New Challenges for Cancer Systems Biomedicine

Part I Towards a Comprehensive Theory of Cancer Growth.- Combining Game Theory and Graph Theory to Model Interactions between Cells in the Tumor Microenvironment.- Growth as the Root of all Evil in Carcinomas: Synergy between pH Buffering and Anti-Angiogenesis prevents Emergence of Hallmarks of Cancer.- Phase Transitions in Cancer.- Part II Cancer Related Signalling Pathways.- Spatio-Temporal Modelling of Intracellular Signalling Pathways: Transcription Factors, Negative Feedback Systems and Oscillations.- Understanding Cell Fate Decisions by Identifying Crucial System Dynamics.- Modelling Biochemical Pathways with the Calculus of Looping Sequences.- Dynamic Simulations of Pathways Downstream of TGFβ, Wnt and EGF-Family Growth Factors, in Colorectal Cancer, including Mutations and Treatments with Onco-Protein Inhibitors.- Part III Basic Mechanisms of Tumor Progression.- Some Results on the Population Behavior of Cancer Stem Cells.- Glucose Metabolism in Multicellular Spheroids, ATP Production and Effects of Acidity.- Cell-Cell Interactions in Solid Tumors - the Role of Cancer Stem Cells.- Hybrid Cellular Potts Model for Solid Tumor Growth.- Part IV Tumor-Immune System Interplay and Immunotherapy.- Computational Models as Novel Tools for Cancer Vaccines.- On the Dynamics of Tumor-Immune System Interactions and Combined Chemo- and Immunotherapy.- Modeling the Kinetics of the Immune Response.- Part V Computational Method for Improving Chemotherapy.- Optimizing Cancer Chemotherapy: from Mathematical Theories to Clinical Treatment.- A Systems Biomedicine Approach for Chronotherapeutics Optimization: Focus on the Anticancer Drug Irinotecan.- Modeling the Dynamics of HCV Infected Cells to Tailor Antiviral Therapy in Clinical Practice: Can This Approach Fit for Neoplastic Cells?.- Introducing Drug Transport Early in the Design of Hypoxia Selective Anticancer Agents Using a Mathematical Modelling Approach.- Top-Down Multiscale Simulation of Tumor Response to Treatment in the Context of In Silico Oncology. The Notion of Oncosimulator.- Challenges in the Integration of Flow Cytometry and Time-Lapse Live Cell Imaging Data Using a Cell Proliferation Model.