Clinical-data-driven pharmacological framework in liver disease: From liver cirrhosis to hepatocellular carcinoma.

[BACKGROUND AND PURPOSE] This study aimed to identify key effectors and their potential ligands relevant to liver cirrhosis (LC), hepatocellular carcinoma (HCC) and adjacent non-tumour tissue (ANT; reflecting the tumour-influenced yet non-cancerous liver environment rather than true disease tissue) using clinical GEO data (GSE25097) within a systems pharmacology framework.

[EXPERIMENTAL APPROACH] Differentially expressed genes (DEGs;|log₂FC| > 1) were identified and visualised using R software in conjunction with the STRING database. Protein-protein interaction (PPI) networks were constructed, with up-regulated and down-regulated genes depicted as blue and red circles, respectively. Candidate ligands were screened from a repository of natural organic compounds (NOCs), focussing on flavonoids and alkaloids. Kaplan-Meier Plotter (KMP), molecular docking tests (MDT) and density functional theory (DFT) analyses were employed to ensure robustness.

[KEY RESULTS] A total of 123 down-regulated and 146 up-regulated genes were identified and mapped into PPI networks. Among these, CCNB1, associated with the p53 signalling pathway, emerged as the most significantly up-regulated gene across LC, HCC, and ANT tissues. Flavopiridol, a flavonoid-based inhibitor, was initially highlighted; however, subsequent screening identified coronaridine hydroxyindolenine (CH), an alkaloid, as the most promising candidate. CH demonstrated superior binding affinity compared to flavopiridol in both MDT and DFT analyses.

[CONCLUSION AND IMPLICATIONS] The CH-CCNB1 complex exhibited high stability, indicating that CH may represent potential candidate warranting further study against LC, HCC and ANT.