From Molecular to Modular Tumor Therapy: (eBook)

From Molecular to ModularTumor Therapy 3
Contents 5
Part I:Therapy-Derived Systems Biology:A Pragmatic Communication Theory 9
Chapter 1: Bridging Theory and Therapeutic Practice: From Generalized Disease Models to Particular Patients 10
1.1 Introduction 11
Chapter 2: Tumor Systems Need to be RenderedUsable for a New Action-Theoretical Abstraction:The Starting Point for Novel Therapeutic Options 15
2.1 Explorative Considerations (The ‘Now’) 16
2.2 Methodological Approach 17
2.2.1 Theory of Communicative Interactions in Tumor Compartments 17
2.2.2 Structural Differentiation 17
2.2.3 Rationalization 18
2.2.4 Deformation 19
2.2.5 Resulting Observation Levels 19
2.2.6 Approach to an Action-Theoretical Systems Term: The Scientist as a Subject of the System 20
2.2.7 Tumor Systems Need to be Rendered Useable for a New Action-Theoretical Abstraction 20
2.2.8 Assignment of Systems-Theoretical and Action-Theoretical Inconsistencies 20
2.3 Conceptual Equipment 21
2.3.1 Sensitive Assessment Tools 23
2.3.2 Action-Oriented Research Approaches: Broadening of the Therapeutic Spectrum (Individualized Therapy) 26
2.4 Discussion: Critical Reflection on Tumor Systems Biology (The ‘Then’) 28
References 31
Chapter 3: Principles of Modular Tumor Therapy 35
3.1 Introduction 36
3.2 Methods: A Formal-Pragmatic Communication Theory 38
3.2.1 Definition of the Tumor’s Living World as a Holistic Communicative Unit 38
3.2.2 Situative Objectivation of the Tumor’s Living World 39
3.2.3 Formal-Pragmatic Theory About Denotation of a Communication Process 40
3.2.4 Perception of Validity 40
3.2.5 Novel Idealizations: Therapeutically Relevant Redemption of Validity 41
3.3 Implementation of the Formal-Pragmatic Communication Theory 42
3.3.1 Clinical Results Supporting a Formal-Pragmatic Communication Theory 42
3.3.2 Translation of Clinical Results in a Formal Communication Theory 43
3.3.3 Explication of a Formal-Pragmatic Communication Theory 44
3.4 Discussion 48
3.4.1 Glossary 50
3.4.1.1 Co-option 50
3.4.1.2 Evolvability 50
3.4.1.3 Modularity 50
3.4.1.4 Modular Communication (Therapies) 51
3.4.1.5 Risk-Absorbing Background Knowledge 51
3.4.1.6 Tumor’s Living World 51
3.4.1.7 Reconstruction of Tumor-Associated Systems 51
3.4.1.8 Robustness 51
3.4.1.9 Separated or Separating ‘Social’ Tumor Systems 52
References 52
Part II:Tumors Share Common Processes DuringTumor Evolution: Communicative Aspectsof a Situation’s Interpretation for CreatingSystems-Directed Therapies 54
Chapter 4: Cancer and Coagulation Focusing on Tissue Factor and Heparanase55
4.1 Introduction 56
4.2 Tissue Factor (TF) 57
4.2.1 TF Structure and Expression 57
4.2.2 TF and the Coagulation System 57
4.2.3 Increased TF Expression in Tumors 59
4.2.4 TF and Angiogenesis 59
4.2.5 TF Signaling 60
4.2.6 Blood-Borne TF 60
4.3 Thrombin 61
4.4 Tissue Factor Pathway Inhibitor (TFPI) 62
4.4.1 TFPI Structure and Expression 62
4.4.2 TFPI in Blood and Cells 63
4.5 Heparanase 63
4.5.1 Heparanase Structure 63
4.5.2 Pro-angiogenic Properties 64
4.5.3 Pro-metastatic Properties 65
4.5.4 Non-enzymatic Functions 66
4.5.5 Hematopoetic Cells and Heparanase 66
4.5.6 Inhibition of Heparanase by Heparins 66
4.5.7 Heparanase and TF 67
4.5.8 Heparanase and TFPI 68
4.5.9 A Model for Interaction Between Heparanase, TF, and TFPI 69
References 70
Chapter 5: The Role of Mesenchymal Cells in Cancer: Contribution to Tumor Stroma and Tumorigenic Capacity 79
5.1 Introduction 79
5.2 Current Status of Pre-clinical Attempts and Clinical Trials Using Isolated MSCs 82
5.3 Homing and Engraftment of MSCs Following Transplantation 84
5.4 MSCs as a Double-Edged Sword: Do They Support Tumor Cell Growth or Are They Safe for Use in Tumor Ablation? 85
5.4.1 MSCs in Tumor Promotion 86
5.4.2 MSCs in Tumor Inhibition 87
5.5 MSCs as Tumor-Initiating Cells: Does MSC Transplantation Pose a Threat in Terms of Cancer Formation? 88
5.5.1 In Vitro Senescence of MSCs 89
5.5.2 Aneuploidy and Chromosomal Aberrations in Cultured MSCs 90
5.5.3 MSC Tumorigenicity 91
5.6 Possible Mechanisms Underlying MSC Tumorigenicity: Chromosomal Instability – Culprit or Savior? 92
5.7 Summary 94
References 95
Chapter 6: Shaping Tumor Associated Macrophages: The Role of NF-kB 101
6.1 Introduction 101
6.2 Macrophage Polarisation 102
6.3 Tumor Associated Macrophages: An Alternative Macrophage Phenotype 103
6.4 The NF-kB Signaling Pathway 104
6.5 NF-k.B and Macrophage Polarization 107
6.6 Crosstalk Between Hypoxia Inducible Factor and NF-k.B 110
6.7 Concluding Remarks 111
References 111
Chapter 7: The Metabolic Achilles Heel: Tumor Cell Metabolism as Therapeutic Target 115
7.1 Tumor Glucose Metabolism: The Warburg Phenotype 115
7.2 Amino Acid Metabolism in Cancer: Increased Glutaminolysis and Expression of IDO and Arginase in the Tumor Environment 117
7.3 Alterations in Tumor Lipid Metabolism: COX Expression and Ganglioside Production 118
7.4 Adenosine Accumulation in the Tumor Environment 119
7.5 Molecular Background of Metabolic Alterations in the Tumor Environment 120
7.5.1 Oncogenic Transformation and Hypoxia Lead to Metabolic Alterations 120
7.6 Impact of Tumor Metabolism on Immune Cell Function 121
7.7 Tumor-Derived Lipids Suppress Immune Cell Activity 123
7.8 Immunosuppression by Adenosine 123
7.9 Tumor Metabolism as Therapeutic Target 124
7.10 Inhibition of Tumor Glycolysis 124
7.11 Targeting the Glucose Uptake 125
7.12 Acceleration of the Mitochondrial Activity 125
7.13 Modulation of Tumor Lipid Metabolism 125
7.14 Rescuing Anti-tumor Immune Response 126
7.15 Summary and Concluding Remarks 127
References 127
Chapter 8: Could Be Systems-Directed Therapy Approaches Promising in Glioblastoma Patients? 137
8.1 The Target: Glioblastoma 138
8.2 Therapy Resistance in Glioblastoma 138
8.3 Insufficient Activity of Targeted Agents in Monotherapy 138
8.4 Glioblastomas’ Intrinsic Resistance 139
8.5 Resistance Induced by Treatment 139
8.6 Consequences of Therapy Resistance 139
8.7 Systems Biology in Glioblastoma 140
8.8 Pathophysiology of Glioblastoma as Therapeutic Target 140
8.9 Glioblastoma Cells with Stem Cell Function 141
8.10 The Glioblastoma Stem Cell Niche 143
8.11 Key Regulators of the Tumor Niche 144
8.12 Tumor Metabolism 144
8.13 Tumor-Associated Inflammation in GBM 145
8.14 Proliferation Behavior 145
8.15 Invasion 146
8.16 Angiogenesis 146
8.17 Local Immunosuppression 147
8.18 Pathophysiology-Based Therapy in Glioblastoma 147
8.18.1 Diagnostics Promoting Systems Comprehension 147
8.19 Targeting the Invasive Feature 149
8.20 Targeting Angiogenesis 149
8.21 Targeting Immunosuppressive Features 150
8.22 Multi-Targeted Treatment 151
8.23 Approaches for Personalizing GBM Therapy 152
8.24 Outlook 152
References 153
Part III:Systems-Relevant Molecularand Cellular Targets: Implementationof Modular ‘Knowledge’ 162
Chapter 9: Functional Impacts of Signal Integration:Regulation of Inflammation-Related Transcription Factors by Heterotrimeric G Proteins 163
9.1 Introduction 166
9.2 G protein-Mediated NFkB Regulation in Inflammation and Cancer 167
9.3 The Modulation of STAT Activity by Heterotrimeric G Proteins 172
9.4 Interaction Between NF-kB and STAT3 in Inflammatory Responses 176
9.5 Other Transcription Factors Regulated by Heterotrimeric G Proteins 176
9.6 Functional Impacts of Signal Integration 181
9.7 Future Perspectives 182
References 182
Chapter 10: Molecular Cross-Talk Between Nuclear Receptors and Nuclear Factor-kB 192
10.1 Introduction 195
10.2 Nuclear Factor-kB (NF-kB): A Central Player 196
10.3 Nuclear Receptors: The Road to Relief 199
10.3.1 NF-kB and the Glucocorticoid Receptor, GR 203
10.3.1.1 Transactivation of Promoters of Inflammation-Repressing Proteins 203
10.3.1.2 Destabilization of Pro-inflammatory Gene mRNA 205
10.3.1.3 Transrepression of NF-kB-Dependent Gene Expression 206
Direct GR:NF-kB Association 206
Modulation of Activational NF-kB Signalling Cascades 207
GR Targeting the Enhanceosome 209
10.3.2 NF-k.B and the Peroxisome Proliferator-Activated Receptors, PPAR 211
10.3.3 NF-k.B and Liver X Receptor, LXR 214
10.3.4 NF-k.B and the Estrogen Receptor, ER 214
10.3.5 NF-k.B and the Androgen Receptor, AR 217
10.3.6 NF-k.B and the Progesterone Receptor, PR 218
10.3.7 NF-k.B and the RARs, RXRs, RORs 219
10.3.8 NF-k.B and the Thyroid Hormone Receptor, TR 220
10.3.9 NF-k.B and the Vitamin D Receptor, VDR 220
10.3.10 NF-k.B and Other Nuclear Receptors 221
10.4 Conclusions 224
References 224
Chapter 11: The Biomodulatory Capacities of Low-Dose Metronomic Chemotherapy: Complex Modulation of the Tumor Microenvironment 244
11.1 Introduction 245
11.2 Conventional Chemotherapy: Beyond Cytotoxic Effects 245
11.3 Low-Dose Metronomic Chemotherapy 247
11.3.1 Principles 247
11.3.2 Clinical Applications 249
11.4 Low-Dose Metronomic Chemotherapy: Beyond Antiangiogenic Effects 250
11.4.1 Hypoxia-Inducible Factor 1a Inhibition 251
11.4.2 TSP-1 Induction 252
11.4.3 Immunomodulation 252
11.4.4 Lack of Pro-Thrombotic Activity 253
11.5 Low-Dose Metronomic Chemotherapy: The Pharmacogenetic Perspective 253
11.5.1 How to Integrate Pharmacogenetic Investigations into Metronomic Phase II/III Clinical Trials? 254
11.5.2 What Is the Most Effective Pharmacogenetic Strategy to be Used? 254
11.5.3 How to Decide About Candidate Genes to be Investigated? 254
11.6 Outlook 255
References 256
Part IV:Tumors are Evolvable Modularand Rationalized Systems: FromMolecular to Modular Tumor Therapy 264
Chapter 12: Systems Biology: A Therapeutic Target for Tumor Therapy 265
12.1 Introduction 266
12.2 Patients and Methods 267
12.2.1 Selection of Metastatic Diseases 267
12.2.2 Patients’ Characteristics 269
12.2.3 Basic Treatment Considerations 269
12.2.4 Anti-Inflammatory Therapies 269
12.2.5 Angiostatic Therapies 270
12.3 Systems Biology: A Therapeutic Target for Tumor Therapy 270
12.3.1 Treatment Schedules 270
12.3.2 Combined Targeting of Wound Healing Processes 271
12.4 Pre-Treatment Evaluation Is Indicated in the Respective Publications 271
12.4.1 Evaluation of Efficacy 271
12.5 Modulation of Tumor-Associated Disease Traits 271
12.5.1 ECOG Status: ECOG Performance Status Was Routinely Monitored 271
12.5.2 Metastatic Sites 272
12.5.3 Statistics and Data Analysis 272
12.6 Results 272
12.7 Tailored Modeling of Tumor-Associated Disease Traits 274
12.7.1 ECOG Performance Status 274
12.7.2 Paraneoplastic Syndromes 275
12.7.3 Serum CRP Level in Follow-Up 275
12.7.4 Impact of Anti-inflammatory Therapy 275
12.7.5 Intensification of Anti-inflammatory Therapy 276
12.7.6 Combined Transcriptional Modulation 276
12.7.7 Angiostatic Therapy 276
12.7.8 Metastatic Sites and Response 277
12.7.9 Metastatic Sites at Progression 277
12.8 Safety Profile 277
12.9 Discussion 278
References 283
Chapter 13: The Comparative Uncovering of Tumor Systems Biology by Modularly Targeting Tumor-Associated Inflammation 286
13.1 Introduction 287
13.2 Methods 290
13.2.1 Tumor-Specific and Stage-Specific Therapeutic Accessibility of Inflammation-Related Processes 292
13.2.2 Statistics and Data Analysis 293
13.3 Results 293
13.3.1 CRP Response as Predictor for Clinical Tumor Response 294
13.4 Discussion 297
13.4.1 Systems Rationalization and Inter-systemic Exchange Processes 298
13.4.2 The Systems Biology of a Tumor: An Independent Feature at a Distinct Stage? 300
References 302
Chapter 14: Searching for the ‘Metabolism’ of Evolution 303
14.1 Letter 303
References 307
Part V:Biomodulatory Therapy Approachesin Metastatic Cancer 308
Chapter 15: The Impact of Inflammation Control and Active Cancer Palliation on Metabolic Pathways Determining Tumor Progressio and Patient Survival* 309
15.1 Introduction 310
15.1.1 Tumor–Host Interaction 310
15.1.2 Cancer Cachexia 311
15.1.2.1 Prostaglandin Biosynthesis 311
15.1.3 Prostanoid Related Effects in Tumor Bearers 314
15.1.3.1 Inflammation and Tumor Growth 314
15.1.3.2 Prostanoids and Metabolic Alterations 314
15.1.3.3 Tumor Angiogenesis 316
15.1.4 Inflammatory Mediators in Colon Cancer 317
15.1.5 Prostanoids and Immunological Tumor Alterations 322
15.1.6 Anti-Inflammatory Therapy 324
References 326
Chapter 16: Pioglitazone and Rofecoxib Combined with Angiostatically Scheduled Capecitabine in Far-Advanced Hepatobiliary Carcinoma 337
16.1 Introduction 338
16.2 Patients and Methods 338
16.2.1 Patients’ Characteristics 338
16.2.2 Treatment 338
16.2.3 Evaluation of Efficacy and Safety 339
16.2.4 Pre-treatment Evaluation and Follow-Up 339
16.2.5 Statistics and Data Analysis 340
16.3 Results 340
16.3.1 Patients 340
16.3.2 Antitumor Activity 340
16.3.3 Progression-Free Survival (PFS) 342
16.3.4 Pre-treatment with Pioglitazone and Rofecoxib 344
16.3.5 Response Characteristics 344
16.3.6 Survival 344
16.3.7 Tolerability and Safety 344
16.4 Discussion 346
References 347
Chapter 17: C-Reactive Protein As a Secretome-Derived Biomarker for Predicting Response to Biomodulatory Therapy in Metastatic Renal Clear Cell Carcinoma 349
17.1 Introduction 350
17.2 Patients and Methods 351
17.3 Eligibility 351
17.4 Pre-treatment Evaluation 352
17.5 Treatment 352
17.6 Efficacy Assessment 352
17.7 Dosage Modification 353
17.8 Statistical Considerations 353
17.9 Results 353
17.9.1 Patients’ Characteristics 353
17.10 Treatment 355
17.11 Treatment Efficacy 355
17.12 CRP Response 358
17.13 Tolerability and Safety 358
17.14 Discussion 360
References 361
Chapter 18: Modular Therapy Approach in Metastatic Castration-Resistent Prostate Cancer 363
18.1 Introduction 364
18.2 Patients and Methods 365
18.3 Results 367
18.4 Biochemical and Objective Responses 369
18.5 PFS and Overall Survival 370
18.6 Toxicity 370
18.7 Discussion 371
References 372
Chapter 19: Systems-Directed Therapy in Metastatic Castration-Resistent Prostate Cancer (CRCP) 374
References 377
Part VI:Criteria for Checking SystemsBehavior and Creating Predictions:Systems-Associated Biomarkersand Molecular Imaging 378
Chapter 20: Early Detection of Systems Response: Molecular and Functional Imaging of Angiogenesis 379
20.1 Introduction 380
20.2 Vascular Volume Fraction, Tumor Perfusion, Vessel Permeability and Vessel Maturation 382
20.2.1 PET and SPECT 382
20.2.2 Computed Tomography 382
20.2.3 Magnetic Resonance Imaging 383
20.2.4 Vessel Size Imaging 385
20.2.5 Ultrasound Imaging 386
20.3 Molecular Imaging 387
20.3.1 (Bimodal) Molecular MRI Probes 388
20.3.2 Ultrasound (US) 389
20.3.3 PET and SPECT 391
20.3.4 Optical Imaging (OI) 393
20.4 Outlook 394
References 395
Chapter 21: Secretome Proteomics, a Novel Tool for Biomarkers Discovery and for Guiding Biomodulatory Therapy Approaches 398
21.1 Introduction 399
21.1.1 The Proteome 399
21.1.2 Clinical Proteomics 399
21.1.3 Metastasis and Tumor Microenvironment 400
21.2 Biomarker 401
21.2.1 Definition 401
21.2.2 Biomarker in Cancer 401
21.2.3 Stages of Biomarker Development 402
21.2.4 Proteomic Technology in Biomarker Discovery 402
21.3 Secretome as Reservoir for Biomarker Discovery 403
21.3.1 Definition 403
21.3.2 The Cancer Secretome 403
21.3.3 Development of Rational Therapy Design by Secretome Analysis 404
21.3.4 Clinical Application 406
21.4 Methods 407
21.4.1 2D-gel Electrophoresis 407
21.4.2 Mass Spectrometry 409
21.5 Bioinformatics 411
21.6 Identification of Biomarker Candidates by Secretome Analysis 416
21.7 Conclusion 419
References 422
Part VII:Pharmacological Considerationson Systems Biological Therapy Approaches 458
Chapter 22: Cyclooxygenase 2 (COX2) and Peroxisome Proliferator-Activated Receptor Gamma (PPARG) Are Stage-Dependent Prognostic Markers of Malignant Melanoma 425
22.1 Introduction 427
22.2 Materials and Methods 428
22.3 Results 435
22.4 Discussion 450
References 455
Chapter 23: Uncovering Tumor Systems Biology by Biomodulatory Therapy Strategies 459
23.1 Introduction 459
23.2 Problems with Therapy Strategies in Metastatic Tumors in a Historical Context 460
23.3 Explorative Considerations 462
23.4 Uncovering Systems-Biological Processes in Tumor Tissues by Biomodulatory Therapy Strategies 462
23.5 Program of a Scientific Theory 465
23.6 Constitution of a New Kind of Consideration About Objects of Interest 467
23.7 Discussion 469
References 470
Chapter 24: Breathing New Life into Old Drugs: Indication Discovery by Systems Directed Therapy 472
24.1 Introduction 473
24.2 IMiDs 475
24.2.1 History of Thalidomide 475
24.2.2 IMiDs in Cancer 475
24.2.3 IMiDs in Clinical Trials 476
24.3 COX 2 Inhibitors 477
24.3.1 Cyclooxygenase – Isoforms and Function 477
24.3.2 COX 2 in Cancer 477
24.4 mTOR Antagonists 480
24.4.1 The mTOR Receptor 480
24.4.2 mTOR Antagonists 480
24.4.3 Blocking mTOR Function in Cancer 480
24.4.4 mTOR Antagonists in Clinical Trials 481
24.5 PPARg Agonists 484
24.5.1 The PPARg Receptor 484
24.5.2 PPARg in Cancer 484
References 486
Part VIII:Tumors’ Systems Biology: Implicationsfor Personalized Therapy 493
Chapter 25: A Methodological Approach to Personalized Therapies in Metastatic Cancer 494
25.1 Personalized Medicine: Post-metaphysic Thinking 495
25.1.1 Therapy-Relevant Phenotype 496
25.1.2 The Reductionist Therapy Approach 496
25.1.3 The Holistic Therapy Approach 497
25.2 The Idea of Homogeneous Patient Subsets 497
25.2.1 Evidence-Based Therapy: Uncovering Prognostic Parameters 497
25.2.2 Individual Tumor Disease 498
25.2.3 Novel Therapy-Relevant Methodological Approaches 499
25.3 Differential Model-Creating Determinants 499
25.3.1 Hierarchical Therapy-Relevant Structures 499
25.3.2 May Hierarchical Structures Be Abated for Therapeutic Purposes? 501
25.3.3 Model-Creating Determinants 501
25.4 Modularity and Rationalization of Tumor-Associated Functions: Therapeutic Targets for the Therapy of Metastatic Tumors 503
25.5 Creating a Cancer-Drug Portfolio: Interest in the Technical Disposability over Verifiable Tumor-Associated Processes 504
25.5.1 The Classic Approach: Cytotoxic Therapy 504
25.5.2 Targeted Therapy 505
25.5.3 A Tumor’s Holistic Communicative Structure as a Therapeutic Target 505
25.5.4 Expansion of Therapeutic Options 508
25.6 Monitoring Therapy 508
25.6.1 Integration of the Classic Reductionist Approach 509
25.6.2 Are Therapeutic Approaches Developing into a Systems-Associated Marker-Guided Therapy? 509
25.6.3 Tumor Type-Specific and Systems Stage-Specific Therapy 510
25.6.4 Guiding Systems-Directed Therapies 511
25.7 Implementation of New Therapy Models 512
25.7.1 Can Patient Selection for Therapy Be Improved or, Vice Versa, Can Therapy Selection Be Improved for Patients? 512
25.7.2 Using and Incorporating Systems-Relevant Information in Clinical Trial Designs for Metastatic Tumors 513
25.8 Therapeutic Aims 514
25.9 Challenging Space 515
25.9.1 Communication Theory, Basic Science, and Therapy of Metastases 515
25.9.2 Reverse Engineering, Reconstruction of Systems Features (Intensio Obliqua) Versus Forward Engineering (Intensio Recta) 515
25.9.3 Biomodulatory Therapy: Gene-Based and Non-DNA-Based Heritage 516
References 517
Part IX:Summary 521
Chapter 26: To Be an Object in a Biological System 522
26.1 The Problematization of Established Interpretations of Evolving Tumor Systems 522
26.2 Re-interpretation of Reductionist Considerations on Tumor Evolution 524
26.3 The Collapsed Reductionist Interpretations of Observations on Tumor Evolution Have Now to Be Reconstructed with Novel 525
26.4 Implementation of Internally-Derived or Externally-Derived Modular Knowledge 525
26.5 Objects Anticipate the Attitudes of Subjects 526
26.6 The Accomplishment of the Interactive Roles of Cells Within a Tumor Tissue may Never Only Imply their Reproduction 526
26.7 Homeostasis-Preserving ‘Social’ Subject 527
26.8 The Situative Identity of Systems Objects Proves the Sustained Subjectivity of Communication 527
26.9 Discussion: The Privileged Access of Systems Actors 528
References 528
Chapter 27: From Molecular to Modular, from Theme-Dependent to Evolution-Adjusted Tumor Therapy 530
27.1 Introduction 530
27.2 Tumors Are Communicative Networks 531
27.3 From Molecular to Modular Tumor Biology 532
27.4 Model-Creating Capacity of Biomodulatory Therapies 532
27.5 Therapy-Derived Systems Biology: A Formal-Pragmatic Communication Theory 533
27.6 Novel Systems Determinants Constitute a ‘Big World’ Inside Small World Networks 534
27.7 Tumors May Be Viewed and Uncovered as Communicatively Structured Holistic Systems 535
27.8 Evolutionary Systems Development 536
27.9 Adaptive Trial Designs 538
27.10 Biomodulatory Therapies Accentuate and Focus Practical Issues 539
27.11 Holism and Reductionism Represent Separate, Scientifically Accessible Scopes of View 539
27.12 The Ambition for Personalized Tumor Therapy: Configuring Situational, Stage- and Tumor-Specific Systems Features 540
27.13 Outlook 541
Index 542