Integrated bioinformatics and molecular docking ıdentify CCNB1, CDK1, and CYP1A2 as therapeutic targets of phytochemicals in hepatocellular carcinoma.

Abstract

Hepatocellular carcinoma (HCC) is a globally prevalent malignancy and a leading cause of cancer-related mortality; robust prognostic biomarkers and actionable therapeutic strategies are urgently needed. This study aimed to identify potential diagnostic and therapeutic gene targets in HCC through integrated transcriptomic and bioinformatics analyses. Specifically, we integrated four GEO microarray datasets to derive consensus differentially expressed genes (DEGs), constructed a high-confidence protein-protein interaction network, and prioritized hub genes using multiple CytoHubba topological metrics. To explore pharmacological relevance, hub genes were cross-referenced with known targets of four bioactive compounds (metformin, curcumin, resveratrol, silymarin) from the Comparative Toxicogenomics Database; in-silico validations (GEPIA2, UALCAN, TIMER) and molecular docking were then performed. We identified 290 consensus DEGs and seven hub genes, among which CCNB1 and CDK1 were upregulated while CYP1A2 was downregulated and selected as key candidates. Gene ontology and KEGG analyses implicated these genes in cell cycle progression and p53 signaling. Immune-infiltration analysis showed positive associations between CCNB1/CDK1 expression and innate immune cell infiltration, whereas CYP1A2 correlated negatively. Molecular docking revealed favorable binding affinities between the selected compounds and target proteins. Collectively, our results suggest CCNB1 and CDK1 as potential oncogenic markers and CYP1A2 as a putative tumor suppressor in HCC, warranting further functional validation for diagnostic and therapeutic development.