Elucidating the beneficial effects of gut microbiota-derived metabolites in treating hepatocellular carcinoma: an integrated network pharmacology, molecular docking, and single-cell sequencing analysis

Hepatocellular carcinoma (HCC) is the most common type of liver cancer and the third leading cause of cancer-related mortality worldwide. While accumulating evidence has highlighted the beneficial effects of gut microbiota (GM)-derived metabolites in HCC treatment, the underlying mechanisms remain unclear. We retrieved GM-derived metabolites from gutMGene v2.0, acquired their targets using the Similarity Ensemble Approach (SEA) and Swiss Target Prediction (STP), and identified HCC-related targets from public databases. Overlapping targets were then obtained via Venn diagram analysis. We constructed protein-protein interaction (PPI) networks, analyzed signaling pathways, and established a comprehensive microbiota-metabolite-target-disease (M-M-T-D) network. We also examined the correlation between core gene expression and overall survival in HCC patients using UALCAN and GEPIA2. Single-cell transcriptomic data from TISCH2 were analyzed to explore the cellular distribution of core genes. To identify candidate compounds, we evaluated the ADMET properties of metabolites and determined the compound with the highest binding affinity via molecular docking. Ultimately, 8 core targets (AKT1, IL6, PPARG, IL1B, JUN, NFKB1, CASP3, and PTGS2) were identified. These targets interacted with seven core metabolites (10-oxo-12(Z)-octadecenoic acid, genipin, 3-indolepropionic acid, succinate, acetate, propionate, and butyrate) through the M-M-T-D network to exert inhibitory effects on HCC. Single-cell RNA sequencing (scRNA-seq) analysis revealed that core gene expression was correlated with the tumor microenvironment (TME) of HCC. Molecular docking confirmed that 3-indolepropionic acid exhibited the strongest binding affinity to the core targets. Collectively, GM-derived metabolites exert beneficial effects against HCC by regulating multiple signaling pathways and targets, supporting their potential as therapeutic candidates.