Chemosensitivity: Volume I: In Vitro Assays (Methods in Molecular Medicine)

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M E T H O D S I N M O L E C U L A R M E D I C I N E TM

Chemosensitivity Volume 1 In Vitro Assays Edited by

Rosalyn D. Blumenthal

Chemosensitivity

M E T H O D S I N M O L E C U L A R M E D I C I N E™

John M. Walker, SERIES EDITOR 118. Antifungal Agents: Methods and Protocols, edited by Erika J. Ernst and P. David Rogers, 2005 117. Fibrosis Research: Methods and Protocols, edited by John Varga, David A. Brenner, and Sem H. Phan, 2005 116. Inteferon Methods and Protocols, edited by Daniel J. J. Carr, 2005 115. Lymphoma: Methods and Protocols, edited by Timothy Illidge and Peter W. M. Johnson, 2005 114. Microarrays in Clinical Diagnostics, edited by Thomas Joos and Paolo Fortina, 2005 113. Multiple Myeloma: Methods and Protocols, edited by Ross D. Brown and P. Joy Ho, 2005 112. Molecular Cardiology: Methods and Protocols, edited by Zhongjie Sun, 2005 111. Chemosensitivity: Volume 2, In Vivo Models, Imaging, and Molecular Regulators, edited by Rosalyn D. Blumethal, 2005 110. Chemosensitivity: Volume 1, In Vitro Assays, edited by Rosalyn D. Blumethal, 2005 109. Adoptive Immunotherapy: Methods and Protocols, edited by Burkhard Ludewig and Matthias W. Hoffman, 2005 108. Hypertension: Methods and Protocols, edited by Jérôme P. Fennell and Andrew H. Baker, 2005 107. Human Cell Culture Protocols, Second Edition, edited by Joanna Picot, 2005 106. Antisense Therapeutics, Second Edition, edited by M. Ian Phillips, 2005 105. Developmental Hematopoiesis: Methods and Protocols, edited by Margaret H. Baron, 2005 104. Stroke Genomics: Methods and Reviews, edited by Simon J. Read and David Virley, 2004 103. Pancreatic Cancer: Methods and Protocols, edited by Gloria H. Su, 2004 102. Autoimmunity: Methods and Protocols, edited by Andras Perl, 2004 101. Cartilage and Osteoarthritis: Volume 2, Structure and In Vivo Analysis, edited by Frédéric De Ceuninck, Massimo Sabatini, and Philippe Pastoureau, 2004 100. Cartilage and Osteoarthritis: Volume 1, Cellular and Molecular Tools, edited by Massimo Sabatini, Philippe Pastoureau, and Frédéric De Ceuninck, 2004

99. Pain Research: Methods and Protocols, edited by David Z. Luo, 2004 98. Tumor Necrosis Factor: Methods and Protocols, edited by Angelo Corti and Pietro Ghezzi, 2004 97. Molecular Diagnosis of Cancer: Methods and Protocols, Second Edition, edited by Joseph E. Roulston and John M. S. Bartlett, 2004 96. Hepatitis B and D Protocols: Volume 2, Immunology, Model Systems, and Clinical Studies, edited by Robert K. Hamatake and Johnson Y. N. Lau, 2004 95. Hepatitis B and D Protocols: Volume 1, Detection, Genotypes, and Characterization, edited by Robert K. Hamatake and Johnson Y. N. Lau, 2004 94. Molecular Diagnosis of Infectious Diseases, Second Edition, edited by Jochen Decker and Udo Reischl, 2004 93. Anticoagulants, Antiplatelets, and Thrombolytics, edited by Shaker A. Mousa, 2004 92. Molecular Diagnosis of Genetic Diseases, Second Edition, edited by Rob Elles and Roger Mountford, 2004 91. Pediatric Hematology: Methods and Protocols, edited by Nicholas J. Goulden and Colin G. Steward, 2003 90. Suicide Gene Therapy: Methods and Reviews, edited by Caroline J. Springer, 2004 89. The Blood–Brain Barrier: Biology and Research Protocols, edited by Sukriti Nag, 2003 88. Cancer Cell Culture: Methods and Protocols, edited by Simon P. Langdon, 2003 87. Vaccine Protocols, Second Edition, edited by Andrew Robinson, Michael J. Hudson, and Martin P. Cranage, 2003 86. Renal Disease: Techniques and Protocols, edited by Michael S. Goligorsky, 2003 85. Novel Anticancer Drug Protocols, edited by John K. Buolamwini and Alex A. Adjei, 2003 84. Opioid Research: Methods and Protocols, edited by Zhizhong Z. Pan, 2003 83. Diabetes Mellitus: Methods and Protocols, edited by Sabire Özcan, 2003 82. Hemoglobin Disorders: Molecular Methods and Protocols, edited by Ronald L. Nagel, 2003

M E T H O D S I N M O L E C U L A R M E D I C I N E™

Chemosensitivity Volume 1 In Vitro Assays

Edited by

Rosalyn D. Blumenthal Garden State Cancer Center, Belleville, NJ

© 2005 Humana Press Inc. 999 Riverview Drive, Suite 208 Totowa, New Jersey 07512 www.humanapress.com All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, microfilming, recording, or otherwise without written permission from the Publisher. Methods in Molecular Medicine™ is a trademark of The Humana Press Inc. The content and opinions expressed in this book are the sole work of the authors and editors, who have warranted due diligence in the creation and issuance of their work. The publisher, editors, and authors are not responsible for errors or omissions or for any consequences arising from the information or opinions presented in this book and make no warranty, express or implied, with respect to its contents. This publication is printed on acid-free paper. ∞ ANSI Z39.48-1984 (American Standards Institute) Permanence of Paper for Printed Library Materials. Cover illustrations: Foreground illustration: Figure 3, from Chapter 10, “Chemosensitivity Testing Using MicroplateAdenosine Triphosphate–Based Luminescence Measurements,” by Christian M. Kurbacher and Ian A. Cree. Background illustration: Figure 4, from Chapter 22 (Volume 2), “Assessing Growth and Response to Therapy in Murine Tumor Models,” by C. P. Reynolds et al. Cover design by Patricia F. Cleary. For additional copies, pricing for bulk purchases, and/or information about other Humana titles, contact Humana at the above address or at any of the following numbers: Tel.: 973-256-1699; Fax: 973-256-8341; E-mail: [email protected]; or visit our Website: www.humanapress.com Photocopy Authorization Policy: Authorization to photocopy items for internal or personal use, or the internal or personal use of specific clients, is granted by Humana Press Inc., provided that the base fee of US $30.00 per copy is paid directly to the Copyright Clearance Center at 222 Rosewood Drive, Danvers, MA 01923. For those organizations that have been granted a photocopy license from the CCC, a separate system of payment has been arranged and is acceptable to Humana Press Inc. The fee code for users of the Transactional Reporting Service is: [1-58829-345-9/05 $30.00]. Printed in the United States of America. 10 9 8 7 6 5 4 3 2 1 E-ISBN 1-59259-869-2 Library of Congress Cataloging in Publication Data Chemosensitivity / edited by Rosalyn D. Blumenthal. v. ; cm. — (Methods in molecular medicine ; 110-111) Includes bibliographical references and index. Contents: v. 1. In vitro assays — v. 2 In vivo models, imaging, and molecular regulators. ISBN 1-58829-345-9 (hardcover : alk. paper) 1. Cancer—Chemotherapy—Laboratory manuals. 2. Antineoplastic agents—Effectiveness—Laboratory manuals. 3. Cancer cells—Laboratory manuals. 4. Cancer--Molecular aspects—Laboratory manuals. [DNLM: 1. Antineoplastic Agents—pharmacology. 2. Drug Screening Assays, Antitumor—methods. 3. Drug Resistance, Neoplasm. 4. Models, Animal. 5. Neoplasms—drug therapy. QV 269 C5177 2005] I. Blumenthal, Rosalyn D. II. Series. RC271.C5C396 2005 616.99’4061—dc22

2004012494

Preface Chemotherapy is used to treat many types of cancer. A large number of drug classes are in use, including the vinca alkaloids, taxanes, antibiotics, anthracyclines, DNA alkylators, other DNA damaging agents, hormones, and interferons. More potent analogs of existing drugs and novel agents directed at new targets are continuously being developed. Over the last few years, agents that affect COX-2, PPARγ, and various signal transduction pathways have received much attention. To identify which agents are effective for which types of tumors, it is important to develop accurate in vitro and preclinical in vivo screening systems that can identify the cytotoxic and/or cytostatic potential of an agent on established tumor cell lines or cells isolated from individual fresh cancer biopsy specimens removed from cancer patients. Chemosensitivity testing allows the selection of drugs that appear sensitive in the laboratory, thus offering patients a better chance of response. One of the main problems associated with chemotherapy has been that patient tumors with the same histology do not necessarily respond identically to the same agent or dose schedule of multiple agents. Identifying the presence of resistance mechanisms and other determinants for drug sensitivity in order to classify tumors into response categories has been an ongoing research effort. Advances in our understanding of the genetic and protein fingerprints of primary tumors and their metastases has opened a door to the possibility of customizing therapy to individuals. There is accumulating evidence suggesting that laboratory screening of samples from a patient’s tumor may help select the appropriate treatment(s) to administer, thereby avoiding ineffective drugs, and sparing patients the side effects normally associated with these agents. The aim of these two volumes on Chemosensitivity of the Methods in Molecular Medicine series, is to comprehensively present protocols that can be used to (a) assess chemosensitivity in vitro and in vivo, and (b) assess parameters that modulate chemosensitivity in individual tumors. Volume I presents an overview in Chapter 1 and then covers In Vitro Measures of Chemosensitivity, includes clonogenic, colorimetric, fluorometric, and histochemical approaches. Volume II, Part I, Measurements of DNA Damage, Cell Death, and Regulators of Cytotoxicity, includes methods to detect chromosome loss and breakage, changes in cell cycle, expression of members of the bcl-2 family of proteins, expression of caspases and PARP cleavage, metabolic factors influencing sensitivity, measurements of drug retention, expression of drug resistance proteins, and measurements of ceramide and sphingolipids associated with drug sensitivity. Volume

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II, Part II, Genomics, Proteomics, and Chemosensitivity, addresses DNA microarrays for gene profiling, genetic manipulation to identify genes regulating chemosensitivity, proteomics using 2D-PAGE and mass spectrometry, and bioinformatics approaches. The last part, In Vivo Animal Modeling of Chemosensitivity, covers protocols to establish clinically meaningful metastatic and orthotropic models of solid and liquid tumors, statistical approaches to analyze preclinical data, and animal imaging approaches that can be used to assess chemosensitivity such as GFP-tagged genes, SPECT using 99mTc-annexin, PET imaging with 18FDG, and magnetic resonance imaging. Each chapter is written by someone experienced with the methodology and contains a detailed introductory section with references of how the technique has been used in the past, a list of materials and equipment needed to perform the assay, and a step-by-step set of instructions for each method. At the end of each chapter a “Notes” section is included with useful information, helpful hints, and problems and pitfalls to be aware of, in order to make the assay run smoothly and allow for easy interpretation of data.

Rosalyn D. Blumenthal

Contents Preface .............................................................................................................. v Contributors ..................................................................................................... ix Contents of Volume 2 ...................................................................................... xi

PART I. OVERVIEW 1 An Overview of Chemosensitivity Testing Rosalyn D. Blumenthal ......................................................................... 3

PART II. IN VITRO MEASURES

OF

CHEMOSENSITIVITY

2 Clonogenic Cell Survival Assay Anupama Munshi, Marvette Hobbs, and Raymond E. Meyn .............. 21 3 High-Sensitivity Cytotoxicity Assays for Nonadherent Cells M. Jules Mattes ................................................................................... 29 4 Sulforhodamine B Assay and Chemosensitivity Wieland Voight ................................................................................... 39 5 Use of the Differential Staining Cytotoxicity Assay to Predict Chemosensitivity Gertjan J. L. Kaspers ........................................................................... 49 6 Collagen Gel Droplet Culture Method to Examine In Vitro Chemosensitivity Hisayuki Kobayashi ............................................................................. 59 7 The MTT Assay to Evaluate Chemosensitivity Jack D. Burton .................................................................................... 69 8 Histoculture Drug Response Assay to Monitor Chemoresponse Shinji Ohie, Yasuhiro Udagawa, Daisuke Aoki, and Shiro Nozawa .......................................................................... 79 9 In Vitro Testing of Chemosensitivity in Physiological Hypoxia Rita Grigoryan, Nino Keshelava, Clarke Anderson, and C. Patrick Reynolds .................................................................. 87 10 Chemosensitivity Testing Using Microplate Adenosine Triphosphate–Based Luminescence Measurements Christian M. Kurbacher and Ian A. Cree .......................................... 101 11 High-Throughput Technology: Green Fluorescent Protein to Monitor Cell Death Marylène Fortin, Ann-Muriel Steff, and Patrice Hugo ..................... 121

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12 DIMSCAN: A Microcomputer Fluorescence-Based Cytotoxicity Assay for Preclinical Testing of Combination Chemotherapy Nino Keshelava, Tomásˇ Frgala, Jir˘ í Krejsa, Ondrej Kalous, and C. Patrick Reynolds ................................................................ 139 13 The ChemoFx® Assay: An Ex Vivo Cell Culture Assay for Predicting Anticancer Drug Responses Robert L. Ochs, Dennis Burholt, and Paul Kornblith ....................... 155 14 Evaluating Response to Antineoplastic Drug Combinations in Tissue Culture Models C. Patrick Reynolds and Barry J. Maurer .......................................... 173 15 Image Analysis Using the Fluochromasia Assay to Quantify Tumor Drug Sensitivity John F. Gibbs, Youcef M. Rustum, and Harry K. Slocum ................. 185 16 Immunohistochemical Detection of Ornithine Decarboxylase as a Measure of Chemosensitivity Uriel Bachrach .................................................................................. 197 17 Immunohistochemistry of p53, Bcl-2 and Ki-67 as Predictors of Chemosensitivity Mitsuyoshi Itaya, Jiro Yoshimoto, Kuniaki Kojima, and Seiji Kawasaki ........................................................................ 213 Index ............................................................................................................ 229

Contributors CLARKE ANDERSON • Division Hematology-Oncology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA DAISUKE AOKI • Department of Obstetrics-Gynecology, Keio University School of Medicine, Keio, Japan URIEL BACHRACH • Department of Molecular Biology, Hebrew University– Hadassah Medical School, Jerusalem, Israel ROSALYN D. BLUMENTHAL • Garden State Cancer Center, Belleville, NJ, USA DENNIS BURHOLT • Precision Therapeutics, Pittsburgh, PA, USA JACK D. BURTON • Garden State Cancer Center, Belleville, NJ, USA IAN A. CREE • Department of Histopathology, Queen Alexandria Hospital, Portsmouth, UK MARYLENE FORTIN • Topigen Pharmaceuticals, Montreal, Quebec, Canada TOMÁSˇ FRGALA • USC-CHLA Institute for Pediatric Clinical Research, University of Southern California and Childrens Hospital Los Angeles, Los Angeles, CA, USA JOHN F. GIBBS • Department of Surgical Oncology, Roswell Park Cancer Institute, Buffalo, NY, USA RITA GRIGORYAN • Developmental Therapeutics Section, Children’s Hospital of Los Angeles, Los Angeles, CA, USA MARVETTE HOBBS • Department of Experimental Radiology, University of Texas M.D. Anderson Cancer Center, Houston, TX, USA PATRICE HUGO • Caprion Pharmaceuticals Inc., Saint Laurent, QC, Canada MITSUYOSHI ITAYA • Department of Hepato-Biliary-Pancreatic Surgery, Juntendo University, Tokyo, Japan ONDREJ KALOUS • USC-CHLA Institute for Pediatric Clinical Research, University of Southern California and Childrens Hospital Los Angeles, Los Angeles, CA, USA GERTJAN J. L. KASPERS • Department of Pediatric Hematology Oncology, VU University Medical Center, Amsterdam, Netherlands SEIJI KAWASAKI • Department of Hepato-Biliary-Pancreatic Surgery, Juntendo University, Tokyo, Japan NINO KESHELAVA • USC-CHLA Institute for Pediatric Clinical Research, University of Southern California and Childrens Hospital Los Angeles, Los Angeles, CA, USA HISAYUKI KOBAYASHI • Biochemical Laboratory, Nitta Gelatin Inc., Futamata, Yao-City, Japan

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KUNIAKI KOJIMA • Department of Breast and Endocrine Surgery, Juntendo University, Tokyo, Japan PAUL KORNBLITH • Precision Therapeutics, Pittsburgh, PA, USA JIR˘ Í KREJSA • USC-CHLA Institute for Pediatric Clinical Research, University of Southern California and Childrens Hospital Los Angeles, Los Angeles, CA, USA CHRISTIAN M. KURBACHER • Department of Gynecology & Obstetrics, University of Cologne, Cologne, Germany M. JULES MATTES • Center for Molecular Medicine and Immunology, Belleville, NJ, USA BARRY J. MAURER • USC-CHLA Institute for Pediatric Clinical Research, University of Southern California and Childrens Hospital Los Angeles, Los Angeles, CA, USA RAYMOND E. MEYN • Department of Experimental Radiology, University of Texas M.D. Anderson Cancer Center, Houston, TX, USA ANUPAMA MUNSHI • Department of Experimental Radiology, University of Texas M.D. Anderson Cancer Center, Houston, TX, USA SHIRO NOZAWA • Department of Obstetrics-Gynecology, Keio University School of Medicine, Keio, Japan ROBERT L. OCHS • Precision Therapeutics, Pittsburgh, PA, USA SHINJI OHIE • Cancer Research Laboratory, Hanno Research Center, Taiho Pharmaceutical Co., Saitama, Japan C. PATRICK REYNOLDS • USC-CHLA Institute for Pediatric Clinical Research, University of Southern California and Childrens Hospital Los Angeles, Los Angeles, CA, USA YOUCEF M. RUSTUM • Department of Experimental Therapeutics, Roswell Park Cancer Institute, Buffalo, NY, USA HARRY K. SLOCUM • Department of Experimental Therapeutics, Roswell Park Cancer Institute, Buffalo, NY, USA ANN-MURIEL STEFF • World Anti-Doping Agency, Montreal, Quebec, Canada YASUHIRO UDAGAWA • Department of Obstetrics-Gynecology, Fujita Health University School of Medicine, Japan WIELAND VOIGHT • Klinik für Innere Medizin IV–Martin Luther Universität Halle, Halle/Saale, Germany JIRO YOSHIMOTO • Department of Hepato-Biliary-Pancreatic Surgery, Juntendo University, Tokyo, Japan

Contents of Volume 2 Preface .............................................................................................................. v Color Plate ....................................................................................................... xi Contributors .................................................................................................. xiii Contents of Volume 1 ................................................................................... xvii

PART I. MEASUREMENTS OF DNA DAMAGE, CELL DEATH, AND REGULATORS OF CYTOTOXICITY 1 In Vitro Micronucleus Technique to Predict Chemosensitivity Michael Fenech ..................................................................................... 3 2 Cell Cycle and Drug Sensitivity Aslamuzzaman Kazi and Q. Ping Dou ................................................ 33 3 TUNEL Assay as a Measure of Chemotherapy-Induced Apoptosis Robert Wieder ..................................................................................... 43 4 Apoptosis Assessment by the DNA Diffusion Assay Narendra P. Singh ............................................................................... 55 5 PARP Cleavage and Caspase Activity to Assess Chemosensitivity Alok C. Bharti, Yasunari Takada, and Bharat B. Aggarwal ................ 69 6 Diphenylamine Assay of DNA Fragmentation for Chemosensitivity Testing Cicek Gercel-Taylor ............................................................................ 79 7 Immunodetecting Members of the Bcl-2 Family of Proteins Richard B. Lock and Kathleen M. Murphy.......................................... 83 8 Correlation of Telomerase Activity and Telomere Length to Chemosensitivity Yasuhiko Kiyozuka .............................................................................. 97 9 Application of Silicon Sensor Technologies to Tumor Tissue In Vitro: Detection of Metabolic Correlates of Chemosensitivity Pedro Mestres-Ventura, Andrea Morguet, Anette Schofer, Michael Laue, and Werner Schmidt ............................................. 109 10 Overview of Tumor Cell Chemoresistance Mechanisms Laura Gatti and Franco Zunino ........................................................ 127 11 Flow Cytometric Monitoring of Fluorescent Drug Retention and Efflux Awtar Krishan and Ronald M. Hamelik ............................................ 149

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12 Flow Cytometric Measurement of Functional and Phenotypic P-Glycoprotein Monica Pallis and Emma Das-Gupta ................................................ 167 13 Measurement of Ceramide and Sphingolipid Metabolism in Tumors: Potential Modulation of Chemosensitivity David E. Modrak ............................................................................... 183

PART II. GENOMICS, PROTEOMICS,

AND

CHEMOSENSITIVITY

14 Gene Expression Profiling to Characterize Anticancer Drug Sensitivity James K. Breaux and Gerrit Los ........................................................ 15 Identifying Genes Related to Chemosensitivity Using Support Vector Machine Lei Bao .............................................................................................. 16 Genetic Manipulation of Yeast to Identify Genes Involved in Regulation of Chemosensitivity Giovanni L. Beretta and Paola Perego .............................................. 17 Real-Time RT-PCR (Taqman®) of Tumor mRNA to Predict Sensitivity of Specimens to 5-Fluorouracil Tetsuro Kubota .................................................................................. 18 Use of Proteomics to Study Chemosensitivity Julia Poland, Silke Wandschneider, Andrea Urbani, Sergio Bernardini, Giorgio Federici, and Pranav Sinha ...............

PART III. IN VIVO ANIMAL MODELING

OF

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241

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19 Clinically Relevant Metastatic Breast Cancer Models to Study Chemosensitivity Lee Su Kim and Janet E. Price ........................................................... 20 Orthotopic Metastatic (MetaMouse®) Models for Discovery and Development of Novel Chemotherapy Robert M. Hoffman ........................................................................... 21 Preclinical Testing of Antileukemic Drugs Using an In Vivo Model of Systemic Disease Richard B. Lock, Natalia L. Liem, and Rachael A. Papa ................... 22 Assessing Growth and Response to Therapy in Murine Tumor Models C. Patrick Reynolds, Bee-Chun Sun, Yves A. DeClerck, and Rex A. Moats ..........................................................................

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Contents of Vol. 2

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23 Evaluation of Chemosensitivity of Micrometastatses with Green Fluorescent Protein Gene-Tagged Tumor Models in Mice Hayao Nakanishi, Seiji Ito, Yoshinari Mochizuki, and Masae Tatematsu ................................................................... 351 99m 24 Tc-Annexin A5 Uptake and Imaging to Monitor Chemosensitivity Tarik Z. Belhocine and Francis G. Blankenberg ............................... 363 25 Magnetic Resonance Imaging of Tumor Response to Chemotherapy Richard Mazurchuk and Joseph A. Spernyak ................................... 381 26 Metabolic Monitoring of Chemosensitivity with 18FDG PET Guy Jerusalem and Tarik Z. Belhocine ............................................. 417 Index ............................................................................................................ 441

I OVERVIEW

1 An Overview of Chemosensitivity Testing Rosalyn D. Blumenthal Summary This overview chapter presents the importance of chemosensitivity testing for screening new therapeutic agents, identifying patterns of chemosensitivity for different types of tumors, establishing patterns of cross-resistance and sensitivity in treatment naive and relapsing tumors; identifying genomic and proteomic profiles associated with sensitivity; correlating in vitro response, preclinical in vivo effect, and clinical outcome associated with a particular therapeutic agent, and tailoring chemotherapy regimens to individual patients. Various assays are available to achieve these end points, including several in vitro clonogenic and proliferation assays, cell metabolic activity assays, molecular assays to monitor expression of markers for responsiveness, development of drug resistance and induction of apoptosis, in vivo tumor growth and survival assays in metastatic and orthotopic models, and in vivo imaging assays. The advantages and disadvantages of the specific assays are discussed. A summary of research areas related to chemosensitivity testing is also included.

Key Words Dose-response curve; IC50 values; imaging; metabolic assays; molecular markers; proliferation assays.

1. Introduction Chemosensitivity testing is an ex vivo means of determining the cytotoxic and/or cytostatic, or apoptosis-inducing effect of anticancer drugs. The emphasis on screening new agents derived from synthetic compound archives, and from pure natural products and their extracts, for antitumor activity necessitates in vitro evaluation in cell culture and then in vivo in appropriate tumorbearing animal models. If the agent appears effective in this system, then the drug may be further evaluated in clinical trials. This paradigm seeks to identify the single best treatment to administer to the average patient with a given form of cancer through the use of prospective, randomized trials. From: Methods in Molecular Medicine, vol. 110: Chemosensitivity: Vol. 1: In Vitro Assays Edited by: R. D. Blumenthal © Humana Press Inc., Totowa, NJ

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In addition to the standard, DNA-damaging and metabolic inhibiting agents in use, many new target classes now exist, such as kinase and nonkinase enzymes, transcriptional regulators, growth factor receptors, chemokines, angiogenic regulators, and protein–protein interactions. Identifying which types of tumors (e.g., breast, lung, pancreas) and which subtypes (e.g., based on morphology, differentiation status, growth rate, drug resistance status, p53 expression) within each tumor category will respond to each new agent is essential. Experience has shown that individual patients with a similar tumor histology do not necessarily respond identically to a given agent or set of agents. Defining the best treatment options, combinations, and schedules using standard agents alone or combined with new agents for an individual patient is an area of active investigation that requires both in vitro and in vivo testing. Chemosensitivity assays can potentially facilitate the individualization of patient treatment plans. Many retrospective and prospective studies for leukemia and for solid tumors have shown that drug resistance/sensitivity can be determined accurately by in vitro drug-response assays. As a consequence, knowing the drug sensitivity of a given tumor for a particular agent can significantly impact decision making and treatment planning. By identifying inactive drugs, patients can be spared “standard chemotherapy” regimens and their associated toxicities. In cases in which the patient’s tumor is unresponsive to chemotherapy, the oncologist may be able to offer alternative or experimental treatments much sooner, when they may have a better chance of succeeding. Cell culture drug resistance testing refers to testing the resistance of a patient’s own cancer cells in the laboratory to drugs that may be used to treat the patient’s cancer (1). Table 1 summarizes the potential value of predictive chemosensitivity assays. When addressing the usefulness of an assay method, several questions must be addressed: (1) Are the drug sensitivity patterns observed in vitro with tumors of a particular histological type similar to those observed clinically for the same tumor type? (2) Can chemotherapy, which is selected on the basis of in vitro studies, improve patient survival? Efforts have been made to correlate in vitro drug sensitivity at initial diagnosis with 4-yr survival results, or in vitro resistance and early relapse. If this can be achieved, it may allow one to select more intensive regimens. (3) Do the results obtained in vitro predict those obtained in vivo? Since the process of tumor resection, transport, and processing for culture (mechanical or enzymatic disaggregation) introduces tissue stress and damage, which can perturb cell function and potentiate drug sensitivity, obtaining good correlations can be problematic. Another important consideration is that tumor cell growth rate in vitro is likely to be much faster than in vivo. Therefore, the in vitro assay might indicate chemosensitivity in a situation of rapid cell division, which may be a false positive result, when attempting to translate results in vivo. Test systems using single-cell suspensions may

Chemosensitivity Testing

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Table 1 Summary of Potential Value of Chemosensitivity Assays Conducting an initial screening of new therapeutic agents Tailoring chemotherapy regimens to the individual patient: determining tumors that are likely to respond to a particular agent and eliminating ineffective drugs Identifying patterns of chemosensitivity for different types and subtypes of tumors Establishing patterns of cross-resistance and sensitivity in treatment-naive and in relapsing patients Identifying genomic and proteomic profiles associated with sensitivity Correlating in vitro, preclinical in vivo, and clinical response to a therapeutic agent

overestimate sensitivity. Finally, the ability to shrink tumors in vivo with a given treatment does not necessarily translate into a significant survival benefit. Prediction of chemosensitivity in the clinic is particularly challenging because drug responses reflect not only properties intrinsic to the target cell, but also host metabolic properties. Pharmacokinetic and pharmacodynamic variables that affect drug action in vivo are not considered by in vitro assays. Because each patient has a unique pharmacogenetic makeup, leading to significant interpatient variations in drug half-life, volume of distribution, types of metabolites formed, and routes of elimination, correlating in vitro and in vivo results is often not a straightforward process. Furthermore, because some therapeutic agents (e.g., cyclophosphamide or CPT-11) are prodrugs that require metabolic activation, the in vitro modeling of in vivo tumor cell drug exposure becomes even more complex. However, by using in vitro models to address questions of chemosensitivity, one limits the study to cell-intrinsic properties found in cultured cells, which simplifies the system and focuses the initial investigation on tumor cell responsiveness. Many different methods are available for assessing chemosensitivity (2–4). In general, all assays generate dose-response curves where the dose of the drug is related to the percentage effect, such as tumor cell kill (Fig. 1). Determining the molar concentration that results in a 50% reduction in cell survival (IC50) can be used to compare the efficacy of different drugs in one tumor cell system or the same drug in different cell systems. The most common in vitro assays can be divided into one of three categories: (1) clonogenic/proliferation assays, (2) assessment of cell metabolic activity, and (3) measurement of cell membrane integrity. There has been much debate as to the characteristics of the “best” chemosensitivity assay. For example, should the assay measure colony formation or tumor cell proliferation? Should the assay be short term (hours to days) vs long term (days to weeks)?

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Fig. 1. Theoretical dose response curve.

Should the assay measure cytostatic or cytotoxic end points? Should the assay use a cell suspension or tumor microorgans? Should metabolic or morphological end points be used? Various assays measure different end points of cellular damage. Morphological appearance is generally considered too insensitive. Measurements of biochemical parameters or reproductive capacity are likely to be more reliable. Short-term assays may suggest that an agent is cytotoxic, but cells may recover. Thus, early indicators of drug-induced cell damage may provide misleading results. For an assay to be useful, the results must correlate with clinical response and survival; the end point of the assay must detect effects on cancer cells exclusive of other cellular elements such as fibroblasts, mesothelial cells, and endothelial cells; the turnaround time must meet clinical requirements; the test information must be easily interpreted and applied; and the test must be cost-effective. 2. Clonogenic and Proliferation Assays The clonogenic method such as the human tumor colony-forming assay (5) is analogous to antibiotic sensitivity testing in bacteria. Single untreated or treated tumor cells are grown in Petri dishes in a soft agar system and colonies are counted after about 2 to 3 wk. Automated image analyzers now make this a much faster procedure. The use of agar allows most tumor cells to grow but prevents fibroblast proliferation. A reduction in colony number in treated groups reflects cytotoxicity of the agent toward the tumor cells. This is the “gold standard” to which all other predictive assays have been compared for positive predictive reliability (predicting patient response). Controlling the number of colonies per plate and including only colonies with at least 40–50 cells is


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important for obtaining accurate information from this assay. However, the method is complicated by the ability to obtain a single cell tumor suspension, adequate plating efficiency, proper growth in agar, and sufficient cell numbers to test multiple concentrations of drug. Variations on this assay include microclonogenic assays on tumor cells grown in a 96-well plate or in suspension (6). IC50 values are determined based on dose-response curves that fit the data to a linear quadratic equation. Several other in vitro short-term growth inhibition assays are in use, which are based on survival of tumor cell populations that have been in contact with a chemotherapeutic agent. In these assays, which are experimentally simpler than clonogenic assays, growth inhibition might not reflect true cell kill and can result in higher false positive results. However, a measure of chemosensitivity can be obtained even when plating efficiencies are low. One such assay is the differential staining cytotoxicity assay (DiSC; [7]), which consists of incubating dissociated cells from biopsy specimens in the presence or absence of a drug for 4–6 d, and using a dye such as fastgreen, which permeates only through dead cells. The ratio of dead cells to total cells is a measure of cell kill. In general, there has been good qualitative agreement between the DiSC assay and the clonogenic assay. Duration of the assay is relatively short, and the assay can be used on the majority of tumor specimens but is labor intensive and subject to individual interpretation. Another method, the Kern assay (8), relies on uptake of radiolabeled precursor such as 3H-thymidine into the DNA of proliferating cells and is an example of similar assays that measure drug-induced inhibition of radioactive precursor incorporation into cellular macromolecules (DNA, RNA, or protein) of single-cell suspensions or tumor slices. The assumption is that thymidine incorporation into DNA reflects cell division. There is a difference in view as to whether the assay is considered a reliable means of quantifying drug sensitivity. Some believe that it is not an accurate measure in biopsies because of contaminating nontumor cells and, in general, may be problematic because the effect on thymidine incorporation is not the same as measuring cell kill or growth inhibition (2). Others have reported similar results with the Kern assay to that obtained with clonogenic assays and significant correlations between clinical responses and depression of DNA synthesis in vitro (9). In general, this assay excels at negative predictive reliability (predicting drug resistance). A third approach based on proliferation is the collagen gel droplet drug sensitivity test, which is a quick and simple colorimetric quantitative approach using neutral red staining within collagen gel drops that are imaged on a videomicroscope (10). It affords the advantage of being able to eliminate the influence of fibroblasts in a mixed tumor/stroma population derived from a biopsy specimen.

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3. Cell Metabolic Activity Assays Assays that use various surrogate markers of cell number and viability have been used to measure cell survival in response to a therapeutic. These methods include bioluminescence of adenosine triphosphate (ATP) (ATP-based tumor chemosensitivity assay [ATP-TCA]) (11) using the firefly luciferin-luciferase reagent; fluorometric microculture cytotoxicity assay (FMCA), which measures fluorescence generated from cellular hydrolysis of nonfluorescent fluorescein diacetate to fluorescein by viable cells in microtiter plates (12); coloration with sulforhodamine B (SRB), a general aminoxanthene dye for proteins, which binds electrostatically to basic amino acids; and coloration with reduction of a yellow tetrazolium dye such as MTT or MTS (13), substrates for mitochondrial dehydrogenases, resulting in a blue-purple formazan product that reflects metabolic activity of living cells. The ATP-TCA is extremely sensitive because ATP levels are linear with the number of viable cells and correlate with cytotoxicity to a number of antineoplastic agents in vitro. Assay results have also been used to predict clinical responses (14). This assay is done in a 96-well microplate and can use cell lines, or specimens from surgical needle biopsies, pleural or ascites fluid, and requires only 10,000–20,000 cells/well (15). The FMCA is also a useful assay in that it is simple, is rapid, and seems to report clinically relevant cytotoxic drug sensitivity data. An alternative high-throughput fluorescence assay using enhanced green fluorescent protein (GFP) is available that can be analyzed by flow cytometry or by fluorescence microplate reader (16). It is a sensitive and rapid method to detect drug-induced cell death that provides results comparable to those obtained by other traditional apoptosis assays such as annexin-V binding, propidium iodide incorporation, or reactive oxygen species production. The SRB assay provides a sensitive index of cellular protein content that is linear over a cell density range of two orders of magnitude, has a stable end point that does not require immediate range, and compares favorably with the MTT assay. However, the MTT assay is able to discriminate live cells from cellular debris, which the SRB assay cannot do. The drawbacks of assays such as the MTT are the sensitivity to the pH and glucose content of the media; chemical interferences with dye reduction; the quality of reagents used to solubilize the formazan crystals; the need to read the assay immediately before the color fades; and the limited dynamic range, with a sensitivity of only 1-log cell kill (17). In addition, such assays do not differentiate between cytostatic and cytotoxic effects. In spite of these limitations, the MTT assay has been effective at predicting the sensitivity of patients who have attained remission and of patient resistance (18). Both SRB and MTT assays provide rapid results and hold more promise in the screening and evaluation of potential new agents in


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established tumor cell lines than in evaluating chemosensitivity of primary tumor specimens. Some researchers believe that results derived from single-cell preparations are not as accurate as those obtained from tumor fragments in which the threedimensional structure of the tumor tissue is maintained (19). Two methods to assess chemosensitivity using tumor fragments in place of single cells have been utilized. The first is a variation on the MTT assay, called the histoculture drug response assay (20). The second approach, the fluorescent cytoprint assay (FCA), can be directly used on biopsy tissue without cell dissociation (21). In this assay, the tumor fragments are maintained in a collagen matrix during drug exposure. They are then treated with a fluorescent dye, which is visualized and photographed as “cytoprints” before and after drug treatment. This method has been shown to have a very high positive and negative predictive accuracy. Another marketed in vitro assay that has been reported to have a high predictive value is the extreme drug resistance assay (22). Tumor cells are exposed to suprapharmacological drug concentrations and either precursor incorporation or colony formation is measured. A drug resistance profile (extreme, intermediate, or low) can be determined based on statistical comparison to a historical database of tumor specimens tested against the same panel of chemotherapeutic agents (23). An alternative approach to measuring cell proliferation or metabolic viability is to measure drug-induced DNA damage at the chromosome level using morphological criteria. The cytokinesis block micronucleus assay can reliably measure chromosome loss, chromosome breakage, chromosome rearrangement (nucleoplasmic bridges), cell division inhibition, necrosis, and apoptosis (24). All the previously summarized in vitro assays, and which are detailed in the chapters that follow, must ultimately provide a drug sensitivity index to put the results into the context of other similar assay results, or calculate a probability of response. Table 2 provides a summary of correlations of in vitro results with patient response (25). The most sensitive assays are the DiSc and the FCA, and the most specific are the clonogenic, MTT, and ATP assays. The ATP assay also gives the highest positive prediction, and the clonogenic assay, thymidine incorporation assay, DiSc and FCA are all highly accurate. 4. In Vivo Assays In vitro assays in general are limited in that they do not take into account insufficient drug absorption, inadequate drug distribution to the tumor owing to poor vascularization, pharmacological barriers, the need for drug activation, detoxification of drug by general metabolic pathways, differences in tumor growth rate in vitro and in vivo, or the problem of tumor heterogeneity. Therefore, assessing

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Table 2 Correlation of In Vitro Results with Patient Responsea Type of assay

Total (N)

Clonogenic Thymidine DiSC MTT ATP FCA Total

2300 512 1427 494 123 232 510 247 175 326 187 74 129 74 37 333 154 116 4092 1297 2061

TP

TN

FP

FN

226 119 72 37 6 52 512

135 20 16 28 12 11 222

Positive Accuracy Sensitivity Specificity prediction (%) (%) (%) (%) 69 51 77 83 93 75 75

91 92 92 73 76 91 86

79 86 94 86 86 93 87

86 66 71 86 86 69 74

a Summary of clinical correlations from Table 7 in ref. 25. TP = true positive—patients who are sensitive in vitro and respond to therapy; TN = true negative—patients who are resistant in vitro and do not respond to therapy; FP = false positive—patients who are sensitive in vitro but resistant clinically; FN = false negative—patients who are resistant in vitro but respond clinically; positive prediction = TP/(TP + FP); accuracy = TN/(TN + FN); sensitivity = test’s ability to detect clinically responsive patients = TP/(TP + FN); specificity = test’s ability to detect clinically unresponsive patients = TN/(TN + FP).

chemosensitivity in preclinical tumor-bearing animal models is essential. Primary tumor models that have been utilized include human tumors grown subcutaneously in athymic nude mice, severe combined immunodeficient mice, or triple-deficient mice (bg/nu/xid mutations; [26]). Examples of metastasis models of human tumors include those grown orthotopically (27) or introduced systemically via iv, ip, intracardiac, intrasplenic, or intrahepatic injection or via inoculation of a cell suspension or tumor fragment into the mammary pad (28) or subrenal capsule (29). For primary growth, tumor size is followed by caliper measurement and tumor growth curves are constructed. Various formulas to measure tumor volume, area, and diameter have been used (30). Absolute tumor size, change in tumor size, percentage of growth inhibition, and area under the tumor growth curve have been reported. Using appropriate statistical methods to analyze tumor growth experiments that have sufficient power and low type I error rates is essential when performing in vivo chemosensitivity experiments (31). For metastasis models, median animal survival time, number and/or size of metastases after a fixed time, and weight of an organ containing metastases have been used as measures of response to a therapeutic agent. In addition to direct measurements of tumor growth, imaging approaches have been developed to assess tumor chemosensitivity (32). These tools include the use of 18 FDG positron emission tomography (33), 99mTc-annexin-V scintigraphy (34), magnetic resonance imaging (35) and GFP (36).


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5. Molecular Assays of Chemosensitivity The range of response to a particular cytotoxic agent can be quite substantial, and studies to understand the molecular parameters at the gene and at the protein level that regulate chemosensitivity or resistance are an active area of investigation (37). The molecular basis of sensitivity to chemotherapy is a complex product of cellular and tissue factors (38–41). These include expression of the P-glycoprotein family of membrane transporters (e.g., MDR1, MRP, LRP), which decrease the intracellular accumulation of drug; changes in cellular proteins involved in detoxification (e.g., glutathione S-transferase π, metallothioneins, NADP cytochrome P-450 reductase); changes in expression of molecules involved in DNA repair (e.g., O6-methylguanine DNA methyltransferase, DNA topoisomerase II, hMLH1, p21WAF1/CIP1); and activation oncogenes such as Her-2/neu, bcl-2, bcl-XL, c-myc, ras, c-jun, c-fos, MDM2, p210, BCR-abl, or mutant p53. In addition, expression of growth factors and receptors, proliferation markers (42), telomerase (43), enzymes that regulate intracellular ceramide levels (44), positive and negative regulators of apoptosis, and cell-cycle checkpoint controls are all important (45,46). For example, the form of p53 expression (null, wild type, or mutant and the location of the mutation) is known to affect chemosensitivity (47). Drug resistance can occur at the onset of the disease or can be acquired after previous chemotherapy. Methods that identify and detect expression of drug resistance genes (48) or proteins (49) by flow cytometry (50), Western blotting, or immunohistochemistry (IHC) (51); or by induction of apoptosis by the DNA diffusion assay (52), diphenylamine assay to evaluate DNA fragmentation (53), TUNEL assay (54), flow cytometry with fluorescein isothiocyanate-annexin-V (34), PARP assay (55), or expression of BCl-2 family proteins including Bcl-2, Bcl-X(L), Bax, Bad, and Bak (56); or by changes in cell cycle (57) can be used as indirect measures of chemosensitivity. 6. Genomic and Proteomic Approaches to Understand Chemosensitivity Previous efforts to use genetic information to predict drug sensitivity primarily have focused on individual genes that have broad effects, such as the multidrug resistance genes mdr1 and mrp1 (58). There has been an effort to develop a genomics- and proteomics-based approach for the prediction of drug response (59–61). An example of the clinical application of single-gene analysis as a predictor of chemosensitivity is the evaluation of thymidylate synthase mRNA expression from tumor core needle biopsies using real-time polymerase chain reaction analysis. Those patients with a clinical response to 5-fluorouracil (5-FU) therapy had a significantly lower level of expression of this gene. Expanding beyond single-gene effects on treatment response, the recent development of

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DNA microarrays permits large-scale screening of genes and the simultaneous measurement of the expression levels of thousands of genes and raises the possibility of an unbiased, genomewide approach to understand the genetic basis of drug response (62). Algorithms have been developed for the classification of cell line chemosensitivity based on gene expression profiles. Using oligonucleotide microarrays, the expression levels of genes can be measured in a panel of cancer cell lines with known chemosensitivity profiles for various chemical compounds. Genes associated with repair processes, cell-cycle checkpoints, apoptosis, signal transduction, and metabolism can all be studied. Microarray analysis of baseline gene expression (63,64) and drug-induced changes in gene expression (65) have been successfully applied to predicting chemotherapy response. Further development of this technology will enable those responsible for treatment planning not only to predict chemosensitivity prior to therapy, but to answer whether the classifiers are dependent on tumor type or tumor class. Toward that goal, chemosensitivity prediction studies are being extended beyond cell line models to include the analysis of primary patient material. The addition of proteomic studies to genomic studies will further facilitate the ability to identify a priori sensitive and resistant tumors (66). In the past, protein analysis of formalin-fixed paraffin-embedded tumor tissue or Western blotting was used to assess prediction of therapeutic response. Techniques such as IHC provide semiquantitative information on the level of expression of key proteins. Similar to mRNA results, thymidylate synthase expression at the protein level has been a consistent predictor of response to 5-FU-based chemotherapy of metastatic colorectal cancer (67). Other protein markers that have been useful for predicting chemosensitivity include ornithine decarboxylase (68), HER-2/neu (69), the p27 cell-cycle regulatory protein (70), and Bcl-2 (71). Other proteins that have been studied but have not been predictive include p53 and cerbB-2 (72). The use of tissue arrays allows IHC to be performed on 0.6-mm core tissue sections from a large panel of tumor samples of varying histotypes (73). The field is now expanding beyond detection and quantification of single proteins, to include evaluation of a sizable panel of proteins by combining the tools of laser capture detection of tumor cells with silver stained twodimensional gel electrophoresis and generate a tumor phenotype (74). Much of this effort has focused on the mass spectral identification of the thousands of proteins that populate complex biosystems. Protein patterns can be analyzed in hundreds of clinical samples per day utilizing this technology. 7. Future Directions The availability of predictive in vitro and in vivo assays provides a mean of addressing many important issues in tumor biology. Several areas of investiga-


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tion related to chemosensitivity testing are worthy of consideration. First, work is required to establish gene and protein profiles associated with drug sensitivity (59). Studies are needed to address whether baseline gene/protein expression or drug-induced changes in expression are most predictive of response to treatment. Second, developing a better understanding of how to use drug combinations and schedules is essential. In vitro (75) and in vivo (76) models have been developed to assess interactions between multiple therapeutic agents. Toward that end, studies to determine how the use of one agent influences the biology of the surviving tumor cells and environmental milieu, and thus affects sensitivity to the second agent, are needed. Third, how chemosensitivity can be modulated, such as by using compounds that affect DNA repair (77); pharmacological agents (e.g., small molecule [78]); or genetic methods such as antisense, ribozyme, or RNA interference technology to overcome drug resistance (79) or antiapoptotic states must be determined. Fourth, the role that circadian rhythms play in chronotherapy (80) is just beginning to receive attention. In vivo designs to address how light/dark cycles impact the optimal time of day to administer a particular drug to achieve maximal efficacy are under investigation. Fifth, tumor heterogeneity within a patient is important. Clinically, this is seen when a tumor mass in one area responds to chemotherapy, while a separate site may remain stable or progress. Intrapatient response variations have been evaluated by comparing the in vitro drug response of primary vs metastatic sites from the same patient. Thus, in vitro test results for solid tumors from one site may not be representative for other sites within the same patient. Additional research to understand the molecular differences in chemosensitivity between primary and secondary sites is needed. Finally, developing approaches to individualize drug treatment as a function of tumor cell sensitivity (as has been done in infectious disease) requires further attention. References 1. Kaspers, G., Zwaan, C., Pieters, R., and Veerman, A. (1999) Cellular drug resistance in childhood acute myeloid leukemia: a mini-review with emphasis on cell culture assays. Adv. Exp. Med. Biol. 457, 415–421. 2. Robert, J. (1999) Chemosensitivity testing: prediction of response to anticancer drugs using in vitro assays. Electronic J. Oncol. 2, 198–210. 3. Bellamy, W. (1992) Prediction of response to drug therapy of cancer: a review of in vitro assays. Drugs 44, 690–708. 4. Gercel-Taylor, C., Ackermann, M., and Taylor, D. (2001) Evaluation of cell proliferation and cell death based assays in chemosensitivity testing. Anticancer Res. 21, 2761–2768. 5. Von Hoff, D., Clark, G., Stogdill, B., et al. (1983) Prospective clinical trial of a human tumor cloning system. Cancer Res. 43, 1926–1936.

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6. Engblom, P., Rantanen, V., Kulmala, J., and Grenman, S. (1996) Paclitaxel and cisplatin sensitivity of ovarian carcinoma cell lines tested with a 96-well plate clonogenic assay. Anticancer Res. 16, 1743–1747. 7. Weisenthal, L., Marsden, J., Dill, P., and Macaluso, C. (1983) A novel dye exclusion method for testing in vitro chemosensitivity of human tumors. Cancer Res. 43, 749–757. 8. Kern, D., Drozemuller, C., Kennedy, M., et al. (1985) Development of a miniaturized improved nucleic acid precursor incorporation assay for chemosensitivity testing of human solid tumors. Cancer Res. 45, 5436–5441. 9. Sondak, V., Bertelson, C., Tanigawa, N., et al. (1984) Clinical correlations with chemosensitivities measured in a rapid thymidine incorporation assay. Cancer Res. 46, 1725–1728. 10. Kobayashi, H., Higashiyami, M., Minamigawa, K., et al. (2001) Examination of in vitro chemosensitivity test using collagen gel droplet culture method with colorimetric endpoint quantitation. Jpn. J. Cancer Res. 92, 203–210. 11. Kangas, L., Gronroos, M., and Nieminen, A. (1984) Bioluminesence of cellular ATP: a new method for evaluating cytotoxic agents in vitro. Med. Biol. 62, 338–343. 12. Csoka, K., Larsson, R., Tholander, B., Gerdin, E., de la Torre, M., and Nygren, P. (1994) Cytotoxic drug sensitivity testing of tumor cells from patients with ovarian carcinoma using the fluorometric microculture cytotoxicity assay (FMCA). Gynecol. Oncol. 54, 163–170. 13. Rubinstein, L., Shoemaker, R., Pacell, K., Simon, R., and Tosini, S. (1990) Comparison of in vitro anticancer-drug-screening data generated with a tetrazolium assay versus a protein assay against a diverse panel of human tumor cells lines. J. Natl. Cancer Inst. 82, 1113–1118. 14. Sevin, B., Peng, Z., Perras, J., Panalver, G., and Averette, H. Application of an ATP bioluminescence assay in human tumor chemosensitivity testing. Gynecol. Oncol. 31, 191–204. 15. Andreotti, P., Cree, I., Kurbacher, C., et al. (1995) Chemosensitivity testing of human tumors using a microplate adenosine triphosphate luminescence assay: clinical correlation for cisplatin resistance of ovarian carcinoma. Cancer Res., 55, 5276–5282. 16. Steff, A., Fortin, M., Arguin, C., and Hugo, P. (2001) Detection of a decrease in green fluorescent protein fluorescence for the monitoring of cell death: an assay amenable to high-throughput screening technologies. Cytometry 45, 237–243. 17. Vistica, D., Skehan, P., Scudiero, D., et al. (1991) Tetrazolium-based assays for cellular viability: a critical examination of selected parameters affecting formazan production. Cancer Res. 51, 2515–2520. 18. Sargent, J. and Taylor, C. Appraisal of the MTT assay as a rapid test of chemosensitivity in acute myeloid leukemia. Br. J. Cancer 60, 206–210. 19. Hoffman, R. (1991) Three-dimensional histoculture: origins and applications in cancer research. Cancer Cells 3, 86–92.


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20. Singh, B., Li, R., Xyu, L., et al. (2002) Prediction of survival in patients with head and neck cancer using the histoculture drug response assay. Head Neck 24, 437–442. 21. Meitner, P. (1991) The fluorescence cytoprint assay: a new approach to in vitro chemosensitivity testing. Oncology 5, 75–81. 22. Kern, D. and Weisenthal, L. (1990) Highly specific prediction of antineoplastic drug resistance with an in vitro assay using supra-pharmacologic drug exposures. J. Natl. Cancer Inst. 82, 582–588. 23. Haroun, R., Clatterbuck, R., Gibbons, M., et al. (2002) Extreme drug resistance in primary brain tumors: in vitro analysis of 64 resection specimens. J. Neurooncol. 58, 115–123. 24. Fenech, M. (2000) The in vitro micronucleus technique. Mutation Res. 455, 81–95. 25. Fruhauf, J. and Bosanquet, A. (1993) In vitro determination of drug response: a discussion of clinical applications. PPO Updates 7, 1–21. 26. Clarke, R. (1996) Human breast cancer cell line xenografts as models of breast cancer: the immunobiologies of recipient mice and the characteristics of several tumorigenic lines. Breast Cancer Res. Treat. 39, 69–86. 27. Hoffman, R. (1999) Orthotopic metastatic mouse models for anticancer drug discovery and evaluation: a bridge to the clinic. Invest. New Drugs 17, 343–359. 28. Price, J. (1996) Metastasis from human breast cancer cell lines. Breast Cancer Res. Treat. 39, 93–102. 29. Konovalova, N., Diatchkovskaya, R., Ganieva, L., Volkova, L., Lapshin, I., Rudakov, B., Shaposhnikov, Y., and Shapiro, A. (1991) Subrenal capsule assay of human tumor chemosensitivity. Neoplasma 38, 275–284. 30. Tomayko, M. and Reynolds, C. (1989) Determination of subcutaneous tumor size in athymic (nude) mice. Cancer Chemother. Pharmacol. 24, 148–154. 31. Heitjan, D., Manni, A., and Santen, R. (1993) Statistical analysis of in vivo tumor growth experiments. Cancer Res. 53, 6042–6050. 32. Gibbs, J., Slocum, H., Cao, S., and Rustum, Y. (1999) Image analysis for quantitation of solid tumor drug sensitivity. Int. J. Surg. Invest. 1, 133–138. 33. Kubota, K. (2001) From tumor biology to clinical PET: a review of positron emission tomography (PET) in oncology. Ann. Nucl. Med. 15, 471–486. 34. Belhocine, T., Steinmetz, N., Hustinx, R., et al. (2002) Increased uptake of the apoptosis imaging agent (99m)Tc recombinant human Annexin V in human tumors after one course of chemotherapy as a predictor of tumor response and patient prognosis. Clin. Cancer Res. 8, 2766–2774. 35. Mazurchuk, R., Glaves, D., and Raghavan, D. (1997) Magnetic resonance imaging of response to chemotherapy in orthotopic xenografts of human bladder cancer. Clin. Cancer Res. 3, 1635–1641. 36. Nakanishi, H., Mochizuki, Y., Kodera, Y., et al. (2003) Chemosensitivity of peritoneal micrometastases as evaluated using green fluorescence protein (GFP)–tagged human gastric cancer cell line. Cancer Sci. 94, 112–118. 37. Tewari, K. and Manetta, A. (1999) In vitro chemosensitivity testing and mechanisms of drug resistance. Curr. Oncol. Rep. 1, 77–84.

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38. el-Deiry, W. S. (1997) Role of oncogenes in resistance and killing by cancer therapeutic agents. Curr. Opin. Oncol. 9, 79–87. 39. Fan, S., el-Deiry, W., Bae, I., et al. (1994) p53 gene mutations are associated with decreased sensitivity of human lymphoma cells to DNA damaging agents. Cancer Res. 54, 5824–5830. 40. Bosken, C., Wei, Q., Amos, C., and Spitz, M. (2002) An analysis of DNA repair as a determinant of survival in patients with non-small-cell lung cancer. J. Natl. Cancer Inst. 94, 1091–1099. 41. Zunino, F., Perego, P., Pilotti, S., and Pratesi, G. (1997) Role of apoptotic response in cellular resistance to cytotoxic agents. Pharmacol. Ther. 76, 177–185. 42. Wang, Y., Ashkenazi, Y., and Bachrach, U. In vitro chemosensitivity of hematological cancers: immunohistochemical detection of ornithine decarboxylase. Anticancer Drugs 10, 797–805. 43. Park, K., Rha, S., Kim, C., et al. (1998) Telomerase activity and telomere lengths in various cell lines: changes of telomerase activity can be another method for chemosensitivity evaluation. Int. J. Oncol. 13, 489–495. 44. Modrak, D., Rodriguez, M., Goldenberg, D., Lew, W., and Blumenthal, R. (2002) Sphingomyelin enhances chemotherapy efficacy and increases apoptosis in human colonic tumor xenografts. Int. J. Oncol. 20, 379–384. 45. Epstein, R. (1990) Drug-induced DNA damage and tumor chemosensitivity. J. Clin. Oncol. 8, 2062–2084. 46. Xia, F. and Powell, S. (2002) The molecular basis of radiosensitivity and chemosensitivity in the treatment of breast cancer. Semin. Radiat. Oncol. 12, 296–304. 47. Manahan, K., Taylor, D., and Gercel-Taylor, C. (2001) Clonal heterogeneity of p53 mutations in ovarian cancer. Int. J. Oncol. 19, 387–394. 48. Granjean, F., Bremaud, L., Verdier, M., Robert, J., and Ratinaud, M. (2001) Sequential gene expression of P-glycoprotein (P-gp), multidrug resistance associated protein (MRP) and lung resistance protein: functional activity of P-gp and MRP present in the doxorubicin-resistant human K562 cell lines. Anticancer Drugs 12, 247–258. 49. Michieli, M., Damiani, D., Ermacora, A., et al. (2000) P-glycoprotein (PGP), lung resistance–related protein (LRP) and multidrug resistance–associated protein (MRP) expression in acute promyelocytic leukemia. Br. J. Haematol. 108, 703–709. 50. Pallis, M., Turzanski, J., Langabeer, S., and Russell, N. (1999) Reproducible flow cytometric methodology for measuring multidrug resistance in leukaemic blasts. Adv. Exp. Med. Biol. 457, 77–88. 51. Pall, G., Spitaler, M., Hofmann, J., Thaler, J., and Ludescher, C. (1997) Multidrug resistance in acute leukemia: a comparison of different diagnostic methods. Leukemia 11, 1067–1072. 52. Singh, N. (2000) A simple method for accurate estimation of apoptotic cells. Exp. Cell. Res. 256, 328–337.


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53. Munshi, A., McDonnell, T., and Meyn, R. (2002) Chemotherapeutic agents enhance TRAIL-induced apoptosis in prostate cancer cells. Cancer Chemother. Pharmacol. 50, 46–52. 54. Maciorowski, Z., Klijanienko, J., Padoy, E., et al. (2001) Comparative image and flow cytometric TUNEL analysis of fine needle samples of breast carcinoma. Cytometry 46, 150–156. 55. Ogata, S., Okumura, K., and Taguchi, H. (2000) A simple and rapid method for the detection of poly(ADP-ribose) by flow cytometry. Biosci. Biotechnol. Biochem. 64, 510–515. 56. Nita, M., Nagawa, H., Tominago, O., et al. (1998) 5-Fluorouracil induces apoptosis in human colon cancer cell lines with modulation of Bcl-2 family proteins. Br. J. Cancer 78, 986–992. 57. Smith, D., Gao, G., Zhang, X., Wang, G., and Dou, Q. (2000) Regulation of tumor cell apoptotic sensitivity during the cell cycle [review]. Int. J. Mol. Med. 6, 503–507. 58. Sonneveld, P. (2000) Multidrug resistance in hematological malignancies. J. Intern. Med. 247, 521–534. 59. Staunton, J., Slonim, D., Coller, H., et al. (2001) Chemosensitivity prediction by transcriptional profiling. Proc. Natl. Acad. Sci. USA 98, 10,787–10,792. 60. Bao, L. and Sun, Z. (2002) Identifying genes related to drug anticancer mechanisms using support vector machine. FEBS Lett. 521, 109–114. 61. McLeod, H. Individualized cancer therapy: molecular approaches to the prediction of tumor response. Expert Rev. Anticancer Ther. 2, 113–119. 62. Amundson, S., Myers, T., Scudiero, D., Kitada, S., Reed, J., and Fornace, A. (2000) An informatics approach identifying markers of chemosensitivity in human cancer cell lines. Cancer Res. 60, 6101–6110. 63. Alizadeh, A., Eisen, M., and Dasvis, R. (2000) Distinct types of diffuse large B-cell lympoma identified by gene expression profiling. Nature 403, 503–511. 64. Kihara, C., Tsunoda, T., Tanaka, T., et al. (2001) Prediction of sensitivity of esophageal tumors to adjuvant chemotherapy by cDNA microarray analysis of gene-expression profiles. Cancer Res. 61, 6474–6479. 65. Sotirious, C., Powles, T., Dowsett, M., et al. (2002) Gene expression profiles derived from fine needle aspiration correlate with response to systemic chemotherapy in breast cancer. Breast Cancer Res. 4, R3. 66. Poland, J., Schadendorf, D., Lage, H., Schnolzer, M., Celis, J., and Siha, P. (2002) Study of therapy resistance in cancer cells with functional proteome analysis. Clin. Chem. Lab. Med. 40, 221–234. 67. Aschele, C., Debernardis, D., Casazza, S., et al. (1999) Immunohistochemical quantitation of thymidylate synthase expression in colorectal cancer metastases predicts for clinical outcome to fluorouracil-based chemotherapy. J. Clin. Oncol. 17, 1760–1770. 68. Bachrach, U. and Wang, Y. (2003) In vitro chemosensitivity testing of hematological cancer patients: detection of ornithine decarboxylase. Rec. Results Cancer Res. 161, 62–70.

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69. Konecny, G., Fritz, M., Untch, M., et al. (2001) Her-2/neu overexpression and in vitro chemosensitivity to CMF and FEC in primary breast cancer. Breast Cancer Res. Treat. 69, 53–63. 70. Yang, Q., Sakurai, T., Yoshimura, G., et al. (2000) Overexpression of p27 protein in human breast cancer correlates with in vitro resistance to doxorubicin and mitomycin C. Anticancer Res. 20, 4319–4322. 71. Yang, Q., Sakurai, T., Yoshimura, G., et al. (2000) Expression of Bcl-2 but not Bax or p53 correlates with in vitro resistance to a series of anticancer drugs in breast carcinoma. Breast Cancer Res. Treat. 61, 211–216. 72. Rozan, S., Vincent-Salomon, A., Zafrani, B., et al. (1998) No significant predictive value of c-erbB-2 or p53 expression regarding sensitivity to primary chemotherapy or radiotherapy in breast cancer. Int. J. Cancer 79, 27–33. 73. Ginestier, C., Charafe-Jauffret, E., Bertucci, F., et al. (2002) Distinct and complementary information provided by use of tissue and DNA microarrays in the study of breast tumor markers. Am. J. Pathol. 161, 1223–1233. 74. Jones, M., Krutzsch, H., Shu, H., et al. (2002) Proteomic analysis and identification of new biomarkers and therapeutic targets for invasive ovarian cancer. Proteomics 2, 76–84. 75. Konecny, G., Untch, M., Slamon, D., et al. (2001) Drug interactions and cytotoxic effects of paclitaxel in combination with carboplatin, epirubicin, gemcitabine, or vinorelbine in breast cancer cell lines and tumor samples. Breast Cancer Res. Treat. 67, 223–233. 76. Lopez, A., Pegram, M., Slamon, D., and Landaw, E. (1999) A model-based approach for assessing in vivo combination therapy interactions. Proc. Natl. Acad. Sci. USA 96, 13,023–13,028. 77. Heim, M., Eberhardt, W., Seeber, S., and Muller, M. (2000) Differential modulation of chemosensitivity to alkylating agents and platinum compounds by DNA repair modulators in human lung cancer cell lines. J. Cancer Res. Clin. Oncol. 126, 198–204. 78. Kondratov, R., Komarov, P., Becker, Y., Ewenson, A., and Gudkov, A. (2001) Small molecules that dramatically alter multidrug resistance phenotype by modulating the substrate specificity of P-glycoprotein. Proc. Natl. Acad. Sci. USA 98, 14,078–14,083. 79. Henewisch-Becker, S. (1996) MDR1 reversal: criteria for clinical trials designed to overcome the multidrug resistance phenotype. Leukemia 10, S32–S38. 80. Levi, F., Giacchetti, S., Zidani, R., et al. (2001) Chronotherapy of colorectal cancer metastases. Hepatogastroenterology 48, 320–322.

II IN VITRO MEASURES

OF

CHEMOSENSITIVITY

2 Clonogenic Cell Survival Assay Anupama Munshi, Marvette Hobbs, and Raymond E. Meyn Summary The clonogenic cell survival assay determines the ability of a cell to proliferate indefinitely, thereby retaining its reproductive ability to form a large colony or a clone. This cell is then said to be clonogenic. A cell survival curve is therefore defined as a relationship between the dose of the agent used to produce an insult and the fraction of cells retaining their ability to reproduce. Although clonogenic cell survival assays were initially described for studying the effects of radiation on cells and have played an essential role in radiobiology, they are now widely used to examine the effects of agents with potential applications in the clinic. These include, in addition to ionizing radiation, chemotherapy agents such as etoposide and cisplatin, antiangiogenic agents such as endostatin and angiostatin, and cytokines and their receptors, either alone or in combination therapy. Survival curves have been generated for many established cell lines growing in culture. One can use cell lines from various origins including humans and rodents; these cells can be neoplastic or normal. Because survival curves have wide application in evaluating the reproductive integrity of different cells, we provide here the steps involved in setting up a typical experiment using an established cell line in culture.

Key Words Survival curve; cell survival; plating efficiency; radiation.

1. Introduction Clonogenic cell survival is a basic tool that was described in the 1950s for the study of radiation effects. Much of the information that has been generated on the effect of radiation on mammalian cells has been obtained from clonogenic cell survival assays. Various mechanisms have been described for cell death; however, loss of reproductive integrity and the inability to proliferate indefinitely are the most common features. Therefore, a cell that retains its ability to synthesize proteins and DNA and go through one or two mitoses, but is unable to divide and From: Methods in Molecular Medicine, vol. 110: Chemosensitivity: Vol. 1: In Vitro Assays Edited by: R. D. Blumenthal © Humana Press Inc., Totowa, NJ

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produce a large number of progeny is considered dead. This is very commonly referred to as loss of reproductive integrity or reproductive death and is the end point measured with cells in culture. On the other hand, a cell that is not reproductively dead and has retained the capacity to divide and proliferate indefinitely can produce a large clone or a large colony of cells and is then referred to as “clonogenic.” A cell survival curve describes a relationship between the insult-producing agent and the proportion of cells that survive. The ability of a single cell to grow into a large colony that can be visualized with the naked eye is proof that it has retained its capacity to reproduce. The loss of this ability as a function of dose of radiation or chemotherapy agent is described by the dose-survival curve. Most laboratories now extensively use established cell lines for studying the effects of various agents either alone or in combination. Therefore, the aim of this chapter is to go through the steps involved in setting up a typical clonogenic cell survival experiment using established cells lines growing as monolayer cultures. In brief, cells from an actively growing stock culture in monolayer are prepared in a suspension by the use of trypsin, which causes the cells to detach from the substratum. The number of cells per milliliter in this suspension is then counted using a hemocytometer or a Coulter counter. From this stock culture, if 50 cells are seeded into a dish, e.g., and the dish is incubated for approx 2 wk, each single cell divides many times and forms a colony that is easily visible with the naked eye, especially if it is fixed and stained (the steps involved in this process are briefly outlined in Fig. 1). All the cells that make up the colony are the progeny of a single cell. For the 50 cells seeded into the dish, the number of colonies counted may be anywhere from 0 to 50. One would ideally expect the number to be 50, but that is rarely the case for several possible reasons, including suboptimal growth medium, errors in counting the number of cells initially plated, and the loss of cells by trypsinization and general handling. The term plating efficiency (PE) indicates the percentage of cells seeded into a dish that finally grow to form a colony. Therefore, in the previous example, if there are 25 colonies in the dish, then the PE becomes 50%. If a parallel dish is seeded with cells exposed to a dose of 6 Gy of gamma rays and incubated for approx 2 wk before being fixed and stained, then the following may be observed: 1. Some cells may remain single, not divide, and, in some cases, may show evidence of nuclear deterioration as they die by apoptosis. These cells would be scored as dead. 2. Some cells may go through one or two divisions and form small colonies of just a few cells. These cells would be scored as dead. 3. Some cells may form large colonies, indicating that the cells have survived the treatment and have retained the ability to reproduce indefinitely.

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Fig. 1. Schematic representation of steps involved in setting up a clonogenic cell survival assay.

2. Materials 2.1. Preparation of Cell Lines Prior to Setting Up Clonogenic Assays 1. Cell lines that need to be tested for their ability to form colonies. 2. Complete growth medium as recommended by the manufacturer typically containing 10% fetal bovine serum plus antibiotics (penicillin–streptomycin) and glutamine. For every 500 mL of medium, add 55 mL of serum, 5 mL of 200 mM L-glutamine, and 5 mL of 10,000 U/mL penicillin–streptomycin solution. Medium should be stored at 4°C but warmed to 37°C prior to use. 3. Trypsin-EDTA, to make single-cell suspensions from monolayer cultures. Store at 4°C. 4. Plasticware, for carrying out tissue culture including flasks (T-25 and T-75); 100-mm dishes; and 5-, 10-, and 25-mL pipets. 5. Micropipets and corresponding tips. 6. 70% ethanol, for wiping the surface of the hood as well as the surface of all medium bottles prior to bringing them into the hood. 7. Cidecon (detergent disinfectant with bactericidal and virucidal properties), to wipe the surface of the shelf on which the dishes will be incubated. 8. Phosphate-buffered saline (PBS) (calcium magnesium free). Store at 4°C. 9. Isoton II (diluent for counting cells using a Coulter counter). Store at room temperature.

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2.2 Staining of Plates 1. 0.5% Gentian Violet (made up in methanol). Store at room temperature in a dark bottle. Do not pour it down the sink.

3. Methods 3.1. Cells Growing in Monolayers or Attached Cells The procedure that we outline in this chapter is a basic protocol for setting up radiation clonogenic assays. However, this protocol can be modified to test the effect of different agents on the cell line of interest, either alone or in combination. These could include gene therapy vectors, chemotherapy agents, tyrosine kinase inhibitors, antiangiogenic agents—basically any agent that has to be tested for its ability to affect reproductive cell death. 3.2. Preparation of Cell Lines Prior to Setting Up Clonogenic Cell Survival 1. Label six T-25 flasks in preparation for setting each flask with a known number of cells as 0, 2, 4, and 6 Gy (depending on the experiment) for the various doses of radiation to be given. Add 5 mL of growth medium to the flasks and keep them aside in a hood. 2. Trypsinize the stock flask of cells containing the cells that have to be tested for their radiosensitivity. Make sure that the cells are in single-cell suspension and obtain an accurate cell count. We use a Coulter counter to obtain a cell count. If a Coulter counter is not available, cells can be counted using a hemocytometer. Using a Pipettman, add 250,000 cells (the cell number can vary depending on the cell type) to the 5 mL of medium in each T-25 flask. Shake gently to distribute the cells evenly. 3. Place the flasks in a 37°C incubator set at 5% CO2 and be sure to leave the cap one thread loose so as to allow CO2 exchange (see Note 1). 4. Allow the cells to settle and attach as a monolayer.

3.3. Irradiation of Flasks and Performance of Plating Experiment for Clonogenic Assay 1. Prepare the hood and clean an incubator shelf. Because these cells are going to be left untouched in an incubator for up to 2 wk, and the possibility of contamination is high, clean the shelf thoroughly with Cidecon and 70% ethanol. Keep the cleaned shelf in the hood. Make sure that more than one bottle of complete medium is available; this experiment may require >500 mL of medium. 2. Prepare the 100-mm dishes and 15-mL tubes in advance. One will need 100-mm dishes in triplicate, and two cell numbers will be plated for each dose of radiation. Because cells will be exposed to six doses of radiation, 36 dishes will be needed. Label the bottom of each dish as the lid, for the dishes will be loose during staining, and the bottom is where the colonies will form, which is what will actually


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be counted. Label the first set of triplicate dishes as 0 Gy A and 0 Gy B (A and B for the two cell numbers to be used). Repeat this for all dose levels: 2, 4, 6, 8, and 10 Gy. Place 10 mL of complete medium in each dish. Place all dishes, stacked in threes, on the incubator shelf and put back in the incubator until ready for plating. Place 18, 15-mL tubes on a clean rack three deep. Label the first tube 0Gy, 11; the next one 0 Gy 110; and the next 0 Gy 1100. Repeat this for all dose levels. Place 4.5 mL of complete medium in the back two tubes but not in the 11 dilution tubes. Put the flasks on ice. Clean a rectangular tub and fill it halfway with ice. Remove the flasks from the incubator and close the caps tightly. Place the flasks on ice, and insert half depth into the ice. Tilt the flasks to the bottom so that the medium does not rest against the cap. Start a timer for 20 min. While waiting, prepare the Coulter counting vials. Label each as 0, 2, 4, and 6 Gy. Place 9.9 mL of Isoton (to be used for counting cells if using a Coulter counter) into each vial. Place Isoton in a control vial and run through the counter to get a background measurement; repeat until a satisfactory low background is obtained. Make sure that the Coulter is set to the appropriate size parameter for the cell line. When the 20-min time is up, irradiate the flasks using an appropriate irradiator according to the desired dose. Return to the hood, keeping the flasks on ice outside the hood. Begin the trypsinization procedure for each flask. Start with the 0-Gy flask. Aspirate the medium, rinse the cells gently with PBS, and then trypsinize. Place the harvested cells in the 15-mL tube labeled 0 Gy, 11. Make sure that you have a good singlecell suspension. From this cell suspension, take 100 µL and place in the appropriate counting vial for 0 Gy. Now trypsinize the next flask. While the flask is on the warming tray, count the previous counting vial and record the counts on a dilution sheet (see Fig. 2 for a setup of a dilution sheet that we commonly use in the laboratory). This expedites the experiments and lessens the chance of cell divisions taking place unequally during the time of trypsinization and counting. Continue this procedure until all the flasks have been trypsinized and counted. There should now be cells in each of the 11 dilution tubes, with a known number of cells/milliliter, all documented on the dilution sheet. Perform serial dilutions for each radiation dose so that the desired number of cells will be obtained by adding between 100 and 1000 µL of volume to the dishes. If the number of cells needed requires a volume exceeding 1000 µL, use a more concentrated dilution. Plate a number of cells consistent with obtaining a colony count of 50–100. This may require only 100 cells for the control plate whereas at 6 Gy this may require 4000 cells or more. Remember that the larger the insult to the flask (i.e., increasing radiation dose or increasing drug concentration if using chemotherapy agents), the lower the plating efficiency and the more cells are needed to obtain the desired colony count (see Note 2). It is important to resuspend the cell pellet, which has probably settled to the bottom of the tube by the time all the flasks have been counted. Place 0.5 mL of the 11

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Fig. 2. (A) Setup of dilution sheet used during clonogenic cell survival assays; (B) survival curve plotted using hypothetical numbers derived from dilution sheet

11.

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dilution into the 110 dilution tube (containing 4.5 mL of medium). Similarly, mix each dilution well before aliquoting 0.5 mL to the next-higher dilution tube. When the final dilution tube for each dose has been made, mark the top of each tube with an X and place the other tubes that are not needed outside the hood. This will minimize the chance of grabbing the wrong tube at the time of plating. Place the calculated volume of cell solution slowly into each appropriate 100-mm dish. Start with the bottom dish and work up. Place the solution on the medium drop by drop, spreading the drops evenly over the entire surface area to prevent clumping and overlap of colonies. After placing the solution in the three 100-mm dishes, rock the plates north–south and east–west to distribute the cells evenly. Avoid swirling the solution, which allows cells to group at the sides, making counting difficult. When all of the dishes have been plated, return the shelf to the incubator. Label the inside door of the incubator with the name of the experiment, initials, date of the project in and date expected to come out (see Note 3). As a rule of thumb, incubate for 10–12 d for cells with 13 h or less of generation time, approx 14 d for 14 h or more. We routinely set up clonogenic assays for these periods of time without any contamination.


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3.4. Staining of Plates Staining plates with Gentian Violet is easy, but care must be taken not to get it on one’s clothes, because it is difficult to remove. It is suggested that a laboratory coat and double glove be used for the staining procedure. 1. Take the shelf from the incubator and place it by the sink. Empty the medium from six plates into a flask with bleach in the sink. Place 0.5% Gentian Violet onto each of the six plates. Gentian Violet is diluted from a stock with methanol. 2. Run a gentle stream of lukewarm water into a pan in the sink. Take the stained plates and transfer the stain from them into an additional six plates. Rinse the stained plates upside down in the pan to prevent the colonies from loosening and washing off. 3. Continue steps 1 and 2 until all the plates have been stained. Let the plates air-dry overnight; they will be ready for counting the next day (see Note 4).

3.5. Counting of Colonies 1. Take the air-dried colonies and count the colonies in each dish to obtain the plating efficiency. We use a dissecting scope to view the colonies under a magnified field. A cluster of blue-staining cells is considered a colony if it comprises at least 25–50 cells. However, it is important to keep the cutoff constant so that there are no variations introduced between experiments. Count the colonies and note the numbers for both the A and B dilutions in a chart (prepare one similar to the one shown in Fig. 2). 2. Average the three colony counts for each dilution A and B and divide the mean by the number of cells plated. This will give the PE: Number of colonies counted PE = ———————————— × 100 Number of cells plated The PE of some cells may be close to 80–90%. This is especially true for human tumor cells of various origins. However, the PE of normal human fibroblasts is usually very low (ranging from as low as 1 to 12–15%). 3. Following determination of PE, calculate the fraction of cells surviving a given treatment. First, normalize all the plating efficiencies of the treated samples to that of the control unirradiated plates, considering that to be 100%. The surviving fraction (SF) is determined by dividing the PE of the treated cells by the PE of the controls, and then multiplying by 100: PE of treated sample SF = —————————— × 100 PE of control Plot the data on an Excel spreadsheet with the dose of radiation on the x-axis and survival on the y-axis.

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4. Notes 1. The CO2 requirement may vary depending on the cell type. If the flasks have lids with a membrane that allows gas exchange, there is no need to loosen the cap. 2. Note that you can use prior cell survival data, if available, to extrapolate exactly the number of cells to plate for a desired colony count. 3. If possible, it is a good idea to dedicate an incubator to clonogenic cell survival. This avoids unnecessary bumping of colonies as people open and close the door to the incubator. As the colonies grow, bumping the incubator or shelf can cause the cells to shed and settle as new colonies, thereby leading to an increase in the colony count and erroneous results. 4. We usually do not pour the used stain down the sink but, instead, collect it in a bottle dedicated to spent stain.

References 1. Elkind, M. E. and Whitmore, G. F. (1967) In vitro survival curves, in The Radiobiology of Cultured Mammalian Cells, Gordon and Breach, New York, NY, pp. 53–115. 2. Hall, E. J. (2000) Cell survival curves, in Radiobiology for the Radiologist, 5th ed. (Hall, E. J., ed.), Philadelphia, J.B. Lippincott, pp. 32–50. 3. Elkind, M. M and Sutton, H. (1960) Radiation response of mammalian cells grown in culture. I. Repair of X-ray damage in surviving Chinese hamster cells. Radiat. Res. 13, 556–593. 4. Elkind, M. M., Han, A., and Volz, K. W. (1963) Radiation response of mammalian cells grown in culture. IV. Dose dependence of division delay and postirradiation growth of surviving and non surviving Chinese Hamster cells. J. Natl. Cancer. Inst. 30, 705–721. 5. Sinclair, W. K. and Stroud, A. N. (1962) Postirradiation changes in growth, chromosome number and survival properties of cultures of Chinese hamster cells [abstract]. Radiat. Res. 16, 590. 6. Puck, T. T. and Marcus, P. I. (1956) Action of X-rays on mammalian cells. J. Exp. Med. 103, 653–666. 7. Sinclair, W. K. (1964) X-ray induced heritable damage (small-colony formation) in cultured mammalian cells. Radiat. Res. 21, 584–611. 8. Whitfield, J. F. and Rixon, R. H. (!960) Radiation resistant derivatives of L strain mouse cells. Exp. Cell Res. 19, 531–538. 9. Barendsen, G. W., Beusker, T. L. J., Vergroesen, A. J., and Budke, L. (1960) Effects of different ionizing radiations on human cells in tissue culture. II. Biological experiments. Radiat. Res. 13, 841–849. 10. Alper, T., Gillies, N. E., and Elkind, M. M. (1960) The sigmoid survival curve in radiobiology. Nature 186, 1062–1063.

3 High-Sensitivity Cytotoxicity Assays for Nonadherent Cells M. Jules Mattes Summary High-sensitivity cytotoxicity assays refer to assays that can detect high levels of cell kill, to many powers of 10, and that can detect, ideally, a single remaining viable cell. Two such assays are described here, which have been used with Raji B-lymphoma cells, and are applicable to other nonadherent target cells. The first is a cell-counting assay, performed over a 3-wk period, which provides a simple, reliable, and sensitive assay of cytotoxicity. By determining the time required for 16-fold multiplication, the apparent fraction surviving can be calculated. This assay does not correct for treatment-induced delays in cell division and is dependent on maintaining the cells in exponential growth. The second assay measures colony-forming units using a limiting dilution method. Feeder cells are required to obtain a high cloning efficiency. Each dilution is plated in 48 wells of a 96-well plate, and positive wells are scored rapidly, by eye, after two wk.

Key Words Cytotoxicity; limiting dilution; B-cell lymphoma.

1. Introduction A high-sensitivity cytotoxicity assay refers to an assay that can detect high levels of cell kill, to many powers of 10. Such assays can detect a single remaining viable cell, or at least a small number of viable cells. They are important in cancer research, because high levels of cell kill are required in order to have a significant therapeutic effect; a cell kill of 90%, e.g., would be expected to prolong survival for only a few days for rapidly growing tumor cells. In this chapter, I describe two assays that have been used to measure cytotoxicity with radiolabeled antibodies (Abs). These assays can be used to monitor the cytotoxicity of any type of toxic agent. The first is based on cell counts; because the counts are continued for 21 d, a single viable cell can be readily detected. The advantages of this assay are its simplicity and its reliability, but it might be From: Methods in Molecular Medicine, vol. 110: Chemosensitivity: Vol. 1: In Vitro Assays Edited by: R. D. Blumenthal © Humana Press Inc., Totowa, NJ

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considered less accurate than a limiting dilution clonogenic assay, which is the second assay described. Two factors can be considered to limit the value of the cell-counting assay. First, the assay does not consider growth delay that may result from sublethal treatment. For this reason, it may overestimate the fraction of cells that are killed. However, this does not represent a lack of accuracy, only a problem in interpretation, and the problem is solved by recognizing that the end point is not “fraction surviving” but, rather, “apparent fraction surviving.” Second, and more important, is the fact that the calculations assume that the cells are dividing at a constant rate. In fact, doubling times, at least with the cell lines my laboratory has used, are sensitive to small variations in the culture medium, and only very dilute cells truly grow exponentially. As the cell density increases, growth rate decreases. Therefore, the calculated time interval required for 16fold multiplication of the cells, which is the basis for calculations, depends, to some extent, on variables such as the day of the week that the experiment was started, because for experiments started on Monday, cells counts are obtained on d 2, 4, and 7, and for experiments started on Tuesday, cell counts are obtained on d 2 and 6, and for experiments started on Wednesday, cell counts are obtained on d 2 and 5. Since control cells multiply 16-fold in 4 to 5 d, depending on the experiment, and are relatively dense at that time, the growth rate is often significantly lower by d 5. Therefore, this factor will affect the calculated doubling time, which will, in turn, affect the calculation of the apparent fraction surviving. The calculated doubling time of Raji cells using the method described herein varied from 20 to 28 h; in other experiments, in which the cell density was very low, doubling times of 14.4 h have been observed. Another variable is that killed cells (meaning cells that are unable to divide) are often still metabolically active and may become markedly enlarged. Such metabolic activity will affect the growth rate of the remaining viable cells. Both of these problems could be circumvented by maintaining the cells at a lower concentration and by counting them more frequently, but both of these changes would diminish the convenience of this assay. For these reasons, the limiting dilution assay was developed. Although the limiting dilution assay provides greater accuracy, it does require considerably more work than the cell-counting assay, and it should be emphasized that the cell-counting assay is reliable and useful for many purposes. 2. Materials 1. Raji human B-lymphoma cell line (American Type Culture Collection, Rockville, MD). 2. RPMI-1640 medium with 12.5% fetal calf serum, supplemented with penicillin, streptomycin, glutamine, and pyruvate (Life Technologies, Grand Island, NY).

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3. Phosphate-buffered saline (PBS) (Dulbecco’s PBS without calcium and magnesium, cat. no. D5652; Sigma, St. Louis, MO). 4. Trypan blue (Eastman Kodak, Rochester, NY). 5. Mitomycin C (M4287; Sigma). 6. Hemacytometer, Bright-line (cat. no. 15170-172; VWR, West Chester, PA). 7. Plate-reading mirror (Bel-Art, Pequannock, NJ). 8. Sterile syringe filter, 0.2-µm pore size, Corning cat. no. 431219 (purchased from VWR).

3. Methods 3.1. General Methods The cells are split every 3 to 4 d, generally 110 or 120, and thus are under conditions of exponential growth. Cells are tested routinely for mycoplasma contamination with the Mycotect Assay (Life Technologies). Abs used include Abs to CD74, CD20, and major histocompatibility complex class II and have been described previously (1). Radiolabeling with 125I, 131I, 111In, 67Ga, or 90Y was also described previously (2). Ab solutions are sterilized by passage through a 0.2-µm-pore-size sterile syringe filter. 3.2. Cell Counting Assay (3) 1. Pellet 4.5 × 106 cells (600g, 5 min) and resuspend in 6 mL of tissue culture medium. 2. Add 1.1 mL of this suspension to 2.2 mL of radiolabeled Ab at the desired concentration. The Ab concentrations used in our studies were usually based on the concentration of radioactivity (microcuries per milliliter), but never exceeded 5 µg/mL, a near-saturating concentration. Generally, three-fold dilutions of Ab are tested, and four Ab concentrations are tested in each experiment. Note that the Ab is diluted 23 due to the addition of the cell suspension. A control tube has no Ab. 3. Plate the cells from each tube in two wells of a 24-well plate, with 1.5 mL/well. The wells used are dispersed in the plate (leaving empty wells between the wells that are used), to reduce any chance of “crossfire” of radiation between the adjacent well; however, no significant crossfire between adjacent wells was detected in experiments using 131I, intentionally designed to detect it. 4. Count viable cells in the remainder of the control sample after plating; the nominal cell concentration is 2.5 × 105 cells/mL. Use a twofold dilution (using 50 µL of the cell suspension) with Trypan blue solution (0.1% [w/v] Trypan blue in PBS), which stains dead cells, for counting in a hemacytometer. 5. Count viable cell counts at d 2. Suspend the cells by repipetting with a Pasteur pipet, and dilute 30 µL with an equal volume of Trypan blue solution. 6. Transfer the entire contents of each well into a T30 flask containing 20 mL of medium. This transfer is required in order to maintain the cells in exponential growth. Thus, Ab is kept in the medium for the duration of the experiment, but it is diluted approx 14-fold on d 2, so most of the uptake is in the first 2 d.

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7. Count viable cells every 2–5 d thereafter, out to 21 d or until the cells have multiplied 16-fold. At each time point, count one of the two duplicates and alternate the particular sample counted in subsequent counts, to ensure that the duplicates behave similarly. This has always been the case, except for some samples in which near-complete kill was obtained (see example in ref. 3), in which case variation between the duplicates would be expected to occur sometimes. For the cell count, count either 100 cells or all nine large squares on the hemacytometer (for cases in which the cell count is low). In certain cases, in which partial toxicity occurs, the medium can turn yellowish and cell growth can slow before 16-fold multiplication is attained. In such cases, dilute an aliquot of cells (usually 4 mL) fivefold in order to maintain the cells in exponential growth (see Note 1). 8. Calculate the apparent percentage cell kill from the growth curves. This calculation does not take into account any delay in cell division resulting from irradiation. Such delays in division are known to occur in many cases (4,5), so the calculation may overestimate the percentage kill; therefore, the calculated value is designated the “apparent” cell kill. More specifically, the time required for 16-fold cell multiplication is determined in control wells and in treated wells. This time interval is calculated by interpolation from the two points on either side of 16-fold multiplication, using a semilog graph of cell number vs days. The value from control wells, in each experiment, is used to calculate the doubling time. The time required for treated cells to multiply 16-fold is expressed in doubling times and is designated TR (time required). The fraction surviving = 1/2(TR4) (see Note 2). Representative results are given in Fig. 1, which shows toxicity with 90Y-labeled Abs (2). Figure 1A shows the growth curves, and Fig. 1B shows the graph of the calculated fraction surviving as a function of the initial microcuries per milliliter in the medium.

3.3. Limiting Dilution Clonogenic Assay (2) (see Note 3) Cells are incubated for 2 d with serial dilutions of radiolabeled Ab, exactly as decribed above. Typically three, twofold dilutions of each Ab are tested. The range of concentrations tested is selected to include the concentration at which the cell kill is approx 99–99.9% (based on the cell-counting assay described in Subheading 3.2.). This level of killing is selected to allow accurate comparison of potent cytotoxic Abs. Cells from one well of a 24-well plate are used for the clonogenic assay. 1. Count viable cells in one well of each group, using an aliquot of 30 µL. 2. Dilute the remaining cells with 17.3 mL of tisue culture medium. 3. Prepare fourfold serial dilutions by transferring 4.7 mL into 14.1 mL of medium; make a total of eight dilutions. 4. Add to each dilution 0.9 mL of “feeder cells.” This was found to markedly improve the cloning efficiency. The feeder cells are prepared as described in Subheading 3.4. A control tube has only feeder cells; there should be no growth of only the feeder cells.


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Fig. 1. (A) Toxicity of 90Y-LL1 (anti-CD74) for Raji cells (solid symbols) in comparison with the nonreactive control Ab MN-14 labeled in the same way (open symbols). Cells were incubated for 2 d with radiolabeled Ab at a starting concentration of 20 µCi/mL (circles), 10 µCi/mL (squares), 5 µCi/mL (triangles), or 2.5 µCi/mL (inverted triangles). The growth rate of control, untreated cells is also shown (dotted line without symbols). The data shown are calculated from cell counts obtained at various times and are representative of two experiments, each done in duplicate. Cells treated with the highest concentration of LL1 were 100% killed, since no viable cells were detected after d 6, and growth of a single viable cell would be readily detected in 22 d. (B) The fraction surviving was calculated from the growth curves and plotted vs the initial microcuries per milliliter for LL1 () or the nonreactive control Ab (). One hundred percent killing cannot be shown on the exponential y-axis, but the nexthigher concentration of 90Y-LL1, 20 µCi/mL, produced 100% killing. The results shown are representative of two experiments, each done in duplicate. Other experimental details were described previously (2). (Reprinted by permission of the Society of Nuclear Medicine from ref. 2.)

5. Plate each dilution of treated cells plus feeder cells in 48 wells of a 96-well plate, with 0.2 mL/well. Therefore, approx 104 feeder cells are plated per well (see Note 4). 6. Incubate for 14 d at 37°C in a humid incubator with 5% CO2. 7. Using the plate reader, count the number of wells with growing clones. These wells are easily recognized by their yellow color and by the large, dense colony

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or colonies of cells that are seen, by eye, at the bottom of the well. Control clones are large and countable after 12 d, but the irradiated cells grow more slowly, so two additional days are allotted (see Note 5). 8. Calculate the number of colony-forming units per milliliter. This can be done in various ways. In our published studies to date, we calculated the average number of cells per well as –ln(FN), in which FN = the fraction of wells that are negative (6,7). Dilutions at which 10–90% of the wells were negative were used for calculations. By multiplying by the dilution factor, and by a factor of 1.33 (since one-fourth of the total cells was used for the serial dilutions), the number of clones in the original well is calculated. If more than one dilution gives results within the usable range (10–90% of the wells negative), then the mean of the individual values is used. A better method of calculation is via the QUALITY program that is on-line at http://ubik.microbiol.washington.edu/computing/ (using the Java applet). This program gives the concentration of colony-forming units per 0.2 mL (the volume plated per well) and standard deviation using the χ2 method of Taswell (8). The difference between the two methods of calculation, in our experiments, is minor (see Note 6). 9. Calculate the cloning efficiency of the control, untreated cells from the cell count at d 2 and the calculated number of colony-forming units. This value ranged from 35 to 94% in our experiments.

3.4. Preparation of Feeder Cells for Limiting Dilution Assay 1. Prepare 2.3 × 107 Raji cells in 2.3 mL of tisue culture medium (see Note 7). 2. Add 0.23 mL of mitomycin C at 0.5 mg/mL in 10 mM sodium phosphate buffer, pH 7.6. To prepare the mitomycin C (1.0 mg/vial), dissolve in 2.0 mL of 10 mM sodium phosphate buffer, pH 7.6, and freeze aliquots of 0.23 mL at –70°C. Use one tube for each experiment. 3. Incubate for 45 min at 37°C, with mixing every 15 min. 4. Pellet the cells and wash three times with 10 mL of tissue culture medium. Then suspend in 26.6 mL.

4. Notes 1. The fact that the cells are examined under a microscope can be considered an advantage of the cell-counting assay, because additional information is obtained. Heavily irradiated cells, which subsequently die, become very large. This was unmistakable at d 5 and was also evident at d 2. Hence, by noting the size of the cells, the level of toxicity could be reliably estimated at d 5, even though the assay would not be completed for another 11 d. However, the need for cell counts might also be considered a disadvantage, because this is time-consuming. As an alternative, it is possible to use any type of automated cell-counting method. Some of these methods would also be able to detect the increase in the size of the cells. However, visual counting is best able to count samples in which considerable cell


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clustering occurs; although it is simple to count small clusters (of 5 cells) by eye, none of the automated counting methods can do this. This is a significant factor, because most of the B-lymphoma cell lines that we have used, e.g., normally form clusters, which may be large. Although such clusters are readily dispersed by repipetting, they also may re-form rapidly, and it is difficult to exclude the possibility that clusters may be present. Calculations for the cell-counting assay are correct only if the cells are maintained in exponential growth and if the treatment does not affect the growth rate. The latter is probably not correct, because it is known that radiation induces growth delay (4,5). Therefore, the level of toxicity observed is the “apparent” cell kill. For this reason, the calculated level of cell kill is sometimes higher than is possible. For example, a fraction surviving of 10–8 or 10–7 has sometimes been calculated in an assay in which only 5 × 105 cells were used. This can be attributed to growth delay. The selection of 16-fold multiplication as the end point is arbitrary but was chosen for practical and theoretical reasons. A few cell divisions might, in some case, be compatible with eventual cell death, but if the cells can multiply 16-fold (four divisions), then it seems reasonable to conclude that the cells can multiply indefinitely. To extend the assay to greater than 16-fold multiplication would require more medium and larger volumes, in order to keep the cells in exponential growth. The limiting dilution clonogenic assay was developed to provide greater accuracy in the measure of the fraction surviving. For example, we wanted to determine the number of radioactive decays required for a particular level of cell kill, and to compare this value for different radionuclides. Since the actual difference between some of the radionuclides tested was small, this comparison requires a high level of accuracy. Representative results are shown in Fig. 2. When the same experiments were performed using the cell-counting assay, which was done previously, the variation among individual, identical experiments was greater. This difference appeared to be due to variation in the calculated fraction surviving, rather than to variation in the decays per cell. These data, then, support our contention that the limiting dilution assay provides greater accuracy than the cell-counting assay. The number of dilutions plated can be reduced somewhat, since those dilutions at which all or none of the wells are positive are not important in the calculations. Thus, for the control cells, it is necessary to plate only dilutions no. 5–8. For the treated cells, it is sufficient to plate seven dilutions, since low levels of cell kill are of little interest. Nonadherent cells such as Raji form dense colonies in the wells, which are readily identified by eye. Moreover, the color of the medium distinguishes wells containing clones, because it changes from pink to yellow. Therefore, wells with growing clones are readily counted, in a few minutes. This is in contrast to results that would be obtained with most adherent target cells: these cells form monolayers, which are not evident by eye, and which often do not turn the medium yellow. Thus, doing this assay with adherent cells would require either microscopic observation of each well or some type of staining procedure to make the cells more visible.

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Fig. 2. Relationship between fraction surviving and total disintegrations per cell. Raji cells were incubated with radiolabeled LL1 (anti-CD74) for 2 d, and the fraction surviving was determined by a limiting dilution clonogenic assay. Cell-bound counts per minute were determined at d 1, 2, 3, and 6, or d 1, 2, and 5, and the cumulative disintegrations per initial cell number were calculated. The results are shown for 90Y (), 131 I (), 125I (), 111In (), and 67Ga (). Note that open symbols represent β-particle emitters, and solid symbols represent Auger electron emitters. The results shown are representative of two experiments performed with each radiolabel. Other experimental details were described previously (2). (Reprinted by permission of the Society of Nuclear Medicine from ref. 2.)

6. Statistical analysis of limiting dilution assays is relatively complex. In our published data, we calculated the concentration of colony-forming units per milliliter using the formula given under Subheading 3.3., step 8. The means and standard deviations of the fraction surviving were calculated from replicate experiments, and statistical comparisons between two treatment groups could then utilize student’s t-test. However, there are more sophisticated methods of calculation and error analysis (6–11). Although we are not aware of commercial software that performs these calculations, a program on the Internet is available, as described under Subheading 3.3., step 8. This program uses the χ2 method of Taswell (8). Although it has been argued that the maximum likelihood method is optimal (11), the difference between these two methods is small (11), and we are not aware of readily available software that utilizes the maximum likelihood method. A calculation method that can more readily be done manually, because it does not require iterative calculations, is the weighted mean method of Taswell (8). 7. The feeder cells that we have used are the same cells used as targets but treated with mitomycin. Cloning efficiency was approx 10-fold lower in the absence of feeder cells. Since our cloning efficiency with Raji cells was usually >50%, we


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can conclude that the feeder cells used were adequate. However, different target cells may require different types (or different amounts) of feeder cells. Although it is often convenient to use the same cell line as both target and feeder, this may not always be optimal. Some target cells may not require feeder cells at all. Such determinations can only be made by trial and error.

Acknowledgments We are grateful to Rosana B. Michel for technical support and to Dr. Andre Rogatko for assistance with the statistics. This work was supported in part by USPHS grant CA87059 and USDOE grant ER63191. References 1. Ong, G. L., Elsamra, S. E., Goldenberg, D. M., and Mattes, M. J. (2001) Singlecell cytotoxicity with radiolabeled antibodies. Clin. Cancer Res. 7, 192–201. 2. Govindan, S. V., Goldenberg, D. M., Elsamra, S. E., Griffiths, G. L., Ong, G. L., Brechbiel, M. W., Burton, J., Sgouros, G., and Mattes, M. J. (2000) Radionuclides linked to a CD74 antibody as therapeutic agents for B-cell lymphoma: comparison of Auger electron emitters with beta-particle emitters. J. Nucl. Med. 41, 2089–2097. 3. Griffiths, G. L., Govindan, S. V., Sgouros, G., Ong, G. L., Goldenberg, D. M., and Mattes, M. J. (1999) Cytotoxicity with Auger electron-emitting radionuclides delivered by antibodies. Int. J. Cancer 81, 985–992. 4. Little, J. B. and Williams, J. R. (1977) in Handbook of Physiology, Sect. 9 (Lee, D. H. K., Falk, H. L., Murphy, S. D., and Geiger, S. R., eds.), American Physiological Society, Bethesda, MD, pp. 127–155. 5. Warters, R. L. and Hofer, K. G. (1977) Radionuclide toxicity in cultured mammalian cells. Elucidation of the primary site for radiation-induced division delay. Radiat. Res. 69, 348–358. 6. Finney, D. (1978) Statistical Methods in Biological Assay, 3rd ed., Charles Griffin & Co., London. 7. Fazekas de St. Groth, S. (1982) The evaluation of limiting dilution assays. J. Immunol. Methods 49, R11–R23. 8. Taswell, C. (1981) Limiting dilution assays for the determination of immunocompetent cell frequencies. I. Data analysis. J. Immunol. 126, 1614–1619. 9. Johnson, E. A. and Brown, B. W. (1961) Biometrics 27, 79–88. 10. Lefkovits, I. and Waldmann, H. (1979) Limiting Dilution Analysis of Cells in the Immune System, Cambridge University Press, Cambridge. 11. Strijbosch, L. W. G., Buurman, W. A., Does, R. J. M. M., Zinken, P. H., and Groenewegen, G. (1987) Limiting dilution assays. Experimental design and statistical analysis. J. Immunol. Methods 97, 133–140.

4 Sulforhodamine B Assay and Chemosensitivity Wieland Voigt Summary The sulforhodamine B (SRB) assay was developed by Skehan and colleagues to measure drug-induced cytotoxicity and cell proliferation for large-scale drug-screening applications. Its principle is based on the ability of the protein dye sulforhodamine B to bind electrostatically and pH dependent on protein basic amino acid residues of trichloroacetic acid–fixed cells. Under mild acidic conditions it binds to and under mild basic conditions it can be extracted from cells and solubilized for measurement. Results of the SRB assay were linear with cell number and cellular protein measured at cellular densities ranging from 1 to 200% of confluence. Its sensitivity is comparable with that of several fluorescence assays and superior to that of Lowry or Bradford. The signal-to-noise ratio is favorable and the resolution is 1000–2000 cells/well. It performed similarly compared to other cytotoxicity assays such as MTT or clonogenic assay. The SRB assay possesses a colorimetric end point and is nondestructive and indefinitely stable. These practical advances make the SRB assay an appropriate and sensitive assay to measure drug-induced cytotoxicity even at large-scale application.

Key Words Sulforhodamine B; trichloroacetic acid; optimal cell number; cytotoxicity.

1. Introduction The sulforhodamine B (SRB) assay as first described by Skehan and colleagues was developed for use in the disease-orientated, large-scale anticancer drug discovery program of the National Cancer Institute (NCI) that was launched in 1985 (1). The SRB assay is based on the ability of the SRB dye to bind electrostatically and pH dependent on protein basic amino acid residues. Under mild acidic conditions, SRB binds to protein basic amino acid residues of trichloroacetic acid (TCA)–fixed cells. It can be quantitatively extracted from cells and solubilized for optical densitiy (OD) measurement by weak bases such as Tris base. Results of the SRB assay were linear with the number of From: Methods in Molecular Medicine, vol. 110: Chemosensitivity: Vol. 1: In Vitro Assays Edited by: R. D. Blumenthal © Humana Press Inc., Totowa, NJ

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cells and the cellular protein measured at cellular densities in 96-well microtiter plates ranging from 1 to 200% of confluence (1). The sensitivity of the SRB assay is comparable with that of several fluorescence assays and is superior to that of Lowry or Bradford. It has a signal-to-noise ratio at 5000 cells/well of 4.83 and a resolution of 1000–2000 cells/well (1). The end point of the SRB assay is colorimetric, nondestructive, and indefinitely stable. The SRB assay represents an appropriate and sensitive assay to measure drug-induced cytotoxicity and is useful to quantify clonogenicity. In addition, the SRB method is rapid and inexpensive. In comparison with tetrazolium assays [2,3-Bis (2-methoxy-4-nitro-5-sulfophenyl)-2H-tetrazolium-5-carboxanilide (XTT) or 3-(4,5-dimethylthiazolyl-2)-2,5-diphenyltetrazolium bromide (MTT) assay] or clonogenic assay, the SRB assay performed similarly when data were limited to the inhibitory 50% concentration (IC50) (2–5). More important, since the endpoint measurement is not time critical, the SRB assay possesses practical advantages over the tetrazolium assays. Once automated using a microplate washer and microplate reader, it is suitable for high-throughput screening approaches. SRB is an anionic bright pink aminoxanthene protein dye with two sulfonic groups. Its molecular formula and molecular weight are C27H30N2O7S2 and 558.66, respectively. The optimal wavelength for measurement of the OD of SRB is 564 nm. Curves of OD vs dye concentration were linear up to 1.5–2 OD units. When linearity range is exceeded, it is necessary to dilute an aliquot or to use a suboptimal wavelength (490–550 nm). SRB fluoresced with laser excitation at 488 nm, and measuring SRB fluorometrically increases sensitivity about threefold (1). When establishing the SRB assay, Skehan et al. (1) determined the SRB binding as a function of time, dye concentration, number of destaining washes, and dye volume per unit area of cell culture. Based on their results, it is recommended that a 96-well culture plate be stained with 100 µL of 0.4% SRB solution per well for 30 min. The number of acetic acid washes to remove unbound dye should be at least four (1). Most researchers use the IC50 as a measure of in vitro cytotoxicity. This is defined as the concentration that yields 50% less cells than the drug-free control. At the NCI, the GI50 (concentration that causes 50% growth inhibition) was defined. The GI50 is corrected for the cell count at time zero (start of drug exposure) and follows the following equation: 100 × (T – T0) / (C – T0)

in which T is the OD after exposure to a certain concentration of a drug, T0 is the OD at the start of drug exposure, and C is the OD of the control. To present response patterns of a drug in a cell line panel such as the NCI 60 panel, a mean graph could be constructed (6).

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The clinical relevance of in vitro cytotoxicity data is a critical issue. To estimate potential clinical activity of a drug based on in vitro data, we and others defined the relative antitumor activity (RAA) as peak plasma concentration of a drug/IC50 (7). Overall, it is assumed that in vitro drug screening was approx 60% reliable for predicting in vivo sensitivity and 90% reliable for in vivo resistance. 2. Materials 2.1. Seeding of Microtiter Plates and Drug Exposure 1. 96-Well culture microtiter plates. 2. Conventional cell culture equipment and reagents such as cell culture microscope and cell incubator, sterile tubes (different sizes), growth medium and fetal calf serum (according to the requirements of cultured cell lines), trypsin. 3. Cell count chamber or other cell count device such as a Coulter counter. 4. Eight-channel multipipet. 5. Sterile gauzes. 6. Sterile plastic troughs.

2.2. SRB Procedure 1. 2. 3. 4. 5. 6. 7. 8.

10% (w/v) TCA. 1% Acetic acid. 0.4% (w/v) SRB dissolved in 1% acetic acid (store at 4°C protected from light). Eight-channel multipipet. 10 mM Unbuffered Tris base (pH 10.0). Deionized water. Automated microplate washer. Automated microplate reader (enzyme-linked immunosorbent assay [ELISA] reader).

3. Methods All cell culture work must be performed under sterile working conditions and under standard cell culture conditions (humidified air, 5% CO2, and 37°C) or adapted to requirements of the specific cell lines, if necessary. 3.1. Seeding of Microtiter Plates for Growth Kinetics For cytotoxicity experiments, it is critical to ensure exponential cell growth for the entire duration of the assay. In particular, this is dependent on the number of cells seeded per well in the microtiter plate at the initiation of the experiment. Therefore, prior to cytotoxicity experiments, it is important to determine the optimal cell count ensuring exponential cell growth for the entire period of the assay and an OD at the end of the experiment in a range of 1.5–2.0.

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3.1.1. Day 1 1. Harvest cells by trypsinization and determine the cell count according to standard cell culture procedures (see Note 1). 2. Seed serial dilutions of cells (should cover a broad range, e.g., 100–50,000 cells/ well) in microtiter plates in 100 µL of growth medium per well at d 1 (keep one eight-well row as a blank containing only growth medium, usually row 1). The number of culture plates seeded depends on the desired length of the cytotoxicity experiment (usually 5–7 d).

3.1.2. Day 2 1. Gently remove the growth medium of one culture plate (generally, we flip the culture plate and soak up residual medium with a sterile piece of gauze while keeping the culture plate upside down). 2. Fix cellular protein by the addition of 100 µL of 10% TCA (4°C) per well. 3. Add 100 µL/well of growth medium to the remaining plates only at this time point. 4. Stop another culture plate by fixating cellular protein as described in steps 1 and 2 every 24 h until all the plates are fixed. Fixed culture plates must be kept at 4°C for at least 1 h but can be stored for up to several days prior to analysis by the SRB assay (keep in mind that storage for several days may lead to a slight increase in background levels).

At this time point, perform the SRB assay as described next. Analyze OD values graphically as illustrated in Fig. 1. From these growth kinetics plots, the optimal number of cells per well can be depicted for use in further cytotoxicity experiments. 3.2. Choice of Drug Dose Range and Seeding of Culture Plates for Cytotoxicity Assays The design of the culture plates depends on the intended experiment. For example, for a regular dose-response curve of a single drug, rows 1 and 12 are kept as blank rows containing only growth medium (to determine the nonspecific background). The choice of doses to be tested and the exposure time to the drug are the most critical points. It is conventionally agreed that a drug, when singly administered, must be used at concentrations around the clinically achievable peak plasma concentration in cancer patients. Dose- and timeresponse curves must also be defined for each drug in order to identify the concentration and the exposure time capable of inhibiting cell growth by 50% (IC50). We usually do half log step dilutions, ensuring a homogeneous distribution of data points on the growth curve and coverage of a broad activity range (see Fig. 2). This further allows extrapolation of data concerning drug dose at high levels of activity, e.g., 90% of growth inhibition or higher.


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Fig. 1. Determination of optimal cell number per well for cytotoxicity experiments by cell growth kinetics. A typical cell growth kinetics is illustrated. Various numbers of cells/well were seeded in 96-well culture plates and fixed at the indicated time points. OD was measured at 570 nm subsequent to performing the SRB assay. OD values were evaluated graphically, and the optimal cell number for further growth experiments could be determined from the plots. According to the two criteria, exponential cell growth for the entire assay period and OD 1.5–2 at the end of the 120-h assay time, the optimal cell number for further cytotoxicity experiments is 1600 cells/well.

3.2.1. Day 1 1. Seed in 100 µL of growth medium a cell line–specific number of cells (see Subheading 3.1.) per well in 96-well culture plates. Include blanks depending on the experimental design, and allow 24 h of cell growth.

3.2.2. Day 2

Exponentially growing cells are exposed to serial dilutions of the drug for the desired times (we usually choose a 2- or 96-h drug exposure time). 1. Control cellular growth, distribution of cells in the well, and cellular density in different wells using a cell culture microscope (see Note 2). 2. Add 100 µL/well of drug-free growth medium to the blank and control rows (usually rows 1, 12, and 2 in our laboratory, respectively). 3. Add 100 µL/well of growth medium containing different drug concentrations to rows 3–11 (starting with the lowest concentration and finishing with the highest).

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4. Stop one culture plate per cell line to estimate the cell count/OD at the time of adding the drug (“zero h plate”). 5. Allow the cells to grow depending on the desired drug exposure time (e.g., 96 h). 6. Remove gently the growth medium by flipping the culture plate (be cautious; medium contains potentially toxic drugs). 7. Remove residual medium by utilizing a sterile piece of gauze while keeping the culture plate upside down. 8. Fix the cellular protein using 100 µL/well of 10% TCA (4°C), and store the plates at 4°C for at least 1 h prior to analysis by the SRB assay.

In contrast to the original method as described by Skehan and colleagues, we remove growth medium before the TCA fixation step because this significantly reduces the signal-to-noise ratio. Cell loss is negligible and assay results are unaffected (8). In the case of short-term drug exposure (e.g., 2 h), follow steps 6 and 7. Then include a washing step by adding 200 µL/well of either sterile growth medium or phosphate-buffered saline. Again perform steps 6 and 7. Subsequently, add 200 µL/well of complete growth medium and allow further cell growth for, e.g., 94 h to reach a total assay time of 96 h (see Note 3). Depending on experience and cell line characteristics, one may risk a high and variable cell loss during the washing procedure leading to high variations in the experimental data. In our hands, as determined by wash kinetics, cell loss approximates cell line dependence (10–20%). However, some cell lines might have an only weak attachment to the plastic bottom of the culture well and, thus, might be unsuitable for this kind of experiment. Using the washing procedure as described, one can expect a drug dilution of about 1400 to 11000, depending on the drain of residual medium or washing solution. Keep this in mind when using highly active drugs or cell cycle– specific drugs; the remaining substance could flaw the results. If this is a critical point in the experiment, consider including an additional washing step. However, this may increase cell loss significantly. 3.3. SRB Procedure The SRB assay outlined next represents the method described by Skehan and colleagues with minor modifications. Prior to beginning the SRB assay, cellular protein must be fixed with 10% TCA for at least 1 h at 4°C. 1. Rinse TCA using an automated 96-well plate washer and add five washing cycles using deionized water (200 µL/well). 2. Sharply flick the plates over a sink and remove roughly the residual wash solution with a piece of gauze. 3. Pipet 100 µL of SRB solution into each well of the culture plate using a multichannel pipet. Allow a 30-min staining period.


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4. Remove the SRB from the culture plates with an automated plate washer by five washing cycles using 1% acetic acid (remember to prefill the automated plate washer with the appropriate wash solution) (see Note 4). 5. Flick the culture plates over a sink and remove the residual wash solution with a piece of gauze. 6. Air-dry the culture plates until no further moisture is visible. (When air-dried, both TCA-fixed and SRB-stained culture plates can be stored indefinitely. Trissolubilized SRB is also stable for extended periods of time, provided that evaporation does not occur.) 7. Solubilize the protein-bound dye with 100 µL of 10 mM Tris base per well. Shake the plates for at least 10 min on a gyratory shaker to homogenize the dye solution. 8. Measure the OD by using an automated 96-well plate reader (ELISA reader) at a wavelength of 564 nm (see Note 5).

3.4. Data Processing and Interpretation of Results Generally, the reproducibility of the SRB assay is high and the standard deviation (SD) relatively low. Processing of the raw data can easily be performed by programs such as Excel or similar. It should include quality control of the data (SD? OD in correct range? [see Note 6]), subtraction of background staining, and subtraction of the OD at the time of adding the drug (“zero h plate”). The data of each eight-well row should be averaged and the SD calculated. Finally, the percentage of growth inhibition should be calculated as the percentage of the untreated control. We developed an Excel spreadsheet that processes the data as outlined in one step. Subsequently, plots of the processed data can be generated by graphic programs such as Sigma plot or similar. From these plots, one can graphically determine growth inhibitory concentrations such as IC50 (Fig. 2). Alternatively, mathematical curve fitting can be performed, which allows a more precise estimation of the IC50. Models used are often based on the Hill equation. The topic of curve fitting and estimation of drug interaction is not part of this protocol’s description. For extended reviews, see refs. 9 and 10. For clinical correlation of in vitro drug sensitivity data, we use the model of RAA (7). Potential clinical activity can be assumed if RAA exceeds 1. 4. Notes 1. It is important to obtain and maintain a homogeneous cell suspension. Cellular clumps/aggregates should be avoided. To disaggregate cells, it is often sufficient to pipet up and down the cell suspension with a regular cell culture pipet. Otherwise, we sometimes use a syringe and a 26-gauge needle. If this is still insufficient, changing the trypsinization procedure might help. Depending on the cell line used, one may have a varying fraction of dead cells. To estimate this fraction, we usually add Trypan blue when counting the cells in a cell chamber. It is advisable to correct the cell count according to the fraction of dead cells.

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Fig. 2. Graphic determination of IC50 from dose-response plots. A typical doseresponse plot is illustrated. For graphic determination of the IC50 (drug concentration that yields 50% less cells than the drug-free control), a bar (P) parallel to the x-axis and intersecting the point 50% on the y-axis was constructed. In the next step, a bar was plotted parallel to the y-axis that starts from the point of intersection of P with the dose-response plot. The IC50 could then be directly determined at the point of intersection with the x-axis.

2. To ensure optimal assay results and a low SD, it is important to have homogeneously distributed cells in a well and an approximately similar amount of cells in each well of each culture plate of the same cell line. Inhomogeneous cell distribution might be owing to the method of pipeting or unsuitable culture plates (the plastic of the culture plates is a critical issue in our opinion and should be kept constant for the entire experimental series). Sometimes it is useful to gently shake the plates on the shelf of the incubator after seeding. If the numbers of cells vary obviously between different wells, one should consider not continuing the experiment because of the high deviation that is to be expected. Reasons might be an inhomogeneous cell suspension while pipeting, a malfunction of the eightchannel multipipet, a bad batch of culture plates, or an early sign of microbiological contamination. 3. Try to pipet as gently as possible—this helps to reduce cell loss. Do not process too many plates per time, particularly while learning the assay; one may easily run out of time and not be able to hold the time points. Additionally, culture plates cool down while being stored in the hood and pH of the growth medium changes


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dramatically. Sometimes, it might be beneficial to store plates on a warming bench. 4. Carefully watch the cell monolayer at the bottom of the 96-well culture plates. If the needles of the 96-well plate washer are poorly adjusted, they may scratch the monolayer. This could result in partial or even complete loss of TCA-fixed cells. Sometimes, some needles of the plate washer become clotted with debris and so on. This may lead to inhomogeneous washing results. 5. If one does not have the appropriate filter for the microplate reader, measurements can be made at 570 nm or at a suboptimal wavelength ranging from 490 to 550 nm. 6. Usually, results of the SRB assay are highly reproducible. SD between independent experiments should not exceed 20–30%. SD of an eight-well row should not exceed 20% and is usually the highest in the range of the IC50. If the SD greatly exceeds these values, this may be caused by additional washing steps or problems outlined in Notes 1–4. The OD at the end of the experiment is a critical issue. First, measurement is not linear if OD values exceed 2. Second, if culture wells were overgrown, this may lead to exhaustion of growth medium, partial cell arrest, and cell death, particularly in control wells and wells with lower drug concentration. Taken together, this may lead to a significant change in IC50 (mostly an underestimation).

References 1. Skehan, P., Storeng, R., Scudiero, D., Monks, A., McMahon, J., Vistica, D., Warren, J. T., Bokesch, H., Kenney, S., and Boyd, M. R. (1990) New colorimetric cytotoxicity assay for anticancer-drug screening. J. Natl. Cancer Inst. 82, 1107–1112. 2. Rubinstein, L. V., Shoemaker, R. H., Paull, K. D., Simon, R. M., Tosini, S., Skehan, P., Scudiero, D. A., Monks, A., and Boyd, M. R. (1990) Comparison of in vitro anticancer-drug-screening data generated with a tetrazolium assay versus a protein assay against a diverse panel of human tumor cell lines. J. Natl. Cancer Inst. 82, 1113–1118. 3. Perez, R. P., Godwin, A. K., Handel, L. M., and Hamilton, T. C. (1993) A comparison of clonogenic, microtetrazolium and sulforhodamine B assays for determination of cisplatin cytotoxicity in human ovarian carcinoma cell lines. Eur. J. Cancer 29A, 395–399. 4. Griffon, G., Merlin, J. L., and Marchal, C. (1995) Comparison of sulforhodamine B, tetrazolium and clonogenic assays for in vitro radiosensitivity testing in human ovarian cell lines. Anticancer Drugs 6, 115–123. 5. Keepers, Y. P., Pizao, P. E., Peters, G. J., van Ark-Otte, J., Winograd, B., and Pinedo, H. M. (1991) Comparison of the sulforhodamine B protein and tetrazolium (MTT) assays for in vitro chemosensitivity testing. Eur. J. Cancer 27, 897–900. 6. Hodes, L., Paull, K., Koutsoukos, A., and Rubinstein, L. (1992) Exploratory data analytic techniques to evaluate anticancer agents screened in a cell culture panel. J. Biopharm. Stat. 2, 31–48.

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7. Voigt, W., Bulankin, A., Muller, T., Schoeber, C., Grothey, A., Hoang-Vu, C., and Schmoll, H. J. (2000) Schedule-dependent antagonism of gemcitabine and cisplatin in human anaplastic thyroid cancer cell lines. Clin. Cancer Res. 6, 2087–2093. 8. Papazisis, K. T., Geromichalos, G. D., Dimitriadis, K. A., and Kortsaris, A. H. (1997) Optimization of the sulforhodamine B colorimetric assay. J. Immunol. Methods 208, 151–158. 9. Berenbaum, M. C. (1989) What is synergy? Pharmacol. Rev. 41, 93–141. 10. Greco, W. R., Bravo, G., and Parsons, J. C. (1995) The search for synergy: a critical review from a response surface perspective. Pharmacol. Rev. 47, 331–385.

5 Use of the Differential Staining Cytotoxicity Assay to Predict Chemosensitivity Gertjan J. L. Kaspers Summary The differential staining cytotoxicity (DiSC) assay is one of the total cell-kill assays that can be used for drug resistance testing. Numerous publications have demonstrated the clinical value of chemosensitivity testing with that assay (and similar ones). The DiSC assay is successful in the majority of malignant samples of which the cells can be brought in suspension (not necessarily as single-cell suspension). Although the assay is laborious and requires skilled technicians, it requires few cells, can be used for proliferating and nonproliferating cell populations, and can discriminate between malignant and contaminating nonmalignant cells. The latter is a major advantage of the DiSC assay. This chapter describes the practical aspects of this assay, several topics that need to be taken into account, and potential pitfalls. As such, it is not an extensive review of studies in which the DiSC assay was used.

Key Words Differential staining cytotoxicity assay; dye exclusion assay; drug resistance; chemosensitivity testing; leukemia; solid tumors; childhood; prognosis; clonogenic assay.

1. Introduction The success of chemotherapy in cancer may be limited by at least three factors (1). First, unfavorable pharmakinetics may result in inappropriately low drug exposure of the malignant cells. Second, increased cellular drug resistance may explain the lack of total cell kill despite appropriate drug exposure. Third, increased regrowth potential of remaining minimal residual disease may result in a relapse. The extent of cellular drug sensitivity or resistance of malignant cells can be measured in vitro by different methods, and this provides clinically relevant information in numerous malignancies, including childhood leukemia (1–6). These different methods include clonogenic and nonclonogenic From: Methods in Molecular Medicine, vol. 110: Chemosensitivity: Vol. 1: In Vitro Assays Edited by: R. D. Blumenthal © Humana Press Inc., Totowa, NJ

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assays, as reviewed by several researchers (1,3,6–8). Clonogenic assays have the theoretical advantage that clonogenic cells are being studied, which might be the cells responsible for a possible relapse (a more frequent problem in, e.g., leukemia, in which an apparent complete remission normally is obtained, than in the case of more drug-resistant malignancies). However, they have disadvantages as well, such as having a (very) low plating efficiency and being very laborious and not highly reproducible. Moreover, several investigators have reported similar results using clonogenic and nonclonogenic assays (9–12). Therefore, nonclonogenic assays such as the differential staining cytotoxicity (DiSC) assay, tetrazolium-based colorimetric assays, and flow cytometry assays have recently been used more often. Several investigators reported similar results with different nonclonogenic assays under specific conditions, especially a high purity of the samples (13–16). Each assay has its own advantages and disadvantages, and pitfalls. This chapter focuses on the DiSC assay, based on dye exclusion assays, which was probably most well studied by Weisenthal et al. (e.g., see ref. 12), Bird et al. (17), and Bosanquet et al. (e.g., see ref. 2). The main advantages of the DiSC assay are that relatively few cells are needed (as compared with, e.g., colorimetric assays) and especially that the results can be determined regarding only the malignant cells. The latter is especially important in the case of a significant amount of contaminating nonmalignant cells, which cannot be discriminated with the often used colorimetric assays. Kaspers et al. (18) reported that in childhood acute lymphoblastic leukemia (ALL) samples, this became a significant problem in the case of more than 30% of contaminating nonmalignant cells in the control experiments at the time of the actual measurements, because contaminating nonmalignant cells are more drug resistant (19). The DiSC assay can overcome this problem. However, the DiSC assay is laborious and has several practical disadvantages and pitfalls, as described in Table 1. Nevertheless, the DiSC assay has provided clinically relevant information. Its results are therefore being used for risk-group stratified treatment of pediatric ALL cases (not eligible for the 3-(4,5-dimethylthiazolyl-2)-2,5-diphenyltetrazolium bromide [MTT] assay) in ongoing studies of the German COALL Study Group (20), and for DiSC assay–guided therapy in chronic lymphatic leukemia according to an MRC trial (21). These types of studies may demonstrate the clinical benefit of cellular drug resistance assays. 2. Materials 1. Lymphoprep (density: 1.077 g/mL; Axis-Shield, Norway), to isolate mononuclear or malignant cells by density gradient centrifugation. 2. Falcon polystyrene tubes, 14-mL (Becton Dickinson, Belgium) and 50-mL polypropylene tubes (Sarstedt, Germany).

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Table 1 Advantages and Disadvantages of DiSC Assaya Advantages Needs few cells, results within 4–7 d Discrimination between malignant and contaminating nonmalignant cells possible Clinically relevant correlations reported Not restricted to single-cell suspensions Suitable for different tumor types, and for both proliferating and nonproliferating cells

Disadvantages Laborious Discrimination sometimes difficult No proven benefit on patient survival No dose-dependent cytotoxicity for some drugs (e.g., methotrexate) (as with similar assays)

a

Note that other cellular drug resistance assays have partly similar disadvantages as well.

3. Immunomagnetic Dynabeads M-450 (Dynal, Norway) (18) to remove contaminating lymphocytes. 4. RPMI culture medium plus fetal calf serum (FCS) (Integro, The Netherlands) and appropriate supplements (e.g., insulin, glutamine, and transferrin) (see Note 1). 5. Anticancer agents (see Note 2). 6. 96-Well round-bottomed microculture plates (Greiner, The Netherlands). 7. Cytospin columns (Shandon, UK). 8. Duck red blood cells (DRBCs) (Sigma, The Netherlands). 9. May-Grunwald-Giemsa (MGG) (Merck, Germany). 10. Cytospin slides (Menzo & Gläzer, Germany). 11. Gauze with 70-µm pores (Becton-Dickinson).

3. Methods 3.1. Culture of Leukemic Samples 1. For isolation of leukemic cells, dilute bone marrow or peripheral blood 11 with RPMI-1640, or more in the case of >30 × 106 cells/mL. 2. Carefully layer up to 8 mL of the diluted sample onto 4 mL of lymphoprep at room temperature in a 14-mL Falcon tube. 3. Carry out density gradient centrifugation for 20 min (room temperature, at 540g) when cells are handled the same day as the sampling, or for 15 min (room temperature, at 380g) when cells are handled at least 1 d or later after sampling. The acceleration time is 90 s, the break at 3. 4. Collect the interphase cells in a 50-mL tube, and add wash medium (RPMI-1640 plus 1% heat-inactivated FCS [heat inactivation: incubation of FCS for 20 min at 56°C]) up to a maximum of 35 mL. 5. Take a sample of 100 µL for cell counting using 2% trypan blue (in phosphatebuffered saline [PBS]), to determine the percentage and total number of viable

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6.

7. 8.

9.

10.

11.

Kaspers cells, and to check the percentage of malignant cells after making a cytospin and MGG staining (see below). Meanwhile, centrifuge the tube at 540g for 10 min at room temperature, break 7 (mainly to remove contaminating platelets); remove the supernatant, and resuspend the pellet in wash medium (10–20 mL, depending on the amount of cells). Centrifuge the tube at 300g for 10 min at room temperature, break 5. Remove the supernatant and resuspend the pellet in culture medium (see step 9 and also Note 1). If one wishes to remove contaminating nonmalignant lymphocytes, then cells should be resuspended in culture medium: in the case of 20 × 106 cells, add 0.5 mL of culture medium; in the case of >20 × 106 cells, add 1 mL of culture medium. This procedure is a truly separate subject, and the reader is referred to ref. 18. Suspend leukemic cells in specific culture medium as described below, in the case of ALL at ±2 × 106 cells/mL, and in the case of acute myelogenous leukemia at 0.8–1.4 × 106 cells/mL (1.4 in the case of FAB type M0, M1, and M2). This can also be done with chronic myeloid and lymphocytic leukemia cells, at 1 and 2 × 106 cells/mL, respectively. It can be done with solid tumor cells as well, but we do not have enough experience with these specimens in the DiSC assay ourselves to advise on the cell concentrations needed. However, in the MTT assay, we use 0.5 × 106 cells/mL. If one aims at using the DiSC assay anyhow, the percentage of malignant cells does not matter at this point. Moreover, one may decide to use fewer cells, because the DiSC assay allows the detection of fewer cells. However, if one prefers the use of, e.g., the MTT assay if possible, removal of contaminating nonmalignant cells may be indicated. This is a separate procedure, and the reader is referred to ref. 18. Dispense 80 µL of the leukemic cell suspension into each well of the 96-well plates, except for the outer wells (evaporation, not reliable). Fill these outer wells with 100 µL of RPMI-1640. These wells already contain 20 µL of drug dilution (see Notes 3 and 4) (or RPMI-1640 in the case of the blanks), with the plates being stored at –90°C until use. Next the culture and drug exposure period follows (in our laboratory always 4 d, although this is not necessarily the “gold standard”). Determine the number of contaminating nonleukemic cells at the end of 4 d of culture after making four cytospins from this suspension. For this purpose, remove the cell suspension from the two lower control wells (i.e., the wells located at the greatest distance from the wells with the highest drug concentrations) of a plate. We always use the same plate (what we call plate I) for this purpose. Similarly, make a cytospin before culture to determine the percentage of malignant cells. For this purpose, make a cell suspension of 0.5 × 106/mL in PBS plus 0.1% bovine serum albumin (BSA) plus 5% human serum albumin (HSA). Prewet the cytospin slides in the cytospin centrifuge by adding one drop of PBS plus 0.1% BSA to each cytospin cup with a Pasteur pipet and centrifuge at 60g for a few seconds. Then add 50 µL of cell suspension to each cup, followed by one drop of PBS plus 0.1% BSA. Centrifuge at 60g for 7 min (low acceleration, no break).


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Air-dry the slides for several minutes before staining. For any immunocytochemical staining, the slides are first silicagel dried for at least 24 h. However, this discussion concerns determining the percentage of malignant cells. For that purpose, fix cytospin slides in 100% methanol for 3 min, subsequently stain in standard May–Grünwald solution for 3 min, rinse in tap water, stain for 10–15 min in Giemsa (time depending on the freshness of the solution; Giemsa is made fresh every week, diluted 120 in tap water), and rinse again with tap water. Dry the slides before microscopic evaluation. Then determine the percentage of malignant cells by microscopy.

3.2. DiSC Assay (see Notes 5 and 6) There are several important points to consider when using the DiSC assay, some of which are more in general relevant to all cell culture and total cell-kill assays, whereas others are more specific for the DiSC assay. Although the DiSC assay is labor-intensive and subjective, a main advantage is that malignant and contaminating nonmalignant cells can be discriminated. The results have been reported in numerous publications and appear to have clinical relevance in several aspects (2,3,22). A team of dedicated and experienced technicians and investigators is required for meaningful experiments with the DiSC assay. 1. After the 4 d of culture and drug exposure, remove the cell suspension from the two lower control wells (i.e., the wells at the greatest distance from the wells with the highest drug concentrations) of a plate. We always use the same plate (what we call plate I) for this purpose. If one wishes to perform the DiSC assay anyhow, independent from the percentage of malignant cells, this and step 2 are not necessary. 2. Use 50 µL of cell suspension for cytospin centrifugation and conventional MGG staining. (See Subheading 3.1., step 11 for an explanation of how to perform this procedure.) 3. If the sample shows 70% or less malignant cells, add 20 µL of DRBC suspension (see Note 6) to the remaining ±80-µL cell suspension, and make another cytospin slide and stain. The DRBC suspension is made by adding 0.5 mL of HSA, 0.5 mL of PBS, and 0.1 mL of DRBCs (10 × 106/mL) together and is used only after filtration through gauze with pores of 70-µm. This cytospin ideally shows about 20–30 leukemic cells/100 DRBCs, and the final amount of DRBC suspension to be added to all (except blank) wells is chosen such that this is achieved. This should be done as quickly as possible and with continuous mixing of the DRBC suspension. Aliquots from the wells are mixed and then cytocentrifuged at 690g for 7 min to deliver the cells onto cytospin slides that have been cleaned thoroughly with alcohol. After centrifugation, clean the equipment. 4. Air-dry the resultant cytospin slides, fix with methanol (100%), and counterstain with MGG (see Subheading 3.1., step 5).

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5. Have an experienced technician determine the ratio of living (MGG-stained) leukemic cells over DRBCs by using a light microscope and counting at least 300 (normally 500) DRBCs per slide (see Notes 7 and 9). The viable leukemic cells/DRBC ratio of a treated well is again expressed as the percentage of the untreated control wells and then called leukemic cell survival.

4. Notes 1. The culture medium being used depends on the type of cells being studied. In general, cell lines can be cultured in basic culture medium such as RPMI-1640 supplemented with 10% FCS (end concentration in the culture of 8%). Partly depending on how cells grow, other supplements can be added. Other researchers use serum-free culture medium, also for patient samples, partly depending on the type of study questions (23). In the case of patient cells, we normally use RPMI1640 (Gibco, Dutch modification, without L-glutamine) with 20% FCS in the cell suspension (end concentration in the culture of 16%), supplemented with 2 mM glutamine (Flow, The Netherlands), 5 µg/mL of insulin, 5 µg/mL of transferrin, and 5 ng/mL of sodium selenite (all from Sigma). To prevent culture infections, we also add 100 IU/mL of penicillin, 100 µg/mL of streptomycin, 0.125 µg/mL of fungizone, and 200 µg/mL of gentamycin (end concentrations in the culture medium; from Flow and ICN, The Netherlands). It may be easy to make 10-mL aliquots of penicillin, streptomycin, and fungizone and store these at –20°C. Similarly, one may decide to make 0.6- or 1.2-mL aliquots of insulin, transferrin, and sodium selenite. 2. Handling of these drugs is extremely important for reliable test results. Stability of the drug may depend on light exposure, temperature, solvents used, storage conditions of the drug and its stock solutions. 3. Some drugs may not show dose-dependent cytotoxicity in (mainly) nonproliferating cell cultures, especially methotrexate. This theoretically is also a problem for other drugs, of which the cytotoxicity might be circumvented by the uptake of specific counteracting products through one or more salvage pathways. However, this has not been convincingly demonstrated for drugs other than methotrexate and is not a problem in proliferating models such as cell lines (24). This problem is not unique for the DiSC assay but is relevant for all nonclonogenic total cell-kill assays. Sensitivity or resistance to methotrexate may be measured indirectly by the thymidylate synthase inhibition assay (24). 4. Drug instability is a concern for all in vitro drug resistance assays and should be taken into account. Bosanquet and Bell (25) have written an extensive review on this. Another pitfall is the use of nonactive (pro-) drugs such as prednisone instead of prednisolone, ifosfamide instead of 4-hydroperoxy-ifosfamide, and cyclophosphamide instead of mafosfamide. 5. The DiSC assay is laborious. This fact in itself makes it more appealing to use other assays, such as colorimetric or flow cytometric ones, provided that the malignant samples are pure enough (i.e., that the percentage of malignant cells is high enough). The procedure may improve by making multispotted cytospins, and


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by reducing the number of analyses, such as by calculating the number of living cells at only one drug concentration. Alternatively, one may quickly screen for the two drug concentrations at which the cell survival is just below and above 50%, respectively, to calculate an LC50 value without the need to actually determine cell survival at all drug concentrations. Under these circumstances, triple instead of duplicate experiments should be considered. The conditions when the DiSC assay would be recommended or preferred are highlighted in Table 1. 6. An internal standard is needed. Since dying and dead cells may disappear completely but unpredictably, it is important to include an internal standard in all wells, to avoid an underestimation of the cytotoxicity of a given drug. DRBCs are suitable. 7. Recognition of malignant cells can be difficult. Therefore, one needs dedicated and especially skilled and experienced technicians for the actual microscopic examinations, sometimes helped by the use of additional immunological stainings. This subjectivity also makes the DiSC assay less reproducible, especially if several technicians are involved in the analyses. 8. Infection is a problem not unique to the DiSC assay but may in fact occur in all cell culture assays. The routine prophylactic use of antibiotics and an antifungal drug in the culture medium is indicated.

Acknowledgments I thank all the research technicians who performed DiSC assays in the research laboratory of pediatric oncology at the VU university medical center (Amsterdam, The Netherlands), and A. H. Loonen for critical comments on the manuscript. References 1. Kaspers, G. J. L. and Veerman, A. J. P. (2003) Clinical significance of cellular drug resistance in childhood leukemia. Recent Results Cancer Res. 161, 196–220. 2. Bosanquet, A. G. (1991) Correlations between therapeutic response of leukaemias and in-vitro drug-sensitivity assay. Lancet 337, 711–714. 3. Freuhauf, J. P. and Bosanquet, A. G. (1993) In vitro determination of drug response: a discussion of clinical applications. Principles Pract. Oncol. 7(12), 1–16. 4. Kaspers, G. J. L., Veerman, A. J. P., Pieters, R., et al. (1997) In vitro cellular drug resistance and prognosis in childhood acute lymphoblastic leukemia. Blood 90, 2723–2729. 5. Kaspers, G. J. L., Zwaan, C. M., Veerman, A. J. P., et al. (1999) Cellular drug resistance in acute myeloid leukemia: literature review and preliminary analysis of an ongoing collaborative study. Klin. Pädiatr. 211, 239–244. 6. Veerman, A. J. P. and Pieters, R. (1990) Drug sensitivity assays in leukaemia and lymphoma. Br. J. Haematol. 74, 381–384.

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7. Pieters, R., Kaspers, G. J. L., and Veerman, A. J. P. (1997) Drug resistance culture assays in childhood leukemia: a review of the results and applications. Int. J. Pediatr. Hematol. Oncol. 4, 531–541. 8. Weisenthal, L. M. and Lippman, M. E. (1985) Clonogenic and non-clonogenic in vitro chemosensitivity assays. Cancer Treat. Rep. 69, 615–632. 9. Bird, M. C., Godwin, V. A. J., Antrobus, J. H., and Bosanquet, A. G. (1987) Comparison of in vitro drug sensitivity by the differential staining cytotoxicity (DiSC) and colony-forming assays. Br. J. Cancer 55, 429–431. 10. Carmichael, J., deGraff, W. G., Gazdar, A. F., Minna, J. D., and Mitchell, J. B. (1987) Evaluation of a tetrazolium-based semi-automatic colorimetric assay: assessment of chemosensitivity testing. Cancer Res. 47, 936–942. 11. Laurent, G., Kuhlein, E., Casellas, P., et al. (1986) Determination of sensitivity of fresh leukemia cells to immunotoxins. Cancer Res. 46, 2289–2294. 12. Weisenthal, L. M., Marsden, J. A., Dill, P. L., and Macaluso, C. K. (1983) A novel dye exclusion method for testing in vitro chemosensitivity of human tumors. Cancer Res. 43, 749–757. 13. Alley, M. C., Scudiero, D. A., Monks, A., et al. (1988) Feasibility of drug screening with panels of human tumor cell lines using a microculture tetrazolium assay. Cancer Res. 48, 589–596. 14. Finlay, G. J., Wilson, W. R., and Baguley, B. C. (1986) Comparison of in vitro activity of cytotoxic drugs towards human carcinoma and leukaemia cell lines. Eur. J. Cancer Clin. Oncol. 22, 655–662. 15. Pieters, R., Huismans, D. R., Leyva, A., and Veerman, A. J. P. (1989) Comparison of the rapid automated MTT-assay with a dye exclusion assay for chemosensitivity testing in childhood leukemia. Br. J. Cancer 59, 217–220. 16. Twentyman, P. R., Fox, N. E., and Rees, J. K. H. (1989) Chemosensitivity testing of fresh leukaemia cells using the MTT colorimetric assay. Br. J. Haematol. 71, 19–24. 17. Bird, M. C., Bosanquet, A. G., Forskitt, S., and Gilby, E. D. (1986) A novel dye exclusion method for testing in vitro chemosensitivity of haematological malignancies. Leuk. Res. 10, 445–449. 18. Kaspers, G. J. L., Veerman, A. J. P., Pieters, R., et al. (1994) Mononuclear cells contaminating leukemic samples tested for cellular drug resistance using the methyl-thiazol-tetrazolium assay. Br. J. Cancer 70, 1047–1052. 19. Kaspers, G. J. L., Pieters, R., Van Zantwijk, C. H., et al. (1991) In vitro drug sensitivity of normal peripheral blood lymphocytes and childhood leukaemic cells from bone marrow and peripheral blood. Br. J. Cancer 64, 469–474. 20. Janka-Schaub, G. E., Harms, D. O., den Boer, M. L., Veerman, A. J., and Pieters, R. (1999) In vitro drug resistance as independent prognostic factor in the study COALL-O5-92 treatment of childhood acute lymphoblastic leukemia; two-tiered classification of treatments based on accepted risk criteria and drug sensitivity profiles in study COALL-06-97. Klin. Pädiatr. 211, 233–238. 21. Bosanquet, A. G., Johnson, S. A., and Richards, S. M. (1999) Prognosis for fludarabine therapy of chronic lymphocytic leukaemia based on ex vivo drug response by DiSC assay. Br. J. Haematol. 106, 71–77.


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22. Staib, P., Lathan, B., Schinkothe, T., et al. (1999) Prognosis in adult AML is precisely predicted by the DISC-assay using the chemosensitivity-index Ci. Adv. Exp. Med. Biol. 457, 437–444. 23. Duyn, A. E. J., Kaspers, G. J. L., Pieters, R., et al. (1999) Effects of interleukin 3, interleukin 7 and B-cell growth factor on proliferation and drug resistance in vitro in childhood acute lymphoblastic leukemia. Ann. Hematol. 78, 163–171. 24. Rots, M. G., Pieters, R., Kaspers, G. J. L., et al. (1999) Differential methotrexate resistance in childhood T- versus common/pre-B acute lymphoblastic leukemia can be measured by an in situ thymidylate synthase inhibition assay, but not by the MTT assay. Blood 93, 1067–1074. 25. Bosanquet, A. G. and Bell, P. B. (1993) Handling requirements to achieve active drugs in in vitro drug sensitivity and resistance assays, in Drug Resistance in Leukemia and Lymphoma—The Clinical Value of Laboratory Studies (Kaspers, G. J. L., ed.), Harwood Academic, Chur, Switzerland, pp. 227–255.

6 Collagen Gel Droplet Culture Method to Examine In Vitro Chemosensitivity Hisayuki Kobayashi Summary For effective cancer chemotherapy, chemosensitivity testing of anticancer drugs should be performed using fresh surgical specimens obtained from the cancer. We have developed a new in vitro chemosensitivity test named the collagen gel droplet embedded culture drug sensitivity test (CD-DST). The CD-DST method consists of a collagen gel droplet embedded culture step, exposure and washout of anticancer drug, a serum-free culture step, and evaluation of anticancer effect by image analysis. This method has many advantages including a high success rate for primary culture, the need for only a small number of cells for the test, easy quantification of the anticancer effects without contamination with fibroblasts by using an image analysis system, a good correlation between in vitro and in vivo results, and simplicity and speed. The CD-DST method can be performed in the laboratory using a system kit Primaster®.

Key Words Collagen gel droplet embedded culture drug sensitivity test; anticancer agents; primary cancer cell; image analysis system.

1. Introduction For effective cancer chemotherapy, chemosensitivity testing of anticancer drugs should be performed using fresh surgical specimens obtained from the cancer. Various chemosensitivity tests have been developed and studied (1–16). However, none of these methods have been adopted clinically for various reasons. We have, therefore, developed an in vitro chemosensitivity test that satisfies the following requirements: a high success rate for primary culture, the need for a small number of cells for the test, easy quantification of the antitumor effects without contamination with fibroblasts, and a good correlation between the results of in vitro and clinical response. We have named this From: Methods in Molecular Medicine, vol. 110: Chemosensitivity: Vol. 1: In Vitro Assays Edited by: R. D. Blumenthal © Humana Press Inc., Totowa, NJ

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Fig. 1. Process of CD-DST method.

method the collagen gel droplet embedded culture drug sensitivity test (CDDST) (17–20) and reported its clinical usefulness (18–26). In this chapter, we report the protocol and major procedure (Fig. 1) of the CD-DST using fresh surgical cancer specimens. 2. Materials 1. Primaster® (Nitta Gelatin, Japan); this is composed of the following reagents: a. Collagen Drop Culture Kit (Cellmatrix Type CD, 10X F12 medium, Reconstitution Buffer). b. Cell Dissociation Enzyme EZ (Nitta Gelatin). c. CG (Collagen Gel-coated) Flask (Nitta Gelatin). d. Pre-Culture Medium PCM-1 (Nitta Gelatin). e. Serum-Free Medium PCM-2 (Nitta Gelatin). f. Neutral Red Solution (Nitta Gelatin). 2. DF(10) medium: DF medium with 10% fetal bovine serum, 100 µg/mL of penicillin, 100 µg/mL of kanamycin, and 10 mM HEPES buffer. 3. 1 mM EGTA (cat. no. 152-14; Nakarai Tesque, Japan). 0.03% trypsin (T-8003; Sigma-Aldrich Japan) solution.

CD-DST Method 4. 5. 6. 7. 8. 9. 10. 11. 12.

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10% Formalin neutral buffer solution (cat. no. 062-01661; Wako, Japan). Conical beaker covered with nylon mesh. Mild mixer (PR-12; Taitec Co., Japan). Apple PowerMacintosh G3 or G4. NIH-Image (Ver. 1.56) Macro (software). Gray-scale image digitizer (LG-3/PCI; Scion). Videomicroscope (VH-5910 + [VH-W50]; Keyence, Japan). Device for lighting (MegaLight100 + FGF6F1000-30 × 30, Hoya-Schott, Japan). Macro program Primage (for NIH-IMage) (Nitta Gelatin).

3. Methods 3.1. Collection of Primary Cancer Cells Using Cell Dissociation Enzyme EZ, it becomes possible to digest stroma from the tumor and dissociate tumor cells without any reduction in the viability of cancer cells in human tumor tissues. This enzyme maintains the viable cells better than when collagenase treatment is used to disrupt tumor tissues. This step is followed by growth of tumor cells on collagen gel–coated flasks (CG flasks) in PCM-1 medium, allowing living cells to adhere and selectively removing dead cells, blood, and noncell elements. 3.1.1. Pretreatment of Tumor Tissue 1. Transfer a tumor tissue specimen into a 10-cm plastic dish and add 10 mL of Hank’s solution. 2. Cut the tumor tissue into small pieces, approx 5 × 5 mm, using forceps and scissors. 3. Transfer the pieces of tissue into a new 10-cm dish and mince the pieces into paste form with a razor blade (see Note 1). 4. Add 10 mL of Hank’s solution to the paste form tumor, and disperse the tumor by pipetting.

3.1.2. Dissociation of Tumor Cells 1. Transfer all the tissue dispersion into a 50-mL centrifuge tube. 2. Add more Hank’s solution to a total volume of 30–45 mL. Spin the tube at 250g for 3 min. 3. Remove the supernatant, and add 5 mL of Dulbecco’s modified Ealge’s medium (DMEM) solution and 0.5 mL of Cell Dissociation Enzyme EZ to the pellet (see Note 2). Incubate for 2 h at 37°C with rotation (using a mild mixer) (see Note 3). 4. Remove the supernatant, and treat the pellet with EGTA-trypsin. 5. Add 30 mL of Hank’s solution. After pipetting gently, filter the cells through 300-µm nylon mesh overlaid on a conical beaker.

3.1.3. Preculture Using CG Flask 1. After centrifuging, remove the supernatant and add 5 mL of PCM-1 medium to the cell pellet and pipet gently to generate cell suspension.

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2. Inoculate 5 mL of the suspension into a 25-cm2 CG flask, and preculture for 12–24 h at 37°C in CO2 incubator.

3.1.4. Collection of Viable Cells 1. After culturing, remove the preculture medium in the CG flask. 2. Add 2 mL of DMEM solution and 100 µL of Cell Dissociation Enzyme EZ solution to the CG flask (the final concentration of the EZ solution is 0.05%), and shake the flask at 37°C. 3. When the gel in the CG flask has been completely dissolved, transfer the cell suspension in the flask into a 50-mL centrifuge tube and perform centrifugation. 4. Remove the supernatant, add 1 mL of EGTA-trypsin solution, and then filter the cell through using a conical beaker provided with 125-µm nylon mesh (see Note 4). 5. Repeat steps 3 and 4 twice, and then add 100–500 µL of DF(10) medium to the pellet.

3.2. Collagen Gel Droplet Embedded Culture Drug Sensitivity Test The CD-DST method is a new in vitro chemosensitivity test that combines the collagen gel droplet culture method and image analysis system. Cancer cells and fibroblast cells respectively show specific growth morphologies in the collagen gel droplet. The CD-DST method quantifies only cancer cells in the image by utilizing the differences of morphology and stains in the collagen gel droplet. 3.2.1. Collagen Gel Droplet Culture 1. Transfer 4 mL of Cellmatrix®-type CD into an ice-cold 50-mL centrifuge tube. Add 0.5 mL of 10X F-12 medium to the solution and mix well. Add 0.5 mL of reconstitution buffer to prepare a collagen mixture (see Note 5). 2. Add the cell suspension to the collagen mixture, and mix well (see Notes 6 and 7). 3. Place three droplets (30 µL/droplet) of the collagen mixture containing cells into each well of a six-well plate, using a micropipettor. 4. Incubate the plate for 1 h at 37°C to gelate the collagen gel (Fig. 2). 5. After gelation, overlay each well with 3 mL of DF(10) medium and incubate overnight.

3.2.2. Exposure to Anticancer Agents

The exposure conditions of anticancer agents should be designed to reproduce the clinical area under the curve. The concentration should be similar to the physiological concentration (27). 1. Add 30 µL/well (1/100 vol of the medium in each well) of an anticancer agent solution, using a micropipettor. 2. Incubate the plate for 24 h in an incubator.

CD-DST Method

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Fig. 2. Three collagen gel droplets placed on a multiwell.

3. Remove the medium from each well in the plate and overlay with 4 mL of DME medium for each well. 4. Incubate the plate for 10 min with agitation at 37°C in a CO2 incubator. Repeat this step twice to remove the anticancer agent.

3.2.3. Serum-Free Culture

After the anticancer agents are removed, apply 4 mL of serum-free medium PCM-2 to each well and incubate the plate for 7 d at 37°C in a CO2 incubator. 3.2.4. Staining and Fixation 1. After cultivation for 7 d, add 40 µL (1/100 vol of the medium) of a neutral red solution to each well. 2. Stain the cell for 2 h while gently shaking the plate in a CO2 incubator at 37°C (see Note 8). 3. Two hours after the staining, remove the medium containing neutral red. 4. Dispense 4 mL of phosphate-buffered saline (PBS) in each well, shake the plate at room temperature, and then remove the PBS. 5. Apply 4 mL of 10% neutral buffered formalin to each well. Allow the plate to stand for 45 min at room temperature.

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Fig. 3. Procedure for quantification by an image analysis system. 6. After removing the formalin, soak the plate in a tray filled with water and wait 10 min (see Note 9). 7. Drain off the water and air-dry the plate.

3.2.5. Quantification by Image Analysis

Using a measuring apparatus consisting of a personal computer, an image digitizer, and a videomicroscope, density on images is measured according to the procedure in Fig. 3. Cumulative value of density on the binary image is calculated, and image-optical density (A) is obtained according to the following formula: A = log10 [(∑WC – ∑BC) / (∑TC – ∑BC)]

in which ∑WC is the cumulative density value of the blank image, ∑BC is the cumulative density value in the covering light, and ∑TC is the cumulative density value of the test sample image. 3.2.6. In Vitro Chemosensitivity

The in vitro sensitivity is expressed as the percentage T/C ratio, in which T is the image–optical density of the treated group and C is the image–optical

CD-DST Method

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Fig. 4. Collagen gel droplet stained in neutral red (after being air-dried).

density of the control group; a T/C ratio of 50% or less is regarded as being sensitive in vitro (Fig. 4). 4. Notes 1. Mince the tissue pieces quickly before they become dried. 2. The volume of the solution can be increased up to 10 mL of D-MEM + 1 mL of Cell Dissociation Enzyme EZ, if the tumor volume is large. 3. When any large pieces of tissue are found at this step, collect those pieces and digest them again with Cell Dissociation Enzyme EZ. 4. Prolonged treatment with EGTA-trypsin leads to overreduction in size of the cell clusters and lowers the cellular activity. 5. Cool the tube sufficiently to avoid rapid gelation. 6. Be sure to add the cell suspension in a 1/10 or less volume of the collagen mixture. 7. Adjust the cell density to 2 × 105 to 5 × 105 cells/mL. 8. Inadequate shaking will lead to uneven staining. 9. The gel should be handled gently; it will detach from the plate if the plate is handled roughly.

Acknowledgments This method was developed through the collaboration of Dr. M. Koezuka, K. Tanisaka, and many staff of the biochemical laboratory of Nitta Gelatin Inc. I appreciate their advice on this work and cooperation. I also thank Mr. K. Minamigawa, T. Takano, and Ms. N. Yoneda for excellent technical supports. References 1. Osieka, R., Houchens, D. P., Goldin, A., and Johnson, R. K. (1977) Chemotherapy of human colon cancer xenografts in athymic nude mice. Cancer 40, 2640–2650.

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2. Countenay, V. D. and Mills, J. (1978) An in vitro colony assay for human tumours grown in immune-suppressed mice and treated in vivo with cytotoxic agents. Br. J. Cancer 37, 261–268. 3. Fujita, M., Fujita, F., and Taguchi, T. (1984) Chemosensitivity of human gastrointestinal and breast cancer xenografts in nude mice and predictability to clinical response of anti-cancer agents: immune-deficient animals, in 4th International Workshop on Immune-Deficient Animals in Experimental Research, Karger, Basel, Germany, pp. 311–315. 4. Rygaard, J. and Povlsen, C. O. (1969) Heterotransplantation of a human malignant tumour to nude mice. Acta Pathol. Microbiol. Scand. 77, 758–760. 5. Bogden, A. E., Kelton, D. E., Cobb, W. R., and Esber, H. J. (1978) A rapid screening method for testing chemotherapeutic agents against human tumor xenografts, in Symposium on the Use of Athymic (Nude) Mice Cancer Research. Gustav New York, New York, pp. 231–250. 6. Bogden. A. E., Griffin, W., Reich, S. D., Costanza, M. E., and Cobb, W. R. (1984) Predictive testing with the subrenal capsule assay. Cancer Treat. Rev. 11, 113–124. 7. Salmon, S. E., Hamburger, A. W., Soehnlen, B., et al. (1978) Quantitation of differential sensitivity of human-tumor stem cells to anticancer drugs. N. Engl. J. Med. 298, 1321–1327. 8. Von Hoff, D. D., Cowan, J., Harris, G., and Reisdorf, G. (1981) Human tumor cloning: feasibility and clinical correlations. Cancer Chemother. Pharmacol. 6, 265–271. 9. Rozencweig, M., Hofmann, V., Sanders, C., Rombaut, W., Fruh, L. J., and Martz, G. (1984) In vitro growth of human malignancies in a cloning assay. Recent Results Cancer Res. 94, 1–7. 10. Tanigawa, N., Kern, D. H., Hikasa, Y., and Morton, D. L. (1982) Rapid assay for evaluating the chemosensitivity of human tumors in soft agar culture. Cancer Res. 42, 2159–2164. 11. Kern, D. H., Drogemuller, C. R., Kennedy, M. C., Hildebrand-Zanki, S. L., Tanigawa, N., and Sondak, V. K. (1985) Development of miniaturized, improved nucleic acid precursor incorporation assay for chemosensitivity testing of human solid tumors. Cancer Res. 45, 5436–5441. 12. Tanigawa, N., Morimoto, H., Dohmae, N., Shimomatsuya, T., Takahashi, K., and Muraoka, R. (1992) In vitro growth ability and chemosensitivity of gastric and colorectal cancer cells assessed with the human tumor clonogenic assay and thymidine incorporation assay. Eur. J. Cancer 28, 31–34. 13. Kondo, T., Imamura, T., and Ichihashi, H. (1966) In vitro test for sensitivity of tumor to carcinostatic agents. Jpn. J. Cancer Res. 57, 113–121. 14. Mosmann, T. (1983) Rapid colorimetric assay for cellular growth and survival: application to proliferation and cytotoxicity assays. J. Immunol. Methods 65, 55–63. 15. Carmichael, J., DeGraff, W. G.. Gazdar, A. F.. Minna, J. D., and Mitchell, J. B. (1987) Evaluation of a tetrazolium-based semiautomated colorimetric assay: assessment of chemosensitivity testing. Cancer Res. 47, 936–942.

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16. Shoemaker, R. H., Wolpert-DeFilippes, M. K., Kern. D. H., et al. (1985) Application of human tumor colony-forming assay to new drug screening. Cancer Res. 45, 2145–2153. 17. Koezuka, M., Kondo, N., Kobayashi, H., et al. (1993) Drug sensitivity test for primary culture of human cancer cells using collagen gel embedded culture and image analysis. Int. J. Oncol. 2, 953–959. 18. Kobayashi, H., Tanisaka, K., Kondo, N., et al. (1995) Development of new in vitro chemosensitivity test using collagen gel droplet embedded culture and its clinical usefulness. Jpn. J. Cancer Chemother. 22(13), 1933–1939 (in Japanese). 19. Kobayashi, H., Tanisaka, K., Doi, O., et al. (1997) An in vitro chemosensitivity test for solid tumors using collagen gel droplet embedded cultures. Int. J. Oncol. 11, 449–455. 20. Kobayashi, H., Higashiyama, M., Minamigawa, K., et al. (2001) Examination of in vitro chemosensitivity test using collagen gel droplet culture method employing colorimetric endpoint quantification. Jpn. J. Cancer Res. 92, 203–210. 21. Yasuda, H., Takada, T., Wada, K., et al. (1998) A new in-vitro drug sensitivity test (collagen-gel droplet embedded-culture drug sensitivity test) in carcinomas of pancreas and biliary tract: possible clinical utility. J. Hepatobiliary Pancreat. Surg. 5, 261–268. 22. Araki, Y., Isomoto, H., Matsumoto, A., et al. (1999) An in vitro chemosensitivity test for colorectal cancer using collagen-gel droplet embedded cultures. Kurume Med. J. 46, 163–166. 23. Hanatani, Y., Kobayashi, H., Kodaira, S., et al. (2000) An in vitro chemosensitivity test for gastric cancer using collagen gel droplet embedded culture. Oncol. Rep. 7, 1027–1033. 24. Higashiyama, M., Kodama, K., Tokouchi, H., et al. (2001) Cisplatin-based chemotherapy for postoperative recurrence in non-small cell lung cancer patients: relation of the in vitro chemosensitive test to clinical response. Oncol. Rep. 8, 279–283. 25. Kawamura, M., Inoue, Y., Oyama, T., and Kobayashi, K. (2002) Chemosensitivity test for unresectable non-small cell lung cancer. Nihon geka-gakkai zassi. 103, 229–232 (in Japanese). 26. Takamura, Y., Kobayashi, H., Taguchi, T., Motomura, K., Inaji, H., and Noguchi, S. (2002) Prediction of chemotherapeutic response by collagen gel droplet embedded culture-drug sensitivity test. Int. J. Cancer 98, 450–455. 27. Kobayashi, H. (2003) Development of a new in vitro chemosensitivity test using collagen gel droplet embedded culture and image analysis for clinical usefulness. Recent Results Cancer Res. 161, 48–61.

7 The MTT Assay to Evaluate Chemosensitivity Jack D. Burton Summary The assessment of the degree or rate of cellular proliferation and cell viability is critical to the assessment of the effects of drugs, antibodies, or cytokines on both normal and malignant cell populations. This can be accomplished by either direct or indirect counting methods. Direct counting by manual or automated methods, using a hemacytometer or particle counter, respectively, allows for serial cell counting at multiple time points, but these are low-throughput approaches. High-throughput and robust alternatives to direct counting utilize either radiotracers (e.g., 3H-thymidine) or dye compounds, which can be adapted to multiwell culture plate formats. This chapter focuses on the use of tetrazolium-type indicator dyes, of which the compound 3-(4,5-dimethylthiazolyl-2)-2,5-diphenyltetrazolium bromide (MTT) has been the most widely utilized. Newer tetrazolium dyes that yield water-soluble products and offer added flexibility, increases in sensitivity, and fewer steps, which are offset by increased costs, are also covered.

Key Words Tetrazolium dye; MTT, proliferation; optical density; 50% inhibitory concentration; test agent/drug.

1. Introduction Assessment of the effects of drugs, antibodies, and cytokines on the proliferation and viability of specific cell types grown in culture is a critical initial step toward understanding and quantifying the effects of such agents. The ability to evaluate the effects of these test agents in vitro allows for the screening of a larger number of agents to identify those with the desired activity. In the case of anticancer agents such as chemotherapy or other small-molecule drugs, those with the greatest antiproliferative activity are typically selected for in vivo testing in appropriate animal models of human cancer. This is also true for antitumor antibodies that are being evaluated as anticancer agents. For immunological studies involving either cytokines or antibodies, agonist or From: Methods in Molecular Medicine, vol. 110: Chemosensitivity: Vol. 1: In Vitro Assays Edited by: R. D. Blumenthal © Humana Press Inc., Totowa, NJ

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growth-promoting effects are usually of interest. In this case, normal immune cell populations or factor-dependent cells lines are used to assess such effects. In all of these cases, the effect of these agents on total, viable cell numbers at the end of the assay period is one of the key endpoints. Tetrazolium dyes have been shown to be sensitive, accurate, and efficient in the in vitro evaluation of anticancer or immunological agents prior to preclinical and, ultimately, clinical testing. 3-(4,5-Dimethylthiazolyl-2)-2,5-diphenyltetrazolium bromide (MTT) is a yellow, water-soluble tetrazolium dye, which crosses both plasma and mitochondrial membranes. In the latter organelle of viable and glycolytically active cells, MTT is reduced by the action of NADH- or NADPH-dependent dehydrogenases. Cellular reduction of MTT produces an insoluble, purple formazan. The amount of the formazan product that results from this reaction is dependent on the number of cells and their viability. As this reaction goes to completion, residual viable cells die, the formazan product can be solubilized, and the optical density (OD) can be measured, which reflects the number of cells present at the end of the assay period. This approach to identifying viable cells as well as estimating cellular metabolic activity was first described using another tetrazolium dye, 2,3,4-triphenyl tetrazolium chloride (TTC) (1–3). It was used to aid microscopic visualization of viable cells grown in soft agar in experiments designed to assess in vitro growth conditions and cellular responses to drug treatment (2,3). A quantitative approach to determining the metabolic activity of tracheal explants was developed by adding TTC to these cultures, dissolving the resulting formazan precipitates in an organic solvent, followed by determining OD of the solubilized formazan product (1). Mosmann (4) first described the design and setup of an assay using the MTT dye, in which cells are added to replicate wells of 96-well plates. The plates are placed in an incubator for a sufficient time interval (usually 3–7 d) to allow cells to undergo several cell division cycles. At the end of the incubation period, MTT is added to each well followed by an additional incubation period of at least 4 h to allow for complete bioreduction of MTT to the final formazan product. The OD of each well is determined in a plate reader, allowing a highthroughput, accurate, and sensitive method to estimate cell numbers. The original work with this dye was with growth factor–dependent cell lines, but it was later shown to be useful for assessing growth characteristics and responses to chemotherapy drugs of cancer cell lines (5–7). Two groups of researchers addressed the factors that affect the performance of MTT-based assays (6,7). As described in more detail below, the limitation of MTT and other earlier tetrazolium dyes is the water insolubility of the formazan product. This led to the development and evaluation of other tetrazolium dyes whose formazan biore-

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duction products are water soluble. The first of this class of tetrazolium dyes to be described was 2,3-bis(2-methoxy-4-nitro-5-sulfophenyl)-2H-tetrazolium5-carboxanilide (XTT) (8,9). It was noted that with XTT (and later with other members of this class) it was necessary to add an electron-coupling reagent (typically phenazine methosulfate [PMS]) to achieve optimal absorbance values. When XTT/PMS was compared with MTT, similar absorbance values were obtained with both methods, but the former method did not require either the centrifugation or solubilization steps of the MTT method (8). Although XTT has this advantage, it has limited solubility and requires prewarming of the medium to at least 37°C; it is also necessary to prepare XTT/PMS fresh just prior to adding it to the culture plate. Thus, other dyes in this class were synthesized and evaluated. The dye 3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)2-(4-sulfophenyl)-2H-tetrazolium (MTS) was the next one to be described (10,11). As with XTT, PMS needs to be added to the MTS solution prior to its addition to cells. Unlike XTT, MTS solutions are stable, as are PMS solutions; thus, individual stock solutions of each can be stored and mixed just prior to adding to cells. MTS is available in a kit format containing stock solutions of both MTS and PMS from Promega. (Madison, WI). Another dye with improved characteristics over XTT has also been described, (4-iodophenyl)3-(4-nitrophenyl)-5-(2,4-disulfophenyl)-2H-tetrazolium (WST-1). It has been shown to perform at least as well as MTT and XTT (12–15). Like MTS, WST-1 is stable in solution. It also requires the use of PMS. This dye is available in kit format from Roche Diagnostics, GmbH (Penzberg, Germany). XTT, MTS, and WST-1 are all considerably more expensive than MTT, but the time that is saved, as well as the increased sensitivity and utility of these dyes with a wider range of cell lines, often makes them a fairly cost-effective alternative. 2. Materials 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11.

Sterile laminar flow hood or biosafety cabinet. Incubator (usually kept at 37°C with an internal atmosphere of 95% air/5% CO2). Cell culture medium and required additives (see Note 1). Phosphate-buffered saline (PBS) (see Note 2). Trypsin/EDTA solution. Sterile disposables including pipets, pipet tips, and tissue culture flasks. Repeating Eppendorf-type pipettor and compatible, sterile Combi-Tips (also helpful is an electronic pipettor with repetitive dispensing capability). 96-Well plate reader with adjustable, visible wavelength settings. Source of cells (usually continuously growing cell lines) (see Note 3). Chemotherapeutic drugs (see Note 4). MTT.

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3. Methods 3.1. Design of MTT Assays The MTT assay is useful for measuring the effect of a wide range of compounds on the in vitro growth of either normal or cancer cell lines. The assay is set up in a 96-well, flat-bottomed polystyrene microtiter plate. Cells are suspended in appropriate growth medium, and the cells are added to replicate wells (triplicates are usually preferred) (see Note 5). It is preferable to add the cells to the required number of wells in the plate prior to adding the drugs or agents to be tested. After the cells are added to the plate, it can be placed on the incubator to allow cells to settle and attach (in the case of adherent cells) while the agents to be tested are being prepared. Drugs or other compounds are added at defined concentrations to each set of replicate wells (see Notes 6 and 7). Agents to be tested must be properly solubilized. Aqueous solubility does not pose a problem for protein agents such as antibodies and cytokines. Many small-molecule compounds, however, have limited water solubility. Most of these compounds can be dissolved in dimethyl sulfoxide (DMSO)– or dimethyl formamide (DMF)–based solvents. DMSO is preferable over DMF, because it tends to have slightly less toxicity for cells in culture. Since most compounds of interest demonstrate antiproliferative activity at or below the micromolar level, they should be dissolved at concentrations of 10–100 mM. This should result in a stock solution that has a concentration of 1000–5000 times the highest concentration that will be tested in the assay. This results in final concentrations of DMSO or DMF that usually exhibit minimal cellular toxicity. It is critical, however, to prepare control solutions of the identical dilutions of the solvent used for the stock solution for each cell line to rule out or control for any solvent effects. The choice of the concentration range to be tested depends on what is known about the agent in question and the cell line(s) to be tested. If little is known about the agent to be tested, a high initial concentration should be selected followed by approximately five serial dilutions to cover a range of at least 100fold. To accomplish this, serial dilutions of threefold or higher are needed. The procedure for the preparation of serial dilutions is shown in Fig. 1. Once initial experiments define the boundaries of the dynamic range of antiproliferative activity for a compound, a narrower concentration range should be evaluated. This can be accomplished by using approximately twofold dilutions. For a series of twofold dilutions, the highest concentration is selected and prepared in a volume of at least 2 mL of the appropriate tissue culture medium (higher volumes are needed if a large number of plates are being set up). If 2 mL is selected for the final volume of the first tube, then 1 mL of medium is added to each of the subsequent tubes in the series of dilutions. After the first tube is


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Fig. 1. Procedure for preparation of serial dilutions.

prepared by adding the correct volume of test agent from its stock solution followed by thorough mixing, 1 mL from the first tube is added to the second tube. Tube 2 is then mixed, and 1 mL from this tube is added to tube 3 and so on to reach the required number of tubes (dilutions). Cells are allowed to grow under incubator conditions (usually 37°C with supplemental CO2). The planned duration of the assay determines the appropriate number of cells to add to each well. For the assessment of the antiproliferative effects of a wide range of compounds, an incubation period of 5–7 d is reasonable (see Note 8). To maximize the dynamic range of this assay, cells that are untreated, which serve as controls, should be allowed to proliferate until the level of cellular confluence (the estimated percentage of the total area of the well that is covered by cells) is 70–90%. This parameter should be monitored by inspecting plates daily using an inverted microscope (see Note 9). 3.2. Processing of Plates for Adherent Cells Once cells in the untreated wells have reached a confluency of 70–90%, 5 mg/mL MTT is added to the plate (see Note 10). The approach to adding MTT and harvesting plates depends upon whether the cell lines or populations are adherent or nonadherent in their growth patterns. While adherence to the plastic surface of microplate wells varies among cell lines, the line of demarcation with respect to these assays is whether trypsin treatment is needed to release cells from the surface of culture flasks. For such adherent cell types (usually epithelial and fibroblast-like cells), the processing procedure may be carried out as outlined next. 1. Prepare a stock solution of MTT in PBS. This final part of the assay does not require sterile conditions. 2. Remove the microplate from the incubator, and invert it over a container with mild shaking to remove most of the culture medium. While the plate is still inverted, remove the remaining medium by blotting it on a small stack of paper towels.

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3. Prepare a working solution of MTT by diluting the stock solution 110 (final concentration: 0.5 mg/mL) using tissue culture medium (RPMI-1640-based medium should be used). Using a repeating pipettor, add 100 µL of this working solution to each well. 4. Cover the plate and place back in the incubator for at least 4 h to allow full conversion of the MTT. 5. After incubation, centrifuge the plate to pellet the precipitated formazan dye. To accomplish this, a standard tabletop centrifuge with an appropriate microplate carrier is needed. Centrifuge the plates at 1000g for 10 min at ambient temperature, and then invert the plate and blot onto paper towels to remove the bulk of the liquid. 6. Solubilize the MTT product (formazan) by adding 100 µL of DMSO to each well. To speed the rate of solubilization of the dye, the plate can be returned to the 37°C incubator, with gentle tapping of the plate every 5–10 min. Solubilization is usually complete within 30 minutes. An alternative approach to solubilize the MTT product in plates containing adherent cell types is to use an acid-isopropanol solvent as follows. At the end of the initial culture period, the plate is inverted and blotted to remove the culture medium. In this case, the MTT working solution should be prepared using RPMI-1640 medium without added fetal bovine serum (FBS) at a 110 dilution as described in step 3 and added to the plate at 100 µL/well. After the requisite 4-h (or more) incubation period, the MTT product is solubilized by the direct addition of an equal volume (in this case, 100 µL) of 0.04 N HCl in isopropanol to each well. Since residual protein may precipitate if the resulting solution is allowed to stand more than 30 min, plates should be read 5–15 min after addition of the acid-isopropanol.

3.3. Processing of Plates for Nonadherent Cells Nonadherent cells cover the gamut of both normal and malignant cell lines of hematopoietic origin. While these cells settle and distribute fairly evenly over the surface of the plates, changing medium in plates containing nonadherent cells requires either removing the medium with a multichannel pipettor or centrifuging the plates followed by inverting and blotting them to remove the medium. The latter approach is much quicker. To facilitate the process, a modification of the MTT method described in Subheading 3.2. is useful. (This method may also be used with adherent cells.) 1. Dilute the same MTT stock solution (5 mg/mL) with an equal volume of tissue culture medium, and add 25 µL of this solution directly to each well with a repeating pipettor. 2. As with the adherent-cell method, return the plates to the incubator for a period of at least 4 h. 3. Centrifuge the plates at 1000g for 10 min at ambient temperature, followed by inversion of the plates and blotting of excess medium.


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4. Use DMSO to solubilize the MTT formazan product as described in Subheading 3.2., step 6.

3.4. Obtaining of OD Values A standard microplate reader with adjustable wavelengths across the visible spectrum is required. The detection wavelength for MTT should be between 560 and 570 nm (see Note 11). The OD values obtained for each set of triplicates corresponding to a specific concentration of a test agent can then be transferred into a spreadsheet program such as Excel as described below. 3.5. Quantification and Calculation of Inhibitory Activity The antiproliferative activity of agents is expressed as the 50% inhibitory concentration (IC50). This may be expressed as a molar concentration or on a mass-per-volume basis such as micrograms per milliliter or milligrams per liter. The former mode of expression is preferable; it can be readily calculated using the molecular mass of the agent in question. Thus, the IC50 is defined as the concentration of the test agent that results in a 50% decrease in the baseline or control level of proliferation. Since the readout of the MTT assay is OD, the baseline for calculation of IC50 values is the OD value of the corresponding control wells in the MTT assay plate. To perform this analysis, the appropriate control OD value is essential. This control should be exactly matched for the dilution of the solvent that was used to prepare the stock solution of the test agent. Using the control OD values, the percent inhibition at each concentration of the test agent can be calculated by dividing the observed OD value by the corresponding control and multiplying by 100 as shown in the following equation: 1 – (ODobserved / ODcontrol) × 100 = % inhibition

Once the percent inhibition values corresponding to each concentration of the test agent are calculated, these values can be plotted on a graph to allow for the interpolation of the IC50 value. To obtain a linear or nearly linear plot, the percent inhibition values should be log-transformed to obtain a linear equation, y = ax. The r 2 value for the plot will indicate the goodness of fit for this equation. 4. Notes 1. Cell culture medium is usually supplied according to specific, published formulations, such as RPMI-1640 or Dulbecco’s modified Eagle’s medium. Such widely used and published media formulations can usually be obtained from any established vendor.

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2. Vendors also supply standard stock solutions in sterile cell culture–tested formulations such as PBS (note that calcium/magnesium-free PBS is usually preferred) and trypsin/EDTA (needed to detach adherent cells). The latter two solutions as well as other additives are supplied in concentrated stock solutions that either are diluted in sterile deionized water (in the case of PBS concentrates) or sterile PBS (in the case of trypsin/EDTA concentrates), or are added directly to media to achieve the desired final concentrations (in the case of antibiotics and L-glutamine). For any solutions that require dilution in deionized water, a source of highly pure water from which contaminating ions and volatile organics (activated charcoal adsorbed and exhibiting 18 mΩ of resistance) have been sufficiently removed is critical. 3. Cell lines can be either obtained from individual investigators or purchased from repositories such as the American Type Culture Collection (ATCC; Manassas, VA). The published requirements of the cell lines (provided by the investigator who established the cell line or by the repository [e.g, ATCC]) will determine the additives that are needed for the culture medium. Typically, basic cell culture medium needs to be supplemented with FBS; antibiotics; L-glutamine; and, potentially, other additives. The specific preferred vendor from which to purchase these components is specified by the investigator or the repository such as ATCC. 4. For drugs that are not water soluble, organic solvents are required to prepare stock solutions. DMSO is the most useful and least toxic of these solvents. Other alternatives are DMF and ethanol. These should be obtained either in tissue culture–tested formulations or in their most pure forms from any established supplier of fine chemicals. Although microbial contamination is unusual in organic solvents, it is still important that they be sterile filtered. To achieve an acceptable level of sterility, solutions must be filtered through filters with a cutoff of 0.45 µ or less. For these organic solvents, a solvent-resistant syringe-tip filter is preferred. For filtration of other aqueous solutions, syringe-tip or vacuum-assisted filters may be used, depending on the volume of the solution that needs sterile filtration. Obtain information about the stability of the test agent or drug. If there is a question, prepare a new stock solution of it. Be sure to control as much as possible for the effects of the organic solvents used to prepare drug stock solutions on the growth of the cells by setting up control wells containing equal dilutions of solvent without the test agent or drug. 5. Cell lines should be maintained in culture medium to which they are adapted, and that supports consistent cellular proliferation. They should have maximum viability (>90% at the start of the assay) and be in the logarithmic phase of growth at the time of harvest. For most cell lines, this is either a basal or an enriched medium (e.g., RPMI-1640, Dulbecco’s modified Eagle’s medium, or Iscove’s modified Eagle’s medium) that is supplemented with bovine or other serum or purified serum components as well as antibiotics and L-glutamine. The culture medium in which cell line(s) are routinely carried should be used for setting up the MTT assay.


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6. The final volume of medium in each well should be 200 µL. It is common to assess binary combinations of agents to examine the interaction of the two agents, which may be additive, synergistic, or antagonistic. In most instances, no more than two agents need to be added to each well. Thus, it is convenient to first plate the cells in a volume of 100 µL of culture medium. This allows for a single agent to be added to each of the wells in a volume of 100 µL or, for two agents, in a volume of 50 µL for each agent. 7. To increase precision and reduce the setup time for assays, it is very helpful to utilize repeating pipettors. Commonly used repeating pipettors are those that are similar in design to one of the original instruments of this type, the Eppendorf repeater. This pipettor requires specialized tips, which are often referred to as Combi-Tips. These must be sterile and are usually available in individually packaged and sterile form. These tips may also be used to add the agents to be tested to the individual wells, but it is more economical over time to use an electronic pipettor with a repeat pipetting mode. A 1000-µL size of such a pipettor will allow for the precise delivery of up to 20 separate 50-µL vol with a single standard pipet tip. A standard manual pipettor may also be used. 8. For plates being incubated for 5 d or longer, an incubator chamber that is humidified should be used to minimize evaporative effects. To reduce the tendency toward evaporation in the wells on the perimeter of the plate, the outer columns and rows should not be used. To further reduce evaporation of the inner wells, 200–250 µL/well of sterile water or PBS should be added to the outer perimeter wells. 9. For most cell lines, a total of 3–9 × 104 cells/well will result in the target level of confluence of 70–90%. To reach the target number of cells within the planned time frame (5–7 d), the doubling time of the cell line(s) needs to be estimated from their current growth and maintenance characteristics. Typical doubling times for most mammalian cell lines range from 20 to 60 h. Thus, the number of cells that typically needs to be added to the wells of the plate at the start of the assay ranges from 1.5 to 7.5 × 103/well. Estimating an appropriate cell number for initial plating often requires repeat experiments to calibrate this parameter. 10. Observe the plate under an inverted microscope on a daily basis to assess the level of confluence and the color of the medium. If the medium has taken on a yellowish color, it is depleted, and the MTT (or other dye) should be added soon. 11. If it is not possible to achieve maximum control OD values of >0.9 with MTT, try substituting one of the dyes that yields water-soluble end product (formazan), such as MTS or WST-1.

References 1. Gabridge, M. G. and Polisky, R. B. (1976) Quantitative reduction of 2,3,4-triphenyl tetrazolium chloride by hamster trachea organ cultures: effects of Mycoplasma pneumoniae cells and membranes. Infect. Immun. 13, 84–91.

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2. Douglas, W. H., McAteer, J. A., Dell’orco, R. T., and Phelps, D. (1980) Visualization of cellular aggregates cultured on a three dimensional collagen sponge matrix. In Vitro 16, 306–312. 3. Alley, M. C., Uhl, C. B., and Lieber, M. M. (1982) Improved detection of drug cytotoxicity in the soft agar colony formation assay through use of a metabolizable tetrazolium salt. Life Sci. 31, 3071–3078. 4. Mosmann, T. (1983) Rapid colorimetric assay for cellular growth and survival: application to proliferation and cytotoxicity assays. J. Immunol. Methods 65, 55–63. 5. Carmichael, J., DeGraff, W. G., Gazdar, A. F., Minna, J. D., and Mitchell, J. B. (1987) Evaluation of a tetrazolium-based semiautomated colorimetric assay: assessment of chemosensitivity testing. Cancer Res. 47, 936–942. 6. Twentyman, P. R. and Luscombe, M. (1987) A study of some variables in a tetrazolium dye (MTT) based assay for cell growth and chemosensitivity. Br. J. Cancer 56, 279–285. 7. Vistica, D. T., Skehan, P., Scudiero, D., Monks, A., Pittman, A., and Boyd, M. R. (1991) Tetrazolium-based assays for cellular viability: a critical examination of selected parameters affecting formazan production. Cancer Res. 51, 2515–2520. 8. Scudiero, D. A., Shoemaker, R. H., Paull, K. D., et al. (1988) Evaluation of a soluble tetrazolium/formazan assay for cell growth and drug sensitivity in culture using human and other tumor cell lines. Cancer Res. 48, 4827–4833. 9. Roehm, N. W., Rodgers, G. H., Hatfield, S. M., and Glasebrook, A. L. (1991) An improved colorimetric assay for cell proliferation and viability utilizing the tetrazolium salt XTT. J. Immunol. Methods 142, 257–265. 10. Cory, A. H., Owen, T. C., Barltrop, J. A., and Cory, J. G. (1991) Use of an aqueous soluble tetrazolium/formazan assay for cell growth assays in culture. Cancer Commun. 3, 207–212. 11. Buttke, T. M., McCubrey, J. A., and Owen, T. C. (1993) Use of an aqueous soluble tetrazolium/formazan assay to measure viability and proliferation of lymphokine-dependent cell lines. J. Immunol. Methods 157, 233–240. 12. Ishiyama, M., Shiga, M., Sasamoto, K., Mizoguchi, M., and He, P. (1993) A new sulfonated tetrazolium salt that produces a highly water-soluble formazan dye. Chem. Pharm. Bull. 41, 1118–1122. 13. Takenouchi, T. and Munekata, E. (1995) Trophic effects of substance P and betaamyloid peptide on dibutyryl cyclic AMP–differentiated human leukemic (HL-60) cells. Life Sci. 56, PL479–PL484. 14. Teruya, K., Yano, T., Shirahata, S., et al. (1995) Ras amplification in BHK-21 cells produces a host cell line for further rapid establishment of recombinant protein hyper-producing cell lines. Biosci. Biotechnol. Biochem. 59, 341–344. 15. Ishiyama, M., Tominaga, H., Shiga, M., Sasamoto, K., Ohkura, Y., and Ueno, K. (1996) A combined assay of cell viability and in vitro cytotoxicity with a highly water-soluble tetrazolium salt, neutral red and crystal violet. Biol. Pharm. Bull. 19, 1518–1520.

8 Histoculture Drug Response Assay to Monitor Chemoresponse Shinji Ohie, Yasuhiro Udagawa, Daisuke Aoki, and Shiro Nozawa Summary We provide a detailed explanation of the procedure of the histoculture drug response assay (HDRA) with 3-(4,5-dimethylthiazolyl-2)-2,5-diphenyltetrazolium bromide (MTT) end point among several modified HDRA procedures. Fresh surgical specimens are cut into approx 1- to 2-mm3 pieces and put on a gelatin sponge infiltrated with culture medium containing a test drug. After incubation for 7 d, cell viability is assessed by the MTT assay. HDRA uses cancer tissue fragments with cells growing in three dimensions, with maintenance of intercellular contact and interactions with stromal cells. Therefore, it seems that HDRA can assess the sensitivity of tumor cells to anticancer drugs in conditions similar to those in vivo and, consequently, shows high prediction rate.

Key Words Histoculture drug response assay; chemoresponse; chemosensitivity; surgical specimen; gelatin sponge; collagen matrix.

1. Introduction Hoffman and colleagues developed the histoculture drug response assay (HDRA) and applied it to three-dimensional culture of tissue fragments of tumor using a collagen gel matrix and a [3H]thymidine uptake end point (1–5). Many conventional drug sensitivity tests reported use isolated tumor cells obtained after enzymatic digestion. By contrast, the HDRA technique uses cancer tissue fragments with cells maintained in their native tissue architecture, which can grow in three dimensions, with maintenance of intercellular contact and interactions with stromal cells. Therefore, HDRA can assess the sensitivity of tumor cells to anticancer drugs in conditions similar to those present in vivo. Kubota et al. (6) demonstrated that in vitro response in HDRA From: Methods in Molecular Medicine, vol. 110: Chemosensitivity: Vol. 1: In Vitro Assays Edited by: R. D. Blumenthal © Humana Press Inc., Totowa, NJ

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with the [3H]thymidine end point is correlated with survival of patients with gastric cancer. Furukawa et al. (7–9) demonstrated that the response in HDRA with 3-(4,5-dimethyl-2-thiazolyl-2)-2,5-diphenyltetrazolium bromide (MTT) reduction as an endpoint is correlated with patient drug response and survival. Ohie et al. (10) modified the HDRA procedure to be able to perform it more easily without measuring the weights of tumor fragments aseptically. Eightyfive (97%) cases were evaluable, and a high prediction rate (87%) was found when HDRA results for CDDP were compared to clinical response to combination chemotherapy containing CDDP in patients with ovarian cancer (10). Of several modified HDRA procedures, we provide a detailed explanation of the HDRA procedure with MTT as the end point that we have used for assessing the drug sensitivities of ovarian cancer specimens. 2. Materials 1. Gelatin sponge (Gelfoam Sterile Sponge no. 100, Pharmacia; or Spongostan 70 × 50 × 10 mm Standard, Health Design, Rochester, NY) (see Note 1). 2. Ham’s F-12 medium (Gibco-BRL, Gaithersburg, MD) (see Note 2). 3. Heat-immobilized fetal bovine serum (FBS). 4. Hank’s solution. 5. Phosphate-buffered saline (PBS). 6. MTT. 7. Sodium succinate. 8. Dimethyl sulfoxide (DMSO). 9. Membrane filter (pore size: 0.2 µm diameter). 10. 24-Well culture plates. 11. 96-Well culture plates. 12. Antibiotics (kanamycin, penicillin, gentamycin, and so on) (see Note 3). 13. Surgical knife (Disposable Scalpel no. 11; Feather Safety Razor, Medical Division). 14. Surgical scissors. 15. Microplate reader. 16. Clean bench (laminar flow chamber). 17. CO2 incubator (5% CO2, 37°C). 18. Gelatin sponge (Gelfoam; Pharmacia).

3. Methods The HDRA procedure is shown in Fig. 1. From excision of specimens to generation of MTT-formazan in cells, specimens must be kept wet and sterile. 3.1. Preparation of Tissue Specimens 1. Obtain fresh surgical specimens in the operating room as aseptically as possible. 2. Wash the surgical specimens with Hank’s solution containing antibiotic (100 U/mL penicillin, 100 µg/mL gentamycin, and the like), if necessary (see Note 3).

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Fig. 1. HDRA procedure.

3. Cut the tissue specimens with sterile surgical scissors into approx 1- to 2-mm3 pieces in Hank’s solution on a clean bench (see Note 4).

3.2. Preparation of Assay Plate and Culture 1. Cut the gelatin sponge into approx 1-cm3 pieces with a sharp surgical knife under sterile conditions on a clean bench.

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Fig. 2. Illustration of HDRA. The side and top views of 1 well of a 24-well plate are shown. 2. Place one piece of cut gelatin sponge in each well of a 24-well culture plate. 3. Drugs are dissolved at varying concentrations in Ham’s F-12 medium containing 20% heat-immobilized fetal bovine serum and kanamycin (80 µg/mL). Then sterilize this solution by filtration with a 0.2-µm-pore membrane filter. 4. Pour medium containing the test drug into each well of the plate (1 mL/well). Use four wells at each concentration of test drug (n = 4) (see Note 5). 5. Allow the culture medium to infiltrate sufficiently (see Note 6). 6. Place the pieces of cancer tissue on the gelatin foam (see Note 7). 7. Incubate the plate for 7 d at 37°C under 5% CO2 (see Fig. 2).

3.3. Estimation of Number of Live Cells Cell viability is assessed by MTT assay at the end of incubation. 1. MTT is dissolved in PBS (5 mg/mL) containing 100 mM sodium succinate. 2. Aseptically add MTT solution to each well of the 24-well plate (100 µL/well). Sink the fragment in the medium completely (see Fig. 1). 3. Incubate the plate for about 4 h at 37°C under 5% CO2. 4. Stain the pieces of tumor tissue violet with generation of MTT-formazan in proportion to the activities of succinyldehydrogenase in cancer cells. 5. Transfer the stained tumor fragments to another new 24-well plate containing DMSO at a rate of 1 mL/well to extract the MTT-formazan (see Fig. 3). 6. Place the extract in a 96-well microplate (100 µL/well). 7. Measure the absorbance of each well at 540 nm using a microplate reader. 8. Measure the weights of the residual tumors after extraction of MTT-formazan. 9. Calculate the absorbance per gram of residual tumor (see Note 8).

3.4. Data Processing and Analysis 1. Calculate the tumor inhibition rate (%), relative to the untreated control group, using the following equations:


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Fig. 3. Twenty-four-well plate after extraction of MTT-formazan with DMSO from ovarian cancer fragments treated with CDDP.

T/C =

Absorbance/g tumor in treated group ——————–————————————— Mean of absorbance/g tumor in untreated group

Tumor inhibition rate (%) = (1 – T/C) × 100 2. At each concentration, average the inhibition rates for the four wells and draw the dose-response curve (see Note 5). 3. Calculate the concentration yielding 50% inhibition of tumor growth (IC50).

3.5. Estimation of Optimal Cutoff IC50 Value 1. Draw the cumulative efficacy rate curve for the IC50 values as determined by HDRA. The vertical axis represents the cumulative efficacy rate, and the horizontal axis is the IC50 value. 2. Obtain the equation representing an approximate curve by curve fitting using computer processing. 3. Apply the clinical response rate of the tested drug to this equation to calculate the optimal cutoff IC50 value (see Note 9).

3.6. Evaluation of Results When the IC50 value estimated by HDRA is lower than the cutoff IC50 value, the case is determined to be sensitive to test drug and expected to exhibit complete or partial response clinically, whereas cases not sensitive to test drug with

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IC50 values higher than the cutoff IC50 value are not expected to exhibit clinical response. If one cannot obtain a specimen of sufficient volume and are obliged to use a simplified HDRA procedure, one must set the concentration of test drug at the cutoff IC50 value. When the absorbance per gram of tumor in the drugtreated group is lower than 50% of absorbance per gram of tumor in the control group, the case is determined to be sensitive to test drug. 4. Notes 1. The gelatin sponges introduced here are sterile and dry. If one uses pure collagen gel containing water prepared in the laboratory, adjustment of the final concentration of drug is extremely difficult and too expensive. 2. Dr. Hoffman has used Eagle’s minimal essential medium and Dr. Kubota and many researchers have used RPMI-1640 medium for gastric cancer, colon cancer, liver cancer, and so on. Before starting HDRA on a large scale, one must preliminarily determine a medium suitable for examination of the cancer concerned. 3. We have used F-12 medium containing kanamycin (80 µg/mL) for culture and transport from the operating room to the laboratory. During HDRA for ovarian cancer and uterine cancer, contamination with bacteria has only rarely been observed. However, for specimens at greater risk of contamination with bacteria, such as colon cancer specimens, surgical specimens should be washed with Hank’s solution containing penicillin (100 U/mL) and gentamycin (100 µg/mL) and the culture medium containing these two antibiotics should be used at the same concentrations. However, the effects of such antibiotics on cell growth and interaction among the antibiotics and test drug must be considered. 4. When the tissues are cut to fragments of the same volume as precisely as possible, good results are obtained although absorbance is normalized to fragment weight. This appears to be due to diffusion of drug in the tissue fragment. 5. To maintain a high level of confidence in the results obtained, we recommend using four wells at each concentration of test drug (n = 4). Values for out of range can then be omitted. For the same reason, one must draw the dose-response curve using inhibition rates for four or more drug concentrations and should confirm that inhibition of growth of cells is caused by the test drug. 6. In many cases, infiltration of the culture medium into the gelatin sponge requires a long period of time. In this case, time can be saved by putting the plate in a 37°C CO2 incubator and turning the gelatin sponge upside down in the same well aseptically more than 10 min after the medium has been poured. 7. If one has a clean room pressurized with air filtered through high-efficiency particle filters and can weigh the fragments precisely and aseptically, several cut fragments of tissue can be placed on a gelatin sponge up to about 10 mg/well of 24-well plates at the start of the HDRA. If this procedure is chosen, an MTT solution with collagenase type I (Sigma, St. Louis, MO) is applied and incubated at 37°C under 5% CO2 for 8 h. Then the gelatin sponge is digested and MTT-


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formazan is generated. The medium is carefully removed with a micropipet, and 1.0 mL of DMSO is poured to extract the MTT-formazan. 8. We have confirmed a good correlation between fresh tissue fragments and the residual tumors after extraction of MTT-formazan for results obtained for ovarian and uterine cancers, and we recommend preliminarily confirming the correlation for results between fresh tissue fragments and residual tumor. 9. Furukawa et al. (11) reported that 2 µg/mL for MMC, 300 µg/mL for 5-fluorouracil, 15 µg/mL for ADM, and 20 µg/mL for CDDP are the optimal cutoff IC50 values for gastric and colon cancers. Ohie et al. (10) reported that 25 µg/mL for CDDP was the optimal cutoff IC50 value for ovarian and uterine cancers. These IC50 values are very high compared to the peak blood levels of drugs. Maehara et al. (12) reported that the reason for this is that the activity of succinate dehydrogenase measured by the MTT procedure remained even after cells died.

References 1. Freeman, A. E. and Hoffman, R. M. (1986) In vivo-like growth of human tumors in vitro. Proc. Natl. Acad. Sci. USA 83, 2694–2698. 2. Vescio, R. A., Redfern, C. H., Nelson, T. J., Ugoretz, S., Stern, P. H., and Hoffman, R. M. (1987) In vivo-like drug responses of human tumors growing in three-dimensional gel-supported primary culture. Proc. Natl. Acad. Sci. USA 84, 5029–5033. 3. Hoffman, R. M., Connors, K. M., Meerson-Monosov, A. Z., Herrera, H., and Price, J. H. (1989) A general native-state method for determination of proliferative capacity of human normal and tumor tissues in vitro. Proc. Natl. Acad. Sci. USA 86, 2013–2017. 4. Vescio, R. A., Connors, K. M., Kubota, T., and Hoffman, R. M. (1991) Correlation of histology and drug response of human tumors grown in native-state threedimensional histoculture and in nude mice. Proc. Natl. Acad. Sci. USA 88, 5163–5166. 5. Hoffman, R. M. (1991) Three-dimensional histoculture: origins and application in cancer research. Cancer Cells 3, 86–92. 6. Kubota, T., Sasano, N., Abe, O., Nakao, I., Kawamura, E., Saito, T., Endo, M., Kimura, K., Demura, H., and Sasano, H. (1995) Potential of the histoculture drug response assay to contribute to cancer patient survival. Clin. Cancer Res. 1, 1537–1543. 7. Furukawa, T., Kubota, T., Watanabe, M., et al. (1992) High in vitro–in vivo correlation of drug response using spongegel-supported three-dimensional histoculture and the MTT end-point. Int. J. Cancer 51, 489–498. 8. Furukawa, T., Kubota, T., Watanabe, M., et al. (1992) Chemosensitivity testing of clinical gastrointestinal cancers using histoculture and the MTT end-point. Anticancer Res. 12, 1377–1382. 9. Furukawa, T., Kubota, T., and Hoffman, R. M. (1995) Clinical applications of the histoculture drug response assay. Clin. Cancer Res. 1, 305–311.

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10. Ohie, S., Udagawa, Y., Kozu, A., Komuro, Y., Aoki, D., Nozawa, S., Moossa, A. R., and Hoffman, R. M. (2000) Cisplatin sensitivity of ovarian cancer in the histoculture drug response assay correlates to clinical response to combination chemotherapy with cisplatin, doxorubicin and cyclophosphamide. Anticancer Res. 20, 2049–2054. 11. Furukawa, T., Suzuki, K., Yuasa, S., Izumo, M., Kozakai, K., Yano, T., Harada, N., and Kubota, T. (1996) Clinical application of histoculture drug response assay (HDRA) for gastrointestinal cancers with reference to cumulative efficacy rate curve. J. Jpn. Soc. Cancer Ther. 31(2), 116–126. 12. Maehara, Y., Anai, H., Tamada, R., and Sugimachi, K. (1987) The ATP assay is more sensitive than the succinate dehydrogenase inhibition test for predicting cell viability. Eur. J. Cancer Clin. Oncol. 23, 273–276.

9 In Vitro Testing of Chemosensitivity in Physiological Hypoxia Rita Grigoryan, Nino Keshelava, Clarke Anderson, and C. Patrick Reynolds Summary Highly aggressive, rapidly growing tumors are often hypoxic, owing to an inadequate supply relative to consumption of oxygen (O2) in the expanding tumor mass, or growth in tissues with physiologically low O2 concentrations (such as bone marrow). Selection of tumor cells that can grow or survive under hypoxic conditions appears from both experimental and clinical studies to impact tumor progression, response to therapy, and to increase resistance to radiation and to certain cytotoxic drugs. Therefore, the predictive value of preclinical testing of anticancer agents in cell culture might be improved by conducting testing in conditions of physiological hypoxia. We review the impact of hypoxia on anticancer drug cytotoxicity and the methods used in our laboratory to asses the cytotoxic activity of single antineoplastic drugs under conditions of physiological hypoxia.

Key Words Tumor hypoxia; drug resistance; hypoxia-targeted therapy; cytotoxicity assay; digital image microscopy.

1. Introduction Solid tumors often have areas in which circulation is compromised because of structurally disorganized blood vessels and tumor cells that grow faster than the developing tumor capillary network (1,2). The fraction of solid tumors that are hypoxic can vary from 0.2 to >50% (3,4). The degree of hypoxia in tumors is highly variable, with the PO2 generally 90%, with a positive predictive value of 85–90% and a negative predictive value near 100%, respectively. In primary ovarian cancers, the ATP-TCA has been found to accurately predict both clinical response and survival. In two prospective clinical trials in patients with heavily pretreated ovarian cancer, chemotherapy individually selected by the ATP-TCA has been found to triple the response rates and nearly double the survival compared to empirically chosen regimens. Consequently, this assay, which is now under phase III evaluation, has successfully been used in new agent development to screen for novel chemotherapy regimens for the treatment of patients with breast and ovarian carcinoma and melanoma, respectively. This chapter highlights the recent preclinical and clinical experience with this promising technology and gives a detailed description of all the technical aspects of the ATP-TCA.

Key Words Adenosine triphosphate–based tumor chemosensitivity assay; breast cancer; chemoresistance; chemotherapy; colorectal cancer; luminescence; malignant melanoma; nonclonogenic assay; ovarian carcinoma. From: Methods in Molecular Medicine, vol. 110: Chemosensitivity: Vol. 1: In Vitro Assays Edited by: R. D. Blumenthal © Humana Press Inc., Totowa, NJ

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1. Introduction Because of the considerable toxicity of antineoplastic agents in conjunction with their often uncertain clinical efficacy, the concept of individualized chemotherapy based on pretherapeutic chemosensitivity testing has attracted attention for almost five decades (1–3). In particular, the 1980s saw an intensive preclinical and clinical research in this field mainly focused on clonogenic assays stimulated by the work of Hamburger and Salmon and Courtenay in the late 1970s (see Chapter 2). A number of clinical trials using these technologies in various tumor entities have been conducted, sometimes providing promising results, but none were able to provide indisputable evidence of the superiority of assay-directed chemotherapy over empirical treatments (4–6). As a consequence, the validity of the whole concept of individualized chemotherapy was principially questioned by many oncologists. However, many of these studies were unable to unequivocally demonstrate a clinical benefit owing to severe technical limitations of the utilized assays such as low evaluability rates, long incubation periods, the requirement of large numbers of tumor cells, and a low degree of reproducibility (3,5,6). Nevertheless, it is quite clear from these early studies that individualized chemotherapy is extremely unlikely to worsen a patient’s clinical outcome (6). During the last two decades, a number of newer nonclonogenic assays have been developed that seem to overcome technical problems associated with older technologies. Among these, the adenosine triphosphate (ATP)–based tumor chemosensitivity assay (ATP-TCA) may be regarded as having the best track record for testing native tumor cells derived from nonhematological human malignancies (3,7). ATP is the ubiquitary end point of all energy-gaining processes in eukaryote cells. Moreover, after lethal cell demage, ATP levels drop to zero within a few milliseconds owing to the hydrolytic activity of intracellular adenosine triphosphatases (8). Thus, ATP may be regarded as the most sensitive marker for cell viability that can easily be measured by the luciferin–luciferase (Lu-Lu) bioluminescence reaction using the luciferase of various firefly species. Because of its extreme sensitivity, the lu-lu bioluminescence reaction is able to determine exactly the cellular ATP content of no more than 10 viable cells (9–11) Moreover, the relationship between the intracellular ATP and the luminescense response—i.e., the emission of visible light—remains linear over a broad concentration range (7,11). In the early 1980s, several groups combined bioluminescence measures that were initially used to test microbes with common cell culture methods in order to assess the viabilty of eukaryote cells, namely permanently growing tumor cell lines (8–10,12). Subsequently, these techniques have been adopted to

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develop novel nonclonogenic assays for pretherapeutic chemosensitivity testing of native tumor cells. Currently, three major types of ATP-based chemosensitivity assays exist, all incorporating the principles of nonadherence and/or selective culture conditions to guarantee the exclusive growth of neoplastic cells: the ATP cell viability assay (ATP-CVA) and its microplate modification, the serum-free ATP assay (SF-ATPA), and the ATP-TCA (7,13–15). All three types use techniques of both single cell and tissue culture simultaneously. Two major components guarantee the exclusive growth of neoplastic cells: the use of nonadherent culture plates in the ATP-CVAs and selective cell culture media in the SF-ATPA. The ATP-TCA, which was originally designed with respect to the requirement of a routine laboratory, combines both principles (3,7). To provide a higher degree of standardization, agar-coated culture vessels, which are used in the ATP-CVA, have been substituted by nonadherent polypropylene microplates. Another important advantage of the ATP-TCA is its suitability for both solid tumor samples and malignant effusions (3,7). A number of different tumor entities have since been investigated in depth using the ATP-TCA such as breast, ovarian, renal cell, pancreatic, colorectal, and lung cancer; malignant melanoma (cutaneous and choroidal type); retinoblastoma; and mesothelioma (3,7,16–25). The ATP-TCA provides evaluability rates of about 90% and a highly standardized methodology that makes this technique particularly suitable for multicenter investigations (3,7,17,18,20,22, 23). Comparison of the assay results with the clinical outcome of individual patients demonstrates a predictive accuracy of >90% for the majority of tumors tested, with a negative predictive value approaching 100% and a positive predictive value between 85 and 95%, respectively (17,26,27). Moreover, the ATPTCA has been found to accurately predict the survival of patients with primary International Federation of Gynecology and Obstetrics stage III ovarian carcinomas undergoing postoperative platinum-based chemotherapy (28). Because of these technical advantages, the assay has already been used successfully to screen for novel chemotherapy regimens to be subsequently used in patients with advanced or recurrent ovarian, breast, or colorectal cancer and malignant melanoma (20,27,29,30). Additionally, the ATP-TCA appears to be a valuable tool in the preclinical development of investigational cytostatics using both native tumor cells and permanently growing cell lines that can be tested with a slightly modified methodology (19,31–33). During the last decade, we conducted a number of prospective clinical trials of ATP-TCA-directed chemotherapy in patients with pretreated solid neoplasms. In a first case-control intervention study in patients with recurrent ovarian cancer, individual chemotherapy produced both a threefold increase in clinical responses and a doubled progression-free and overall survival (Fig. 1)

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Fig. 1. Survival curves of ATP-TCA-directed chemotherapy in patients with recurrent ovarian cancer vs empirically chosen chemotherapy: (A) overall survival; (B) progression-free survival. (Reprinted from ref. 34 with permission of the publisher.)

(34). Two subsequent phase II trials in heavily pretreated patients with recurrent ovarian cancer that were independently run in both the United Kingdom and Germany showed response rates of 59 and 68% and a median overall survival of 15 and 21 mo, respectively (26,35,36). The most exciting finding of both these trials was the fact that patients with platinum-refractory disease did as well as those with potentially platinum-sensitive tumors, a result that is clearly unique in comparison to empirical chemotherapy for recurrent ovarian carcinoma. As a consequence, we set up a phase III trial of ATP-TCA-directed vs empirically chosen chemotherapy in patients with platinum-refractory relapsed ovarian carcinoma; recruitment was stopped in February 2003. The first follow-

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up data, which will be available at the end of 2004, are eagerly awaited. Recently, additional clinical trials of ATP-TCA-directed chemotherapy in breast and ovarian cancer and malignant melanoma are actively recruiting patients in different European countries and will help to determine further the role of individually tailored chemotherapy as a routine procedure in clinical oncology. 2. Materials 2.1. ATP-TCA Kits For the ATP-TCA, commercially available test kits (TCA 100®, Sartoritest®, DCS Innovative Diagnostik Systeme, Hamburg, Germany) providing the following materials, reagents, and medium are used: 1. Two sterile disposable scalpels (no. 11). 2. Disposable syringe (10 mL) and 0.22-µm cellulose acetate filter. 3. Sterile serum- and glutathione (GSH)-free complete assay medium (CAM) (250 mL) at 2–8°C. 4. Sterile round-bottomed 96-well polypropylene microplates (Costar no. 4690). 5. Lyophilized tumor dissociation enzymes (TDE); these must be reconstituted with 10 mL of CAM. TDE solution can be stored briefly at 2–8°C. Reconstituted TDE can be stored longer at –20°C. Reagent that has been frozen and thawed should not be frozen again. 6. Sterile maximum ATP inhibitor reagent (MI) (4 mL); store at 2–8°C. 7. Sterile buffered tumor cell extraction reagent (TCER) (20 mL); store at 2–8°C. 8. Sterile reconstitution buffer, pH 7.8 (dilution buffer) (20 mL). 9. Luciferin–luciferase light reagent (Lu-Lu): a lyophilized mixture of D-luciferin and luciferase (EC 1.13.12.7) must be reconstituted with 15 mL of dilution buffer and is ready to use after subsequent incubation for 30 min at room temperature. Reconstituted Lu-Lu can be stored in the dark at 2–8°C for a maximum of 14 d. Longer storage is possible at –20°C. Lu-Lu that has been frozen and thawed must not be frozen again. 10. ATP lyophilizate (500 ng) to be dissolved in 2 mL of dilution buffer. Reconstituted ATP standard can be stored briefly at 2–8°C or for a longer period at –20°C.

2.2. Additional Materials The following reagents, medium, and materials not included in the ATPTCA kit are also required: 1. 2. 3. 4.

Sterile conical centrifuge tubes (15 and 50 mL). Sterile disposable pipets (1, 5, and 10 mL). Adjustable automated pipets (0–200 µL, 200–1000 µL) with sterile tips. Adjustable automated multichannel pipets (6-, 8-, or 12-fold) at 0–200 µL with sterile tips. 5. Sterile disposable Petri dishes (100 × 15 mm).

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6. Round-bottomed polysterol tubes (12 × 75 mm) (no. 55476, Sarstedt, Nümbrecht, Germany) to be used in chain luminometers or 96-well white microplates (Costar no. 3912/13) to be used in microplate luminometers. 7. Neubauer hemocytometer (0.1 mm). 8. Sterile destilled water. 9. Sterile preservative-free sodium-heparin (Vetren®, Promonta, Hamburg, Germany). 10. Sterile Ficoll-Hypaque® (1077 g/mL). 11. Trypan blue solution (0.14%).

2.3. Laboratory Equipment The ATP-TCA can be performed in a routine cell culture laboratory providing the following equipment: 1. 2. 3. 4. 5. 6. 7.

Centrifuge (minimum: 400g). Inverted and phase-contrast microscopes. Class II laminar airflow cabinet. Humidified incubator (37°C, 5% CO2). Chain or plate luminometer. Shaker water bath, 37°C (facultative). Personal computer.

2.4. Drugs The ATP-TCA uses commercial formulations of most common antineoplastic agents except cyclophosphamide (CPA) and ifosfamide (IFO) and hormonal agents. CPA and IFO are inactive in vitro and must be substituted either by their activated metabolites 4-hydroperoxy-cyclophosphamide (4-HC) and 4-hydroperoxy-IFO, respectively, or by mafosfamide cyclohexylamine, which is able to generate 4-HC after dissociation in watery solution. All three active derivatives are provided by ASTA Medica (Frankfurt, Germany). Hormonal agents should be used as free substances and must be dissolved in absolute ethanol prior to use. Stock solutions of drugs should be prepared and stored according to the manufacturer’s instructions and to previous publications (7,37). If information about the adequate solvent is not provided by the manufacturer, stock solutions should be prepared with CAM except melphalan (L-PAM; methanol 100%) and nitrosoureas (100% ethanol). Detailed information is summarized in Table 1. 3. Methods 3.1. Sampling of Tumor Specimens The methodology of the ATP-TCA is illustrated in Fig. 2. Native tumor cells derived from both solid tumors and effusions can be tested with the ATP-TCA (see Notes 1 and 2). Strict asepsis is mandatory during all steps of cell collec-

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Table 1 Preclinical Characteristics of Single Agents Tested in ATP-TCA Drug Actinomycin D Bleomycin Carboplatin Carmustine Cisplatin 4-OOH-cyclophosphamide Cytosine arabinoside Dacarbacin Daunorubicin Docetaxel Doxorubicin Epirubicin Etoposide Ca-folinate 5-Fluorouracil Gemcitabine Irinotecan Melphalan Methotrexate Mitomycin C Mitoxantrone Oxaliplatin Paclitaxel Tamoxifen Thiotepa Topotecan Treosulfan Vinblastine Vincristine Vindesine Vinorelbine a

Clinical dosage Stock solution (mg/m2)a (mg/mL)b

100% TDC (µg/mL)

Storage of stock solutionc

1110.51 30 mg abs. 14001.1 5 × 100 11001.1 10001.1

0.1 3.0 15.8 4.0 3.8 3.0

1.0 3.0 10.0 3.3 2.0 5.0

–70°C/6 mo 2–8°C/28 d 2–8°C/5 d 2–8°C/2 d 2–8°C/2 d –20°C/3 mo

11001.1 5 × 250 11601.1 11001.1 11751.1 11901.1 3 × 100 14501,1 10001.1 10001,1 13501,1 4 × 10 11401.1 11121.1 11121.1 11301.1 11751.1 20 mg daily 11601.1 1111.25 50001.. 11141.. 111111. 111411. 113011.

2.4 20.0 0.4 11.3 0.5 0.5 48.0 1.2 22.5 25.0 100.0 1.8 2.8 0.23 0.6 5.0 13.6 20.0 2.0 0.75 20.0 0.5 0.5 0.4 1.94

20.0 10.0 1.0 5.0 2.0 2.0 20.0 10.0 50.0 40.0 20.0 0.5 2.5 1.0 2.0 5.0 6.0 50.0 5.0 1.0 50.0 1.0 1.0 1.0 10.0

2–8°C/8 d 2–8°C/4 d 2–8°C/28 d –70°C/3 mo 2–8°C/28 d 2–8°C/2 d 25°C/28 d 2–8°C/28 d 25°C/28 d –70°C/6 mo –20°C/6 mo — 2–8°C/28 d 2–8°C/14 d 25°C/28 d –20°C/6 mo 2–8°C/28 d –70°C/6 mo 2–8°C/5 d –70°C/3 mo –70°C/3 mo 2–8°C/30 d 2–8°C/14 d 2–8°C/28 d 2–8°C/28 d

Clinical standard dosage Stocks of drugs should be prepared in sterile water or saline according to the manufacturer’s instructions. c See ref. 37 or refer to the manufacturer’s instructions. b

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Fig. 2. Methodology of ATP-based tumor sensitivity assay.

tion and processing. If possible, solid material for chemosensitivity testing should be separated intraoperatively provided that histopathological diagnosis and staging are not compromised. If the surgeon cannot decide which part of the tumor should be reserved for ATP-TCA, it is also appropriate to transfer the whole tissue to the pathologist prior to separation. One should be aware, however, that this may increase the risk of contamination. 1. After sampling, place solid specimens into a sterile tightly closed transport vessel containing Hank’s balanced salt solution or serum-free Dulbecco’s modified Eagle’s medium (DMEM) with antibiotics (200 IU/mL of penicillin, 100 µg/mL of streptomycin). In potentially infected probes (i.e., tumors derived from the skin, upper aerodigestive tract, bronchi, large bowel, or lower female genital tract), transport medium should additionally contain 2.5 µg/mL of amphotericin B and 1 µg/mL of metronidazole (20) (see Note 3). 2. Collect malignant effusions by paracenthesis. 3. Coagulate all exudates with 10 IU/mL of sodium heparin. 4. Do not fix or freeze samples. Perfrom transport and storage at room temperature; gentle cooling may be appropriate at temperatures exceeding 25°C. Process all specimens as soon as possible, preferably within 24 h after sampling.

3.2. Preparation of Cell Suspensions The ATP-TCA utilizes cell suspensions containing both single cells and small organoid aggregates composed of tumor cells and stroma. All preparation steps are carried out under a laminar airflow hood.

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1. Place solid specimens in a 10-cm Petri dish to remove necrotic parts, fat, and connective tissue using sterile scissors and scalpels. 2. Add a few milliliters of serum-free DMEM, and then cut the tumor tissue into particles of approx 2 mm in diameter. 3. Pour the tumor fragments into a 15-mL test tube and mix with 10 mL of TDE. 4. Depending on the consistency of the individual material, the following enzymatic digestion can be performed either in a 37°C shaker bath for 2–4 h or overnight at 37°C in a humidified 5% CO2 atmosphere. 5. Pass the tumor lysate through an 80-µm mesh filter gauze in order to remove the undissociated particles. 6. Wash the enzymes by two centrifugation steps at 200g for 10 min after adding 10 mL of DMEM. 7. Fill 50-mL test tubes with aliquots of liquid samples and then centrifuge for 10 min at 200g in order to remove all the serum components. 8. Resuspend the pellets with 10 mL of DMEM. 9. Purify all tumor preparations by Ficoll-Hypaque density gradient centrifugation and subsequently resuspend in 1–5 mL of CAM. 10. Determine the quality and viabilty of the resulting tumor suspensions by cytological examination using Papanicolau or Wright-Giemsa staining and Trypan blue dye exclusion. 11. Add another amount of CAM, and then adjust the suspensions to a final concentration of 1 to 2 × 105 viable tumor cells/mL.

3.3. Final Drug Concentrations (see Note 4) All drugs and drug combinations are tested at six test drug concentrations (TDCs) ranging from 6.25 to 200%. Both therapeutic and supratherapeutic concentrations are included, with 100% TDC referring to either the plasma peak or a clinically relevant equivalent of the area under the plasma elimination curve. For each assay, 800% TDCs are freshly prepared in 10 mL of CAM from the aforementioned stock solutions (see Table 1) with drug combinations being made up by simply mixing an adequate amount of individual single agents. Final TDCs of both single agents and combinations are prepared directly on the culture plates by serial 11 dilutions. Each cytostatic regimen is tested in triplicates. 3.4. Preparation of Culture Plates All of the following preparation steps prior to incubation are performed directly on culture plates. Each plate comprises 72 test drug wells with each cytostatic regimen set up in triplicate and two internal controls in 12 wells of the remainder, a no-inhibition control (M0) with blank CAM, and a maximum inhibition control with MI instead of medium or drugs. The design of a culture plate is shown in Fig. 3. Preparation of culture plates should be performed as follows:

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Fig. 3. Design of a 96-well microplate to test four drugs or drug combinations in triplicates. MI, maximum inhibition control; M0, no inhibition control.

1. Add 100 µL of CAM to 84 wells of each microplate using a multichannel pipet and change the pipet tips. 2. Add 100 µL of MI to the remaining 12 wells and change the tips. 3. Add 100 µL of each drug or combination 800% TDC to either of three wells, and mix gently by repeated aspiration. Four regimens can be set up on every plate; starting wells should be positioned in the same row as shown in Fig. 3. 4. Transfer 100 µL of mixture to the subsequent three wells and mix gently. 5. Repeat step 4 until the last row is reached and mix gently. Aspirate 100 µL of the resultant dilution and discard it together with the pipet tips. Each well of the culture plate now contains 100 µL of blank CAM, MI, or drugs at serial 11 dilutions. 6. Add 100 µL of cell suspension to each well and mix gently.

3.5. Incubation Prepared microplates are covered and then transferred to a humidified 5% CO2 incubator with subsequent routine incubation for 6 (range: 5–7) d. Both to guarantee complete disappearance of stromal components and to allow the tumor cells time for sufficient DNA repair, the incubation period should not be shorter than 4 d. On the other hand, nutritive exhaustion may falsify the test results at incubation periods exceeding 8 d. To avoid drying artifacts, plates may be placed in a sterile wet chamber. 3.6. ATP Extraction At the end of incubation, another cytological examination should be performed using cells from three to six M0 wells in order to confirm tumor cell

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enrichment. From the remaining wells, cellular ATP is extracted and stabilized by the following procedure: 1. Add 50 µL of TCER to each MI and M0 control well using a multichannel pipet, mix gently by repeated aspiration without producing bubbles or foam, and change the pipet tips. 2. Add another 50 µL of TCER to each test well and mix gently. 3. Incubate the uncovered plates for 20–30 min at room temperature. 4. Immediately after ATP extraction and incubation, perform measurement as described in Subheading 3.7. Alternatively, extracted microplates can be frozen and stored at –20°C. Plates that have been frozen and thawed must be immediately processed for ATP measurement and should not be frozen again.

3.7. ATP Measurement by Firefly Luminescence Reaction After lysing the cells by adding TCER, ATP measurement should be performed within 1 h. Alternatively, lysed plates can be frozen and stored at –20°C without addition of cryoprotectants. Frozen plates should be thawed completely by appropriate incubation at 37°C. Prior to ATP determination, Lu-Lu must be dissolved in 15 µL of dilution buffer. After gently mixing, the reagent should be incubated at room temperature for 30 min and covered with aluminum foil in order to avoid loss of activity. For ATP determination, both chain and plate luminometers can be used. When using a chain luminometer, the procedure is as follows: 1. Aspirate 50 µL of each cell lysate separately and place it in a 12 × 75 mm counting tube. 2. Connect the bottle with Lu-Lu with the injector system of the luminometer. 3. Put five empty tubes (“washing tubes”) in the luminometer to guarantee complete preload of the injection system. 4. Leave one space blank and add another empty tube. 5. Put all the prepared tubes into the luminometer in the correct sequence of different regimens investigated. 6. Close the luminometer tightly and start the measurement; the counting time should be 10–15 s with a 4-s delay. 7. After ATP determination, wash the injection system five times with both 70% ethanol and distilled water in order to avoid microbial contamination.

Generally, the use of a plate luminometer is less time-consuming. Both devices with and without injectors are suitable. All lysates must first be transferred to a 96-well microplate. When using a luminometer with an injector, 50 µL of Lu-Lu will be automatically added to each well. The injector must be washed with Lu-Lu prior to ATP measurement according to the manufacturer’s instructions and afterward cleaned with both 70% ethanol and distilled water. When using devices without an injector, as we do in our laboratories, 50 µL of Lu-Lu must

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be manually pipetted to each well of the microplate. The plate must then be immediately placed into the counting chamber. For all types of plate luminometers, the counting time is 1 s. Luminescence response (i.e., the amount of visible light) is expressed as relative light units (RLU = photons/10). 3.8. Evaluation and Interpretation of Assay (see Note 5) For each tumor and drug, respectively, relative tumor growth inhibition (TGI) is determined by the following formula: TGI (%) = [1 – (RLUTest – RLUMI) / (RLUM0 – RLUMI)] × 100

(1)

The six TGI values of each regimen are then transferred into individual inhibition curves from which the following parameters are drawn by using DCS evaluation software based on Microsoft Excel®: AUIC = area under the inhibition curve, calculated by a trapezoidal rule IC50, IC90 = relative 50 and 90% inhibitory concentration (in % TDC) IndexSUM = natural logarithmic sum index calculated as 600 – ∑(TGI6.25 + ••• + TGI200)

When regarded separately, both the AUIC and IndexSUM can easily distinguish between principally resistant (AUIC < 12,500 and/or IndexSUM ≥ 300) and potentially sensitive tumors (AUIC ≥ 12,500; IndexSUM < 300). However, a more detailed differentiation is possible by using a semiquantitative score that integrates the other aforementioned parameters (29,34). A typical example is shown in Fig. 4: High sensitivity (S): AUIC ≥ 12,500/IndexSUM < 300; IC90 ≤ 90% TDC; IC50 ≤ 25% TDC Partial sensitivity (P): AUIC ≥ 12,500/IndexSUM < 300; IC90 > 90% TDC; IC50 ≤ 25% TDC Weak sensitivity (W): any other with AUIC ≥ 12,500/IndexSUM < 300 Resistance (R ): AUIC < 12,500/IndexSUM ≥ 300

When testing drug combinations, it may be of interest to obtain information about possible drug interactions, which requires separate testing of all single agents included. In the ATP-TCA, all components are tested in natural logarithmic dilutions. Therefore, the sigmoid action model described by Pöch et al. (38), which compares the actuarial dose-response curves with a theoretical one assuming that the components act independently (or additively), is considered the most reliable procedure to analyze drug interactions observed in this assay. This analysis may be performed by using the appropriate spreadsheet included in the DCS evaluation software. Automated interaction analysis can be per-

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Fig. 4. Typical dose-response curves achieved with different drugs tested in the ATPTCA. The different types of ex vivo chemosensitivity are adapted from ref. 29.

formed only if both the combination and the different single agents involved are set up on the same microplate. Figure 5 demonstrates different types of drug interactions ranging from antagonism to potentiation (or synergism). 3.9. ATP Standard Curve An ATP standard measurement should be performed as follows every day prior to the first assay evaluation in order to guarantee the linearity of all subsequent ATP determinations: 1. Mix the ATP lyophilisate with 2 mL of reconstitution buffer to prepare the ATP stock. Shake gently and wait a few minutes. The resultant stock ATP concentration is 250 ng/mL. 2. Add 300 µL of reconstitution buffer to each of nine 12 × 75 mm test tubes. 3. Add 150 µL of the ATP stock to the first tube, mix carefully, and transfer 150 µL to the second tube. Continue the procedure until the ninth tube. The final ATP concentrations of the resultant 13 dilution series are 83.33, 27.78, 9.26, 3.09, 1.03, 0.34, 0.11, 0.04, and 0.01 ng/mL. 4. Transfer a 50-µL aliquot of each dilution to either of three wells of a 96-well microplate or to three round-bottomed luminometer tubes (if a chain luminometer is used). Add both Reconstitution Buffer without ATP and the ATP stock solution to another three wells or tubes. Thus, the luminescence vs ATP concentration curve will range between 0 and 250 µg/mL. 5. Measure the ATP following the instructions in Subheading 3.7. When using a chain luminometer, it is preferred that the ATP measurement be performed using decreasing concentrations.

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Fig. 5. Drug interactions in two-drug combination analyzed with sigmoid model of Pöch (38). Combination C, potentiation (synergism); combination D, independent action (additivity); combination E, antagonism. The dashed line represents the theoretical dose-response curve for the combination assuming that both drugs act independently.

6. Graph the mean of each triplicate against the ATP concentrations. The Pearson’s correlation coefficient of the resulting dose-response plot should be at a minimum of 0.975.

3.10. Quality Control (see Notes 6 and 7) Particularly when using the ATP-TCA as a guide to select chemotherapy regimens for individual patients pretherapeutically, each assay must meet the following criteria to be considered as providing valid results (3,7,34): 1. Prior to being tested with the ATP-TCA, the malignant nature of the sample must be uneqivocally confirmed by morphological (histopathological or cytological) analysis. Additional immunohistochemistry or immunocytochemistry may prove useful in selected cases. 2. Tumor cell enrichment during the 5- to 7-d incubation period should be confirmed by pre- and postassay cytology. Preassay examination can be performed using the original cell suspension prior to seeding. Postassay evaluation must use cells derived from three M0 wells before TCER is added to the microplate. Cytological confirmation of tumor cell enrichment is particularly important in cases with a low initial tumor cell content and/or a low viabilty in order to demonstate the proliferative capacity of the specimen under culture conditions.

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3. Viable tumor cells must be able to proliferate in the ATP-TCA system. Low M0 values after 5–7 d of culturing may indicate a reduced proliferative activity, which often causes artificially high chemosensitivity ex vivo. Therefore, assays with a mean M0 0.01 should be regarded as being potentially infected and thus nonevaluable. 7. When performing ATP-TCA-based multicenter trials in which multiple laboratories are involved, quality control evaluations preferentially using easy-to-grow cell lines and simultaneous testing of a standard panel of drugs are strongly recommended.

4. Notes 1. Recently, the ATP-TCA has been regarded as the most advanced and best documented biological system for pretherapeutic chemosensitivity testing of native organ tumors. As mentioned in Subheading 1., clinical trials using the ATP-TCA to individually select chemotherapy all gave promising results. Numerous different tumor types including carcinomas of the breast, lung, stomach, pancreas, gallbladder, liver, colon, ovary, endometrium, uterine cervix, vulva, pharynx, larynx, and kidney have now been successfully tested with the ATP-TCA, as have various sarcomas, malignant brain tumors, mesotheliomas, and malignant melanomas of both the skin and the uvea. The assay may also be suitable to test hematological malignancies. However, growth characteristics and culture requirements of leukemias and lymphomas are only poorly elucidated so far (39). 2. Blood samples should be processed according to the recommendations for malignant effusions. Repeated density-gradient centrifugation is strongly recommended in these cases. In blood samples, the proportion of blasts should exceed 70%. Assuming the high intrinsic chemosensitivity of hematological malignancies, it

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Kurbacher and Cree may be appropriate to use 10-fold lower TDCs compared with the concentrations used for solid tumors to obtain reasonable test results. Another important problem is the prevention of microbial infection of the culture plates. Strictly aseptic conditions are therefore a must for all methodological steps of the ATP-TCA. Potentially contaminated samples should normally not be further processed. However, a recent publication has shown that infection of colon cancer specimens can effectively be prevented by adding both amphotericin B and metronidazole to the transport and culture media without deteriorating the tumor cell viability and biology (20). It may thus be important to routinely add these drugs to the media if the material is potentially contaminated and performing the ATP-TCA is mandatory in the individual case. Liposomal formulations of anthracyclines and other cytostatics are attracting increasing interest in modern oncology. Unfortunately, it is uncertain whether they can be tested directly in the ATP-TCA system. It is well known, however, that liposomal anthracyclines achieve a three- to fivefold higher intracellular accumulation compared with the parent compounds. Therefore, testing a threefold higher concentration of free anthracyclines may be regarded as a good substitute for the corresponding liposomal preparations (40,41). Strict quality criteria, as mentioned in Subheading 3.10., are mandatory to obtain valid test results with the ATP-TCA. Among these, demonstration of doseresponse relationships is particularly important. Dose-response curves should be sigmoid shaped, especially for alkylators, platinum analogs, and intercalating agents. Flat curves may indicate the absence of cells that have retained their complete proliferative capacity. However, some drugs are known to frequently produce such atypical dose-response curves. Antimetabolites such as methotrexate and vinca alkaloids may demonstrate flat curves as well. Moreover, cytidine analogs such as cytosine arabinoside and gemcitabine are internalized via a transmembranal energy-dependent transporter system that is refractory beyond a certain drug concentration (generally 50% TDC). Dose-response curves for these drugs therefore show remarkable plateau effects above this threshold concentration (30). To exclude artifacts, it is therefore recommended that both drugs with presumably typical curves and those often producing atypical curves be simultaneously incubated on the same culture plate. Among different other in vitro or ex vivo predictive assays, the ATP-TCA can be regarded as a true chemosensitivity assay owing to its exceptionally high positive predictive accuracy. This should be taken into account when deciding what chemotherapy regimens should be tested in an individual patient. It is of particular importance that drug combinations be assayed when the patient is planned to be treated with combination chemotherapy, because single agent activity ex vivo is unlikely to accurately predict its clinical efficacy when used as part of a combination regimen. Drug interactions may be more important for the clinical utility of a drug combination than the isolated activity of its components. Good examples are combinations of gemcitabine or cytosine arabinoside and platinum, or treo-

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sulfan or mitoxantrone and paclitaxel. These combinations display features of true clinical synergism, which may be related to resistance-modulating effects. As a consequence, these regimens have been shown to produce major preclinical and clinical activity even when both of the single agents included were completely inactive (26,29,30). Exclusive testing of single agents, which has been preferred in the past, is therefore appropriate only in cases in which combination chemotherapy is abandoned. 7. With slight modifications, the ATP-TCA can be used to test cell lines that may sometimes be preferred. However, note that cell lines including their resistant variants display a remarkably higher chemosensitivity compared to native tumors. This may be due to the absence of tumor stroma in permanent growing cell lines that are known to exhibit important chemomodulating effects. Moreover, the heterogeneity in cell lines is generally inferior to that in clinical tumors. By using modern nonclonogenic techniques such as the ATP-TCA, testing a large number of native samples per entity in a considerably short time may provide a more reliable estimate of the activity of the drug under investigation than evaluating a panel of different tumor cell lines (42). These methods are thus of particular interest in future preclinical development of novel agents and combinations (41,43).

References 1. Bellamy, W. T. (1992) Prediction of response to drug therapy of cancer: a review of in vitro assays. Drugs 44, 690–708. 2. De Vita, V. T. (1997) Principles of cancer management: chemotherapy, in Cancer: Principles and Practice of Oncology (DeVita, V. T., Hellman, S., and Rosenberg, S. A., eds.), Lippincott-Raven, Philadelphia, pp. 333–347. 3. Cree, I. A. and Kurbacher C. M. (1997) Individualizing chemotherapy for solid tumors—is there any alternative? Anti-Cancer Drugs 8, 541–548. 4. Von Hoff, D. D. (1990) He’s not going to talk about in vitro predictive assays again, is he? J. Natl. Cancer Inst. 82, 97–101. 5. Brown, E. and Markman, M. (1996) Tumor chemosensitivity and chemoresistance assays. Cancer 77, 1020–1025. 6. Cortazar, R. and Johnson, B. E. (1999) Review of the efficacy of individualized chemotherapy selected by in vitro drug sensitivity testing for patients with cancer. J. Clin. Oncol. 17, 1625–1631. 7. Andreotti, P. E., Cree, I. A., Kurbacher, C. M., et al. (1995) Chemosensitivity testing of human tumors using a microplate adenosine triphosphate luminescence assay: clinical correlation for cisplatin resistance of ovarian carcinoma. Cancer Res. 55, 5276–5282. 8. Kangas, L., Grønroos, M., and Nieminen, A. (1984) Bioluminescence of cellular ATP: a new method for evaluating cytotoxic agents in vitro. Med. Biol. 62, 338–343. 9. Kuzmits, R., Rumpold, H., Muller, M., and Schopf, G. (1986) The use of bioluminescence to evaluate the influence of chemotherapeutic drugs on ATP levels of malignant cell lines. J. Clin. Chem. Clin. Biochem. 24, 293–298.

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10. Maehara, Y., Anai, H., Tamada, R., and Sugimachi, K. (1987) The ATP assay is more sensitive than the succinate dehydrogenase inhibition test for predicting cell viability. Eur. J. Cancer Clin. Oncol. 23, 273–276. 11. Petty, R. D., Sutherland, L. A., Hunter, E. M., and Cree, I. A. (1995) Comparison of MTT and ATP-based assays for the measurement of viable cell number. J. Biolum. Chemilum. 10, 29–34. 12. Ahmann, F., Garewal, H., Schifman, R., Celniker, A., and Rodney, S (1987) Intracellular adenosine triphosphate as a measure of human tumor cell viability and drug modulated growth. In Vitro Cell. Dev. Biol. 23, 474–480. 13. Sevin, B.-U., Peng, Z., Perras, J., Penalver, G., and Averette, H. (1988) Application of an ATP bioluminescence assay in human tumor chemosensitivity testing. Gynecol. Oncol. 31, 191–204. 14. Koechli, O. R., Avner, B. P., Sevin, B.-U., et al. (1994) Application of the ATP-Cell Viability Assay in human breast cancer chemosensitivity testing: a report on the first results. J. Surg. Oncol. 54, 119–125. 15. Tereshima, M., Ikeda, K., Kawamura, H., et al. (1994) A comparative study on the ATP assay in serum-free media and the adhesive tumor cell culture system as a drug sensitivity test for human esophageal cancer. Cancer Res. Ther. Control 3, 297–304. 16. Hunter, E. M., Sutherland, L. A., Cree, I. A., Dewar, J. A., Preece, P. E., and Andreotti, P. E. (1993) Heterogeneity of chemosensitivity in human breast carcinoma: use of an adenosine triphosphate (ATP) chemiluminescence assay. Eur. J. Surg. Oncol. 19, 242–249. 17. Cree, I. A., Kurbacher, C. M., Untch, M., et al. (1996) Correlation of the clinical response to chemotherapy in breast cancer with ex vivo chemosensitivity. AntiCancer Drugs 7, 630–635. 18. Kurbacher, C. M., Cree, I. A., Brenne, U., et al. (1996) Heterogeneity of in vitro chemosensitivity in perioperative breast cancer cells to mitoxantrone versus doxorubicin evaluated by a microplate ATP bioluminescence assay. Breast Cancer Res. Treat. 41, 161–170. 19. Kurbacher, C. M., Nagel, W., Mallmann, P., et al. (1994) In vitro activity of titanocenedichloride in human renal cell carcinoma compared to conventional antineoplastic agents. Anticancer Res. 14, 1529–1534. 20. Whitehouse, P. A., Knight, L. A., Di Nicolantonio, F., Mercer, S. J., Sharma, S., and Cree, I. A. (2003) Heterogeneity of chemosensitivity of colorectal adenocarcinoma determined by a modified ex vivo ATP-tumor chemosensitivity assay. AntiCancer Drugs 14, 369–375. 21. Lee, J.-M., Bruckner, H. W., Szrajer, L., and Brenne, U. (1995) Taxol inhibits growth of mesothelioma xenografts. Anticancer Res. 15, 693–696. 22. Myatt, N., Cree, I. A., Kurbacher, C. M., Foss, A. J. E., Hungerford, J. L., and Plowman, P. N. (1997) The ex vivo chemosensitivity profile of choroidal melanoma. Anti-Cancer Drugs 8, 756–762. 23. Cree, I. A., Neale, M. H., Myatt, N. E., et al. (1999) Heterogeneity of chemosensitivity of metastatic cutaneous melanoma. Anti-Cancer Drugs 10, 437–444.

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24. Ugurel, S., Tilgen, W., and Reinhold, U. (2003) Chemosensitivity testing in malignant melanoma. Recent Results Cancer Res. 161, 81–92. 25. Di Nicolantonio, F., Neale M., Onadim, Z., Hungerford, J. L., Kingston, J., and Cree, I. A. (2003) The chemosensitivity profile of retinoblastoma. Recent Results Cancer Res. 161, 73–80. 26. Kurbacher, C. M., Grecu, O. M., Stier, U., et al. (2003) ATP chemosensitivity testing in ovarian and breast cancer: early clinical trials. Recent Results Cancer Res. 161, 221–230. 27. Untch, M., Ditsch, N., Langer, E., et al. (2003) Chemosensitivity testing in gynecologic oncology—dream or reality? Recent Results Cancer Res. 161, 146–158. 28. Konecny, G., Crohns, C., Pegram, M., et al. (2000) Correlation of drug response with the ATP tumor chemosensitivity assay in primary FIGO stage III ovarian cancer. Gynecol. Oncol. 77, 258–263. 29. Kurbacher, C. M., Bruckner, H. W., Cree, I. A., et al. (1997) Mitoxantrone combined with paclitaxel as salvage therapy for platinum-refractory ovarian cancer: laboratory study and clinical pilot trial. Clin. Cancer Res. 3, 1527–1533. 30. Neale, M. H., Myatt, N., Cree, I. A., et al. (1999) Combination chemotherapy for choroidal melanoma: ex vivo sensitivity to treaosulfan with gemcitabine or cytosine arabinoside. Br. J. Cancer 79, 1487–1493. 31. Kurbacher, C. M., Mallmann, P., Kurbacher, J. A., et al. (1994) In vitro activity of titanocenedichloride versus cisplatin and doxorubicin in primary and recurrent epithelial ovarian cancer. Anticancer Res. 14, 1961–1966. 32. Neale, M. H., Charlton, P. A., and Cree, I. A. (2000) Ex vivo activity of XR5000 against solid tumors. Anti-Cancer Drugs 11, 471–478. 33. Kurbacher, C. M., Bruckner, H. W., Andreotti, P. E., Kurbacher, J. A., Saβ, G., and Krebs, D. (1995) In vitro activity of titanocenedichloride in four ovarian carcinoma cell lines evaluated by a microtiter plate ATP bioluminescence assay. AntiCancer Drugs 6, 697–704. 34. Kurbacher, C. M., Cree, I. A., Bruckner, H. W., et al. (1998) Use of an ex vivo ATP luminescence assay to direct chemotherapy for recurrent ovarian cancer. AntiCancer Drugs 9, 51–57. 35. Kurbacher, C. M., Stier, U., Janät, M.-M., Cree, I. A., and Bruckner, H. W. (2001) ATP-assay directed chemotherapy for recurrent ovarian cancer: mature results of an ISCO clinical study group trial. Proc. Am. Soc. Clin. Oncol. 20, 185b. 36. Sharma, S., Neale, M. H., Di Nicolantonio, F., et al. (2003) Outcome of ATPbased tumor chemosensitvity assay directed chemotherapy in heavily pretreated ovarian carcinoma. BMC Cancer 3, 19. 37. Hunter, E. M., Sutherland, L. A., Cree, I. A., Subedi, A. M. C., Hartmann, D., Linder, D., and Andreotti, P. E. (1994) The influence of storage on cytotoxic drug activity in an ATP-based chemosensitivity assay. Anti-Cancer Drugs 5, 171–176. 38. Pöch, G. (1993) Combined Effects of Drugs and Toxic Agents: Modern Evaluation in Theory and Practice, Springer, Vienna, Austria. 39. Andreotti, P. E., Linder, D., Hartmann, D. M., et al. (1993) ATP tumor chemosensitivity assay: application for solid tumor and leukemia, in Bioluminescence and

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41. 42.

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Chemiluminescence: Current Status (Szalay, A. A., Stanley, P. E., and Kricka, L. J., eds.), John Wiley & Sons, Chichester, UK, pp. 271–275. Neale, M. H., Lamont, A., Hindley, A., Kurbacher, C. M., and Cree, I. A. (2000) The ex vivo effect of high concentrations of doxorubicin on recurrent ovarian carcinoma. Anti-Cancer Drugs 11, 865–871. Cree, I. A. and Kurbacher, C. M. (1999) ATP based tumour chemosensitivity testing: assisting new agent development. Anti-Cancer Drugs 10, 431–435. Andreotti, P. E., Linder, D., Hartmann, D. M., Cree, I. A., Pazzagli, M., and Bruckner, H. W. (1994) TCA-100 Tumor Chemosensitivity Assay: differences in sensitivity between cultured tumor cell lines and clinical studies. J. Biolum. Chemilum. 9, 373–378. Cree, I. A. (2003) Chemosensitivity testing as an aid to anti-cancer drug and regimen development. Recent Results Cancer Res. 161, 119–125.

11 High-Throughput Technology Green Fluorescent Protein to Monitor Cell Death Marylène Fortin, Ann-Muriel Steff, and Patrice Hugo Summary Reliable assessment of cell death is now pivotal to many research programs aiming at generating new antitumor compounds or at screening cDNA libraries to identify genes with pro- or antiapoptotic functions. Such approaches need to rely on reproducible, easy handling, and rapid microplate-based cytotoxicity assays that are amenable to high-throughput screening technologies. We describe here a method for the direct measurement of cell death, based on the detection of a decrease in fluorescence observed following death induction in cells stably expressing enhanced green fluorescent protein (EGFP). Our data clearly show that such a decrease in EGFP fluorescence after cell death induction happens in various cell types, including those routinely used in anticancer drug screening (i.e., murine and human, lymphoid, fibroblastic, or epithelial cell lines). Moreover, the decrease in EGFP fluorescence is observed in cells induced to die by a variety of apoptosis-inducing agents, such as glucocorticoids (dexamethasone), DNAdamaging agents (etoposide, cisplatin), microtubule disorganizers (paclitaxel), protein kinase C inhibitors (staurosporine), or a caspase-independent apoptotic stimulus (CD45 crosslinking). A decrease in fluorescence can be assessed either by flow cytometry or with a fluorescence microplate reader. The kinetics and specificity of this EGFP-based assay were comparable with those of other conventional techniques used to detect cell death. This novel EGFP-based microplate assay combines sensitivity and rapidity and is amenable to high-throughput setups, making it an assay of choice for evaluation of cell cytotoxicity.

Key Words Green fluorescent protein; apoptosis; cell death; high-throughput screening; flow cytometry; fluorescence plate reader; cytotoxicity.

1. Introduction Several approaches have been developed to assess cellular viability based on the targeting of various cellular components. For instance, measurement of From: Methods in Molecular Medicine, vol. 110: Chemosensitivity: Vol. 1: In Vitro Assays Edited by: R. D. Blumenthal © Humana Press Inc., Totowa, NJ

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the ability of a cell to uptake or retain vital probes (e.g., propidium iodide) (1–3), measurement of the cellular metabolic activity by mitochondrial activity (e.g., 3-(4,5-dimethylthiazolyl-2)-2,5-diphenyltetrazolium bromide assay, rhodamine 123 staining) or labeled nucleotide (e.g., radioactive thymidine) incorporation into the DNA (4–8), the release into the culture medium of cellular contents (e.g., 51Cr-release assay, intracytoplasmic enzyme–release assay) (9), the remodeling of chromatin by labeling of DNA with dyes (e.g., DAPI, Hoechst) (10–12), or the specific labeling of nicked DNA (i.e., TUNEL assay) (13) have conventionally been used to assess cell viability. One drawback shared by these assays is that they all require the addition of staining reagents and washing of the cells. Moreover, after these assays are carried out, cells cannot be reused, thus preventing dynamic studies. A high number of samples is therefore necessary to cover a range of time points for each drug to be tested. A simple alternative to these assays would be to use fluorescent probes directly synthesized within the cells, which could be used to monitor viability of the cells without affecting their potential to grow further in culture. We provide here detailed information on a method for the direct evaluation of cell viability, based on the fact that cells transfected with the enhanced green fluorescent protein (EGFP) gene display a loss in EGFP-mediated fluorescence after the induction of cell death. The GFP from Aequoria victoria has been shown to be an ideal reporter gene for in vitro (14) and even in vivo assays (15). This protein exhibits a spontaneous fluorescence in diverse cell types that does not require the presence of cofactors or substrates. Furthermore, GFP fluorescence can be easily monitored and quantified by a conventional flow cytometry unit or microplate-based fluorometric readers (16). The EGFP-based assay described here for the monitoring of cell death cumulates several advantages: 1. It only requires to derive a cell line of interest stably expressing high levels of EGFP. 2. It does not necessitate the addition of reagents, substrates, or buffers, thus minimizing time, expenses, and quality control steps. 3. It is as sensitive as other methods for measuring cytotoxicity. 4. It can be used at the cellular or population levels. 5. It is easily amenable to automation in high-throughput screening (HTS) setups. 6. It allows real-time and kinetic measurements of cell death, because the detection of the loss of EGFP fluorescence does not damage or alter the cells.

Accordingly, applications for this GFP-based cytotoxicity assay are diverse, ranging from anticancer drug screening to the screening of cDNA libraries for the identification of new pro- or antiapoptotic genes. Although the technique described in this chapter is applicable to diverse cell types, including adherent

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and nonadherent cells, a murine T-cell hybridoma cell line stably expressing EGFP is used to illustrate this method for detection of apoptosis. 2. Materials 2.1. Generation of Cell Line Stably Expressing EGFP 1. Retroviral vector encoding EGFP (LZRS-pBMN-IRES-EGFP; a gift from Dr. H. Spits) (17). EGFP is a Ser65 → Thr, Phe64 → Leu GFP mutant (BD BioSciences, Clontech, Palo Alto, CA; [18]). 2. Ecotropic BOSC 23 packaging cell line (American Type Culture Collection no. CRL-11270). 3. Iscove’s modified Eagle’s medium (IMDM) cell culture medium supplemented with 10% fetal calf serum (FCS) (Wisent, St-Bruno, Quebec, Canada). 4. Freezing medium: 90% (v/v) FCS and 10% (v/v) dimethyl sulfoxide. 5. OPTI medium (Invitrogen, Burlington, ON, Canada). 6. Lipofectamine and Plus reagent (Invitrogen). 7. Phosphate-buffered saline (PBS). 8. Trypsin-EDTA solution: 0.25% trypsin, 0.03% EDTA (Wisent). 9. Puromycin (Sigma Aldrich, Oakville, Ontario, Canada). 10. DO11.10 cells (murine T-cell hybridoma) (19). 11. RPMI-1640 supplemented with 20% FCS (Wisent). 12. Coulter XL flow cytometer (Beckman Coulter, Ville St-Laurent, Quebec, Canada). 13. FACStar cell sorter (Becton Dickinson, San Jose, CA).

2.2. Flow Cytometric Detection of Apoptosis Through Monitoring of the Decrease in EGFP Fluorescence in Cells Induced to Undergo Apoptosis 1. 2. 3. 4. 5.

RPMI-1640 cell culture medium supplemented with 5% FCS (Wisent). Dexamethasone (Sigma Aldrich). Propidium iodide (PI) (Sigma Aldrich). Dihydroethidium (Molecular Probes, Eugene, OR). AnnexinV (BioDesign, Kennebunk, ME).

2.3. Adaptation of GFP-Based Assay to High-Throughput Settings 1. Black/clear-bottomed 96-well plate (Falcon Microtest, Optilux 1; Fisher, Ontario, Canada). 2. Analyst HTS assay detection system (LJL BioSystem, Sunnyvale, CA) equipped with 485- and 530-nm excitation and emission filters, respectively.

3. Methods 3.1. Generation of Cell Line Stably Expressing EGFP The procedure used to generate DO11.10 cells stably expressing EGFP relies on retroviral infection performed with the LZRS-pBMN-IRES-EGFP

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bicistronic vector (kindly provided by G. Nolan). This vector is a murine Moloney leukemia virus–based retroviral vector encoding the EGFP located downstream of an internal ribosome entry site and under the control of the viral long terminal repeat promoter. The EGFP protein is a Ser65 → Thr, Phe64 → Leu GFP mutant displaying high fluorescence intensity. The vector also contains ampicillin and puromycin resistance genes for selection into bacteria and mammalian cells, respectively. Generation of the EGFP-expressing cell lines involves introduction of the retroviral vector into a packaging cell line (BOSC 23) by standard lipofectamine transfection procedures, and the subsequent infection of a cell line with the supernatant of the retrovirus-producing packaging cell line, as described in more detail in Subheadings 3.1.1. and 3.2.2., respectively. Transduction of the murine T-cell hybridoma DO11.10 serves as an example to illustrate the technique. Stable EGFP expression can also be achieved using other standard transduction methods (see Notes 1 and 2). 3.1.1. Transfection of BOSC 23 Packaging Cell Line

Thaw fresh BOSC 23 cells and maintain them in IMDM cell culture medium supplemented with 10% FCS. Because the viral production capabilities of these cells diminish after a few weeks in culture, plan to perform transfections as soon as the cells have recovered (i.e., 4 or 5 d after thawing). We recommend not to split the cells at a dilution higher than 15 in order to maintain homogeneity and avoid the generation of clonal variants. Do not let the cells become overconfluent, for cell clump formation might result in reduced transfection efficiency. It is important to freeze a large number of backup vials (50–100) of BOSC 23 cells at early passages; this will allow uniform and efficient virus production over several years. To freeze the cells, spin 5 × 106 cells at 4°C, remove the supernatant, and add 1 mL of cold freezing medium. Allow the cells to freeze slowly by placing the vials in a Styrofoam holder in a –80°C freezer for 48 h; then place the vials in a liquid nitrogen tank. 3.1.1.1. DAY 0 1. Split the BOSC 23 cells into wells of a six-well plate. 2. Prepare three wells with different cell numbers (e.g., 3 × 105, 6 × 105, and 1 × 106 cells per well), in order to be able to choose the best cell confluence for transfection the following day. 3. Let the cells adhere overnight. The highest transfection efficiencies are obtained with BOSC 23 cells that are 70–80% confluent at the time of transfection.

3.1.1.2. DAY 1 1. Select the well where confluence has reached 70–80%. Carefully rinse the cells to be transfected with OPTI medium or with other serum-free medium (make sure that the cells do not detach by gently pipetting the medium on the side of the well).


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2. Prepare the two following solutions: a. Solution A: Bring 4 µg of DNA (at 1 µg/µL) up to 80 µL with OPTI medium, and then add 20 µL of lipofectamine Plus reagent (do not add the Plus reagent directly to the DNA; it may precipitate out). Let sit at room temperature for 15 min. b. Solution B: Combine 8 µL of lipofectamine and 92 µL of OPTI, and let sit at room temperature for 15 min. 3. Combine solutions A and B and incubate for 15–30 min at room temperature (solution C). 4. Add 800 µL of OPTI medium to solution C and dispense into wells containing cells to be transfected. Keep one well of cells without DNA as a negative control (solution C without DNA). 5. Incubate for 3 h at 37°C under gentle rocking. 6. Add 4 mL of IMDM medium supplemented with FCS to reach a 20% final concentration of serum and culture overnight.

3.1.1.3. DAY 2 1. Remove the medium; rinse with 4 mL of PBS; and add 1 mL of 0.25% trypsin, 0.03% EDTA solution. Incubate the plate at 37°C until the cells detach. Resuspend the cells in fresh IMDM 10% FCS medium, and transfer into a 10-cm Petri dish. Keep an aliquot of cells for determination of the percentage of EGFP+ cells by flow cytometry analysis. Prepare an aliquot of nontransfected cells as a negative control. Transfection efficiencies usually range between 5 and 15%. Retrovirus-producing cells must be handled in Level 2 facilities (for more details on safety issues related to the use of retroviruses, see “Biosafety in Microbiological and Biomedical Laboratories,” http://www.cdc.gov/od/ohs/pdffiles/4th%20BMBL. pdf). 2. Begin selection by culturing the cells in IMDM 10% FCS medium supplemented with 1 µg/mL of puromycin. Selection of puromycin-resistant cells takes from 4 to 6 d. During the selection process, it is possible that dead cells will accumulate and that the culture medium will become yellow. In this case, simply aspirate the medium to remove the nonadherent dead cells and add fresh medium containing puromycin. However, do not trypsinize the cells until the selection process is complete.

3.1.1.4. DAYS 6–8 1. When the cells are confluent, trypsinize and transfer the cells into a 15-cm Petri dish with 10 mL of IMDM 10% FCS medium supplemented with 1 µg/mL of puromycin. Keep an aliquot of the cells for determination of the percentage of EGFP+ cells by flow cytometry analysis (use nontransfected cells as a negative control). A high percentage of EGFP+ cells (80% or more) is required to ensure maximal viral production. If the percentage of EGFP+ cells is higher than 80%, plan to collect the viral supernatant the next day or 2 d later, i.e., when the cells reach 75% confluence in the 15-cm Petri dish. If the percentage of EGFP+ cells has not reached 80%, maintain the selection with 1 µg/mL of puromycin for an additional 3–5 d and split the cells when necessary. If this does not result in an

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3.1.2. Infection of DO11.10 Murine T-Cell Hybridoma with Retroviral Supernatant 3.1.2.1. DAY 1 1. Rinse the BOSC 23 producer cells twice with 10 mL of OPTI medium. 2. For viral production, add 10 mL of OPTI medium and incubate for 6 h at 37°C with gentle rocking. 3. Harvest the viral supernatant, centrifuge for 10 min at 200g, and filtrate the supernatant on an acetate filter (0.45 µm) to remove any cell debris. Prepare 2-mL aliquots and freeze at –80°C or use immediately. Frozen supernatant can be kept for up to 3 mo; however, fresh viral supernatant gives better transduction efficiencies. 4. Keep the producer cells with IMDM 10% FCS supplemented with puromycin for a second viral production the following day; then discard the producer cells. 5. Take a 2-mL aliquot of viral supernatant, add 2 µL of lipofectamine, and incubate at room temperature for 15 min (solution D). 6. Wash the DO11.10 cells (target cells) with PBS, and resuspend 2 × 105 cells in 2 mL of solution D (viral supernatant plus lipofectamine). 7. Transfer the cells to a well in a six-well plate and culture overnight at 37°C under gentle rocking. Plate the cells without viral supernatant as a negative control.

3.1.2.2. DAY 2 1. Add 2 mL of RPMI-1640 supplemented with 20% FCS to each well. Culture overnight at 37°C.

3.1.2.3. DAY 3 1. Transfer the cells of a well into a T75 flask. Keep an aliquot of cells for the determination of the percentage of EGFP+ cells by flow cytometry, using noninfected cells as a negative control. Transduction efficiencies usually range between 2 and 15% (for this specific cell type). At this stage, puromycin selection can be used in order to increase the proportion of EGFP+ cells before cell sorting (the optimal puromycin concentration must be determined for each specific cell type). Plan to accumulate large quantities of retrovirally transduced cells for cell sorting by fluorescence-activated cell sorting (FACS).

3.1.2.4. DAYS 4–7 1. Sort the EGFP+ cells by FACS. Many successive rounds of cell sorting might be required in order to obtain cell populations in which nearly 100% of the cells are EGFP+ (see Note 3). It is also important to obtain cells expressing high levels of EGFP, because the higher the intensity of fluorescence, the easier will be the discrimination of dead cells in future assays. It is recommended that EGFP-expressing and EGFP– cells display at least one log difference in fluorescence intensity.


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2. When a cell culture in which nearly 100% of the cells express high levels of EGFP is obtained (DO11.10-EGFP), prepare a large number of vials (25–50) of frozen cells for subsequent uses (see Subheading 3.1.1. for the freezing procedure).

3.2. Flow Cytometric Detection of Apoptosis Through Monitoring of Decrease in EGFP Fluorescence in Cells Induced to Undergo Apoptosis This section describes the EGFP-based assay for the monitoring of cell death by flow cytometry and provides validation of the technique by comparison with other commonly used markers for detection of apoptosis. The induction of apoptosis by dexamethasone treatment in DO11.10-EGFP cells is used as an example to illustrate the method. Other cell types and other apoptosis-inducing agents can be used as well (see Note 4). 3.2.1. Induction of Apoptosis 1. Thaw fresh DO11.10-EGFP cells and maintain them in RPMI-1640 cell culture medium supplemented with 5% FCS. Because the susceptibility to apoptosis induction increases with the time in culture, use only freshly thawed cells (less than 10 passages). In addition, we recommend using exponentially growing cells (less than 1 × 106 cells/mL). Make sure that the percentage of EGFP+ cells is near 100% (among viable cells) by flow cytometry analysis before starting an experiment. 2. Plate DO11.10-EGFP cells at a concentration of 4 × 105 cells/mL in the wells of a flat-bottomed 96-well plate (8 × 104 cells/well in 200 µL of RPMI-1640 5% FCS). Prepare triplicate wells for untreated and for treated cells. 3. Using a stock solution of dexamethasone at 10–3 M (diluted in ethanol), prepare intermediate dilutions and add dexamethasone to the wells to reach a final concentration of 10–7 M. The final concentration of ethanol in the culture medium should not exceed 1% (v/v). Add an equivalent concentration of ethanol to untreated control cells. 4. Incubate at 37°C, 5% CO2 for 16 h. 5. Harvest and transfer the cells into a conical 96-well plate, centrifuge at 85g for 3 min, and remove the supernatant. 6. Wash the cells twice with 200 µL of PBS. 7. Resuspend the cells in 400 µL of PBS and transfer into microtiter tubes for direct flow cytometry analysis. No additional procedure is required for EGFP detection by flow cytometry. The cells can be kept on ice for up to 2 h before analysis.

3.2.2. Measurement of Apoptosis Induction Through Monitoring of Decrease in EGFP Fluorescence by Flow Cytometry 1. Using noninfected, parental DO11.10 cells, set the parameters of the flow cytometer. First, adjust the forward side (FS) and side scatter (SS) parameters in order to be able to see both viable (high FS, low SS) and dead (low FS, high SS) cells on an FS/SS dot plot (see Fig. 1B, top panel). Second, set the FL-1 voltage such that EGFP– (noninfected cells) appear in the first log decade on an FL-1 histogram.

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Fig. 1. Dead cells exhibit decreased EGFP fluorescence. (A) DO11.10-EGFP cells were treated with dexamethasone (10–7 M for 16 h). EGFP fluorescence was detected by flow cytometry in treated (dashed line) or untreated (solid line) cells. (B) DO11.10-EGFP cells were treated as in (A). Electronic gating was performed to evaluate EGFP fluorescence in either viable (R1 region) or dead (R2 region) cells, as determined by a reduction in forward scatter. Data are representative of at least five independent experiments.


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Using untreated DO11.10-EGFP cells, make sure that at least one log difference in fluorescence intensity is detected between EGFP-expressing and EGFP– cells. 2. For determination of the percentage of apoptotic cells in dexamethasone-treated DO11.10-EGFP cells, draw a region (R1) on the FS/SS dot plot that includes both viable (high FS, low SS) and dead (low FS, high SS) cells, excluding cell debris that may appear on the lower left corner of the FS/SS dot plot. Two well-discriminated peaks should be visible on the FL-1 histogram that is gated on R1; the FL-1-negative peak (EGFP-low) represents dead cells and the FL-1-positive peak (EGFP-high) represents viable cells. The percentage of apoptotic cells can then be obtained by drawing a region for the negative peak.

An example of apoptosis induction in DO11.10-EGFP cells by dexamethasone is presented below. In DO11.10-EGFP cells, induction of apoptosis with dexamethasone causes a dramatic decrease in EGFP fluorescence readily detectable by flow cytometry (Fig. 1A, dashed line). DO11.10-EGFP cells displayed the same sensitivity to apoptosis induction as parental DO11.10 cells (data not shown). The small proportion of EGFP– cells that can be seen in nontreated cells (Fig. 1A, solid line) is owing to background cell death in the culture (4 logs. The linearity and dynamic range were preserved during repeated scanning up to five times with a correlation coefficient of r 2 >0.999. Detection of single viable cells by DIMSCAN was achieved in 93% of wells seeded without any false-positive wells (22). The wide linear range offered by DIMSCAN allows the user to more accurately measure concentrations of drugs lethal for 90 or 99% of treated cells (i.e., LC90 or LC99 values, also expressed as 1 log or 2 logs of cell kill), as opposed to more commonly used LC50 values. Obtaining at least a 2 log cytotoxicity is accepted as the amount of cell kill necessary to achieve a partial response (23). This points toward the importance of using LC99 values at a clinically achievable level as criteria for defining a potentially active agent based on in vitro data. Equally important, the 4 log dynamic range renders DIMSCAN an invaluable tool for determining synergistic, additive, and antagonistic effects for tested drug combinations. Such assessments are limited in systems with a dynamic range of 1 to 2 logs.

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DIMSCAN can be used as a cytostatic assay if lower numbers of cells are seeded and the growth inhibitory effect of a tested agent is measured 14– 21 d after initiating the experiment (vs 3–7 d as a cytotoxicity assay). As a cytostatic assay, DIMSCAN was used to develop 13-cis-retinoic acid for neuroblastoma, which led to successful phase I and phase III clinical trials of that drug (24). Results from DIMSCAN cytotoxicity testing have been used to identify promising new agents for neuroblastoma that have shown responses in clinical trials—buthionine sulfoximine (BSO) + melphalan (25,26) and low-dose (oral) fenretinide ([27]; unpublished data)—and also to develop additional agents currently in or about to enter phase I trials [prolonged infusion of pyrazoloacridine (28), or high-dose (iv) fenretinide (27), and fenretinide + safingol (21)]. 2. Materials 1. FDA (Sigma, St. Louis, MO). Prepare a 1 mg/mL solution in dimethyl sulfoxide, aliquot into 1.5-mL Eppendorf tubes, and store at –20°C in the dark. Avoid repeated thawing and refreezing. 2. Hoechst 33342 (Calbiochem, San Diego, CA). Dissolve in double-distilled water to make a 1 mg/mL stock solution, and store in 1.5-mL Eppendorf tubes in the dark at 4°C. 3. Eosin Y. Prepare a 1% stock solution (w/v) in 0.9% NaCl and store in an amber bottle at room temperature. 4. Precision 2000 robot pipettor (Bio-Tek). 5. DIMSCAN system (Fig. 1; www.DIMSCAN.com). This consists of an inverted microscope; a stepper motor scanning stage; a stage controller; a charge-coupled device [CCD] camera; and a Pentium 4 microcomputer (Microsoft Windows 2000) running the main application software (DIMSCAN 3.0, developed at Childrens Hospital Los Angeles), which controls stage movement and processes CCD camera images ([15,22]; unpublished). An inverted microscope, Olympus IX50, is equipped with a 103-W mercury vapor lamp (HBO®-103 W/2), optical filters (Omega Optical [Woburn, MA] XF22 filter set for FDA or BCECF [excitation: 490 nm; emission: 525 nm] and an Omega Optical XF05 filter set for Hoechst 33342 [excitation: 345 nm; emission: 475 nm]), and a ×4, N.A. = 0.16 objective lens. It is also equipped with a motorized Prior Pro Scan stage with two stepper motors for stage movements in the horizontal plane (x and y) and one stepper motor for focusing (z-axis). The stage controller communicates with the computer through a serial port. A Qimaging Microimager II CCD camera is attached to the standard trinocular head with an 80/20 beam splitter. Maximum resolution of the camera CCD chip is 1024/768 pixels, and the camera has internal cooling, enabling long-term use without degrading image quality. The camera is connected to the PC through IEEE1394 FireWire interface, which enables a high rate of data transfer from the camera to the computer memory. 6. DIMSCAN 3.0 software (Fig. 2). This is a user-friendly interface for all the tasks: plate definition, scan control, camera settings, autofocus, well-image reconstruc-

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Fig. 1. DIMSCAN system: (A) A computer equipped with IEEE1394 FireWire PCI card running DIMSCAN application; (B) Olympus IX50, inverted microscope, equipped with mercury lamp, optical filters, and high N.A. ×4 objective lens; (C) Qimaging Microimager II CCD camera; (D) motorized stage Prior Pro Scan; (E) stage controller, which communicates with computer through serial port; (F) focus drive. tion. It automatically controls stage motion, quantifies fluorescence for individual wells, performs image processing to reduce background fluorescence (digital thresholding) (15), and stores images of scanned wells for repeated scan or elimination from final analysis of selected wells ([15,22]; unpublished). 7. Data analysis software. Following incubation with drugs and scanning of microwell plates by DIMSCAN, the DataAnalyzer software (developed at Childrens Hospital Los Angeles) calculates fractions of affected cells (Fa) (Fa = 1 – RFdrug / RF control), survival fractions (calculated as RFdrug / RF control), standard deviations (SDs), confidence levels, and standard errors (SEs) using the relative fluorescence (RF) values obtained during the DIMSCAN. Fractions of affected cells, survival fractions, and SDs can be calculated using Microsoft Excel. This program can also be used for creating dose-response graphs. Analyzed data can be copied to SigmaPlot (Jandell, San Rafael, CA). to create publication-quality dose-response graphs. 8. Dose-effect analysis with microcomputers software. This program utilizes doseeffect data to compute the median-effect dose (i.e., the lethality [LC50], effect [ED50], inhibition [IC50]), whether the dose-effect relationships conform to the mass-action principle (i.e., r value); the dose that is required to produce a given effect (lethal drug concentration for 50% [LC50], 90% [LC90], or 99% [LC99], and so on of treated cells), and the effect that can be produced by a given dose. The

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Fig. 2. Layout of DIMSCAN software window at the end of scan. The main window displays the menu bar and three panels: plate control panel (shown on the left side of the window), live camera panel (not shown), and thumbnail panel (shown on the right of the window), displaying an image of a representative well of a 96-well microplate with viable cells. Cells are stained with FDA, and background fluorescence is quenched with digital thresholding and eosin Y. Dead cells are not detectable. The plate control panel displays a picture of the whole plate, miniatures of images of already scanned wells. It enables the user to select the wells for scan, and it also contains a virtual joystick, which allows the user to control the stage movement, a necessary practice prior to scanning a plate to check uniformity of thresholding throughout the well. Also shown are output data—the sum of pixel intensities per well. The live camera panel allows the user to control the camera output (gain, exposure time, threshold). These parameters must be set prior to the scan and should not be changed during the scan. The thumbnail panel displays reconstructed images of individual wells for the user’s revision at the end of the scan. Unsatisfactory images can be rescanned or deleted from further analysis. program also computes a combination index (CI), which determines synergism, summation, or antagonism at different dose levels (29).

3. Method 1. Harvest cells that are 75–80% confluent and seed the cells in complete medium into 96-well plates. Cell number is determined by tumor type; for example, solid


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tumor cell lines should be seeded at lower cell concentrations (1000–15,000) than leukemia (up to 50,000) owing to the appreciable difference in cell size, or the doubling time of a given cell line (slower-growing cells are plated at higher numbers than fast-growing lines), and the length of an experiment (experimental design for a cytotoxicity assay may vary from 3 to 7 d). If one desires to assess the cytostatic effect of a drug, then longer-term (14–21 d) assays should be employed and fewer cells should be seeded. If inappropriately high cell concentrations are used, the control wells will “overgrow” and cause erratic results. However, using the highest number of cells that will not cause overgrowth of controls is advisable to provide the largest dynamic range. To calculate the 96-well plate format for the single-drug cytotoxicity assay (see Note 1), first determine the total amount of cells per plate (e.g., n cells/ well × 80 wells/plate). Then determine the amount of complete medium with which to seed the cells (e.g., 150 µL/well × 80 wells/plate = 12 mL/ plate). Often, only 60 wells are utilized, and the wells on the edges are filled with water because evaporation of medium can result in a change in drug concentrations in the outer wells. To avoid a shortage of cell/medium or drug/medium suspensions, make calculations for 10% more wells than the expected use. Use a multichannel pipettor or Precision 2000 robot pipettor for seeding cells or drugging the plates. After overnight incubation, for a single-drug experiment, add four different drug concentrations in complete medium to each well (see Note 2). At least three drug concentrations must be tested to be able to calculate lethal drug concentrations. Each drug concentration is added to two consecutive columns of wells comprising 12 replicates. Drug concentrations are chosen to cover the established clinically achievable levels. This range includes the lowest drug levels up to a clinically unachievable high drug concentration to demonstrate possible drug activity. The maximum volume used is 250 µL/well (150 µL/well was deposited when seeding the cells; an additional 100 µL/well is used for delivering drug[s]), or 4 mL/condition (250 µL/well × 16 wells/plate). Therefore, dissolve drug in 100 µL/well × 16 wells/plate = 1.6 mL/condition/plate. Use vehicle solution in controls. Pipet drugs into the columns in increasing drug concentrations. Discard leftover drug/medium suspension from the reservoir in between drug conditions to avoid dilution of desired drug concentrations. For drug combination assays, set up separate plates for Drug A, Drug B, and Drug A + Drug B (see Note 3). In the latter case, the first two columns will carry cells treated with vehicle solution; the next two columns will carry Drug Acondition1 + Drug Bcondition1, then Drug Acondition2 + Drug Bcondition2, Drug Acondition4 + Drug Bcondition4. It is preferable to set Drug A and Drug B in such a fashion that the ratio between them is maintained throughout all the concentrations (e.g. drug concentrations of Drug A = 0, 3, 6, 9, and 12 µM, and drug concentrations of Drug B = 0, 1, 2, 3, and 4 µM gives a ratio of 31). For drug resistance modulation experiments, determine a dose-response curve for one drug against one fixed dose of a modulator that can be obtained clinically

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10. 11. 12. 13.

Keshelava et al. (e.g., 500 µM BSO + increasing melphalan concentrations, or 2 µg/mL of the cyclosporin analog SDZ PSC 833 + increasing etoposide concentrations.). Incubate plates for 3–7 d, depending on the type of cells and the total time of drug exposures desired. For drugs with a very short t1/2, in vitro incubation times days longer than the t1/2, may be needed to allow for maximal cell death to occur. Prior to DIMSCAN analysis (20–30 min), turn on the mercury bulb of the DIMSCAN system and allow it to warm up and stabilize, turn on the stage controller with CCD camera, and then run the DIMSCAN application software. After incubation of cells with tested drugs, add to each well 0.5% eosin Y and FDA (the final FDA concentration should be 10 µg/mL) using a multichannel pipettor (see Notes 4 and 5). Incubate the plate for an additional 20 min (see Note 6) in the dark at room temperature and analyze total fluorescence measured by the DIMSCAN assay. One can stain three to four plates at once with FDA and eosin Y. Eosin Y considerably reduces background fluorescence (especially in dead cells). However, fluorescence still remains in the medium and is easily controlled by digital thresholding. For cytostatic experiments one may find it preferable to use Hoechst 33342, a supravital DNA stain, instead of FDA (see Note 7). Before scanning or “reading” the plate, define the type of plate (e.g., 96-well, 384-well) from the menu bar by choosing File, Basic default, New plate, and then 96-well plate. Scanning options are Overscan (covering 100% of well and scanning nine frames), Optiscan I (covering 89% of well and scanning four frames), Optiscan II (covering 98% of well and scanning six frames), and Underscan (covering 42% of well and scanning two frames). The Autofocus feature is implemented for automation of the reading (see Note 8). Choose a well by double-clicking on the plate map from the Plate control panel for thresholding. Digital thresholding is provided on the Live camera panel. Using the arrows from the Stage movement (virtual joystick), make sure that background fluorescence is eliminated. Check other representative wells for background fluorescence. Highlight the wells to be scanned. Choose Scan from the Plate control panel. In addition, this panel provides options such as Abort, Pause/Continue (to pause, terminate, or continue the scan), Bad well, Rescan, and Go to well. At the end of the scan, go to the Thumbnail panel, and by navigating through the Plate Control panel, inspect well by well the reconstructed thumbnail images. Wells with unsatisfactory images can be rescanned, or labeled as “bad well.” “Bad wells” are not used in further data processing. Store fluorescence values of a cytotoxicity/cytostatic assay as a .txt file using the DIMSCAN software. If multiple plates are scanned, select Another plate from the File. Making this selection will avoid the plate definition process. At the end of the DIMSCAN session, exit the DIMSCAN software and then turn off the mercury bulb, the stage controller, and the CCD camera. Once a week conduct stage alignment of the DIMSCAN as follows: From the menu bar select File, Basic default, New plate, and then 96-well plate. Doubleclick on A1 well. Place on the stage a 96-well plate modified for stage alignment


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(it has a very fine cross in the center of the A1 well). Turn on an incandescent light. Choose Start from the Plate control panel. One should see a fine cross in the middle of Live camera panel. From Tools choose Reset stage center wizard. The following message will appear:

This is stage center reset wizard. If stage lost its position (wells are not centerd) it is necessary to reset stage center. To do it use following steps: 1. Turn on the microscope incandescent light 2. Put the calibration plate onto the scope 3. Adjust light to get reasonable image of the plate 4. Press Next. Cancel

Next >>

Press Next. Then follow the instructions of the next message: 1. Move the stage using joystick (or virtual joystick) to the left upper well of the calibration plate. 2. Match the cross-hair of the camera image with the cross-hair image on the well. 3. Press Finish to reset the stage center. Cancel

Finish

Then the last message will appear:

Stage center reset—Command successful OK

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14. Use the DataAnalyzer software to analyze fluorescence values obtained by the DIMSCAN system. The software opens DIMSCAN files containing RF values and the user maps of the treatment groups. The software will first calculate average fluorescence values per condition and apply these to compute affected fractions, surviving fractions, SDs, SEs, and 95% confidence intervals. Alternatively, Microsoft Excel can be used to make these calculations. 15. Copy the surviving fractions ± SD to SigmaPlot 2000 or Microsoft Excel. Doseresponse curves are then created. The drug cytotoxic/cytostatic effect is plotted on a log scale (y-axis) against increasing drug concentrations on a linear scale (x-axis). 16. Determine the LC50, LC90, or LC99 values (drug concentration lethal for 50, 90, and 99% of treated cells, respectively) using the software Dose-Effect Analysis with Microcomputers. This is achieved by entering the drug dose and a corresponding Fa into the software. The program computes these lethal drug concentrations along with r value (mass-action relationship). The r value should be close to 1, and if low values are obtained, then one should consider repeating an experiment. Calculate CI values to establish synergistic, additive, or antagonistic interaction between drugs for studies of drug combinations. The CI values can be calculated by choosing the Multiple drug-effect analysis. Enter the drug dose and corresponding Fa value for both of the drugs separately and then in combination. The software will compute various lethal drug concentrations for both single agents and drug combinations, and CI values. When CI = 1, summation effect is assumed; when CI < 1, synergism is assumed; when CI > 1, antagonism is assumed. The CI value at any effect level can be calculated (see Fig. 3 and Table 2).

4. Notes 1. Similar calculations are used when setting up multiweek cytotostatic experiments. However, once a week washout and exchange of medium is necessary to avoid medium exhaust effect. 2. It is preferable to seed cells uniformly and then drug the plates, rather than prepare cell suspensions with individual drug concentrations and then plate, because it will introduce less plating error, and it allows cells to adapt (and attach for some cell lines) prior to drug exposure. 3. If Drug B is separately added from Drug A, then Drug A should be added with Drug B to maintain the desired drug concentration. 4. For a 96-well microplate format, if each well contains 250 µL of medium, add 50 µL/well of 0.5% eosin Y (4 mL/plate) and a final FDA concentration of 10 µg/mL (or 240 µL of stock solution/plate). 5. One can add 30–50 µL of 0.5% eosin Y in between the wells to eliminate occasional artificial fluorescence that occurs from the edge of the wells. 6. Do not incubate cells longer than 30–40 min with FDA to diminish toxicity from the dye and artificially high background owing to hydrolysis of FDA to fluorescein in the medium by esterases.


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Fig. 3. Dose-response curves of 4-hydroperoxycyclophosphamide (4-HC) () and etoposide ( ), and combination of 4-HC + etoposide () tested by DIMSCAN. A representative synergistic drug interaction is shown using the multidrug-resistant human neuroblastoma cell line CHLA-171 (28). The cytotoxic effect of 4-HC, an active in vitro metabolite of the alkylating agent cyclophosphamide, in combination with etoposide, a topoisomerase inhibitor, was greater than the summation effect of these drugs alone at all concentrations tested; CI values were 1 indicates antagonism. The precise biological significance of various degrees of synergism or antagonism remains to be defined, but it has been proposed that CI values be interpreted as follows: 3.3

very strong synergism strong synergism synergism moderate to slight synergism nearly additive slight to moderate antagonism antagonism strong to very strong antagonism

Because CI values may change with the fraction affected (Fa) in a nonlinear manner, the CI should optimally be presented for each effective concentration (EC) tested, or an overall CI value presented that is generally reflective of the CI values calculated at the various ECs tested (e.g., EC50, EC90, and EC90 or EC99). 3.2. Conducting Fixed-Ratio Analysis of Drug Interactions A prerequisite for fixed-ratio calculations is the generation of accurate doseresponse curves for the agents tested, both alone and in combination. The accuracy of assessing drug interactions will depend directly on the accuracy of the method used to assess their cytotoxicity or growth inhibition. In testing the antitumor properties of antineoplastic drugs, the effect can be an inhibition of growth or cytotoxicity (most assays measure a combination of both). The

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dynamic range of the assay is important, because effective combinations should achieve an inhibition of growth over time, or direct cytotoxicity, of >2 to 3 logs (the “two-log” rule) for an expectation of clinical response (based on current response definitions and calculated disease burdens in leukemia patients and solid tumor masses) (22). Accuracy of the calculations is also impacted by the number of different points taken along the dose-response curve. To determine potency and shape in a dose-response relationship, three data points are a minimum value, although CI can be calculated using any number of data points. The linear correlation coefficient (r) of the median-effect plot should be reasonably good (r > 0.9 is common for cell culture experiments). To assess synergy, each drug should have some effect as a single agent. Both the potency (Dm) and shape (m) parameters that are derived from dose-response data are required for assessing synergism or antagonism. A CI can be derived for a combination of a noneffective agent and an effective agent, and although these can be referred to in terms of synergism or antagonism, such interactions are more properly termed modulation (potentiation, augmentation, or inhibition) of the active agent by the inactive agent. CI values for each data point of a nonconstant ratio experiment can also be calculated, as long as m and Dm parameters are available for each single drug. An example of such an experiment is the use of one drug at a fixed concentration while varying the concentration of the second drug. However, such an experimental design does not allow calculation of an Fa-CI plot simulation (though the points can still be placed on the Fa-CI plot), nor does it allow plotting of a classic isobologram. The preferred experimental design is to employ each drug alone, and in combination, at a fixed ratio of concentrations (e.g., 21 or 13). Drugs with two different units (micromolar vs micrograms/milliliter) can be analyzed directly in fixed-ratio combinations. One approach to selecting values for the fixed ratio combinations is to combine each drug at its equipotent ratio (i.e., the ratio of the EC50 concentrations), and then to create a combination that is four- to eightfold higher than the EC50, and use serial dilutions of the highest concentration combination to generate the dose-response curve (each single agent in the combination is tested alone in the same manner) (see Note 2). 3.3. Examples of Assessing Drug Interaction Data The first example (Fig. 1) provided is from a published study that assessed the synergistic interaction of fenretinide (a cytotoxic retinoid known to stimulate generation of ceramides in tumor cells in vitro) and safingol (a stereoisomer of sphinganine, a precursor of ceramide) (23). First, the data for Fig. 1 were obtained from the DIMSCAN assay of fixed-ratio exposures to each drug

178 Fig. 1. Effects of L-threo-dihydrosphingosine (safingol) on fenretinide (4-HPR) cytotoxicity in a neuroblastoma and a breast cancer cell line (23). The cytotoxicity dose response of (A) the SK-N-RA neuroblastoma cell line and (B) the DoxR MCF-7 breast cancer cell line to 4-HPR (H), safingol (S), and 4-HPR/safingol (31 ratio) (H+S) using a fluorescence-based assay employing digital imaging microscopy (DIMSCAN) is shown (24). Cell lines were exposed to drug(s) and responses were assayed at 4 d. () 4HPR; () safingol; () 4-HPR/safingol (31 ratio). Synergy was quantified by Combination Index (CIN) analysis and expressed as log10 (CIN) vs fraction affected. By this method, log10 (CIN) < 0 indicates synergy; log10 (CIN) = 0 indicates an additive effect; and log10 (CIN) > 0 indicates antagonism. Ninety-five percent confidence intervals are shown on CIN plots where calculable. Bars indicate 95% confidence intervals. Note that CIN is used as an abbreviation for Combination Index because the journal in which the data were originally published used CI as an abbreviation for confidence interval.


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alone and in combination, and the data were analyzed in CalcuSyn. Second, values from the CI tables were then plotted using SigmaPlot to generate publication-quality graphics demonstrating the synergistic interaction between fenretinide and safingol. The second example is a computer screen showing CalcuSyn after it has generated the median-effect and CI plots that are used to analyze drug interactions for the combination of cyclophosphamide (as the active metabolite 4-hydroperoxycyclophosphamide [4-HC]) and etoposide (Fig. 2). The data, data analysis, and methods of obtaining and analyzing the data associated with Fig. 2 are presented elsewhere in this volume (24) (see Note 3). A number of examples of the use of the CI approach to assess interactions of antineoplastic drugs can be found in the literature (12,23,25–29). 4. Notes 1. Determination of drug interactions for antineoplastic agents is ideally done using an assay with a ≥3 log dynamic range, especially if each individual agent is capable of 1 to 2 logs of cytotoxicity. Some commonly used cytotoxicity assays (such as 3-[4,5-dimethylthiazolyl-2]-2,5-diphenyltetrazolium bromide) cannot achieve >2 logs of dynamic range with many cell types and, thus, should not be employed for assessing synergy and antagonism. We find that the DIMSCAN assay, owing to its 4 log dynamic range, is particularly suitable for drug combination testing (23,25). DIMSCAN and other in vitro cytotoxicity assays are reviewed by Keshelava et al. in Chapter 12 (24). 2. If the actual clinically achievable plasma level for each drug is known or suspected, then the ratio between the drugs should reflect this. The drug concentration ratios should also reflect the lower than maximal drug concentrations likely to be achieved when using the combination owing to the additive systemic toxicities of each agent, and the possible lower drug levels achieved in tumor tissue relative to plasma. Otherwise, in vitro overmodeling may occur, which can diminish the predictive value of the preclinical studies when the drug combination is tested in clinical trials. 3. Details on the use of CalcuSyn are found in the software user’s manual (14).

Acknowledgments We thank Dr. Nino Keshelava and Dr. Rita Grigoryan for the data used to generate Fig. 2. This work was supported in part by the Neil Bogart Memorial Laboratories of the T.J. Martell Foundation for Leukemia, Cancer, and AIDS Research; and by National Cancer Institute grants CA82830 and CA81403.

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References 1. Frei, E. and Antman, K. H. (1997) Combination chemotherapy, dose, and schedule, in Cancer Medicine (Holland, J. F., Bast, R. C., Morton, D. L., Frei, E., Kufe, D. W., and Weichselbaum, R. R., eds.), Williams & Wilkins, Baltimore, pp. 817–837. 2. Kaufman, D. C. and Chabner, B. A. (2001) Clinical strategies for cancer treatment: the role of drugs, in Cancer Chemotherapy & Biotherapy (Chabner, B. A. and Longo, D. L., eds.), Lippincott Williams & Wilkins, Philadelphia, pp. 1–16. 3. Gitler, M. S., Monks, A., and Sausville, E. A. (2003) Preclinical models for defining efficacy of drug combinations: mapping the road to the clinic. Mol. Cancer Ther. 2, 929–932. 4. Tallarida, R. J. (2000) Drug Synergism and Dose-Effect Data Analysis, Chapman & Hall/CRC, New York. 5. Tallarida, R. J. (2001) Drug synergism: its detection and applications. J. Pharmacol. Exp. Ther. 298, 865–872. 6. Teicher, B. A. (2003) Assays for in vitro and in vivo synergy [review]. Methods Mol. Med. 85, 297–321. 7. White, D. B., Slocum, H. K., Brun, Y., Wrzosek, C., and Greco, W. R. (2003) A new nonlinear mixture response surface paradigm for the study of synergism: a three drug example. Curr. Drug Metab. 4, 399–409. 8. Levasseur, L. M., Greco, W. R., Rustum, Y. M., and Slocum, H. K. (1997) Combined action of paclitaxel and cisplatin against wildtype and resistant human ovarian carcinoma cells. Cancer Chemother. Pharmacol. 40, 495–505. 9. Greco, W. R., Bravo, G., and Parsons, J. C. (1995) The search for synergy: a critical review from a response surface perspective [review]. Pharmacol. Rev. 47, 331–385. 10. Chou, T. C. (1996) The median-effect principle and the combination index for quantitation of synergism and antagonism, in Synergism and Antagonism in Chemotherapy (Chou, T. C. and Rideout, D. C., eds.), Academic, San Diego, pp. 61–102. 11. Chou, T. C., Rideout, D., Chou, J., and Bertino, J. R. (1991) Chemotherapeutic synergism, potentiation, and antagonism, in Encyclopedia of Human Biology (Dulbecco, R., ed.), Academic, San Diego, pp. 371–379. 12. Chou, T. C., Motzer, R. J., Tong, Y., and Bosl, G. J. (1994) Computerized quantitation of synergism and antagonism of taxol, topotecan, and cisplatin against human teratocarcinoma cell growth: a rational approach to clinical protocol design [see comments]. J. Natl. Cancer Inst. 86, 1517–1524.

Fig. 2. (see opposite page) Screen captured from a computer analyzing data from a fixed-ratio analysis of the combination of 4-HC + etoposide using a human neuroblastoma cell line. Dose-response curves and data tables from the same experiment as shown in Fig. 2 can be found elsewhere in this volume (24). Shown are windows containing the dose-effect curves (upper left), the Fa-CI plot (upper right), the medianeffect plot (lower left), and a small portion of CI tables (lower right).

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13. Chou, T. C. (1998) Drug combinations: from laboratory to practice. J. Lab. Clin. Med. 132, 6–8. 14. Chou, T. C. and Hayball, M. P. (1996) CalcuSyn Windows Software for Dose Effect Analysis, Biosoft, Cambridge, MA. 15. Houghton, P. J., Stewart, C. F., Cheshire, P. J., et al. (2000) Antitumor activity of temozolomide combined with irinotecan is partly independent of O6-methylguanineDNA methyltransferase and mismatch repair phenotypes in xenograft models. Clin. Cancer Res. 6, 4110–4118. 16. Meco, D., Colombo, T., Ubezio, P., et al. (2003) Effective combination of ET-743 and doxorubicin in sarcoma: preclinical studies. Cancer Chemother. Pharmacol. 52, 131–138. 17. Thompson, J., George, E. O., Poquette, C. A., et al. (1999) Synergy of topotecan in combination with vincristine for treatment of pediatric solid tumor xenografts. Clin. Cancer Res. 5, 3617–3631. 18. Coggins, C. A., Elion, G. B., Houghton, P. J., et al. (1998) Enhancement of irinotecan (CPT-11) activity against central nervous system tumor xenografts by alkylating agents. Cancer Chemother. Pharmacol. 41, 485–490. 19. Tan, M., Fang, H. B., Tian, G. L., and Houghton, P. J. (2003) Experimental design and sample size determination for testing synergism in drug combination studies based on uniform measures. Stat. Med. 22, 2091–2100. 20. Chou, T.-C., Rideout, D., Chou, J., and Bertino, J. R. (1974) Relationships between inhibition constants and fractional inhibitions in enzyme-catalyzed reactions with different numbers of reactants, different reaction mechanisms, and different types of mechanisms of inhibition. Mol. Pharmacol. 10, 235–247. 21. Chou, T.-C. and Talalay, P. (1984) Quantitative analysis of dose-effect relationships: the combined effects of multiple drugs or enzyme inhibitors. Adv. Enyzme Regul. 22, 27–55. 22. Harrison, S. (2002) Perspective on the history of tumor models, in Anticancer Drug Development Guide (Teicher, B. A., ed.), Humana, Totowa, NJ, pp. 3–19. 23. Maurer, B. J., Melton, L., Billups, C., Cabot, M. C., and Reynolds, C. P. (2000) Synergistic cytotoxicity in solid tumor cell lines between N-(4-hydroxyphenyl)retinamide and modulators of ceramide metabolism. J. Natl. Cancer Inst. 92, 1897–1909. 24. Keshelava, N., Frgala, T., Krejsa, J, Kalous, O, and Reynolds, C. P. (2005) DIMSCAN: a microcomputer fluorescence-based cytotoxicity assay suitable for pre-clinical testing of combination chemotherapy, in Chemosensitivity (Blumenthal, R. D., ed.), Humana Press, Totowa, NJ, 2005, vol. 1, chap. 12. 25. Anderson, C. P. and Reynolds, C. P. (2002) Synergistic cytotoxicity of buthionine sulfoximine (BSO) and intensive melphalan (L-PAM) for neuroblastoma cell lines established at relapse after myeloablative therapy. Bone Marrow Transplant. 30, 135–140. 26. Xu, J. M., Azzariti, A., Colucci, G., and Paradiso, A. (2003) The effect of gefitinib (Iressa, ZD1839) in combination with oxaliplatin is schedule-dependent in colon cancer cell lines. Cancer Chemother. Pharmacol. 52, 442–448.


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27. Ricotti, L., Tesei, A., De Paola, F., et al. (2003) In vitro schedule-dependent interaction between docetaxel and gemcitabine in human gastric cancer cell lines. Clin. Cancer Res. 9, 900–905. 28. Takahashi, N., Li, W., Banerjee, D., et al. (2002) Sequence-dependent synergistic cytotoxicity of ecteinascidin-743 and paclitaxel in human breast cancer cell lines in vitro and in vivo. Cancer Res. 62, 6909–6915. 29. Topaly, J., Zeller, W. J., and Fruehauf, S. (2001) Synergistic activity of the new ABL-specific tyrosine kinase inhibitor STI571 and chemotherapeutic drugs on BCR-ABL-positive chronic myelogenous leukemia cells. Leukemia 15, 342–347.

15 Image Analysis Using the Fluorochromasia Assay to Quantify Tumor Drug Sensitivity John F. Gibbs, Youcef M. Rustum, and Harry K. Slocum Summary A method of assessing chemosensitivity of tissue utilizing tissue fluorescence and image analysis was implemented to provide a rapid and quantitative means of assessing the effect of drugs on tissue metabolic activity and proliferative capacity. The fluorescent microscopic image captured by a silicon-intensified target (low-light-detecting) camera and linked to an imageprocessing unit was measured for fluorescent brightness and tumor image area. An established rodent model served to characterize the system’s ability to measure serially the tumor’s metabolic activity and growth. Further studies on fresh human tumors were conducted with a novel topoisomerase II inhibitor, NC-190. Tumor image area and fluorescent brightness were measured 24 h pretreatment, 48 h posttreatment, and 48 h post–drug removal. Fifty-five percent (28/51) of fresh human tumors showed sensitivity to 48-h exposure to 10, 30, or 100 µM NC-190. The potential benefit of this technique is the ability to predict the response of tumors to chemotherapeutic agents as a laboratory tool for preclinical drug evaluation and clinically prior to the commencement of therapy.

Key Words Chemosensitivity; image analysis; fluorescein; fluorochromasia assay; NC-190; topoisomerase II inhibitor.

1. Introduction An analytical image analysis system to assess drug responsiveness of solid organ tumors was implemented to evaluate the activity of chemotherapeutic agents utilizing the fluorochromasia assay. Fluorochromasia is the production of a fluorescent molecule within a cell owing to metabolism of a nonfluorescent precursor substrate. This provides the basis for a noninvasive assessment of metabolic activity within a cell or tissue. The precursor substrate that we used is fluorescein diacetate (FDA) (nonpolar), which diffuses across viable cellular From: Methods in Molecular Medicine, vol. 110: Chemosensitivity: Vol. 1: In Vitro Assays Edited by: R. D. Blumenthal © Humana Press Inc., Totowa, NJ

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Fig. 1. Fluorochromasia is a nondestructive process of intracellular accumulation of fluorescein. FDA (nonpolar) diffuses across viable cellular membrane and is cleaved by esterase(s) into the fluorescein ion (polar). The process is rapid at a concentration of 0.06 µM for 10 min. Fluorescein diffuses out of the cell very slowly.

membrane and is cleaved by esterase(s) into the fluorescein ion (polar) (Fig. 1). The process is rapid, and fluorescein ion is produced intracellularly (1–4). The fluorescein emits green light under blue light illumination. Quantitative analysis within the assay would improve its general usefulness. A program was developed to detect changes in fluorescent brightness and tumor area as an index of drug responsiveness with computer-assisted imaging. The physicochemical components of the system were validated initially with a fluorescent standard. Our fluorochromasia assay system deviated from that of the original description by Rotman in the use of single instead of multiple tumor fragments. Individual tumor fragments allow for more precise analysis. We initially evaluated the biological growth pattern and drug responsiveness characteristics with a known fluoropyrimidine-sensitive rodent model, which had been well characterized in our laboratory (5). We then evaluated the activity of novel drugs on fresh human tumor specimens. NC-190 is a novel benzophenazine topoisomerase II inhibitor that was selected as the most active analog of the original compound NC-021 against the P388 murine leukemia cell line (6,7). The effect of NC-190 on fresh human tissue is reported to illustrate the effectiveness of the computer-assisted fluorochromasia assay. 2. Materials 1. RPMI-1640 medium, 10% fetal bovine serum, Dulbecco’s solution, penicillin– streptomycin, and gentamicin (Gibco, Grand Island, NY). 2. FDA (mol wt = 416.39) (Aldrich, Milwaukee, WI) and sodium fluorescein (mol wt = 376.28) (Alcon, Fort Worth, TX). 3. Purified collagen (Vitrogen 100; 3 mg/mL) (Celtrix, Santa Clara, CA). 4. 5-Fluorouracil (5-FU) (mol wt = 130.1) (Sigma, St. Louis, MO).

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5. Non-heat-treated tea bag paper (cellulose matrix) (C.H. Dexter, Windsor Locks, CT). 6. Twenty-mesh stainless-steel screen (Small Parts, Miami, FL). 7. Falcon 12-well plates. 8. Qualitative Whatman no. 1 filter paper. 9. Evan’s antistatic spray (Evan’s Specialty, Richmond, VA). 10. NC-190 (mol wt = 456.4). This was kindly supplied by Taisho. Drug solubility and stability under culture conditions was determined by ultraviolet spectroscopy using freshly diluted stock (5 mM) at pH 10.2 into pH 7.4 aqueous buffer before and after 2 h incubation at 37°C. In vitro drug concentrations up to 100 µM could be utilized without fear of precipitation or chemical breakdown owing to the physiological pH and temperature conditions employed.

3. Methods 3.1. Fluorescent Standard A fluorescent standard is utilized to test the physical and chemical stability of the system and to define its proper settings (see Note 1). 1. Place Whatman filter paper strips (2 × 2 mm) saturated with 1.5 µL of linear dilutions of stock fluorescein solution on metal grids in Falcon multiwell plates. 2. Precondition plates with antistatic spray to avoid electrostatic effect on the fluorescent paper strips. This is only necessary for the fluorescent standards, not for the papers bearing biological samples. The fluorescent standard is stable to diminution in intensity from photobleaching over time. 3. Measure the integrated optical brightness and image area (8). The system is standardized for its ability to quantitate fluorescence and the area of the fluorescent object.

3.2. Fluorescent Analytical Measurements An image analysis system previously described was modified for this assay (9). 1. Obtain a fluorescent image under an Olympus Highlight 2000 light source filtered to maximize blue light intensity, and view through a yellow barrier filter at ×10 magnification with an Olympus stereomicroscope model SZH. 2. Connect the microscope to a Hamamatsu C2400 silicon-intensified target (SIT) low-light-detecting camera at settings gain 0, offset 0, sensitivity minimal, and shading off (Fig. 2). 3. Capture 32 frames (l frame = 1/32nd s) using an Argus 10 image processor (Hamamatsu). 4. Maintain the background intensity threshold at 4–11 for the fluorescent standard and 5–12 for biological tissue to enhance the border-vs-background delineation (see Note 2).

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Fig. 2. Image capture of fluorescent object by blue light source connected via fiberoptics to microscope. The magnified image is transferred to an image processor by an SIT camera. After accumulation of the image and modification of the background, the image is transferred to a Quantimet Q970, where the binary area and integrated optical brightness are recorded. Data files are transferred to a PC/IBM computer for analysis. 5. Transfer the integrated image to a Cambridge Quantimet Q970 (Leica, Deerfield, IL) for programmed analytical measurements, which are recorded and stored on removable disks (Iomega). 6. Transfer the data from the Cambridge Quantimet Q970 to a PC/IBM, format through an Excel 4.0 file, and import into Sigmaplot 5.0 for graphic display. A program is created to measure binary image area and to detect changes in fluorescent brightness. Figure 3 shows the pattern of recognition by the system. The image is detected by the system as a series of measuring units termed pixels. A background threshold is set, and each pixel’s fluorescent brightness is recorded, on a scale of 256 levels of gray, and the sum of the brightness of all pixels in the image area is calculated. This provides data on total integrated brightness (of all pixels), and brightness per unit area, as the pixels per unit area is measured using a sizing standard. Figure 4 shows the expected linear relationship between total brightness and fluorescein concentration.

3.3. Fresh Rodent Specimens The 1,2-dimethlylhydrazine-induced mucinous colon and jejunal adenocarcinoma described by Ward et al. (9) was passed by sc trocar technique into Fischer rats. This model was selected for this study because of its fluoropyri-

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Fig. 3. Computerized interpretation of fluorescent image. The letter A characterizes the image capture. The area is measured by summating small processing units termed pixels. The pixel is calibrated a priori to a known size. Each pixel additionally has an associated fluorescent brightness unit. If a detector threshold is set to interpret pixel brightness greater than a set value, the corresponding image is obtained.

midine sensitivity (11–14). The transplanted tumor has a doubling time of approx 4 d in the rodent after a latent period. Fresh samples of cells were taken from a freezer for implantation every 3 to 4 mo so that the tumors did not undergo more than 10 serial passages in rats. Therapeutic manipulation of the Ward rat tumor proceeded according to the following scheme: 1. 2. 3. 4.

Measurement 24 h pretreatment measurement on explant d 7. Drug treatment on explant d 8. Evaluation for direct drug effect 48 h following drug removal on d 10. Evaluation for tissue recovery 48 h post–drug treatment on d 12 (see Note 3).

Using these time points, the effect of 5-FU on the Ward rat tumor was ascertained using the imaging system. Figure 5 demonstrates the system’s ability to detect dose responsiveness in the rodent model. At the highest clinically achievable dose of 5-FU (500 µM), there was a 39% decrease in area compared with the nontreated group, 113% when compared with pretreatment measurements immediately after drug treatment. There was an intermediate effect using 50 µM 5-FU (84.5%). Dose responsiveness was not demonstrated between 50 and 150 µM 5-FU. When evaluated for recovery 48 h following drug removal, dose responsiveness was sustained; the tumor fragments did not recover from the drug effect.

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Fig. 4. Changes in total brightness of the fluorescent image while measuring a constant area are detected by the image analysis system. The fluorescent standard reveals a linear decrease in total brightness at a concentration between 24 and 37 µM fluorescein. The total brightness units are arbitrarily set for the integrated optical brightness above the preset threshold for a given pixel area.

3.4. Fresh Human Surgical Specimens The effect of NC-190 on fresh human surgical tissues was evaluated. NC-190 had shown promising activity among a variety of cell lines in our laboratory. There was a wide range of IC50 values among the cell lines evaluated even within a given tumor type, suggesting intertumor heterogeneity. Fresh solid tumor specimens are sent to the laboratory on ice and mechanically disaggregated. 1. Slice the tumors into 0.5-mm slices with a Stadie-Riggs microtome and then crosscut with scalpel blades. Prefabricate 24-well tissue culture plates (Falcon) containing sterilized collagen-impregnated cellulose papers on metallic grids and store at 4°C for later use. 2. Following mechanical disaggregation, embed small tissue fragments in the collagen-impregnated cellulose mattress on top of the metallic grids. 3. Fill the wells to an air-fluid interface with culture medium, and return the plates to a 95% air/5% CO2 incubator at 37°C. 4. One day after implantation, incubate the samples in the presence of FDA (15 µM) for 30 min. 5. Assess fluorescent brightness and image area under blue light.

Fig. 5. Effect of 5-FU drug treatment on (A) tumor surface area and (B) total brightness of rodent colon adenocarcinoma. The drug treatment conditions were performed in triplicate with an SD

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