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Thomas D, Wu M, Nakauchi Y, Zheng M, Thompson-Peach CA, Lim K, Landberg N, Köhnke T, Robinson N, Kaur S, Kutyna M, Stafford M, Hiwase D, Reinisch A, Peltz G, Majeti R. Dysregulated Lipid Synthesis by Oncogenic IDH1 Mutation Is a Targetable Synthetic Lethal Vulnerability. Cancer Discov 2023; 13:496-515. [PMID: 36355448 PMCID: PMC9900324 DOI: 10.1158/2159-8290.cd-21-0218] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Revised: 09/18/2022] [Accepted: 11/08/2022] [Indexed: 11/12/2022]
Abstract
Isocitrate dehydrogenase 1 and 2 (IDH) are mutated in multiple cancers and drive production of (R)-2-hydroxyglutarate (2HG). We identified a lipid synthesis enzyme [acetyl CoA carboxylase 1 (ACC1)] as a synthetic lethal target in mutant IDH1 (mIDH1), but not mIDH2, cancers. Here, we analyzed the metabolome of primary acute myeloid leukemia (AML) blasts and identified an mIDH1-specific reduction in fatty acids. mIDH1 also induced a switch to b-oxidation indicating reprogramming of metabolism toward a reliance on fatty acids. Compared with mIDH2, mIDH1 AML displayed depletion of NADPH with defective reductive carboxylation that was not rescued by the mIDH1-specific inhibitor ivosidenib. In xenograft models, a lipid-free diet markedly slowed the growth of mIDH1 AML, but not healthy CD34+ hematopoietic stem/progenitor cells or mIDH2 AML. Genetic and pharmacologic targeting of ACC1 resulted in the growth inhibition of mIDH1 cancers not reversible by ivosidenib. Critically, the pharmacologic targeting of ACC1 improved the sensitivity of mIDH1 AML to venetoclax. SIGNIFICANCE Oncogenic mutations in both IDH1 and IDH2 produce 2-hydroxyglutarate and are generally considered equivalent in terms of pathogenesis and targeting. Using comprehensive metabolomic analysis, we demonstrate unexpected metabolic differences in fatty acid metabolism between mutant IDH1 and IDH2 in patient samples with targetable metabolic interventions. See related commentary by Robinson and Levine, p. 266. This article is highlighted in the In This Issue feature, p. 247.
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Affiliation(s)
- Daniel Thomas
- Department of Medicine, Division of Hematology, Cancer Institute, and Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Palo Alto, California
- Adelaide Medical School, University of Adelaide, South Australia and Precision Medicine, South Australian Health and Medical Research Institute, Adelaide, Australia
| | - Manhong Wu
- Department of Anesthesiology, Pain and Perioperative Medicine, Stanford University School of Medicine, Palo Alto, California
| | - Yusuke Nakauchi
- Department of Medicine, Division of Hematology, Cancer Institute, and Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Palo Alto, California
| | - Ming Zheng
- Department of Anesthesiology, Pain and Perioperative Medicine, Stanford University School of Medicine, Palo Alto, California
| | - Chloe A.L. Thompson-Peach
- Adelaide Medical School, University of Adelaide, South Australia and Precision Medicine, South Australian Health and Medical Research Institute, Adelaide, Australia
| | - Kelly Lim
- Adelaide Medical School, University of Adelaide, South Australia and Precision Medicine, South Australian Health and Medical Research Institute, Adelaide, Australia
| | - Niklas Landberg
- Department of Medicine, Division of Hematology, Cancer Institute, and Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Palo Alto, California
| | - Thomas Köhnke
- Department of Medicine, Division of Hematology, Cancer Institute, and Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Palo Alto, California
| | - Nirmal Robinson
- Centre for Cancer Biology, University of South Australia, South Australia, Australia
| | - Satinder Kaur
- Department of Medicine, Division of Hematology, Cancer Institute, and Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Palo Alto, California
| | - Monika Kutyna
- Adelaide Medical School, University of Adelaide, South Australia and Precision Medicine, South Australian Health and Medical Research Institute, Adelaide, Australia
| | - Melissa Stafford
- Department of Medicine, Division of Hematology, Cancer Institute, and Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Palo Alto, California
| | - Devendra Hiwase
- Adelaide Medical School, University of Adelaide, South Australia and Precision Medicine, South Australian Health and Medical Research Institute, Adelaide, Australia
| | - Andreas Reinisch
- Department of Medicine, Division of Hematology, Cancer Institute, and Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Palo Alto, California
- Division of Hematology and Department of Blood Group Serology and Transfusion Medicine, Medical University of Graz, Graz, Austria
| | - Gary Peltz
- Department of Anesthesiology, Pain and Perioperative Medicine, Stanford University School of Medicine, Palo Alto, California
| | - Ravindra Majeti
- Department of Medicine, Division of Hematology, Cancer Institute, and Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Palo Alto, California
- Corresponding Author: Ravindra Majeti, Department of Medicine, Division of Hematology, Stanford Institute for Stem Cell Biology and Regenerative Medicine, Lokey Stem Cell Building, 265 Campus Drive, Stanford, CA 94305. Phone: 650-721-6376; Fax: 650-736-2961; E-mail:
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Xie Z, Ferreira CR, Virequ AA, Cooks RG. Multiple reaction monitoring profiling (MRM profiling): Small molecule exploratory analysis guided by chemical functionality. Chem Phys Lipids 2021; 235:105048. [PMID: 33561466 DOI: 10.1016/j.chemphyslip.2021.105048] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2020] [Revised: 10/17/2020] [Accepted: 01/04/2021] [Indexed: 02/06/2023]
Abstract
Small molecules, including metabolites and lipids, provide information on metabolic pathways and active biological processes in living organisms. They are often diagnostic of disease. Current exploratory methods for metabolomics and lipidomics mostly rely on separation using liquid or gas chromatography (LC or GC) coupled with mass spectrometers capable of acquiring high resolution data to generate an enormous data, but at the cost of lengthy processing and data acquisition. Even though many molecules can be identified and quantified by these methods, the laborious protocols for purification, identification, and validation limit the accessible sample chemical information. To improve the speed and efficiency of exploratory metabolomics and lipidomics, multiple reaction monitoring profiling (MRM profiling) has been developed. This strategy involves a three-stage workflow which starts by considering the metabolome as a collection of functional groups. The Discovery Stage interrogates a representative sample mixture for functional groups using the functional group specific precursor ion (Prec) scans and neutral loss (NL) scans. This experiment usually uses a triple quadrupole mass spectrometer without chromatography, i.e. by direct sample infusion. In the second Screening Stage, the main features seen in the Prec and NL scans are organized into lists of precursor ion/product ion transitions (MRMs) which are then used for the fast, specific, and sensitive interrogation of each individual sample. Data analysis by univariate and multivariate statistical methods is used to identify the most informative MRMs and so classify the individual samples. The compounds (biomarkers) which are responsible for the most informative MRMs in particular sample classes can be investigated in an optional third Identification Stage i.e. in a structural identification study. MRM profiling benefits from the much smaller number of functional groups compared to the number of individual metabolites existing in biological samples (where most metabolites are still unknown), resulting in acquisition of a much smaller data set and a shorter analysis time. The application of MRM Profiling to several biological and clinical problems is used to illustrate its features.
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Affiliation(s)
- Zhuoer Xie
- Department of Chemistry, Purdue University, West Lafayette, IN 47907, USA
| | - Christina R Ferreira
- Department of Chemistry, Purdue University, West Lafayette, IN 47907, USA; Bindley Bioscience Center, Purdue University, West Lafayette, IN 47907, USA
| | - Alessandra A Virequ
- Invitra - Assisted Reproductive Technologies LTD, Supera Innovation and Technology Park, Ribeirão Preto, São Paulo, 14056-680, Brazil
| | - R Graham Cooks
- Department of Chemistry, Purdue University, West Lafayette, IN 47907, USA.
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