Identification and evaluation of network modules for the prognosis of basal-like breast cancer.

ABSTRACT:

Purpose

Basal-like breast cancer (BLBC) is a molecular subtype of breast cancer associated with poor clinical outcome, although some patients with BLBC experience long-term survival. Apart from nodal status, current clinical/histopathological variables show little capacity to identify BLBC patients at either high- or low-risk of disease recurrence. Accordingly, we sought to develop a network based genomic predictor for predicting the outcome of patients with BLBC.

Experimental design

We performed network analysis on global gene expression profiling data of BLBCs, and identified BLBC network modules associated with AP-1 transcription, G-protein coupled receptors, and T-, B-, and NK-cells that are significant predictors of BLBC patient survival.

Results

In gene expressi

SUBMITTER: Hallett RM 

PROVIDER: S-EPMC4627340 | biostudies-literature | 2015 Jul

REPOSITORIES: biostudies-literature