Construction of An Immune-Related CeRNA Network as a Prognostic Signature in Bladder Cancer

Abstract

Background: Immunotherapy has been proved to be effective for bladder cancer (BLCA). However, the molecular network involved in BLCA tumor immune response remains unclear. This study aims to construct an immune-related ceRNA network and to identify the prognostic value. Methods: Based on The Cancer Genome Atlas (TCGA), we used single-sample gene set enrichment analysis (ssGSEA), weighted gene co-expression network analysis (WGCNA) to determine immune-related mRNA, lncRNA and miRNA. Then least absolute shrinkage, and selection operator (LASSO) and Cox regression were performed to identify the mRNAs with high prognostic value, and accordingly, the risk score was calculated. Internal and external validation were performed both in TCGA and GSE13507 with Kaplan-Meier (KM) survival and Receiver Operating Characteristic (ROC) curve analysis. Using the immune-related mRNA, lncRNA and miRNA, a ceRNA network was established via MiRcode, starBase, miRDB, miRTarBase and TargetScan. Besides, we also explore the relationship between the risk score and immune cell infiltration via CIBERSORT algorithm. Results: 5 mRNAs (PCGF3, FASN, DPYSL2, TGFBI and NTF3) were ultimately identified, and KM survival analysis displayed the 5-mRNA risk signature could predict the prognosis of BLCA with high efficacy both in TCGA (p = 1.006e-13) and GSE13507 (p = 7.759e-04). Using miRNA targeting molecular prediction database, an immune-related ceRNA network, including 5 mRNAs, 24 miRNAs and 86 lncRNAs, was constructed. Memory B cells, activated dendritic cells, and regulatory T cells infiltration into tumors were negatively correlated with risk score, while the infiltration levels of macrophages M0, M1 and M2 were positively correlated with risk score. Conclusion: This study helped to better understand the molecular mechanisms of tumor immune response from the view of ceRNA hypothesis, and provided a novel prognostic signature for bladder cancer.