Identification and validation of a five-gene prognostic signature based on bioinformatics analyses in breast cancer.

ABSTRACT:

Background

This study aimed to identify prognostic signatures to predict the prognosis of breast cancer (BRCA) patients based on a series of comprehensive analyses of gene expression data.

Methods

The RNA-sequencing expression data and corresponding BRCA patient clinical data were collected from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) datasets. Firstly, the differently expressed genes (DEGs) related to prognosis between tumor tissues and normal tissues were ascertained by performing R package "limma". Secondly, the DEGs were used to construct a polygenic risk scoring model by the weighted gene co-expression network analysis (WGCNA) and the least absolute shrinkage and selection operator Cox regression (Lasso-cox) analysis method. Thirdly, surviva

SUBMITTER: Du XJ 

PROVIDER: S-EPMC9898304 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature