A novel prognostic model based on cellular senescence-related gene signature for bladder cancer

BACKGROUND: Cellular senescence plays crucial role in the progression of tumors. However, the expression patterns and clinical significance of cellular senescence-related genes in bladder cancer (BCa) are still not clearly clarified. This study aimed to establish a prognosis model based on senescence-related genes in BCa. METHODS: The transcriptional profile data and clinical information of BCa were downloaded from TCGA and GEO databases. The least absolute shrinkage and selection operator (LASSO), univariate and multivariate Cox regression analyses were performed to develop a prognostic model in the TCGA cohort. The GSE13507 cohort were used for validation. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and single-sample gene set enrichment analysis (ssGSEA) were performed to investigate underlying mechanisms. RESULTS: A six-gene signature (CBX7, EPHA3, STK40, TGFB1I1, SREBF1, MYC) was constructed in the TCGA databases. Patients were classified into high risk and low risk group in terms of the median risk score. Survival analysis revealed that patients in the higher risk group presented significantly worse prognosis. Receiver operating characteristic (ROC) curve analysis verified the moderate predictive power of the risk model based on the six senescence-related genes signature. Further analysis indicated that the clinicopathological features analysis were significantly different between the two risk groups. As expected, the signature presented prognostic significance in the GSE13507 cohort. Functional analysis indicated that immune-related pathways activity, immune cell infiltration and immune-related function were different between two risk groups. In addition, risk score were positively correlated with multiple immunotherapy biomarkers. CONCLUSION: Our study revealed that a novel model based on senescence-related genes could serve as a reliable predictor of survival for patients with BCa.