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

IF 44.4 Q1 MICROBIOLOGY
iMeta Pub Date : 2026-04-02 eCollection Date: 2026-04-01 DOI:10.1002/imt2.70123
Yang Liu, Zefan Zhang, Guojun Wu, Bowen Li, Linghua Wang, Jincheng Wang, Zixian Wei, Zhiyue Wang, Jinhua Yang, Kunyu Zhang, Tianqi Zhang, Xin Tao, Tao Chen, Jia Fan, Jian Zhou, Xinrong Yang, Liping Zhao, Yunwei Wei
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Abstract

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.

两个稳定的肠道微生物组协会预测肝脏肿瘤的类别和治疗反应。
肠道微生物组的改变越来越多地与肝细胞癌(HCC)相关,强调肠-肝轴是肿瘤进展和预后的关键因素。基于分类的HCC微生物组研究显示可重复性有限,因为它们受到数据库依赖性、分类模糊性和忽视生态相互作用的影响。两个竞争行会(TCG)模型基于稳定的肠道微生物组相互作用,为稳健的、可推广的生物标志物提供了一个结构基础框架。利用新招募的120例手术切除的HCC患者和76例良性肝肿瘤对照的散枪宏基因组数据,我们构建了共丰度网络,以鉴定稳定相关的基因组对,并组装了由142个基因组组成的肝癌- tcg (HCC- tcg)模型。在功能上,一个Guild有更多的碳水化合物发酵丁酸盐生产基因,而另一个Guild则富含毒力因子和抗生素耐药性基因,突出了其潜在的促炎作用。根据HCC- tcg基因组丰度谱训练的分类器成功地将HCC与良性肝肿瘤(接受者工作特征下面积,AUROC = 0.70)和结直肠肝转移(CRLM) (AUROC = 0.78)区分开来。在外部验证队列中,该模型进一步区分了来自肝内胆管癌(iCCA) (AUROC = 0.72)和健康对照(AUROC = 0.79-0.85)的HCC,证明了其在临床背景下肿瘤分层的广泛适用性。此外,HCC-TCG谱预测了术后复发风险和对辅助治疗的反应(AUROC高达0.83)。重要的是,在接受PD-1/PD-L1抑制剂治疗的晚期HCC患者的两个独立队列中,外部验证显示出一致的预测性能(AUROC = 0.64-0.73),证实了该模型在非手术和免疫治疗背景下的可推广性。这种基因组特异性、生态结构和数据库独立的框架确定了HCC的保守的基于行会的微生物组特征。我们的研究结果表明,一个固定的基因组解析的生态结构保留了可转移的歧视性信号在临床环境。HCC-TCG框架为需要前瞻性验证的非侵入性微生物组分层策略的未来发展提供了基因组特异性、基于相互作用的基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
10.80
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