Identification of high-risk signatures and therapeutic targets through molecular characterization and immune profiling of TP53-mutant breast cancer.

ABSTRACT:

Background

TP53 mutations are commonly observed in aggressive subtypes of breast cancer, influencing the tumor microenvironment (TME) and patient prognosis. In this study, we developed a prognostic gene-based risk model to stratify TP53-mutant breast cancer patients and explore potential therapeutic targets.

Methods

We performed comprehensive bioinformatics analyses using TCGA and METABRIC datasets to identify key prognostic genes in TP53-mutant breast cancer. Differential expression and Gene Set Enrichment Analysis (GSEA) revealed dysregulated pathways, while protein-protein interaction (PPI) networks highlighted functional hubs. Survival analysis, followed by univariate Cox regression, LASSO, and multivariate regression, led to the construction of a robust gene-based risk

SUBMITTER: Paulino PJIV 

PROVIDER: S-EPMC12514579 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature