Integrating biomedical knowledge to model pathways of prostate cancer progression

David S. Morris, Scott A. Tomlins, Daniel R. Rhodes, Rohit Mehra, Rajal B. Shah, Arul M. Chinnaiyan

Research output: Contribution to journalReview article

13 Scopus citations

Abstract

Due to pathologic, histologic, and biologic variation within prostate cancers, profiling the genetic changes associated with disease progression has been difficult. Although initial integration of data from profiling studies had been limited by platform variation, bioinformatic tools and analytic techniques have enabled integrative analysis of profiling studies and the identification of more robust and valid profiles. The identification of key transition points in the progression of prostate cancer relies on profiling precursor lesions and "pure" cell populations. Utilizing laser-capture microdissection to isolate 101 cell populations, a more specific genetic profile of progression from benign epithelium to metastatic disease was obtained. This laser-capture profile was analyzed in the context of the molecular concepts map (MCM), a compendium of over 20,000 molecular concepts including other expression profiles of prostate cancer, to obtain an integrative molecular model of progression. The conceptual connections associated with progression confirm that prostate cancer biology is largely driven by pathways related to androgen signaling and epithelial cell biology; however, further analysis of concepts associated with progression suggests stromal factors are highly associated with progression of prostate cancer. The effect of stromal signatures on the progression model suggests the impact of stromal signature downregulation may reflect both a change in the epithelia:stroma ratio within higher grade tumors and also a microenvironment influence on prostate epithelia. Analyzing complex gene expression signatures in the context of molecular concepts improves integrative models and may improve detection, prognostication, or targeted therapy.

Original languageEnglish (US)
Pages (from-to)1177-1187
Number of pages11
JournalCell Cycle
Volume6
Issue number10
DOIs
StatePublished - May 15 2007
Externally publishedYes

Keywords

  • Expression profiling
  • Integrative analysis
  • Laser capture microdissection
  • Prostate cancer progression

ASJC Scopus subject areas

  • Molecular Biology
  • Developmental Biology
  • Cell Biology

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  • Cite this

    Morris, D. S., Tomlins, S. A., Rhodes, D. R., Mehra, R., Shah, R. B., & Chinnaiyan, A. M. (2007). Integrating biomedical knowledge to model pathways of prostate cancer progression. Cell Cycle, 6(10), 1177-1187. https://doi.org/10.4161/cc.6.10.4247