Homogeneous datasets of triple negative breast cancers enable the identification of novel prognostic and predictive signatures.

ABSTRACT:

Background

Current prognostic gene signatures for breast cancer mainly reflect proliferation status and have limited value in triple-negative (TNBC) cancers. The identification of prognostic signatures from TNBC cohorts was limited in the past due to small sample sizes.

Methodology/principal findings

We assembled all currently publically available TNBC gene expression datasets generated on Affymetrix gene chips. Inter-laboratory variation was minimized by filtering methods for both samples and genes. Supervised analysis was performed to identify prognostic signatures from 394 cases which were subsequently tested on an independent validation cohort (n = 261 cases).

Conclusions/significance

Using two distinct false discovery rate thresholds, 25% and <3.5%, a larger (n =

SUBMITTER: Karn T 

PROVIDER: S-EPMC3248403 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature