Abstract 2314: Plasma metabolomics profiles in the progression of adverse liver conditions to liver cancer

Abstract Background: Circulating metabolites may mark the progression from metabolic dysfunction-associated steatotic liver disease (MASLD) and liver cirrhosis to liver cancer. We characterized metabolomic patterns and evaluated prospective associations with stage-specific transitions. Methods: We used data from 47,972 participants in Mass General Brigham Biobank with Nightingale metabolomics and longitudinal medical records before and after assessment. Stage at metabolomics was defined based on if MASLD, liver cirrhosis, or liver cancer had occurred by International Classification of Diseases codes. For participants with no adverse liver condition, we excluded those with Charlson comorbidity index >5 or death in 1 year of assessment to limit the impact of other diseases. Adjusted means and linear trends were estimated with covariates including demographics, comorbidities, and lifestyles. Adjusted Cox models examined the associations of pre-cancer metabolite and incident liver cancer. Interactions between metabolite and the hepatic fat-associated polygenic risk score (PRS) were tested. Results: At metabolomics assessment, 17,869 participants had no adverse liver condition, 2041 had MASLD, 1774 had liver cirrhosis, and 206 had liver cancer. In the 249 metabolomic variables, 181 displayed significant linear trends by stage (FDR <0.05), e.g., small HDL cholesterol and very large HDL cholesterol / total lipids ratio decreased while large HDL free cholesterol / total lipids ratio and tyrosine increased with progression. These metabolites also show significant associations (FDR <0.05) with liver cancer incidence in participants with no liver disease or cirrhosis. We did not observe metabolite × PRS interactions (FDR >0.05). Conclusions: Metabolomic profiles capture signals along the MASLD - cirrhosis - liver cancer continuum. These markers may improve risk stratification, timing of surveillance, and inform the biological mechanisms along the liver conditions spectrum. Citation Format: Xinyuan Zhang, Longgang Zhao, Yun Chen, Lu Cai, Michelle Lai, Wenjie Ma, Andrew T. Chan, Xuehong Zhang. Plasma metabolomics profiles in the progression of adverse liver conditions to liver cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 2314.