The following is a summary of “Senescence-specific molecular subtypes stratify the hallmarks of the tumor microenvironment and guide precision medicine in bladder cancer,” published in the February 2025 issue of the BMC Cancer by Yan et al.

Bladder cancer (BLCA) is predominantly a disease of aging, with its incidence and mortality rates significantly increasing among elderly individuals. While recent molecular classification models have integrated tumor subtypes with therapeutic responses and prognostic outcomes, the substantial heterogeneity of BLCA limits their broad clinical applicability. Given the strong association between BLCA and aging, there is an urgent need for a molecular subtyping system that accounts for senescence-related characteristics, which could refine prognostic assessments and guide personalized treatment strategies.

This study employed unsupervised clustering analysis on the Cancer Genome Atlas Program (TCGA)-BLCA cohort to develop a senescence-associated molecular classification and a quantitative scoring system, termed Senescore. The Senescore framework was rigorously validated against established molecular subtypes, treatment responses, clinical outcomes, immune tumor microenvironment (TME) characteristics, immune checkpoint relevance, and potential therapeutic targets. 

The findings revealed that patients with a high Senescore were more frequently classified within the basal molecular subtype, characterized by increased immune infiltration, a higher prevalence of driver gene mutations, and upregulated senescence-associated secretory phenotype (SASP) factors in the transcriptomic profile. Although this high Senescore group exhibited poorer overall prognoses, they demonstrated enhanced responsiveness to immunotherapy and neoadjuvant chemotherapy, suggesting that senescence-related tumor biology influences treatment efficacy.

In conclusion, the Senescore-based molecular classification system offers a robust, senescence-informed framework for characterizing BLCA’s biological and clinical features. By integrating age-related molecular signatures into existing classification models, this system provides a refined approach for prognostic assessment and therapeutic decision-making. Moreover, Senescore may facilitate the identification of novel senolytic targets, advancing the incorporation of aging research into precision oncology for BLCA.

Source: bmccancer.biomedcentral.com/articles/10.1186/s12885-025-13698-9