Integrative bioinformatics analysis for the identification of hub genes and Virtual screening of phytochemicals to inhibit AURKA in HepatoCellular carcinoma

Abstract

HepatoCellular Carcinoma (HCC) is one of the most deadly and prevalent neoplasia, accounting for nearly 830,180 mortalities and 905,677 fresh occurrences worldwide annually. Aggressive malignancy with multifaceted etiologies increases in occurrence due to inadequate early diagnosis and ineffective treatment outcomes. Hence the present study aims to identify novel HCC associated biomarkers and inhibit the plausible genes through phytocompounds. Herein, we have implemented the meta-analysis of GSE36376, GSE57957 and GSE84598 micro-array profiles by utilizing GEO2R which resulted in identification of 1683 aberrantly expressed genes. The predicted DEGs were further subjected to Functional annotation and pathway enrichment analysis by using Blast2GO and ExpressAnalyst respectively. Successively, Protein-Protein Interaction analysis was performed by Cytoscape software, and the top 11 most significant hub nodes were identified. The most frequently occurring hub gene Aurora Kinase A (AURKA) was considered as plausible target for subsequent identification of inhibitors. The plant-derived small molecules retrieved from NPACT database were subjected to molecular docking, Molecular dynamic simulations and MMGBSA analysis against AURKA. Conclusively, findings from our study postulates Garcinone C and Silymarin targeting elevated AURKA levels which may contribute as potential inhibitors for HCC patients. However, these outcomes provide only computational insights for targeted HCC-therapeutics but for clinical application of Garcinone C and Silymarin in vitro and in vivo molecular validations are still warranted.