Aim. We aim to develop a signature that could accurately predict prognosis and evaluate the response to immune checkpoint blockade (ICB) in bladder urothelial carcinoma (BLCA). Methods. Based on comprehensive analysis of public database, we identified prognosis-related hub genes and investigated their predictive values for the ICB response in BLCA. Results. Among 69 common DEGs, three genes (AURKA, BIRC5, and CKS1B) were associated with poor prognosis, and which were related to histological subtypes, TP53 mutation status, and the C2 (IFN-gamma dominant) subtype. Three genes and their related risk model can effectively predict the response of immunotherapy. Their related drugs were identified through analysis of drug bank database. Conclusions. Three genes could predict prognosis and evaluate the response to ICB in BLCA.
Background: There are currently no satisfactory biomarkers to predict prognosis and evaluate the benefit of immunotherapy in bladder urothelial carcinoma (BLCA) patients. This study aimed to develop a predictive signature that could accurately predict prognosis and evaluate the response to immunotherapy in BLCA. Methods: Differentially expressed genes (DEGs) were identified using the GEPIA and Oncomine databases, and the common genes between the two database were selected using a Venn diagram. In addition, gene ontology enrichment and protein–protein interaction (PPI) network analyses were performed. We further identified the prognosis-related hub genes using the survival R package and confirmed in three online databases (PROGgenesV2, PrognoScan, and OSblca). Moreover, the correlation between prognosis-related hub genes and clinical characteristics was analyzed. Finally, comprehensive bioinformatics analysis was carried out to investigate the association between the three genes and immunity. Results: A total of 750 and 1881 DEGs were identified from GEPIA and Oncomine, respectively, and 69 common DEGs were selected. The most significantly enriched term among the 69 common DEGs was “mitotic cell cycle”, and 11 hub genes were detected by PPI analysis. Moreover, three prognosis-related hub genes, AURKA, BIRC5, and CKS1B, were identified, and which were associated with clinical characteristics, in particular, histological subtypes and TP53 mutation status. Furthermore, our results showed that the expression levels of the three genes were positively correlated with CD8+ T cells and tumor mutation burden (TMB), and with PD-L1, which had higher expression in responders to immunotherapy and in the C2 (IFN-gamma dominant) subtype. Drug–gene interaction network analysis demonstrated that these genes and related drugs could be used to help develop new targets for BLCA immunotherapy. Conclusions: Our study suggested that three key genes in BLCA were correlated with poor prognosis and immune cell infiltration, especially that of CD8+ T cells. The responses of these prognosis-related genes to immunotherapy in BLCA may be associated with CD8+ T cells, TMB, and PD-L1 expression. These key genes and their related drugs may help to develop new targets for BLCA immunotherapy.
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