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Stromal gene expression predicts clinical outcome in breast cancer

Nature Medicine, ISSN: 1078-8956, Vol: 14, Issue: 5, Page: 518-527
2008
  • 1,368
    Citations
  • 0
    Usage
  • 856
    Captures
  • 0
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    1,368
    • Citation Indexes
      1,357
    • Patent Family Citations
      10
      • Patent Families
        10
    • Policy Citations
      1
      • Policy Citation
        1
  • Captures
    856

Article Description

Although it is increasingly evident that cancer is influenced by signals emanating from tumor stroma, little is known regarding how changes in stromal gene expression affect epithelial tumor progression. We used laser capture microdissection to compare gene expression profiles of tumor stroma from 53 primary breast tumors and derived signatures strongly associated with clinical outcome. We present a new stroma-derived prognostic predictor (SDPP) that stratifies disease outcome independently of standard clinical prognostic factors and published expression-based predictors. The SDPP predicts outcome in several published whole tumor-derived expression data sets, identifies poor-outcome individuals from multiple clinical subtypes, including lymph node-negative tumors, and shows increased accuracy with respect to previously published predictors, especially for HER2-positive tumors. Prognostic power increases substantially when the predictor is combined with existing outcome predictors. Genes represented in the SDPP reveal the strong prognostic capacity of differential immune responses as well as angiogenic and hypoxic responses, highlighting the importance of stromal biology in tumor progression. © 2008 Nature Publishing Group.

Bibliographic Details

Finak, Greg; Bertos, Nicholas; Pepin, Francois; Sadekova, Svetlana; Souleimanova, Margarita; Zhao, Hong; Chen, Haiying; Omeroglu, Gulbeyaz; Meterissian, Sarkis; Omeroglu, Atilla; Hallett, Michael; Park, Morag

Springer Science and Business Media LLC

Biochemistry, Genetics and Molecular Biology

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