| Objetive:Bladder cancer（BLCA）is one of the most common malignant tumors of the genitourinary system in clinical urology.N6-methyladenosine-related long-chain RNA（Lnc RNA）is associated with cancer,but the role of m6A-related Lnc RNAs in the microenvironment of bladder cancer is unclear.The purpose of this study is to explore the potential biological function of m6A-related Lnc RNAs in bladder cancer and to establish a prognostic model.To elucidate the effect of m6A related Lnc RNAs on the prognosis and microenvironment of bladder cancer and the regulation of immune infiltration.Methods:Through bioinformatics analysis,RNA-seq transcriptome data and corresponding clinical data of bladder cancer were screened and downloaded from The Cancer Genome Atlas database.According to m6A related gene types（"writers","readers","erasers"）and corresponding gene names,m6A related gene expression data were extracted by LIMMA software package in R software.The relationship between Lnc RNA and m6A was determined by co-expression analysis.m6A-related Lnc RNAs was obtained by R software and combined with clinical survival data to obtain prognosis-related m6A-related Lnc RNAs.Consensus Clustering cluster analysis was used to analyze the cluster correlation of BLCA patients with different prognosis.ESTIMATE and CIBERSORT algorithms were used to analyze tumor microenvironment difference and immune correlation analysis to determine the level of immune cell infiltration and its relationship with clinical prognosis.In order to identify related pathways and functions,prognosis-related m6A-related Lnc RNAs was functionally annotated.Then KEGG was analyzed by GSEA software for gene expression enrichment analysis to analyze its main biological functions and processes,and visualization was used to establish a prognostic model by lasso regression.A new m6A-related multi-Lnc RNAs prognostic marker was established and verified.The survival data of all patients were randomly divided into training group（Train group）and verification group（Test group）at 1:1.The risk scores of the two groups were calculated.According to the median risk score,the patients were divided into high risk group and low risk group.Survival analysis,ROC curve,independent prognosis analysis,clinical correlation analysis,genetic difference analysis of target gene and immune correlation analysis were performed.Results:Coexpression analysis showed that the expression of Lnc RNAs was closely related to m6A.A total of 28 prognosis-related m6A-related Lnc RNAs were screened,including 5 up-regulated genes and 23 down-regulated genes.PD-L1（gene name:CD274）was highly expressed in cluster2,but there was no significant difference in tumor and normal tissues.Tumor microenvironment and immune correlation analysis showed that immature B cells,plasma cells and regulatory T cells had higher infiltration in Cluster1.However,the infiltration of resting memory CD4+T cells,activated memory CD4+T cells and neutrophils was higher in cluster2,and all related scores were higher in cluster2,indicating that the purity of tumor cells was lower and the density of immune-related cells was higher in tumor microenvironment.GSEA enrichment analysis showed that"Cytokine-cytokinereceptorinteraction signal pathway"was the most abundant.m6A related Lnc RNAs genes related to prognosis were analyzed by lasso regression to determine that the predictive model was constructed by 10 genes,such as PTOV1-AS2,AC005306.1,AC116914.2,BDNF-AS,AC025280.1,AC012568.1,AL136295.2,AL138921.1,AC005479.1 and AC104564.31.The risk signal of predicting patients was significantly correlated with their prognosis,and the area under the ROC curve for predicting the risk value of the model was 0.723.In order to verify the effectiveness of risk signals on the prognosis of bladder cancer,the AUC of the risk value of verification group（Test group）was 0.653,which verified the validity of the model and its predictive value for bladder cancer.Clinical grouping model verification verified the effectiveness of the model again.Univariate and multivariate Cox regression analysis confirmed that prognosis-related m6A-related Lnc RNAs model risk score was an independent prognostic predictor.Clinical correlation analysis showed that risk score was significantly correlated with immune score,cluster classification,stage grade,grade grade,T stage and N stage.Genetic difference analysis of target gene showed that risk score was significantly correlated with PD-L1.The expression level in high risk group was significantly higher than that in low risk group.Immune correlation analysis showed that m6A related Lnc RNAs may be a regulatory factor of tumor microenvironment and immune cell infiltration in patients with bladder cancer.Conclusion:Based on bioinformatics method,the best predictive model of gene composition of PTOV1-AS2,AC005306.1,AC116914.2,BDNF-AS,AC025280.1,AC012568.1,AL136295.2,AL138921.1,AC005479.1 and AC104564.31 was obtained by BLCA analysis of TCGA database.The risk score based on m6A related Lnc RNAs can be used as an independent prognostic factor to predict the prognosis of bladder cancer patients.m6A-related Lnc RNAs may be used as a regulator of immune cell infiltration and participate in the regulation of immune microenvironment of bladder cancer.New prognostic markers may provide new insights into the occurrence,development and treatment of bladder cancer. |
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