Metabolomic profiles of hepatocellular carcinoma in a European prospective cohort Fages, Anne Molina Montes, María Ester Epidemiology European Prospective Investigation into Cancer and Nutrition Hepatocellular carcinoma Liver cancer Metabolomics Nuclear magnetic resonance Background: Hepatocellular carcinoma (HCC), the most prevalent form of liver cancer, is difficult to diagnose and has limited treatment options with a low survival rate. Aside from a few key risk factors, such as hepatitis, high alcohol consumption, smoking, obesity, and diabetes, there is incomplete etiologic understanding of the disease and little progress in identification of early risk biomarkers. Methods: To address these aspects, an untargeted nuclear magnetic resonance metabolomic approach was applied to pre-diagnostic serum samples obtained from first incident, primary HCC cases (n = 114) and matched controls (n = 222) identified from amongst the participants of a large European prospective cohort. Results: A metabolic pattern associated with HCC risk comprised of perturbations in fatty acid oxidation and amino acid, lipid, and carbohydrate metabolism was observed. Sixteen metabolites of either endogenous or exogenous origin were found to be significantly associated with HCC risk. The influence of hepatitis infection and potential liver damage was assessed, and further analyses were made to distinguish patterns of early or later diagnosis. Conclusion: Our results show clear metabolic alterations from early stages of HCC development with application for better etiologic understanding, prevention, and early detection of this increasingly common cancer. 2018-01-29T09:06:48Z 2018-01-29T09:06:48Z 2015-09-23 info:eu-repo/semantics/article Fages, A.; et al. Metabolomic profiles of hepatocellular carcinoma in a European prospective cohort. BMC Medicine, 13: 242 (2015). [http://hdl.handle.net/10481/49218] 1741-7015 http://hdl.handle.net/10481/49218 10.1186/s12916-015-0462-9 eng http://creativecommons.org/licenses/by-nc-nd/3.0/ info:eu-repo/semantics/openAccess Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License Biomed Central