Clinical Efficacy of ONC201 in H3K27M-Mutant Diffuse Midline Gliomas Is Driven by Disruption of Integrated Metabolic and Epigenetic Pathways.

Patients with H3K27M-mutant diffuse midline glioma (DMG) have no proven effective therapies. ONC201 has recently demonstrated efficacy in these patients, but the mechanism behind this finding remains unknown. We assessed clinical outcomes, tumor sequencing, and tissue/cerebrospinal fluid (CSF) correlate samples from patients treated in two completed multisite clinical studies. Patients treated with ONC201 following initial radiation but prior to recurrence demonstrated a median overall survival of 21.7 months, whereas those treated after recurrence had a median overall survival of 9.3 months. Radiographic response was associated with increased expression of key tricarboxylic acid cycle-related genes in baseline tumor sequencing. ONC201 treatment increased 2-hydroxyglutarate levels in cultured H3K27M-DMG cells and patient CSF samples. This corresponded with increases in repressive H3K27me3 in vitro and in human tumors accompanied by epigenetic downregulation of cell cycle regulation and neuroglial differentiation genes. Overall, ONC201 demonstrates efficacy in H3K27M-DMG by disrupting integrated metabolic and epigenetic pathways and reversing pathognomonic H3K27me3 reduction. SIGNIFICANCE: The clinical, radiographic, and molecular analyses included in this study demonstrate the efficacy of ONC201 in H3K27M-mutant DMG and support ONC201 as the first monotherapy to improve outcomes in H3K27M-mutant DMG beyond radiation. Mechanistically, ONC201 disrupts integrated metabolic and epigenetic pathways and reverses pathognomonic H3K27me3 reduction. This article is featured in Selected Articles from This Issue, p. 2293.

Alignment and Analysis of a Disparately Acquired Multibatch Metabolomics Study of Maternal Pregnancy Samples.

Untargeted liquid chromatography-mass spectrometry metabolomics studies are typically performed under roughly identical experimental settings. Measurements acquired with different LC-MS protocols or following extended time intervals harbor significant variation in retention times and spectral abundances due to altered chromatographic, spectrometric, and other factors, raising many data analysis challenges. We developed a computational workflow for merging and harmonizing metabolomics data acquired under disparate LC-MS conditions. Plasma metabolite profiles were collected from two sets of maternal subjects three years apart using distinct instruments and LC-MS procedures. Metabolomics features were aligned using metabCombiner to generate lists of compounds detected across all experimental batches. We applied data set-specific normalization methods to remove interbatch and interexperimental variation in spectral intensities, enabling statistical analysis on the assembled data matrix. Bioinformatics analyses revealed large-scale metabolic changes in maternal plasma between the first and third trimesters of pregnancy and between maternal plasma and umbilical cord blood. We observed increases in steroid hormones and free fatty acids from the first trimester to term of gestation, along with decreases in amino acids coupled to increased levels in cord blood. This work demonstrates the viability of integrating nonidentically acquired LC-MS metabolomics data and its utility in unconventional metabolomics study designs.

Comparing the Fasting and Random-Fed Metabolome Response to an Oral Glucose Tolerance Test in Children and Adolescents: Implications of Sex, Obesity, and Insulin Resistance.

As the incidence of obesity and type 2 diabetes (T2D) is occurring at a younger age, studying adolescent nutrient metabolism can provide insights on the development of T2D. Metabolic challenges, including an oral glucose tolerance test (OGTT) can assess the effects of perturbations in nutrient metabolism. Here, we present alterations in the global metabolome in response to an OGTT, classifying the influence of obesity and insulin resistance (IR) in adolescents that arrived at the clinic fasted and in a random-fed state. Participants were recruited as lean (n = 55, aged 8-17 years, BMI percentile 5-85%) and overweight and obese (OVOB, n = 228, aged 8-17 years, BMI percentile ≥ 85%). Untargeted metabolomics profiled 246 annotated metabolites in plasma at t0 and t60 min during the OGTT. Our results suggest that obesity and IR influence the switch from fatty acid (FA) to glucose oxidation in response to the OGTT. Obesity was associated with a blunted decline of acylcarnitines and fatty acid oxidation intermediates. In females, metabolites from the Fasted and Random-Fed OGTT were associated with HOMA-IR, including diacylglycerols, leucine/isoleucine, acylcarnitines, and phosphocholines. Our results indicate that at an early age, obesity and IR may influence the metabolome dynamics in response to a glucose challenge.

Medium-Chain Acyl-CoA Dehydrogenase Protects Mitochondria from Lipid Peroxidation in Glioblastoma.

Glioblastoma (GBM) is highly resistant to chemotherapies, immune-based therapies, and targeted inhibitors. To identify novel drug targets, we screened orthotopically implanted, patient-derived glioblastoma sphere-forming cells using an RNAi library to probe essential tumor cell metabolic programs. This identified high dependence on mitochondrial fatty acid metabolism. We focused on medium-chain acyl-CoA dehydrogenase (MCAD), which oxidizes medium-chain fatty acids (MCFA), due to its consistently high score and high expression among models and upregulation in GBM compared with normal brain. Beyond the expected energetics impairment, MCAD depletion in primary GBM models induced an irreversible cascade of detrimental metabolic effects characterized by accumulation of unmetabolized MCFAs, which induced lipid peroxidation and oxidative stress, irreversible mitochondrial damage, and apoptosis. Our data uncover a novel protective role for MCAD to clear lipid molecules that may cause lethal cell damage, suggesting that therapeutic targeting of MCFA catabolism may exploit a key metabolic feature of GBM. SIGNIFICANCE: MCAD exerts a protective role to prevent accumulation of toxic metabolic by-products in glioma cells, actively catabolizing lipid species that would otherwise affect mitochondrial integrity and induce cell death. This work represents a first demonstration of a nonenergetic role for dependence on fatty acid metabolism in cancer.This article is highlighted in the In This Issue feature, p. 2659.

metabCombiner: Paired Untargeted LC-HRMS Metabolomics Feature Matching and Concatenation of Disparately Acquired Data Sets.

LC-HRMS experiments detect thousands of compounds, with only a small fraction of them identified in most studies. Traditional data processing pipelines contain an alignment step to assemble the measurements of overlapping features across samples into a unified table. However, data sets acquired under nonidentical conditions are not amenable to this process, mostly due to significant alterations in chromatographic retention times. Alignment of features between disparately acquired LC-MS metabolomics data could aid collaborative compound identification efforts and enable meta-analyses of expanded data sets. Here, we describe metabCombiner, a new computational pipeline for matching known and unknown features in a pair of untargeted LC-MS data sets and concatenating their abundances into a combined table of intersecting feature measurements. metabCombiner groups features by mass-to-charge (m/z) values to generate a search space of possible feature pair alignments, fits a spline through a set of selected retention time ordered pairs, and ranks alignments by m/z, mapped retention time, and relative abundance similarity. We evaluated this workflow on a pair of plasma metabolomics data sets acquired with different gradient elution methods, achieving a mean absolute retention time prediction error of roughly 0.06 min and a weighted per-compound matching accuracy of approximately 90%. We further demonstrate the utility of this method by comprehensively mapping features in urine and muscle metabolomics data sets acquired from different laboratories. metabCombiner has the potential to bridge the gap between otherwise incompatible metabolomics data sets and is available as an R package at https://github.com/hhabra/metabCombiner and Bioconductor.

Multi-Omics Approach Profiling Metabolic Remodeling in Early Systolic Dysfunction and in Overt Systolic Heart Failure.

Metabolic remodeling plays an important role in the pathophysiology of heart failure (HF). We sought to characterize metabolic remodeling and implicated signaling pathways in two rat models of early systolic dysfunction (MOD), and overt systolic HF (SHF). Tandem mass tag-labeled shotgun proteomics, phospho-(p)-proteomics, and non-targeted metabolomics analyses were performed in left ventricular myocardium tissue from Sham, MOD, and SHF using liquid chromatography-mass spectrometry, n = 3 biological samples per group. Mitochondrial proteins were predominantly down-regulated in MOD (125) and SHF (328) vs. Sham. Of these, 82% (103/125) and 66% (218/328) were involved in metabolism and respiration. Oxidative phosphorylation, mitochondrial fatty acid ß-oxidation, Krebs cycle, branched-chain amino acids, and amino acid (glutamine and tryptophan) degradation were highly enriched metabolic pathways that decreased in SHF > MOD. Glycogen and glucose degradation increased predominantly in MOD, whereas glycolysis and pyruvate metabolism decreased predominantly in SHF. PKA signaling at the endoplasmic reticulum-mt interface was attenuated in MOD, whereas overall PKA and AMPK cellular signaling were attenuated in SHF vs. Sham. In conclusion, metabolic remodeling plays an important role in myocardial remodeling. PKA and AMPK signaling crosstalk governs metabolic remodeling in progression to SHF.

Pharmacologic modulation of brain metabolism by valproic acid can induce a neuroprotective environment.

OBJECTIVE: Traumatic brain injury (TBI) is a leading cause of trauma-related morbidity and mortality. Valproic acid (VPA) has been shown to attenuate brain lesion size and swelling within the first few hours following TBI. Because injured neurons are sensitive to metabolic changes, we hypothesized that VPA treatment would alter the metabolic profile in the perilesional brain tissues to create a neuroprotective environment. METHODS: We subjected swine to combined TBI (12-mm cortical impact) and hemorrhagic shock (40% blood volume loss and 2 hours of hypotension) and randomized them to two groups (n = 5/group): (1) normal saline (NS; 3× hemorrhage volume) and (2) NS-VPA (NS, 3× hemorrhage volume; VPA, 150 mg/kg). After 6 hours, brains were harvested, and 100 mg of the perilesional tissue was used for metabolite extraction. Samples were analyzed using reversed-phase liquid chromatography-mass spectrometry in positive and negative ion modes, and data were analyzed using MetaboAnalyst software (McGill University, Quebec, Canada). RESULTS: In untargeted reversed-phase liquid chromatography-mass spectrometry analysis, we detected 3,750 and 1,955 metabolites in positive and negative ion modes, respectively. There were no significantly different metabolites in positive ion mode; however, 167 metabolite features were significantly different (p < 0.05) in the negative ion mode, which included VPA derivates. Pathway analysis showed that several pathways were affected in the treatment group, including the biosynthesis of unsaturated fatty acids (p = 0.001). Targeted amino acid analysis on glycolysis/tricarboxylic acid (TCA) cycle revealed that VPA treatment significantly decreased the levels of the excitotoxic amino acid serine (p = 0.001). CONCLUSION: Valproic acid can be detected in perilesional tissues in its metabolized form. It also induces metabolic changes in the brains within the first few hours following TBI to create a neuroprotective environment.

Dissemination and analysis of the quality assurance (QA) and quality control (QC) practices of LC-MS based untargeted metabolomics practitioners.

INTRODUCTION: The metabolomics quality assurance and quality control consortium (mQACC) evolved from the recognized need for a community-wide consensus on improving and systematizing quality assurance (QA) and quality control (QC) practices for untargeted metabolomics. OBJECTIVES: In this work, we sought to identify and share the common and divergent QA and QC practices amongst mQACC members and collaborators who use liquid chromatography-mass spectrometry (LC-MS) in untargeted metabolomics. METHODS: All authors voluntarily participated in this collaborative research project by providing the details of and insights into the QA and QC practices used in their laboratories. This sharing was enabled via a six-page questionnaire composed of over 120 questions and comment fields which was developed as part of this work and has proved the basis for ongoing mQACC outreach. RESULTS: For QA, many laboratories reported documenting maintenance, calibration and tuning (82%); having established data storage and archival processes (71%); depositing data in public repositories (55%); having standard operating procedures (SOPs) in place for all laboratory processes (68%) and training staff on laboratory processes (55%). For QC, universal practices included using system suitability procedures (100%) and using a robust system of identification (Metabolomics Standards Initiative level 1 identification standards) for at least some of the detected compounds. Most laboratories used QC samples (>86%); used internal standards (91%); used a designated analytical acquisition template with randomized experimental samples (91%); and manually reviewed peak integration following data acquisition (86%). A minority of laboratories included technical replicates of experimental samples in their workflows (36%). CONCLUSIONS: Although the 23 contributors were researchers with diverse and international backgrounds from academia, industry and government, they are not necessarily representative of the worldwide pool of practitioners due to the recruitment method for participants and its voluntary nature. However, both questionnaire and the findings presented here have already informed and led other data gathering efforts by mQACC at conferences and other outreach activities and will continue to evolve in order to guide discussions for recommendations of best practices within the community and to establish internationally agreed upon reporting standards. We very much welcome further feedback from readers of this article.

Purine metabolism regulates DNA repair and therapy resistance in glioblastoma.

Intratumoral genomic heterogeneity in glioblastoma (GBM) is a barrier to overcoming therapy resistance. Treatments that are effective independent of genotype are urgently needed. By correlating intracellular metabolite levels with radiation resistance across dozens of genomically-distinct models of GBM, we find that purine metabolites, especially guanylates, strongly correlate with radiation resistance. Inhibiting GTP synthesis radiosensitizes GBM cells and patient-derived neurospheres by impairing DNA repair. Likewise, administration of exogenous purine nucleosides protects sensitive GBM models from radiation by promoting DNA repair. Neither modulating pyrimidine metabolism nor purine salvage has similar effects. An FDA-approved inhibitor of GTP synthesis potentiates the effects of radiation in flank and orthotopic patient-derived xenograft models of GBM. High expression of the rate-limiting enzyme of de novo GTP synthesis is associated with shorter survival in GBM patients. These findings indicate that inhibiting purine synthesis may be a promising strategy to overcome therapy resistance in this genomically heterogeneous disease.

Mitochondrial Nutrient Utilization Underlying the Association Between Metabolites and Insulin Resistance in Adolescents.

CONTEXT: A person's intrinsic metabolism, reflected in the metabolome, may describe the relationship between nutrient intake and metabolic health. OBJECTIVES: Untargeted metabolomics was used to identify metabolites associated with metabolic health. Path analysis classified how habitual dietary intake influences body mass index z-score (BMIz) and insulin resistance (IR) through changes in the metabolome. DESIGN: Data on anthropometry, fasting metabolites, C-peptide, and dietary intake were collected from 108 girls and 98 boys aged 8 to 14 years. Sex-stratified linear regression identified metabolites associated with BMIz and homeostatic model assessment of IR using C-peptide (HOMA-CP), accounting for puberty, age, and muscle and fat area. Path analysis identified clusters of metabolites that underlie the relationship between energy-adjusted macronutrient intake with BMIz and HOMA-CP. RESULTS: Metabolites associated with BMIz include positive associations with diglycerides among girls and positive associations with branched chain and aromatic amino acids in boys. Intermediates in fatty acid metabolism, including medium-chain acylcarnitines (AC), were inversely associated with HOMA-CP. Carbohydrate intake is positively associated with HOMA-CP through decreases in levels of AC, products of ß-oxidation. Approaching significance, fat intake is positively associated with HOMA-CP through increases in levels of dicarboxylic fatty acids, products of omega-oxidation. CONCLUSIONS: This cross-sectional analysis suggests that IR in children is associated with reduced fatty acid oxidation capacity. When consuming more grams of fat, there is evidence for increased extramitochondrial fatty acid metabolism, while higher carbohydrate intake appears to lead to decreases in intermediates of ß-oxidation. Thus, biomarkers of IR and mitochondrial oxidative capacity may depend on macronutrient intake.

Deep annotation of untargeted LC-MS metabolomics data with Binner.

MOTIVATION: When metabolites are analyzed by electrospray ionization (ESI)-mass spectrometry, they are usually detected as multiple ion species due to the presence of isotopes, adducts and in-source fragments. The signals generated by these degenerate features (along with contaminants and other chemical noise) obscure meaningful patterns in MS data, complicating both compound identification and downstream statistical analysis. To address this problem, we developed Binner, a new tool for the discovery and elimination of many degenerate feature signals typically present in untargeted ESI-LC-MS metabolomics data. RESULTS: Binner generates feature annotations and provides tools to help users visualize informative feature relationships that can further elucidate the underlying structure of the data. To demonstrate the utility of Binner and to evaluate its performance, we analyzed data from reversed phase LC-MS and hydrophilic interaction chromatography (HILIC) platforms and demonstrated the accuracy of selected annotations using MS/MS. When we compared Binner annotations of 75 compounds previously identified in human plasma samples with annotations generated by three similar tools, we found that Binner achieves superior performance in the number and accuracy of annotations while simultaneously minimizing the number of incorrectly annotated principal ions. Data reduction and pattern exploration with Binner have allowed us to catalog a number of previously unrecognized complex adducts and neutral losses generated during the ionization of molecules in LC-MS. In summary, Binner allows users to explore patterns in their data and to efficiently and accurately eliminate a significant number of the degenerate features typically found in various LC-MS modalities. AVAILABILITY AND IMPLEMENTATION: Binner is written in Java and is freely available from http://binner.med.umich.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Towards quality assurance and quality control in untargeted metabolomics studies.

We describe here the agreed upon first development steps and priority objectives of a community engagement effort to address current challenges in quality assurance (QA) and quality control (QC) in untargeted metabolomic studies. This has included (1) a QA and QC questionnaire responded to by the metabolomics community in 2015 which recommended education of the metabolomics community, development of appropriate standard reference materials and providing incentives for laboratories to apply QA and QC; (2) a 2-day 'Think Tank on Quality Assurance and Quality Control for Untargeted Metabolomic Studies' held at the National Cancer Institute's Shady Grove Campus and (3) establishment of the Metabolomics Quality Assurance and Quality Control Consortium (mQACC) to drive forward developments in a coordinated manner.

Excess ω-6 fatty acids influx in aging drives metabolic dysregulation, electrocardiographic alterations, and low-grade chronic inflammation.

Maintaining a balance of ω-6 and ω-3 fatty acids is essential for cardiac health. Current ω-6 and ω-3 fatty acids in the American diet have shifted from the ideal ratio of 2:1 to almost 20:1; while there is a body of evidence that suggests the negative impact of such a shift in younger organisms, the underlying age-related metabolic signaling in response to the excess influx of ω-6 fatty acids is incompletely understood. In the present study, young (6 mo old) and aging (≥18 mo old) mice were fed for 2 mo with a ω-6-enriched diet. Excess intake of ω-6 enrichment decreased the total lean mass and increased nighttime carbohydrate utilization, with higher levels of cardiac cytokines indicating low-grade chronic inflammation. Dobutamine-induced stress tests displayed an increase in PR interval, a sign of an atrioventricular defect in ω-6-fed aging mice. Excess ω-6 fatty acid intake in aging mice showed decreased 12-lipoxygenase with a concomitant increase in 15-lipoxygenase levels, resulting in the generation of 15( S)-hydroxyeicosatetraenoic acid, whereas cyclooxygenase-1 and -2 generated prostaglandin E2, leukotriene B4, and thromboxane B2. Furthermore, excessive ω-6 fatty acids led to dysregulated nuclear erythroid 2-related factor 2/antioxidant-responsive element in aging mice. Moreover, ω-6 fatty acid-mediated changes were profound in aging mice with respect to the eicosanoid profile while minimal changes were observed in the size and shape of cardiomyocytes. These findings provide compelling evidence that surplus consumption of ω-6 fatty acids, coupled with insufficient intake of ω-3 fatty acids, is linked to abnormal changes in ECG. These manifestations contribute to functional deficiencies and expansion of the inflammatory mediator milieu during later stages of aging. NEW & NOTEWORTHY Aging has a profound impact on the metabolism of fatty acids to maintain heart function. The excess influx of ω-6 fatty acids in aging perturbed electrocardiography with marked signs of inflammation and a dysregulated oxidative-redox balance. Thus, the quality and quantity of fatty acids determine the cardiac pathology and energy utilization in aging.

Harmonizing lipidomics: NIST interlaboratory comparison exercise for lipidomics using SRM 1950-Metabolites in Frozen Human Plasma.

As the lipidomics field continues to advance, self-evaluation within the community is critical. Here, we performed an interlaboratory comparison exercise for lipidomics using Standard Reference Material (SRM) 1950-Metabolites in Frozen Human Plasma, a commercially available reference material. The interlaboratory study comprised 31 diverse laboratories, with each laboratory using a different lipidomics workflow. A total of 1,527 unique lipids were measured across all laboratories and consensus location estimates and associated uncertainties were determined for 339 of these lipids measured at the sum composition level by five or more participating laboratories. These evaluated lipids detected in SRM 1950 serve as community-wide benchmarks for intra- and interlaboratory quality control and method validation. These analyses were performed using nonstandardized laboratory-independent workflows. The consensus locations were also compared with a previous examination of SRM 1950 by the LIPID MAPS consortium. While the central theme of the interlaboratory study was to provide values to help harmonize lipids, lipid mediators, and precursor measurements across the community, it was also initiated to stimulate a discussion regarding areas in need of improvement.

Metabolomic Determinants of Metabolic Risk in Mexican Adolescents.

OBJECTIVE: The goal of this study was to identify metabolites associated with metabolic risk, separately by sex, in Mexican adolescents. METHODS: Untargeted metabolomic profiling was carried out on fasting serum of 238 youth aged 8 to 14 years, and metabolites associated with a metabolic syndrome risk z-score (MetRisk z-score) were identified separately for boys and girls, using the simulation and extrapolation algorithm. Associations of each metabolite with MetRisk z-score were examined using linear regression models that accounted for maternal education, child's age, and pubertal status. RESULTS: Of the 938 features identified in metabolomics analysis, 7 named compounds (of 27 identified metabolites) were associated with MetRisk z-score in girls, and 3 named compounds (of 14 identified) were associated with MetRisk z-score in boys. In girls, diacylglycerol (DG) 16:0/16:0, 1,3-dielaidin, myo-inositol, and urate corresponded with higher MetRisk z-score, whereas N-acetylglycine, thymine, and dodecenedioic acid were associated with lower MetRisk z-score. For example, each z-score increment in DG 16:0/16:0 corresponded with 0.60 (95% CI: 0.47-0.74) units higher MetRisk z-score. In boys, positive associations of DG 16:0/16:0, tyrosine, and 5'-methylthioadenosine with MetRisk z-score were found. CONCLUSIONS: Metabolites on lipid, amino acid, and carbohydrate metabolism pathways are associated with metabolic risk in girls. Compounds on lipid and DNA pathways correspond with metabolic risk in boys.

Cancer-Associated IDH1 Promotes Growth and Resistance to Targeted Therapies in the Absence of Mutation.

Oncogenic mutations in two isocitrate dehydrogenase (IDH)-encoding genes (IDH1 and IDH2) have been identified in acute myelogenous leukemia, low-grade glioma, and secondary glioblastoma (GBM). Our in silico and wet-bench analyses indicate that non-mutated IDH1 mRNA and protein are commonly overexpressed in primary GBMs. We show that genetic and pharmacologic inactivation of IDH1 decreases GBM cell growth, promotes a more differentiated tumor cell state, increases apoptosis in response to targeted therapies, and prolongs the survival of animal subjects bearing patient-derived xenografts (PDXs). On a molecular level, diminished IDH1 activity results in reduced α-ketoglutarate (αKG) and NADPH production, paralleled by deficient carbon flux from glucose or acetate into lipids, exhaustion of reduced glutathione, increased levels of reactive oxygen species (ROS), and enhanced histone methylation and differentiation marker expression. These findings suggest that IDH1 upregulation represents a common metabolic adaptation by GBMs to support macromolecular synthesis, aggressive growth, and therapy resistance.

2-Hydroxyglutarate produced by neomorphic IDH mutations suppresses homologous recombination and induces PARP inhibitor sensitivity.

2-Hydroxyglutarate (2HG) exists as two enantiomers, (R)-2HG and (S)-2HG, and both are implicated in tumor progression via their inhibitory effects on α-ketoglutarate (αKG)-dependent dioxygenases. The former is an oncometabolite that is induced by the neomorphic activity conferred by isocitrate dehydrogenase 1 (IDH1) and IDH2 mutations, whereas the latter is produced under pathologic processes such as hypoxia. We report that IDH1/2 mutations induce a homologous recombination (HR) defect that renders tumor cells exquisitely sensitive to poly(adenosine 5'-diphosphate-ribose) polymerase (PARP) inhibitors. This "BRCAness" phenotype of IDH mutant cells can be completely reversed by treatment with small-molecule inhibitors of the mutant IDH1 enzyme, and conversely, it can be entirely recapitulated by treatment with either of the 2HG enantiomers in cells with intact IDH1/2 proteins. We demonstrate mutant IDH1-dependent PARP inhibitor sensitivity in a range of clinically relevant models, including primary patient-derived glioma cells in culture and genetically matched tumor xenografts in vivo. These findings provide the basis for a possible therapeutic strategy exploiting the biological consequences of mutant IDH, rather than attempting to block 2HG production, by targeting the 2HG-dependent HR deficiency with PARP inhibition. Furthermore, our results uncover an unexpected link between oncometabolites, altered DNA repair, and genetic instability.

Glioblastoma Therapy Can Be Augmented by Targeting IDH1-Mediated NADPH Biosynthesis.

NADPH is a critical reductant needed in cancer cells to fuel the biosynthesis of deoxynucleotides and antioxidants and to sustain stress-survival responses after radiation-induced DNA damage. Thus, one rational strategy to attack cancer cells is to target their heavy reliance on NADPH. Here, we report that the isocitrate dehydrogenase IDH1 is the most strongly upregulated NADPH-producing enzyme in glioblastoma (GBM). IDH1 silencing in GBM cells reduced levels of NADPH, deoxynucleotides, and glutathione and increased their sensitivity to radiation-induced senescence. Rescuing these metabolic restrictions was sufficient to reverse IDH1-mediated radiosensitization. In a murine xenograft model of human GBM, we found that IDH1 silencing significantly improved therapeutic responses to fractionated radiotherapy, when compared with either treatment alone. In summary, our work offers a mechanistic rationale for IDH1 inhibition as a metabolic strategy to improve the response of GBM to radiotherapy. Cancer Res; 77(4); 960-70. ©2016 AACR.