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.

Public Health Relevance

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

National Institute of Health (NIH)
National Cancer Institute (NCI)
Specialized Center--Cooperative Agreements (U54)
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Special Emphasis Panel (ZCA1-SRLB-9 (O1))
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Eljanne, Mariam
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H. Lee Moffitt Cancer Center & Research Institute
United States
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Gatenby, Robert; Brown, Joel (2018) The Evolution and Ecology of Resistance in Cancer Therapy. Cold Spring Harb Perspect Med 8:
Gravenmier, Curtis A; Siddique, Miriam; Gatenby, Robert A (2018) Adaptation to Stochastic Temporal Variations in Intratumoral Blood Flow: The Warburg Effect as a Bet Hedging Strategy. Bull Math Biol 80:954-970
Ibrahim-Hashim, Arig; Robertson-Tessi, Mark; Enriquez-Navas, Pedro M et al. (2017) Defining Cancer Subpopulations by Adaptive Strategies Rather Than Molecular Properties Provides Novel Insights into Intratumoral Evolution. Cancer Res 77:2242-2254
Brown, Joel S; Cunningham, Jessica J; Gatenby, Robert A (2017) Aggregation Effects and Population-Based Dynamics as a Source of Therapy Resistance in Cancer. IEEE Trans Biomed Eng 64:512-518
Perfahl, Holger; Hughes, Barry D; Alarcón, Tomás et al. (2017) 3D hybrid modelling of vascular network formation. J Theor Biol 414:254-268
de Groot, Amber E; Roy, Sounak; Brown, Joel S et al. (2017) Revisiting Seed and Soil: Examining the Primary Tumor and Cancer Cell Foraging in Metastasis. Mol Cancer Res 15:361-370
Gatenby, Robert A; Frieden, B Roy (2017) Cellular information dynamics through transmembrane flow of ions. Sci Rep 7:15075
McFarland, Christopher D; Yaglom, Julia A; Wojtkowiak, Jonathan W et al. (2017) The Damaging Effect of Passenger Mutations on Cancer Progression. Cancer Res 77:4763-4772
Zhang, Jingsong; Cunningham, Jessica J; Brown, Joel S et al. (2017) Integrating evolutionary dynamics into treatment of metastatic castrate-resistant prostate cancer. Nat Commun 8:1816
Zhang, Xiaomeng; Wojtkowiak, Jonathan W; Martinez, Gary V et al. (2016) MR Imaging Biomarkers to Monitor Early Response to Hypoxia-Activated Prodrug TH-302 in Pancreatic Cancer Xenografts. PLoS One 11:e0155289

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