Novel Long Non-coding RNA Markers for Prognostic Prediction of Patients with Bladder Cancer

Abstract

To explore novel long non-coding RNA (lncRNA) molecular markers related to bladder cancer prognosis and to construct a prognostic prediction model for bladder cancer patients. Methods: LncRNA expression data of patients with bladder cancer were downloaded from TCGA database. Univariate Cox regression and likelihood-based survival analysis were used to discover prognosis related lncRNAs. Functional studies of prognosis related lncRNAs were conducted by co-expression analysis and pathway enrichment analysis. Multivariate Cox regression analysis was used to establish risk score model, and Receiver Operating Characteristic analysis was used to determine the optimal cut-off point of the model. The risk score model was validated through Kaplan Meier estimation method and log-rank test. Results: Seven prognosis related lncRNAs (OCIAD1-AS1, RP11-111J6.2, AC079354.3, RP11-553A21.3, RP11-598F7.3, CYP4F35P and RP11-113K21.4) which can predict survival of bladder cancer patient were discovered. Co-expression analysis and pathway analysis of these novel lncRNA signature and their target genes further revealed that these lncRNAs play important roles in the occurrence and development of bladder cancer. Additionally, a seven-lncRNA signature based risk score model for prognostic prediction of bladder cancer patients was established and validated. Notably, we identified the potential significance of two tumor-related antisense lncRNAs (OCIAD 1-AS1 and RP11-5S3A21.3) in the prognosis of bladder cancer. Conclusion: Our results suggest that these lncRNA markers may serve as potential prognosis predictors for bladder cancer and deserve further functional verification studies.