The DOI matches its Crossref record; 49 of the 49 references it cites were found in a registry or an index.
Metabolism of [U‐ 13 C]glucose in human brain tumors in vivo
Open accessAbstract
Glioblastomas and brain metastases demonstrate avid uptake of 2-[(18) F]fluoro-2-deoxyglucose by positron emission tomography and display perturbations of intracellular metabolite pools by (1) H MRS. These observations suggest that metabolic reprogramming contributes to brain tumor growth in vivo. The Warburg effect, excess metabolism of glucose to lactate in the presence of oxygen, is a hallmark of cancer cells in culture. 2-[(18) F]Fluoro-2-deoxyglucose-positive tumors are assumed to metabolize glucose in a similar manner, with high rates of lactate formation relative to mitochondrial glucose oxidation, but few studies have specifically examined the metabolic fates of glucose in vivo. In particular, the capacity of human brain cancers to oxidize glucose in the tricarboxylic acid cycle is unknown. Here, we studied the metabolism of human brain tumors in situ. [U-(13) C]Glucose (uniformly labeled glucose, i.e. d-glucose labeled with (13) C in all six carbons) was infused during surgical resection, and tumor samples were subsequently subjected to (13) C NMR spectroscopy. The analysis of tumor metabolites revealed lactate production, as expected. We also determined that pyruvate dehydrogenase, turnover of the tricarboxylic acid cycle, anaplerosis and de novo glutamine and glycine synthesis contributed significantly to the ultimate disposition of glucose carbon. Surprisingly, less than 50% of the acetyl-coenzyme A pool was derived from blood-borne glucose, suggesting that additional substrates contribute to tumor bioenergetics. This study illustrates a convenient approach that capitalizes on the high information content of (13) C NMR spectroscopy and enables the analysis of intermediary metabolism in diverse cancers growing in their native microenvironment.
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“In fact, tracing the fate of glucose-derived carbons in human patients and in mouse models of glioblastoma and non-small cell lung carcinoma (NSCLC) reveals that at least in these tumorigenic contexts, the principal source for the TCA cycle intermediates is not glutamine, but glucose (Maher et al., 2012; Marin-Valencia et al., 2012; Sellers et al., 2015).”
From The emerging hallmarks of cancer metabolism (2016) · cites this paper as Maher et al., 2012
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Hallmarks of Cancer: The Next Generation
Hanahan, D., & Weinberg, R. A. (2011) · Cell · doi:10.1016/j.cell.2011.02.013 · Cited by 66,590
Understanding the Warburg Effect: The Metabolic Requirements of Cell Proliferation
Vander Heiden, M. G., Cantley, L. C., & Thompson, C. B. (2009) · Science · doi:10.1126/science.1160809 · Cited by 16,197
Warburg, O. (1956) · Science · doi:10.1126/science.123.3191.309 · Cited by 13,425
IDH1 and IDH2 Mutations in Gliomas
Yan, H., Parsons, D. W., Jin, G., McLendon, R., Rasheed, B. A., Yuan, W., Kos, I., Batinic-Haberle, I., Jones, S., Riggins, G. J., et al. (2009) · New England Journal of Medicine · doi:10.1056/nejmoa0808710 · Cited by 5,847
Why Do Cancers Have High Aerobic Glycolysis?
Gatenby, R. A., & Gillies, R. J. (2004) · Nature reviews. Cancer · doi:10.1038/nrc1478 · Cited by 4,784
Cancer-associated IDH1 mutations produce 2-hydroxyglutarate
Dang, L., White, D. W., Gross, S., Bennett, B. D., Bittinger, M. A., Driggers, E. M., Fantin, V. R., Jang, H. G., Jin, S., Keenan, M. C., et al. (2009) · Nature · doi:10.1038/nature08617 · Cited by 4,154
The Biology of Cancer: Metabolic Reprogramming Fuels Cell Growth and Proliferation
DeBerardinis, R. J., Lum, J. J., Hatzivassiliou, G., & Thompson, C. B. (2008) · Cell Metabolism · doi:10.1016/j.cmet.2007.10.002 · Cited by 4,088
On Respiratory Impairment in Cancer Cells
Warburg, O. H. (1956) · Science · doi:10.1126/science.124.3215.269 · Cited by 3,472
Otto Warburg's contributions to current concepts of cancer metabolism
Koppenol, W. H., Bounds, P. L., & Dang, C. V. (2011) · Nature Reviews Cancer · doi:10.1038/nrc3038 · Cited by 3,427
DeBerardinis, R. J., Mancuso, A., Daikhin, E., Nissim, I., Yudkoff, M., Wehrli, S., & Thompson, C. B. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0709747104 · Cited by 2,622
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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
Fundamentals of Cancer Metabolism
DeBerardinis, R. J., & Chandel, N. S. (2016) · Science Advances · doi:10.1126/sciadv.1600200 · Cited by 3,013
Self-citationUnderstanding the Intersections between Metabolism and Cancer Biology
Heiden, M. G. V., & DeBerardinis, R. J. (2017) · Cell · doi:10.1016/j.cell.2016.12.039 · Cited by 2,369
Metabolic pathways promoting cancer cell survival and growth
Boroughs, L. K., & DeBerardinis, R. J. (2015) · Nature Cell Biology · doi:10.1038/ncb3124 · Cited by 1,499
Zong, W., Rabinowitz, J. D., & White, E. (2016) · Molecular Cell · doi:10.1016/j.molcel.2016.02.011 · Cited by 1,330
Metadata
- Authors
- Maher, E. A., Marin‐Valencia, I., Bachoo, R. M., Mashimo, T., Raisanen, J., Hatanpaa, K. J., Jindal, A., Jeffrey, F. M., Choi, C., Madden, C., Mathews, D., Pascual, J. M., Mickey, B. E., Malloy, C. R., & DeBerardinis, R. J.
- Affiliations
- Harold C. Simmons Comprehensive Cancer Center (US)
- The University of Texas Southwestern Medical Center (US)
- VA North Texas Health Care System (US)
- Corresponding author
- Maher, Elizabeth A.
- DeBerardinis, Ralph J.
- ORCID
- Venue
- NMR in Biomedicine
- Publisher
- Wiley
- Published
- 2012-03-15
- Volume
- 25
- Issue
- 11
- Pages
- 1234-1244
- ISSN
- 0952-3480 (ISSN-L)
- 1099-1492
- PMC
- PMC3406255
- OpenAlex
- W2114805483
- Cited by
- 341
- References
- 49
- Citations by year
- 2026: 16 · 2025: 22 · 2024: 21 · 2023: 19 · 2022: 28 · 2021: 41 · 2020: 28 · 2019: 30 · 2018: 22 · 2017: 18 · 2016: 34 · 2015: 33 · 2014: 14 · 2013: 11 · 2012: 4
- FWCI
- 6.54
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- NMR in Biomedicine (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Cancer Prevention and Research Institute of Texas
- National Institutes of Health
- National Cancer Institute (R01CA154843, R01CA157996)
- National Institute of Neurological Disorders and Stroke (RC1NS0760675, RC1NS070675)
- National Center for Research Resources (P41RR002584, RR‐02584)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer, Hypoxia, and Metabolism
- Health Sciences › Medicine › Oncology › Glioma Diagnosis and Treatment
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolomics and Mass Spectrometry Studies
- Keywords
- brain tumors, glioblastoma, brain metastases, glucose metabolism, Warburg effect, lactic acid production, TCA cycle, pyruvate dehydrogenase, anaplerosis, acetyl-CoA, tumor bioenergetics, metabolic reprogramming
- MeSH terms
- Acetyl Coenzyme A, Blood Glucose, Brain Neoplasms, Breast Neoplasms, Carbon Isotopes, Carcinoma, Non-Small-Cell Lung, Citric Acid Cycle, Female, Glioblastoma, Glucose, Glycine, Glycolysis, Humans, Oxidation-Reduction
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