We are convinced that the diverse perspectives and techniques developed by physical and quantitative scientists can make a significant impact on cancer management and treatment in potentially revolutionary ways. This proposal is centered on our strong belief that diverse physical measurements at multiple scales from molecular to organismic need to be integrated with sophisticated and diverse modeling approaches to generate a model of cancer that can be used predict the behavior of cancers during emergence and in response to perturbation. Our primary hypothesis is that multi-scale measurement and modeling will allow specific cases of cancer to be modeled with sufficient fidelity to estimate'the relative probable efficacy of alternative therapies (rationally integrating genotype, tumor environment and treatment parameters to predict outcome). Our strategy presupposes that analyses of specific properties at the molecular-cell, tumor and host levels when integrated in an appropriate modeling framework can inform therapeutic response. The consortium that has committed to this project is a group of investigators with widely diverse expertise and a common vision to develop and to apply physical sciences approaches to the study of cancer. This proposal describes the development of an integrated virtual cancer model that Incorporates a molecular-cellular model (RP1), a cancer cell evolutionary model of tumor heterogeneity (RP2), a whole tumor model with physically relevant spatial parameters to model tumor micro-environment and interaction with vasculature (RP3), and, lastly, a host model that aims to model physiological, immune and metabolic responses to tumor growth (RP4). These models will be built upon a unique synchronized dataset wherein a suite of novel measurement platforms are applied to a common set of samples from clinically relevant model systems testing therapeutic response of acute myelogenous leukemia (AML) and non-Hodgkins lymphoma (NHL) to standard cytotoxic therapy.
Clinical tools to accurately describe, evaluate and predict an individual's response to cancer therapy are a field-wide priority. Through our virtual cancer, we anticipate it will become possible to take a small number of measurements from a patient, input those measurements as calibrants to our virtual cancer and then simulate the growth and response to therapy of the patient.
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