Construction and application of metabolic risk model for bladder cancer

Objective:To establish a high-efficiency metabolic risk model of bladder cancer (BLCA) and reveal the heterogeneity of different risk populations using multi-omics technology.Methods:Based on the transcrip-tome data of TCGA-BLCA, a total of 1, 660 metabolism-related genes in 86 metabolic pathways were analyzed by univariate COX analysis, Lasso regression analysis and multivariate COX analysis to construct the metabolic risk model of BLCA.Transcriptomics, metabolomics and single-cell proteomics techniques were used to reveal the molecular expression profiles, metabolite expression profiles and immune microenvironment characteristics of high-risk and low-risk populations.Results:A BLCA metabolic risk model was constructed consisting of 13 genes: CYP2J2, GDPD3, IL4I1, ATP6V1B1, AKR1B1, ENGASE, CHPF, MBOAT7, CAD, FASN, AHCY, FLAD1 and ALG3.The areas under the curves (AUC) predicted by receiver operating characteristic (ROC)curves corresponding to the training cohort for 1-year, 3-year and 5-year overall survival (OS) of BLCA patients were 0.796, 0.702 and 0.717, respectively.The corresponding areas under the ROC curves for the Guangxi cohort predicting the 1-year, 2-year, and 3-year overall survival(OS)of BLCA patients were 0.866, 0.810 and 0.816, re-spectively.Kaplan-Meier curve analysis showed that the prognosis of low-risk group was significantly bet-ter than that of high-risk group (P< 0.001).There were significant changes in metabolites between the high-risk group and the low-risk group, and metabolites such as pyroglutamic acid, citric acid and uric acid were enriched in the high-risk group.Patients in the high-risk group recruited more immunosuppressive cell subsets and had a higher degree of immunosuppression.Conclusion:The metabolic risk model constructed in this study can accurately predict the clinical prognosis of BLCA pa-tients.The heterogeneity of metabolites and immune microenvironment in BLCA patients with different metabol-ic risk patterns provide potential targets for the development of precision treatment plans for BLCA.