Long non-coding RNAs (lncRNAs) act as competing endogenous RNAs (ceRNAs) to regulate
mRNA expression through sponging
microRNA in
tumorigenesis and progression. However, following the discovery of new
RNA interaction, the differentially expressed RNAs and
ceRNA regulatory network are required to update. Our study comprehensively analyzed the differentially expressed
RNA and corresponding
ceRNA network and thus constructed a potentially predictive tool for prognosis. "DESeq2" was used to perform differential expression analysis. Two hundred and six differentially expressed (DE) lncRNAs, 222 DE
miRNAs, and 2,463 DE mRNAs were found in this study. The
lncRNA-
mRNA interactions in the miRcode database and the
miRNA-
mRNA interactions in the starBase, miRcode, and mirTarBase databases were searched, and a
competing endogenous RNA (
ceRNA) network with 186 nodes and 836 interactions was subsequently constructed. Aberrant expression patterns of
lncRNA NR2F1-AS1 and
lncRNA AC010168.2 were evaluated in two datasets (GSE89006, GSE31684), and real-time polymerase chain reaction was also performed to validate the expression pattern. Furthermore, we found that these two lncRNAs were independent prognostic
biomarkers to generate a prognostic
lncRNA signature by univariate and multivariate Cox analyses. According to the
lncRNA signature, patients in the high-risk group were associated with a poor prognosis and validated by an external dataset. A novel genomic-clinicopathologic nomogram to improve prognosis prediction of
bladder cancer was further plotted and calibrated. Our study deepens the understanding of the regulatory
ceRNA network and provides an easy-to-do genomic-clinicopathological nomogram to predict the prognosis in patients with
bladder cancer.