Significance of SUMOylation in breast cancer progression: a comprehensive investigation using single-cell analysis and bioinformatics.

ABSTRACT:

Background

Breast cancer remains a major global health challenge because of limitations in early detection and therapeutic outcomes. This study employed bulk and single-cell RNA sequencing to investigate SUMOylation-associated molecular networks, aiming to identify prognostic biomarkers and potential therapeutic applications.

Methods

Transcriptomic profiling was performed on 1,445 breast cancer and 113 normal samples to identify differentially expressed genes. Four hub genes, NR3C2, CDCA8, AURKA, and PLK1, were prioritized using machine learning. Consensus clustering stratified patients into molecular subtypes based on the hub gene expression patterns. Differential immune infiltration analysis was used to evaluate 28 immune cell populations betwee

SUBMITTER: He W 

PROVIDER: S-EPMC12676025 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature