Identification and validation of a novel prognostic signature based on transcription factors in breast cancer by bioinformatics analysis.

ABSTRACT:

Background

Breast cancer (BRCA) is the leading cause of cancer mortality among women, and it is associated with many tumor suppressors and oncogenes. There is increasing evidence that transcription factors (TFs) play vital roles in human malignancies, but TFs-based biomarkers for BRCA prognosis were still rare and necessary. This study sought to develop and validate a prognostic model based on TFs for BRCA patients.

Methods

Differentially expressed TFs were screened from 1,109 BRCA and 113 non-tumor samples downloaded from The Cancer Genome Atlas (TCGA). Univariate Cox regression analysis was used to identify TFs associated with overall survival (OS) of BRCA, and multivariate Cox regression analysis was performed to establish the optimal risk model. The predictive value of t

SUBMITTER: Yang Y 

PROVIDER: S-EPMC9177273 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature