Title Details

Dimitri Semizarov, PhD, is a Senior Group Leader in the Cancer Research Department of Abbott Laboratories' Global Pharmaceutical R&D. Dr. Semizarov leads cancer genomics research at Abbott, applying genomics technologies to enable personalization of cancer therapy. He is author or coauthor of more than twenty scientific articles and eight patent applications, as well as three book chapters (including two chapters in Wiley's Preclinical Development Handbook).

Eric Blomme, DVM, PhD, Diplomate, American College of Veterinary Pathologists, is a Senior Project Leader for Cellular, Molecular, and Exploratory Toxicology in Global Pharmaceutical R&D at Abbott Laboratories. He has extensive drug discovery, toxicology, and screening experience working for Abbott, Pharmacia, Monsanto, Searle, Ohio State University, and Cornell University. Dr. Blomme has written over fifty journal articles and eight book chapters, and is a reviewer for multiple scientific journals in the fields of toxicology and pathology.

Preface xiii

1. Introduction: Genomics and Personalized Medicine 1
Dimitri Semizarov

1.1. Fundamentals of Genomics 1

1.2. The Concept of Personalized Medicine 5

1.3. Genomics Technologies in Drug Discovery 8

1.4. Scope of This Book 13

References 20

2. Genomics Technologies as Tools in Drug Discovery 25
Dimitri Semizarov

2.1. Introduction to Genomics Technologies 25

2.2. Gene Expression Microarrays: Technology 27

2.2.1. Standard Microarray Protocol 27

2.2.2. Monitoring the Quality of Input RNA for Microarray Experiments 29

2.2.3. Specialized Microarray Protocols for Archived and Small Samples 31

2.2.4. Quality of Microarray Data and Technical Parameters of Microarrays 33

2.2.5. Reproducibility of Expression Microarrays and Cross-Platform Comparisons 35

2.2.6. Microarray Databases and Annotation of Microarray Data 38

2.2.6.1. Target Identification 39

2.2.6.2. Disease Classification 39

2.2.6.3. Compound Assessment 40

2.3. Gene Expression Microarrays: Data Analysis 47

2.3.1. Identification of Significant Gene Expression Changes 47

2.3.2. Sample Classification and Class Prediction with Expression Microarrays 48

2.3.3. Pathway Analysis with Gene Expression Microarrays 49

2.3.4. Common Problems Affecting the Validity of Microarray Studies 56

2.4. Comparative Genomic Hybridization: Technology 57

2.5. Comparative Genomic Hybridization: Data Analysis 69

2.6. Microarray-Based DNA Methylation Profiling 76

2.7. Microarray-Based MicroRNA Profiling 80

2.8. Technical Issues in Genomics Experiments and Regulatory Submissions of Microarray Data 86

2.8.1. Study of a Drug’s Mechanism of Action by Gene Expression Profiling 87

2.8.2. Early Assessment of Drug Toxicity in Model Systems 88

2.8.3. Biomarker Identification in Discovery and Early Development 89

2.8.4. Patient Stratification in Clinical Trials with Gene Expression Signatures 90

2.8.5. Genotyping of Patients in Clinical Studies to Predict Drug Response 91

2.9. Conclusion 92

References 93

3. Genomic Biomarkers 105
Dimitri Semizarov

3.1. Introduction to Genomic Biomarkers 105

3.2. DNA Biomarkers 109

3.2.1. DNA Copy Number Alterations 110

3.2.1.1. DNA Copy Number Alterations in Cancer 110

3.2.1.2. DNA Copy Number Alterations in Other Diseases 118

3.2.1.3. Identification of DNA Copy Number Biomarkers in Drug Discovery 119

3.2.2. Mutations 123

3.2.2.1. p53 Mutations 124

3.2.2.2. K-ras Mutations 125

3.2.2.3. EGFR Mutations 127

3.2.2.4. Bcr-abl and KIT Mutations 129

3.2.3. Epigenetic Markers 131

3.3. RNA Biomarkers 137

3.3.1. Gene Expression Biomarkers Validated as Diagnostic Tests 138

3.3.2. Other Examples of Gene Expression Biomarkers 142

3.4. Clinical Validation of Genomic Biomarkers 148

References 156

4. Fundamental Principles of Toxicogenomics 167
Eric Blomme

4.1. Introduction 167

4.2. Fundamentals of Toxicogenomics 168

4.2.1. Principle of Toxicogenomics 169

4.2.2. Technical Reproducibility 170

4.2.3. Biological Reproducibility 174

4.2.4. Species Extrapolation 175

4.3. Analysis of Toxicogenomics Data 176

4.3.1. Compound-Induced Gene Expression Changes 177

4.3.2. Visualization Tools 181

4.3.3. Class Prediction 184

4.3.4. Network and Pathway Analysis 188

4.4. Practical and Logistic Aspects of Toxicogenomics 191

4.4.1. Species Considerations 191

4.4.2. Toxicogenomics Studies 194

4.4.2.1. Sample Considerations 194

4.4.2.2. Experimental Design in Toxicogenomics Studies 196

4.5. Toxicogenomics Reference Databases 199

4.5.1. Utility of Reference Databases in Toxicogenomics 199

4.5.2. Design and Development of Toxicogenomics Reference Databases 200

4.5.3. Existing Toxicogenomics Databases 203

4.5.3.1. Chemical Effects in Biological Systems (CEBS) 204

4.5.3.2. ArrayTrack^® 206

4.5.3.3. Gene Expression Omnibus 206

4.5.3.4. ArrayExpress 207

4.5.3.5. DbZach 207

4.5.3.6. ToxExpress^® 208

4.5.3.7. DrugMatrix^® 208

4.6. Conclusion 208

References 209

5. Toxicogenomics: Applications to In Vivo Toxicology 219
Eric Blomme

5.1. The Value of Toxicogenomics in Drug Discovery and Development 219

5.2. Basic Principles of Toxicology in Drug Discovery and Development 221

5.2.1. Preclinical Safety Assessment 221

5.2.1.1. Genetic Toxicology 222

5.2.1.2. Single-Dose Toxicity 223

5.2.1.3. Repeat-Dose Toxicity 223

5.2.1.4. Reproductive Toxicity 224

5.2.1.5. Carcinogenicity 225

5.2.2. Discovery Toxicology 226

5.3. Toxicogenomics in Predictive Toxicology 227

5.3.1. Prediction of Hepatotoxicity 229

5.3.1.1. Hepatotoxicity: an Important Toxicology Problem in Drug Discovery and Development 229

5.3.1.2. Predictive Genomic Models of Hepatotoxicity 230

5.3.1.3. Additional Toxicogenomics Approaches to Predict Hepatotoxicity 233

5.3.2. Prediction of Nephrotoxicity 235

5.3.2.1. Kidney as a Target Organ of Toxicity 235

5.3.2.2. Predictive Genomic Models of Nephrotoxicity 236

5.3.3. Prediction of In Vivo Carcinogenicity 237

5.3.3.1. Value Created by Toxicogenomics in the Assessment of Carcinogenicity 237

5.3.3.2. Predictive Genomic Models of Carcinogenicity 238

5.3.4. Gene Expression-Based Biomarkers in Other Tissues and the Promise of Hemogenomics 242

5.3.5. Integration of Toxicogenomics in Discovery Toxicology 244

5.4. Toxicogenomics in Mechanistic Toxicology 246

5.4.1. Toxicogenomics to Investigate Mechanisms of Hepatoxicity 250

5.4.2. Intestinal Toxicity and Notch Signaling 253

5.4.3. Cardiac Toxicity 256

5.4.4. Testicular Toxicity 260

5.5. Toxicogenomics and Target-Related Toxicity 265

5.5.1. Target Expression in Normal Tissues 266

5.5.2. Target Modulation 267

5.5.2.1. Genetically Modified Animals 268

5.5.2.2. Tool Compounds 268

5.5.2.3. Gene Silencing 269

5.6. Predicting Species-Specific Toxicity 271

5.7. Evaluation of Idiosyncratic Toxicity with Toxicogenomics 273

5.8. Conclusion 277

References 279

6. Toxicogenomics: Applications in In Vitro Systems 293
Eric Blomme

6.1. Introductory Remarks on In Vitro Toxicology 293

6.2. Overview of Current Approaches to In Vitro Toxicology 294

6.3. Toxicogenomics in In Vitro Systems: Technical Considerations 300

6.3.1. Reproducibility 300

6.3.2. Genomic Classifiers 300

6.3.3. Testing Concentrations 301

6.3.4. Throughput and Cost 302

6.4. Proof-of-Concept Studies using Primary Rat Hepatocytes 303

6.5. Use of Gene Expression Profiling to Assess Genotoxicity 306

6.5.1. Toxicogenomics Can Differentiate Genotoxic Carcinogens from Nongenotoxic Carcinogens 307

6.5.2. Toxicogenomics Can Differentiate DNA-Reactive from Non-DNA-Reactive Compounds Positive in In Vitro Mammalian Cell-Based Genotoxicity Assays 307

6.5.3. Toxicogenomics Assays May Be Less Sensitive than the Standard Battery of In Vitro Genetic Toxicity Tests 308

6.6. Application of Gene Expression Profiling for In Vitro Detection of Phospholipidosis 309

6.7. Toxicogenomics in Assessment of Idiosyncratic Hepatotoxicity 312

6.8. Do Peripheral Blood Mononuclear Cells Represent a Useful Alternative In Vitro Model? 314

6.9. Current and Future Use of In Vitro Toxicogenomics 316

6.9.1. Improved Gene Expression Platforms 316

6.9.2. Standardization of Protocols and Experimental Approaches 316

6.9.3. Performance Accuracy 317

6.9.4. Battery of Gene Expression Signatures 317

6.9.5. Clear, Actionable Data Points 318

6.10. Conclusions 319

References 321

7. Germ Line Polymorphisms and Drug Response 329
Dimitri Semizarov

7.1. Introduction to Germ Line Polymorphisms 329

7.2. Polymorphisms and Drug Response in Oncology 332

7.2.1. UGT1A1 Polymorphism and Response to Irinotecan 333

7.2.2. FGFR4 Polymorphism and Response to Chemotherapy 334

7.2.3. Mdr-1 Polymorphism and Response to Paclitaxel 335

7.2.4. DPD Polymorphisms and Response to 5-Fluorouracil 336

7.2.5. TPMT Variants and Response to Thiopurines 337

7.2.6. MTHFR Polymorphisms and Response to Chemotherapy 339

7.2.7. Tandem Repeat Polymorphisms in the TS Gene and Response to Drugs Targeting Thymidylate Synthase 340

7.2.8. Use of Cancer Cell Lines to Identify Predictive SNPs 342

7.3. Polymorphisms and Response to Anticoagulants 343

7.4. Polymorphisms in Neuroscience 345

7.5. Polymorphisms and Drug Response in Immunology 347

7.6. Polymorphisms and Response to Antiviral Agents 353

7.6.1. Anti-HIV Drugs 353

7.6.2. Interferon Therapy in Hepatitis B Treatment 356

7.7. Gene Copy Number Polymorphisms 357

7.8. Conclusion: Approaches to Identification of Polymorphisms as Predictors of Drug Response 360

7.8.1. Candidate Gene Approach 360

7.8.2. Genome-wide Approach 363

7.8.3. Pathway Approach 366

7.8.4. Use of Model Systems in Identification of Predictive Pharmacogenetic Markers 369

7.8.5. Comparison of Methodologies in the Context of Drug Discovery 373

References 375

8. Pharmacogenetics of Drug Disposition 385
Anahita Bhathena

8.1. Introduction 385

8.2. Genes and Polymorphisms Affecting Drug Disposition 387

8.2.1. Drug-Metabolizing Enzymes 391

8.2.1.1. Cytochrome P450s 391

8.2.1.2. Flavin-Containing Monooxygenases 396

8.2.1.3. Arylamine N-Acetyltransferases 397

8.2.1.4. UDP-Glucuronosyltransferases 397

8.2.1.5. Sulfotransferases 399

8.2.2. Drug Transport Proteins 400

8.2.2.1. SLC Transporters 401

8.2.2.2. ABC Transporters 402

8.3. Genomic Biomarkers for PK Studies 403

8.3.1. Warfarin, CYP2C9, and VKORC1 403

8.3.2. Irinotecan and UGT1A1 404

8.4. Utility of PG-PK Studies in Early Clinical Trials 405

8.5. Limitations of PG-PK Studies 408

8.6. Genotyping Technologies 408

8.7. Conclusion 409

References 411

9. Overview of Regulatory Developments and Initiatives Related to the Use of Genomic Technologies in Drug Discovery and Development 423
Eric Blomme

9.1. Introduction to Recent Regulatory Developments in the Genomic Area 423

9.2. FDA Guidance on Pharmacogenomic Data Submission 428

9.2.1. Voluntary Genomic Data Submission (VGDS) 428

9.2.2. Pharmacogenomic Data Submission 431

9.2.3. International Harmonization 432

9.3. Pharmacogenomic Data Submissions: Draft Companion Guidance 434

9.4. Drug-Diagnostic Co-development Concept Paper 436

9.5. Regulations for In Vitro Diagnostic Assays 439

9.5.1. General Overview of Regulatory Pathways for Devices in the U.S. 439

9.5.2. Draft Guidance for Industry, Clinical Laboratories, and FDA Staff on In Vitro Diagnostic Multivariate Index Assays 440

9.6. Biomarker Qualification 442

9.7. Current Initiatives Relevant to Pharmacogenomics 443

9.8. Future Impact of Genomic Data on Drug Development 444

References 447

Index 449

?This book is highly recommended to active researchers in genomics and to the comparative and veterinary clinician or researchers looking for a focused review of the emerging discipline.? (The Veterinary Journal , August 2009)

?Overall, it provides excellent, up-to-date coverage of the application of genomics in drug development.? (Doody's Reviews, June 2009)

?The chapters are logically arranged and the structure of the book and hence approach of the topics by the authors is easily followed. [They] have managed to find a (rare) balance between the urge for comprehensive coverage of textbook dimensions with accessibility of content for readers who are less grounded in the authors? respective fields of expertise. The book therefore represents an excellent overview with sufficient depth, providing a wide range of readers in preclinical research and discovery, as well as clinical drug development with the necessary background to make more sense of a plethora of genomic publications and data that are presented in journals and at conferences.? -- Leonardo Sahelijo, Director Pharmacogenomics, TGRD Biological Sciences