Senescence-associated gene signatures predict survival in lung cancer: a multi-cohort analysis

Lung cancer is a leading cause of cancer-related mortality worldwide and is predominantly diagnosed in older adults, underscoring the need to explore aging-related biological mechanisms that influence disease progression and prognosis. Cellular senescence, a hallmark of aging, plays a dual role in cancer by contributing to both tumor suppression and tumor promotion through its influence on tumor growth, modulation of the tumor microenvironment, the senescence-associated secretory phenotype (SASP), and response to therapy. In this study, we evaluated the prognostic significance of senescence-related gene expression in lung cancer using three independent gene signatures, including the SenMayo gene set and two additional curated lists. Transcriptomic and clinical data from publicly available datasets were analyzed using Cox regression, Kaplan-Meier survival analysis, and multivariate modeling. All three senescence signatures were significantly associated with overall survival, with the SenMayo signature showing the most robust and consistent prognostic power. Notably, higher expression of senescence-associated genes was associated with improved survival in the overall lung cancer cohort and in lung adenocarcinoma, while a more heterogeneous pattern emerged in squamous cell carcinoma. Although hazard ratios varied among the gene sets, their broadly concordant associations with clinical outcomes highlight the biological relevance and context dependence of senescence in lung cancer. These findings suggest that senescence-associated gene expression may serve as a valuable prognostic biomarker and offer mechanistic insights into tumor behavior. Our results contribute to the growing body of gero-oncology research and emphasize the need for tumor-specific exploration of aging-related processes in cancer.