ABSTRACT
Objective To construct a regulatory network of competing endogenous RNA(ceRNA)with prognostic value for bladder urothelial carcinoma(BLCA),and analyze the relationship between key messenger RNA(mRNA)and immune function.Methods The UCSC Xena database was used to download mRNA expression data from 404 BLCA patients and 28 normal individuals and key mRNAs were screened by differential analysis.ENCORI database was utilized to search microRNAs(miRNAs)that bind to key mRNAs and all long non-coding RNAs(LncRNAs)that bind to miRNAs.The expression data of miRNA and LncRNA were downloaded from TCGA database,co-expression analysis was performed to identify key mRNA with all miRNAs and miRNA with all LncRNAs,and thus key miRNAs and LncRNAs were screened out.Survival analysis was conducted based on the differences in expression levels of these key mRNAs,miRNAs,and LncRNAs between tumor patients and normal individuals,and finally a ceRNA regulatory network was constructed.The correlation between key mRNAs and immune cells,immune checkpoints(CD274,PDCD1 and CTLA4),and immune cell marker genes(IG)was analyzed using the TIMER 2.0 database.Results A total of 22 key mRNAs were screened,with the most significant difference being proline 3-hydroxylase 4(P3H4).The expression of P3H4 in patients with BLCA was high,and survival time was shorter in patients with high expression.A sum of 33 miRNAs and 14 LncRNAs were screened using the key mRNAs as the central link.Through co-expression analysis and survival analysis,hsa-miR-151a-3p and MIR100 HG were identified as the key miRNA and key LncRNA with prognostic value.The differences in the above analysis results were statistically significant(all P＜0.05).Based on these findings,a ceRNA regulatory network consisting of 1 mRNA,1 miRNA,and 1 LncRNA was constructed.Immunoassay firstly revealed a significant positive correlation between double positive T cells and P3H4 expression in the tumor microenvironment of BLCA.Moreover,there were 3 types of immune cells(tumor-associated neutrophils,and tumor-associated macrophages,dendritic cells),3 immune checkpoints(CD274,PDCD1,CTLA4),and 15 IGs with significant correlation with P3H4.These differences were statistically significant(all P＜0.01).Conclusion This study could help to reveal the progression mechanism of BLCA.The constructed ceRNA network and immune analysis can offer new insights into potential biological targets and immunotherapy directions for the diagnosis,treatment,and prediction of BLCA patients.