Our overall goal is to develop an integrative, multidisciplinary research program that applies mathematical methods to the investigation of problem in tumor biology and clinical oncology. The great challenge - both intellectually and educationally - is to integrate biological data and mathematical models into a conceptual framework that can encompass observable cellular and extracellular dynamics in tumor biology. To achieve this goal the following specific aims will be pursued during the life-time of the planning grant: Project 1: Escape from Homeostasis: Integrated mathematical and experimental investigation of carcinogenesis will focus on tumor cell initiation promotion and progression with particular focus on the interactions of the evolving tumor populations with elements of the microenvironment. Most of this corresponding experimental work will be in-vitro. Project 2 : The Physiological Microenvironment and its role in Tumor Invasion and Metastases will focus on the mutual interactions of cancer cell phenotypic evolution with the tumor microenvironment including fibroblasts, blood vessels, and physical parameters such as oxygen, glucose and H"""""""" concentrations. The corresponding empirical research will be largely carried out in-vivo particularly using window chambers. Project 3: Environment-driven Mathematical modeling for Clinical Cancer imaging will focus on the challenge modeling tumor growth and response to therapy in an environment in which imaging resolution is restricted to a few mm and temporal variations obtainable only through occasional imaging sessions. n each project the research will be carried out by a team of mathematicians and experimentalists and will focus on system dynamics, particularly on the mutually interactions of tumor phenotypic evolution and the changing microenvironment.
Relevance We propose that Cancer is a dynamic complex multiscale system that can only truly be understood via the integration of theory and experiments. The goal of the proposal is to use such an integrated approach to better understand, predict and treat cancer
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