Journal
CANCER RESEARCH
Volume 69, Issue 17, Pages 7111-7120Publisher
AMER ASSOC CANCER RESEARCH
DOI: 10.1158/0008-5472.CAN-08-3957
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Funding
- NIH/National Cancer Institute [2T32 CA009592-21A1]
- TMEN [IU54 CA126505, IU54 CA 126568]
- ICBP [5U54 CA113007]
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We have implemented a hybrid cellular automata model based on the structure of human prostate that recapitulates key interactions in nascent tumor foci between tumor cells and adjacent stroma. Model simulations show how stochastic interactions between tumor cells and stroma may lead to a structural suppression of tumor growth, modest proliferation, or unopposed tumor growth. The model incorporates key aspects of prostate tumor progression, including transforming growth factor-beta (TGF-beta), matrix-degrading enzyme activity, and stromal activation. It also examines the importance of TGF-beta during tumor progression and the role of stromal cell density in regulating tumor growth. The validity of one of the key predictions of the model about the effect of epithelial TGF-beta production on glandular stability was tested in vivo. These experimental results confirmed the ability of the model to generate testable biological predictions in addition to providing new avenues of experimental interest. This work underscores the need for more pathologically representative models to cooperatively drive computational and biological modeling, which together could eventually lead to more accurate diagnoses and treatments of prostate cancer. [Cancer Res 2009;69(17):7111-20]
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