The DOI matches its Crossref record; 34 of the 35 references it cites were found in a registry or an index.
Human SHMT inhibitors reveal defective glycine import as a targetable metabolic vulnerability of diffuse large B-cell lymphoma
Open accessAbstract
Significance Enzymes of the folate cycle are among the most consistently overexpressed proteins in cancer. Whereas multiple clinical agents inhibit thymidylate synthase, no current drugs target the incorporation of one-carbon into folates via serine hydroxymethyltransferase (SHMT). Using genetics, we show that cancer cells require SHMT to generate tumors. We then describe small-molecule SHMT inhibitors, and show that they block the growth of many human cancer cells, with B-cell lymphomas particularly sensitive to SHMT inhibition. We find that this sensitivity arises from the lymphomas’ inability to import the amino acid glycine, which is made as a byproduct of the SHMT reaction. Thus, B-cell lymphomas have an intrinsic defect in amino acid import, which causes a therapeutically targetable metabolic vulnerability.
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“Further optimization of this scaffold led to potent inhibitors of both SHMT1 and SHMT2.”
From A review of small-molecule inhibitors of one-carbon enzymes: SHMT2 and MTHFD2 in the spotlight (2021) · cites this paper as [143]
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“Prior to Nonaka and co-worker’s study, generally, only marginal selectivity between the two SHMT isoforms has been achieved, with the inhibitors being selective for SHMT1 by 2- to 3-fold.”
From A review of small-molecule inhibitors of one-carbon enzymes: SHMT2 and MTHFD2 in the spotlight (2021) · cites this paper as [143]
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The emerging hallmarks of cancer metabolism
Pavlova, N. N., & Thompson, C. B. (2016) · Cell Metabolism · doi:10.1016/j.cmet.2015.12.006 · Cited by 5,926 · cited 1×
“C growth and proliferation are supported by metabolic changes, including enhanced glucose uptake, aerobic glycolysis (the Warburg effect), and folate-dependent one-carbon (1C) metabolism (1, 2).”
BackgroundDouble nicking by RNA-guided CRISPR Cas9 for enhanced genome editing specificity
Ran, F. A., Hsu, P. D., Lin, C.-Y., Gootenberg, J. S., Konermann, S., Trevino, A. E., Scott, D. A., Inoue, A., Matoba, S., Zhang, Y., et al. (2013) · Cell · doi:10.1016/j.cell.2013.08.021 · Cited by 3,299
One-Carbon Metabolism in Health and Disease
Ducker, G. S., & Rabinowitz, J. D. (2017) · Cell Metabolism · doi:10.1016/j.cmet.2016.08.009 · Cited by 2,239
Treatment of Acute Lymphoblastic Leukemia
Pui, C., & Evans, W. E. (2006) · New England Journal of Medicine · doi:10.1056/nejmra052603 · Cited by 2,012
Farber, S., Diamond, L. K., Mercer, R. D., Sylvester, R. F., & Wolff, J. A. (1948) · New England Journal of Medicine · doi:10.1056/nejm194806032382301 · Cited by 1,806
Functional genomics reveal that the serine synthesis pathway is essential in breast cancer
Possemato, R., Marks, K. M., Shaul, Y. D., Pacold, M. E., Kim, D., Birsoy, K., Sethumadhavan, S., Woo, H.-K., Jang, H. G., Jha, A. K., et al. (2011) · Nature · doi:10.1038/nature10350 · Cited by 1,683
Metabolite profiling identifies a key role for glycine in rapid cancer cell proliferation
Jain, M., Nilsson, R., Sharma, S., Madhusudhan, N., Kitami, T., Souza, A. L., Kafri, R., Kirschner, M. W., Clish, C. B., & Mootha, V. K. (2012) · Science · doi:10.1126/science.1218595 · Cited by 1,403
Phosphoglycerate dehydrogenase diverts glycolytic flux and contributes to oncogenesis
Locasale, J. W., Grassian, A. R., Melman, T., Lyssiotis, C. A., Mattaini, K. R., Bass, A. J., Heffron, G., Metallo, C. M., Muranen, T., Sharfi, H., et al. (2011) · Nature Genetics · doi:10.1038/ng.890 · Cited by 1,120
How cancer metabolism is tuned for proliferation and vulnerable to disruption
Schulze, A., & Harris, A. L. (2012) · Nature · doi:10.1038/nature11706 · Cited by 945
mTORC1 induces purine synthesis through control of the mitochondrial tetrahydrofolate cycle
Ben-Sahra, I., Hoxhaj, G., Ricoult, S. J. H., Asara, J. M., & Manning, B. D. (2016) · Science · doi:10.1126/science.aad0489 · Cited by 795
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Metadata
- Authors
- Ducker, G. S., Ghergurovich, J. M., Mainolfi, N., Suri, V., Jeong, S. K., Hsin-Jung Li, S., Friedman, A., Manfredi, M. G., Gitai, Z., Kim, H., & Rabinowitz, J. D.
- Affiliations
- Princeton University (US)
- Raze Therapeutics, Cambridge, MA 02139;
- Department of Molecular Biology, Princeton University, Princeton NJ 08544;
- ORCID
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2017-10-09
- Volume
- 114
- Issue
- 43
- Pages
- 11404-11409
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC5664509
- OpenAlex
- W2761750372
- Cited by
- 261
- References
- 35
- Citations by year
- 2026: 26 · 2025: 29 · 2024: 30 · 2023: 39 · 2022: 29 · 2021: 36 · 2020: 34 · 2019: 26 · 2018: 12
- FWCI
- 6.60
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- Funders
- HHS | NIH | National Cancer Institute (NCI) (R01CA163591, K99CA215307)
- EIF | Stand Up To Cancer (SU2C) (SU2CAACR-DT-20-16)
- American Cancer Society (ACS) (PF-15-190-01-TBE)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer, Hypoxia, and Metabolism
- Health Sciences › Nursing › Nutrition and Dietetics › Folate and B Vitamins Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biochemistry › Amino Acid Enzymes and Metabolism
- Keywords
- serine hydroxymethyltransferase, folate cycle, one-carbon metabolism, diffuse large B-cell lymphoma, metabolic vulnerability, small molecule inhibitors, cancer metabolism
- MeSH terms
- Animals, Binding Sites, Enzyme Inhibitors, Female, Glycine, Humans, Mice, Nude, Models, Molecular, Neoplasms, Experimental, Protein Conformation, Glycine Hydroxymethyltransferase, Molecular Structure, Gene Expression Regulation, Neoplastic, Lymphoma, Large B-Cell, Diffuse, Gene Deletion, Cell Line, Tumor, Mice
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