Identification of Drug Targets and Agents Associated with Hepatocellular Carcinoma through Integrated Bioinformatics Analysis

Abstract

Background: Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death globally. The mechanisms underlying the development of HCC are mostly unknown till now. Objective: The main goal of this study was to identify potential drug target proteins and agents for the treatment of HCC. Methods: The publicly available three independent mRNA expression profile datasets were downloaded from the NCBI-GEO database to explore common differentially expressed genes (cDEGs) between HCC and control samples using the Statistical LIMMA approach. Hub-cDEGs as drug targets highlighting their functions, pathways, and regulators were identified by using integrated bioinformatics tools and databases. Finally, Hub-cDEGs-guided top-ranked drug agents were identified by molecular docking study for HCC. Results: We identified 160 common DEGs (cDEGs) from three independent mRNA expression datasets in which ten cDEGs (CDKN3, TK1, NCAPG, CDCA5, RACGAP1, AURKA, PRC1, UBE2T, MELK, and ASPM) were selected as Hub-cDEGs. The GO functional and KEGG pathway enrichment analysis of Hub-cDEGs revealed some crucial cancer-stimulating biological processes, molecular functions, cellular components, and signaling pathways. The interaction network analysis identified three TF proteins and five miRNAs as the key transcriptional and post-transcriptional regulators of HubcDEGs. Then, we detected the proposed Hub-cDEGs guided top-ranked three anti-HCC drug molecules (Dactinomycin, Vincristine, Sirolimus) that were also highly supported by the already published top-ranked HCC-causing Hub-DEGs mediated receptors. Conclusion: The findings of this study would be useful resources for diagnosis, prognosis, and therapies of HCC.