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.