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Vanderbilt-Ingram Cancer CenterVanderbilt-Ingram Cancer Center


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Multiscale Mathematical Modeling of Cancer Progression

Center for Cancer Systems Biology at Vanderbilt
Grant #: 2U54CA113007

Principal Investigator: Vito Quaranta, M.D.

Overview: The Center for Cancer Systems Biology at Vanderbilt University is a cross-disciplinary, highly-collaborative research and education center. The team of scientists aims to unravel the complexities of cancer progression and drug resistance through the novel application of technology and mathematical modeling. The expertise of its investigators span the disciplines of Cancer Biology, Mathematics, Bioinformatics, Engineering, and Computer Science. Our Center is part of NCI's Integrative Cancer Biology Program (ICBP), which is the NCI's primary effort in cancer systems biology, a field that is rapidly seen as an essential component in the future of cancer research.

Research: The overarching theme of our proposal is to quantify the impact of cancer cell heterogeneity in tumor growth and treatment resistance. It logically extends results from the previous funding period, pointing to phenotypic heterogeneity as key determinant of progression and invasion. We will consider heterogeneity with respect to phenotypic traits (Proliferation, Motility and Metabolism), in a large panel of breast cancer cell lines and in drug resistant breast cancer cell lines. Trait heterogeneity will be quantified primarily by high-content automated microscopy and image processing. Between cell lines, trait variability will be compared as averages and distribution shapes. Within a cell line, cell-to-cell variability (presumably non-genetic) will be represented as subpopulations by statistical modeling, e.g., bayesian information criteria and clustering algorithms. To estimate adaptability, we will measure trait variation in response to perturbations mimicking tumor microenvironment conditions. This large dataset (3 traits in >50 lines under >10 perturbations) will be input to mathematical and computational predictive models, tracking the fate of individual cancer cells and the microenvironment in space-time during tumor growth. With the experimental component, this suite of theoretical models forms a Center "Backbone" deployed towards two Projects. Project 1 will quantify adaptive advantage in cancer progression by incorporating cell trait heterogeneity data into mathematical and computational models that exploit evolution dynamics and game theory concepts. Project 2 will measure impact of trait heterogeneity and fitness cost in the rise of breast cancer resistance to HER2 tyrosine kinase inhibitors. Hypotheses/predictions from the Projects will be validated in vitro and in mouse tumors, by iteration loops of experimentation and theory. Finally, we will continue education/outreach efforts, e.g., hands-on cancer modeling workshops, to attract physical and biological scientists, especially the brightest of the new generations.

Impact: Though central to cancer progression, phenotypic heterogeneity is understudied due to its complexity. Our interdisciplinary team integrates experimentation and theory to quantify the impact of cell heterogeneity in cancer progression, and deploy novel approaches to cancer drug and radiation resistance. By specializing in Cancer Systems Biology at the subcellular, cellular and tissue scales, we will continue to build a much-needed data and modeling bridge between genetic/molecular and clinical/epidemiological scales.