Construction A Prognostic Risk Model Of Bladder Cancer And Analysis Of Immune Infiltration Based On Bioinformatics Analysis Based On ScRNA-seq

Objective:By performing bioinformatic analyses in patients with bladder cancer(BCa),the genes corelative with BCa patients’ prognosis were identified,and risk prognostic model was established,and analyses of its’ relationship with clinicopathological features and immune infiltration were also performed.This provide novel biomarkers for BCa and new ideas for anti-tumor immunotherapy.Methods:Perform quality control and cell annotation of BLCA single-cell data a downloaded from Gene Expression Omnibus(GEO).Cell communication analysis was performed to predict the incoming and outgoing signals.Differentially expressed genes(DEGs)was identified by using univariable Cox regression analysis.A prediction model was established using LASSO-COX regression analysis.Kaplan–Meier survival analysis and receiver operating characteristic(ROC)curves were carried to analyze the diagnostic and prognostic ability of the model.A nomogram was used to predict survival probabilities.Correlation between BCa patients’ risk scores and clinicopathological features was evaluated by student’t test.DEGs were annotated using Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analysis.Gene set enrichment analysis(GSEA)was used to perform gene set functional annotation.Finally,immune cell infiltration analysis was used to explore the role of DEGs in BCa.Results:50263 cells were filtered out,and were divided into 14 subsets.43519 cells were annotated as urothelial cell,which were primary sender of the MK signaling pathway.Nine prognostic genes(SPINK1,FN1,EFEMP1,ELN,PCOLCE2,TUBA1 A,COL14A1,TCF4,and TM4SF1)were identified.Based on the risk scores,patients in TCGA and GEO sets were separated into high-risk and low-risk groups.An inferior OS was noted for those in high-risk group in comparison with those in the low-risk group(p<0.05).The predictive ability of the model did not differ among 1-year,3-year,and 5-year overall survival(AUC>0.6).The probability of relapse or progression was higher in the high-risk group.It was found that the high-risk group was correlated with the progression and recurrence characteristics of BCa,including N stage,M stage,pathological stage and age(P<0.05).According to the GO,KEGG,and GSEA results,multiple genes with significant enrichments were related to immunological GO terms and pathways,such as the MAPK signaling pathway,humoral immune response,and B cell-mediated immunity.Immune infiltration analysis revealed that activated dendritic cells,B cell memory,macrophages M1,macrophages M2,T cells CD4 memory activated,and T cell regulation may be involved in the BCa process.Conclusion:The risk model can predict the patients’ prognoses with BCa.The high-risk group was significantly associated with malignant clinical features and poor prognosis of BCa,and the pathways and functions mechanically was related to immunity.This provides a new basis for anti-tumor immunotherapy.