Protein interaction network underpins concordant prognosis among heterogeneous breast cancer signatures.

ABSTRACT: Characterizing the biomolecular systems' properties underpinning prognosis signatures derived from gene expression profiles remains a key clinical and biological challenge. In breast cancer, while different "poor-prognosis" sets of genes have predicted patient survival outcome equally well in independent cohorts, these prognostic signatures have surprisingly little genetic overlap. We examine 10 such published expression-based signatures that are predictors or distinct breast cancer phenotypes, uncover their mechanistic interconnectivity through a protein-protein interaction network, and introduce a novel cross-"gene expression signature" analysis method using (i) domain knowledge to constrain multiple comparisons in a mechanistically relevant single-gene network interactions and (ii) scal

SUBMITTER: Chen J 

PROVIDER: S-EPMC2878851 | biostudies-literature | 2010 Jun

REPOSITORIES: biostudies-literature