Hepatic levels of S-adenosylmethionine regulate the adaptive response to fasting

26 p.-6 fig.-1 tab.-1 graph. abst.There has been an intense focus to uncover the molecular mechanisms by which fasting triggers the adaptive cellular responses in the major organs of the body. Here, we show that in mice, hepatic S-adenosylmethionine (SAMe)—the principal methyl donor—acts as a metabolic sensor of nutrition to fine-tune the catabolic-fasting response by modulating phosphatidylethanolamine N-methyltransferase (PEMT) activity, endoplasmic reticulum-mitochondria contacts, β-oxidation, and ATP production in the liver, together with FGF21-mediated lipolysis and thermogenesis in adipose tissues. Notably, we show that glucagon induces the expression of the hepatic SAMe-synthesizing enzyme methionine adenosyltransferase α1 (MAT1A), which translocates to mitochondria-associated membranes. This leads to the production of this metabolite at these sites, which acts as a brake to prevent excessive β-oxidation and mitochondrial ATP synthesis and thereby endoplasmic reticulum stress and liver injury. This work provides important insights into the previously undescribed function of SAMe as a new arm of the metabolic adaptation to fasting.M.V.-R. is supported by Proyecto PID2020-119486RB-100 (funded by MCIN/AEI/10.13039/501100011033), Gilead Sciences International Research Scholars Program in Liver Disease, Acción Estratégica Ciberehd Emergentes 2018 (ISCIII), Fundación BBVA, HORIZON-TMA-MSCA-Doctoral Networks 2021 (101073094), and Redes de Investigación 2022 (RED2022-134485-T). M.L.M.-C. is supported by La CAIXA Foundation (LCF/PR/HP17/52190004), Proyecto PID2020-117116RB-I00 (funded by MCIN/AEI/10.13039/501100011033), Ayudas Fundación BBVA a equipos de investigación científica (Umbrella 2018), and AECC Scientific Foundation (Rare Cancers 2017). A.W. is supported by RTI2018-097503-B-I00 and PID2021-127169OB-I00, (funded by MCIN/AEI/10.13039/501100011033) and by “ERDF A way of making Europe,” Xunta de Galicia (Ayudas PRO-ERC), Fundación Mutua Madrileña, and European Community’s H2020 Framework Programme (ERC Consolidator grant no. 865157 and MSCA Doctoral Networks 2021 no. 101073094). C.M. is supported by CIBERNED. P.A. is supported by Ayudas para apoyar grupos de investigación del sistema Universitario Vasco (IT1476-22), PID2021-124425OB-I00 (funded by MCIN/AEI/10.13039/501100011033 and “ERDF A way of making Europe,” MCI/UE/ISCiii [PMP21/00080], and UPV/EHU [COLAB20/01]). M.F. and M.G.B. are supported by PID2019-105739GB-I00 and PID2020-115472GB-I00, respectively (funded by MCIN/AEI/10.13039/501100011033). M.G.B. is supported by Xunta de Galicia (ED431C 2019/013). C.A., T.L.-D., and J.B.-V. are recipients of pre-doctoral fellowships from Xunta de Galicia (ED481A-2020/046, ED481A-2018/042, and ED481A 2021/244, respectively). T.C.D. is supported by Fundación Científica AECC. A.T.-R. is a recipient of a pre-doctoral fellowship from Fundación Científica AECC. S.V.A. and C.R. are recipients of Margarita Salas postdoc grants under the “Plan de Recuperación Transformación” program funded by the Spanish Ministry of Universities with European Union’s NextGeneration EU funds (2021/PER/00020 and MU-21-UP2021-03071902373A, respectively). T.C.D., A.S.-R., and M.T.-C. are recipients of Ayuda RYC2020-029316-I, PRE2019/088960, and BES-2016/078493, respectively, supported by MCIN/AEI/10.13039/501100011033 and by El FSE invierte en tu futuro. S.L.-O. is a recipient of a pre-doctoral fellowship from the Departamento de Educación del Gobierno Vasco (PRE_2018_1_0372). P.A.-G. is recipient of a FPU pre-doctoral fellowship from the Ministry of Education (FPU19/02704). CIC bioGUNE is supported by Ayuda CEX2021-001136-S financiada por MCIN/AEI/10.13039/501100011033. A.B.-C. was funded by predoctoral contract PFIS (FI19/00240) from Instituto de Salud Carlos III (ISCIII) co-funded by Fondo Social Europeo (FSE), and A.D.-L. was funded by contract Juan Rodés (JR17/00016) from ISCIII. A.B.-C. is a Miguel Servet researcher (CPII22/00008) from ISCIII.Peer reviewe

Genetic profiling of poorly differentiated sinonasal tumours

Contains fulltext : 191237.pdf (publisher's version ) (Open Access)The sinonasal cavities harbour a variety of rare tumour types. Many carry a poor prognosis while therapeutic options are limited. Histopathological classification can be difficult, especially for poorly differentiated tumours such as olfactory neuroblastoma (ONB), sinonasal neuroendocrine carcinoma (SNEC) and sinonasal undifferentiated carcinoma (SNUC). We analysed Affymetrix OncoScan genome-wide copy number profiles of these three tumour types, both as originally diagnosed and as regrouped by their cytokeratin (Ck) and neuroendocrine (Ne) expression pattern, aiming to find a relation between phenotype and genotype. According to the original histopathological classification our series consisted of 24 ONB, 11 SNEC and 19 SNUC, while immunohistochemistry indicated 11 Ck-Ne+/ONB, 18 Ck+Ne+/SNEC, 24 Ck+Ne-/SNUC, and 1 Ck-Ne-/unclassified. As originally diagnosed, the three tumour types showed similar copy number profiles. However, when regrouped by Ck/Ne immunostaining we found a distinct set of gains and losses; Ck-Ne+/ONB harboured few and predominantly whole chromosomes abnormalities, Ck+Ne+/SNEC carried both gains and losses in high frequency, and Ck+Ne-/SNUC showed mostly gains. In addition, each tumour carried a number of unique chromosomal deletions. Genome-wide copy number profiling supports the value of immunohistochemical CkNe staining of ONB, SNEC and SNUC for tumour classification, which is important for prognosis and therapeutic decision-making

IDH2 Mutation Analysis in Undifferentiated and Poorly Differentiated Sinonasal Carcinomas for Diagnosis and Clinical Management

A large number of tumor types arise from the mucosa of the sinonasal cavities. Although presenting clinically distinct behavior, due to poorly differentiated histologic features, they can be difficult to classify correctly. Our aim was to investigate whether IDH2 and IDH1 mutations may be specific to a subset of undifferentiated and poorly differentiated sinonasal carcinomas. A total of 125 tumor samples of 7 different histologic subtypes were analyzed for IDH mutations by sequencing and mutant-specific immunohistochemistry, and the results were correlated to clinical and follow-up data. The highest incidence of IDH2 mutations occurred in sinonasal undifferentiated carcinoma, with 11/36 (31%) cases affected. However, also, 1/9 neuroendocrine carcinomas, 2/4 high-grade non-intestinal-type adenocarcinomas, and 1/8 poorly differentiated squamous cell carcinomas carried the IDH2 mutation, whereas 1/48 intestinal-type adenocarcinomas harbored an IDH1 mutation. Immunohistochemical analysis of mutant IDH1/2 produced a number of false-negative results, but also 1 false-positive tumor was found. Disease-specific survival was more favorable in IDH2-mutant versus wild-type cases. Our data suggest that IDH-mutant sinonasal cancers, independent of their histologic subtype, may represent a distinct tumor entity with less aggressive clinical behavior. Clinically, patients with these mutations may benefit from specific IDH-guided therapies

Intragenic NF1 deletions in sinonasal mucosal malignant melanoma

Mucosal malignant melanoma (MMM) is a rare and aggressive tumor. Despite effective local therapies, tumor recurrence and metastasis remain frequent. The genetics of MMM remain incompletely understood. This study is aimed to identify actionable genetic alterations by next-generation sequencing. Fifteen MMM samples were analyzed by next-generation and Sanger sequencing. Gene copy number alterations were analyzed by MLPA. Mutation status was correlated with pERK, pAKT, and Ki-67 expression and follow-up data. Inactivating mutations and intragenic deletions in neurofibromatosis type-1 (NF1) were identified in 3 and 2 cases, respectively, (in total 5/15, 33%) and activating mutations in NRAS and KRAS (3/15, 20%) cases. Other mutated genes included CDKN2A, APC, ATM, MITF, FGFR1, and FGFR2. BRAF and KIT mutations were not observed. Cases with NF1 alterations tended to have worse overall survival. The mutational status was not associated with pERK, pAKT, or Ki-67 immunostaining. MMM carries frequent gene mutations activating the MAPK pathway, similar to cutaneous melanoma. In contrast, NF1 is the most frequently affected gene. Intragenic NF1 deletions have not been described before and may go undetected by sequencing studies. This finding is clinically relevant as NF1-mutated melanomas have worse survival and could benefit from therapy with immune checkpoint and MEK inhibitors

Neddylation of phosphoenolpyruvate carboxykinase 1 controls glucose metabolism

Neddylation is a post-translational mechanism that adds a ubiquitin-like protein, namely neural precursor cell expressed developmentally downregulated protein 8 (NEDD8). Here, we show that neddylation in mouse liver is modulated by nutrient availability. Inhibition of neddylation in mouse liver reduces gluconeogenic capacity and the hyperglycemic actions of counter-regulatory hormones. Furthermore, people with type 2 diabetes display elevated hepatic neddylation levels. Mechanistically, fasting or caloric restriction of mice leads to neddylation of phosphoenolpyruvate carboxykinase 1 (PCK1) at three lysine residues—K278, K342, and K387. We find that mutating the three PCK1 lysines that are neddylated reduces their gluconeogenic activity rate. Molecular dynamics simulations show that neddylation of PCK1 could re-position two loops surrounding the catalytic center into an open configuration, rendering the catalytic center more accessible. Our study reveals that neddylation of PCK1 provides a finely tuned mechanism of controlling glucose metabolism by linking whole nutrient availability to metabolic homeostasis

Hepatic levels of S-adenosylmethionine regulate the adaptive response to fasting

There has been an intense focus to uncover the molecular mechanisms by which fasting triggers the adaptive cellular responses in the major organs of the body. Here, we show that in mice, hepatic S-adenosylmethionine (SAMe)—the principal methyl donor—acts as a metabolic sensor of nutrition to fine-tune the catabolic-fasting response by modulating phosphatidylethanolamine N-methyltransferase (PEMT) activity, endoplasmic reticulum-mitochondria contacts, β-oxidation, and ATP production in the liver, together with FGF21-mediated lipolysis and thermogenesis in adipose tissues. Notably, we show that glucagon induces the expression of the hepatic SAMe-synthesizing enzyme methionine adenosyltransferase α1 (MAT1A), which translocates to mitochondria-associated membranes. This leads to the production of this metabolite at these sites, which acts as a brake to prevent excessive β-oxidation and mitochondrial ATP synthesis and thereby endoplasmic reticulum stress and liver injury. This work provides important insights into the previously undescribed function of SAMe as a new arm of the metabolic adaptation to fasting

Hepatic levels of S-adenosylmethionine regulate the adaptive response to fasting

There has been an intense focus to uncover the molecular mechanisms by which fasting triggers the adaptive cellular responses in the major organs of the body. Here, we show that in mice, hepatic S-adenosylmethionine (SAMe)—the principal methyl donor—acts as a metabolic sensor of nutrition to fine-tune the catabolic-fasting response by modulating phosphatidylethanolamine N-methyltransferase (PEMT) activity, endoplasmic reticulum-mitochondria contacts, β-oxidation, and ATP production in the liver, together with FGF21-mediated lipolysis and thermogenesis in adipose tissues. Notably, we show that glucagon induces the expression of the hepatic SAMe-synthesizing enzyme methionine adenosyltransferase α1 (MAT1A), which translocates to mitochondria-associated membranes. This leads to the production of this metabolite at these sites, which acts as a brake to prevent excessive β-oxidation and mitochondrial ATP synthesis and thereby endoplasmic reticulum stress and liver injury. This work provides important insights into the previously undescribed function of SAMe as a new arm of the metabolic adaptation to fasting