CNS Cancer (eBook)

Erwin G Van Meir is Professor of Neurosurgery and Hematology & Medical Oncology in the School of Medicine at Emory University. A native of Belgium, he obtained Bachelor’s degrees in Biology and Education at the University of Fribourg, Switzerland. He pursued graduate studies in Molecular Virology at the University of Lausanne, Switzerland where he obtained his PhD in 1989. He then became interested in cancer and pursued postdoctoral work at the University Hospital in Lausanne and at the Ludwig Institute for Cancer Research in San Diego. In 1994 he became a Junior Faculty and Director of the Laboratory of Brain Tumor Biology and Genetics in the Neurosurgery Department at the University of Lausanne. In 1998 he joined Emory University in Atlanta, where he now serves as the Leader of the Winship Cancer Institute Molecular Pathways and Biomarkers scientific program and as the co-Director of the brain tumor working group. For the past 20 years Dr. Van Meir’s research has focused on defining the biological significance of specific genetic alterations for brain tumor development, with particular emphasis on extracellular signaling regulating heterotypic cell communication as in tumor angiogenesis, and translating this knowledge into new therapeutic approaches. His research is described in more than 140 peer-reviewed research papers and review articles in internationally recognized journals that have cumulated over 5,000 citations and received several awards. These contributions were presented in over 100 invited seminars worldwide and have furthered the understanding of cytokine expression for glioma biology, Turcot syndrome, the role of transcription factors p53 and HIF and of pro- and anti-angiogenesis factors IL-8, thrombospondin-1 and brain angiogenesis inhibitor-1 in brain tumor angiogenesis, hypoxia, and pseudopalisade formation. He also discovered novel biomarkers in the cerebrospinal fluid of brain tumor patients and developed novel therapeutic agents including oncolytic hypoxia-activated adenoviruses, pro-apoptotic galectin-3, anti-angiogenic vasculostatins and small molecule HIF/Hsp90/plectin1 inhibitors that are covered by several US and foreign patents. Perhaps most importantly, over his still young 20 year independent career Dr Van Meir has already mentored and trained over 60 postdoctoral fellows, students and visiting scientists, many of which now hold independent leading positions in Academia or Industry. Dr Van Meir is an active member of the International Neuro-Oncology community and served on the Board of Directors of the Society for Neuro-Oncology from 2004-2008. He organized several international conferences on brain tumors, has served on the Scientific Committee of the European Association for Neuro-Oncology, the Scientific Advisory Board of the Southeastern Brain Tumor Foundation and is a current or former member of several other international cancer societies including the American Association for Cancer Research, the European Association for Cancer Research, and the American Society for Investigative Pathology. Dr. Van Meir currently serves on the Editorial Board of Neuro-Oncology, Frontiers in Bioscience, and International Journal of Oncology and is a former Associate Editor of the International Journal of Cancer. He has served as a reviewer for over 30 international scientific journals and for grant proposals from public and private agencies including the US National Institutes of Health, the US Department of Defense, the Swiss National Science Foundation, the Swiss Cancer Society, the Wellcome Trust of the UK, Cancer Research UK, the Research Grants Council of Hong Kong, the Israel Science Foundation, The Belgian Fournier-Majoie and Baudouin Foundations and the Italian Association for Cancer Research. He acknowledges present and past support by multiple funding agencies for his scientific work, including the US National Institutes of Health, the Swiss National Science Foundation, the Goldhirsh Foundation, the Charlotte Geyer Foundation, the Southeastern and National Brain Tumor Foundations, The Brain Tumor Society, the Pediatric Brain Tumor Foundation of the US, the American Brain Tumor Association, the Brain Tumor Foundation for Children, the Al Musella, Wayne O Rollins and Frances Wood Wilson Foundations, the Brain Tumor Trust, the Emory University Research Council and EmTechBio, the Swiss Cancer League and Anti-Cancer Foundations, the San Salvatore, Tossizza, Ott and Chuard-Smith Foundations, and the European Institute of Oncology.

Cancer Drug Discovery and Development 2
CNS Cancer 3
Foreword 6
Preface 8
Editor 10
Contents 12
Contributors 17
Color Plates 26
Part 1: Animal Models for Central Nervous Tumors 39
Modeling Gliomas Using PDGF-Expressing Retroviruses 40
1.1 The Utility of Animal Glioma Models 41
1.2 Comparing Retroviral Glioma Models to Other Model Systems 41
1.2.1 Transplantation of Glioma Cell-Lines 42
1.2.2 Transplantation of Primary Glioma Cells or Cancer Stem Cells 43
1.2.3 Glioma Models Using Genetically Engineered Mice (GEM) 43
1.2.4 Retroviral Glioma Models 45
1.2.4.1 Using Retroviruses to Deliver Genetic Lesions to Discrete Cell Populations at a Specific Place and Time 45
1.2.4.2 PDGF as a Link Between Glial Progenitors and Gliomas 47
1.2.4.3 PDGF Retroviruses Drive the Formation of Tumors That Closely Resemble Human Gliomas 48
1.2.4.4 PDGF Drives Adult Glial Progenitors to form Malignant Gliomas 49
1.2.4.5 Using Retroviruses to Test the Effects of Multiple Genetic Lesions 52
1.2.4.6 Using Retroviral Models to Study Glioma Infiltration 52
1.2.4.7 Using Retroviral Models to Study Interactions Within the Brain Microenvironment 54
1.2.4.8 Using Retroviral Models for Preclinical Studies 56
References 59
Modeling Brain Tumors Using Avian Retroviral Gene Transfer 65
2.1 History 66
2.2 RCAS 67
2.3 Retroviral Life Cycle 68
2.4 Tv-a Transgenic Mice 70
2.5 Modeling Brain Tumors with RCAS/tv-a 71
2.5.1 Gliomas 72
2.5.2 Loss of Function, Knockouts, and Cre/lox 72
2.5.3 Medulloblastomas - SHH Signaling 74
2.6 Imaging, Stem Cell Niches, and Preclinical Trials 75
References 76
Using Neurofibromatosis Type 1 Mouse Models to Understand Human Pediatric Low-Grade Gliomas 80
3.1 Pediatric Low-Grade Glioma 81
3.2 Neurofibromatosis Type 1 82
3.2.1 NF1 Clinical Features 82
3.2.2 Brain Tumors in NF1 82
3.3 Mouse Models of NF1-Associated Optic Glioma 83
3.3.1 Growth Regulatory Pathways 83
3.3.2 Tumor Microenvironment 85
3.3.3 Preclinical Therapeutic Studies 88
3.4 Future Directions 90
References 91
Transgenic Mouse Models of CNS Tumors: Using Genetically Engineered Murine Models to Study the Role of p21-Ras in Glioblastoma Multiforme 95
4.1 Introduction 96
4.2 Embryonic Stem Cell Transgenesis to Generate Mouse Models 96
4.3 Genetically Engineered Murine Mouse Models (GEMs) of GBM 98
4.4 GFAP:12 V-HaRas Astrocytoma Model: Characterization of RasD7, RasB8 99
4.5 Study of Cooperative Interactions Between Ras Overexpression and Other Known Genetic Alterations in Human Astrocytomas 103
4.6 Identifying Novel GBM Modifier Genes Using the RasB8 GEM and Gene-Trapping 105
4.7 Ontogeny of Astrocytomas 107
4.8 Conclusions 108
References 109
Pten-Deficient Mouse Models for High-Grade Astrocytomas 111
5.1 Introduction 112
5.2 Pten-Null or Akt-Activated Mouse Models of High-Grade Astrocytoma 113
5.3 Pten-Heterozygous Mouse Models of High-Grade Astrocytoma 116
5.4 Discussion 118
References 122
The Nf1-/+ Trp53-/+cis Mouse Model of Anaplastic Astrocytoma and Secondary Glioblastoma: Dissecting Genetic Susceptibility to Brain Cancer
6.1 Introduction 128
6.2 Clinical History, Pathology, and Genetics of Astrocytomas 128
6.3 The NPcis Mouse Model of Astrocytoma/Glioblastoma 132
6.3.1 Histology of NPcis Astrocytomas 134
6.3.2 Molecular Biology of NPcis Astrocytomas 135
6.3.3 Tumor Cell Lines Derived from NPcis Astrocytomas 136
6.4 Factors Affecting Astrocytoma Susceptibility in NPcis Mice 137
6.4.1 The Effect of Parental Origin and Offspring Sex on NPcis Astrocytomas 137
6.4.2 The Effect of Background Polymorphisms on NPcis Astrocytomas 141
6.5 Application of the NPcis Model of Astrocytoma 142
6.5.1 Advantages of the NPcis Astrocytoma Model 142
6.5.2 Limitations of the NPcis Astrocytoma Model 144
6.6 Summary 146
References 147
Modeling Astrocytomas in a Family of Inducible Genetically Engineered Mice: Implications for Preclinical Cancer Drug Development 153
7.1 Introduction 154
7.2 In Vivo Modeling of Astrocytomas in Genetically Engineered Mice 155
7.2.1 Overview of Genetic Modeling of Diffuse Gliomas 155
7.2.2 Conditional, Inducible GEM of Astrocytomas 163
7.2.3 The Future of GEM Astrocytoma Models 168
7.3 Astrocytoma GEM Application in Translational and Preclinical Research 170
References 174
Human Brain Tumor Cell and Tumor Tissue Transplantation Models 180
8.1 Cell Culture-Based Approaches 181
8.2 Xenograft-Based Tumor Propagation 184
8.3 Intracranial vs. Subcutaneous Tumor Therapy Response Experiments 186
8.4 The Impact of Bioluminescence Imaging 188
8.5 Human Tumor Panels and Pre-Clinical Therapeutic Testing of Multiple Tumors 191
References 192
Transformed Human Brain Cells in Culture as a Model for Brain Tumors 195
9.1 Introduction 196
9.2 Early Developments 198
9.3 Modifiers of Transformation and Tumor Behavior 201
9.4 Answers and More Questions 204
9.5 New Approaches 207
9.6 Conclusions 208
References 209
Rat Glioma Models for Preclinical Evaluation of Novel Therapeutic and Diagnostic Modalities 213
10.1 Introduction 214
10.2 9L Gliosarcoma 217
10.3 T9 Glioma 221
10.4 C6 Glioma 222
10.5 F98 Gliomas 223
10.6 RG2 (or D74) Glioma 225
10.7 Avian Sarcoma Virus-Induced and RT-2 Gliomas 226
10.8 CNS-1 Glioma 227
10.9 BT4C Glioma 227
10.10 Concluding Comments 228
References 229
Neuro-oncogenesis Induced by Nitroso Compounds in Rodents and Strain-Specific Genetic Modifiers of Predisposition 238
11.1 Introduction 239
11.2 The Neuro-Oncogenic Effect of ENU and MNU 240
11.3 Characteristics of ENU- and MNU-Induced Nervous System Tumors 241
11.3.1 Histological Classification 241
11.3.2 Genetic Alterations 242
11.4 Determinants of ENU- and MNU-Induced Neuro-oncogenesis 243
11.4.1 Developmental Stage of the Nervous System at ENU Exposure 243
11.4.2 Doses and Route of Administration 244
11.4.3 Rodent Species and Strain 244
11.5 Genetics of Susceptibility and Resistance to ENU-Induced Neuro-oncogenesis and Analyses of the Underlying Phenotypes 245
11.5.1 Inheritance of Susceptibility to ENU-Induced MPNST Development 247
11.5.2 Identification and Characterization of Gene Loci Involved in Susceptibility or Resistance to ENU-Induced MPNST Development 247
11.5.3 Phenotypic Analyses of Effector Mechanisms Underlying Differential MPNST Risk 250
11.6 Conclusions 253
References 255
The Murine GL261 Glioma Experimental Model to Assess Novel Brain Tumor Treatments 258
12.1 The Murine GL261 Glioma Experimental Model 259
12.2 The Murine GL261 Glioma Experimental Model: Validation Studies for a Predictive Preclinical Model 260
12.3 Neuropathology 262
12.4 Tumor Biology 264
12.4.1 Invasion, Angiogenesis, and Hypoxia 264
12.4.2 Signaling Pathways 266
12.5 Neuroimaging and Neuroradiology 267
12.6 Significance of GL261 Glioma Animal Model for Use as a Predictive Preclinical Model 268
References 270
Spontaneous Occurrence of Brain Tumors in Animals: Opportunities as Preclinical Model Systems 273
13.1 Introduction 274
13.2 Drosophila and Cancer Research 275
13.2.1 Drosophila Brain Tumor (brat) Gene 276
13.3 Zebrafish: A New Model of Nervous System Tumorigenesis? 280
13.4 Mouse and Rat Models of Brain Tumors 281
13.4.1 The 4C8 Mouse Glioma Syngeneic Graft Model 281
13.4.2 The Spontaneous VM/Dk Murine Astrocytoma 282
13.4.2.1 Cytological Characteristics 282
13.4.2.2 Biological Characteristics 282
13.4.3 Rat Brain Tumor Models 283
13.5 Spontaneous Brain Tumors in Dogs 284
13.5.1 Epidemiology and Pathology 285
13.5.1.1 Canine Meningiomas 287
13.5.1.2 Canine Astrocytomas 288
13.5.1.3 Canine Glioblastoma Multiforme 289
13.5.1.4 Canine Oligodendrogliomas 294
13.5.1.5 Canine Choroid Plexus Papillomas 294
13.5.2 Prognosis and Treatment for Canine CNS Tumors 294
13.5.3 Canine Brain Tumor Experimental Treatment Trials 298
13.5.3.1 Immunotherapy 298
13.5.3.2 Gene Therapy 298
13.5.3.3 Convection-Enhanced Delivery 298
13.5.4 Canine Glioma Cell Lines 299
13.5.5 Problems and Challenges with the Use of Spontaneous Canine Brain Tumors 300
13.6 Summary 300
References 301
Part 2: Prognostic Factors and Biomarkers 311
p53 Pathway Alterations in Brain Tumors 312
14.1 Introduction 313
14.2 The p53 Family 314
14.3 p53 Functions: Intracellular Effects 314
14.3.1 p53 and Cell Cycle Arrest 315
14.3.2 p53 and Apoptosis 316
14.3.3 p53 Regulation of Cellular Senescence 317
14.3.4 p53 and the Mechanisms Maintaining Genomic Integrity 318
14.3.5 p53 and MicroRNA 319
14.3.6 p53 and Invasion/Motility 319
14.3.7 p53 in Differentiation, Development, and Aging 319
14.3.8 p53 and Aerobic Respiration and Glycolysis 320
14.4 p53 Function: Effects on the Tumor Microenvironment (p53 Extracellular Effects) 320
14.4.1 p53 and Angiogenesis 321
14.4.2 p53 and the Immune Response 322
14.5 p53 Regulation 322
14.5.1 The p14ARF/MDM2/p53 Pathway 323
14.5.2 Phosphorylation 324
14.5.3 Acetylation 325
14.5.4 Subcellular Localization 325
14.6 TP53 Mutations in Brain Tumors 326
14.6.1 p53 Mutation Spectrum in Brain Tumors 326
14.6.2 Mutation Sites 328
14.6.3 Mechanism of Action of p53 Mutants 328
14.7 Mutant p53 as a Therapeutic Target 330
14.7.1 Reactivation of Mutant p53 by Structural Manipulations and Peptides 330
14.7.2 Small Molecules That Target Mutant p53 330
14.7.3 Gene Delivery of wt p53 331
14.7.4 Viral Therapy Specific for Tumor Cells with Mutant p53 331
14.8 Summary 332
References 332
The PTEN/PI3 Kinase Pathway in Human Glioma 344
15.1 Introduction 345
15.2 Pathway Activation: PI3K Signaling and Downstream Effectors 346
15.2.1 Class 1 PI3Ks 346
15.3 Upstream Activation of PI3K by RTK Signaling 348
15.3.1 Epidermal Growth Factor Receptor 349
15.3.2 Platelet-Derived Growth Factor Receptor 349
15.3.3 Receptor Co-activation as a Mechanism of Therapeutic Resistance in Glioma 350
15.3.4 Ras 351
15.4 Regulation of Downstream PI3K Effectors 351
15.5 Mouse Models Defining the Function of Class 1 PI3Ks 354
15.6 Pathway Inhibition: PTEN 355
15.6.1 Loss of Heterozygosity of Chromosome 10 and the Search for Tumor Suppressor Genes 355
15.6.2 PTEN Discovery and Its Link to Genetic Syndromes 356
15.6.3 Lipid Phosphatase-Specific Functions of PTEN 357
15.6.4 Protein Phosphatase-Specific Functions of PTEN 358
15.6.5 Non-enzymatic Functions of PTEN 358
15.7 PTEN in Glioma Biology: Primary vs Secondary Glioma 359
15.8 PTEN Involvement in Brain Tumor Stem Cells 361
15.9 Transcriptional Regulation 362
15.10 Inactivation Mechanisms of PTEN 364
15.10.1 PTEN Loss and Mutation Spectrum in Glioma 364
15.10.2 Modulation of PTEN Function by Protein Modifications 364
15.10.3 MicroRNA Regulation of PTEN Expression 366
15.11 PTEN Localization 366
15.12 Other Regulators of Akt Activity 367
15.13 Mouse Glioma Models and PTEN Involvement 367
15.14 Therapeutic Intervention and Conditions for Resistance in Glioma and Breast Cancer: PTEN as a Marker for Drug Response and Resistance 368
15.15 Conclusions 369
References 370
Value of 1p/19q and Other LOH Markers for Brain Tumor Diagnosis, Prognosis, and Therapy 387
16.1 Introduction 388
16.2 1p/19q Loss Is Associated with Response to Therapy in Grade III Gliomas 388
16.3 Is There a Common Prognostic Denominator in GBM and ODG on Chromosome 1p? 389
16.4 The Search for 1p Glioma Suppressor Genes 390
16.5 The Search for 19q Glioma Suppressor Genes 391
16.6 Fine Mapping of the Deletions in the 1p Arm Reveals that Loss of the Centromeric 1p Region/Area Correlates with Survival in ODG and GBM 392
16.7 Gene Mapping Within the Chromosome 1 Pericentric Duplication 393
16.8 ROC Analysis for 1p and Prognosis Shows that N2/N2N Analysis Is Superior to Histology 394
16.9 An Oncogenic Role of Notch2 in Gliomagenesis? 396
16.10 Conclusion 397
References 398
Discovery of Genetic Markers for Brain Tumors by Comparative Genomic Hybridization 401
17.1 Historical Perspective 401
17.2 General Methodology 403
17.3 Interpretation of aCGH Data 407
17.4 Strategy for Identifying Genetic Markers with Clinical Relevance Using Array CGH 408
17.5 New Insights in Primary Brain Tumors Using Array CGH 412
17.6 Array CGH in Cancer Subgroup and Gene Discovery 416
17.7 Useful Resources 418
References 419
Genomic Identification of Significant Targets in Brain Cancer 423
18.1 Introduction 424
18.2 Key Features of the GISTIC Algorithm 426
18.3 The Four Stages of the GISTIC: A Detailed View 427
18.4 Application of GISTIC to Glioma 430
18.5 Application of GISTIC to Other Cancers 435
18.6 Limitations and Future Modifications of the GISTIC Algorithm 436
References 438
Oncomodulatory Role of the Human Cytomegalovirus in Glioblastoma 442
19.1 Human Cytomegalovirus Background 444
19.1.1 HCMV Is Widely Prevalent and Persistently Infects Adult Human Stem Cells 444
19.1.2 HCMV and Human Malignant Gliomas 444
19.2 Oncomodulatory Properties of HCMV and Their Contribution to Glioma Pathogenesis 445
19.2.1 The Role of Inflammatory Chemokines and Chemokine Receptors 445
19.2.2 HCMV Immediate-Early (IE) Gene Products Dysregulate Cell Cycle Controls, Are Mutagenic, Are Anti-Apoptotic, and Promote Oncogenic Transformation 446
19.2.3 HCMV Infection Modulates Cell Proliferation and Cell Survival Signaling Pathways 447
19.2.4 HCMV Infection Modulates Cellular Pathways that Promote Cell Migration and Invasion 447
19.2.5 HCMV Promotes Angiogenesis 448
19.2.6 HCMV Strain Variability and Gene Expression Patterns Influence Viral Neurotropism 448
19.3 HCMV Reactivation in Patients with Malignant Gliomas: The Role of the Immune System and Lessons from Animal Models 449
19.3.1 The Impact of the Immunosuppressed Status of GBM Patients on HCMV Reactivation 449
19.3.2 Reactivation of CMV During Neural Precursor Differentiation: Evidence from Mouse Models 450
19.3.3 HCMV Infection Can Arrest Differentiation of Stem Cells 450
19.4 The Glioma Cell of Origin: The Role of Glioma Stem-Like Cells 450
19.4.1 Glioma Stem Cells 450
19.4.2 Evidence for a Role of HCMV IE1 Expression in Glioma Stem-Like Cells 452
19.5 The Role of PDGF/PDGFRalpha Signaling in Gliomagenesis 453
19.5.1 The PDGF/PDGFR System Is Genetically Altered in GBMs 453
19.5.2 PDGFRalpha Is a Required Cellular Receptor for HCMV 454
19.6 Evidence in Support of a Role for HCMV-Induced Oncogenesis by Activation of Human PDGFRalpha 457
19.6.1 PDGFRalpha and HMCV IE1 Co-localize in Primary Human GBM Tissues and Cells 457
19.6.2 HCMV Promotes Glioma Cell Invasiveness by Engaging PDGFRalpha and the alphavbeta3 Integrin 458
19.6.3 Mechanisms of HCMV-Induced Oncogenesis in Human Adult Neural Precursor Cells 458
19.7 HCMV Association with Glioblastoma: Implications for Cancer Prevention, Detection, and Therapy 460
19.7.1 HCMV Association with Glioblastoma: Cause or Consequence? 460
19.7.2 Clinical Impact of HCMV Association with Glioblastoma: Implications for Cancer Prevention, Detection, Screening, and Treatment 461
19.8 Summary 461
References 463
Aberrant EGFR Signaling in Glioma 468
20.1 DeltaEGFR 468
20.2 Other Glioma-Associated Mutations of the EGFR 472
20.3 Clinical Significance of EGFR Abnormalities: Biomarker and Target 473
20.4 EGFR Localization Beyond the Plasma Membrane 476
References 480
Mechanisms of Brain Tumor Angiogenesis 487
21.1 Angiogenesis in Brain Tumors 488
21.1.1 Neovascularization as an Independent Prognostic Marker for Brain Tumors 489
21.1.2 How Angiogenesis Occurs in Brain Tumors 490
21.1.3 Morphology of Neo-Vessels and Blood-Brain Barrier (BBB) in Gliomas 491
21.2 Regulation in Brain Tumor Angiogenesis 491
21.2.1 VEGF-A and Its Isoforms 493
21.2.2 Other VEGF Family Members 494
21.2.3 VEGF Receptors (VEGFR) 496
21.2.4 VEGFR-Mediated Signaling 497
21.2.5 Angiopoietins 501
21.2.6 Tie2-Mediated Signaling 503
21.2.7 Interaction Between Angiopoietins and Integrins 504
21.2.8 PDGF and Their Receptors 505
21.2.9 Other Growth Factors and Their Receptors: HGF/c-Met 506
21.2.10 FGF/FGFR 506
21.2.11 TGF-beta 507
21.2.12 Integrins 507
21.2.13 Interleukin-8 (IL-8) 508
21.2.14 Nitric Oxide (NO) 508
21.2.15 Hypoxia in Brain Tumor Angiogenesis 509
21.2.16 Hypoxia-Inducible Factor-1 (HIF-1) 509
21.2.17 Induction of Angiogenic Inhibitors by Tumor Suppressor Genes 511
21.2.18 Contribution of Tumor Angiogenesis by Stem Cell-Like Glioma Cells 511
21.2.19 Anti-angiogenic Therapy of Brain Tumors: Clinical Applications and Challenges 512
21.3 Summary 513
References 513
Vaso-occlusive Mechanisms that Intiate Hypoxia and Necrosis in Glioblastoma: The Role of Thrombosis and Tissue Factor 533
22.1 Introduction 534
22.2 Distinctive Features of Glioblastoma 534
22.3 The Significance of Pseudopalisades, Necrosis, and Hypoxia 538
22.4 Vascular Pathology Underlies Hypoxia, Necrosis, and Pseudopalisades 539
22.5 Initiators of Vascular Pathology 540
22.6 Intravascular Thrombosis Accentuates and Propagates Tumor Hypoxia 540
22.7 Tissue Factor, a Potent Pro-Coagulant, Is Upregulated in GBM 541
22.8 PTEN, EGFR, and Hypoxia Regulate Tissue Factor Expression in GBM 542
22.9 TF Intitiates Signaling Through Its Cytoplasmic Tail and Through PARs 546
22.10 Angiogenesis Supports Peripheral Tumor Growth 547
22.11 Conclusion 549
References 549
Transcription Profiling of Brain Tumors: Tumor Biology and Treatment Stratification 555
23.1 Microarray Profiling 556
23.2 Expression Profiling in Human Brain Tumors 559
23.3 Expression Profiling of Human Gliomas 561
23.4 Molecular Subtypes of Infiltrating Gliomas 565
23.5 Stem-Cell Biomarkers 566
23.6 The Future of Profiling: Multiplatform Integration 567
23.7 Conclusions 568
References 568
Proteomic Profiling of Human Brain Tumors 578
24.1 Background 579
24.2 Protein Separation 580
24.2.1 Two-Dimensional Polyacrylamide Gel Electrophoresis (2D PAGE) 580
24.2.2 Two-Dimensional Difference Gel Electrophoresis (2D DIGE) 582
24.2.3 Liquid Chromatography (LC) 583
24.3 MS-Based Protein Identification 584
24.3.1 Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF-MS) 585
24.3.2 Surface-Enhanced Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (SELDI-TOF-MS) 586
24.4 Tissue Microarray (TMA) 588
24.5 Protein and Antibody Array Analysis 589
24.6 Conclusion 593
References 596
Proteomic Discovery of Biomarkers in the Cerebrospinal Fluid of Brain Tumor Patients 601
25.1 Introduction 602
25.2 Why Proteomics? 602
25.3 Cerebrospinal Fluid as a Biomarker Repository 603
25.3.1 Composition of the CSF 603
25.3.2 Significance of CNS Barriers 606
25.4 CSF Proteomics for the Identification of CNS Neoplasia 608
25.4.1 The Promise of CSF Proteomics: The Identification of Markers of CNS Neoplasia for Patient Diagnosis, Prognosis, and Follow-Up After Therapy 608
25.4.2 Proteomic Methods for CSF Profiling 609
25.4.2.1 1-D and 2-D Gel Electrophoresis 611
25.4.2.2 Preparative 2-D Liquid-Phase Electrophoresis 613
25.4.2.3 MS Identification of 2-DE-Separated Proteins 613
25.4.3 Quantitative Proteomics 614
25.4.4 Initial Results and First Biomarker Panel for Brain Tumor CSF 615
25.4.5 Lessons Learned from Initial CSF Proteomic Studies 618
25.5 Importance of Experimental Design in CSF Proteomics 619
25.5.1 Accounting for Individual Variation Through Appropriate Biostatistical Design 619
25.5.2 Sample Selection and Processing 620
25.5.2.1 Prefractionation and Depletion of CSF 622
25.5.2.2 Preparation of CSF Samples 622
25.6 Data Analysis and Validation 623
25.7 Future Directions 624
25.7.1 Glyco-/Phospho Proteomics 624
25.7.2 Protein and Peptide Arrays 625
25.7.3 Antibody Arrays 625
25.7.4 Biomarker Panel 626
25.8 Conclusion 626
References 634
Epigenetic Profiling of Gliomas 638
26.1 A Central Role for Epigenetics in Biology 639
26.1.1 DNA Methylation and DNA Methyltransferases 639
26.1.2 Histone Modifications 640
26.1.3 Other Potential Epigenetic Factors 641
26.1.4 Epigenetic Regulation of Promoter CpG Islands 642
26.1.5 Functions of DNA Methylation 643
26.1.6 Environment and Epigenetics 644
26.1.7 Epigenetic Regulation in the CNS 645
26.1.8 Role of DNA Methyltransferases in the CNS 645
26.2 Epigenetic Dysregulation in Cancer 646
26.2.1 DNA Hypomethylation in Cancer 646
26.2.2 DNA Hypermethylation in Cancer 647
26.2.3 Histone Code Modifications and Cancer 648
26.2.4 Nucleosome Positioning Alterations in Cancer 649
26.2.5 Causes of Epigenetic Modifications in Cancer 649
26.2.6 Environmental Factors Affecting Epigenetic Modifications in Cancer 650
26.3 Epigenetic Dysregulation in Gliomas 651
26.3.1 Overview of Epigenetic Alterations in Gliomas 651
26.3.2 Epigenetic Silencing of MGMT and Drug Resistance to Alkylating Agents 652
26.3.3 Patterns of Epigenetic Alterations in Gliomas 653
26.3.4 Epigenetics of Glioma Tumor Initiating Cells 654
26.3.5 Identification of Genome-Wide Methylation Patterns in Brain Tumors 655
26.3.6 Aberrant Expression of MicroRNAs in Gliomas 656
26.4 Targeting Epigenetic Events for Therapy in Gliomas 656
26.4.1 Overview of Epigenetic Therapy for Gliomas 656
26.4.2 Histone Deacetylase (HDAC) Inhibitors for Glioma Treatment 657
26.4.3 Epigenetic Marks as Biomarkers for Clinical Evaluation 659
26.5 Future Directions for Epigenetics of Gliomas 660
References 661
MicroRNAs in the Central Nervous System and Potential Roles of RNA Interference in Brain Tumors 674
27.1 Introduction 675
27.2 miRNA and siRNA Background 675
27.3 MicroRNAs in CNS Development and Function 678
27.4 Individual MicroRNAs in the CNS 679
27.5 MicroRNAs in Cancer 680
27.6 MicroRNAs in Brain Tumors 683
27.6.1 Oncogenic miRNAs in Brain Tumors 684
27.6.2 miRNAs with Tumor Suppressor Properties in Brain Tumors 686
27.7 Potential miRNA- and siRNA-Based Therapies for Brain Tumors 687
27.7.1 Delivery of siRNAs or miRNAs as Therapy 687
27.7.2 Oncogenic miRNA-Based Therapies 688
27.7.3 Tumor-Suppressive miRNA-Based Therapies 688
27.7.4 Indirect miRNA-Based Strategies for Brain Tumor Therapy 689
27.8 Conclusion 690
References 691
Of Escherichia coli and Man: Understanding Glioma Resistance to Temozolomide Therapy 701
28.1 Introduction 702
28.2 Temozolomide (TMZ): Chemical Properties 703
28.3 Repair of Temozolomide-Induced DNA Damage in E. coli 703
28.3.1 N7-Methyl Guanine 703
28.3.2 N3-Methyl Adenine 705
28.3.3 N3-Methyl Cytosine 708
28.3.4 O6-Methyl Guanine 708
28.4 Evolutionarily Conserved Temozolomide Resistance Mechanisms 712
28.4.1 N7-Methyl Guanine 713
28.4.2 N3-Methyl Adenine 714
28.4.3 N3-Methyl Cytosine 714
28.4.4 O6-Methyl Guanine 715
28.4.5 MMR and DNA Damage Checkpoint Activation 717
28.4.6 Fanconi Anemia (FA) DNA Repair Pathway 719
28.5 Temozolomide Resistance Mechanism Unique to Higher Eukaryotes 721
28.5.1 p53 721
28.5.2 Autophagy 722
28.6 Conclusion 723
References 725
Brain Tumor Stem Cell Markers 734
29.1 Introduction 735
29.2 Tumor Stem Cell Markers 736
29.3 Prominin-1/CD133 738
29.4 Nestin 740
29.5 Bmi1 740
29.6 Musashi1 741
29.7 Notch 741
29.8 Sox2 741
29.9 A2B5 742
29.10 Other Potential Brain Tumor Stem Cell Markers 742
29.11 Perspectives 742
29.12 Conclusions 743
References 743
Part 3: Therapeutic Targets and Targeting Approaches 750
Clinical Agents for the Targeting of Brain Tumor Vasculature 751
30.1 Introduction 752
30.2 Angiogenesis in Gliomas 752
30.3 Antibodies to Growth Factors/Receptors 755
30.3.1 Bevacizumab (Avastin) 756
30.3.2 Aflibercept (VEGF-Trap) 757
30.4 Tyrosine Kinase Inhibitors 757
30.4.1 Cediranib (Recentin) 757
30.4.2 Vatalanib 758
30.4.3 Other TKIs 758
30.5 Resistance to Anti-VEGF Therapy 759
30.6 Toxicities of Anti-VEGF Agents 759
30.7 VEGF-Inhibitors as Anti-edema Therapies 760
30.8 Assessing Glioblastoma Response and Progression with Anti-VEGF Therapies 761
30.9 Future Role of Anti-VEGF Agents in the Therapy of Glioblastoma 762
References 763
Bone Marrow-Derived Cells in GBM Neovascularization 768
31.1 Introduction 769
31.1.1 Neovascularization Is a Prerequisite for Tumor Progression 769
31.1.2 Tumor Neovascularization Is Driven by Angiogenic and Vasculogenic Mechanisms 770
31.2 Bone Marrow-Derived Cells Contribute to Neovascularization in GBM 771
31.2.1 Vascular Progenitor Cells 773
31.2.1.1 Endothelial Progenitor Cells (EPC) 774
31.2.1.2 Pericyte Progenitor Cells (PPC) 778
31.2.2 Proangiogenic Myeloid Support Cells 779
31.2.2.1 Tumor-Associated Macrophages (TAM) 780
31.2.2.2 TIE2-Expressing Monocytes (TEM) 782
31.2.2.3 VEGFR1+ CXCR4+ Hemangiocytes 783
31.2.2.4 Myeloid-Derived Suppressor Cells (MDSC) 783
31.3 Conclusions 784
References 787
Vascular Targeting of Brain Tumors - Bridging the Gap with Phage Display 793
32.1 Introduction 794
32.2 The Principles of Phage Display 795
32.3 The Blood-Brain Barrier 797
32.4 Glioblastoma and Angiogenesis 798
32.5 Targeting of the Brain Tumors by Phage Display 799
32.6 Targeted Therapy and Imaging 800
32.6.1 AAVP, a Novel Hybrid Gene Delivery System 801
32.7 Conclusions 802
References 803
Impact of the Blood-Brain Barrier on Brain Tumor Imaging and Therapy 806
33.1 Introduction 807
33.2 Historical Beginnings of the BBB Concept 807
33.3 Structure and Function of the Blood-Brain Barrier 808
33.3.1 Renewed Emphasis on Understanding of the Blood-Brain Barrier 811
33.4 Importance of the BBB for Imaging of Brain Tumors 814
33.4.1 Angiogenesis and Permeability: Similarities and Differences 814
33.4.2 Permeability as a Surrogate Marker for Angiogenesis 814
33.4.3 T1-Weighted Imaging Techniques 815
33.4.4 Dynamic Susceptibility Contrast MR Imaging in Brain Tumor Assessment 818
33.4.5 Correlation of MR Perfusion Imaging with Angiographic and Histological Tumor Features 819
33.5 Importance of BBB for Therapy of Brain Tumors 820
33.5.1 Impact on Brain Tumor Therapy 820
33.5.2 Enhanced Transit of Agents across the Blood-Brain Barrier 821
33.5.3 Drug Dose Intensification 821
33.5.4 BBB Alteration to Allow Increased Drug Transport 821
33.5.5 Drugs with Increased Transport Capabilities Across the BBB 822
33.5.6 Local Delivery Techniques 823
33.5.7 Convection-Enhanced Delivery 823
33.5.8 Assessment of Drug Pharmacokinetics Within Brain Tissue 823
33.6 Summary 824
References 825
Targeting CXCR4 in Brain Tumors 829
34.1 Introduction 830
34.2 Classification of Chemokines and Their Receptors 831
34.3 History of CXCR4/CXCL12 833
34.4 Functions of CXCR4 in the Normal CNS 834
34.5 Involvement of CXCR4 in Non-CNS Cancers 836
34.6 Involvement of CXCR4 in Glioma 842
34.7 Involvement of CXCR4 in Medulloblastoma 843
34.8 Involvement of CXCR4 in Meningioma 844
34.9 Involvement of CXCR4 in Neuroblastoma 845
34.10 Concluding Remarks 846
References 847
Molecular Targeting of IL-13Ralpha2 and EphA2 Receptor in GBM 862
35.1 Molecularly Targeted Recombinant Cytotoxins for the Treatment of Brain Tumors 863
35.2 Targetable Molecular Fingerprints in GBM 865
35.2.1 Overexpression of IL-13Ralpha2 in GBM 865
35.2.2 Targeting IL-13Ralpha2 for Therapeutic Purposes 867
35.2.3 EphA2 Receptor in GBM 869
35.2.3.1 EphA2 Protein Expression in GBM Cells and Tumors 870
35.2.3.2 Function of EphA2 in GBM 872
35.2.3.3 Targeting EphA2 in GBM with EphrinA1-Based Cytotoxins 872
35.3 Summary 874
References 874
Molecular Targets for Antibody-Mediated Immunotherapy of Malignant Glioma 879
36.1 Introduction 879
36.2 Brain-Tumor Targets and Immunotherapeutic Antibodies 883
36.2.1 Tenascin 883
36.2.2 Epidermal Growth Factor Receptor and Its Variant III Form 890
36.2.3 Chondroitin Sulfate Proteoglycans 893
36.2.4 Other Molecular Targets of Interest 895
36.2.4.1 Gangliosides 895
36.2.4.2 Glycoprotein Nonmetastatic Melanoma Protein B 895
36.2.4.3 Multidrug Resistance Protein 3 897
36.2.4.4 Podoplanin 897
36.2.4.5 Neural Cell Adhesion Molecule 898
36.2.4.6 Vascular Endothelial Growth Factor 899
36.3 Perspective 899
36.4 Conclusion 901
References 902
Stat3 Oncogenic Signaling in Glioblastoma Multiforme 913
37.1 Introduction 914
37.2 Biology of Malignant Gliomas 915
37.3 Activated Stat3 Acts as an Oncoprotein 917
37.4 Stat3 Signaling Is Activated in GBM and Other Brain Tumors 917
37.5 Activated Stat3 Induces Proliferation and Survival of GBM Cells 918
37.6 Proangiogenic Activity of Stat3 in GBM 920
37.7 Immune Suppression by Stat3 in GBM 921
37.8 Antitumor Activity of Stat3 in GBM 922
37.9 Physiologic and Pharmacologic Inhibitors of Stat3 923
37.10 Perspectives 925
References 925
Inhibition of Ras Signaling for Brain Tumor Therapy 933
38.1 Introduction 934
38.2 p21-Ras Structure and Processing 934
38.3 Activation and p21-Ras Signaling 937
38.4 Mutated and Activated p21-Ras in Brain Tumors 938
38.5 Farnesyltransferase Inhibitors (FTIs) and Preclinical Studies 939
38.6 Alternative Methods to Target p21-Ras Signaling 941
38.7 p21-Ras Signaling in Non-glioma CNS Tumors 942
38.8 Conclusion 942
References 943
HGF/c-Met Signaling and Targeted Therapeutics in Brain Tumors 947
39.1 Introduction 948
39.2 c-Met and HGF Structure and Signal Transduction 948
39.2.1 Structure of HGF and c-Met 948
39.2.2 c-Met-Dependent Signal Transduction 949
39.3 Involvement of HGF/c-Met in Brain Tumors 951
39.3.1 Deregulation of HGF and c-Met in Brain Tumors 951
39.3.1.1 Mechanisms of HGF and c-Met Deregulation in Brain Tumors 951
39.3.1.2 HGF and c-Met Expression in Brain Tumors 952
39.3.1.3 HGF and c-Met Expression in Brain Tumor Endothelial Cells 953
39.3.2 Oncogenic Effects of c-Met Activation in Brain Tumors 953
39.3.2.1 Cell Proliferation 953
39.3.2.2 Cell Survival 954
39.3.2.3 Cell Migration and Cell Invasion 955
39.3.2.4 Angiogenesis 955
39.4 HGF and c-Met as Targets for Brain Tumor Therapy 956
39.4.1 U1snRNA/Ribozymes and Antisense 957
39.4.2 NK4 958
39.4.3 Soluble Met 959
39.4.4 Small-Molecule Inhibitors 959
39.4.5 Neutralizing Monoclonal Antibodies 960
39.5 Therapeutic Considerations 962
References 962
Combinatorial Therapeutic Strategies for Blocking Kinase Pathways in Brain Tumors 967
40.1 Introduction: From Single Genes to Biological Networks 968
40.2 Robustness in Oncogenic Signaling Networks 968
40.2.1 The Akt-mTOR Feedback Loop 969
40.2.2 EGFRvIII-PTEN Connection 971
40.2.3 The RAS-PI3K Crosstalk 972
40.3 Tools to Survey Signaling Networks in GBM 973
40.3.1 Revealing Novel Network Connections Through Mass Spectrometry 973
40.3.2 Understanding Chemoresistance Through the Use of Antibody Microarrays 975
40.3.3 Multiparameter Flow Cytometry as a Tool for Determining Oncogenic Networks in Cancer Stem Cell Populations 976
40.4 Combinatorial Targets from GBM Signaling Networks Through Integrative Analysis 977
40.5 Mechanistic Models and Computational Approaches to Drug Targets 980
40.6 Bench to Bedside - Can Integrative Strategies Be Extended to the Clinic? 981
40.7 Conclusions 983
References 984
Targeting of TRAIL Apoptotic Pathways for Glioblastoma Therapies 990
41.1 Introduction 991
41.2 Development of TNF Family Death Receptors Targeted Cancer Therapies 992
41.2.1 Toxicity in TNFR and Fas-Targeted Therapies 992
41.2.2 Controversy in TRAIL-Induced Toxicity 993
41.3 TRAIL-Induced Apoptotic Pathways in Human Cancer Cells 994
41.3.1 TRAIL-Induced DISC and Extrinsic Apoptotic Pathway 994
41.3.2 TRAIL-Induced Intrinsic Apoptotic Pathway 995
41.3.3 Caspase-8 in TRAIL-Induced Apoptosis 996
41.3.4 TRAIL-Induced Apoptosis in Glioblastoma Cells 996
41.4 TRAIL Resistance in Human Cancers 997
41.4.1 Decoy Receptors 997
41.4.2 DISC Modifications 998
41.4.3 NF-kappaB and ERK1/2 Pathways 999
41.4.4 Bcl-2 and IAP Family Proteins 1000
41.4.5 Cancer Genomics 1000
41.4.6 TRAIL Resistance in Glioblastomas 1001
41.5 Development of TRAIL-Based Combination Therapies 1002
41.5.1 Targeting of TRAIL Resistance in the DISC and Mitochondrial Pathway 1002
41.5.2 Targeting Oncogene-Driven Signaling Pathways 1003
41.5.3 Combination of TRAIL and Chemotherapy 1003
41.5.4 TRAIL-Based Combination Therapies for Glioblastomas 1004
41.6 Clinical Development of TRAIL Agonists for Cancer Therapies 1005
41.6.1 Clinical Trials of rhTRAIL 1005
41.6.2 Clinical Trials of DR4 and DR5 Agonistic Antibodies 1006
41.7 Development of TRAIL-Based Treatments of Glioblastomas 1007
41.7.1 TRAIL-Based Therapeutic Modalities 1008
41.7.2 Evaluation of Patient Glioblastomas in TRAIL-Based Treatments 1009
41.8 Conclusions and Future Directions 1009
References 1010
The NF-kappaB Signaling Pathway in GBMs: Implications for Apoptotic and Inflammatory Responses and Exploitation for Therapy 1023
42.1 NF-kappaB Family and Signaling Pathway 1024
42.2 NF-kappaB and Angiogenesis 1027
42.3 NF-kappaB and Cell Migration and Invasion 1028
42.4 NF-kappaB and Cellular Proliferation 1028
42.4.1 Cyclin D1, E, and CDK2 1028
42.4.2 c-Myc 1029
42.4.3 Interleukin-6 1029
42.5 NF-kappaB and Apoptosis 1030
42.6 Activation of NF-kappaB in Gliomas 1033
42.6.1 Immune Cell Infiltration 1033
42.6.2 The PI3K Pathway 1034
42.6.3 ING4 1034
42.6.4 Pin1 1035
42.6.5 PIAS Family 1036
42.6.6 Alternative Reading Frame (ARF) 1036
42.6.7 DNA Damage and Reactive Oxygen Species (ROS) 1036
42.7 Targeting NF-kappaB in Gliomas 1037
42.7.1 Proteasome Inhibitors 1038
42.7.2 IKK Inhibitors 1039
42.7.3 Antioxidants 1040
42.8 Conclusions 1041
References 1041
Targeting Endoplasmic Reticulum Stress for Malignant Glioma Therapy 1049
43.1 Introduction 1050
43.2 ER Stress Response (ESR) 1050
43.3 Downregulation of the ER Chaperone GRP78 Results in Increased Glioma Cell Sensitivity to Temozolomide (TMZ) 1053
43.4 ER Stress Modulation of Intracellular Calcium in Malignant Gliomas 1055
43.5 Induction of ER Stress by Affecting Protein Balance in the ER 1058
43.6 Combination Therapy by Affecting Multiple Targets Within the ER 1060
43.7 Potential Clinical Applications of ER Stress Modulation in Malignant Glioma Treatment 1061
43.8 Conclusion 1064
References 1064
Brain Cancer Stem Cells as Targets of Novel Therapies 1069
44.1 Introduction 1070
44.2 Defining Cancer Stem Cells 1070
44.3 Signaling Pathways as Drug Targets in Cancer Stem Cells 1071
44.3.1 Epidermal Growth Factor and PI(3)K Signaling 1072
44.3.2 Hedgehog Signaling 1073
44.3.3 Bone Morphogenic Protein Signaling 1074
44.3.4 Notch Signaling 1074
44.3.5 Platelet-Derived Growth Factor Signaling 1074
44.3.6 Additional CSC Regulators 1074
44.4 Targeting the Perivascular Stem Cell Niche 1075
44.5 Cancer Stem Cells and Niches in Therapeutic Resistance 1077
44.5.1 Cancer Stem Cells Are Resistant to Conventional Therapy 1077
44.5.2 Cancer Stem Cells Express High Levels of ABC Drug Transporters 1077
44.5.3 Cancer Stem Cells Have Augmented DNA Damage Repair Capacity 1078
44.5.4 The Perivascular Niche Contributes to Cancer Stem Cell Resistance to Therapy 1078
44.6 Cancer Stem Cells as Markers of Prognosis 1079
44.7 Imaging of Cancer Stem Cells 1079
44.8 Perspectives 1080
44.9 Summary 1081
References 1081
The Use of Retinoids as Differentiation Agents Against Medulloblastoma 1088
45.1 Introduction-Medulloblastoma (MB) as a Lapse of Proper Development 1089
45.1.1 Normal Cerebellum Development 1090
45.1.2 Mice with Dysregulated Shh Signaling Develop Desmoplastic/Nodular MB 1091
45.1.3 Wnt Pathway Activation in Classic MBs 1091
45.1.4 Notch Amplification and Overexpression in MBs 1092
45.1.5 OTX2 Amplification and Overexpression in Anaplastic MBs 1092
45.2 Endogenous Retinoid Function 1093
45.2.1 An Introduction to Retinoid Metabolism and Signal Regulation 1093
45.2.2 Retinoids Function by Activating Ligand-Activated Transcription Factors 1093
45.2.3 Endogenous Function of Retinoids During Embryonic Development 1094
45.2.4 A Focus upon ATRA Function in Cerebellar Development 1095
45.3 Therapeutic Application of Retinoids 1096
45.3.1 A Link Between Vitamin A Deficiency and Cancer 1096
45.3.2 Clinical Application of Retinoids 1097
45.3.3 Mechanisms of Retinoid Antitumor Activity 1098
45.3.4 Retinoid Therapy Targets Pathways Implicated in MB Tumorigenesis 1099
45.3.4.1 Variability of Retinoid Responsiveness Among MB Cell Lines Resulted in Disproportionately Negative Results in Early Studies 1101
45.3.4.2 ATRA Can Induce Reversible Differentiation and Chemosensitize MB Cells 1101
45.3.4.3 ATRA Can Introduce a Cell Cycle Blockade in an MB Cell Line 1102
45.3.4.4 Identifying a Predominantly Apoptotic Response to ATRA in Some MB Cell Lines 1102
45.3.4.5 Bmp2 Is a Functional Downstream Target of Retinoid Treatment in MB Cell Lines and Surgically Derived Primary Tumors 1103
45.3.4.6 ATRA Treatment Silences the Oncogene OTX2, Which Is Distinctly Expressed in Retinoid-Sensitive Cell Lines 1104
45.3.4.7 Development of Retinoid-Based Therapeutic Strategies in Preclinical Models 1105
45.3.4.8 A Synthetic Retinoid, Fenretinide, Induces Apoptosis in MBs via an RAR-Independent Effect 1106
45.3.4.9 Overview of Known Retinoid Targets in MB 1106
45.3.4.10 Strategies to Identify Mechanisms of Retinoid Resistance in MB Cell Lines 1107
45.3.4.11 Clinical Trials Utilizing Retinoid Treatment for MB 1108
45.4 Overview of Retinoid-Mediated Differentiation Therapy of MB 1108
References 1109
Herpes Simplex Virus 1 (HSV-1) for Glioblastoma Multiforme Therapy 1116
46.1 Introduction 1117
46.2 Basic Biology of HSV-1 1118
46.2.1 HSV-1 Structure and Genome 1118
46.2.2 HSV-1 Cell Entry 1119
46.2.3 HSV-1 Pathogenesis 1121
46.2.4 HSV-1 Gene Expression 1121
46.2.5 HSV-1 Latency 1122
46.2.6 HSV-1 Immediate-Early (IE) Proteins 1123
46.2.7 HSV-1 DNA Replication and Recombination 1124
46.2.8 HSV-1 Assembly and Release 1124
46.3 HSV-1 as a Gene Therapy Vector Against Malignant Gliomas 1125
46.3.1 HSV-1 Replication-Defective Mutants 1125
46.3.1.1 Generation of Replication-Deficient HSV-1 Viruses 1125
46.3.1.2 Replication-Defective HSV-1 in Malignant Glioma Therapy 1126
46.3.2 HSV-1 Replication-Conditional (Oncolytic) Viruses 1127
46.4 Combination Therapies with HSV-1 for Malignant Gliomas 1128
46.4.1 HSV-1 d106-Mediated Chemoradiosensitivity Enhancement in GBM 1129
46.4.1.1 ICP0 and Effects on Cell Metabolism 1130
46.5 Clinical Trials with HSV-1 Based Viruses for Malignant Glioma Therapy 1131
46.6 Limitations in the Treatment of Malignant Gliomas with HSV-Mediated Therapy 1133
46.6.1 Delivery 1133
46.6.2 Host Immune Response 1134
46.6.3 Safety 1134
46.7 Perspectives 1135
46.7.1 Tumor Targeting of HSV-1 1135
46.7.2 Chemo/Radiotherapy-Activated Transcriptional Targeting of Malignant Gliomas 1136
46.7.3 Imaging 1136
46.8 Summary 1136
References 1137
The Development of Targeted Cancer Gene-Therapy Adenoviruses for High-Grade Glioma Treatment 1148
47.1 Historic Background 1149
47.2 The Ad as a Cancer Therapy Agent 1149
47.2.1 Replication-Deficient Ads 1150
47.2.2 Tumor-Specific Replication-Competent Ads 1151
47.2.3 Advantages and Disadvantages of Using the Ad as a Cancer Therapy Agent 1154
47.3 Clinical Trials of Cancer Therapy Ads for Glioma Therapy 1155
47.3.1 Ad-HSV-TK Clinical Trials 1155
47.3.2 Ad-p53 Clinical Trial 1159
47.3.3 Ad-IFNbeta Clinical Trial 1159
47.3.4 E1B-55K-Deleted Oncolytic Ad (dl1520, ONYX-015) Clinical Trial 1160
47.3.5 Clinical Trial Data: Anti-Ad Neutralizing Antibody Levels 1160
47.3.6 Clinical Trial Data: Regional and Systemic Virus Dissemination 1161
47.3.7 Clinical Trial Data: Antitumor Efficacy 1161
47.4 Future Directions to Improve the Safety and Efficacy of Cancer Gene-Therapy and Oncolytic Ads for Glioma Therapy 1162
47.4.1 Preclinical Brain Tumor Models 1162
47.4.2 Improving the Virus Vectors 1164
47.4.3 Improving Virus Delivery, Intratumoral Dispersion, and Transduction of Tumor Cells 1165
47.4.4 Local and Systemic Host Immune Response 1166
47.4.5 Tracking Viral Replication in the Patient 1167
47.5 Summary 1168
References 1168
Harnessing T-Cell Immunity to Target Brain Tumors 1176
48.1 Introductory Remarks 1177
48.2 Immune Privilege and Cancer Immunosurveillance 1177
48.3 The Stages of Tumor Immunity 1178
48.3.1 The Tumor First Stimulates Innate Immune Sentinels, at the Site of the Malignancy 1179
48.3.1.1 Detection 1179
48.3.1.2 Innate Immune Functions 1180
48.3.2 The Induction of Adaptive Immune Responses Against Brain Tumors: From the Brain to the Lymph Node 1181
48.3.2.1 Generation of Naïve CD4 and CD8 T Cells 1181
48.3.2.2 Naïve T-Cell Activation Requires Two Signals 1182
48.3.2.3 How Does Antigen from the Tumor Site Reach the Naïve T Cells in the Lymph Node? 1183
48.3.2.4 Cell-Free Drainage of Antigen 1184
48.3.2.5 Cell-Mediated Transport of Antigen from the Brain to the Lymph Node 1184
48.3.3 The Effector Phase of the T-Cell Mediated Antitumor Response: From the Lymph Node to the Brain 1185
48.3.3.1 T-Cell Entry to the Brain and Antigen Specificity 1185
48.3.3.2 Antigen-Independent T-Cell Extravasation to the Brain 1186
48.3.3.3 Role of Integrins in CNS Tropism 1187
48.3.3.4 Role of Non-integrin Adhesion Molecules 1187
48.3.3.5 Role of Chemokines and Chemokine Receptors 1188
48.3.3.6 Suboptimal Trafficking of T Cells to Brain Tumors May Lead to Suboptimal Tumor Therapies 1189
48.3.4 The Effector Phase of the T-Cell Mediated Antitumor Response: At the Tumor Site 1190
48.3.4.1 CD8 T Cells 1190
48.3.4.2 CD4 T Cells 1191
48.4 Glioma Immune Escape 1191
48.4.1 Passive Immune Escape Mechanisms 1192
48.4.2 Active Immune Escape 1192
48.4.2.1 Soluble Immunosuppresive Molecules 1193
48.4.2.2 Cell Surface Immunosuppressive Factors 1193
48.4.2.3 Immunosuppressive Cells 1194
48.5 Identification of Glioma-Associated Antigens 1195
48.5.1 Identifying Tumor-Associated-Antigens (‘‘Reverse Immunology’’) 1195
48.5.2 Microarray Technology and Tumor-Associated-Antigens 1196
48.6 Preclinical Studies of T-Cell Immunity to Target Brain Tumors 1197
48.6.1 Passive Immunotherapy 1197
48.6.1.1 Adoptive Transfer 1197
48.6.1.2 Cytokines 1198
48.6.1.3 Toll- Like Receptor Agonists 1198
48.6.2 Active Immunotherapy (Tumor Vaccines) 1198
48.6.2.1 Dendritic Cell-Based Vaccines 1199
48.6.2.2 Adjuvants 1200
48.6.2.3 Blocking Regulatory T Cells (Tregs) 1200
48.6.2.4 Immune Gene Therapy 1201
48.6.2.5 Bacterial/Viral-Based Vaccines 1201
48.7 Clinical Trials of Cellular Immunotherapy for Brain Tumors 1202
48.7.1 Lymphokine-Activated Killer Cells 1202
48.7.2 Cytotoxic T Lymphocytes 1202
48.7.3 Dendritic Cell Vaccination Trials 1203
48.7.4 Bacterial and Viral Tumor Vaccine Trials for Malignant Glioma 1207
48.8 Conclusion 1208
References 1215
Glioma Invasion: Mechanisms and Therapeutic Challenges 1229
49.1 Introduction 1230
49.2 Overview of Glioma Cell Invasion in the CNS 1230
49.3 Glioma Cell Microenvironment: Extracellular Matrix 1235
49.3.1 Neural ECM 1235
49.3.2 Basal Lamina 1239
49.4 Extracellular Remodeling and Glioma Invasion 1240
49.4.1 ECM Degradation 1240
49.4.2 ECM Synthesis 1244
49.5 Soluble Signals and Transduction Mechanisms in Glioma Invasion 1247
49.5.1 Chemoattractants 1247
49.5.2 Chemorepellents 1249
49.6 Targeting Strategies Against Glioma Cell Invasion 1250
References 1254
Index 1263