Two stable gut microbiome guilds predict liver tumor class and treatment responses.

Gut microbiome alterations are increasingly associated with hepatocellular carcinoma (HCC), highlighting the gut-liver axis as a key contributor to tumor progression and prognosis. Taxon-based HCC microbiome studies have shown limited reproducibility because they are affected by database dependency, taxonomic ambiguity, and overlooked ecological interactions. The Two Competing Guilds (TCG) model, based on stable gut microbiome interactions, provides a structurally grounded framework for robust, generalizable biomarkers. Using shotgun metagenomic data from a newly recruited cohort of 120 surgically resectable HCC cases and 76 benign liver tumor controls, we constructed co-abundance networks to identify stably correlated genome pairs and assembled a hepatic cancer-TCG (HCC-TCG) model composed of 142 genomes. Functionally, one Guild had more genes for butyrate production from carbohydrate fermentation while the other Guild was enriched in genes for virulence factors and antibiotic resistance, highlighting its potential proinflammatory roles. Classifiers trained on the abundance profiles of HCC-TCG genomes successfully distinguished HCC from benign liver tumors (area under the receiver operating characteristic, AUROC = 0.70) and from colorectal liver metastases (CRLM) (AUROC = 0.78). In an external validation cohort, the model further discriminated against HCC from intrahepatic cholangiocarcinoma (iCCA) (AUROC  =  0.72), and from healthy controls (AUROC  =  0.79-0.85), demonstrating its broad applicability for tumor stratification across clinical contexts. Moreover, HCC-TCG profiles predicted post-resection recurrence risk and response to adjuvant therapies (AUROC up to 0.83). Importantly, external validation in two independent cohorts of advanced HCC patients treated with PD-1/PD-L1 inhibitors demonstrated consistent predictive performance (AUROC  =  0.64-0.73), confirming the model's generalizability in nonsurgical and immunotherapy contexts. This genome-specific, ecologically structured, and database-independent framework identifies a conserved Guild-based microbiome signature for HCC. Our findings demonstrate that a fixed genome-resolved ecological structure retains transferable discriminatory signal across clinical contexts. The HCC-TCG framework provides a genome-specific, interaction-based foundation for future development of non-invasive microbiome stratification strategies requiring prospective validation.