A new 4-gene-based prognostic model accurately predicts breast cancer prognosis and immunotherapy response by integrating WGCNA and bioinformatics analysis.

ABSTRACT:

Background

Breast cancer (BRCA) is a common malignancy in women, and its resistance to immunotherapy is a major challenge. Abnormal expression of genes is important in the occurrence and development of BRCA and may also affect the prognosis of patients. Although many BRCA prognosis model scores have been developed, they are only applicable to a limited number of disease subtypes. Our goal is to develop a new prognostic score that is more accurate and applicable to a wider range of BRCA patients.

Methods

BRCA patient data from The Cancer Genome Atlas database was used to identify breast cancer-related genes (BRGs). Differential expression analysis of BRGs was performed using the 'limma' package in R. Prognostic BRGs were identified using co-expression and univariate Cox analy

SUBMITTER: Chen W 

PROVIDER: S-EPMC10869553 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature