A tumor microenvironment-related risk model for predicting the prognosis and tumor immunity of breast cancer patients.

ABSTRACT:

Background

This study aimed to construct a tumor microenvironment (TME)-related risk model to predict the overall survival (OS) of patients with breast cancer.

Methods

Gene expression data from The Cancer Genome Atlas was used as the training set. Differentially expressed gene analysis, prognosis analysis, weighted gene co-expression network analysis, Least Absolute Shrinkage and Selection Operator regression analysis, and Wald stepwise Cox regression were performed to screen for the TME-related risk model. Three Gene Expression Omnibus databases were used to validate the predictive efficiency of the prognostic model. The TME-risk-related biological function was investigated using the gene set enrichment analysis (GSEA) method. Tumor immune and mutation signatures were analy

SUBMITTER: Geng S 

PROVIDER: S-EPMC9433750 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature