The DOI matches its Crossref record; 85 of the 85 references it cites were found in a registry or an index.
Slow TCA flux and ATP production in primary solid tumours but not metastases
Open accessAbstract
Tissues derive ATP from two pathways-glycolysis and the tricarboxylic acid (TCA) cycle coupled to the electron transport chain. Most energy in mammals is produced via TCA metabolism 1. In tumours, however, the absolute rates of these pathways remain unclear. Here we optimize tracer infusion approaches to measure the rates of glycolysis and the TCA cycle in healthy mouse tissues, Kras-mutant solid tumours, metastases and leukaemia. Then, given the rates of these two pathways, we calculate total ATP synthesis rates. We find that TCA cycle flux is suppressed in all five primary solid tumour models examined and is increased in lung metastases of breast cancer relative to primary orthotopic tumours. As expected, glycolysis flux is increased in tumours compared with healthy tissues (the Warburg effect 2,3), but this increase is insufficient to compensate for low TCA flux in terms of ATP production. Thus, instead of being hypermetabolic, as commonly assumed, solid tumours generally produce ATP at a slower than normal rate. In mouse pancreatic cancer, this is accommodated by the downregulation of protein synthesis, one of this tissue's major energy costs. We propose that, as solid tumours develop, cancer cells shed energetically expensive tissue-specific functions, enabling uncontrolled growth despite a limited ability to produce ATP.
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?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Intriguingly, a recent study determined that “bulk” fermentative and respiratory rates in primary tumors are lower than previously postulated,4”
From Dynamic IL-6R/STAT3 signaling leads to heterogeneity of metabolic phenotype in pancreatic ductal adenocarcinoma cells (2024) · cites this paper as [4]
Experimental — accuracy not yet measured
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
KEGG: Kyoto Encyclopedia of Genes and Genomes
Kanehisa, M. (2000) · Nucleic Acids Research · doi:10.1093/nar/28.1.27 · Cited by 37,077
An Algorithm for Least-Squares Estimation of Nonlinear Parameters
Marquardt, D. W. (1963) · Journal of the Society for Industrial and Applied Mathematics · doi:10.1137/0111030 · Cited by 30,728
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
A method for the solution of certain non-linear problems in least squares
Levenberg, K. (1944) · Quarterly of Applied Mathematics · doi:10.1090/qam/10666 · Cited by 12,753
Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool
Chen, E. Y., Tan, C. M., Kou, Y., Duan, Q., Wang, Z., Meirelles, G. V., Clark, N. R., & Ma’ayan, A. (2013) · BMC Bioinformatics · doi:10.1186/1471-2105-14-128 · Cited by 7,814
Sokoloff, L., Reivich, M., Kennedy, C., Rosiers, M. H. D., Patlak, C. S., Pettigrew, K. D., Sakurada, O., & Shinohara, M. (1977) · Journal of Neurochemistry · doi:10.1111/j.1471-4159.1977.tb10649.x · Cited by 6,000
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
The Warburg Effect: How Does it Benefit Cancer Cells?
Liberti, M. V., & Locasale, J. W. (2016) · Trends in Biochemical Sciences · doi:10.1016/j.tibs.2015.12.001 · Cited by 5,150
A cell initiating human acute myeloid leukaemia after transplantation into SCID mice
Lapidot, T., Sirard, C., Vormoor, J., Murdoch, B., Hoang, T., Caceres-Cortes, J., Minden, M., Paterson, B., Caligiuri, M. A., & Dick, J. E. (1994) · Nature · doi:10.1038/367645a0 · Cited by 4,783
Rappsilber, J., Mann, M., & Ishihama, Y. (2007) · Nature Protocols · doi:10.1038/nprot.2007.261 · Cited by 4,641
Research works printed but not linked: 1
- Frayn, K. N. & Evans, R. Human Metabolism: A Regulatory Perspective (John Wiley & Sons, 2019).
Cited by
Sorted by citations
Items 201–300 of 300
Jin, Z., Li, Y., Ma, Y., Ye, Z., Zhang, Z., Wang, Y., Hu, C., Dong, J., Zhang, X., Xu, Z., et al. (2025) · Genes & Diseases · doi:10.1016/j.gendis.2025.101717 · Cited by 2
Tu, L., Qin, J., Long, Q., Lin, N., Zhao, S., Li, C., Chen, X., & Ye, S. (2025) · Journal of Colloid and Interface Science · doi:10.1016/j.jcis.2025.138263 · Cited by 2
Wu, Y., Jiang, X., Qing, H., Hou, Y., Ma, Y., Wang, T., Wang, K., Qin, L., Cai, W., Xing, Z., et al. (2025) · Research · doi:10.34133/research.0838 · Cited by 2
Mitochondria, OXPHOS, and Cancer Progression: A Modular View
Sokolov, D., & Sullivan, L. B. (2025) · Annual Review of Cancer Biology · doi:10.1146/annurev-cancerbio-071124-125626 · Cited by 2
Tu, X., Li, X., Li, T., Li, X., Zhu, S., Zang, Q., Zhang, H., & Zhang, R. (2025) · Analytical Chemistry · doi:10.1021/acs.analchem.5c03723 · Cited by 2
Zhu, X., Ma, W., Ji, X., He, J., Luo, J., Kong, X., Guo, H., Zhang, L., Ju, Y., Xu, L., et al. (2026) · Cancer Letters · doi:10.1016/j.canlet.2026.218275 · Cited by 2
Pope, A. N., Moose, D. L., Hudson, G., Weresh, H., Dykstra, M., Joshi, A. Y., Breheny, P. J., Taylor, E. B., & Henry, M. D. (2026) · Cell Reports · doi:10.1016/j.celrep.2025.116908 · Cited by 2
Luo, Z., Li, K., Yu, Y., Liu, Y., Weng, H., Zeng, X., Zheng, Y., & Li, W. (2026) · Cancer Research · doi:10.1158/0008-5472.can-25-2792 · Cited by 2
Chai, D., Xi, M., Gao, L., Sun, L., Kong, D., Zhu, Y., Zhang, J. Y., Cai, Q., Xiao, X., & Wang, C. (2026) · Frontiers in Immunology · doi:10.3389/fimmu.2026.1780159 · Cited by 2
Reprogramming lipid metabolism in pediatric cancers
Lindemann, V. L., Noureddine, N., & Morscher, R. J. (2026) · Oncogenesis · doi:10.1038/s41389-026-00617-1 · Cited by 2
Re-evaluating the rationale for targeting oxidative phosphorylation in acute myeloid leukemia
Chrest, B. R., & Fisher‐Wellman, K. H. (2026) · Biochemical Journal · doi:10.1042/bcj20260185 · Cited by 2
Chen, F., Cai, X., Zhou, Q., Huang, Z., Wang, J., Kang, R., Tang, D., & Liu, J. (2026) · APOPTOSIS · doi:10.1007/s10495-026-02408-w · Cited by 2
Yao, S., Liang, Y. I. X. I. U., Liang, X., Su, Q., & Li, X. (2026) · Journal of Biochemical and Molecular Toxicology · doi:10.1002/jbt.71035 · Cited by 2
Badarni, M., Gabbay, S., Elkabets, M., & Rotblat, B. (2023) · Biology · doi:10.3390/biology12070988 · Cited by 2
Enhancing the Treating Efficacy of Immunotherapy through the Restructure of Tumor Microenvironment
Gong, B., Jia, W., Zhou, Y., Xu, Y., Ya, W., & Gao, H. (2023) · Advanced NanoBiomed Research · doi:10.1002/anbr.202300061 · Cited by 2
Nie, X.-H., Li, T.-Z., & Peng, C.-M. (2025) · Pathology - Research and Practice · doi:10.1016/j.prp.2025.155844 · Cited by 2
Hernández‐Esquivel, L., Mazo‐Monsalvo, I. D., Pacheco-Velázquez, S. C., Feregrino-Mondragón, R. D., Robledo‐Cadena, D. X., Sánchez‐Thomas, R., Jasso‐Chávez, R., Saavedra, E., & Marín‐Hernández, Á. (2025) · Frontiers in Oncology · doi:10.3389/fonc.2025.1557638 · Cited by 2
Li, Y., Guo, T., He, J., Liu, D., Peng, S., & Xu, A. (2025) · International Immunopharmacology · doi:10.1016/j.intimp.2025.114505 · Cited by 2
Metabolic pathway analysis of tumors using stable isotopes
Bi, Q., Zhao, J., Nie, J. H., & Huang, F. (2025) · Seminars in Cancer Biology · doi:10.1016/j.semcancer.2025.05.002 · Cited by 3
Laro, J. A., Ness, M., Godinho, J. L. P., Coats, R., & McCall, L. (2025) · Methods · doi:10.1016/j.ymeth.2025.09.004 · Cited by 2
Zheng, W., Yang, H., Lin, H., & Huang, H. (2023) · Molecular & Cellular Toxicology · doi:10.1007/s13273-023-00395-6 · Cited by 2
Kakafika, M. G., Lyta, A., Gavriilidis, G. I., Tsiftsoglou, S. A., Miliotou, Α. N., Pappas, I. S., Vizirianakis, I. S., Papadopoulou, L. C., & Tsiftsoglou, A. S. (2024) · International Journal of Oncology · doi:10.3892/ijo.2024.5630 · Cited by 3
Fung, T. S., Ghosh, A., Tigano, M., Higgs, H. N., & Chakrabarti, R. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.07.26.605389 · Cited by 2
Ye, J., Jiang, H., Tiche, S. J., He, C. J., Liu, J., Bian, F., Jedoui, M., Forgo, B. L., Islam, M. T., Zhao, M., et al. (2024) · Research Square · doi:10.21203/rs.3.rs-5494402/v1 · Cited by 2
Self-citationOverflow metabolism originates from growth optimization and cell heterogeneityPreprint
Wang, X. (2025) · eLife · doi:10.7554/elife.94586.3 · Cited by 2
Genome-wide CRISPRi screen identifies basigin loss as protective in cardiac hypoxiaPreprint
Flanigan, W., Midha, A. D., Blume, S. Y., Martí-Mateos, Y., Costa, M. W., Huang, Y., Baik, A. H., Huynh, H., Susarla, G., Bennett, N. K., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.01.26.701810 · Cited by 2
Polyurea-magnetic hierarchical porous composites for profiling of anionic metabolites
Zhang, R., Lai, Z., Tian, H., Wang, M., Guo, Y.-Y., Zhang, M., Zhou, J., Yao, M., & Li, Z. (2023) · Analytical Methods · doi:10.1039/d3ay01718d · Cited by 1
A novel m.5906G > a variant in MT-CO1 causes MELAS/Leigh overlap syndrome
Liu, Z., Xie, Y., Lou, X., Zeng, X., Zhang, L., Yu, M., Wang, J., Li, J., Shen, D., Li, H., et al. (2024) · Molecular Genetics and Genomics · doi:10.1007/s00438-024-02181-y · Cited by 1
Effects of the number of ethylene glycol units on the efficacy of novel complex I inhibitor 9bw
Sekimoto, K., Kinjo, H., Murakami, M., Ohashi, A., Fukui, R., Nagasaki‐Maeoka, E., Inagaki, Y., Takayama, T., Ikeda, K., Takayama, K., et al. (2025) · Biochemistry and Biophysics Reports · doi:10.1016/j.bbrep.2025.101981 · Cited by 1
Research trends on lactate in cancer: a bibliometric analysis and comprehensive review (2015–2024)
Li, S., Yang, Z., Lv, M., Zong, L., Xie, Y., Cai, Z., Zhang, Y., Wang, Z., Liu, Z., & Sang, L. (2025) · Frontiers in Immunology · doi:10.3389/fimmu.2025.1587867 · Cited by 1
Impact of physiological media on acute myeloid leukemia bioenergetics and cell proliferation
Chrest, B. R., Montgomery, M. M., Aruleba, R. T., Krassovskaia, P. M., Pacheco, E. A., Hagen, J. T., Vandiver, K. J., Tung, K., Alexander, M., Williamson, N. C., et al. (2025) · Cancer & Metabolism · doi:10.1186/s40170-025-00395-1 · Cited by 1
Ji, X., Zhang, W., Xue, F., Zeng, J., Zhao, Q., Sun, X., Sun, J. H., Zhou, H., Xu, Q., Ma, G., et al. (2025) · Advanced Science · doi:10.1002/advs.202507533 · Cited by 1
Li, D., & Zhou, L. (2025) · Journal of Cellular and Molecular Medicine · doi:10.1111/jcmm.70922 · Cited by 1
Wang, Z., Dai, B., Zhang, J., Wu, Y., Li, Y., Cao, Y. J., You, Q., Wang, W., Singhal, S. K., Nie, S., et al. (2025) · Med-X · doi:10.1007/s44258-025-00072-4 · Cited by 1
Rethinking mitochondria as a target for cancer therapy
Minarrieta, L., & St‐Pierre, J. (2026) · Trends in Molecular Medicine · doi:10.1016/j.molmed.2025.12.002 · Cited by 1
Chen, Y., Wang, L., & Ding, J. (2026) · Genes & Diseases · doi:10.1016/j.gendis.2026.102231 · Cited by 1
Self-citationZhang, L., Zhang, Y., 韩流, Wang, J., Hou, L., & Fu, S. (2026) · Molecular Medicine · doi:10.1186/s10020-026-01521-5 · Cited by 2
Metabolic danger signals: TCA cycle metabolites regulate immunity and disease
Ryan, T. A. J., & Zanoni, I. (2026) · Cell chemical biology · doi:10.1016/j.chembiol.2026.07.004 · Cited by 1
CAR signaling instructs divergent metabolic reprogramming and functional fates in αβ and γδ T cells
Bustos, X. E., Tordesillas, L., Martinez-Planes, E., Fontela, M. G., Snedal, S. A., Rossetti, R., Izumi, V., Fang, B., Koomen, J. M., Welsh, E. A., et al. (2026) · Cellular & Molecular Immunology · doi:10.1038/s41423-026-01475-y
Large-scale metabolite imaging gallery of mouse organ tissues to study spatial metabolismPreprint
Phapale, P. B., Smith, K. W., Fecke, A., & Kasarla, S. S. (2024) · Research Square · doi:10.21203/rs.3.rs-3891634/v1 · Cited by 1
A critical role of protein damage response in mediating cancer drug resistancePreprint
Shao, F., Li, J., Xiao, H., Li, L., Li, B., Chen, Y. H., Chu, X., Ran, M., Tang, D., Peng, Y., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.07.17.603840 · Cited by 1
Self-citationZhou, S. X., Madden, B. J., Charlesworth, C. M., Hitosugi, T., Favier, J., & Maher, L. J., III (2026) · Journal of Biological Chemistry · doi:10.1101/2025.08.01.668168 · Cited by 1
Tumor Genotype Dictates Mitochondrial and Immune Vulnerabilities in Liver CancerPreprint
Ünlü, G., Millet, A., Wangdu, K., Donné, R., Erdal, R., DelGaudio, N. L., Uygur, B., Shah, V., Cho, K., Fecke, A., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.09.10.675369 · Cited by 1
Mapping the mammalian dark metabolome by in vivo isotope tracingPreprint
MacArthur, M. R., Raeber, J., Lu, W., Qiang, H., Schueppert, A. V., Ayres, L. B., Cordova, R. A., Neinast, M. D., Leiva, E., Pham, V. N., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.03.31.713900 · Cited by 1
Self-citationBarnhart, B., Kan, T., Srivastava, A., Wessner, C. E., Waters, J., Ambelil, M., Eisenbrey, J. R., Hoek, J. B., & Vadigepalli, R. (2023) · Frontiers in Physiology · doi:10.3389/fphys.2023.1102393
Flux measurements of the tricarboxylic acid cycle in the tumors of mice
Liu, S., & Locasale, J. W. (2023) · Life Metabolism · doi:10.1093/lifemeta/load020 · Cited by 1
Lin, T.-Y., Li, P., Lin, Y.-H., Shih, J., Lin, T., Gu, S., Chou, T., Lee, Y., Lang, Y., & Chang, S.-F. (2023) · Research Square · doi:10.21203/rs.3.rs-3371799/v1
Approaches to Study Tumor Metabolism in MicePreprint
Gültekin, Y., Heiden, M. G. V., & Lien, E. C. (2023) · Cold Spring Harbor Perspectives in Medicine · doi:10.1101/cshperspect.a041420
Fan, M., Hu, J., Xu, X., Chen, J., Zhang, W., Zheng, X., Pan, J., Xu, W., & Feng, S. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.12.17.570960
Mini review of metabolism in leukaemia: from complexity to the clinic
Rattigan, K. M. (2024) · Frontiers in Hematology · doi:10.3389/frhem.2023.1353994
Balcke, G. U., Saoud, M., Grau, J., Rennert, R., Mueller, T., Yousefi, M., Davari, M. D., Hause, B., Csük, R., Rashan, L. J., et al. (2024) · Research Square · doi:10.21203/rs.3.rs-3494185/v1
Ottestad, A. L., Johansen, H., Halvorsen, T. O., Dai, H. Y., Wahl, S. G. F., Emdal, E. F., & Grønberg, B. H. (2023) · Figshare · doi:10.6084/m9.figshare.23665299
Ma, D., Wei, P., Liu, H., Hao, J., Chen, Z., Chu, Y., Li, Z., Shi, W., Yuan, Z., Cheng, Q., et al. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4889531
Molecular Mechanisms of Anticarcinogenic Potential of Hydrocotyle umbellata and Its Major Components
Kim, J.-K., Park, S. H., Kim, D.-Y., Ryu, H. W., & Jun, H. S. (2024) · Nutrition and Cancer · doi:10.1080/01635581.2024.2377344
Overflow metabolism originates from growth optimization and cell heterogeneityPreprint
Wang, X. (2024) · eLife · doi:10.7554/elife.94586.2
Neural Ordinary Differential Equations Inspired Parameterization of Kinetic ModelsPreprint
van Lent, P., Bunkova, O., Planken, L., Schmitz, J. P. J., & Abeel, T. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.12.20.629595
Rojas, M., Rodrigo, C., Moreno, R., Cascante, M., & Maurel, J. (2025) · Exploration of Digestive Diseases · doi:10.37349/edd.2025.100564
Jakobsen, E., Bech, J. M., Andersen, J. V., Westi, E. W., Larsen, M. R., Skotte, N. H., Moreira, J. M. A., Aldana, B. I., & Bak, L. K. (2025) · Biochimica et Biophysica Acta (BBA) - Bioenergetics · doi:10.1016/j.bbabio.2025.149567
Alternatively Spliced Citrate Synthase Supports Colorectal Cancer
Schatton, D., & Frezza, C. (2025) · Cancer Research · doi:10.1158/0008-5472.can-25-3356
Mitochondria redistribution organizes the immunosuppressive tumor ecosystemPreprint
Terasaki, A., Weiner, A. T., Tan, Y., Szeifert, V., Bhatnagar, K., Rada, C. C., Shankar, V., Kernick, C., Mahmood, M., Wiggers, L., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.11.11.687895
Guo, Z., Liu, C., Li, J., Chang, D., Bai, L., Duan, G., Li, X., Sun, T., Yu, X.-H., Sheng, J., et al. (2025) · Advanced Functional Materials · doi:10.1002/adfm.202523071
Genetic regulators of neuronal survival across metabolic environmentsPreprint
Bennett, N. K., Soto-Muniz, Y., Meng, J. X., Lee, M., Yang, J. L., Flanigan, W., Pico, A. R., Jain, I. H., & Nakamura, K. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2025.12.19.695350
Zhou, W., Tang, M., He, D., Shen, Y., Huang, Z., Xia, W., Wu, Z., Wei, W., Zheng, H., Wang, Q., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26693991
Self-citationMichaels, A. M., Zoccarato, A., Hoare, Z., Firth, G., Chung, Y. J., Kuchel, P. W., Shah, A. M., Shattock, M. J., Southworth, R., & Eykyn, T. R. (2024) · Figshare · doi:10.6084/m9.figshare.26724914
Zhou, W., Tang, M., He, D., Shen, Y., Huang, Z., Xia, W., Wu, Z., Wei, W., Zheng, H., Wang, Q., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26693988
Self-citationOttestad, A. L., Johansen, H., Halvorsen, T. O., Dai, H. Y., Wahl, S. G. F., Emdal, E. F., & Grønberg, B. H. (2023) · Figshare · doi:10.6084/m9.figshare.23665302
Zhou, W., Tang, M., He, D., Shen, Y., Huang, Z., Xia, W., Wu, Z., Wei, W., Zheng, H., Wang, Q., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26693979
Self-citationZhou, W., Tang, M., He, D., Shen, Y., Huang, Z., Xia, W., Wu, Z., Wei, W., Zheng, H., Wang, Q., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26693985
Self-citationZhou, W., Tang, M., He, D., Shen, Y., Huang, Z., Xia, W., Wu, Z., Wei, W., Zheng, H., Wang, Q., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26693982
Self-citationDong, H., Gao, Y., Jiang, D., Feng, C., Gu, X., Cai, X., Liu, Y., Zhang, G., Wen, J., Diao, W., et al. (2025) · Cancers · doi:10.3390/cancers18010092
Paul, D. (2025) · Springer eBooks · doi:10.1007/978-3-032-08808-6_7
Methodologies for monitoring alkaliptosis in cancer cells
Chen, F., Kang, R., Liu, J., & Tang, D. (2026) · Methods in cell biology · doi:10.1016/bs.mcb.2026.01.011
Cao, Y., Tan, Y., Li, C., Long, E., & Wang, L. (2026) · The Analyst · doi:10.1039/d6an00012f
Self-citationYang, S. R. E., Xiao, Z., Wang, M., Wang, L.-L., & Tang, Y.-H. (2026) · Sensors and Actuators B Chemical · doi:10.1016/j.snb.2026.139836
Self-citationXu, N., Zhang, L., Yao, Z., Li, L., Cai, M., Wang, Y., Wang, X., Tan, S., Li, K., Lyu, J., et al. (2026) · Molecular & Cellular Proteomics · doi:10.1016/j.mcpro.2026.101568
Jeong, M., Ryu, S.-H., Cho, Y.-J., Na, D.-H., Baek, J., Nah, J., Kim, K. W., & Jung, Y. (2026) · Cell Death and Disease · doi:10.1038/s41419-026-08777-z
Lyu, Y., Guo, R., Gui, B., Zhong, W., & Zhu, L. Y. (2026) · Environment International · doi:10.1016/j.envint.2026.110308
Li, T., Zang, Q., Zhu, S., Tu, X., Li, X., Liu, J., Zhang, Y., & Zhang, R. (2026) · Journal of Pharmaceutical Analysis · doi:10.1016/j.jpha.2026.101707
Li, M., Zhang, J., Zhang, H., Chen, X., Zou, X., Wang, J., Huang, W., Peng, H., Jia, H., & Hou, Z. (2026) · Cell Reports · doi:10.1016/j.celrep.2026.117621
Yang, R., Ge, Q., Wu, F., 龙满美, Li, B., Hong, Z., Xu, W., Guo, M., Feng, T., Tian, X., et al. (2026) · Oncogene · doi:10.1038/s41388-026-03867-w
Lesner, N. P., Kim, L. C., Shelton, S. D., Landis, M. D., Cai, X., Zheng, D., Parnaik, T. S., Bartman, C., Keith, B., & Simon, M. C. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.07.13.738248
Self-citationWang, L., Ren, X., Su, N., Mi, Q., Liu, R., Chong, H., Chen, X., & Huang, Q. Y. (2026) · Analytica Chimica Acta · doi:10.1016/j.aca.2026.346070
Self-citationThe microenvironment dictates glyco-immune surveillance via HSF1-mediated metabolism
Tharp, K. M., Park, S., Timblin, G. A., Richards, A., Berg, J. A., Twells, N. M., Riley, N. M., Alvarez, K., Lee, A., Peltan, E. L., et al. (2026) · Science Advances · doi:10.1126/sciadv.aeb1136
Niu, S., Sun, H., Wang, Z., Jin, Q., Sun, Z., Yu, D., & Zhang, Y. (2026) · Frontiers in Oncology · doi:10.3389/fonc.2026.1885113
Zhao, Y., Linghu, T., Wang, Q., Gao, X., Qin, X., & Tian, J. (2026) · Analytical Chemistry · doi:10.1021/acs.analchem.6c00087
Mitochondria as central regulators of cancer progression and antitumor immunity
Gómez-Durán, A., & Martínez‐Reyes, I. (2026) · Trends in Endocrinology and Metabolism · doi:10.1016/j.tem.2026.07.005
Targeting metabolic reprogramming in cancer: Past, present, and future
Kumari, N., Shukla, S. K., & Thakur, R. (2026) · Pharmacology & Therapeutics · doi:10.1016/j.pharmthera.2026.109109
Decoding T cell exhaustion in the tumour microenvironment
Park, J. A., Im, J., & Hwang, S.-M. (2026) · Experimental & Molecular Medicine · doi:10.1038/s12276-026-01809-w · Cited by 2
Photoactivated tetrahedral DNA nanostructure for intracellular imaging of ATP
He, S., Tan, H., Zhao, J., Yuan, R., Ruan, Y., & Chen, S. (2026) · Analytica Chimica Acta · doi:10.1016/j.aca.2026.346220
Jordan, H. A., Tandurella, J. A., Vengayil, V., Parnaik, T. S., Pokharel, S. M., Mulka, K. R., Cherry, S. R., Wherry, E. J., & Bartman, C. (2026) · Journal of Biological Chemistry · doi:10.1016/j.jbc.2026.113519
Self-citationA simple, anesthesia-free infusion technique for in vivo metabolic tracing
Kim, Y., Caldwell, S., Long, M., ABRAHAMS, D., Baldwin, M. W., & DeNicola, G. M. (2026) · Science Advances · doi:10.1126/sciadv.aeg1157
Metabolites and cancer metastasis
Yang, S., Shi, S., Hou, J., Zhang, J., & Su, Z. (2026) · Oncogene · doi:10.1038/s41388-026-03930-6
Chen, X., Su, Y., Ni, Z., Lu, Y., Zhou, Y., 黄剑飞, & Jiang, J. (2026) · International Immunopharmacology · doi:10.1016/j.intimp.2026.117515
Disentangling the Crabtree and Warburg effects across syngeneic non-tumor and tumor cellsPreprint
Duraj, T., Miller, E. Y., Ta, N. L., Lee, C., Lee, D. C., Ramos, M. B., Aristizabal‐Henao, J. J., Kiebish, M., Mukherjee, P., Pellicer, M. B., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.10.06.756891
Zhang, Y., Dong, Y., Chen, S., Li, M., Liu, X., Hou, J., & Zhou, S. (2026) · 中国科学通报:英文版 · doi:10.1016/j.scib.2026.10.019
Qian, J., Wang, M., Liu, J., & Gao, M. (2026) · Cancer Reports · doi:10.1002/cnr2.70723
Xu, T., Luo, Y., Zheng, R., Yang, L., & Wang, M. (2026) · Chemical Communications · doi:10.1039/d6cc06324a
Self-citationNitaramorn, N., Kobpornchai, P., & Kulkeaw, K. (2026) · Methods · doi:10.1016/j.ymeth.2026.10.009
Metadata
- Authors
- Bartman, C. R., Weilandt, D. R., Shen, Y., Lee, W. D., Han, Y., TeSlaa, T., Jankowski, C. S. R., Samarah, L., Park, N. R., da Silva-Diz, V., Aleksandrova, M., Gultekin, Y., Marishta, A., Wang, L., Yang, L., Roichman, A., Bhatt, V., Lan, T., Hu, Z., Xing, X., Lu, W., Davidson, S., Wühr, M., Vander Heiden, M. G., Herranz, D., Guo, J. Y., Kang, Y., & Rabinowitz, J. D.
- Affiliations
- Princeton University (US)
- University of California, Los Angeles (US)
- Rutgers, The State University of New Jersey (US)
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- Corresponding author
- Rabinowitz, Joshua D.
- ORCID
- Bartman, Caroline R.
- Weilandt, Daniel R.
- Shen, Yihui
- Lee, Won Dong
- Han, Yujiao
- TeSlaa, Tara
- Jankowski, Connor S. R.
- Samarah, Laith
- Park, Noel R.
- da Silva-Diz, Victoria
- Aleksandrova, Maya
- Wang, Lin
- Yang, Lifeng
- Roichman, Asael
- Bhatt, Vrushank
- Lan, Taijin
- Hu, Zhixian
- Xing, Xi
- Lu, Wenyun
- Davidson, Shawn
- Wühr, Martin
- Vander Heiden, Matthew G.
- Herranz, Daniel
- Guo, Jessie Yanxiang
- Kang, Yibin
- Rabinowitz, Joshua D.
- Venue
- Nature
- Published
- 2023-02-01
- Volume
- 614
- Issue
- 7947
- Pages
- 349-357
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC10288502
- OpenAlex
- W4318771331
- Cited by
- 299
- References
- 83
- Citations by year
- 2026: 49 · 2025: 93 · 2024: 97 · 2023: 60
- FWCI
- 38.49
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- Damon Runyon Cancer Research Foundation
- Leukemia and Lymphoma Society (1386-23)
- Ludwig Institute for Cancer Research
- National Institutes of Health
- Stand Up To Cancer (SU2C-AACR-DT-20-16, T32GM007388)
- National Cancer Institute (R01CA236936, K99CA273517, P30CA072720, R01CA237347, R50CA211437, R35CA242379, R01CA163591)
- National Institute of General Medical Sciences (T32GM007388, R35GM128813)
- National Institute of Diabetes and Digestive and Kidney Diseases (F32DK127843, DP1DK113643)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer, Hypoxia, and Metabolism
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolism, Diabetes, and Cancer
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Cancer and biochemical research
- Keywords
- TCA cycle, glycolysis, ATP production, cancer metabolism, Warburg effect, lung metastasis, breast cancer, pancreatic cancer, leukemia, tracer infusion, energy metabolism, protein synthesis
- MeSH terms
- Adenosine Triphosphate, Animals, Breast Neoplasms, Citric Acid Cycle, Deceleration, Energy Metabolism, Glycolysis, Lung Neoplasms, Neoplasm Metastasis, Organ Specificity, Pancreatic Neoplasms, Protein Biosynthesis, Proto-Oncogene Proteins p21(ras), Mice
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