Highly robust model of transcription regulator activity predicts breast cancer overall survival.

ABSTRACT:

Background

While several multigene signatures are available for predicting breast cancer prognosis, particularly in early stage disease, effective molecular indicators are needed, especially for triple-negative carcinomas, to improve treatments and predict diagnostic outcomes. The objective of this study was to identify transcriptional regulatory networks to better understand mechanisms giving rise to breast cancer development and to incorporate this information into a model for predicting clinical outcomes.

Methods

Gene expression profiles from 1097 breast cancer patients were retrieved from The Cancer Genome Atlas (TCGA). Breast cancer-specific transcription regulatory information was identified by considering the binding site information from ENCODE and the top co-express

SUBMITTER: Dong C 

PROVIDER: S-EPMC7118819 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature