A combined transcriptomic, epigenetic, and functional analysis identifies novel biomarkers in breast cancer.

ABSTRACT:

Background

Breast cancer is a leading cause of cancer-related mortality among women worldwide. Identifying reliable molecular biomarkers and therapeutic targets is crucial for improving early diagnosis and treatment strategies. This study aimed to identify and functionally validate key hub genes involved in breast cancer progression using an integrated bioinformatics and experimental approach.

Methodology

Three microarray datasets (GSE42568, GSE29431, and GSE21422) were retrieved from the GEO database to identify differentially expressed genes (DEGs). DEGs common across datasets were subjected to PPI network analysis using STRING and Cytoscape, and hub genes were identified via CytoHubba. The expression of hub genes was validated using RT-qPCR in six breast cancer and five n

SUBMITTER: Gari M 

PROVIDER: S-EPMC12853850 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature