In silico identification of microRNAs as candidate colorectal cancer biomarkers.

The involvement of microRNA in cancers plays a significant role in their pathogenesis. Specific expressions of these non-coding RNAs also serve as biomarkers for early colorectal cancer diagnosis, but their laboratory/molecular identification is challenging and expensive. The aim of this study was to identify potential microRNAs for colorectal cancer diagnosis using in silico approach. Sequence similarity search was employed to obtain the candidate microRNA from the datasets, and three target prediction software were employed to determine their target genes. To determine the involvement of these microRNAs in colorectal cancer, the microRNA gene list obtained was used alongside with colorectal cancer expressed genes from gbCRC and CoReCG databases for gene intersection analysis. The involvement of these genes in the cancer subtype was further strengthened with the DAVID database. KEGG and Gene Ontology were used for the pathway and functional analysis, while STRING was employed for the interactions of protein network and further visualized by Cytoscape. The cBioPortal database was used to prioritize the target genes; prognostic and expression analysis were finally performed on the candidate microRNAs and the prioritized targets. This study, therefore, identified five candidate microRNAs, two hub genes (CTNNB1 and epidermal growth factor receptor), and seven significant target genes associated with colorectal cancer. The molecular validation studies are ongoing to ascertain the biological fitness of these findings.