Design and multiseries validation of a web-based gene expression assay for predicting breast cancer recurrence and patient survival.

ABSTRACT: Gene expression analysis is a valuable tool for determining the risk of disease recurrence and overall survival of an individual patient with breast cancer. The purpose of this study was to create and validate a robust prognostic algorithm and implement it within an online analysis environment. Genomic and clinical data from 477 clinically diverse patients with breast cancer were analyzed with Cox regression models to identify genes associated with outcome, independent of standard prognostic factors. Percentile-ranked expression data were used to train a "metagene" algorithm to stratify patients as having a high or low risk of recurrence. The classifier was applied to 1016 patients from five independent series. The 200-gene algorithm stratifies patients into risk groups with statistically

SUBMITTER: Van Laar RK 

PROVIDER: S-EPMC3128745 | biostudies-literature | 2011 May

REPOSITORIES: biostudies-literature