2-Hydroxyglutarate Production, but Not Dominant Negative Function, Is Conferred by Glioma-Derived NADP+-Dependent Isocitrate Dehydrogenase Mutations

Gliomas frequently contain mutations in the cytoplasmic NADP(+)-dependent isocitrate dehydrogenase (IDH1) or the mitochondrial NADP(+)-dependent isocitrate dehydrogenase (IDH2). Several different amino acid substitutions recur at either IDH1 R132 or IDH2 R172 in glioma patients. Genetic evidence indicates that these mutations share a common gain of function, but it is unclear whether the shared function is dominant negative activity, neomorphic production of (R)-2-hydroxyglutarate (2HG), or both.We show by coprecipitation that five cancer-derived IDH1 R132 mutants bind IDH1-WT but that three cancer-derived IDH2 R172 mutants exert minimal binding to IDH2-WT. None of the mutants dominant-negatively lower isocitrate dehydrogenase activity at physiological (40 µM) isocitrate concentrations in mammalian cell lysates. In contrast to this, all of these mutants confer 10- to 100-fold higher 2HG production to cells, and glioma tissues containing IDH1 R132 or IDH2 R172 mutations contain high levels of 2HG compared to glioma tissues without IDH mutations (54.4 vs. 0.1 mg 2HG/g protein).Binding to, or dominant inhibition of, WT IDH1 or IDH2 is not a shared feature of the IDH1 and IDH2 mutations, and thus is not likely to be important in cancer. The fact that the gain of the enzymatic activity to produce 2HG is a shared feature of the IDH1 and IDH2 mutations suggests that this is an important function for these mutants in driving cancer pathogenesis

Application of holistic liquid chromatography-high resolution mass spectrometry based urinary metabolomics for prostate cancer detection and biomarker discovery

Human exhibit wide variations in their metabolic profiles because of differences in genetic factors, diet and lifestyle. Therefore in order to detect metabolic differences between individuals robust analytical methods are required. A protocol was produced based on the use of Liquid Chromatography- High Resolution Mass Spectrometry (LC-HRMS) in combination with orthogonal Hydrophilic Interaction (HILIC) and Reversed Phase (RP) liquid chromatography methods for the analysis of the urinary metabolome, which was then evaluated as a diagnostic tool for prostate cancer (a common but highly heterogeneous condition). The LC-HRMS method was found to be robust and exhibited excellent repeatability for retention times (0.9. In addition, using the receiver operator characteristics (ROC) test, the area under curve (AUC) for the combination of the four best characterised biomarker compounds was 0.896. The four biomarker compounds were also found to differ significantly (

Urinary volatile organic compounds for the detection of prostate cancer

© 2015 Khalid et al.This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. The aim of this work was to investigate volatile organic compounds (VOCs) emanating from urine samples to determine whether they can be used to classify samples into those from prostate cancer and non-cancer groups. Participants were men referred for a trans-rectal ultrasound-guided prostate biopsy because of an elevated prostate specific antigen (PSA) level or abnormal findings on digital rectal examination. Urine samples were collected from patients with prostate cancer (n = 59) and cancer-free controls (n = 43), on the day of their biopsy, prior to their procedure. VOCs from the headspace of basified urine samples were extracted using solid-phase micro-extraction and analysed by gas chromatography/mass spectrometry. Classifiers were developed using Random Forest (RF) and Linear Discriminant Analysis (LDA) classification techniques. PSA alone had an accuracy of 62-64% in these samples. A model based on 4 VOCs, 2,6-dimethyl-7-octen-2-ol, pentanal, 3-octanone, and 2-octanone, was marginally more accurate 63-65%. When combined, PSA level and these four VOCs had mean accuracies of 74% and 65%, using RF and LDA, respectively. With repeated double cross-validation, the mean accuracies fell to 71% and 65%, using RF and LDA, respectively. Results from VOC profiling of urine headspace are encouraging and suggest that there are other metabolomic avenues worth exploring which could help improve the stratification of men at risk of prostate cancer. This study also adds to our knowledge on the profile of compounds found in basified urine, from controls and cancer patients, which is useful information for future studies comparing the urine from patients with other disease states

Identification of Metabolites in the Normal Ovary and Their Transformation in Primary and Metastatic Ovarian Cancer

In this study, we characterized the metabolome of the human ovary and identified metabolic alternations that coincide with primary epithelial ovarian cancer (EOC) and metastatic tumors resulting from primary ovarian cancer (MOC) using three analytical platforms: gas chromatography mass spectrometry (GC/MS) and liquid chromatography tandem mass spectrometry (LC/MS/MS) using buffer systems and instrument settings to catalog positive or negative ions. The human ovarian metabolome was found to contain 364 biochemicals and upon transformation of the ovary caused changes in energy utilization, altering metabolites associated with glycolysis and β-oxidation of fatty acids—such as carnitine (1.79 fold in EOC, p<0.001; 1.88 fold in MOC, p<0.001), acetylcarnitine (1.75 fold in EOC, p<0.001; 2.39 fold in MOC, p<0.001), and butyrylcarnitine (3.62 fold, p<0.0094 in EOC; 7.88 fold, p<0.001 in MOC). There were also significant changes in phenylalanine catabolism marked by increases in phenylpyruvate (4.21 fold; p = 0.0098) and phenyllactate (195.45 fold; p<0.0023) in EOC. Ovarian cancer also displayed an enhanced oxidative stress response as indicated by increases in 2-aminobutyrate in EOC (1.46 fold, p = 0.0316) and in MOC (2.25 fold, p<0.001) and several isoforms of tocopherols. We have also identified novel metabolites in the ovary, specifically N-acetylasparate and N-acetyl-aspartyl-glutamate, whose role in ovarian physiology has yet to be determined. These data enhance our understanding of the diverse biochemistry of the human ovary and demonstrate metabolic alterations upon transformation. Furthermore, metabolites with significant changes between groups provide insight into biochemical consequences of transformation and are candidate biomarkers of ovarian oncogenesis. Validation studies are warranted to determine whether these compounds have clinical utility in the diagnosis or clinical management of ovarian cancer patients

Cildb: a knowledgebase for centrosomes and cilia

Ciliopathies, pleiotropic diseases provoked by defects in the structure or function of cilia or flagella, reflect the multiple roles of cilia during development, in stem cells, in somatic organs and germ cells. High throughput studies have revealed several hundred proteins that are involved in the composition, function or biogenesis of cilia. The corresponding genes are potential candidates for orphan ciliopathies. To study ciliary genes, model organisms are used in which particular questions on motility, sensory or developmental functions can be approached by genetics. In the course of high throughput studies of cilia in Paramecium tetraurelia, we were confronted with the problem of comparing our results with those obtained in other model organisms. We therefore developed a novel knowledgebase, Cildb, that integrates ciliary data from heterogeneous sources. Cildb links orthology relationships among 18 species to high throughput ciliary studies, and to OMIM data on human hereditary diseases. The web interface of Cildb comprises three tools, BioMart for complex queries, BLAST for sequence homology searches and GBrowse for browsing the human genome in relation to OMIM information for human diseases. Cildb can be used for interspecies comparisons, building candidate ciliary proteomes in any species, or identifying candidate ciliopathy genes

Precision medicine driven by cancer systems biology

Molecular insights from genome and systems biology are influencing how cancer is diagnosed and treated. We critically evaluate big data challenges in precision medicine. The melanoma research community has identified distinct subtypes involving chronic sun-induced damage and the mitogen-activated protein kinase driver pathway. In addition, despite low mutation burden, non-genomic mitogen-activated protein kinase melanoma drivers are found in membrane receptors, metabolism, or epigenetic signaling with the ability to bypass central mitogen-activated protein kinase molecules and activating a similar program of mitogenic effectors. Mutation hotspots, structural modeling, UV signature, and genomic as well as non-genomic mechanisms of disease initiation and progression are taken into consideration to identify resistance mutations and novel drug targets. A comprehensive precision medicine profile of a malignant melanoma patient illustrates future rational drug targeting strategies. Network analysis emphasizes an important role of epigenetic and metabolic master regulators in oncogenesis. Co-occurrence of driver mutations in signaling, metabolic, and epigenetic factors highlights how cumulative alterations of our genomes and epigenomes progressively lead to uncontrolled cell proliferation. Precision insights have the ability to identify independent molecular pathways suitable for drug targeting. Synergistic treatment combinations of orthogonal modalities including immunotherapy, mitogen-activated protein kinase inhibitors, epigenetic inhibitors, and metabolic inhibitors have the potential to overcome immune evasion, side effects, and drug resistance