Identification of MicroRNAs as Biomarkers in Colorectal Cancer Diagnostics: An In silico approach

Abstract

Colorectal cancer (CRC) is the most common malignancy in the gastrointestinal tract, the third most commonly diagnosed cancer, and a leading cause of cancer‐related deaths worldwide. The involvement of microRNAs in cancers plays a significant role in their pathogenesis. Specific expressions of these non‐coding RNAs also serve as biomarkers for early CRC diagnosis but their laboratory/molecular identification is challenging and expensive. Current diagnostic methods are invasive, more expensive, and lack specificity and sensitivity. Therefore the need for a less invasive, more sensitive and specific biomarkers for early detection of CRC. The present study aimed to identify potential microRNAs and their target genes for CRC diagnosis using in silico approach. Sequence similarity search was employed to obtain the candidate microRNA from two different datasets and target prediction tools were employed to determine their target genes. The involvement of these microRNAs was carried out through the intersection analysis between the candidate microRNAs target gene list and experimentally validated CRC expressed genes. This was further strengthened by determining their enrichment in DAVID. Gene ontology, pathway analysis, and protein network interactions were further evaluated using UniProt, and KEGG, and STRING respectively and visualized by Cytoscape. The cBioPortal was used to prioritize the candidate microRNAs target genes. Prognostic and expression analysis were finally performed on both the candidate microRNAs and the prioritized targets using PROGmiRV2, and PrognoScan, and SurvExpress, and FIREBROWSE respectively. This study, therefore, identified five candidate microRNAs, two hub genes (CTNNB1 and EGFR) and seven statistically significant target genes (p< 0.05) associated with CRC. The molecular validation study of these microRNAs and their targets are pivotal to ascertain the biological fitness of these finding.