In recent studies,obesity is a risk factor for a variety of cancers,including breast cancer and colorectal cancer.Obesity can regulate the tumorigenesis and development of cancer by some factors,such as insulin and insulin-like growth factor-1 (IGF-1),leptin,fat cytokines and hormones.Understanding the relationship between obesity and cancer can provide a new perspective for the prevention and treatment of cancer.

Objective:To explore genes related to costimulatory molecule related to the prognosis of bladder cancer,and to construct and evaluate prognosis model based on costimulatory molecule-based signature(CMS).Methods:Gene expression matrix and clinical information of bladder cancer patients were downloaded from TCGA database and GEO database(GSE31684),and costimulatory molecule-related genes were retrieved from the literature.The univariate and multivariate Cox analysis were used to screened prognostic-related genes and constructed prognostic model.Forecast accuracy of model was verified in TCGA training group,TCGA validation data group and GEO group by Kaplan-Meier survival analysis and receiver operating characteristic curve(ROC).Considering risk score and clinical characteristics,we constructed a nomogram and evaluated its performance by consistency analysis and ROC.CIBERSORT algorithm was used to analyze immune cell composition of tumor microenvironment infiltration,and gene set enrichment analysis(GSEA)was performed to explore the potential mechanism.Results:Four prognostic-related CMSs were found:TNFRSF14,CD276,ICOS and TMIGD2,of which three were included in the risk score construction.Multivariate Cox regression results showed that the risk score based on CMS was an independent prognostic factor for bladder cancer patients.Consistency analysis and ROC results showed that the nomogram had ideal prognosis prediction accuracy.Immune infiltration analysis showed that the high risk group was likely to be in immunosuppressive state.GSEA results suggested that genes in high risk group were enriched in extracel-lular matrix(ECM)receptors interaction,cell cycle and other pathways.Conclusion:TNFRSF14,CD276 and ICOS may be potential prognostic biomarkers for bladder cancer patients.CMS-based risk score and nomogram could contribute to early prognosis and choice of personalized treatment.