Do two machine-learning based prognostic signatures for breast cancer capture the same biological processes?

ABSTRACT: The fact that there is very little if any overlap between the genes of different prognostic signatures for early-discovery breast cancer is well documented. The reasons for this apparent discrepancy have been explained by the limits of simple machine-learning identification and ranking techniques, and the biological relevance and meaning of the prognostic gene lists was questioned. Subsequently, proponents of the prognostic gene lists claimed that different lists do capture similar underlying biological processes and pathways. The present study places under scrutiny the validity of this claim, for two important gene lists that are at the focus of current large-scale validation efforts. We performed careful enrichment analysis, controlling the effects of multiple testing in a manner which t

SUBMITTER: Drier Y 

PROVIDER: S-EPMC3056769 | biostudies-literature | 2011 Mar

REPOSITORIES: biostudies-literature