Cancer modelling and simulation:
Saved in:
| Other Authors: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Boca Raton, Fla. <<[u.a.]>>
Chapman & Hall/CRC
2003
|
| Series: | Chapman & Hall/CRC mathematical biology and medicine series
|
| Subjects: | |
| Links: | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=018488193&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| Physical Description: | XXVI, 426 S. Ill., graph. Darst. |
| ISBN: | 1584883618 |
Staff View
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| 245 | 1 | 0 | |a Cancer modelling and simulation |c ed. by Luigi Preziosi |
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| 300 | |a XXVI, 426 S. |b Ill., graph. Darst. | ||
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| adam_text | Contents
1 Biological Aspects of Tumour Angiogenesis 1
F ederic (Bussolino, Marco Arese, Enrica Auder o, Enrio Gir audo, Seena
Marchio, Stefania Mitola, Luca Primo, and Guido Serini
Institute for Cancer Research and Treatment and Department of Oncological Sci¬
ences, University of Torino Sc hool of Medicine, Candiolo (Italy)
1.1 V asculogenesis, Angiogenesis, and Arteriogenesis 1
1.2 Inducers of Angiogenesis: The Example of the VEGF Family . 5
1.3 The Tissue-Specific Angiogenic Inducers 7
1.4 Molecules Stabilising Nascent Capillaries: The Example of
Angiopoietins 10
1.5 Natural Inhibitors of Angiogenesis 11
1.6 Angiogenesis and Cancer Progression 11
1.7 References 16
2 Nov el Directions in Tumour Biology: From Basement Membrane-
Directed Polarity to DNA Methylation 23
Cedric Plachot and Sophie A. Lelievre
Department of Basic Medical Sciences, Purdue University (U.S.A.)
2.1 Abstract 24
2.2 Introduction 24
2.3 Cell-Basement Membrane Interactions during Tumour
Progression 25
2.3.1 The Roles of Basement Membrane-Integrin Interaction
in Normal Tissue 26
2.3.2 Alteration of Polarity in Cancer 29
2.3.3 Novel Anti-Cancer Strategies Based on Cell-ECM
Interaction 32
2.4 Chromatin Remodelling and Cancer 33
2.4.1 The SWI/SNF ATP-Dependent Chromatin Remodelling
Complex 33
2.4.2 Histone Modifying Enzymes 35
2.4.3 Dysregulation of Chromatin Remodelling in Cancer . . 36
2.4.4 DNA Methylation and Chromatin Remodelling in
Normal and Cancerous Tissues 37
2.4.5 Anti-Cancer Strategies Based on Chromatin Remodelling 39
2.5 Extracellular Matrix Signalling to the Cell Nucleus, Chromatin
Remodelling, and Cell Behaviour 40
2.5.1 Chromatin Remodelling during Differentiation 40
2.5.2 Extracellular Matrix Signalling to Chromatin 41
2.6 Conclusion 42
2.7 References 43
3 Interstitial Transport in Solid Tumours 51
Paolo A. Netti1 and Rakesh K. Jain2
1 Department of Materials and Production Engineering, University of Naples Fe-
derico II , Naples (Italy)
2 Edwin Steele Laboratory, Department of Radiation Oncology, Massachusetts Gen¬
eral Hospital and Harvard Medical School, Boston (U.S.A.)
3.1 Introduction 52
3.2 Interstitial Transport Parameters 53
3.3 Experimental Models 54
3.3.1 Multicellular Spheroids 54
3.3.2 Animal Models 54
3.4 Experimental Techniques to Quantify Interstitial Transport . . 55
3.4.1 Diffusion Coefficient 55
3.4.2 Hydraulic Conductivity 56
3.5 Role of Solute Dimension and Charge 56
3.6 Hydraulic Conductivity 60
3.7 Role of Extracellular Matrix Composition and Assembly .... 62
3.8 Relevance for Delivery of Molecular Medicine 65
3.9 Conclusion and Challenge 66
3.10 References 67
4 Modelling Avascular Tumour Growth 75
Helen M. Byrne
Centre for Mathematical Medicine School of Mathematical Sciences, University of
Nottingham (U.K.)
4.1 Introduction 76
4.2 Spatially-Uniform Models of Avascular Tumour Growth .... 77
4.2.1 Introduction 77
4.2.2 Growth of Homogeneous Solid Tumours 78
4.2.3 Treatment of Homogeneous Solid Tumours 80
4.2.4 Heterogeneous Growth of Solid Tumours 86
4.2.5 Discussion 90
4.3 One-Dimensional Spatial Models of Avascular Tumour Growth 91
4.3.1 Introduction 91
4.3.2 The Mathematical Model 92
4.3.3 Model Simplification 96
4.3.4 Model Predictions 98
4.3.5 Discussion 100
4.4 Asymmetric Growth of Avascular Tumours 101
4.4.1 Introduction 101
4.4.2 The Model Equations 102
4.4.3 Radially-Symmetric Model Solutions 103
4.4.4 Linear Stability Analysis 104
4.4.5 Discussion 106
4.5 Conclusions 107
4.6 Problems 109
4.6.1 Problems Related to Section 4.2 110
4.6.2 Problems Related to Section 4.3 113
4.6.3 Problems Related to Section 4.4 115
4.7 References 119
5 Mechanical Models in Tumour Growth 121
Davide Ambrosi1 and Francesco Mollica2
1 Dipartimento di Matematica, Politecnico di Torino, Torino (Italy)
2Istituto CNR per la Tecnologia dei Materiali Compositi, Napoli (Italy)
5.1 Introduction 122
5.2 Single Constituent Framework 123
5.3 Kinematics of Growth 124
5.4 Balance Laws 125
5.5 Nutrient Factors 127
5.6 Constitutive Equations 128
5.7 Specific Constitutive Assumptions 130
5.8 Simple Applications 131
5.8.1 Isotropic and Homogeneous Growth Inside a Rigid
Cylinder 131
5.8.2 Isotropic and Nonhomogeneous Growth of a Sphere:
Residual Stresses 133
5.9 A Multicellular Spheroid as a Mixture 136
5.10 A Numerical Simulation 140
5.11 Concluding Remarks 142
5.12 References 143
6 Modelling Tumour-Induced Angiogenesis 147
H.A. Levine1 and B.D. Sleeman2
Department of Mathematics, Iowa State University (U.S.A)
2School of Mathematics, University of Leeds (U.K.)
6.1 Abstract 148
6.2 Introduction 149
6.3 Biochemical Kinetics 150
6.4 Reinforced Random Walks and Cell Movement 152
6.5 Numerical Experiments 154
6.6 Antiangiogenesis Models 155
6.6.1 The Geometry of the Problem 158
6.6.2 The Biochemistry of Angiogenesis and Its Inhibition . . 159
6.6.3 Mechanism for the Production of Protease Inhibitors . . 159
6.6.4 Mechanism for the Degradation of Fibronectin 160
6.7 Equations of Mass Action 160
6.8 Chemical Transport in the Capillary and in the ECM 162
6.8.1 Chemical Transport in the Capillary 162
6.8.2 Chemical Transport in the ECM 163
6.9 Cell Movement , 164
6.9.1 Cell Movement in the Capillary 164
6.9.2 Cell Movement in the ECM 164
6.10 Transmission, Boundary, and Initial Conditions 165
6.10.1 Transmission Conditions 165
6.10.2 Boundary Conditions 165
6.10.3 Initial Conditions 166
6.11 Numerical Experiments 166
6.12 Mathematical Analysis 168
6.13 Exact Solutions 170
6.13.1 Method 1 171
6.13.2 Method 2 172
6.13.3 Method 3 174
6.14 Aggregation 175
6.15 Travelling Waves 182
6.16 References 183
7 Multi-Scale Analysis of Angiogenic Dynamics and Therapy 185
Levon Arakelyan, Yifat Merbl, Peteris Daugulis, Yuval Ginosar, Vladimir
Vainstein, Vera Selitser, Yuri Kogan, Hila Harpak, and Zvia Agur
Medical Biomathematics (IMBM), Bene Ataroth (Israel)
7.1 Introduction 185
7.2 Defining the Challenge 187
7.2.1 Analysis of Experimental Results 188
7.3 Mathematical Models of Tumour Growth and Angiogenesis . . 197
7.3.1 Continuous Models 198
7.3.2 A Discrete Model 204
7.4 Applying the Models: From Theory to the Clinic 207
7.4.1 Simulation Results 207
7.4.2 Devising Drug Pharmacokinetic and Pharmacodynamic
Models for Angiogenesis Simulations 211
7.5 Discussion 213
7.6 Conclusions 214
7.7 References 215
8 Adhesion Mechanisms in Cancer Metastasis 221
Anne Leyrat1, Alain Duperray2, and Claude Verdier1
1 Laboratoire de Rheologie, UJF-INPG, CNRS (UMR 5520), BP 53, Grenoble
cedex 9 (France)
2 Laboratoire de Migration Cellulaire et Infiltration Tumorale (EA2942 INSERM),
Institut Albert Bonniot, La Tranche cedex (France)
8.1 Introduction 222
8.2 Cell-Cell Interactions and Signalling 222
8.2.1 Extracellular Signalling and Signal Transduction .... 223
8.2.2 Cell Adhesion Molecules as Biochemical and
Mechanical Transducers 224
8.2.3 Force Measurements for Estimating Adhesive
Interactions 225
8.3 Key Steps of Cancer Metastasis 226
8.4 Cadherin-Catenin Complex and Cancer Metastasis 228
8.4.1 Structure and Regulation of Function 228
8.4.2 Upstream and Downstream Signalling by the Cadherin-
Catenin Complex 231
8.5 Integrins and Metastasis 233
8.5.1 Structure and Regulation of Function 233
8.5.2 Upstream and Downstream Signalling by Integrins . . . 235
8.6 Introducing the Adhesive Properties in Models of Cell
Migration 236
8.6.1 Cell Migration 236
8.6.2 Modelling Cell Migration Using Adhesion Receptors . . 237
8.6.3 Cancer Cell Migration 238
8.7 Conclusion 238
8.8 References 239
9 Static and Dynamic Interaction between Endothelium and
Circulating Cells in Cancer 243
Roxana Chotard-Ghodsnia1 3, Agnes Drochon1, Alain Duperray2, Anne
Leyrafi, and Claude Verdier2
1 Biomecanique et Genie Biomedical, CNRS (UMR 6600), UTC, Compiegne (France)
2 Laboratoire de Migration Cellulaire et Infiltration Tumorale (EA2942 INSERM),
Institut Albert Bonniot, La Tranche cedex (France)
3 Laboratoire de Rheologie, UJF-INPG, CNRS (UMR 5520), BP 53, Grenoble
cedex 9 (France)
9.1 Introduction 244
9.2 Receptors Involved in Interactions between Endothelium and
Leukocytes or Tumour Cells 245
9.2.1 Selectins 245
9.2.2 Integrins 247
9.2.3 Immunoglobulin Superfamily 248
9.2.4 Cadherins 249
9.3 Leukocyte or Tumour Cell Adhesion under Flow Conditions . . 250
9.3.1 Multistep Process of Leukocyte Adhesion 250
9.3.2 Adhesive Interactions between Cancer Cells and
Endothelium 251
9.4 In Vitro Devices to Study Circulating Cell-Endothelial Cell
Adhesion 252
9.4.1 Static Assays 252
9.4.2 In Vitro Flow Assays 252
9.5 In Vitro Flow Studies of Circulating Cell-Endothelium
Adhesion 257
9.6 Modelling of Circulating Cell-Endothelium Interactions .... 259
9.6.1 Experimental Modelling 260
9.6.2 Mathematical Modelling 261
9.7 Conclusion 263
9.8 References 263
10 Mathematical Modelling of Tissue Invasion 269
Mark A.J. Chaplain and Alexander R.A. Anderson
The SIMBIOS Centre, Depaxtment of Mathematics, University of Dundee, Dundee
(Scotland)
10.1 Introduction 269
10.2 The Continuum Mathematical Model 273
10.3 Numerical Simulations 276
10.3.1 One Dimensional Results 276
10.3.2 Two Dimensional Numerical Simulations 279
10.4 The Discrete Mathematical Model 283
10.4.1 Cell Proliferation 285
10.4.2 Simulation Process for the Discrete Model 285
10.5 Discrete Model Simulation Results 286
10.6 Model Extensions 288
10.7 Discussion and Conclusions 289
10.8 Appendix 292
10.9 References 293
11 Cancer Immune System Competition: Modelling and
Bifurcation Problem 299
Nicola Bellomo1, Maria Letizia Bertottt1, and Santo Motta3
^ipartimento di Matematica, Politecnico di Torino (Italy)
2Dipartimento di Matematica, Universita di Palermo (Italy)
3 Dipartimento di Matematica, Universita di Catania (Italy), Institute of Immunol¬
ogy, Singapore University (Republic of Singapore)
11.1 Introduction 300
11.2 Phenomenological Description and Scaling 302
11.3 Modelling at the Cellular Scale 305
11.3.1 An Overview of Discrete Models 306
11.3.2 Automata-Based Models 307
11.3.3 Shape Space Model Approach 309
11.3.4 The Celada-Seiden Model 309
11.4 Modelling by Generalised Boltzmann Models 312
11.4.1 Cell Populations 313
11.4.2 A Mathematical Framework 314
11.4.3 A Mean Field Model 316
11.4.4 Simulations 317
11.5 Finite Models 320
11.5.1 A Model by Kirschner and Panetta 321
11.5.2 A Model by Nani and Freedman 325
11.5.3 Other References 327
11.6 Critical Analysis and Perspectives 327
11.7 References 329
12 Analysing Hypersensitivity to Chemotherapy in a Cellular
Automata Model of the Immune System 333
Filippo Castiglione, Vera Sleitser, and Zvia Agur
Institute for Medical Biomathematics (IMBM), Bene Ataroth (Israel)
12.1 Overview 334
12.2 Background 335
12.2.1 Immunoglobulins and the Isotype Switch 336
12.2.2 Cytokines Production and the Role of Thl/Th2 Shift . 338
12.2.3 Mathematical Models of the Immune System 339
12.3 A Cellular Automata Model of Hypersensitivity 342
12.3.1 Choosing Parameters 347
12.4 Model Validation and Simulation Results 349
12.4.1 Healthy Subjects: Primary and Secondary Immune
Response to a Generic Antigen 349
12.4.2 Allergic Subjects: Sensitisation and Hypersensitivity to
a Generic Allergenic Drug 351
12.4.3 Effects of IFN-7 and IL-4 354
12.4.4 Hypersensitivity Dependence on Drug Dose 354
12.4.5 Dependence of Hypersensitivity on Dosing Interval . . . 357
12.4.6 Fractionating the Drug Dose into Multiple Dosings . . . 359
12.5 Discussion 359
12.6 Conclusions 361
12.7 References 362
13 Reaction-Diffusion Systems: A Mathematical Biology
Approach 367
Miguel A. Herrero
Departamento de Matematica Aplicada, Facultad de Matematicas, Universidad
Complutense de Madrid (Spain)
13.1 Introduction 368
13.2 Reaction-Diffusion Systems: Basic Results 369
13.2.1 Modelling Assumptions 369
13.2.2 Linear Diffusion 370
13.2.3 Diffusion and Random Walks 372
13.2.4 General RD Systems: Some Relevant Questions 374
13.2.5 Linear Theory of Pattern Formation: Turing s
Instability 378
13.2.6 Nonlinear Pattern Formation: The Activator-Inhibitor
Model by Gierer and Meinhardt 380
13.3 Wave-Type Solutions 382
13.3.1 Transition from an Unstable State: The Work by
Kolmogorov, Petrovsky, and Piskunov 382
13.3.2 Bistable Media 387
13.3.3 Excitable Systems: Pulses 390
13.3.4 Excitable Systems: Targets and Spirals 394
13.4 Models of Chemotaxis 402
13.4.1 Axon Growth and Neuron Navigation 402
13.4.2 Aggregation in Slime Moulds: the Keller-Segel System . 406
13.4.3 Modelling Some Aspects of Chemotaxis 410
13.5 References 414
Analytic Index 421
|
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| discipline | Biologie Mathematik Medizin |
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| id | DE-604.BV024514021 |
| illustrated | Illustrated |
| indexdate | 2024-12-20T13:57:04Z |
| institution | BVB |
| isbn | 1584883618 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-018488193 |
| oclc_num | 249238214 |
| open_access_boolean | |
| owner | DE-83 DE-91G DE-BY-TUM |
| owner_facet | DE-83 DE-91G DE-BY-TUM |
| physical | XXVI, 426 S. Ill., graph. Darst. |
| publishDate | 2003 |
| publishDateSearch | 2003 |
| publishDateSort | 2003 |
| publisher | Chapman & Hall/CRC |
| record_format | marc |
| series2 | Chapman & Hall/CRC mathematical biology and medicine series |
| spellingShingle | Cancer modelling and simulation Simulation (DE-588)4055072-2 gnd Mathematisches Modell (DE-588)4114528-8 gnd Invasives Wachstum (DE-588)4193964-5 gnd Krebs Medizin (DE-588)4073781-0 gnd |
| subject_GND | (DE-588)4055072-2 (DE-588)4114528-8 (DE-588)4193964-5 (DE-588)4073781-0 |
| title | Cancer modelling and simulation |
| title_auth | Cancer modelling and simulation |
| title_exact_search | Cancer modelling and simulation |
| title_full | Cancer modelling and simulation ed. by Luigi Preziosi |
| title_fullStr | Cancer modelling and simulation ed. by Luigi Preziosi |
| title_full_unstemmed | Cancer modelling and simulation ed. by Luigi Preziosi |
| title_short | Cancer modelling and simulation |
| title_sort | cancer modelling and simulation |
| topic | Simulation (DE-588)4055072-2 gnd Mathematisches Modell (DE-588)4114528-8 gnd Invasives Wachstum (DE-588)4193964-5 gnd Krebs Medizin (DE-588)4073781-0 gnd |
| topic_facet | Simulation Mathematisches Modell Invasives Wachstum Krebs Medizin |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=018488193&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT preziosiluigi cancermodellingandsimulation |
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Order paper/chapter scan
Branch Library Mathematics & Informatics
| Call Number: |
0102 BO 110f 2015 A 6292
Floor plan |
|---|---|
| Copy 1 | Available for loan On Shelf |