The role of transforming growth factor-β-mediated tumor-stroma interactions in prostate cancer progression: An integrative approach

David Basanta, Douglas W. Strand, Ralf B. Lukner, Omar E. Franco, David E. Cliffel, Gustavo E. Ayala, Simon W. Hayward, Alexander R A Anderson

Research output: Contribution to journalArticle

38 Scopus citations

Abstract

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-β (TGF-β), matrix-degrading enzyme activity, and stromal activation. It also examines the importance of TGF-β 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-β 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.

Original languageEnglish (US)
Pages (from-to)7111-7120
Number of pages10
JournalCancer research
Volume69
Issue number17
DOIs
StatePublished - Sep 1 2009

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ASJC Scopus subject areas

  • Oncology
  • Cancer Research

Cite this

Basanta, D., Strand, D. W., Lukner, R. B., Franco, O. E., Cliffel, D. E., Ayala, G. E., Hayward, S. W., & Anderson, A. R. A. (2009). The role of transforming growth factor-β-mediated tumor-stroma interactions in prostate cancer progression: An integrative approach. Cancer research, 69(17), 7111-7120. https://doi.org/10.1158/0008-5472.CAN-08-3957