An Integrated Clinical-mRNA-lncRNA-miRNA Signature for Muscle-Invasive Bladder Cancer Prognosis

Abstract

An increasing number of evidence suggests that clinical variables alone are not enough to predict the survival of patients with muscle invasive bladder cancer (MIBC), and the expression of mRNAs, long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) also plays an important role in the onset of MIBC. This study aims to establish a more accurate model for predicting the overall survival of MIBC based on clinical information and genetic characteristics. In this study, the RNAs profiles and clinical variable data of patients with MIBC were downloaded from the Cancer Genome Atlas (TCGA) database. Univariate Cox regression analysis, differential expression analysis and elastic net-regulated Cox regression analysis were used to identify the clinical variables and RNAs (mRNAs, lncRNAs and miRNAs) related to the prognosis of MIBC. Prognostic models of MIBC were established by multivariate Cox regression and ridge regression analysis using the identified prognostic clinical variables and RNAs. Three clinical variables, 25 mRNAs, 3 lncRNAs and 2 miRNAs related to the prognosis of MIBC were identified, and an integrated signature, a clinical variable signature, and an mRNA-lncRNA-miRNA signature were established based on the identified clinical variables and/or RNAs. Among the three models, the integrated signature had the highest predictive accuracy (5-year the area under the curve (AUC)=0.835, 95%CI:0.776-0.894) among the three models (P 0.05). The patients in the TCGA MIBC cohort were classified into high- or low-risk groups by the integrated signature, and it was found that the patients in the low-risk group had a significantly longer overall survival time compared with the patients in the high-risk group (P 0.001). Applying published gene signatures and TCGA data, a new and more accurate integrated clinical-mRNA-lncRNA-miRNA signature for MIBC prognostic was established