Exploring metabolic vulnerability and therapeutic potential in cancers with isocitrate dehydrogenase mutations

Treatment of mutant isocitrate dehydrogenase 1 (IDH1) glioma remains challenging; targeted allosteric inhibitors currently provide limited clinical effect. Resistance to mutIDH1 inhibitors has also emerged in other cancers with mutant IDH1. IDH1 catalyses the decarboxylation of isocitrate to 2-oxoglutarate (2-OG) and concomitant reduction of NADP+ to NADPH. Upon mutation, the enzyme instead reduces 2-OG to (R)-2-hydroxyglutarate (2 HG) with NADPH. 2 HG accumulates to high levels in cells and is thought to promote tumorigenesis by e.g., disrupting DNA and histone methylation and impairing DNA repair. Altered central carbon, amino acid and lipid metabolism, as well as redox homeostasis, has been linked to expression of mutIDH1R132H and presence of high levels of 2-HG. Yet, the understanding of the mechanisms by which 2 HG affects metabolism, and what capacity those metabolic changes have to drive tumorigenesis, remains limited. A more detailed comprehension of the metabolic changes in mutIDH1 glioma and how they relate to 2-HG abundance would improve understanding of tumorigenesis and potentially uncover new therapeutic targets. The aim of this thesis was therefore to investigate mutIDH1 glioma metabolism by comparison to a matched wild-type (wt) IDH1 model and with metabolic inhibitors targeting the mutated enzyme or substrate availability. The glioblastoma cell line LN18 with mutant IDH1 expressed via lentiviral vector was compared to wtIDH1 LN18 cells and treated with mutIDH1 inhibitors (AG-120, AG-881, BAY 1436032, GSK864 and FT2102) or glutaminase (GLS) inhibitor (CB-839) to investigate mutIDH1 glioma metabolism. Anion exchange chromatography (IC) and reverse phase liquid chromatography (RPLC), both coupled to mass spectrometers (MS) were used to measure metabolites in samples. Cell viability was measured by colorimetric assay. Univariate and multivariate statistical analyses were performed to identify altered metabolites and reveal correlative relationships to 2-HG abundance. Untargeted pathways analysis was used to assess metabolic changes at the pathway level. The abundance of 2-HG was significantly elevated in mutIDH1R132H LN18 cells and glutamine was the main carbon source. Amino acids and metabolic intermediates, nucleotides, lipid related metabolites, N acetylaspartylglutamate (NAAG) and B citryl L glutamate (B CG) were significantly altered in the mutant cell line. On the pathway level, amino acid metabolism (lysine degradation, BCAA catabolism, glutamate, arginine & proline and aspartate & asparagine), butanoate & propanoate and vitamin B1 and vitamin C were significantly altered between the wtIDH1 and mutIDH1R132H LN18 cells. Certain metabolites required 2-OG or NADPH for biosynthesis, while others did not, suggesting that 2-HG affected metabolism both directly (e.g., competitive inhibition) or indirectly (e.g., altered transcription of enzymes). MutIDH1 inhibitors were capable of significantly decreasing 2-HG abundance in mutIDH1R132H LN18 cells. AG-120, AG-881 and GSK864 were also capable of inhibiting wtIDH1; isocitrate accumulated in treated cells. AG-881 was inferior in ability to decrease 2-HG abundance and reached a maximum inhibition threshold at far lower concentration than the other three mutIDH1 inhibitors. None of the mutIDH1 inhibitors had a substantial impact on cell viability. Mutant cells treated with mutIDH1 inhibitors were metabolically more similar to wtIDH1 cells. Several metabolites correlated with 2-HG abundance. Nevertheless, it was difficult to determine the extent 2-HG abundance affected other metabolites due to concurrent inhibition of wtIDH1. GLS inhibition was assessed as an alternative treatment strategy; it indirectly decreased substrate availability by decreasing glutamate abundance. Cell viability was decreased significantly compared to treatment with mutIDH1 inhibitors. Despite 2-OG abundance decreasing, 2-HG levels were maintained. However, this effect was used to determine which metabolites were affected by 2-HG only or and which were also dependent on 2-OG. Amino acid metabolism was suggested to be affected by competitive inhibition by 2-HG. Amino acids are key for cell proliferation by providing energy and are substrates for anaplerosis and redox-active compounds. B-CG had a particularly strong correlative relationship to 2 HG abundance and the effect was likely indirect. The function of B CG in human metabolism is not well understood, but its proposed redox protective abilities suggest a tumorigenic role in maintaining redox homeostasis. Collectively, the experiments in this thesis revealed that 2-HG abundance correlated consistently with certain metabolic changes and that altered metabolism was due to a combination of direct and indirect effects by 2-HG. Future work should focus on the potential contributions to tumorigenesis and therapeutic potential of B-CG and amino acid metabolism in mutIDH1 glioma

Metabolic adaptations in cancers expressing isocitrate dehydrogenase mutations

The most frequently mutated metabolic genes in human cancer are those encoding the enzymes isocitrate dehydrogenase 1 (IDH1) and IDH2; these mutations have so far been identified in more than 20 tumor types. Since IDH mutations were first reported in glioma over a decade ago, extensive research has revealed their association with altered cellular processes. Mutations in IDH lead to a change in enzyme function, enabling efficient conversion of 2-oxoglutarate to R-2-hydroxyglutarate (R-2-HG). It is proposed that elevated cellular R-2-HG inhibits enzymes that regulate transcription and metabolism, subsequently affecting nuclear, cytoplasmic, and mitochondrial biochemistry. The significance of these biochemical changes for tumorigenesis and potential for therapeutic exploitation remains unclear. Here we comprehensively review reported direct and indirect metabolic changes linked to IDH mutations and discuss their clinical significance. We also review the metabolic effects of first-generation mutant IDH inhibitors and highlight the potential for combination treatment strategies and new metabolic targets

Nuclear magnetic resonance spectroscopy based metabolomics discovers biomarkers of glioblastoma drug response

Glioblastoma is the most common and aggressive form of brain cancer. Even with comprehensive treatment regimes, patients face an expected survival of only 15 months. Currently, methods for assessing treatment response are lacking; it is difficult to accurately determine the efficacy of a treatment. The goal of the present study was to contribute to treatment assessment by scouting for metabolic biomarkers occurring in response to exposure to chemotherapeutic agents temozolomide (TMZ) and sepantronium bromide (YM155). Untargeted metabolomics of lysate from cultured glioblastoma cells was carried out with liquid state proton nuclear magnetic resonance (NMR) spectroscopy at resonance frequency 800 MHz. Spectral data were analyzed with two different multivariate statistical methods: principal component analysis (PCA) and partial least squares (PLS) regression. For YM155, two biomarker candidates were found: citric and lactic acid. Citric acid appeared to increase most in samples from cell lines less sensitive to YM155. Lactic acid decreased in all cell lines and was considered a more general biomarker of treatment exposure. TMZ-treated samples were not distinguishable from control samples, most likely due to too short exposure time (24 hours). Analyses with nano hydrophilic interaction liquid chromatography coupled with mass spectrometry (MS) corroborated the findings by NMR spectroscopy and statistical analyses. Both citric acid and lactic acid are biomarker candidates, but a more detailed understanding of their fluctuations in glioblastoma during treatment is needed. Nevertheless, they represent genuine candidates and should be considered for further in vivo magnetic resonance spectroscopy (MRS) studies. In the future, the biomarkers could be monitored with MRS, allowing a more unambiguous and personalized assessment of response to treatment in individual patients

Protocol/guidelines for 800 MHz NMR Metabolomics, University of Oslo, version VII

The goal of this document is to enable users to be able to obtain NMR–metabolomics data on the 800 MHz NMR instrument at the UiO NMR Center. Interpretation of spectra is not (yet) covered. Statistical treatment of the data is also not covered (yet). A database at Ohio State University, which can help you with identification of individual molecules in the metabolomics samples, is mentioned in this document, but the use is not (yet) covered. In order to understand the content of this document the reader need to know how to perform standard nmr-experiments on Bruker nmr- spectrometers