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Background:  Immunotherapy has recently shown remarkable efficacy for advanced bladder cancer patients. Accordingly, identifying a biomarker associated with the programmed cell death protein 1 (PD-1)/its ligand (PD-L1) genomic signature to predict patient prognosis is necessary.   Methods:  In this study, we used mutation data and RNA-seq data of bladder cancer samples acquired from The Cancer Genome Atlas (TCGA) database to combine PD-1/PD-L1-associated mutational signatures with PD-1/PD-L1-associated differentially expressed genes (DEGs). Then, we performed a Kaplan-Meier analysis on the corresponding clinical data of the TCGA bladder urothelial carcinoma (BLCA) cohort to identify prognostic genes, and the results were validated using the GSE48075 cohort. The online platform UCSC Xena was used to analyze the relationship between the candidate genes and clinical parameters. We utilized the Human Protein Atlas (HPA) database to validate the protein expression levels. Then, correlation analysis, cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) analysis, and gene set enrichment analysis (GSEA) were used to clarify the mechanism.   Results:  We identified one prognostic gene, sortilin related receptor 1 ( SORL1 ), whose downregulation was associated with a comparatively advanced BLCA stage. While further exploring this finding, we found that  SORL1  expression was negatively correlated with PD-1/PD-L1 expression and M2 macrophage levels. Furthermore, we found that the downregulation of  SORL1  expression was significantly associated with a higher epithelial-mesenchymal transition (EMT) score.   Conclusion:  We described a novel PD-1/PD-L1-associated signature,  SORL1 , that predicts favorable outcomes in bladder cancer.  SORL1  might reduce immune suppression and inhibit the M2 macrophage-induced EMT phenotype of tumor cells.

Identification and Mechanism of the PD-1/PD-L1 Genomic Signature SORL1 as Protective Factor in Bladder Cancer