ArticleCancer prevention research (Philadelphia, Pa.)2025
Prediagnostic Plasma Metabolites Are Associated with Incident Hepatocellular Carcinoma: A Prospective Analysis.
Article in Cancer prevention research (Philadelphia, Pa.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The trial behind it
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Who cites it
2 citing papers in PubMed.
- Risk Assessment and Prediction of Hepatocellular Carcinoma in Noncirrhotic Metabolic Dysfunction-Associated Steatotic Liver Disease.International journal of molecular sciences · 2026Review
- The intricate interplay of microbial metabolomics and carcinogenesis: a spotlight on mechanistic pathways, clinical implications and methodological challenges.Frontiers in cellular and infection microbiology · 2026Review
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
Despite increasing incidence of hepatocellular carcinoma (HCC) in vulnerable populations, accurate early detection tools are lacking. We aimed to investigate the associations between prediagnostic plasma metabolites and incident HCC in a diverse population. In a prospective, nested case-control study within the Southern Community Cohort Study, we conducted prediagnostic LC/MS metabolomic profiling in 150 incident HCC cases (median time to diagnosis, 7.9 years) and 100 controls with cirrhosis. Logistic regression assessed metabolite associations with HCC risk. Metabolite set enrichment analysis identified enriched pathways, and a random forest classifier was used for risk classification models. Candidate metabolites were validated in the UK Biobank (N = 12 incident HCC cases and 24 cirrhosis controls). In logistic regression analysis, seven metabolites were associated with incident HCC (MeffP < 0.0004), including N-acetylmethionine (OR = 0.46; 95% confidence interval, 0.31-0.66). Multiple pathways were enriched in HCC, including histidine and CoA metabolism (FDR P < 0.001). The random forest classifier identified 10 metabolites for inclusion in HCC risk classification models, which improved HCC risk classification compared with clinical covariates alone (AUC = 0.66 for covariates vs. 0.88 for 10 metabolites plus covariates; P < 0.0001). Findings were consistent in the UK Biobank (AUC = 0.72 for covariates vs. 0.88 for four analogous metabolites plus covariates; P = 0.04), assessed via nuclear magnetic resonance spectroscopy. Prediagnostic metabolites, primarily amino acid and sphingolipid derivatives, are associated with HCC risk and improve HCC risk classification beyond clinical covariates. These metabolite profiles, detectable years before diagnosis, could serve as early biomarkers for HCC detection and risk stratification if validated in larger studies. Prevention Relevance: Our findings support the need for larger prospective studies examining the role of prediagnostic plasma metabolomics for the preventive management of HCC in diverse patients across multiple etiologies of liver disease. This approach could improve HCC care by identifying metabolic changes years before diagnosis, potentially enhancing screening and early detection practices.
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Registered trials
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