BACKGROUND: Evidence indicates that there is an important role for long non-coding RNAs (lncRNA) in numerous cellular processes and that lncRNAs dysregulation contributes to tumor progression. Improved insight into the molecular characteristics of bladder cancer is required to predict outcomes and to develop a new rationale for targeted therapeutic strategies. Bioinformatics methods, including functional enrichment and network analysis combined with survival analysis, are required to process a large volume of data to obtain further information about differentially expressed genes (DEGs) in bladder cancer. This study aimed to explore the role of lncRNAs and their regulation network in bladder cancer.

MATERIAL AND METHODS: We analyzed bladder cancer data by The Cancer Genome Atlas profiling to identify differentially expressed lncRNAs in bladder cancer. The genes involved in the circlncRNAnet database were evaluated using Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), evolutionary relationship analysis, and protein-protein interaction (PPI) networks.

RESULTS: Two new lncRNAs, ADAMTS9-AS1 and LINC00460, were shown to be differentially expressed in bladder cancer. Patients were divided into 2 groups (high expression and low expression) according to their median expression values. The overall survival and disease-free survival of patients with high ADAMTS9-AS1 bladder cancer were significantly shorter; the expression of LINC00460 had no significant correlation with survival. GO and KEGG analysis of the 2 lncRNA-related genes revealed that these lncRNAs played a vital role in tumorigenesis. Bioinformatics analysis showed that key genes related to LINC00460, including CXCL, CCL, and CSF2, may be related to the development of bladder cancer. The low expression of ADAMTS9-AS1 may influence the survival rate of bladder cancer with the hub gene as a target.

CONCLUSIONS: LncRNA, including LINC00460 and ADAMTS9-AS1, might play a crucial role in the biosynthesis network of bladder cancer. Differential expression results of ADAMTS9-AS1 suggests it may be correlated with a worse prognosis and a shorter survival time. We outlined the biosynthesis network that regulates lncRNAs in bladder cancer. Further experimental data is needed to validate our results.

Keywords: Computational Biology, Gene Regulatory Networks, Biomarkers, Tumor, gene ontology, Protein Interaction Maps