The gut-liver axis: exploring microbial dysbiosis and specific biomarkers in hepatocellular carcinoma.

Abstract

Hepatocellular carcinoma represents a major global health challenge, with its link to the commensal microbiota being clearly established. However, developing reproducible microbial biomarkers for early-stage hepatocellular carcinoma diagnosis across diverse populations remains challenging. We conducted an integrative analysis of 13 studies, examining 16S rRNA sequencing data from 607 fecal samples and 263 liver tissue samples. Data processing utilized VSEARCH, QIIME, and R packages (vegan, phyloseq, cooccur, random forest), with PICRUSt for functional prediction. Alpha diversity analysis revealed significant differences in liver microbiota but not in gut microbiota between hepatocellular carcinoma patients and non-cancer individuals. Linear Discriminant Analysis Effect Size identified Blautia and Streptococcus as biomarker shared across the gut and liver micro-niches. Based on the internal data, the models constructed using gut and liver microbiome characteristics demonstrated high discriminative ability (gut model AUC = 0.8064; liver model AUC = 0.9645). Mendelian randomization analysis revealed a potential association between Streptococcus and the development of hepatocellular carcinoma. KEGG enrichment analysis further indicated marked functional differences in microbiota, primarily linked to metabolic irregularities, between cancer patients and controls. Therefore, this study reveals unique gut-liver microbial community features in patients with hepatocellular carcinoma, identifies potential cross-site diagnostic biomarkers, and constructs gut and liver predictive model with good performance, providing preliminary evidence for the application of microbial biomarkers in the early diagnosis and screening of hepatocellular carcinoma.