A network module-based method for identifying cancer prognostic signatures

Guanming Wu^* and Lincoln Stein

• * Corresponding author: Guanming Wu guanmingwu@gmail.com

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Genome Biology 2012, 13:R112 doi:10.1186/gb-2012-13-12-r112
Published: 10 December 2012

Abstract (provisional)

Discovering robust prognostic gene signatures as biomarkers using genomics data can be challenging. We have developed a simple but efficient method for discovering prognostic biomarkers in cancer gene expression data sets using modules derived from a highly reliable gene functional interaction network. When applied to breast cancer, we discover a novel 31-gene signature associated with patient survival. The signature replicates across five independent gene expression studies, and outperforms 48 published gene signatures. When applied to ovarian cancer, the algorithm identifies a 75-gene signature associated with patient survival. A Cytoscape plugin implementation of the signature discovery method is available at http://wiki.reactome.org/index.php/Reactome_FI_Cytoscape_Plugin.

The complete article is available as a provisional PDF. The fully formatted PDF and HTML versions are in production. 

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At CRBCM we are waiting for the final article.   These types of article shed a light on how we 

can finally identify some of the driver mutation in basal like breast cancer. Will wait to comment as soon as the final article is reviewed.