Integrated analysis of multiple microarray datasets identifies a reproducible survival predictor in ovarian cancer.

ABSTRACT:

Background

Public data integration may help overcome challenges in clinical implementation of microarray profiles. We integrated several ovarian cancer datasets to identify a reproducible predictor of survival.

Methodology/principal findings

Four microarray datasets from different institutions comprising 265 advanced stage tumors were uniformly reprocessed into a single training dataset, also adjusting for inter-laboratory variation ("batch-effect"). Supervised principal component survival analysis was employed to identify prognostic models. Models were independently validated in a 61-patient cohort using a custom array genechip and a publicly available 229-array dataset. Molecular correspondence of high- and low-risk outcome groups between training and validation datasets w

SUBMITTER: Konstantinopoulos PA 

PROVIDER: S-EPMC3066217 | biostudies-literature | 2011 Mar

REPOSITORIES: biostudies-literature