Prognostic factor analysis for breast cancer using gene expression profiles.

ABSTRACT:

Background

The survival of patients with breast cancer is highly sporadic, from a few months to more than 15 years. In recent studies, the gene expression profiling of tumors has been used as a promising means of predicting prognosis factors.

Methods

In this study, we used gene expression datasets of tumors to identify prognostic factors in breast cancer. We conducted log-rank tests and used unsupervised clustering methods to find reciprocally expressed gene sets associated with worse survival rates. Prognosis prediction scores were determined as the ratio of gene expressions.

Results

As a result, four prognosis prediction gene set modules were constructed. The four prognostic gene sets predicted worse survival rates in three independent gene expression data sets. In

SUBMITTER: Joe S 

PROVIDER: S-EPMC4959370 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature