Development and validation of a exosome-related gene signature for predicting prognosis, immune infiltration and immunotherapeutic response in bladder cancer

Abstract Background Recent studies indicate exosomes play an important role in cell-to-cell communication, cancer metastasis, neovascularization, the regulation of the tumor immune microenvironment, and drug resistance in various tumors. However, the prognostic and therapeutic value of exosome-related genes in bladder cancer (BCa) remains to be determined. Hence, the goal of this study was to identify and validate a novel prognostic model based on exosome-associated genes for BCa patients Methods Differentially expressed exosome-related genes (DEGs) were analyzed using the Cancer Genome Atlas (TCGA) databases. DEGs closely associated with BCa patient survival prognosis were identified using Cox regression; and these genes are used for molecular typing. Moreover, we constructed a 17 multigene model using the least absolute shrinkage and selection operator (LASSO) Cox regression model. The five external cohorts (i.e., GSE13507, GSE32894, GSE31684, GSE48075, and IMvigor210) of BCa patients were used to validate the accuracy by KM plot, ROC and calibration curves. Subsequently, we assessed immune infiltration using seven published algorithms: TIMER, CIBERSORT, CIBERSORT-ABS, QUANTISEQ, MCPCOUNTER, XCELL, and EPIC. Furthermore, the correlation results between risk groups (scores) and overall survival, recognised immunoregolatory cells or common chemotherapeutic agents, clinicopathological data and immune checkpoint-related genes of BCa patients, were analyzed based on wilcox rank test, chi-square test, cox regression and spearman's correlation method. Additionally, we also preformed that the expression level of partial modeled genes was significantly associated with objective responses to anti-PD-1/PD-L1 treatment in the IMvigor210, GSE111636, GSE176307 or our Truce01 cohort. Results In BC patients, 156 exosome-related prognostic DEGs were identified, and were clustered into three classes. Subtypes C3 predicts worse OS, DSS, and PFS in patients with BCa. The prognostic model of 17 exosome-related genes showed good prediction performance by the TCGA training set, internal test set and five external verification sets. Our study also additionally confirmed that model riskscore was closely related with drug susceptibility, immune cell infiltration, and the prediction of immunotherapy efficacy. The high-risk group was characterized by a higher number of infiltrating macrophages M2 cells, and cancer-associated fibroblasts (CAFs). Lastly, we verified the protein and mRNA expression of six interested model-related genes (including AKR1B1, CGB5, CSPG4, P4HB, POLR3G and RAC3) from the Human Protein Atlas (HPA) and 10 paired BCa tissues collected by us. Conclusions In summary, the exosome-associated gene signature established by us exhibited a high predictive performance for the prognosis, immunotherapeutic responsiveness, and chemotherapeutic sensitivity of BCa. And, The model also might function as a chemotherapy and immune checkpoint inhibitor (ICI) treatment guidance.