Proteomic profiling of adipose tissue from Zmpste24(-/-) Mice, a model of Lipodystrophy and premature aging, reveals major changes in mitochondrial function and vimentin processing

Lipodystrophy is a major disease involving severe alterations of adipose tissue distribution and metabolism. Mutations in genes encoding the nuclear envelope protein lamin A or its processing enzyme, the metalloproteinase Zmpste24, cause diverse human progeroid syndromes that are commonly characterized by a selective loss of adipose tissue. Similarly to humans, mice deficient in Zmpste24 accumulate prelamin A and display phenotypic features of accelerated aging, including lipodystrophy. Herein, we report the proteome and phosphoproteome of adipose tissue as well as serum metabolome in lipodystrophy by using Zmpste24(-/-) mice as experimental model. We show that Zmpste24 deficiency enhanced lipolysis, fatty acid biogenesis and β-oxidation as well as decreased fatty acid re-esterification, thus pointing to an increased partitioning of fatty acid toward β-oxidation and away from storage that likely underlies the observed size reduction of Zmpste24-null adipocytes. Besides the mitochondrial proteins related to lipid metabolism, other protein networks related to mitochondrial function, including those involved in tricarboxylic acid cycle and oxidative phosphorylation, were up-regulated in Zmpste24(-/-) mice. These results, together with the observation of an increased mitochondrial response to oxidative stress, support the relationship between defective prelamin A processing and mitochondrial dysfunction and highlight the relevance of oxidative damage in lipoatrophy and aging. We also show that absence of Zmpste24 profoundly alters the processing of the cytoskeletal protein vimentin and identify a novel protein dysregulated in lipodystrophy, High-Mobility Group Box-1 Protein. Finally, we found several lipid derivates with important roles in energy balance, such as Lysophosphatidylcholine or 2-arachidonoylglycerol, to be dysregulated in Zmpste24(-/-) serum. Together, our findings in Zmpste24(-/-) mice may be useful to unveil the mechanisms underlying adipose tissue dysfunction and its overall contribution to body homeostasis in progeria and other lipodystrophy syndromes as well as to develop novel strategies to prevent or ameliorate these diseases

A novel serum metabolomic profile for the differential diagnosis of distal cholangiocarcinoma and pancreatic ductal adenocarcinoma

The diagnosis of adenocarcinomas located in the pancreas head, i.e., distal cholangiocarcinoma (dCCA) and pancreatic ductal adenocarcinoma (PDAC), constitutes a clinical challenge because they share many symptoms, are not easily distinguishable using imaging techniques and accurate biomarkers are not available. Searching for biomarkers with potential usefulness in the differential diagnosis of these tumors, we have determined serum metabolomic profiles in healthy controls and patients with dCCA, PDAC or benign pancreatic diseases (BPD). Ultra-high-performance liquid chromatography coupled to mass spectrometry (UHPLC-MS) analysis was performed in serum samples from dCCA (n = 34), PDAC (n = 38), BPD (n = 42) and control (n = 25) individuals, divided into discovery and validation cohorts. This approach permitted 484 metabolites to be determined, mainly lipids and amino acids. The analysis of the results led to the proposal of a logistic regression model able to discriminate patients with dCCA and PDAC (AUC value of 0.888) based on the combination of serum levels of nine metabolites (acylcarnitine AC(16:0), ceramide Cer(d18:1/24:0), phosphatidylcholines PC(20:0/0:0) and PC(O-16:0/20:3), lysophosphatidylcholines PC(20:0/0:0) and PC(0:0/20:0), lysophosphatidylethanolamine PE(P-18:2/0:0), and sphingomyelins SM(d18:2/22:0) and SM(d18:2/23:0)) and CA 19-9. In conclusion, we propose a novel specific panel of serum metabolites that can help in the differential diagnosis of dCCA and PDAC. Further validation of their clinical usefulness in prospective studies is required

A novel serum metabolomic profile for the differential diagnosis of distal cholangiocarcinoma and pancreatic ductal adenocarcinoma

The diagnosis of adenocarcinomas located in the pancreas head, i.e., distal cholangiocarcinoma (dCCA) and pancreatic ductal adenocarcinoma (PDAC), constitutes a clinical challenge because they share many symptoms, are not easily distinguishable using imaging techniques and accurate biomarkers are not available. Searching for biomarkers with potential usefulness in the differential diagnosis of these tumors, we have determined serum metabolomic profiles in healthy controls and patients with dCCA, PDAC or benign pancreatic diseases (BPD). Ultra-high-performance liquid chromatography coupled to mass spectrometry (UHPLC-MS) analysis was performed in serum samples from dCCA (n = 34), PDAC (n = 38), BPD (n = 42) and control (n = 25) individuals, divided into discovery and validation cohorts. This approach permitted 484 metabolites to be determined, mainly lipids and amino acids. The analysis of the results led to the proposal of a logistic regression model able to discriminate patients with dCCA and PDAC (AUC value of 0.888) based on the combination of serum levels of nine metabolites (acylcarnitine AC(16:0), ceramide Cer(d18:1/24:0), phosphatidylcholines PC(20:0/0:0) and PC(O-16:0/20:3), lysophosphatidylcholines PC(20:0/0:0) and PC(0:0/20:0), lysophosphatidylethanolamine PE(P-18:2/0:0), and sphingomyelins SM(d18:2/22:0) and SM(d18:2/23:0)) and CA 19-9. In conclusion, we propose a novel specific panel of serum metabolites that can help in the differential diagnosis of dCCA and PDAC. Further validation of their clinical usefulness in prospective studies is required

A novel serum metabolomic profile for the differential diagnosis of distal cholangiocarcinoma and pancreatic ductal adenocarcinoma

The diagnosis of adenocarcinomas located in the pancreas head, i.e., distal cholangiocarcinoma (dCCA) and pancreatic ductal adenocarcinoma (PDAC), constitutes a clinical challenge because they share many symptoms, are not easily distinguishable using imaging techniques and accurate biomarkers are not available. Searching for biomarkers with potential usefulness in the differential diagnosis of these tumors, we have determined serum metabolomic profiles in healthy controls and patients with dCCA, PDAC or benign pancreatic diseases (BPD). Ultra-high-performance liquid chromatography coupled to mass spectrometry (UHPLC-MS) analysis was performed in serum samples from dCCA (n = 34), PDAC (n = 38), BPD (n = 42) and control (n = 25) individuals, divided into discovery and validation cohorts. This approach permitted 484 metabolites to be determined, mainly lipids and amino acids. The analysis of the results led to the proposal of a logistic regression model able to discriminate patients with dCCA and PDAC (AUC value of 0.888) based on the combination of serum levels of nine metabolites (acylcarnitine AC(16:0), ceramide Cer(d18:1/24:0), phosphatidylcholines PC(20:0/0:0) and PC(O-16:0/20:3), lysophosphatidylcholines PC(20:0/0:0) and PC(0:0/20:0), lysophosphatidylethanolamine PE(P-18:2/0:0), and sphingomyelins SM(d18:2/22:0) and SM(d18:2/23:0)) and CA 19-9. In conclusion, we propose a novel specific panel of serum metabolites that can help in the differential diagnosis of dCCA and PDAC. Further validation of their clinical usefulness in prospective studies is required

A novel serum metabolomic profile for the differential diagnosis of distal cholangiocarcinoma and pancreatic ductal adenocarcinoma

The diagnosis of adenocarcinomas located in the pancreas head, i.e., distal cholangiocarcinoma (dCCA) and pancreatic ductal adenocarcinoma (PDAC), constitutes a clinical challenge because they share many symptoms, are not easily distinguishable using imaging techniques and accurate biomarkers are not available. Searching for biomarkers with potential usefulness in the differential diagnosis of these tumors, we have determined serum metabolomic profiles in healthy controls and patients with dCCA, PDAC or benign pancreatic diseases (BPD). Ultra-high-performance liquid chromatography coupled to mass spectrometry (UHPLC-MS) analysis was performed in serum samples from dCCA (n = 34), PDAC (n = 38), BPD (n = 42) and control (n = 25) individuals, divided into discovery and validation cohorts. This approach permitted 484 metabolites to be determined, mainly lipids and amino acids. The analysis of the results led to the proposal of a logistic regression model able to discriminate patients with dCCA and PDAC (AUC value of 0.888) based on the combination of serum levels of nine metabolites (acylcarnitine AC(16:0), ceramide Cer(d18:1/24:0), phosphatidylcholines PC(20:0/0:0) and PC(O-16:0/20:3), lysophosphatidylcholines PC(20:0/0:0) and PC(0:0/20:0), lysophosphatidylethanolamine PE(P-18:2/0:0), and sphingomyelins SM(d18:2/22:0) and SM(d18:2/23:0)) and CA 19-9. In conclusion, we propose a novel specific panel of serum metabolites that can help in the differential diagnosis of dCCA and PDAC. Further validation of their clinical usefulness in prospective studies is required

Serum metabolites as diagnostic biomarkers for cholangiocarcinoma, hepatocellular carcinoma and primary sclerosing cholangitis

Early and differential diagnosis of intrahepatic cholangiocarcinoma (iCCA) and hepatocellular carcinoma (HCC) by noninvasive methods represents a current clinical challenge. The analysis of low-molecular-weight metabolites by new high-throughput techniques is a strategy for identifying biomarkers. Here, we have investigated whether serum metabolome can provide useful biomarkers in the diagnosis of iCCA and HCC and could discriminate iCCA from HCC. Because primary sclerosing cholangitis (PSC) is a risk factor for CCA, serum metabolic profiles of PSC and CCA have also been compared. The analysis of the levels of lipids and amino acids in the serum of patients with iCCA, HCC, and PSC and healthy individuals (n = 20/group) showed differential profiles. Several metabolites presented high diagnostic value for iCCA versus control, HCC versus control, and PSC versus control, with areas under the receiver operating characteristic curve (AUC) greater than those found in serum for the nonspecific tumor markers carbohydrate antigen 19-9 (CA 19-9) and alpha-fetoprotein (AFP), commonly used to help in the diagnosis of iCCA and HCC, respectively. The development of an algorithm combining glycine, aspartic acid, SM(42:3), and SM(43:2) permitted to accurately differentiate in the diagnosis of both types of tumors (biopsy-proven). The proposed model yielded 0.890 AUC, 75% sensitivity, and 90% specificity. Another algorithm by combination of PC(34:3) and histidine accurately permitted to differentiate PSC from iCCA, with an AUC of 0.990, 100% sensitivity, and 70% specificity. These results were validated in independent cohorts of 14-15 patients per group and compared with profiles found in patients with nonalcoholic fatty liver disease/nonalcoholic steatohepatitis. Conclusion: Specific changes in serum concentrations of certain metabolites are useful to differentiate iCCA from HCC or PSC, and could help in the early diagnosis of these diseases

SUMOylation regulates LKB1 localization and its oncogenic activity in liver cancer.

BACKGROUND: Even though liver kinase B1 (LKB1) is usually described as a tumor suppressor in a wide variety of tissues, it has been shown that LKB1 aberrant expression is associated with bad prognosis in Hepatocellular Carcinoma (HCC). METHODS: Herein we have overexpressed LKB1 in human hepatoma cells and by using histidine pull-down assay we have investigated the role of the hypoxia-related post-translational modification of Small Ubiquitin-related Modifier (SUMO)ylation in the regulation of LKB1 oncogenic role. Molecular modelling between LKB1 and its interactors, involved in regulation of LKB1 nucleocytoplasmic shuttling and LKB1 activity, was performed. Finally, high affinity SUMO binding entities-based technology were used to validate our findings in a pre-clinical mouse model and in clinical HCC. FINDINGS: We found that in human hepatoma cells under hypoxic stress, LKB1 overexpression increases cell viability and aggressiveness in association with changes in LKB1 cellular localization. Moreover, by using site-directed mutagenesis, we have shown that LKB1 is SUMOylated by SUMO-2 at Lys178 hampering LKB1 nucleocytoplasmic shuttling and fueling hepatoma cell growth. Molecular modelling of SUMO modified LKB1 further confirmed steric impedance between SUMOylated LKB1 and the STe20-Related ADaptor cofactor (STRAD¿), involved in LKB1 export from the nucleus. Finally, we provide evidence that endogenous LKB1 is modified by SUMO in pre-clinical mouse models of HCC and clinical HCC, where LKB1 SUMOylation is higher in fast growing tumors. INTERPRETATION: Overall, SUMO-2 modification of LKB1 at Lys178 mediates LKB1 cellular localization and its oncogenic role in liver cancer. FUND: This work was supported by grants from NIH (US Department of Health and Human services)-R01AR001576-11A1 (J.M.M and M.L.M-C.), Gobierno Vasco-Departamento de Salud 2013111114 (to M.L.M.-C), ELKARTEK 2016, Departamento de Industria del Gobierno Vasco (to M.L.M.-C), MINECO: SAF2017-87301-R and SAF2014-52097-R integrado en el Plan Estatal de Investigación Cientifica y Técnica y Innovación 2013-2016 cofinanciado con Fondos FEDER (to M.L.M.-C and J.M.M., respectively), BFU2015-71017/BMC MINECO/FEDER, EU (to A.D.Q. and I.D.M.), BIOEF (Basque Foundation for Innovation and Health Research): EITB Maratoia BIO15/CA/014; Instituto de Salud Carlos III:PIE14/00031, integrado en el Plan Estatal de Investigación Cientifica y Técnica y Innovacion 2013-2016 cofinanciado con Fondos FEDER (to M.L.M.-C and J.M.M), Asociación Española contra el Cáncer (T.C.D, P·F-T and M.L.M-C), Daniel Alagille award from EASL (to T.C.D), Fundación Científica de la Asociación Española Contra el Cancer (AECC Scientific Foundation) Rare Tumor Calls 2017 (to M.L.M and M.A), La Caixa Foundation Program (to M.L.M), Programma di Ricerca Regione-Università 2007-2009 and 2011-2012, Regione Emilia-Romagna (to E.V.), Ramón Areces Foundation and the Andalusian Government (BIO-198) (A.D.Q. and I.D.M.), ayudas para apoyar grupos de investigación del sistema Universitario Vasco IT971-16 (P.A.), MINECO:SAF2015-64352-R (P.A.), Institut National du Cancer, FRANCE, INCa grant PLBIO16-251 (M.S.R.), MINECO - BFU2016-76872-R to (E.B.). Work produced with the support of a 2017 Leonardo Grant for Researchers and Cultural Creators, BBVA Foundation (M.V-R). Finally, Ciberehd_ISCIII_MINECO is funded by the Instituto de Salud Carlos III. We thank MINECO for the Severo Ochoa Excellence Accreditation to CIC bioGUNE (SEV-2016-0644). Funding sources had no involvement in study design; in the collection, analysis, and interpretation of data; in the writing of the report; and in the decision to submit the paper for publication

Serum metabolites as diagnostic biomarkers for cholangiocarcinoma, hepatocellular carcinoma and primary sclerosing cholangitis

Early and differential diagnosis of intrahepatic cholangiocarcinoma (iCCA) and hepatocellular carcinoma (HCC) by noninvasive methods represents a current clinical challenge. The analysis of low-molecular-weight metabolites by new high-throughput techniques is a strategy for identifying biomarkers. Here, we have investigated whether serum metabolome can provide useful biomarkers in the diagnosis of iCCA and HCC and could discriminate iCCA from HCC. Because primary sclerosing cholangitis (PSC) is a risk factor for CCA, serum metabolic profiles of PSC and CCA have also been compared. The analysis of the levels of lipids and amino acids in the serum of patients with iCCA, HCC, and PSC and healthy individuals (n = 20/group) showed differential profiles. Several metabolites presented high diagnostic value for iCCA versus control, HCC versus control, and PSC versus control, with areas under the receiver operating characteristic curve (AUC) greater than those found in serum for the nonspecific tumor markers carbohydrate antigen 19-9 (CA 19-9) and alpha-fetoprotein (AFP), commonly used to help in the diagnosis of iCCA and HCC, respectively. The development of an algorithm combining glycine, aspartic acid, SM(42:3), and SM(43:2) permitted to accurately differentiate in the diagnosis of both types of tumors (biopsy-proven). The proposed model yielded 0.890 AUC, 75% sensitivity, and 90% specificity. Another algorithm by combination of PC(34:3) and histidine accurately permitted to differentiate PSC from iCCA, with an AUC of 0.990, 100% sensitivity, and 70% specificity. These results were validated in independent cohorts of 14-15 patients per group and compared with profiles found in patients with nonalcoholic fatty liver disease/nonalcoholic steatohepatitis. Conclusion: Specific changes in serum concentrations of certain metabolites are useful to differentiate iCCA from HCC or PSC, and could help in the early diagnosis of these diseases