Integrative analysis of somatic mutations, gene expression, and co-expression networks in ERG-stratified prostate adenocarcinoma

Aim: ERG overexpression driven by gene fusions is well-characterized event in prostate cancer, yet its impact on gene expression profiles and regulatory networks remains unclear. This study aims to identify most frequently mutated 20 genes in prostate adenocarcinoma, compare their expression levels in ERG+ and ERG- tumors, and construct gene correlation networks to uncover ERG-dependent molecular interactions. Materials and Methods: RNA-seq and somatic mutation data from the TCGA-PRAD cohort were used. Most frequently mutated 20 genes were identified. Patients were grouped by ERG expression status. Differential expression analysis and gene co-expression network construction were performed for each subgroup. Results: TP53, SPOP, FOXA1, KMT2D, KDM6A, and MUC17 showed higher expression in ERG+ tumors, while TTN, LRP1B, PTEN, and RYR2 were more expressed in ERG- tumors. Network analysis revealed distinct regulatory patterns between subgroups. Conclusion: ERG status significantly shapes transcriptional and regulatory landscape of prostate cancer, offering potential targets for ERG-specific therapies.