Unsuspected task for an old team: Succinate, fumarate and other Krebs cycle acids in metabolic remodeling

AbstractSeventy years from the formalization of the Krebs cycle as the central metabolic turntable sustaining the cell respiratory process, key functions of several of its intermediates, especially succinate and fumarate, have been recently uncovered. The presumably immutable organization of the cycle has been challenged by a number of observations, and the variable subcellular location of a number of its constitutive protein components is now well recognized, although yet unexplained. Nonetheless, the most striking observations have been made in the recent period while investigating human diseases, especially a set of specific cancers, revealing the crucial role of Krebs cycle intermediates as factors affecting genes methylation and thus cell remodeling. We review here the recent advances and persisting incognita about the role of Krebs cycle acids in diverse aspects of cellular life and human pathology

Rapid determination of tricarboxylic acid cycle enzyme activities in biological samples

<p>Abstract</p> <p>Background</p> <p>In the last ten years, deficiencies in tricarboxylic acid cycle (TCAC) enzymes have been shown to cause a wide spectrum of human diseases, including malignancies and neurological and cardiac diseases. A prerequisite to the identification of disease-causing TCAC enzyme deficiencies is the availability of effective enzyme assays.</p> <p>Results</p> <p>We developed three assays that measure the full set of TCAC enzymes. One assay relies on the sequential addition of reagents to measure succinyl-CoA ligase activity, followed by succinate dehydrogenase, fumarase and, finally, malate dehydrogenase. Another assay measures the activity of α-ketoglutarate dehydrogenase followed by aconitase and isocitrate dehydrogenase. The remaining assay measures citrate synthase activity using a standard procedure. We used these assays successfully on extracts of small numbers of human cells displaying various severe or partial TCAC deficiencies and on frozen heart homogenates from heterozygous mice harboring an SDHB gene deletion.</p> <p>Conclusion</p> <p>This set of assays is rapid and simple to use and can immediately detect even partial defects, as the activity of each enzyme can be readily compared with one or more other activities measured in the same sample.</p

In Vivo Detection of Succinate by Magnetic Resonance Spectroscopy as a Hallmark of SDHx Mutations in Paraganglioma

International audiencePurpose: Germline mutations in genes encoding mitochon-drial succinate dehydrogenase (SDH) are found in patients with paragangliomas, pheochromocytomas, gastrointestinal stromal tumors, and renal cancers. SDH inactivation leads to a massive accumulation of succinate, acting as an oncometabolite and which levels, assessed on surgically resected tissue are a highly specific biomarker of SDHx-mutated tumors. The aim of this study was to address the feasibility of detecting succinate in vivo by magnetic resonance spectroscopy. Experimental Design: A pulsed proton magnetic resonance spectroscopy (1 H-MRS) sequence was developed, optimized, and applied to image nude mice grafted with Sdhb À/À or wild-type chromaffin cells. The method was then applied to patients with paraganglioma carrying (n ¼ 5) or not (n ¼ 4) an SDHx gene mutation. Following surgery, succinate was measured using gas chromatography/mass spectrometry, and SDH protein expression was assessed by immunohistochemistry in resected tumors. Results: A succinate peak was observed at 2.44 ppm by 1 H-MRS in all Sdhb À/À-derived tumors in mice and in all paragangliomas of patients carrying an SDHx gene mutation, but neither in wild-type mouse tumors nor in patients exempt of SDHx mutation. In one patient, 1 H-MRS results led to the identification of an unsus-pected SDHA gene mutation. In another case, it helped define the pathogenicity of a variant of unknown significance in the SDHB gene. Conclusions: Detection of succinate by 1 H-MRS is a highly specific and sensitive hallmark of SDHx mutations. This non-invasive approach is a simple and robust method allowing in vivo detection of the major biomarker of SDHx-mutated tumors. Clin Cancer Res; 22(5); 1120–9. Ó2015 AACR

Association of adrenal steroids with metabolomic profiles in patients with primary and endocrine hypertension

Introduction: Endocrine hypertension (EHT) due to pheochromocytoma/paraganglioma (PPGL), Cushing’s syndrome (CS), or primary aldosteronism (PA) is linked to a variety of metabolic alterations and comorbidities. Accordingly, patients with EHT and primary hypertension (PHT) are characterized by distinct metabolic profiles. However, it remains unclear whether the metabolomic differences relate solely to the disease-defining hormonal parameters. Therefore, our objective was to study the association of disease defining hormonal excess and concomitant adrenal steroids with metabolomic alterations in patients with EHT. Methods: Retrospective European multicenter study of 263 patients (mean age 49 years, 50% females; 58 PHT, 69 PPGL, 37 CS, 99 PA) in whom targeted metabolomic and adrenal steroid profiling was available. The association of 13 adrenal steroids with differences in 79 metabolites between PPGL, CS, PA and PHT was examined after correction for age, sex, BMI, and presence of diabetes mellitus. Results: After adjustment for BMI and diabetes mellitus significant association between adrenal steroids and metabolites – 18 in PPGL, 15 in CS, and 23 in PA – were revealed. In PPGL, the majority of metabolite associations were linked to catecholamine excess, whereas in PA, only one metabolite was associated with aldosterone. In contrast, cortisone (16 metabolites), cortisol (6 metabolites), and DHEA (8 metabolites) had the highest number of associated metabolites in PA. In CS, 18-hydroxycortisol significantly influenced 5 metabolites, cortisol affected 4, and cortisone, 11-deoxycortisol, and DHEA each were linked to 3 metabolites. Discussions: Our study indicates cortisol, cortisone, and catecholamine excess are significantly associated with metabolomic variances in EHT versus PHT patients. Notably, catecholamine excess is key to PPGL’s metabolomic changes, whereas in PA, other non-defining adrenal steroids mainly account for metabolomic differences. In CS, cortisol, alongside other non-defining adrenal hormones, contributes to these differences, suggesting that metabolic disorders and cardiovascular morbidity in these conditions could also be affected by various adrenal steroids.</p

Association of adrenal steroids with metabolomic profiles in patients with primary and endocrine hypertension

Introduction: Endocrine hypertension (EHT) due to pheochromocytoma/paraganglioma (PPGL), Cushing’s syndrome (CS), or primary aldosteronism (PA) is linked to a variety of metabolic alterations and comorbidities. Accordingly, patients with EHT and primary hypertension (PHT) are characterized by distinct metabolic profiles. However, it remains unclear whether the metabolomic differences relate solely to the disease-defining hormonal parameters. Therefore, our objective was to study the association of disease defining hormonal excess and concomitant adrenal steroids with metabolomic alterations in patients with EHT. Methods: Retrospective European multicenter study of 263 patients (mean age 49 years, 50% females; 58 PHT, 69 PPGL, 37 CS, 99 PA) in whom targeted metabolomic and adrenal steroid profiling was available. The association of 13 adrenal steroids with differences in 79 metabolites between PPGL, CS, PA and PHT was examined after correction for age, sex, BMI, and presence of diabetes mellitus. Results: After adjustment for BMI and diabetes mellitus significant association between adrenal steroids and metabolites – 18 in PPGL, 15 in CS, and 23 in PA – were revealed. In PPGL, the majority of metabolite associations were linked to catecholamine excess, whereas in PA, only one metabolite was associated with aldosterone. In contrast, cortisone (16 metabolites), cortisol (6 metabolites), and DHEA (8 metabolites) had the highest number of associated metabolites in PA. In CS, 18-hydroxycortisol significantly influenced 5 metabolites, cortisol affected 4, and cortisone, 11-deoxycortisol, and DHEA each were linked to 3 metabolites. Discussions: Our study indicates cortisol, cortisone, and catecholamine excess are significantly associated with metabolomic variances in EHT versus PHT patients. Notably, catecholamine excess is key to PPGL’s metabolomic changes, whereas in PA, other non-defining adrenal steroids mainly account for metabolomic differences. In CS, cortisol, alongside other non-defining adrenal hormones, contributes to these differences, suggesting that metabolic disorders and cardiovascular morbidity in these conditions could also be affected by various adrenal steroids.</p

Loss of succinate dehydrogenase activity results in dependency on pyruvate carboxylation for cellular anabolism

The tricarboxylic acid (TCA) cycle is a central metabolic pathway responsible for supplying reducing potential for oxidative phosphorylation and anabolic substrates for cell growth, repair and proliferation. As such it thought to be essential for cell proliferation and tissue homeostasis. However, since the initial report of an inactivating mutation in the TCA cycle enzyme complex, succinate dehydrogenase (SDH) in paraganglioma (PGL), it has become clear that some cells and tissues are not only able to survive with a truncated TCA cycle, but that they are also able of supporting proliferative phenotype observed in tumours. Here, we show that loss of SDH activity leads to changes in the metabolism of non-essential amino acids. In particular, we demonstrate that pyruvate carboxylase is essential to re-supply the depleted pool of aspartate in SDH-deficient cells. Our results demonstrate that the loss of SDH reduces the metabolic plasticity of cells, suggesting vulnerabilities that can be targeted therapeutically

Targeted metabolomics as a tool in discriminating endocrine from primary hypertension

Context Identification of patients with endocrine forms of hypertension (EHT) (primary hyperaldosteronism [PA], pheochromocytoma/paraganglioma [PPGL], and Cushing syndrome [CS]) provides the basis to implement individualized therapeutic strategies. Targeted metabolomics (TM) have revealed promising results in profiling cardiovascular diseases and endocrine conditions associated with hypertension. Objective Use TM to identify distinct metabolic patterns between primary hypertension (PHT) and EHT and test its discriminating ability. Methods Retrospective analyses of PHT and EHT patients from a European multicenter study (ENSAT-HT). TM was performed on stored blood samples using liquid chromatography mass spectrometry. To identify discriminating metabolites a “classical approach” (CA) (performing a series of univariate and multivariate analyses) and a “machine learning approach” (MLA) (using random forest) were used. The study included 282 adult patients (52% female; mean age 49 years) with proven PHT (n = 59) and EHT (n = 223 with 40 CS, 107 PA, and 76 PPGL), respectively. Results From 155 metabolites eligible for statistical analyses, 31 were identified discriminating between PHT and EHT using the CA and 27 using the MLA, of which 16 metabolites (C9, C16, C16:1, C18:1, C18:2, arginine, aspartate, glutamate, ornithine, spermidine, lysoPCaC16:0, lysoPCaC20:4, lysoPCaC24:0, PCaeC42:0, SM C18:1, SM C20:2) were found by both approaches. The receiver operating characteristic curve built on the top 15 metabolites from the CA provided an area under the curve (AUC) of 0.86, which was similar to the performance of the 15 metabolites from MLA (AUC 0.83). Conclusion TM identifies distinct metabolic pattern between PHT and EHT providing promising discriminating performance

Integrative genomic analysis reveals somatic mutations in pheochromocytoma and

Pheochromocytomas and paragangliomas are neuroendocrine tumors that occur in the context of inherited cancer syndromes in ∼30% of cases and are linked to germline mutations in the VHL, RET, NF1, SDHA, SDHB, SDHC, SDHD, SDHAF2 and TMEM127 genes. Although genome-wide expression studies have revealed some of the mechanisms likely to be involved in pheochromocytoma/paraganglioma tumorigenesis, the complete molecular distinction of all subtypes of hereditary tumors has not been solved and the genetic events involved in the generation of sporadic tumors are unknown. With these purposes in mind, we investigated 202 pheochromocytomas/paragangliomas, including 75 hereditary tumors, using expression profiling, BAC array comparative genomic hybridization and somatic mutation screening. Gene expression signatures defined the hereditary tumors according to their genotype and notably, led to a complete subseparation between SDHx-and VHL-related tumors. In tumor tissues, the systematic characterization of somatic genetic events associated with germline mutations in tumor suppressor genes revealed loss of heterozygosity (LOH) in a majority of cases, but also detected point mutations and copy-neutral LOH. Finally, guided by transcriptome classifications and LOH profiles, somatic mutations in VHL or RET genes were identified in 14% of sporadic pheochromocytomas/paragangliomas. Overall, we found a germline or somatic genetic alteration in 45.5% (92/202) of the tumors in this large series of pheochromocytomas/paragangliomas. Regarding mutated genes, specific molecular pathways involved in tumorigenesis mechanisms are identified. Altogether, these new findings suggest that somatic mutation analysis is likely to yield important clues for personalizing molecular targeted therapies

International initiative for a curated SDHB variant database improving the diagnosis of hereditary paraganglioma and pheochromocytoma

Funder: Cancer Research UK Cambridge Cancer CentreBackground: SDHB is one of the major genes predisposing to paraganglioma/pheochromocytoma (PPGL). Identifying pathogenic SDHB variants in patients with PPGL is essential to the management of patients and relatives due to the increased risk of recurrences, metastases and the emergence of non-PPGL tumours. In this context, the ‘NGS and PPGL (NGSnPPGL) Study Group’ initiated an international effort to collect, annotate and classify SDHB variants and to provide an accurate, expert-curated and freely available SDHB variant database. Methods: A total of 223 distinct SDHB variants from 737 patients were collected worldwide. Using multiple criteria, each variant was first classified according to a 5-tier grouping based on American College of Medical Genetics and NGSnPPGL standardised recommendations and was then manually reviewed by a panel of experts in the field. Results: This multistep process resulted in 23 benign/likely benign, 149 pathogenic/likely pathogenic variants and 51 variants of unknown significance (VUS). Expert curation reduced by half the number of variants initially classified as VUS. Variant classifications are publicly accessible via the Leiden Open Variation Database system (https://databases.lovd.nl/shared/genes/SDHB). Conclusion: This international initiative by a panel of experts allowed us to establish a consensus classification for 223 SDHB variants that should be used as a routine tool by geneticists in charge of PPGL laboratory diagnosis. This accurate classification of SDHB genetic variants will help to clarify the diagnosis of hereditary PPGL and to improve the clinical care of patients and relatives with PPGL

Whole blood methylome-derived features to discriminate endocrine hypertension

Background: Arterial hypertension represents a worldwide health burden and a major risk factor for cardiovascular morbidity and mortality. Hypertension can be primary (primary hypertension, PHT), or secondary to endocrine disorders (endocrine hypertension, EHT), such as Cushing's syndrome (CS), primary aldosteronism (PA), and pheochromocytoma/paraganglioma (PPGL). Diagnosis of EHT is currently based on hormone assays. Efficient detection remains challenging, but is crucial to properly orientate patients for diagnostic confirmation and specific treatment. More accurate biomarkers would help in the diagnostic pathway. We hypothesized that each type of endocrine hypertension could be associated with a specific blood DNA methylation signature, which could be used for disease discrimination. To identify such markers, we aimed at exploring the methylome profiles in a cohort of 255 patients with hypertension, either PHT (n = 42) or EHT (n = 213), and at identifying specific discriminating signatures using machine learning approaches. Results: Unsupervised classification of samples showed discrimination of PHT from EHT. CS patients clustered separately from all other patients, whereas PA and PPGL showed an overall overlap. Global methylation was decreased in the CS group compared to PHT. Supervised comparison with PHT identified differentially methylated CpG sites for each type of endocrine hypertension, showing a diffuse genomic location. Among the most differentially methylated genes, FKBP5 was identified in the CS group. Using four different machine learning methods—Lasso (Least Absolute Shrinkage and Selection Operator), Logistic Regression, Random Forest, and Support Vector Machine—predictive models for each type of endocrine hypertension were built on training cohorts (80% of samples for each hypertension type) and estimated on validation cohorts (20% of samples for each hypertension type). Balanced accuracies ranged from 0.55 to 0.74 for predicting EHT, 0.85 to 0.95 for predicting CS, 0.66 to 0.88 for predicting PA, and 0.70 to 0.83 for predicting PPGL. Conclusions: The blood DNA methylome can discriminate endocrine hypertension, with methylation signatures for each type of endocrine disorder