Abstract 3745: Metabolomic profiling of lipid and metabolite in cirrhosis patients with and without hepatocellular carcinoma

Abstract Early detection of hepatocellular carcinoma (HCC) is crucial for improving patient outcomes, as curative treatments are most effective at the early stages of the disease. The lack of robust biomarkers, particularly a non-invasive diagnostic tool, precludes significant improvement of clinical outcomes for HCC patients. Serum metabolites are one of the best non-invasive means for determining patient prognosis. Established biomarkers for HCC including alpha-fetoprotein (AFP), have shown suboptimal performance in early disease stages. This study aimed to develop a combined metabolite and lipid panel to differentiate early-stage HCC from cirrhosis. Unbiased metabolomic and lipidomic analyses of serum samples were performed for 28 and 30 patients with early HCC and cirrhosis, respectively. We developed an unbiased high-resolution liquid chromatography mass spectrometry (LC-MS) based metabolic profiling platform and evaluated differences in the serum global metabolome and lipidome. This method enabled the detection of over 1200 metabolites and up to 800 lipid molecules in this select cohort. We identified 124 metabolites and 246 lipids that were upregulated and 208 metabolites and 73 lipids that were downregulated in HCC compared to cirrhosis. Using multiomic integrative analysis, we identified the overlap between differentially expressed metabolites and lipid and previously published transcriptomic signatures and illustrate that the overlapping signature associates with clinical disease progression. Lastly, we leveraged machine learning models to identify a minimal panel of lipids and metabolites that accurately distinguish between cirrhosis patients with HCC and without HCC. The best performing classifier was derived using Support Vector Machines, achieving a median AUC of 0.98 over 100 cross-validation iterations, and we showed that we need as little as 12 metabolite and lipids for effective discrimination between cirrhosis and early HCC. Citation Format: Hannah Powell, Elisa Ruiz, Sandra L. Grimm, Omar Najjar, Luis Olivares, Michael Scheurer, Hashem B. El Serag, Cristain Coarfa, Salma Kaochar. Metabolomic profiling of lipid and metabolite in cirrhosis patients with and without hepatocellular carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3745.