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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“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
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
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
Flagged first, then by citations
Cited by
Sorted by citations
Items 301–340 of 340
In Situ Microwave Fixation to Define the Terminal Rodent Brain MetabolomePreprint
Juras, J. A., Webb, M. B., Young, L. E. A., Markussen, K. H., Hawkinson, T. R., Buoncristiani, M. D., Bolton, K. E., Coburn, P. T., Williams, M. I., Sun, L. P. Y., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.08.16.504166 · Cited by 2
Hemalatha, A., Li, Z., Tai, K., Gonzalez, D. G., Lathrop, E., Gil, D. A., Matte-Martone, C. C., Ganesan, S., Yun, S., Gonzalez, L. E., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.11.21.517380 · Cited by 2
Miki, K., Ghoche, M. T., Yuan, F., Li, F., Manoj, N., Oken, S., Yoshimoto, K., Zinn, P. O., Agnihotri, S., McBrayer, S. K., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.02.05.704021 · Cited by 2
Lineage specifying transcription factors determine cell function by direct control of metabolismPreprint
Bott, A. J., Youngs, J. C., Cunningham, C. N., Vranken, J. G. V., Wei, P., Cluntun, A. A., Gygi, S. P., Ayer, D. E., & Rutter, J. P. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.07.02.735862 · Cited by 2
Nitrogen metabolism profiling reveals cell state-specific pyrimidine synthesis pathway choice
Savani, M. R., Li, B., Smith, B. C., Gu, W., Xiao, Y., Baquer, G., Shipman, T. E., Oken, S., Manoj, N., Zacharias, L. G., et al. (2026) · Nature Metabolism · doi:10.1038/s42255-026-01520-0 · Cited by 4
Tumour sampling conditions perturb the metabolic landscape of clear cell renal cell carcinoma
Yong, C., Schmidt, C., Yang, M. H., von Kriegsheim, A., Warren, A. Y., Anand, S., Armitage, J. N., Riddick, A. C. P., Mitchell, T. J., Patil, V., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-65676-1 · Cited by 2
SURVEY AND SUMMARY Regulation of mammalian nucleotide metabolism and biosynthesis
Lane, A. N. (2015) · Cited by 1
Understanding the Role of the Solid Tumour Microenvironment in Brain Tumour Progression
Richards, R. (2017) · University of Liverpool · doi:10.17638/03005579 · Cited by 1
Dobberthien, B. J., Tessier, A. G., Stanislaus, A. E., Sawyer, M. B., Fallone, B. G., & Yahya, A. (2019) · NMR in Biomedicine · doi:10.1002/nbm.4180 · Cited by 1
Simoes, R. V., Henriques, R. N., Olesen, J. L., Cardoso, B. M., Fernandes, F. F., Monteiro, M. A., Jespersen, S. N., Carvalho, T., & Shemesh, N. (2025) · eLife · doi:10.7554/elife.100570.2 · Cited by 1
Future Methods in Tumor Imaging
Pilatus, U., & Hattingen, E. (2015) · Medical radiology · doi:10.1007/174_2015_1055
Residual breast cancer metabolic phenotype after docetaxel treatment
Volpari, T. (2016) · University of Birmingham Institutional Research Archive (University of Birmingham)
Using Metabolomic Approaches to Characterize the Human Pathogen Leishmania in Macrophages
Kloehn, J., Saunders, E. C., & McConville, M. J. (2016) · Springer eBooks · doi:10.1007/978-3-319-46326-1_4
Utilising autophagy modulation to combat cell death resistance in Glioblastoma Multiforme
Kriel, J. (2016) · SUNScholar (Stellenbosch University)
Impact of San-mediated Signaling on Glioblastoma and Neuroblastoma Metabolism
Silva, M. R. (2018) · FIU - Digital Commons (Florida International University) · doi:10.25148/etd.fidc006885
Tracking Metabolic Rewiring of Cancer Metabolism in Humans Using Isotope-Resolved NMR
Pichumani, K. (2019) · Methods in molecular biology · doi:10.1007/978-1-4939-9690-2_10
Metabolic effects of oncogenic K-Ras in cancer cells
Bergner, R. (2018) · doi:10.25560/82596
Cancer Cell Metabolism in Pancreatic Ductal Adenocarcinoma
Hagland, H. R. (2021) · Springer eBooks · doi:10.1007/978-3-030-53786-9_16
New Insights into Metabolic Regulation from Hyperpolarized 13C MRS/MRI Studies
Sherry, A. D., & Malloy, C. R. (2021) · Springer eBooks · doi:10.1007/978-3-030-55043-1_8
The time has come to pull renal cancer’s sweet tooth
Kinnaird, A. S., & Michelakis, E. D. (2019) · Translational Cancer Research · doi:10.21037/tcr.2018.12.31
Vanderstichelen, G. (2022) · Publication Server of Goethe University Frankfurt am Main (Goethe University Frankfurt) · doi:10.21248/gups.68013
Targeting the Immuno-Oncology Metabolism in Cancer
Tripathi, S. C., Fahrmann, J. F., & Amle, D. B. (2022) · Springer eBooks · doi:10.1007/978-981-16-6226-3_5
Simoes, R. V., Henriques, R. N., Olesen, J. L., Cardoso, B. M., Fernandes, F. F., Monteiro, M. A., Jespersen, S. N., Carvalho, T., & Shemesh, N. (2024) · eLife · doi:10.7554/elife.100570.1
Cameron, R. B., Hammond, N. G., & Faubert, B. (2025) · Trends in Pharmacological Sciences · doi:10.1016/j.tips.2025.10.001
Liang, N., Scott, A. J., Al‐Holou, W. N., Xu, J., O’Brien, A. M., Lin, A., Pareek, V., Sha, Z., Zhao, Z., Yang, J. Z., et al. (2025) · medRxiv · doi:10.1101/2025.11.11.25340023
Li, X., Wang, H., Li, Z., Li, D., Lu, X., Ai, S., Dong, Y., Liu, S., Wu, J., & Guan, W. (2022) · Figshare · doi:10.6084/m9.figshare.21192148
Gonsalves, W. I., Jang, J. S., Jessen, E., Hitosugi, T., Evans, L. A., Jevremović, D., Pettersson, X.-M., Bush, A. G., Gransee, J., Anderson, E. I., et al. (2020) · Figshare · doi:10.6084/m9.figshare.13467787
ZEMB, P. A., & Joulia, F. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6068352
Exploring metabolic signatures in urine using NMR for improved prognosis of gliomas
Pandey, A., Datta, A., Verma, R., Jaiswal, A. K., Kumar, R., Das, K. K., & Baishya, B. (2026) · Metabolomics · doi:10.1007/s11306-026-02414-8
Azzout‐Marniche, D., & Tomé, D. (2026) · Metabolites · doi:10.3390/metabo16040231
EVT-701 : targeting electron transport chain complex I as therapeutic approach in cancer
Yolba, R. L. (2021) · theses.fr (ABES) · doi:10.70675/9cadea77z03ccz4a54zb381zf34a432615a5
The anti-tumoral effects of a low protein diet and of the IRE1α signaling
Turtos, A. M. (2022) · theses.fr (ABES) · doi:10.70675/fd90a3e8ze35az42fdzbd0ez966f12ddad22
Datta, A., Pandey, A., Verma, R., Jaiswal, A. K., Kumar, R. V., Baishya, B., & Das, K. K. (2026) · Journal of Neuro-Oncology · doi:10.1007/s11060-026-05674-5
Effects of copper overload on mitochondrial parameters in GBM-1, U-87 MG, and C6 glioma cell lines
Tassinari, G., de Souza, L. A., de Souza, N. A., Mendonça, Y. R., Stoeberl, L., de Melo, M. S., Nazari, E. M., Tasca, C. I., Nedel, C. B., & Glaser, V. (2026) · BioMetals · doi:10.1007/s10534-026-00863-1
Fatty Acid Metabolism Rewires Glioblastoma Progression and Treg-Mediated Immune Resistance
Chowdhury, N. I., Ewida, H. A., Ahmed, M. S., & Villalba, H. (2026) · Cancers · doi:10.3390/cancers18162573
Hu, X., Yang, L., Hu, Y., & Cui, H. (2026) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2026.1821274
Li, H., & Baykal, A. T. (2026) · International Journal of Molecular Sciences · doi:10.3390/ijms27209160
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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review