The Role of Transforming Growth Factor-β-Mediated Tumor-Stroma Interactions in Prostate Cancer Progression: An Integrative Approach

被引:40
作者
Basanta, David [1 ]
Strand, Douglas W. [3 ]
Lukner, Ralf B. [6 ]
Franco, Omar E. [3 ]
Cliffel, David E. [5 ]
Ayala, Gustavo E. [6 ]
Hayward, Simon W. [2 ,3 ,4 ]
Anderson, Alexander R. A. [1 ]
机构
[1] H Lee Moffitt Canc Ctr & Res Inst, Tampa, FL 33612 USA
[2] Vanderbilt Univ, Med Ctr, Dept Canc Biol, Nashville, TN USA
[3] Vanderbilt Univ, Med Ctr, Dept Urol Surg, Nashville, TN USA
[4] Vanderbilt Univ, Med Ctr, Vanderbilt Ingram Canc Ctr, Nashville, TN USA
[5] Vanderbilt Univ, Dept Chem, Nashville, TN USA
[6] Baylor Coll Med, Houston, TX 77030 USA
关键词
CELLULAR-AUTOMATON MODEL; MATHEMATICAL-MODEL; TGF-BETA; EXTRACELLULAR-MATRIX; INTRAEPITHELIAL NEOPLASIA; INDUCED ANGIOGENESIS; LATERAL DIFFUSION; GENE-EXPRESSION; REACTIVE STROMA; BREAST-CANCER;
D O I
10.1158/0008-5472.CAN-08-3957
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
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]
引用
收藏
页码:7111 / 7120
页数:10
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