There is a rising incidence of non-alcoholic fatty liver disease (NAFLD) as well as of the frequency of Hepato-Cellular Carcinoma (HCC) associated with NAFLD. To seek for putative metabolic pathways specific of the NAFLD etiology, we performed comparative metabolomics between HCC associated with NAFLD and HCC associated with cirrhosis. The study included 28 pairs of HCC tissue versus distant Non-Tumoral Tissue (NTT) collected from patients undergoing hepatectomy. HCC was associated with cirrhosis (n = 9), normal liver (n = 6) and NAFLD (n = 13). Metabolomics was performed using 1H-NMR Spectroscopy on tissue extracts and combined to multivariate statistical analysis. In HCC compared to NTT, statistical models showed high levels of lactate and phosphocholine, and low level of glucose. Shared and Unique Structures (SUS) plots were performed to remove the impact of underlying disease on the metabolic profile of HCC. HCC-cirrhosis was characterized by high levels of β-hydroxybutyrate, tyrosine, phenylalanine and histidine whereas HCC-NAFLD was characterized by high levels of glutamine/glutamate. In addition, the overexpression glutamine/glutamate on HCC-NAFLD was confirmed by both Glutamine Synthetase (GS) immuno-staining and NMR-spectroscopy glutamine quantification. This study provides evidence of metabolic specificities of HCC associated with non-cirrhotic NAFLD versus HCC associated with cirrhosis. These alterations could suggest activation of glutamine synthetase pathway in HCC-NAFLD and mitochondrial dysfunction in HCC-cirrhosis, that may be part of specific carcinogenic processes.

Non-Alcoholic Fatty Liver Disease (NAFLD) is considered as the forthcoming predominant cause for hepatocellular carcinoma (HCC). NAFLD-HCC may rise in non-cirrhotic livers in 40 to 50% of patients. The aim of this study was to identify different metabolic pathways of HCC according to fibrosis level (F0F1 vs. F3F4). A non-targeted metabolomics strategy was applied. We analyzed 52 pairs of human HCC and adjacent non-tumoral tissues which included 26 HCC developed in severe fibrosis or cirrhosis (F3F4) and 26 in no or mild fibrosis (F0F1). Tissue extracts were analyzed using ¹H-Nuclear Magnetic Resonance spectroscopy. An optimization evolutionary method based on genetic algorithm was used to identify discriminant metabolites. We identified 34 metabolites differentiating the two groups of NAFLD-HCC according to fibrosis level, allowing us to propose two metabolomics phenotypes of NAFLD-HCC. We showed that HCC-F0F1 mainly overexpressed choline derivatives and glutamine, whereas HCC-F3F4 were characterized by a decreased content of monounsaturated fatty acids (FA), an increase of saturated FA and an accumulation of branched amino acids. Comparing HCC-F0F1 and HCC-F3F4, differential expression levels of glucose, choline derivatives and phosphoethanolamine, monounsaturated FA, triacylglycerides were identified as specific signatures. Our metabolomics analysis of HCC tissues revealed for the first time two phenotypes of HCC developed in NAFLD according to fibrosis level. This study highlighted the impact of the underlying liver disease on metabolic reprogramming of the tumor.

Background: The prevention and early screening of PCa is highly dependent on the identification of new biomarkers. In this study, we investigated whether plasma metabolic profiles from healthy males provide novel early biomarkers associated with future risk of PCa. Methods: Using the Supplémentation en Vitamines et Minéraux Antioxydants (SU.VI.MAX) cohort, we identified plasma samples collected from 146 PCa cases up to 13 years prior to diagnosis and 272 matched controls. Plasma metabolic profiles were characterized using ultra-high-performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS). Results: Orthogonal partial least squares discriminant analysis (OPLS-DA) discriminated PCa cases from controls, with a median area under the receiver operating characteristic curve (AU-ROC) of 0.92 using a 1000-time repeated random sub-sampling validation. Sparse Partial Least Squares Discriminant Analysis (sPLS-DA) identified the top 10 most important metabolites (p < 0.001) discriminating PCa cases from controls. Among them, phosphate, ethyl oleate, eicosadienoic acid were higher in individuals that developed PCa than in the controls during the follow-up. In contrast, 2-hydroxyadenine, sphinganine, L-glutamic acid, serotonin, 7-keto cholesterol, tiglyl carnitine, and sphingosine were lower. Conclusion: Our results support the dysregulation of amino acids and sphingolipid metabolism during the development of PCa. After validation in an independent cohort, these signatures may promote the development of new prevention and screening strategies to identify males at future risk of PCa.

Background and Aims: Metabolic dysfunction‐associated steatotic liver disease (MASLD) is the most common cause of hepatocellular carcinoma (HCC). In this study, we combine metabolomic and gene expression analysis to compare HCC tissues with non‐tumoural tissues (NTT).Methods: A non‐targeted metabolomic strategy LC–MS was applied to 52 pairs of human MASLD‐HCC and NTT separated into 2 groups according to fibrosis severity F0F1‐F2 versus F3F4. The expression of genes related to de Novo lipogenesis (DNL) and fatty acid oxidation (FAO) has been analysed by quantitative RT‐PCR and/or interrogation of RNA‐seq datasets in 259 pairs of tissues (MASLD‐HCC vs. VIRUS‐HCC).Results: Metabolomic analysis revealed that acylcarnitines were the main discriminating metabolites according to fibrosis severity when we compared MASLD‐HCC‐F0F1‐F2 versus NTT and MASLD‐HCC‐F3F4 versus NTT. Based on these metabolomic data, the analysis of a panel of 15 selected genes related to DNL and FAO indicated that there is no difference between the 2 groups of MASLD‐HCC. In contrast the same comparative gene analysis according to the aetiology of HCC: MASLD‐HCC versus VIRUS‐HCC showed that both aetiologies shared the same upregulation of genes involved in DNL. However, five genes involved in FAO (HADHA, CRAT, CPT1, CPT2 and PPARA) are upregulated exclusively in MASLD‐HCC. This result indicates that FAO and DNL pathways are simultaneously activated in MASLD‐HCC in contrast to VIRUS‐HCC.Conclusions: These results suggest that, the involvement of adaptive metabolic pathways is different depending on the aetiology of HCC. Moreover, the dogma that simultaneous activation of FAO and DNL is incompatible in cancer would not apply to MASLD‐HCC.