Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Targeting lactylation reinforces NK cell cytotoxicity within the tumor microenvironment

Nature Immunology volume 26, pages 1099–1112 (2025)Cite this article

Subjects

Abstract

Dysfunction of natural killer (NK) cells can be associated with tumor-derived lactate in the tumor microenvironment. Lactate-induced lysine lactylation (Kla) is a posttranslational modification, and strategies aimed at augmenting NK cell resistance to Kla might enhance cytotoxicity. Here we show that increased Kla levels in NK cells are accompanied by impaired nicotinamide adenine dinucleotide metabolism, fragmented mitochondria and reduced cytotoxicity. Supplementation with nicotinamide riboside (a nicotinamide adenine dinucleotide precursor) and honokiol (a SIRT3 activator) enhanced NK cell cytotoxicity by reducing cellular Kla levels. This combination restores antileukemic activity of NK cells in vivo and ex vivo by modulating Kla on ROCK1, thereby inhibiting ROCK1–DRP1 signaling to prevent mitochondrial fragmentation. Altogether, this study shows how lactylation can compromise NK cells and highlights this lactylation as a target for NK cell-based immunotherapy to enhance resilience to lactate in the tumor microenvironment.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to the full article PDF.

USD 39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Kla levels are increased in NK cells from individuals with relapsed AML.
Fig. 2: NR partially reduces Kla levels and recovers NK cell antileukemic activity.
Fig. 3: NR and HKL reduce Kla and restore NK cell dysfunction.
Fig. 4: NR and HKL enhance NK cell antileukemic activity ex vivo.
Fig. 5: NR and HKL inhibit ROCK1–DRP1 signaling by reducing Kla on ROCK1.
Fig. 6: NR and HKL trigger NK cell-mediated graft-versus-leukemia effects.

Similar content being viewed by others

Data availability

This study made use of data from the HPA database, which can be accessed at https://www.proteinatlas.org/. All data supporting the findings of this study are included in the article and Supplementary Information. Source data are provided with this paper.

References

  1. Wolf, N. K., Kissiov, D. U. & Raulet, D. H. Roles of natural killer cells in immunity to cancer, and applications to immunotherapy. Nat. Rev. Immunol. 23, 90–105 (2023).

    CAS  PubMed  Google Scholar 

  2. Cózar, B. et al. Tumor-infiltrating natural killer cells. Cancer Discov. 11, 34–44 (2021).

    PubMed  Google Scholar 

  3. Terrén, I., Orrantia, A., Vitallé, J., Zenarruzabeitia, O. & Borrego, F. NK cell metabolism and tumor microenvironment. Front. Immunol. 10, 2278 (2019).

    PubMed  PubMed Central  Google Scholar 

  4. Brand, A. et al. LDHA-associated lactic acid production blunts tumor immunosurveillance by T and NK cells. Cell Metab. 24, 657–671 (2016).

    CAS  PubMed  Google Scholar 

  5. Husain, Z., Huang, Y. N., Seth, P. & Sukhatme, V. P. Tumor-derived lactate modifies antitumor immune response: effect on myeloid-derived suppressor cells and NK cells. J. Immunol. 191, 1486–1495 (2013).

    CAS  PubMed  Google Scholar 

  6. Harmon, C. et al. Lactate-mediated acidification of tumor microenvironment induces apoptosis of liver-resident NK cells in colorectal liver metastasis. Cancer Immunol. Res. 7, 335–346 (2019).

    CAS  PubMed  Google Scholar 

  7. Zheng, X. H. et al. Mitochondrial fragmentation limits NK cell-based tumor immunosurveillance. Nat. Immunol. 20, 1656 (2019).

    CAS  PubMed  Google Scholar 

  8. Zhang, D. et al. Metabolic regulation of gene expression by histone lactylation. Nature 574, 575–580 (2019).

    PubMed  PubMed Central  Google Scholar 

  9. Irizarry-Caro, R. A. et al. TLR signaling adapter BCAP regulates inflammatory to reparatory macrophage transition by promoting histone lactylation. Proc. Natl Acad. Sci. USA 117, 30628–30638 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  10. Xiong, J. et al. Lactylation-driven METTL3-mediated RNA m6A modification promotes immunosuppression of tumor-infiltrating myeloid cells. Mol. Cell 82, 1660–1677 (2022).

    Google Scholar 

  11. Gu, J. et al. Tumor metabolite lactate promotes tumorigenesis by modulating MOESIN lactylation and enhancing TGF-β signaling in regulatory T cells. Cell Rep. 40, 110986 (2022).

    Google Scholar 

  12. Fan, W. et al. Global lactylome reveals lactylation-dependent mechanisms underlying T17 differentiation in experimental autoimmune uveitis. Sci. Adv. 9, eadh4655 (2023).

    CAS  PubMed  PubMed Central  Google Scholar 

  13. Wang, Z. H. et al. Altered phenotypic and metabolic characteristics of FOXP3CD3CD56 natural killer T (NKT)-like cells in human malignant pleural effusion. Oncoimmunology 12, 2160558 (2023).

    PubMed  Google Scholar 

  14. Walenta, S. et al. High lactate levels predict likelihood of metastases, tumor recurrence, and restricted patient survival in human cervical cancers. Cancer Res. 60, 916–921 (2000).

    CAS  PubMed  Google Scholar 

  15. Soto, C. A., Lesch, M. L., Munger, J. C. & Frisch, B. J. Effects of elevated lactate in the bone marrow microenvironment during acute myeloid leukemia. Blood 140, 8620–8621 (2022).

    Google Scholar 

  16. Chen, Y. et al. Increased lactate in AML blasts upregulates TOX expression, leading to exhaustion of CD8 T cells. Am. J. Cancer Res. 11, 5726–5742 (2021).

    PubMed  PubMed Central  Google Scholar 

  17. Cantó, C., Menzies, K. J. & Auwerx, J. NAD Metabolism and the control of energy homeostasis: a balancing act between mitochondria and the nucleus. Cell Metab. 22, 31–53 (2015).

    PubMed  PubMed Central  Google Scholar 

  18. Stein, L. R. & Imai, S. The dynamic regulation of NAD metabolism in mitochondria. Trends Endocrinol. Metab. 23, 420–428 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  19. Zou, Y. J. et al. Illuminating NAD metabolism in live cells and using a genetically encoded fluorescent sensor. Dev. Cell 53, 240–252 (2020).

    Google Scholar 

  20. Rajman, L., Chwalek, K. & Sinclair, D. A. Therapeutic potential of NAD-boosting molecules: the evidence. Cell Metab. 27, 529–547 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  21. Trammell, S. A. J. et al. Nicotinamide riboside is uniquely and orally bioavailable in mice and humans. Nat. Commun. 7, 12948 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  22. Zhang, H. B. et al. NAD repletion improves mitochondrial and stem cell function and enhances life span in mice. Science 352, 1436–1443 (2016).

    CAS  PubMed  Google Scholar 

  23. Li, J. H. et al. MEF2C regulates NK cell effector functions through control of lipid metabolism. Nat. Immunol. 25, 928–928 (2024).

    CAS  PubMed  Google Scholar 

  24. Brown, K. D. et al. Activation of SIRT3 by the NAD precursor nicotinamide riboside protects from noise-induced hearing loss. Cell Metab. 20, 1059–1068 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  25. Cantó, C. et al. The NAD precursor nicotinamide riboside enhances oxidative metabolism and protects against high-fat diet-induced obesity. Cell Metab. 15, 838–847 (2012).

    PubMed  PubMed Central  Google Scholar 

  26. Jin, J. et al. SIRT3-dependent delactylation of cyclin E2 prevents hepatocellular carcinoma growth. EMBO Rep. 24, e56052 (2023).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. Uhlen, M. et al. Tissue-based map of the human proteome. Science 347, 1260419 (2015).

    PubMed  Google Scholar 

  28. Archer, S. L. Mitochondrial dynamics—mitochondrial fission and fusion in human diseases. N. Engl. J. Med. 369, 2236–2251 (2013).

    CAS  PubMed  Google Scholar 

  29. Brand, C. S., Tan, V. P., Brown, J. H. & Miyamoto, S. RhoA regulates Drp1 mediated mitochondrial fission through ROCK to protect cardiomyocytes. Cell Signal. 50, 48–57 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  30. Esposito, D. et al. ROCK1 mechano-signaling dependency of human malignancies driven by TEAD/YAP activation. Nat. Commun. 13, 703 (2022).

    CAS  PubMed  PubMed Central  Google Scholar 

  31. Li, Q. F. et al. Inhibition of ROCK ameliorates pulmonary fibrosis by suppressing M2 macrophage polarisation through phosphorylation of STAT3. Clin. Transl. Med. 12, e1036 (2022).

    CAS  PubMed  PubMed Central  Google Scholar 

  32. Li, X. L. et al. Lactate metabolism in human health and disease. Signal Transduct. Target. Ther. 7, 305 (2022).

    CAS  PubMed  PubMed Central  Google Scholar 

  33. Apostolova, P. & Pearce, E. L. Lactic acid and lactate: revisiting the physiological roles in the tumor microenvironment. Trends Immunol. 43, 969–977 (2022).

    CAS  PubMed  PubMed Central  Google Scholar 

  34. Bergers, G. & Fendt, S. M. The metabolism of cancer cells during metastasis. Nat. Rev. Cancer 21, 162–180 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  35. Moreno-Yruela, C. et al. Class I histone deacetylases (HDAC1-3) are histone lysine delactylases. Sci. Adv. 8, eabi6696 (2022).

    CAS  PubMed  PubMed Central  Google Scholar 

  36. Fan, W. et al. A feedback loop driven by H3K9 lactylation and HDAC2 in endothelial cells regulates VEGF-induced angiogenesis. Genome Biol. 25, 165 (2024).

    CAS  PubMed  PubMed Central  Google Scholar 

  37. Myers, J. A. & Miller, J. S. Exploring the NK cell platform for cancer immunotherapy. Nat. Rev. Clin. Oncol. 18, 85–100 (2021).

    PubMed  Google Scholar 

  38. Daher, M. et al. Targeting a cytokine checkpoint enhances the fitness of armored cord blood CAR-NK cells. Blood 137, 624–636 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  39. Laskowski, T. J., Biederstädt, A. & Rezvani, K. Natural killer cells in antitumour adoptive cell immunotherapy. Nat. Rev. Cancer 22, 557–575 (2022).

    CAS  PubMed  PubMed Central  Google Scholar 

  40. Vago, L. & Gojo, I. Immune escape and immunotherapy of acute myeloid leukemia. J. Clin. Invest. 130, 1552–1564 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  41. Bhansali, R. S., Pratz, K. W. & Lai, C. Recent advances in targeted therapies in acute myeloid leukemia. J. Hematol. Oncol. 16, 29 (2023).

    PubMed  PubMed Central  Google Scholar 

  42. Liu, H. T. Emerging agents and regimens for AML. J. Hematol. Oncol. 14, 49 (2021).

    PubMed  PubMed Central  Google Scholar 

  43. Hansrivijit, P., Gale, R. P., Barrett, J. & Ciurea, S. O. Cellular therapy for acute myeloid leukemia—current status and future prospects. Blood Rev. 37, 100578 (2019).

    CAS  PubMed  Google Scholar 

  44. Christopher, M. J. et al. Immune escape of relapsed AML cells after allogeneic transplantation. N. Engl. J. Med. 379, 2330–2341 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  45. Zeiser, R. & Vago, L. Mechanisms of immune escape after allogeneic hematopoietic cell transplantation. Blood 133, 1290–1297 (2019).

    CAS  PubMed  Google Scholar 

  46. Toffalori, C. et al. Immune signature drives leukemia escape and relapse after hematopoietic cell transplantation. Nat. Med. 25, 603–611 (2019).

    PubMed  Google Scholar 

  47. Cooley, S., Parham, P. & Miller, J. S. Strategies to activate NK cells to prevent relapse and induce remission following hematopoietic stem cell transplantation. Blood 131, 1053–1062 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  48. Merindol, N., Charrier, E., Duval, M. & Soudeyns, H. Complementary and contrasting roles of NK cells and T cells in pediatric umbilical cord blood transplantation. J. Leukoc. Biol. 90, 49–60 (2011).

    CAS  PubMed  Google Scholar 

  49. Locatelli, F. et al. Hematopoietic and immune recovery after transplantation of cord blood progenitor cells in children. Bone Marrow Transplant. 18, 1095–1101 (1996).

    CAS  PubMed  Google Scholar 

  50. Xu, J. & Niu, T. Natural killer cell-based immunotherapy for acute myeloid leukemia. J. Hematol. Oncol. 13, 167 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  51. Wang, D. Y. et al. GARP-mediated active TGF-β1 induces bone marrow NK cell dysfunction in AML patients with early relapse post-allo-HSCT. Blood 140, 2788–2804 (2022).

    CAS  PubMed  PubMed Central  Google Scholar 

  52. Liu, Y. J. et al. Inhibition of p300 impairs Foxp3 T regulatory cell function and promotes antitumor immunity. Nat. Med. 19, 1173–1177 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  53. Capello, M. et al. Targeting the Warburg effect in cancer cells through ENO1 knockdown rescues oxidative phosphorylation and induces growth arrest. Oncotarget 7, 5598–5612 (2016).

    PubMed  Google Scholar 

  54. Li, X. J. et al. Mitochondria-translocated PGK1 functions as a protein kinase to coordinate glycolysis and the TCA cycle in tumorigenesis. Mol. Cell 61, 705–719 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  55. Wu, Z. Q. et al. SENP7 senses oxidative stress to sustain metabolic fitness and antitumor functions of CD8 T cells. J. Clin. Invest. 132, e155224 (2022).

    CAS  PubMed  PubMed Central  Google Scholar 

  56. Aydin, E., Johansson, J., Nazir, F. H., Hellstrand, K. & Martner, A. Role of NOX2-derived reactive oxygen species in NK cell-mediated control of murine melanoma metastasis. Cancer Immunol. Res. 5, 804–811 (2017).

    CAS  PubMed  Google Scholar 

Download references

Acknowledgements

This project was supported by Strategic Priority Research Program of the Chinese Academy of Sciences (XDB0940202 to Y.W.); The National Natural Science Foundation of China (22277115, 31770886, 31972933 and 82370217 to Y.W., C.D. and D.W.); National Key R&D Program of China (2017YFA0505102 to C.D.); The Anhui Natural Science Foundation (2408085MH193 and 2308085Y46 to J.J. and D.W.). We express our gratitude to Y. Yang and Y. Zhao from East China University of Science and Technology for generously providing the template plasmid for the NAD+ probe.

Author information

Author notes

  1. These authors contributed equally: Jing Jin, Peidong Yan, Dongyao Wang, Lin Bai.

Authors and Affiliations

  1. National Key Laboratory of Immune Response and Immunotherapy; Department of Hepatobiliary Surgery, The First Affiliated Hospital of USTC, School of Basic Medical Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China

    Jing Jin, Peidong Yan, Hao Liang, Haiming Wei & Yi Wang

  2. Department of Hematology, the First Affiliated Hospital of USTC; Blood and Cell Therapy Institute, Anhui Provincial Key Laboratory of Blood Research and Applications, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China

    Dongyao Wang, Xiaoyu Zhu & Huaiping Zhu

  3. State Key Laboratory of Genetic Engineering, Institutes of Biomedical Sciences, Human Phenome Institute, School of Life Sciences, Zhongshan Hospital, Fudan University, Shanghai, China

    Lin Bai & Chen Ding

  4. Precision Research Center for Refractory Diseases, Shanghai Jiao Tong University Pioneer Research Institute for Molecular and Cell Therapies, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

    Lin Bai

  5. State Key Laboratory of Innovative Immunotherapy, School of Pharmaceutical Sciences, Shanghai Jiao Tong University, Shanghai, China

    Lin Bai

Authors
  1. Jing Jin
    View author publications

    Search author on:PubMed Google Scholar

  2. Peidong Yan
    View author publications

    Search author on:PubMed Google Scholar

  3. Dongyao Wang
    View author publications

    Search author on:PubMed Google Scholar

  4. Lin Bai
    View author publications

    Search author on:PubMed Google Scholar

  5. Hao Liang
    View author publications

    Search author on:PubMed Google Scholar

  6. Xiaoyu Zhu
    View author publications

    Search author on:PubMed Google Scholar

  7. Huaiping Zhu
    View author publications

    Search author on:PubMed Google Scholar

  8. Chen Ding
    View author publications

    Search author on:PubMed Google Scholar

  9. Haiming Wei
    View author publications

    Search author on:PubMed Google Scholar

  10. Yi Wang
    View author publications

    Search author on:PubMed Google Scholar

Contributions

Y.W. and J.J. conceived and conducted the project. Y.W., H.W., C.D and D.W. supervised the project. Y.W. and J.J. wrote the paper. J.J., P.Y., D.W., L.B. and H.L. performed the experiments and data analysis. X.Z. and H.Z. provided human samples.

Corresponding authors

Correspondence to Dongyao Wang, Chen Ding, Haiming Wei or Yi Wang.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Immunology thanks the anonymous reviewers for their contribution to the peer review of this work. Primary Handling Editor: Nick Bernard, in collaboration with the Nature Immunology team.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Measurement of lactate and validation of NAD+ sensor in NK cells.

(a) Lactate concentrations in the bone marrow fluid were measured in 2 groups of AML patients: those without relapse (n = 21) and those with relapse (n = 18). (b) DNA gel electrophoresis showed the cpYFP or FiNAD PCR amplified bands. The image is representative of three independent experiments. (c) Representative immunofluorescence images (left) and quantification (right) of mCherry-cpYFP or mCherry-FiNad levels in BMNK cells from AML patients with relapse (n = 5). Each dot represents a single field. Scale bars, 50 μm. (d) Representative immunofluorescence images (left) and quantification (right) of mCherry-cpYFP levels in BMNK cells from AML patients (n = 8) without or with relapse. Each dot represents a single field. Scale bars, 50 μm. (e) Gating strategy of NK cells for flow cytometry. For all experiments, FSC-A vs. SSC-A gates of the starting cell population were used to identify viable cells. Singlet cells were identified using FSC-A vs. FSC-H gating. Then, target cell population for further analysis were gated by cell surface marker. NK cells were gated by Dead-CD45+CD56+CD3-. (f) Immunoblot analysis (left) and quantification (right, n = 3) of the Kla level in total cell lysates isolated from naive healthy human NK cells subjected to the following treatments for 24 h: dichloroacetate (DCA, 20 mM), rotenone (20 nM), or Ep300 inhibitors (SGC-CBP30, 10 µM; C646, 10 µM), respectively. The image is representative of three independent experiments (β-actin as loading control). (g) Flow cytometry analysis (left) and quantification (right, n = 4) of the percentage of Annexin V+ K562 cells (target cells) co-cultured for 4 h with naive healthy human NK cells under the indicated treatments. Data in a, c and d were analyzed by two-tailed unpaired Student’s t-test; data in f and g were analyzed by one-way ANOVA with Tukey’s multiple comparisons test; means ± SD.

Source data

Extended Data Fig. 2 NR enhances the anti-leukemic activity of BMNK cells.

(a) Representative immunofluorescence images (left) and quantification (right) of mCherry-cpYFP levels in BMNK cells (n = 8 patients) without or with NR treatment (1 mM). Each dot represents a single field. Scale bars, 50 μm. (b-d) Flow cytometry analysis of the percentage of Annexin V+ HL60 cells (target cells) co-cultured for 4 h with control BMNK cells or NR-treated BMNK cells (b and d). Flow cytometry analysis of NKG2D (left, c), CD38 (middle, c) and CD160 (right, c) expression on control BMNK cells or NR-treated BMNK cells (c and d). n = 10 patients. (e-f) Flow cytometry analysis of the proportion of CD107a+ NK (e) and Granzyme B+ NK cells (f) within the total population of control BMNK cells or NR-treated BMNK cells that were co-cultured with HL60 cells for 4 h. n = 10 patients. (g-i) Flow cytometry analysis of the percentage of Annexin V+ MOLM-13 cells (target cells) co-cultured for 4 h with control BMNK cells or NR-treated BMNK cells (g and i). Flow cytometry analysis showing NKG2D (left, h), CD38 (middle, h) and CD160 (right, h) expression on control BMNK cells or NR-treated BMNK cells (h and i). n = 10 patients. (j-k) Flow cytometry analysis of the proportion of CD107a+ NK (j) and Granzyme B+ NK cells (k) within the total population of control BMNK cells or NR-treated BMNK cells that were co-cultured with MOLM-13 cells for 4 h. n = 7 patients. Data in a were analyzed by two-tailed unpaired Student’s t-test; data in d-f, i-k were analyzed by two-tailed paired Student’s t-test; means ± SD.

Source data

Extended Data Fig. 3 NR increases NAD+ levels in NaLa-treated PBMC-derived NK cells.

(a) TEM showed mitochondrial morphology of activated healthy donor (HD) NK cells stimulated with NaLa (25 mM), or co-stimulated with NR (1 mM), or co-stimulated with HKL (100 μM), or co-stimulated with NR plus HKL for 24 h. The bottom-row images are magnified views of the areas in red dashed boxes above. Scale bars, 1 μm. The image is representative of three independent experiments. (b) Length of each mitochondrion (left) in each group (Each dot = 1 mitochondrion). Quantification (middle) and frequency (right) of fractured mitochondria in a single field of each group (Each dot = a single field). n = 8 donors. (c) Representative immunofluorescence images (left) and quantification (right) of mCherry-FiNad levels in naive healthy human NK cells with NaLa alone or co-stimulated with NR. Each dot represents a single field. Scale bars, 50 μm. n = 5 donors. (d) Representative immunofluorescence images (left) and quantification (right) of mCherry-FiNad levels in activated healthy human NK cells with NaLa alone or co-stimulated with NR. Each dot represents a single field. Scale bars, 50 μm. n = 5 donors. (e) Flow cytometry analysis of the percentage of Annexin V+ primary AML blasts (target cells) co-cultured for 4 h with activated healthy human NK cells subjected to various treatments (1st row); proportion of CD107a+ NK cells (2nd row), IFN-γ+ NK cells (3rd row) and Granzyme B+ NK cells (4th row) within the total population of activated healthy human NK cells with various treatments and were co-cultured with primary AML blasts. n = 8 donors. (f) Flow cytometry analysis of NKG2D, CD160 and CD38 expression on activated healthy human NK cells with indicated conditions. n = 8 donors. The data in b-f were analyzed by one-way ANOVA with Tukey’s multiple comparisons test; means ± SD.

Source data

Extended Data Fig. 4 NR and HKL restore mitochondrial dysfunction in NK cells.

(a) OCRs of naive healthy human NK cells that stimulated with NaLa alone (25 mM), or co-stimulated with NR (1 mM), or co-stimulated HKL (100 μM), or co-stimulated with NR plus HKL were measured under basal condition and in response to oligomycin, the mitochondrial decoupler FCCP, and Rotenone + Antimycin A (left). OCR values were estimated for basal respiration (middle) and maximal respiration rates (right). n = 5. (b) OCRs of activated healthy human NK cells that stimulated with NaLa alone (25 mM), or co-stimulated with NR (1 mM), or co-stimulated HKL (100 μM), or co-stimulated with NR plus HKL were measured under basal and in-response conditions (oligomycin, FCCP, and Rotenone + Antimycin A; left). OCR values of basal (middle) and maximal respiration rates (right). n = 5. (c) Flow cytometry analysis (left) and quantification (right, n = 8) of the proportion of TMRM+ (upper) and MitoTracker Green+ (bottom) naive healthy human NK cells subjected to the above treatment conditions. (d) Flow cytometry analysis (left) and quantification (right, n = 8) of the proportion of TMRM+ (upper) and MitoTracker Green+ (bottom) activated healthy human NK cells subjected to the above treatments. Data in a-d were analyzed by one-way ANOVA with Tukey’s multiple comparisons test; means ± SD.

Source data

Extended Data Fig. 5 NR and HKL restore the effector function of PBMC-derived NK cells.

(a-b) Flow cytometry analysis of the percentage of Annexin V+ K562 cells (target cells) co-cultured for 4 h with naive or activated healthy human NK cells subjected to various treatments; the proportion of CD107a+ NK cells, IFN-γ+ NK cells and Granzyme B+ NK cells within the total population of these NK cells; the expression of NKG2D, CD160 and CD38 on these NK cell. n = 8. (c-d) Flow cytometry analysis of the percentage of Annexin V+ HL60 cells (target cells) co-cultured for 4 h with naive or activated healthy human NK cells subjected to various treatments; the proportion of CD107a+ NK cells, IFN-γ+ NK cells and Granzyme B+ NK cells within the total population of these NK cells; the expression of NKG2D, CD160 and CD38 on these NK cell. n = 8. (e-f) Flow cytometry analysis of the percentage of Annexin V+ MOLM-13 cells (target cells) co-cultured for 4 h with naive or activated healthy human NK cells subjected to various treatments; the proportion of CD107a+ NK cells, IFN-γ+ NK cells and Granzyme B+ NK cells within the total population of these NK cells; the expression of NKG2D, CD160 and CD38 on these NK cell. n = 8. Data in a-f were analyzed by one-way ANOVA with Tukey’s multiple comparisons test; means ± SD.

Source data

Extended Data Fig. 6 NR and HKL restore NaLa-induced NK cell dysfunction in vivo.

(a) Experimental scheme: NCG mice were injected with 5×105 HL60 cells (target cells) stably expressing luciferase into the tail vein. After confirmation of engraftment by bioluminescence imaging on day 7, 2.5×106 healthy human PBMC-derived NK cells were transferred to all the mice via tail vein. NK cells: target cells ratio = 5:1. NK cells were treated with vehicle control, or NaLa (25 mM), or NaLa in combination with NR (1 mM), or NaLa in combination with NR and HKL (100 μM). n = 7 mice per group. AML burden was monitored by bioluminescence imaging at the indicated time points. (b) Bioluminescence imaging of AML burden. (c) AML burden was quantified as the average value of the total flux (p/s). n = 7 mice per group. (d) Kaplan-Meier survival curve of mice bearing HL60 cell-derived tumors. Statistical significance was determined by log-rank Mantel-Cox test. n = 7 mice per group. Data in c were analyzed by one-way ANOVA with Tukey’s multiple comparisons test; means ± SD.

Source data

Extended Data Fig. 7 NR and HKL augment the anti-leukemic function of BMNK cells.

(a) Flow cytometry (FCM) analysis of percentage of Annexin V+ K562 cells co-cultured with control, NR-treated or in combination with HKL-treated BMNK cells. n = 12. (b-c) FCM analysis of proportion of Granzyme B+ (n = 11, b), CD107a+ and IFN-γ+ NK cells (n = 8, c) within total population of control, NR-treated or in combination with HKL-treated BMNK cells that co-cultured with K562 cells. (d) FCM analysis of NKG2D (left), CD38 (middle) and CD160 (right) expression on control, NR-treated or in combination with HKL-treated BMNK cells that co-cultured with K562 cells. n = 11. (e) FCM analysis of percentage of Annexin V+ MOLM-13 cells co-cultured with control, NR-treated or in combination with HKL-treated BMNK cells. n = 10. (f-g) FCM analysis of proportion of Granzyme B+ (f), CD107a+ and IFN-γ+ NK cells (g) within total population of control, NR-treated or in combination with HKL-treated BMNK cells that co-cultured with MOLM-13 cells. n = 8. (h) FCM analysis of NKG2D (left), CD38 (middle) and CD160 (right) expression on control, NR-treated or in combination with HKL-treated BMNK cells that co-cultured with MOLM-13 cells. n = 10. (i) FCM analysis of percentage of Annexin V+ HL60 cells co-cultured with control, NR-treated or in combination with HKL-treated BMNK cells. n = 8. (j-k) FCM analysis of proportion of Granzyme B+ (j), CD107a+ and IFN-γ+ NK cells (k) within total population of control, NR-treated or in combination with HKL-treated BMNK cells that co-cultured with HL60 cells. n = 8. (l) FCM analysis of NKG2D (left), CD38 (middle) and CD160 (right) expression on control, NR-treated or in combination with HKL-treated BMNK cells that co-cultured with HL60 cells. n = 10. Data in a-l were analyzed by one-way ANOVA with Tukey’s multiple comparisons test; means ± SD.

Source data

Extended Data Fig. 8 NR and HKL or an ROCK1 inhibitor enhance NK cell cytotoxicity.

(a-b) Flow cytometry analysis of the percentage of Annexin V+ MOLM-13 cells (a) or Annexin V+ HL60 cells (b) after co-culturing for 4 h with naive healthy human NK cells stimulated with NaLa alone (25 mM), co-stimulated with NR (1 mM) plus HKL (100 μM), or co-stimulated with ROCK1 inhibitor (GSK429286A, 10 μM). n = 8. (c-d) Flow cytometry analysis of the percentage of Annexin V+ MOLM-13 cells (c) or Annexin V+ HL60 cells (d) following co-culture for 4 h with activated healthy human NK cells stimulated with NaLa alone (25 mM), co-stimulated with NR (1 mM) plus HKL (100 μM), or co-stimulated with ROCK1 inhibitor (GSK429286A, 10 μM). n = 8. (e-f) Flow cytometry analysis of the percentage of Annexin V+ MOLM-13 cells (e) or Annexin V+ HL60 cells (f) following co-culture for 4 h with BMNK cells from the relapsed AML patients (n = 9) treated with NR (1 mM) plus HKL (100 μM), or treated with ROCK1 inhibitor (GSK429286A, 10 μM). Data in a-f were analyzed by one-way ANOVA with Tukey’s multiple comparisons test; means ± SD.

Source data

Extended Data Fig. 9 The investigation of potential targets in modulating Kla in NK cells.

(a) Immunoblot of Kla and SIRT3 in total cell lysates isolated from BMNK cells of AML patients (n = 4) without or with relapse. GAPDH served as loading control. (b) Immunoblot of Kla in total cell lysates isolated from naive healthy human NK cells overexpressing HDAC1-3 or SIRT1-2. β-actin served as loading control. (c) Immunoblot of Kla on ENO1 or PGK1 in total cell lysates isolated from naive healthy human NK cells without or with Sirt3 shRNA transduction in the presence of NR (1 mM). β-actin served as loading control. (d) Flow cytometry analysis of ROS levels in naive healthy human NK cells subjected to the indicated treatments. n = 5. (e) Flow cytometry analysis of percentage of Annexin V+ K562 cells (target cells) co-cultured for 4 h with naive healthy human NK cells subjected to the indicated treatments. n = 5. Data in a-c are representative of three independent experiments. Data in d-e were analyzed by one-way ANOVA with Tukey’s multiple comparisons test; means ± SD.

Source data

Supplementary information

Source data

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jin, J., Yan, P., Wang, D. et al. Targeting lactylation reinforces NK cell cytotoxicity within the tumor microenvironment. Nat Immunol 26, 1099–1112 (2025). https://doi.org/10.1038/s41590-025-02178-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Version of record:

  • Issue date:

  • DOI: https://doi.org/10.1038/s41590-025-02178-8

This article is cited by

Search

Advanced search

Quick links

Nature Briefing: Cancer

Sign up for the Nature Briefing: Cancer newsletter — what matters in cancer research, free to your inbox weekly.

Get what matters in cancer research, free to your inbox weekly. Sign up for Nature Briefing: Cancer