The present study aimed to identify bladder cancer-associated microRNAs (miRNAs) and target genes, and further analyze the potential molecular mechanisms involved in bladder cancer. The mRNA and miRNA expression profiling dataset GSE40355 was downloaded from the Gene Expression Omnibus database. The Limma package in R was used to identify differential expression levels. The Human microRNA Disease Database was used to identify bladder cancer-associated miRNAs and Target prediction programs were used to screen for miRNA target genes. Enrichment analysis was performed to identify biological functions. The Database for Annotation, Visualization and Integration Discovery was used to perform OMIM_DISEASE analysis, and then protein-protein interaction (PPI) analysis was performed to identify hubs with biological essentiality. ClusterONE plugins in cytoscape were used to screen modules and the InterPro database was used to perform protein domain enrichment analysis. A group of 573 disease dysregulated genes were identified in the present study. Enrichment analysis indicated that the muscle organ development and vascular smooth muscle contraction pathways were significantly enriched in terms of disease dysregulated genes. miRNAs targets (frizzled class receptor 8, EYA transcriptional coactivator and phosphatase 4, sacsin molecular chaperone, calcium voltage-gated channel auxiliary subunit β2, peptidase inhibitor 15 and catenin α2) were mostly associated with bladder cancer. PPI analysis revealed that calmodulin 1 (CALM1), Jun proto-oncogene, AP-1 transcription factor subunit (JUN) and insulin like growth factor 1 (IGF1) were the important hub nodes. Additionally, protein domain enrichment analysis indicated that the serine/threonine protein kinase active site was enriched in module 1 extracted from the PPI network. Overall, the results suggested that the IGF signaling pathway and RAS/MEK/extracellular signal-regulated kinase transduction signaling may exert vital molecular mechanisms in bladder cancer, and that CALM1, JUN and IGF1 may be used as novel potential therapeutic targets.
Keywords: bioinformatics methods; bladder cancer; disease dysregulated genes; microRNA targets.