. Epithelial cell behavior is tightly regulated by the surrounding mE. This control is mediated through the coordinated actions of cell-cell adhesion, paracrine/autocrine growth factors and through adhesion to the extracellular matrix. Together, these mechanisms ensure that cells do not proliferate inappropriately or stray from their immediate mE niche. The process of oncogenic transformation and tumor progression entails the escape from these mechanisms, and the evolution ofthe tumor cell population towards phenotypes that allow them to become independent ofthe normal tissue mE. Activation ofthe underlying stromal fibroblasts, leading to the increased production of paracrine growth factors and pro-survival ECM is one way that developing tumors can achieve mE independence. The complexity of the host-tumor interaction in the carcinogenic process lends itself well to integrated experimental/mathematical based approaches, which are designed to handle multiple variables simultaneously. The current project will initially consider the mechanisms which control normal tissue homeostasis and subsequently homeostatic escape by using three different modeling approaches that examine the roles physical constraints, cell-mE interactions and evolutionary dynamics play in carcinogenesis. In the second part we will use novel in vitro organotypic cell culture models to test whether the presence of an activated stroma can provide the second 'hit' in the transformation of epithelial cells that have been immortalized using the step-wise introduction of activating oncogenes. The final part of the study will integrate our understanding of homeostasis to develop methods for homeostatic control that may require new experimental and theoretical developments. We expect that a deeper understanding of homeostatic escape, in terms of host-tumor interactions, will have major implications for cancer prevention and novel treatment strategies. As with the other projects in the PS-OC, Project 1 is built on the research paradigm that closely integrates mathematical modeling with empirical observations. The proposed research relies heavily on imaging (primarily microscopy) as the enabling technology that bridges cancer biology with the mathematical models. As in the other projects, we will pay close attention to the accuracy of information extraction from the images and critically examine the limits of the integration of imaging in informing model parameters and comparing to system dynamics predicted by model simulations.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
5U54CA143970-04
Application #
8555187
Study Section
Special Emphasis Panel (ZCA1-SRLB-9 (O1))
Project Start
2009-09-30
Project End
2014-08-31
Budget Start
2012-09-01
Budget End
2013-08-31
Support Year
4
Fiscal Year
2012
Total Cost
$457,360
Indirect Cost
$163,100
Name
H. Lee Moffitt Cancer Center & Research Institute
Department
Type
DUNS #
139301956
City
Tampa
State
FL
Country
United States
Zip Code
33612
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
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
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
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
Gatenby, Robert A; Frieden, B Roy (2017) CellularĀ information dynamics through transmembrane flow of ions. Sci Rep 7:15075
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
Gravenmier, Curtis A; Siddique, Miriam; Gatenby, Robert A (2017) Adaptation to Stochastic Temporal Variations in Intratumoral Blood Flow: The Warburg Effect as a Bet Hedging Strategy. Bull Math Biol :
Kim, Eunjung; Rebecca, Vito W; Smalley, Keiran S M et al. (2016) Phase i trials in melanoma: A framework to translate preclinical findings to the clinic. Eur J Cancer 67:213-222
Gillies, Robert J; Kinahan, Paul E; Hricak, Hedvig (2016) Radiomics: Images Are More than Pictures, They Are Data. Radiology 278:563-77
Scott, Jacob G; Fletcher, Alexander G; Anderson, Alexander R A et al. (2016) Spatial Metrics of Tumour Vascular Organisation Predict Radiation Efficacy in a Computational Model. PLoS Comput Biol 12:e1004712

Showing the most recent 10 out of 118 publications