Biomedicines, Journal Year: 2025, Volume and Issue: 13(4), P. 877 - 877
Published: April 4, 2025
Background: Ovarian cancer (OC) is a heterogeneous malignancy associated with poor prognosis, necessitating robust biomarkers for risk stratification and therapy optimization. Cellular senescence-related genes (CSGs) are emerging as pivotal regulators of tumorigenesis immune modulation, yet their prognostic therapeutic implications in OC remain underexplored. Methods: We integrated RNA-sequencing data from TCGA-OV (n = 376), GTEx 88), GSE26712 185) to identify differentially expressed CSGs (DE-CSGs). Consensus clustering, Cox regression, LASSO-penalized modeling, infiltration analyses were employed define molecular subtypes, construct score, characterize tumor microenvironment (TME) dynamics. Drug sensitivity was evaluated using the Genomics Sensitivity Cancer (GDSC)-derived chemotherapeutic response profiles. Results: Among 265 DE-CSGs, 31 OC, frequent copy number variations (CNVs) such STAT1, FOXO1, CCND1. clustering revealed two subtypes (C1/C2): C2 exhibited immune-rich TME, elevated checkpoint expression (PD-L1, CTLA4), poorer survival. A 19-gene model stratified patients into high-/low-risk groups, validated (AUC: 0.586–0.713). High-risk showed lower mutation burden (TMB), dysfunction, resistance Docetaxel/Olaparib. Six hub (HMGB3, MITF, CKAP2, ME1, CTSD, STAT1) independently predictive Conclusions: This study establishes critical determinants prognosis evasion. The provide actionable insights personalized therapy, while identified vulnerabilities highlight opportunities overcome chemoresistance through senescence-targeted strategies.
Language: Английский