Metabolic-Associated Signature and Hub Genes Associated with Immune Microenvironment and Prognosis in Bladder Cancer

Background: The relationship between metabolism and immune microenvironment remains to be studied in bladder cancer (BCa). We aimed to construct a metabolic-associated signature for prognostic prediction and investigate its relationship with the immune microenvironment in BCa. Methods: The RNA expression of metabolism associated genes was obtained from a combined data set including The Cancer Genome Atlas, GSE48075, and GSE13507 to divide BCa patients into different clusters. A metabolic-associated signature was constructed using the differentially expressed genes between clusters in the combined TCGA and validated in the IMvigor210 trial and our center. The sensitivity of metabolic-associated signature to chemotherapy and immunotherapy for predicting BCa was assessed. The proportion of 28 subtypes of tumor-infiltrating immune cells (TIICs) in each BCa sample was assessed using a single sample gene set enrichment analysis (ssGSEA). TST and S100A16 were identified by hub genes screening. Survival analysis and nomograms were used to evaluate the prognosis and predictive value in BCa based on TST and S100A16. The loss of function study further investigated the effects of TST and S100A16 on the biological function and immune microenvironment of BCa cells. Results: BCa patients in high-risk group were associated with advanced clinicopathological features and poor survival outcomes. The percentage of high-risk patients was significantly lower in patients responding to anti-PD-L1 treatment (complete response/partial response). Compared with low-risk patients, the IC50 values of cisplatin and gemcitabine were significantly lower in high-risk patients. ssGSEA revealed that the composition of TIICs including macrophages and regulatory T cells between risk groups. TST and S100A16 were significantly associated with clinicopathological features and prognosis. Down-regulation of TST promoted BCa cell invasion, migration, and EMT, which are inhibited by down-regulation of S100A16. CD8+T cells, neutrophils, and dendritic cells had higher infiltration in the TST low-group and the S100A16 high-group. Furthermore, loss of function TST and S100A16 significantly affected the expression of PD-L1 and CD47. Conclusion: The metabolic-associated signature can stratify BCa patients into distinct risk groups with different immunotherapeutic susceptibility and survival outcomes, may contribute to effective individualized treatment. Dysexpression of TST or S100A16 contributes to the tumor progression and dysregulation of immune microenvironment in BCa.