer preneoplasia. Annu Rev Pathol 2006;1:331–48. Nowell PC. The clonal evolution of tumor cell populations. Science 1976;194(4260):23–28. Dakubo GD, Jakupciak JP, Birch-Machin MA, et al. Clinical implications and utility of field cancerization. Cancer Cell Int 2007;7:2. 5. Hanahan D, Weinberg RA. The hallmarks of cancer. Cell 2000;100(1):57–70. 6. Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell 2011;144(5):646–674. 7. Parkin DM, Bray F, Ferlay J, et al. Global cancer statistics, 2002. CA Cancer J Clin 2005;55(2):74–108. 8. Sun S, Schiller JH, Gazdar AF. Lung cancer in never smokers—a different disease. Nat Rev Cancer 2007;7(10):778–790. 9. Govindan R, Ding L, Griffith M, et al. Genomic landscape of non-small cell lung cancer in smokers and neversmokers. Cell 2012;150(6):1121–1134. 10. Lynch TJ, Bell DW, Sordella R, et al. Activating mutations in the epidermal growth factor receptor underlying responsiveness of non-small-cell lung cancer to gefitinib. N Engl J Med 2004;350(21):2129–2139. 11. Paez JG, Janne PA, Lee JC, et al. EGFR mutations in lung cancer: correlation with clinical response to gefitinib therapy. Science 2004;304(5676):1497–1500. 12. Cancer Genome Atlas Research Network. Comprehensive molecular profiling of lung adenocarcinoma. Nature 2014;511(7511):543–550. 13. Imielinski M, Berger AH, Hammerman PS, et al. Mapping the hallmarks of lung adenocarcinoma with massively parallel sequencing. Cell 2012;150(6):1107–1120. 14. Cancer Genome Atlas Research Network. Comprehensive genomic characterization of squamous cell lung cancers. Nature 2012;489(7417):519–525. 15. George J, Lim JS, Jang SJ, et al. Comprehensive genomic profiles of small cell lung cancer. Nature 2015;524(7563):47–53. 16. Rudin CM, Durinck S, Stawiski EW, et al. Comprehensive genomic analysis identifies SOX2 as a frequently amplified gene in small-cell lung cancer. Nat Genet 2012;44(10):1111–1116. 17. Peifer M, Fernández-Cuesta L, Sos ML, et al. Integrative genome analyses identify key somatic driver mutations of small-cell lung cancer. Nat Genet 2012;44(10):1104–1110. 18. Campbell JD, Alexandrov A, Kim J, et al. Distinct patterns of somatic genome alterations in lung adenocarcinomas and squamous cell carcinomas. Nat Genet 2016;48(6):607–616. 19. Alexandrov LB, Nik-Zainal S, Wedge DC, et al. Signatures of mutational processes in human cancer. Nature 2013;500(7463):415–421. 20. de Bruin EC, McGranahan N, Mitter R, et al. Spatial and temporal diversity in genomic instability processes defines lung cancer evolution. Science 2014;346(6206):251–256. 21. Jamal-Hanjani M, Wilson GA, McGranahan N, et al. Tracking the evolution of non-small-cell lung cancer. N Engl J Med 2017;376(22):2109–2121. 22. Zhang J, Fujimoto J, Zhang J, et al. Intratumor heterogeneity in localized lung adenocarcinomas delineated by multiregion sequencing. Science 2014;346(6206):256–259. 23. Taguchi K, Motohashi H, Yamamoto M. Molecular mechanisms of the Keap1-Nrf2 pathway in stress response and cancer evolution. Genes Cells 2011;16(2):123–140. 24. Xie Y, Minna JD. Predicting the future for people with lung cancer. Nat Med 2008;14(8):812–813. 25. Subramanian J, Simon R. Gene expression-based prognostic signatures in lung cancer: ready for clinical use? J Natl Cancer Inst 2010;102(7):464–474. 26. Tang H, Wang S, Xiao G, et al. Comprehensive evaluation of published gene expression prognostic signatures for biomarker-based lung cancer clinical studies. Ann Oncol 2017;28(4):733–740. 27. Paik S, Shak S, Tang G, et al. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med 2004;351(27):2817–2826.

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28. Ellis MJ, Gillette M, Carr SA, et al. Connecting genomic alterations to cancer biology with proteomics: the NCI Clinical Proteomic Tumor Analysis Consortium. Cancer Discov 2013;3(10):1108–1112. 29. Akbani R, Ng PK, Werner HM, et al. A pan-cancer proteomic perspective on The Cancer Genome Atlas. Nat Commun 2014;5:3887. 30. Kris MG, Johnson BE, Kwiatkowski DJ, et al. Identification of driver mutations in tumor specimens from 1,000 patients with lung adenocarcinoma: the NCI’s Lung Cancer Mutation Consortium (LCMC). J Clin Oncol 2011;29(Suppl):CRA7506. 31. Kim HS, Mendiratta S, Kim J, et al. Systematic identification of molecular subtype-selective vulnerabilities in nonsmall-cell lung cancer. Cell 2013;155(3):552–566. 32. Kim J, McMillan E, Kim HS, et al. XPO1-dependent nuclear export is a druggable vulnerability in KRAS-mutant lung cancer. Nature 2016;538(7623):114–117. 33. McDonald ER 3rd, de Weck A, Schlabach MR, et al. Project DRIVE: a compendium of cancer dependencies and synthetic lethal relationships uncovered by large-scale, deep RNAi screening. Cell 2017;170(3):577–592.e10. 34. Tsherniak A, Vazquez F, Montgomery PG, et al. Defining a cancer dependency map. Cell 2017;170(3):564– 576.e16. 35. Leung AW, de Silva T, Bally MB, et al. Synthetic lethality in lung cancer and translation to clinical therapies. Mol Cancer 2016;15(1):61. 36. Mali P, Esvelt KM, Church GM. Cas9 as a versatile tool for engineering biology. Nat Methods 2013;10(10):957– 963. 37. Meyers RM, Bryan JG, McFarland JM, et al. Computational correction of copy number effect improves specificity of CRISPR-Cas9 essentiality screens in cancer cells. Nat Genet 2017;49(12):1779–1784. 38. Weiswald LB, Bellet D, Dangles-Marie V. Spherical cancer models in tumor biology. Neoplasia 2015;17(1):1–15. 39. Hidalgo M, Amant F, Biankin AV, et al. Patient-derived xenograft models: an emerging platform for translational cancer research. Cancer Discov 2014;4(9):998–1013. 40. Ramirez RD, Sheridan S, Girard L, et al. Immortalization of human bronchial epithelial cells in the absence of viral oncoproteins. Cancer Res 2004;64(24):9027–9034. 41. Kellar A, Egan C, Morris D. Preclinical murine models for lung cancer: clinical trial applications. Biomed Res Int 2015;2015:621324. 42. Weinstein IB. Cancer. Addiction to oncogenes—the Achilles heal of cancer. Science 2002;297(5578):63–64. 43. Knudson AG Jr. The ninth Gordon Hamilton-Fairley memorial lecture. Hereditary cancers: clues to mechanisms of carcinogenesis. Br J Cancer 1989;59(5):661–666. 44. Russo A, Franchina T, Ricciardi GR, et al. A decade of EGFR inhibition in EGFR-mutated non small cell lung cancer (NSCLC): old successes and future perspectives. Oncotarget 2015;6(29):26814–26825. 45. Passiglia F, Listi A, Castiglia M, et al. EGFR inhibition in NSCLC: new findings … and opened questions? Crit Rev Oncol Hematol 2017;112:126–135. 46. Cooper WA, Lam DC, O’Toole SA, et al. Molecular biology of lung cancer. J Thorac Dis 2013;5(Suppl 5):S479– S490. 47. Pillai RN, Behera M, Berry LD, et al. HER2 mutations in lung adenocarcinomas: a report from the Lung Cancer Mutation Consortium. Cancer 2017;123(21):4099–4105. 48. Gelsomino F, Facchinetti F, Haspinger ER, et al. Targeting the MET gene for the treatment of non-small-cell lung cancer. Crit Rev Oncol Hematol 2014;89(2):284–299. 49. McCormick F. KRAS as a therapeutic target. Clin Cancer Res 2015;21(8):1797–1801. 50. Imielinski M, Greulich H, Kaplan B, et al. Oncogenic and sorafenib-sensitive ARAF mutations in lung adenocarcinoma. J Clin Invest 2014;124(4):1582–1586. 51. Tu WB, Helander S, Pilstål R, et al. Myc and its interactors take shape. Biochim Biophys Acta 2015;1849(5):469– 483. 52. Stine ZE, Walton ZE, Altman BJ, et al. MYC, metabolism, and cancer. Cancer Discov 2015;5(10):1024–1039. 53. Conacci-Sorrell M, McFerrin L, Eisenman RN. An overview of MYC and its interactome. Cold Spring Harb Perspect Med 2014;4(1):a014357. 54. Fletcher S, Prochownik EV. Small-molecule inhibitors of the Myc oncoprotein. Biochim Biophys Acta 2015;1849(5):525–543. 55. Skoulidis F, Byers LA, Diao L, et al. Co-occurring genomic alterations define major subsets of KRAS-mutant lung adenocarcinoma with distinct biology, immune profiles, and therapeutic vulnerabilities. Cancer Discov 2015;5(8):860–877. 56. Larsen JE, Minna JD. Molecular biology of lung cancer: clinical implications. Clin Chest Med 2011;32(4):703–

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740. 57. Iams WT, Lovly CM. Molecular pathways: clinical applications and future direction of insulin-like growth factor-1 receptor pathway blockade. Clin Cancer Res 2015;21(19):4270–4277. 58. Nguyen D, Liao W, Zeng SX, et al. Reviving the guardian of the genome: Small molecule activators of p53. Pharmacol Ther 2017;178:92–108. 59. Duffy MJ, Synnott NC, Crown J. Mutant p53 as a target for cancer treatment. Eur J Cancer 2017;83:258–265. 60. Facchinetti F, Tiseo M, Di Maio M, et al. Tackling ALK in non-small cell lung cancer: the role of novel inhibitors. Transl Lung Cancer Res 2016;5(3):301–321. 61. Shaw AT, Felip E, Bauer TM, et al. Lorlatinib in non-small-cell lung cancer with ALK or ROS1 rearrangement: an international, multicentre, open-label, single-arm first-in-man phase 1 trial. Lancet Oncol 2017;18(12):1590–1599. 62. Farago AF, Azzoli CG. Beyond ALK and ROS1: RET, NTRK, EGFR and BRAF gene rearrangements in nonsmall cell lung cancer. Transl Lung Cancer Res 2017;6(5):550–559. 63. Duruisseaux M, Esteller M. Lung cancer epigenetics: from knowledge to applications. Semin Cancer Biol 2017 [Epub ahead of print]. doi:10.1016/j.semcancer.2017.09.005. 64. Inamura K. Major tumor suppressor and oncogenic non-coding RNAs: clinical relevance in lung cancer. Cells 2017;6(2):E12. 65. van Zandwijk N, Pavlakis N, Kao SC, et al. Safety and activity of microRNA-loaded minicells in patients with recurrent malignant pleural mesothelioma: a first-in-man, phase 1, open-label, dose-escalation study. Lancet Oncol 2017;18(10):1386–1396. 66. Denny SK, Yang D, Chuang CH, et al. Nfib promotes metastasis through a widespread increase in chromatin accessibility. Cell 2016;166(2):328–342. 67. Dalvi MP, Wang L, Zhong R, et al. Taxane-platin-resistant lung cancers co-develop hypersensitivity to JumonjiC demethylase inhibitors. Cell Rep 2017;19(8):1669–1684. 68. Sautès-Fridman C, Cherfils-Vicini J, Damotte D, et al. Tumor microenvironment is multifaceted. Cancer Metastasis Rev 2011;30(1):13–25. 69. Sung WJ, Kim H, Park KK. The biological role of epithelial-mesenchymal transition in lung cancer (Review). Oncol Rep 2016;36(3):1199–1206. 70. Korpanty G, Smyth E, Sullivan LA, et al. Antiangiogenic therapy in lung cancer: focus on vascular endothelial growth factor pathway. Exp Biol Med (Maywood) 2010;235(1):3–9. 71. Tran E, Robbins PF, Rosenberg SA. “Final common pathway” of human cancer immunotherapy: targeting random somatic mutations. Nat Immunol 2017;18(3):255–262. 72. Grizzi G, Caccese M, Gkountakos A, et al. Putative predictors of efficacy for immune checkpoint inhibitors in nonsmall-cell lung cancer: facing the complexity of the immune system. Expert Rev Mol Diagn 2017;17(12):1055– 1069. 73. Vanni I, Alama A, Grossi F, et al. Exosomes: a new horizon in lung cancer. Drug Discov Today 2017;22(6):927– 936. 74. Zakaria N, Satar NA, Abu Halim NH, et al. Targeting lung cancer stem cells: research and clinical impacts. Front Oncol 2017;7:80. 75. Leon G, MacDonagh L, Finn SP, et al. Cancer stem cells in drug resistant lung cancer: targeting cell surface markers and signaling pathways. Pharmacol Ther 2016;158:71–90. 76. Frink RE, Peyton M, Schiller JH, et al. Telomerase inhibitor imetelstat has preclinical activity across the spectrum of non-small cell lung cancer oncogenotypes in a telomere length dependent manner. Oncotarget 2016;7(22):31639–31651. 77. Chiappori AA, Kolevska T, Spigel DR, et al. A randomized phase II study of the telomerase inhibitor imetelstat as maintenance therapy for advanced non-small-cell lung cancer. Ann Oncol 2015;26(2):354–362. 78. Liu W, Yin Y, Wang J, et al. Kras mutations increase telomerase activity and targeting telomerase is a promising therapeutic strategy for Kras-mutant NSCLC. Oncotarget 2017;8(1):179–190. 79. Hassanein M, Callison JC, Callaway-Lane C, et al. The state of molecular biomarkers for the early detection of lung cancer. Cancer Prev Res (Phila) 2012;5(8):992–1006. 80. Lindeman NI, Cagle PT, Beasley MB, et al. Molecular testing guideline for selection of lung cancer patients for EGFR and ALK tyrosine kinase inhibitors: guideline from the College of American Pathologists, International Association for the Study of Lung Cancer, and Association for Molecular Pathology. Arch Pathol Lab Med 2013;137(6):828–860. 81. Kris MG, Johnson BE, Berry LD, et al. Using multiplexed assays of oncogenic drivers in lung cancers to select targeted drugs. JAMA 2014;311(19):1998–2006.

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82. Jordan EJ, Kim HR, Arcila ME, et al. Prospective comprehensive molecular characterization of lung adenocarcinomas for efficient patient matching to approved and emerging therapies. Cancer Discov 2017;7(6):596–609. 83. Romero R, Sayin VI, Davidson SM, et al. Keap1 loss promotes Kras-driven lung cancer and results in dependence on glutaminolysis. Nat Med 2017;23(11):1362–1368. 84. Kim J, Hu Z, Cai L, et al. CPS1 maintains pyrimidine pools and DNA synthesis in KRAS/LKB1-mutant lung cancer cells. Nature 2017;546(7656):168–172. 85. Chaudhuri AA, Chabon JJ, Lovejoy AF, et al. Early detection of molecular residual disease in localized lung cancer by circulating tumor DNA profiling. Cancer Discov 2017;7(12):1394–1403. 86. Church TR, Black WC, Aberle DR, et al. Results of initial low-dose computed tomographic screening for lung cancer. N Engl J Med 2013;368(21):1980–1991. 87. Ridker PM, MacFadyen JG, Thuren T, et al. Effect of interleukin-1β inhibition with canakinumab on incident lung cancer in patients with atherosclerosis: exploratory results from a randomised, double-blind, placebo-controlled trial. Lancet 2017;390(10105):1833–1842.

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48

Non–small-cell Lung Cancer Anne Chiang, Frank C. Detterbeck, Tyler Stewart, Roy H. Decker, and Lynn Tanoue

INTRODUCTION Major advances have been made in all aspects of lung cancer, from screening to surgical, chemotherapy, and radiotherapy (RT) treatment, to methods of palliation as well as the understanding of fundamental aspects of the biology of the disease. Lung cancer has become a vibrant and dynamic field, with a vast and growing literature describing advances in every facet of this disease. This makes it an impossible task to summarize the state of the art in one short chapter; it is inevitable that some areas will be missed or covered superficially, and new advances will have emerged during the course of publication. Nevertheless, this chapter is an attempt to cover the most important clinical aspects of lung cancer, which represents a major source of suffering and mortality throughout the world.

INCIDENCE AND ETIOLOGY Lung cancer is the most common cause of cancer death worldwide. The World Health Organization (WHO) International Agency for Research on Cancer (IARC) reported the global incidence of lung cancer at approximately 1.8 million new cases in 2012.1 The overall ratio of mortality to incidence is high, with the 5-year survival rate in the United States still only 18%.2 Consequently, the mortality burden is staggering, with lung cancer causing an estimated 1.59 million deaths per year around the world. Lung cancer accounts for nearly onethird of all cancer deaths in the United States, and accounts for almost as many cancer deaths as the next four leading causes of cancer deaths combined (breast, colon, prostate, and pancreas).2 A relatively unique aspect of lung cancer is the strong association with a potentially avoidable risk factor, namely smoking. This has far-reaching psychological, social, political, and societal implications. An attitude of blame has contributed to low prioritization of lung cancer research and a lack of activism among people affected by the disease. Furthermore, this attitude and the relatively poor outcomes have promoted nihilism in both the medical and patient community about both treatment of the disease and attempts to make advances. It is important to look beyond the simple association of lung cancer and smoking. Over half of those diagnosed with lung cancer in the United States are either never-smokers or people who quit smoking many years earlier.3–5 Furthermore, lung cancer occurring in never-smokers is relatively common, occurring in about 20,000 individuals in the United States; this puts deaths from lung cancer in never-smokers among the top 10 causes of cancer deaths in the United States (e.g., more than cancer of the ovaries, uterus, non-Hodgkin lymphoma, or brain cancer).2 This underscores that the etiology of lung cancer is complex and not well understood. The highest incidence and mortality rates from lung cancer are observed in men in Central and Eastern Europe, Southern Europe, Eastern Asia, Micronesia, and North America and in women in North America, Northern Europe, Australia/New Zealand, and Micronesia (Fig. 48.1).1 The highest estimated age-standardized lung cancer incidence rates occur in more developed regions of the world, where smoking is more prevalent (Fig. 48.2).6 Globally, lung cancer is still more common in men than in women, reflecting different historical and temporal exposure to tobacco smoking. The evidence does not suggest that women are either more or less susceptible than men to the carcinogenic effects of tobacco. On a hopeful note, the incidence rates in men appear to be falling or at least stabilizing in all regions, likely reflecting the impact of successful national initiatives focused on tobacco control (Fig. 48.3). In contrast, incidence rates in women appear to be increasing in most regions or at best stabilizing in a few.

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Smoking At the turn of the 20th century, lung cancer was a rare malignancy. In an extensive autopsy review in the United States and Western Europe in 1916, Adler found that lung cancers represented 1–2

T1c

Tumor >2 but ≤3 cm

T1c>2–3

T2

Tumor >3 but ≤5 cm or tumor involving:



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visceral pleura,b

T2Visc Pl b,c

main bronchus (not carina), atelectasis to hilum

T2Centr

T2a

Tumor >3 but ≤4 cm

T2a>3–4

T2b

Tumor >4 but ≤5 cm

T2b>4–5

Tumor >5 but ≤7 cm

T3>5–7

or invading chest wall, pericardium, phrenic nerve

T3Inv

or separate tumor nodule(s) in the same lobe

T3Satell

Tumor >7 cm

T4>7

or tumor invading mediastinum, diaphragm, heart, great vessels, recurrent laryngeal nerve, carina, trachea, esophagus, spine

T4Inv

or tumor nodule(s) in a different ipsilateral lobe

T4Ipsi Nod

T3

T4

N (Regional Lymph Nodes) N0

No regional node metastasis



N1

Metastasis in ipsilateral pulmonary or hilar nodes



N2

Metastasis in ipsilateral mediastinal/subcarinal nodes



N3

Metastasis in contralateral mediastinal/hilar, or supraclavicular nodes



M (Distant Metastasis) M0

No distant metastasis



M1a

Malignant pleural/pericardial effusiond or nodules

M1aPl



or separate tumor nodule(s) in a contralateral lobe

M1b

Single extrathoracic metastasis

M1bSingle

M1c

Multiple extrathoracic metastases (one or more organs)

M1cMulti

Dissem

M1aContr Nod

a

Superficial spreading tumor of any size but confined to the tracheal or bronchial wall. bSuch tumors are classified as T2a if ≤4 cm, T2b if >4 and ≤5 cm. cAtelectasis or obstructive pneumonitis extending to the hilum. dPleural effusions are excluded that are cytologically negative, nonbloody, transudative, and clinically judged not to be due to cancer. Reproduced with permission from the American College of Chest Physicians from Detterbeck FC, Boffa DJ, Kim AW, et al. The eighth edition lung cancer stage classification. Chest 2017;151(1):193–203.

The histologic classification of lung cancer has become much more nuanced. In the past, the major NSCLC histologic types (adenocarcinoma, squamous cell carcinoma, and large-cell carcinoma) were simply lumped together. Now, it is critical to differentiate these because they respond differently to certain chemotherapeutic agents. Immunohistochemical stains and genetic characterization can facilitate the distinction between subtypes.65,66 It is recognized that the vast majority of adenocarcinomas are mixed subtypes; these are now classified according to the predominant subtype with the percentage of each noted in 10% increments.66 Furthermore, the adenocarcinoma subtypes have been defined according to preinvasive, minimally invasive, and invasive groups (Table 48.2),66 reflecting the increasingly recognized spectrum of aggressiveness of lung cancers encountered in the Western world today. Finally, bronchopulmonary carcinoid and salivary gland tumors are less common types that are also included among lung cancers.67

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Figure 48.4 Stage classification: stage groups of lung cancer in the eighth edition of the TNM classification of malignant tumors. (Reproduced with permission from Detterbeck FC, Boffa DJ, Kim AW, et al. The eighth edition lung cancer stage classification. Chest 2017;151[1]:193–203.)

Genetic Characterization Lung cancer is a genetically heterogenous disease. A systematic characterization of genetic alterations in 1,255 patients with lung cancer revealed that most histologic types have a characteristic pattern of genetic alteration.65 Large-cell lung cancer is the exception, exhibiting alterations associated with each of the other major histologic types. Using genetic characterization, the majority of cases initially classified simply as large-cell lung cancer could be assigned to another histologic group (e.g., adenocarcinoma, squamous, small-cell), which was corroborated by prognostic and other similarities among genetically grouped cohorts.65 Classification by genetic alterations is thwarted by the complexity of these changes. NSCLC has a higher average number of somatic mutations than most cancers, although the range is quite large, with some tumors possessing few, and others containing a large amount.68,69 The genetic makeup is most notably different between smokers and nonsmokers, with tumors in smokers exhibiting a higher number of somatic mutations.70 Even within a single tumor, there is significant genetic heterogeneity, as demonstrated by a recent study that performed multiregional whole-exome sequencing of 100 surgically removed NSCLC specimens from patients with stage I to III NSCLC.71 This report elegantly describes intratumoral branched evolution, identifying multiple subclonal populations with new acquired driver mutations arising from the original clonal population, further emphasizing the complex and dynamic nature of tumor genetic alterations. These subclonal populations illustrate mechanisms for primary and acquired resistance, and highlight the inherent difficulties of cancer treatment.

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TABLE 48.2

IASLC/ATS/ERS Classification of Lung Adenocarcinoma in Resection Specimens Preinvasive Lesions Atypical adenomatous hyperplasia Adenocarcinoma in situ (≤3 cm formerly BAC) Nonmucinous Mucinous Mixed mucinous/nonmucinous Minimally Invasive Adenocarcinoma (≤3 cm Lepidic Predominant Tumor with >5 mm Invasion) Nonmucinous Mucinous Mixed mucinous/nonmucinous Invasive Adenocarcinoma Lepidic predominant (formerly nonmucinous BAC pattern, with >5 mm invasion) Acinar predominant Papillary predominant Micropapillary predominant Solid predominant with mucin production Variants of Invasive Adenocarcinoma Invasive mucinous adenocarcinoma (formerly mucinous BAC) Colloid Fetal (low and high grade) Enteric IASLC, International Association for the Study of Lung Cancer; ATS, American Thoracic Society; ERS, European Respiratory Society; BAC, bronchioloalveolar carcinoma. Reproduced with permission from Travis WD, Brambilla E, Noguchi M, et al. International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society international multidisciplinary classification of lung adenocarcinoma. J Thorac Oncol 2011;6(2):244–285.

Particular mutations have sparked a great deal of attention, primarily because they have led to dramatic therapeutic breakthroughs (Fig. 48.5).72,73 Many of these driver mutations provide sustained proliferation of signaling and dependence on that pathway, leading to “oncogene addiction.” Mutations in the epidermal growth factor receptor (EGFR) gene are the best known examples. Such driver mutations have received much attention because targeted treatment can yield dramatic disease responses; however, these targetable mutations are identified in a minority of patients, mostly non- or light-smokers. Not all driver mutations currently provide actionable targets. Beyond serving as predictors of targeted therapies, some driver mutations portend prognostic relevance. Mutations in KRAS, for instance, were associated with significantly worse clinical outcomes, even before the era of targeted agents.74 Acquired mutations, such as point mutations and gene amplifications, are major mechanisms for acquired resistance to systemic therapy.75 Although driver mutations such as EGFR are targetable, resistance to therapy inevitably develops. These acquired mutations may occur in the original driver oncogene or in downstream or alternative pathway genes,75 with multiple subclonal populations possibly harboring different mechanisms of resistance evolving in parallel within the same individual. Current research aims to understand and predict acquired resistance mechanisms and patterns to tailor and sequence therapy.

Prognostic Factors Prediction of prognosis is fervently desired but remains an elusive goal. Developing a system to do this is complex and must solve a number of inherent conflicts.62 Hence, the state of affairs is that we have identified a few factors that have prognostic value (at least in some clinical settings), but this knowledge is spotty and explains only a small amount of the actual observed outcomes.

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Figure 48.5 Oncogenic driver mutations in non–small-cell lung cancer. Frequency of driver mutations in lung adenocarcinoma. ALK, anaplastic lymphoma kinase; EGFR, epidermal growth factor receptor; MEK, mitogen-activated protein kinase kinase; NTRK, neurotrophic tyrosine kinase; HER2, human epidermal growth factor receptor 2. (Adapted from Hirsch FR, Suda K, Wiens J, et al. New and emerging targeted treatments in advanced non-small-cell lung cancer. Lancet 2016;388[10048]:1012–1024.) Prediction of prognosis is inherently complex.62,76 There are many factors that contribute; these can be grouped into environmental factors, tumor-related factors, and patient-related factors (Fig. 48.6).62 The prognosis is inherently linked to a specific clinical scenario and to the outcome of interest. The scenario includes treatmentrelated factors and timing (e.g., the prognostic significance of an EGFR mutation is different if the patient is to undergo treatment with an EGFR inhibitor, regular chemotherapy, or neither and different prior to treatment than upon developing resistance). There are inherent conflicts in prognostication.62,76,77 We derive our knowledge from studying a (large) cohort of patients, but we seek individualized prognostic prediction, tailored to a particular person. The ability to individualize is limited because we usually do not have sufficient detail about the group to assess how well an individual fits with the group. Furthermore, the prognosis of a group represents an average; usually, there is significant underlying variability of subgroups, limiting the applicability of the group prognosis to subgroups. Additionally, the more specific we get, the more limited the dataset available to derive the prediction becomes and thus the greater the uncertainty about the prediction. Finally, the data we base the prediction on is inherently based on past observation, yet the prediction is for the future, and thus cannot take into account new developments that inevitably occur. Prognostic prediction is inherently different than stage classification.77 Stage classification is a nomenclature to describe the anatomic extent of disease. It must remain relatively static and be used in a consistent uniform manner; the classification we assign to a particular extent of tumor today must be the same as what we assign to the same extent next week or next year; otherwise, it is a useless nomenclature. However, prognostication is inherently fluid and constantly changing as advances occur and the setting changes. Stage classification must be consistent and definitive, whereas prognostic prediction is inherently speculative, fluid, and uncertain. Identification of prognostic factors can be classified as phase I (exploring a potential association between a possible factor and a surrogate for outcome), phase II (exploring an association between a possible factor and outcomes), and phase III (confirmatory studies in well-defined patients demonstrating that a marker is associated with good or poor outcomes).78 Most studies of prognostic factors in lung cancer are phase I or II. Independent prognostic factors identified among surgically resected patients in the IASLC global 1990 to 1999 database

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included pathologic TNM, age, and gender; histologic cell type had some prognostic value but was linked to other variables.79 Identifying prognostic factors is different from using prognostic factors to build a model. Standards for a robust model or one that is appropriate for clinical application have been defined.62,80–82 At the basic level, the prognostic model should include all known prognostic factors in a sufficiently large dataset without a substantial amount of missing data.62,80 Prior to clinical application, the model must be validated in specific and broad settings (independent datasets). Confidently basing clinical decisions on a model requires an analysis of the impact (evaluation whether use of the model actually produces the anticipated outcomes). A recent assessment of prognostic models in lung cancer reveals that the quality of the 32 identified models was poor.83 Most were based on incomplete datasets and used flawed statistical methods (overestimating model performance); few had been subjected to external validation.83 The shortcomings and challenges are amplified when it comes to genomic factors.84,85 In sum, development of a prognostic model is complex, situation specific, and constantly changing. Although there is an intense desire for such a model, the appreciation of the issues involved is limited, and the sophistication and quality of existing studies is relatively rudimentary. Development of an overarching system that addresses the inherent challenges and leads to a robust clinically relevant prognostic prediction model is needed.

Figure 48.6 Prognostic prediction system. Schematic of a prognostic prediction system, taking into account environmental, patient-related, and tumor-related factors. The prediction must be specific to the clinical scenario and the outcome of interest. tmt, treatment; QOL, quality of life. (Reproduced with permission from Detterbeck FC, Boffa DJ, Kim AW, et al. The eighth edition lung cancer stage classification. Chest 2017;151[1]:193–203.)

SCREENING AND PREVENTION Prevention Tobacco Control

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The global epidemic of lung cancer is linked most strongly to population engagement in cigarette smoking. Although other modifiable risk factors (e.g., exposure to occupational or domestic carcinogens) are clearly identifiable, it is tobacco smoking that has driven the steep rises in lung cancer incidence and mortality witnessed over the last century in developed and developing nations. Primary prevention has the greatest overall potential to minimize lung cancer risk, and smoking cessation is still the most powerful intervention to diminish lung cancer risk in persons who smoke. Smoking cessation even into the seventh decade of life results in a decrease in lung cancer incidence, and it is never too late to quit.21,86 Although smoking rates have decreased dramatically since the publication of the first Surgeon General’s report on the health consequences of smoking in 1964, approximately 20% of adult Americans still habitually smoke, with a wide range of smoking rates (10% to 28%) observed across the United States.87 Important public health interventions have included stricter control of tobacco products by government regulatory agencies; limitations on cigarette advertising, particularly those geared toward children; the use of text and graphic warnings on cigarette packaging; limitations of tobacco smoking in indoor workplaces and restaurants; and global initiatives to inform the public of the health hazards of smoking.88–91

Smoking Cessation There are many physiologic and psychologic factors that contribute to make smoking a difficult addiction to overcome. However, there have been major advances in understanding these, and solid scientific data regarding which interventions work best and in which individuals. Nicotine acts in an area of the brain associated with a sense of “safety” and “survival functions.”92 This appears to explain the paradox of difficulty in giving up smoking even when faced with a life-threatening disease that is a consequence of smoking. This struggle and the illogical nature of it, combined with the stigmatism associated with smoking, lead to feelings of shame, helplessness, and depression that further aggravate the problem.92 It is easy to succumb to a fatalistic defense that “it is too late anyhow.” However, data clearly shows that patients with lung cancer who continue to smoke approximately double their risk of dying.92 Quitting smoking is associated with better response to treatment, better quality of life (QOL), better long-term survival, and a lower risk of second primary cancers.92–95 Furthermore, data shows that a diagnosis of lung cancer represents a particularly opportune moment to intervene.92 Smoking cessation intervention should be included in the health care of any individual smoking cigarettes. It is important to use a sophisticated, evidence-based approach and an organized smoking cessation program to achieve the best results.92 A simple recommendation to stop smoking or provision of self-help materials is largely ineffective, but as little as 3 minutes of counseling by clinicians can significantly increase cessation rates.96 Several points are important. Tobacco dependence is best managed in a chronic disease model with repeated intervention over time. Intensive behavioral therapy and counseling (e.g., weekly) is of significant benefit in several randomized controlled trials (RCTs). In addition, seven first-line medications reliably increase long-term smoking abstinence rates (bupropion, varenicline, nicotine patch, gum, lozenges, inhaler, and nasal spray).92 These increase effectiveness two- to threefold and result in abstinence rates of approximately 25%. Often, combinations of these may be more effective than a single intervention. These medications have been shown to be safe in most patients, including those who are about to undergo either surgery, RT, or chemotherapy. It is best to initiate the cessation interventions at the outset. Specifically, it is safe (and beneficial) for patients to stop smoking even a short time (e.g., 1 to 2 weeks) before undergoing surgery; pharmacologic interventions are safe to continue in the perioperative period as well.92 A well-organized thoracic oncology program, therefore, should include an evidence-based smoking cessation program that is fully integrated with the diagnostic and treatment components of patient care.

Chemoprevention The concept of chemoprevention is based on the data that most lung cancer is the end result of a multistep accumulation of carcinogen-driven genetic and epigenetic changes. In theory, chemical agents might prevent these changes by a variety of proposed mechanisms, such as counteracting oxidative stress, blocking inflammation, and modifying pathways that influence cell growth and behavior. Epidemiologic and animal studies have suggested that derivatives of the antioxidant vitamins A and E might be protective against lung cancer. However, large clinical trials of α-tocopherol and β-carotene in subjects at risk of developing lung cancer failed to demonstrate any benefit, and two studies suggested that β-carotene was actually associated with an increased incidence of lung cancer as well as cardiovascular disease.97–100 To date, no chemopreventative intervention has been demonstrated to be of benefit for lung cancer. The focus has shifted from large RCTs to studies to better define the underlying

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biology and appropriate surrogate end points.101

Screening At present, the majority of lung cancer patients have advanced disease at the time of diagnosis. This preponderance of advanced disease, where prognosis is poor even with treatment, is a major contributor to the dismal 5-year overall survival (OS) rate of 18%; this contrasts starkly with breast, colon, and prostate cancers, the next three leading causes of cancer death, whose 5-year survival rates over the past several decades have increased to 90%, 65%, and nearly 100%, respectively.2 These improved survival rates are arguably attributable at least in part to early detection resulting from widely available and broadly accepted, albeit still controversial, screening interventions. An effective screening tool for early detection of lung cancer has been an elusive goal for decades. Several large RCTs performed during the 1960s and 1970s evaluating lung cancer screening with chest radiography with or without sputum analysis at varying time intervals failed to demonstrate any mortality benefit,102–106 and a Cochrane meta-analysis107 concluded that there was no evidence to support the use of chest radiography or sputum cytology as a lung cancer screening modality. More recently, chest radiography was reexamined as a lung cancer screening tool in the Prostate, Lung, Colorectal and Ovarian (PLCO) trial, which enrolled 154,901 participants aged 55 to 74 years from 1993 to 2001.108 No difference in lung cancer mortality was seen between those randomized to screening with annual chest radiography versus no screening, regardless of the degree of smoking. Together, these studies clearly demonstrate that there is no mortality benefit associated with serial chest radiography as a screening tool. In the 1990s, intense interest was generated by the results of a number of observational studies evaluating lowdose chest tomography (LDCT) as a lung cancer screening modality. Eventually, a number of RCTs were performed in various sites around the world. The largest of these was the National Lung Screening Trial (NLST), which included 53,454 subjects, ages 55 to 74 years with at least 30 pack-years of cigarette smoking, who were either currently smoking or had quit smoking within the prior 15 years.109 NLST subjects underwent three rounds of annual screening, randomized to either chest radiograph or LDCT. Approximately 1% of subjects had lung cancer over the duration of the trials. At a median follow-up of 6.5 years, there was a 20% relative reduction in lung cancer mortality observed in the LDCT arm (Fig. 48.7).109 None of the other RCTs evaluating lung cancer screening with LDCT is of the scale of the NLST, which affects their ability to identify any mortality benefit. In the smaller trials in which the data has become available, the mortality benefit has been nonsignificant and without a trend toward a benefit.110–112 The subjects in all of these studies had smoked and were of middle to older age. A multisociety systematic review of lung cancer screening with LDCT analyzed the evidence from 8 RCTs and 13 prospective cohort studies.113 This review found a composite significant benefit for LSCT screening, with few ensuing harms, when LDCT screening was conducted in the setting of an organized, structured program. Consistent with this, many organizations (American College of Chest Physicians [ACCP], American Cancer Society, Society of Thoracic Surgeons, American Association of Thoracic Surgery, National Comprehensive Cancer Network [NCCN], U.S. Preventative Services Task Force [USPSTF]) have recommended that healthy smokers or former smokers (quit 95%).133 The main factors that contribute to this are the risk factors for development of lung cancer (e.g., age, smoking history, family history, presence of significant COPD), the clinical presentation, and the radiographic appearance of the lesion on CT (e.g., spiculated, upper lobe, node enlargement). If needed, algorithms are available that can predict the likelihood of lung cancer,131,134–138 but the judgment of experienced clinicians is just as good.135 If the probability of lung cancer is high (e.g., >80%), it is generally more efficient to proceed with evaluation of the stage than confirmation of the diagnosis.133,139,140 Frequently, this will identify a necessary procedure that will serve to confirm both the stage and the diagnosis. For example, biopsy of a potential solitary metastasis or of a suspicious mediastinal node can confirm both the stage and diagnosis. Those situations that require tissue confirmation of the stage are discussed in the next section. In other situations, the stage is reliably defined by imaging alone; in this case, confirmation of the diagnosis is achieved from whatever site is easiest. Nevertheless, establishing a presumptive clinical stage is an important step that defines how best to proceed to confirm the diagnosis. There are also situations in which the reliability of the clinical diagnosis is less certain; this occurs most frequently in the case of a localized, solitary pulmonary nodule (SPN). An SPN is defined as a solitary lesion