Informatics in Medicine Unlocked (Jan 2021)
Prediction of novel miRNA biomarker candidates for diagnostic and prognostic analysis of STAD and LIHC: An integrated in silico approach
Abstract
Background: miRNAs are endogenous, non-coding and evolutionarily conserved RNA molecules. They have been found to be involved in the progression and proliferation of various cancers due to their contribution in post-transcriptional regulation. Stomach Adenocarcinoma (STAD) and Liver Hepatocellular Carcinoma (LIHC) are the two most common cancers of the upper intestinal tract. Our study aimed to evaluate the circulating miRNAs from both STAD and LIHC samples and to identify commonly dysregulated miRNAs as biomarkers to detect both cancers at the same time. Methods and materials: Common differentially expressed miRNAs (DEMs) from GEO and Bioexpress datasets were considered for initial processing in the analysis. Pathway analysis of the selected miRNAs through DIANA-miRpath tool, followed by survival analysis based on prognostic values through OncoLnc server led to the final biomarker candidates for diagnosis and prognosis of STAD and LIHC. An elaborate miRNA-gene-cancer network was set up for a specialized understanding of the selected DEMs corresponding to the specifically unique target genes and the cancer types. The gene ontology analysis was performed using BINGO to determine functional connotations of the differentially expressed genes (DEGs). Results: After a thorough analysis, we found that the 4 miRNAs: miR-183-5p, miR-203-3p, miR-126-3p and miR-25-3p could be potential prognostic biomarkers against both STAD and LIHC. The differentially expressed genes (DEGs) for these miRNAs were inferred through GEPIA and miRwalk v2.0. The miRNA-gene-cancer network revealed that the commonly deregulated miRNAs could influence the same genes and pathways altered by multiple cancers at the same time-in our case, STAD and LIHC. To support our claim, we showed the gene ontology analysis by BINGO, attesting the functional assignment of the DEGs behind metastasis and development of both the cancers. Conclusion: Our study evaluated a particularly effective avenue of identifying novel miRNA for both early diagnostic and prognostic purposes against more than one cancer.
