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Carbon source availability drives nutrient utilization in CD8+ T cells
Open accessAbstract
How environmental nutrient availability impacts T cell metabolism and function remains poorly understood. Here, we report that the presence of physiologic carbon sources (PCSs) in cell culture medium broadly impacts glucose utilization by CD8 + T cells, independent of transcriptional changes in metabolic reprogramming. The presence of PCSs reduced glucose contribution to the TCA cycle and increased effector function of CD8 + T cells, with lactate directly fueling the TCA cycle. In fact, CD8 + T cells responding to Listeria infection preferentially consumed lactate over glucose as a TCA cycle substrate in vitro , with lactate enhancing T cell bioenergetic and biosynthetic capacity. Inhibiting lactate-dependent metabolism in CD8 + T cells by silencing lactate dehydrogenase A (Ldha) impaired both T cell metabolic homeostasis and proliferative expansion in vivo . Together, our data indicate that carbon source availability shapes T cell glucose metabolism and identifies lactate as a bioenergetic and biosynthetic fuel for CD8 + effector T cells.
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![Figure 1. Physiologic carbon sources influence glucose utilization by T cells (A) Table highlighting major medium components of IMDM and VIM and physiologic carbon sources (PCSs) used in this study. Concentration ranges for metabolites in mouse serum are provided for comparison (Table S1). (B) Heatmap depicting relative incorporation of 13C from [U-13C]-glucose into the indicated intracellular metabolites from activated CD8+ T cells cultured in IMDM or VIM with (+) or without (−) PCSs. Activated (CD44+) T cells were cultured in the indicated medium containing [U-13C]-glucose for 2 or 24 h (n = 3/group). (C) Mass isotopologue distribution (MID) for [U-13C]-glucose-derived metabolites for activated CD8+ T cells cultured in IMDM (gray) or VIM (blue) with or without PCSs. Shown are MID labeling patterns for select metabolites after 2 h of culture as in (B) (mean ± SEM, n = 3/group). (D) MID labeling patterns for [U-13C]-glucose-derived citrate and malate for CD8+ T cells cultured in IMDM (gray) or VIM (blue) with or without PCSs for 24 h as in (B) (mean ± SEM, n = 3/group). (E) Fractional enrichment of [U-13C]-glucose-derived carbon in TCA cycle intermediates in activated CD8+ T cells. T cells activated as in (B) were cultured with [U-13C]-glucose in VIM or VIM plus PCS (VIMPCS) for 24 h. For infusion samples (in vivo), fractional enrichment of [U-13C]-glucose into TCA cycle intermediates was determined relative to [U-13C]-glucose abundance in spleen (mean ± SEM, n = 3–6/sample) (data from Ma et al., 2019). *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001; ns, not significant.](/paper-figures/b6f24b26873f467ebd8a8c49b924722f/carbon-source-availability-drives-nutrient-utilization-in-cd8-t-cells-figure-1.jpg)
![Figure 2. Physiologic carbon sources influence T cell metabolism independent of metabolic programming A–C) PCA for CD8+ T cells cultured for 24 h in IMDM or VIM with or without PCSs as in Figure 1B. Shown are data for total mRNA expression (A), mRNA expression for KEGG central carbon metabolism genes (B), and [U-13C]-glucose-derived metabolites (C) (mean ± SEM, n = 3/group). (D–F) Metabolic flux modeling of central carbon metabolism in CD8+ T cells as determined using 13C-glucose tracing data from Figure 1B. Significant (p < 0.05) differences in net flux are indicated by color and bar weight (red, increased; blue, decreased). (D) Net fluxes for CD8+ T cells cultured for 24 h in VIM relative to IMDM. (E and F) Net fluxes for CD8+ T cells cultured for 24 h in VIM (E) or IMDM (F) containing or lacking PCSs (i.e., PCSs versus unsupplemented medium). Refer to Table S2 for details of flux analysis.](/paper-figures/b579e9c0ebf344ad8907791e73073d9f/carbon-source-availability-drives-nutrient-utilization-in-cd8-t-cells-figure-2.jpg)
![Figure 3. Physiologic carbon sources contribute to TCA cycle metabolism and biosynthesis (A) Schematic depicting potential contribution of carbon sources to TCA cycle metabolism. Enzyme reactions localized to the cytosol and mitochondrion are indicated, with metabolic enzymes listed in gray. (B) Heatmap depicting relative contribution of 13C from indicated [U-13C]-labeled substrates into metabolites of central carbon metabolism in activated CD8+ T cells after 24 h of culture (n = 3/group). (C) MIDs for [U-13C]-PCS-derived carbon into citrate, malate, glutamate, and aspartate for CD8+ T cells cultured as in Figure 1B. Shown are individual isotopologues derived from acetate, βOHB, glucose, and lactate after 24 h of culture (mean ± SEM, n = 3/group). (D) Schematic showing pathways for UTP synthesis from glucose and PCSs. (E) MIDs for [U-13C]-glucose-derived UTP for activated CD8+ T cells cultured in IMDM or VIM with or without PCSs. Shown are MID labeling patterns from [U-13C]-glucose into UTP after 24 h of culture (mean ± SEM, n = 3/group). (F) MID labeling pattens in UTP and carbamoyl-aspartate for in vitro-activated CD8+ T cells cultured in VIMPCS for 24 h. Shown are individual isotopologues derived from specific metabolites as in (C) (mean ± SEM, n = 3/group). (G and H) MIDs for [U-13C]-glucose-derived citrate (G) and UTP (H) for activated CD8+ T cells cultured for 24 h in VIM supplemented with indicated concentrations of lactate (mean ± SEM, n = 3/group). (I) Change in MID from [U-13C]-glucose into indicated metabolite isotopologues in activated CD8+ T cells cultured for 24 h in VIM containing increasing concentrations of lactate. Changes in MID were determined relative to cells cultured in VIM containing no lactate (mean ± SEM, n = 3/group).](/paper-figures/b4ad93d27d11448dacb9b23f1722c3fa/carbon-source-availability-drives-nutrient-utilization-in-cd8-t-cells-figure-3.jpg)

![Figure 5. Lactate is a physiologic fuel for CD8+ T cells (A) Schematic of [U-13C]-glucose (blue) and [U-13C]-lactate (green) tracing into TCA cycle intermediates and TCA cycle-derived metabolites (i.e., aspartate). (B) [U-13C]-glucose (5 mM) and [U-13C]-lactate (2 mM) labeling into lactate in activated CD8+ T cells after 4 h of culture (mean ± SEM, n = 3/group). Left: fractional enrichment of [U-13C]-glucose and [U-13C]-lactate carbon into the lactate pool. Right: total abundance of [U-13C]-glucose- or [U-13C]-lactate-derived lactate in activated CD8+ T cells cultured in VIM lacking (−) or containing (+) 2 mM lactate. (C) [U-13C]-glucose and [U-13C]-lactate labeling into pyruvate for T cells cultured as in (B) (mean ± SEM, n = 3/group). Left: fractional enrichment of [U-13C]-glucose and [U-13C]-lactate carbon into the pyruvate pool. Right: total abundance of [U-13C]-glucose- or [U-13C]-lactate-derived pyruvate in T cells cultured without (−) or with (+) 2 mM lactate. (D–F) Fractional enrichment of [U-13C]-glucose and [U-13C]-lactate in intracellular (D) lactate, (E) TCA cycle intermediates (citrate, malate, and aspartate), and (F) acetyl-carnitine in OT-I CD8+ T cells isolated from LmOVA-infected mice at 3 dpi. Isolated T cells were cultured ex vivo in VIM containing 5 mM glucose and 2 mM lactate (either 12C or 13C) for 4 h (mean ± SEM, n = 4/group). (G) Bioenergetic profile of in vitro-activated CD8+ T cells cultured with no (Ctrl) or 2 mM lactate (+Lac) (mean ± SD, n = 20–22/group). Left: OCR plot for activated CD8+ T cells over time. Time of addition of oligomycin, fluoro-carbonyl cyanide phenylhydrazone (FCCP), and rotenone and antimycin A (rot./AA) are indicated. Right: maximal ATP production rates from OXPHOS. (H and I) MID of [U-13C]-glucose and [U-13C]-lactate carbon in (H) UTP or (I) palmitate for in vitro-activated CD8+ T cells cultured in VIM for 4 h (H) or 24 h (I) (mean ± SEM, n = 3/group).](/paper-figures/6c44fb540b944de9902a34b00830e357/carbon-source-availability-drives-nutrient-utilization-in-cd8-t-cells-figure-5.jpg)
![Figure 6. Ldha regulates T cell metabolism and effector cell expansion in vivo (A) Immunoblot of Ldha and actin protein levels in whole cell lysates from activated CD8+ T cells expressing a control (Ctrl) or Ldha-targeting (shLdha) shRNA. (B) Relative abundance of intracellular [U-13C]-lactate-derived lactate (Lac) and pyruvate (Pyr) in activated CD8+ T cells expressing a control (Ctrl) or Ldha-targeting (shLdha) shRNA. T cells were cultured in VIM containing 5 mM glucose and 2 mM [U-13C]-lactate for 4 h (mean ± SEM, n = 3/group). (C) Basal (left) and maximal (right) ATP production rates from OXPHOS for CD8+ T cells expressing a control (Ctrl) or Ldha-targeting (shLdha) shRNA cultured as in (B) (mean ± SD, n = 10–24/group). (D) Relative abundance of intracellular [U-13C]-glucose-derived lactate (Lac) in control (Ctrl) or shLdha-expressing CD8+ T cells cultured with 5 mM [U-13C]-glucose and 2 mM lactate for 4 h (mean ± SEM, n = 3/group). (E) Flow cytometry plots showing abundance of OVA-specific Thy1.1+ OT-I T cells in the spleen of LmOVA-infected mice 7 dpi. Right: percentage and total number of Thy1.1+ CD8+ OT-I T cells (mean ± SEM, n = 5 mice/shRNA). (F) Flow cytometry plots showing the percentage of IFN-γ+ control (Ctrl) or shLdha-expressing Thy1.1+ CD8+ OT-I T cells in the spleen of LmOVA-infected mice 7 dpi. Right: percentage and total number of IFN-γ+ Thy1.1+ CD8+ T cells (mean ± SEM, n = 5 mice/shRNA). (G and H) MIDs for indicated intracellular metabolites in activated control (Ctrl) or shLdha-expressing CD8+ T cells. Cells were cultured for 4 h in VIM containing (G) 2 mM [U-13C]-lactate and unlabeled 5 mM glucose or (H) 5 mM [U-13C]-glucose and unlabeled 2 mM lactate (mean ± SEM, n = 3/group). (I) [U-13C]-lactate and [U-13C]-glucose labeling into palmitate (in VIM for 24 h) in activated CD8+ T cells expressing a control (Ctrl) or Ldha-targeting (shLdha) shRNA (mean ± SEM, n = 3/group). (J) Heatmap depicting relative abundance of intracellular metabolites in activated control (Ctrl) or shLdha-expressing CD8+ T cells following 4 h culture in VIM. Shown are the top 45 significant metabolites (p < 0.05) based on differential metabolite levels between groups (n = 6/group). (K) NAD+:NADH ratio for control (Ctrl) or shLdha-expressing CD8+ T cells cultured for 2 h in VIM containing 0 or 2 mM sodium lactate (n = 2–4/group). (L) NAD+ abundance in activated CD8+ T cells expressing a control (Ctrl) or Ldha-targeting (shLdha) shRNA following 4 h culture in VIM (mean ± SEM, n = 6/group).](/paper-figures/734f0581ac844f70a9cdf5f059b6750c/carbon-source-availability-drives-nutrient-utilization-in-cd8-t-cells-figure-6.jpg)
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“Also, CD8+ T cells preferentially utilize non-glucose physiologic carbon sources as metabolic fuel, and their activation and effector function are regulated by carbon availability.9”
From SGLT2 inhibitor promotes ketogenesis to improve MASH by suppressing CD8+ T cell activation (2024) · cites this paper as [9]
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“Also, CD8+ T cells preferentially utilize non-glucose physiologic carbon sources as metabolic fuel, and their activation and effector function are regulated by carbon availability.9”
From SGLT2 inhibitor promotes ketogenesis to improve MASH by suppressing CD8+ T cell activation (2024) · cites this paper as [9]
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A RAPID METHOD OF TOTAL LIPID EXTRACTION AND PURIFICATION
Bligh, E. G., & Dyer, W. J. (1959) · Canadian Journal of Biochemistry and Physiology · doi:10.1139/o59-099 · Cited by 54,751 · cited 1×
“…saline and centrifuged before being snap frozen on dry-ice and stored at −80°C. Metabolites were extracted by modified Bligh-Dyer extraction (Bligh and Dyer, 1959) by the addition of ice-cold methanol (A456, Fisher Scientific) directly to frozen cells, to which one volume of chloroform…”
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 guide to immunometabolism for immunologists
O'Neill, L. A. J., Kishton, R. J., & Rathmell, J. (2016) · Nature Reviews Immunology · doi:10.1038/nri.2016.70 · Cited by 3,315
Posttranscriptional Control of T Cell Effector Function by Aerobic Glycolysis
Chang, C.-H., Curtis, J. D., Maggi, L. B., Faubert, B., Villarino, A. V., O’Sullivan, D., Huang, S. C.-C., van der Windt, G. J. W., Blagih, J., Qiu, J., et al. (2013) · Cell · doi:10.1016/j.cell.2013.05.016 · Cited by 2,204
Self-citationThe transcription factor Myc controls metabolic reprogramming upon T lymphocyte activation
Wang, R., Dillon, C. P., Shi, L. Z., Milasta, S., Carter, R., Finkelstein, D., McCormick, L. L., Fitzgerald, P., Chi, H., Munger, J., et al. (2011) · Immunity · doi:10.1016/j.immuni.2011.09.021 · Cited by 2,140 · cited 2×
“Upon activation, CD8 + T cells undergo extensive metabolic reprogramming characterized by transcriptional changes in metabolic gene expression (Wang et al., 2011).”
LDHA-Associated Lactic Acid Production Blunts Tumor Immunosurveillance by T and NK Cells
Brand, A., Singer, K., Koehl, G. E., Kolitzus, M., Schoenhammer, G., Thiel, A., Matos, C., Bruss, C., Klobuch, S., Peter, K., et al. (2016) · Cell Metabolism · doi:10.1016/j.cmet.2016.08.011 · Cited by 2,039
Inhibitory effect of tumor cell-derived lactic acid on human T cells
Fischer, K., Hoffmann, P., Voelkl, S., Meidenbauer, N., Ammer, J., Edinger, M., Gottfried, E., Schwarz, S., Rothe, G., Hoves, S., et al. (2007) · Blood · doi:10.1182/blood-2006-07-035972 · Cited by 1,946
Glucose feeds the TCA cycle via circulating lactate
Hui, S., Ghergurovich, J. M., Morscher, R. J., Jang, C., Teng, X., Lu, W., Esparza, L. A., Reya, T., Zhan, L., Yanxiang Guo, J., et al. (2017) · Nature · doi:10.1038/nature24057 · Cited by 1,721
Transcriptional control of effector and memory CD8+ T cell differentiation
Kaech, S. M., & Cui, W. (2012) · Nature Reviews Immunology · doi:10.1038/nri3307 · Cited by 1,628
The CD28 Signaling Pathway Regulates Glucose Metabolism
Frauwirth, K. A., Riley, J. L., Harris, M. H., Parry, R. V., Rathmell, J. C., Plas, D. R., Elstrom, R. L., June, C. H., & Thompson, C. B. (2002) · Immunity · doi:10.1016/s1074-7613(02)00323-0 · Cited by 1,475 · cited 1×
“…taken up by activated T cells and is a major substrate fueling central carbon metabolism (i.e., glycolysis; the pentose phosphate pathway [PPP]; serine, glycine, and one-carbon [SGOC] metabolism; the TCA cycle; and nucleotide metabolism) in T cells (Frauwirth et al., 2002; Wang et al., 2011).”
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Lee, H., Jeon, J., & Kim, E. S. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2023.1219422 · Cited by 33
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Self-citationFarsani, S. S. M., & Verma, V. (2023) · Frontiers in Oncology · doi:10.3389/fonc.2023.1175532 · Cited by 33
Targeting glycolysis: exploring a new frontier in glioblastoma therapy
Yang, L., Li, S., Yu, L., Leng, J., & Li, N. (2025) · Frontiers in Immunology · doi:10.3389/fimmu.2024.1522392 · Cited by 28
The role of tumor metabolism in modulating T-Cell activity and in optimizing immunotherapy
Ganjoo, S., Gupta, P., Corbali, H. I., Nanez, S., Riad, T. S., Duong, L. K., Barsoumian, H. B., Masrorpour, F., Jiang, H., Welsh, J. W., et al. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2023.1172931 · Cited by 32
Oncometabolites in cancer: from cancer cells to the tumor microenvironment
Chen, L., & Huang, M. (2024) · Holistic Integrative Oncology · doi:10.1007/s44178-024-00096-7 · Cited by 28
Zeng, Y., Huang, Y., Tan, Q., Peng, L., Wang, J., Tong, F., & Dong, X. (2024) · Molecular Medicine Reports · doi:10.3892/mmr.2024.13413 · Cited by 31
Metabolic reprogramming of immune cells in MASH
Ma, C., Wang, S., Dong, B., & Tian, Y. (2025) · Hepatology · doi:10.1097/hep.0000000000001371 · Cited by 32
Glucose-dependent glycosphingolipid biosynthesis fuels CD8+ T cell function and tumor control
Longo, J., DeCamp, L. M., Oswald, B. M., Teis, R., Reyes-Oliveras, A., Dahabieh, M. S., Ellis, A. E., Vincent, M. P., Damico, H., Gallik, K. L., et al. (2025) · Cell Metabolism · doi:10.1016/j.cmet.2025.07.006 · Cited by 30
Self-citationTumor-intrinsic metabolic reprogramming and how it drives resistance to anti-PD-1/PD-L1 treatment
Laubach, K., Turan, T., Mathew, R. S., Wilsbacher, J. L., Engelhardt, J., & Samayoa, J. A. (2023) · Cancer Drug Resistance · doi:10.20517/cdr.2023.60 · Cited by 27
Metabolic plasticity of T cell fate decision
Pan, X., Wang, J., Zhang, L., Li, G., & Huang, B. (2023) · Chinese Medical Journal · doi:10.1097/cm9.0000000000002989 · Cited by 26
A diverse proteome is present and enzymatically active in metabolite extracts
House, R. J., Soper-Hopper, M. T., Vincent, M. P., Ellis, A. E., Capan, C. D., Madaj, Z., Wolfrum, E., Isaguirre, C., Castello, C. D., Johnson, A., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-50128-z · Cited by 32
Self-citationBritt, E. C., Qing, X., Votava, J. A., Lika, J., Wagner, A. S., Shen, S., Arp, N. L., Khan, H., Schieke, S. M., Fletcher, C. D. �., et al. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2321212121 · Cited by 25
Pivotal role of exogenous pyruvate in human natural killer cell metabolism
Coquillat, N. K., Picq, L., Hamond, A., Megy, P., Benezech, S., Drouillard, A., Lager-Lachaud, N., Cahoreau, E., Moreau, M., Fallone, L., et al. (2025) · Nature Metabolism · doi:10.1038/s42255-024-01188-4 · Cited by 24
The prostacyclin receptor PTGIR is a NRF2-dependent regulator of CD8+ T cell exhaustion
Dahabieh, M. S., DeCamp, L. M., Oswald, B. M., Kitchen-Goosen, S. M., Fu, Z. F., Vos, M., Compton, S. E., Longo, J., Foy, N. M., Williams, K. S., et al. (2025) · Nature Immunology · doi:10.1038/s41590-025-02185-9 · Cited by 24
Self-citationThe ATP-exporting channel Pannexin 1 promotes CD8+ T cell effector and memory responses
Vardam-Kaur, T., Banuelos, A., Gabaldon-Parish, M., Macedo, B. D. G., Salgado, C. L., Wanhainen, K. M., Zhou, M. H., van Dijk, S., Santiago-Carvalho, I., Beniwal, A., et al. (2024) · iScience · doi:10.1016/j.isci.2024.110290 · Cited by 25
Lactate in skin homeostasis: metabolism, skin barrier, and immunomodulation
Ruan, D., Hu, T., Yang, X., Mo, X., & Ju, Q. (2025) · Frontiers in Immunology · doi:10.3389/fimmu.2025.1510559 · Cited by 23
The dual role of citrate in cancer
Icard, P., Simula, L., Zahn, G., Alifano, M., & Mycielska, M. E. (2023) · Biochimica et Biophysica Acta (BBA) - Reviews on Cancer · doi:10.1016/j.bbcan.2023.188987 · Cited by 25
Nutrient allocation fuels T cell-mediated immunity
Longo, J., Watson, M. J., Williams, K. S., Sheldon, R. D., & Jones, R. G. (2025) · Cell Metabolism · doi:10.1016/j.cmet.2025.09.008 · Cited by 19
Self-citationThe metabolic cross-talk between cancer and T cells
Miguel, S. C.-D., Lucianer, G., & Elia, I. (2023) · Trends in Biochemical Sciences · doi:10.1016/j.tibs.2023.03.004 · Cited by 22
d'Aria, S., Maquet, C., Li, S., Dhup, S., Lepez, A., Köhler, A., Hée, V. F. V., Dadhich, R. K., Frenière, M., Andris, F., et al. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2306763121 · Cited by 20
Jonker, P. B., & Muir, A. (2024) · Disease Models & Mechanisms · doi:10.1242/dmm.050814 · Cited by 21
Research progress on the regulatory role of lactate and lactylation in tumor microenvironment
Gao, C., Li, J., & Shan, B. (2025) · Biochimica et Biophysica Acta (BBA) - Reviews on Cancer · doi:10.1016/j.bbcan.2025.189339 · Cited by 22
PGC-1β maintains mitochondrial metabolism and restrains inflammatory gene expression
Guak, H., Sheldon, R. D., Beddows, I., Ark, A. V., Weiland, M. J., Shen, H., Jones, R. G., St‐Pierre, J., Ma, E. H., & Krawczyk, C. M. (2022) · Scientific Reports · doi:10.1038/s41598-022-20215-6 · Cited by 17
Self-citationExtracellular domains of CARs reprogramme T cell metabolism without antigen stimulation
Lakhani, A., Chen, X., Chen, L. C., Hong, M., Khericha, M., Chen, Y., Chen, Y. Y., & Park, J. O. (2024) · Nature Metabolism · doi:10.1038/s42255-024-01034-7 · Cited by 21
Mitochondrial fatty acid synthesis and MECR regulate CD4+ T cell function and oxidative metabolism
Steiner, K. K., Young, A., Patterson, A. R., Sugiura, A., Watson, M. J., Preston, S. E. J., Zhelonkin, A. R., Jennings, E. Q., Chi, C., Heintzman, D. R., et al. (2025) · The Journal of Immunology · doi:10.1093/jimmun/vkaf034 · Cited by 17
Self-citationCPT2-mediated Fatty Acid Oxidation Is Dispensable for Humoral Immunity
Li, M., Zhou, X., Zhu, X., Li, Y., Hitosugi, T., Li, Y., & Zeng, H. (2024) · The Journal of Immunology · doi:10.4049/jimmunol.2400285 · Cited by 16
Schofield, J. H., Longo, J., Sheldon, R. D., Albano, E., Ellis, A. E., Hawk, M. A., Murphy, S. P., Duong, L., Rahmy, S., Lü, X., et al. (2024) · Cell Reports · doi:10.1016/j.celrep.2024.113984 · Cited by 15
Self-citationThe potential role of CMC1 as an immunometabolic checkpoint in T cell immunity
Chen, Y., Gao, J., Ma, M., Wang, K., Liu, F., Yang, F., Zou, X., Cheng, Z., & Wu, D. (2024) · OncoImmunology · doi:10.1080/2162402x.2024.2344905 · Cited by 13
Metabolic Dialogue Shapes Immune Response in the Tumor Microenvironment
Gao, F., Shah, R., Xin, G., & Wang, R. (2025) · European Journal of Immunology · doi:10.1002/eji.202451102 · Cited by 15
Role of Neutrophils in Homeostasis and Diseases
Chang, X., Liu, Y., Qiu, J., & Hua, K. (2025) · MedComm · doi:10.1002/mco2.70390 · Cited by 15
Bal, S. K., Giuliani, S., Block, J., Repiščák, P., Hafemeister, C., Shahin, T., Kasap, N., Ransmayr, B., Miao, Y., van de Wetering, C., et al. (2023) · Blood · doi:10.1182/blood.2022018303 · Cited by 17
Why and how citrate may sensitize malignant tumors to immunotherapy
Icard, P., Prieto, M., Coquerel, A., Fournel, L., Gligorov, J., Noel, J., Mouren, A., Dohan, A. J. J., Alifano, M., & Simula, L. (2024) · Drug Resistance Updates · doi:10.1016/j.drup.2024.101177 · Cited by 14
Reprogramming T-cell metabolism to enhance adoptive cell therapies
Kates, M., & Saibil, S. D. (2024) · International Immunology · doi:10.1093/intimm/dxae007 · Cited by 13
Lysine lactylation-based insight to understanding the characterization of cervical cancer
He, C., Zhang, J., Bai, X., Lu, C., & Zhang, K. (2024) · Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease · doi:10.1016/j.bbadis.2024.167356 · Cited by 13
Patterson, A. R., Needle, G. A., Sugiura, A., Jennings, E. Q., Chi, C., Steiner, K. K., Fisher, E. L., Robertson, G. L., Bodnya, C., Markle, J., et al. (2024) · Science Immunology · doi:10.1126/sciimmunol.adh0368 · Cited by 12
Self-citationRegulatory T cells in the context: deciphering the dynamic interplay with the tissue environment
Huang, X. J., & Rudensky, A. Y. (2024) · Current Opinion in Immunology · doi:10.1016/j.coi.2024.102453 · Cited by 11
Glucose metabolism in B cell malignancies: a focus on glycolysis branching pathways
Simon‐Molas, H., Prete, R. D., & Kabanova, A. (2023) · Molecular Oncology · doi:10.1002/1878-0261.13570 · Cited by 10
How lactate affects immune strategies in lymphoma
Zhou, Y., Lou, J., Yuqin, T., Ding, J., Wang, X., & Tang, B. (2024) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2024.1480884 · Cited by 11
Gorría, T., Sierra-Boada, M., Rojas, M., Figueras, C., Marín, S., Madurga, S., Cascante, M., & Maurel, J. (2025) · Cancers · doi:10.3390/cancers17030498 · Cited by 10
The Landscape of Cancer Metabolism as a Therapeutic Target
Ohshima, K. (2025) · Pathology International · doi:10.1111/pin.70034 · Cited by 11
Scaglione, M., Knight, M., Trihemasava, K., Rome, K., Archambault, A., Oh, J., Tanaka, E., Hall, E., Le, T. N. V., Lines, C. L., et al. (2026) · Immunity · doi:10.1016/j.immuni.2026.04.004 · Cited by 10
Madaj, Z., Dahabieh, M. S., Kamalumpundi, V., Muhire, B. M., Pettinga, D., Siwicki, R. A., Ellis, A. E., Isaguirre, C. N., Galvis, M. L. E., DeCamp, L. M., et al. (2023) · RNA Biology · doi:10.1080/15476286.2023.2204586 · Cited by 9
Self-citationChen, X. L., Tharp, K. M., Ojalill, M., Ozmadenci, D., Boyer, A. D., Haanen, T. J., Lawson, C., Lee, J., Xia, M., Tahon, E., et al. (2026) · Cell Reports · doi:10.1016/j.celrep.2026.117009 · Cited by 8
Tiberti, S., Gennari, S., Romeo, M. A., Sheraj, I., Kassir, M. F., Fernández-García, J., Lauson, C. B. N., Noberini, R., Catozzi, C., Dallavilla, T., et al. (2026) · Science Immunology · doi:10.1126/sciimmunol.aeb1459 · Cited by 8
Claiborne, M. D. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2022.1061411 · Cited by 9
Supercharging cancer-fighting T cells with lithium carbonate
Xu, Y., Ma, K., Zhang, L., & Li, G. (2024) · Cell Metabolism · doi:10.1016/j.cmet.2024.02.006 · Cited by 8
Approaches to investigate tissue-resident innate lymphocytes metabolism at the single-cell level
Corkish, C., de Aguiar, C. F., & Finlay, D. K. (2024) · Nature Communications · doi:10.1038/s41467-024-54516-3 · Cited by 8
Targeting organelle function in T cells for cancer immunotherapy
Baldwin, J., Heuser-Loy, C., & Gattinoni, L. (2025) · Nature reviews. Immunology · doi:10.1038/s41577-025-01223-9 · Cited by 8
Benavente, S. (2023) · Cancer Drug Resistance · doi:10.20517/cdr.2022.141 · Cited by 7
Population Structure and Genetic Diversity of Yunling Cattle Determined by Whole-Genome Resequencing
Chen, J., Zhang, L., Gao, L., Wei, Z., Dang, D., & Yang, L. (2023) · Genes · doi:10.3390/genes14122141 · Cited by 7
Mitochondrial protein OPA1 is required for the expansion of effector CD8 T cells
Willett, B. A. S., Thompson, S. B., Chen, V., Darehshouri, A., Jackson, C. L., Brunetti, T. M., D’Alessandro, A., Klarquist, J. S., Nemkov, T. G., & Kedl, R. M. (2025) · Cell Reports · doi:10.1016/j.celrep.2025.115610 · Cited by 9
Immunometabolism at the crossroads of obesity and cancer—a Keystone Symposia report
Cable, J., Rathmell, J. C., Pearce, E. L., Ho, P., Haigis, M. C., Mamedov, M. R., Wu, M., Kaech, S. M., Lynch, L., Febbraio, M. A., et al. (2023) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.14976 · Cited by 6
Self-citationSeeing the world through the eyes of cultured cells
Tan, J., Kunzmann, G. B., Virtue, S., Cantor, J. R., & Fazakerley, D. J. (2025) · Cell Metabolism · doi:10.1016/j.cmet.2025.01.027 · Cited by 6
Li, X., Du, G., Li, L., & Ke, P. (2023) · Frontiers in Oncology · doi:10.3389/fonc.2023.1253783 · Cited by 6
Metabolic Screening of T Lymphocytes During Activation via SEAHORSE Extracellular Flux (XF) Analysis
Gubert, G. F., Hochrein, S. M., Sinning, K., & Vaeth, M. (2025) · Methods in molecular biology · doi:10.1007/978-1-0716-4414-0_17 · Cited by 5
Min, F., Li, J., Wang, Z., Shao, H., Liu, W., Wang, J., Tong, P., Li, X., Wu, Y., & Chen, H. (2025) · Journal of Agricultural and Food Chemistry · doi:10.1021/acs.jafc.5c09540 · Cited by 5
Metabolic traits of T cells and the implications in autoimmune diseases
Zhou, Y., Zhou, Y., Zhu, Q., Guo, W., & Li, C. (2026) · Autoimmunity Reviews · doi:10.1016/j.autrev.2026.103989 · Cited by 6
Strategies for uncovering stable isotope tracing patterns between cell populations
MacPherson, S., Duncan, K. D., Goodlett, D. R., & Lum, J. J. (2023) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2023.102991 · Cited by 5
Blocking tumor-intrinsic MNK1 kinase restricts metabolic adaptation and diminishes liver metastasis
Preston, S. E. J., Dahabieh, M. S., González, R. E. F., Gonçalves, C., Richard, V. R., Leibovitch, M., Dakin, E., Papadopoulos, T., Naranjo, C. L., McCallum, P. A., et al. (2024) · Science Advances · doi:10.1126/sciadv.adi7673 · Cited by 6
Self-citationvan de Wall, S., Crooks, S. D., Varga, S. M., Badovinac, V. P., & Harty, J. T. (2023) · The Journal of Immunology · doi:10.4049/jimmunol.2200931 · Cited by 5
NRF2-dependent regulation of the prostacyclin receptor PTGIR drives CD8 T cell exhaustionPreprint
Dahabieh, M. S., DeCamp, L. M., Oswald, B. M., Kitchen-Goosen, S. M., Fu, Z. F., Vos, M., Compton, S. E., Longo, J., Williams, K. S., Ellis, A. E., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.06.23.600279 · Cited by 5
Self-citation
Metadata
- Authors
- Kaymak, I., Luda, K. M., Duimstra, L. R., Ma, E. H., Longo, J., Dahabieh, M. S., Faubert, B., Oswald, B. M., Watson, M. J., Kitchen-Goosen, S. M., DeCamp, L. M., Compton, S. E., Fu, Z., DeBerardinis, R. J., Williams, K. S., Sheldon, R. D., & Jones, R. G.
- Affiliations
- Van Andel Institute (US)
- University of Copenhagen (DK)
- University of Chicago (US)
- Children's Medical Center (US)
- Corresponding author
- Jones, Russell G.
- ORCID
- Venue
- Cell Metabolism
- Publisher
- Elsevier BV
- Published
- 2022-09
- Volume
- 34
- Issue
- 9
- Pages
- 1298-1311.e6
- ISSN
- 1550-4131 (ISSN-L)
- PMC
- PMC10068808
- OpenAlex
- W4292111508
- Cited by
- 160
- References
- 75
- Citations by year
- 2026: 40 · 2025: 43 · 2024: 41 · 2023: 31 · 2022: 5
- FWCI
- 11.46
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Cell Metabolism (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (publishedVersion, cc-by-nc-nd)
- PubMed Central (acceptedVersion, cc-by-nc-nd)
- Funders
- Van Andel Research Institute
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases
- National Cancer Institute Division of Cancer Prevention
- National Cancer Institute Division of Cancer Epidemiology and Genetics (R35CA22044901)
- The Paul G Allen Frontiers Group
- Howard Hughes Medical Institute
- Fonds de Recherche du Québec - Santé
- National Cancer Institute (T32CA251066-01A1)
- National Institute of Allergy and Infectious Diseases (R01AI165722)
- Topics
- Life Sciences › Immunology and Microbiology › Immunology › T-cell and B-cell Immunology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer, Hypoxia, and Metabolism
- Life Sciences › Immunology and Microbiology › Immunology › Immune cells in cancer
- Keywords
- CD8+ T cells, effector T cells, carbon source availability, nutrient utilization, T cell metabolism, glucose metabolism, T cell activation
- MeSH terms
- Nutrients, Carbon, Glucose, CD8-Positive T-Lymphocytes, Lactic Acid
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