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ETV7 limits the antiviral and antitumor efficacy of CD8+ T cells by diverting their fate toward exhaustion

Nature Cancer volume 6, pages 338–356 (2025)Cite this article

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Abstract

Terminal exhaustion is a critical barrier to antitumor immunity. By integrating and analyzing single-cell RNA-sequencing and single-cell assay for transposase-accessible chromatin with sequencing data, we found that ETS variant 7 (ETV7) is indispensable for determining CD8+ T cell fate in tumors. ETV7 introduction drives T cell differentiation from memory to terminal exhaustion, limiting antiviral and antitumor efficacy in male mice. Mechanistically, ETV7 acts as a central transcriptional node by binding to specific memory genes and exhaustion genes and functionally skewing these transcriptional programs toward exhaustion. Clinically, ETV7 expression is negatively correlated with progression and responsiveness to immune checkpoint blockade in various human cancers. ETV7 depletion strongly enhances the antitumor efficacy of CD8+ T cells and engineered chimeric antigen receptor T cells in solid tumors. Thus, these findings demonstrate a decisive role for ETV7 in driving CD8+ T cell terminal exhaustion and reveal that ETV7 may be a promising target and biomarker for improving the efficacy of cancer immunotherapy.

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Fig. 1: Integration of single-cell analysis and in vitro screening identifies ETV7 as a key TF that diverts differentiation of tumor-infiltrating CD8+ T cells from memory to exhausted states.
Fig. 2: ETV7 expression is increased during differentiation of CD8+ T cells from memory to exhaustion in individuals with various cancers.
Fig. 3: ETV7 diverts CD8+ T cell differentiation from memory to exhaustion.
Fig. 4: ETV7 controls CD8+ T cell fate.
Fig. 5: ETV7 suppresses antitumor function of CD8+ T cells.
Fig. 6: ETV7 increases exhaustion of tumor-infiltrating CD8+ T cells in mice and individuals with ESCA.
Fig. 7: ETV7 acts as a transcriptional node, controlling memory and exhaustion gene expression in CD8+ T cells.
Fig. 8: ETV7 depletion blocks CAR T cell exhaustion and improves CAR T cell antitumor therapies.

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Data availability

All data supporting the findings of this study are available within the article and its Supplementary Information files and from the corresponding authors upon reasonable request. The FACS gating strategies are described in Supplementary Fig. 1. This paper does not report any original code. All scRNA-seq and scATAC-seq data used in this study were obtained from previously published data and were reanalyzed here. We have permission to use all data. No new data were generated in this study. The processed Seurat object of pan-cancer CD8+ T cells was downloaded from Gene Expression Omnibus (GEO) under accession code GSE156728. Processed scATAC-seq fragment files were downloaded from GEO via accession codes GSE181062 and GSE129785. ESCA scRNA-seq data were downloaded using GEO accession code GSE160269. scRNA-seq data of anti-CD19 CAR T cells were downloaded from GEO accession code GSE151511. scRNA-seq data of anti-PD1-treated melanoma immune cells were downloaded from GEO accession code GSE120575. Bulk RNA-seq data for the TCGA ESCA/UCEC/PACA cohort were obtained through the Broad GDAC Firehose (https://gdac.broadinstitute.org/). scRNA-seq data of T cells from individuals infected with SARS-CoV-2 were downloaded from GEO accession code GSE158055. scRNA-seq data of T cells from individuals infected with HBV were downloaded from GEO accession code GSE182159. Images in Figs. 1a,f, 3d, 4e, 5a and 6a and Extended Data Figs. 4a,e and 10i) were generated using BioRender.com under Academic License Terms with agreement numbers KH27FESCLA, KJ27FETVUI and AL27L9XLPG. Further information on research design is available in the Nature Research Reporting Summary linked to this article. Source data are provided with this paper.

Code availability

No software or algorithm was generated in this study. The code for reproducing major figures is available on GitHub (https://github.com/Ting-PKU/ETV7_project).

References

  1. Zhang, N. & Bevan, M. J. CD8+ T cells: foot soldiers of the immune system. Immunity 35, 161–168 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Chang, J. T., Wherry, E. J. & Goldrath, A. W. Molecular regulation of effector and memory T cell differentiation. Nat. Immunol. 15, 1104–1115 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Hellstrom, I., Hellstrom, K. E., Pierce, G. E. & Yang, J. P. Cellular and humoral immunity to different types of human neoplasms. Nature 220, 1352–1354 (1968).

    Article  CAS  PubMed  Google Scholar 

  4. Hellstrom, K. E. & Hellstrom, I. From the Hellstrom paradox toward cancer cure. Prog. Mol. Biol. Transl. Sci. 164, 1–24 (2019).

    Article  CAS  PubMed  Google Scholar 

  5. McLane, L. M., Abdel-Hakeem, M. S. & Wherry, E. J. CD8 T cell exhaustion during chronic viral infection and cancer. Annu. Rev. Immunol. 37, 457–495 (2019).

    Article  CAS  PubMed  Google Scholar 

  6. Philip, M. & Schietinger, A. CD8+ T cell differentiation and dysfunction in cancer. Nat. Rev. Immunol. 22, 209–223 (2022).

    Article  CAS  PubMed  Google Scholar 

  7. Schietinger, A. et al. Tumor-specific T cell dysfunction is a dynamic antigen-driven differentiation program initiated early during tumorigenesis. Immunity 45, 389–401 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Anderson, K. G., Stromnes, I. M. & Greenberg, P. D. Obstacles posed by the tumor microenvironment to T cell activity: a case for synergistic therapies. Cancer Cell 31, 311–325 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Thommen, D. S. & Schumacher, T. N. T cell dysfunction in cancer. Cancer Cell 33, 547–562 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Sade-Feldman, M. et al. Defining T cell states associated with response to checkpoint immunotherapy in melanoma. Cell 175, 998–1013 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Im, S. J. et al. Defining CD8+ T cells that provide the proliferative burst after PD-1 therapy. Nature 537, 417–421 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Siddiqui, I. et al. Intratumoral TCF1+PD-1+CD8+ T cells with stem-like properties promote tumor control in response to vaccination and checkpoint blockade immunotherapy. Immunity 50, 195–211 (2019).

    Article  CAS  PubMed  Google Scholar 

  13. Krishna, S. et al. Stem-like CD8 T cells mediate response of adoptive cell immunotherapy against human cancer. Science 370, 1328–1334 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Kraehenbuehl, L., Weng, C. H., Eghbali, S., Wolchok, J. D. & Merghoub, T. Enhancing immunotherapy in cancer by targeting emerging immunomodulatory pathways. Nat. Rev. Clin. Oncol. 19, 37–50 (2022).

    Article  CAS  PubMed  Google Scholar 

  15. Chow, A., Perica, K., Klebanoff, C. A. & Wolchok, J. D. Clinical implications of T cell exhaustion for cancer immunotherapy. Nat. Rev. Clin. Oncol. 19, 775–790 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  16. Hou, A. J., Chen, L. C. & Chen, Y. Y. Navigating CAR-T cells through the solid-tumour microenvironment. Nat. Rev. Drug Discov. 20, 531–550 (2021).

    Article  CAS  PubMed  Google Scholar 

  17. D’Aloia, M. M., Zizzari, I. G., Sacchetti, B., Pierelli, L. & Alimandi, M. CAR-T cells: the long and winding road to solid tumors. Cell Death Dis. 9, 282 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  18. Newick, K., O’Brien, S., Moon, E. & Albelda, S. M. CAR T cell therapy for solid tumors. Annu. Rev. Med. 68, 139–152 (2017).

    Article  CAS  PubMed  Google Scholar 

  19. Zheng, L. et al. Pan-cancer single-cell landscape of tumor-infiltrating T cells. Science 374, abe6474 (2021).

    Article  PubMed  Google Scholar 

  20. Kourtis, N. et al. A single-cell map of dynamic chromatin landscapes of immune cells in renal cell carcinoma. Nat. Cancer 3, 885–898 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Satpathy, A. T. et al. Massively parallel single-cell chromatin landscapes of human immune cell development and intratumoral T cell exhaustion. Nat. Biotechnol. 37, 925–936 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Vardhana, S. A. et al. Impaired mitochondrial oxidative phosphorylation limits the self-renewal of T cells exposed to persistent antigen. Nat. Immunol. 21, 1022–1033 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Balkhi, M. Y., Wittmann, G., Xiong, F. & Junghans, R. P. YY1 upregulates checkpoint receptors and downregulates type I cytokines in exhausted, chronically stimulated human T cells. iScience 2, 105–122 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Blank, C. U. et al. Defining T cell exhaustion. Nat. Rev. Immunol. 19, 665–674 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Chen, Y. et al. BATF regulates progenitor to cytolytic effector CD8+ T cell transition during chronic viral infection. Nat. Immunol. 22, 996–1007 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Romero, F., Martinez, A. C., Camonis, J. & Rebollo, A. Aiolos transcription factor controls cell death in T cells by regulating Bcl-2 expression and its cellular localization. EMBO J. 18, 3419–3430 (1999).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Philip, M. et al. Chromatin states define tumour-specific T cell dysfunction and reprogramming. Nature 545, 452–456 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Minutti, C. M. et al. Surfactant protein a prevents IFN-γ/IFN-γ receptor interaction and attenuates classical activation of human alveolar macrophages. J Immunol 197, 590–598 (2016).

    Article  CAS  PubMed  Google Scholar 

  29. Matz, M. et al. The regulation of interferon type I pathway-related genes RSAD2 and ETV7 specifically indicates antibody-mediated rejection after kidney transplantation. Clin. Transplant 32, e13429 (2018).

    Article  PubMed  Google Scholar 

  30. Wang, Y. et al. Timing and magnitude of type I interferon responses by distinct sensors impact CD8 T cell exhaustion and chronic viral infection. Cell Host Microbe 11, 631–642 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Snell, L. M., McGaha, T. L. & Brooks, D. G. Type I interferon in chronic virus infection and cancer. Trends Immunol. 38, 542–557 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Degnan, B. M., Degnan, S. M., Naganuma, T. & Morse, D. E. The ETS multigene family is conserved throughout the Metazoa. Nucleic Acids Res. 21, 3479–3484 (1993).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Scott, A. C. et al. TOX is a critical regulator of tumour-specific T cell differentiation. Nature 571, 270–274 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Pircher, H. et al. Viral escape by selection of cytotoxic T cell-resistant virus variants in vivo. Nature 346, 629–633 (1990).

    Article  CAS  PubMed  Google Scholar 

  35. Wherry, E. J. & Ahmed, R. Memory CD8 T-cell differentiation during viral infection. J. Virol. 78, 5535–5545 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Bergthaler, A. et al. Viral replicative capacity is the primary determinant of lymphocytic choriomeningitis virus persistence and immunosuppression. Proc. Natl Acad. Sci. USA 107, 21641–21646 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Salina, A. C. G. et al. Efferocytosis of SARS-CoV-2-infected dying cells impairs macrophage anti-inflammatory functions and clearance of apoptotic cells. eLife 11, e74443 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Zhang, C. et al. Single-cell RNA sequencing reveals intrahepatic and peripheral immune characteristics related to disease phases in HBV-infected patients. Gut 72, 153–167 (2023).

    Article  CAS  PubMed  Google Scholar 

  39. Asselah, T. & Rizzetto, M. Hepatitis D virus infection. N. Engl. J. Med. 389, 1444 (2023).

    Article  Google Scholar 

  40. Liang, T. J. Hepatitis B: the virus and disease. Hepatology 49, S13–S21 (2009).

    Article  CAS  PubMed  Google Scholar 

  41. Bujanover, N. et al. Identification of immune-activated hematopoietic stem cells. Leukemia 32, 2016–2020 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  42. Zhang, X. et al. Dissecting esophageal squamous-cell carcinoma ecosystem by single-cell transcriptomic analysis. Nat. Commun. 12, 5291 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Gao, J. et al. Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal. Sci. Signal. 6, pl1 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  44. Cerami, E. et al. The cBio Cancer Genomics Portal: an open platform for exploring multidimensional cancer genomics data. Cancer Discov. 2, 401–404 (2012).

    Article  PubMed  Google Scholar 

  45. Potter, M. D., Buijs, A., Kreider, B., van Rompaey, L. & Grosveld, G. C. Identification and characterization of a new human ETS-family transcription factor, TEL2, that is expressed in hematopoietic tissues and can associate with TEL1/ETV6. Blood 95, 3341–3348 (2000).

    Article  CAS  PubMed  Google Scholar 

  46. Wei, G. H. et al. Genome-wide analysis of ETS-family DNA-binding in vitro and in vivo. EMBO J. 29, 2147–2160 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Deng, Q. et al. Characteristics of anti-CD19 CAR T cell infusion products associated with efficacy and toxicity in patients with large B cell lymphomas. Nat. Med. 26, 1878–1887 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Liu, X. et al. Highly active CAR T cells that bind to a juxtamembrane region of mesothelin and are not blocked by shed mesothelin. Proc. Natl Acad. Sci. USA 119, e2202439119 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Kim, M., Kim, T., Johnson, R. L. & Lim, D. S. Transcriptional co-repressor function of the hippo pathway transducers YAP and TAZ. Cell Rep. 11, 270–282 (2015).

    Article  CAS  PubMed  Google Scholar 

  50. Laidlaw, B. J., Craft, J. E. & Kaech, S. M. The multifaceted role of CD4+ T cells in CD8+ T cell memory. Nat. Rev. Immunol. 16, 102–111 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Marzo, A. L. et al. Fully functional memory CD8 T cells in the absence of CD4 T cells. J. Immunol. 173, 969–975 (2004).

    Article  CAS  PubMed  Google Scholar 

  52. Sun, J. C., Williams, M. A. & Bevan, M. J. CD4+ T cells are required for the maintenance, not programming, of memory CD8+ T cells after acute infection. Nat. Immunol. 5, 927–933 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Antony, P. A. et al. CD8+ T cell immunity against a tumor/self-antigen is augmented by CD4+ T helper cells and hindered by naturally occurring T regulatory cells. J. Immunol. 174, 2591–2601 (2005).

    Article  CAS  PubMed  Google Scholar 

  54. Joshi, N. S. et al. Regulatory T cells in tumor-associated tertiary lymphoid structures suppress anti-tumor T cell responses. Immunity 43, 579–590 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Topchyan, P., Lin, S. & Cui, W. The role of CD4 T cell help in CD8 T cell differentiation and function during chronic infection and cancer. Immune Netw. 23, e41 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  56. Gu, X. et al. TEL-2 is a novel transcriptional repressor related to the ETS factor TEL/ETV-6. J. Biol. Chem. 276, 9421–9436 (2001).

    Article  CAS  PubMed  Google Scholar 

  57. Ayyoob, K., Masoud, K., Vahideh, K. & Jahanbakhsh, A. Authentication of newly established human esophageal squamous cell carcinoma cell line (YM-1) using short tandem repeat (STR) profiling method. Tumour Biol. 37, 3197–3204 (2016).

    Article  CAS  PubMed  Google Scholar 

  58. Granja, J. M. et al. ArchR is a scalable software package for integrative single-cell chromatin accessibility analysis. Nat. Genet. 53, 403–411 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Grant, C. E., Bailey, T. L. & Noble, W. S. FIMO: scanning for occurrences of a given motif. Bioinformatics 27, 1017–1018 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Stuart, T. et al. Comprehensive integration of single-cell data. Cell 177, 1888–1902 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Li, J. C. A. Modeling survival data: extending the Cox model. Sociol. Method. Res. 32, 117–120 (2003).

    Article  Google Scholar 

  62. Chowdhury, P. S., Viner, J. L., Beers, R. & Pastan, I. Isolation of a high-affinity stable single-chain Fv specific for mesothelin from DNA-immunized mice by phage display and construction of a recombinant immunotoxin with anti-tumor activity. Proc. Natl Acad. Sci. USA 95, 669–674 (1998).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Schumann, K. et al. Generation of knock-in primary human T cells using Cas9 ribonucleoproteins. Proc. Natl Acad. Sci. USA 112, 10437–10442 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Welsh, R. M. & Seedhom, M. O. Lymphocytic choriomeningitis virus (LCMV): propagation, quantitation, and storage. Curr. Protoc. Microbiol. Chapter 15, Unit 15A.11 (2008).

    Google Scholar 

  65. Wherry, E. J. et al. Molecular signature of CD8+ T cell exhaustion during chronic viral infection. Immunity 27, 670–684 (2007).

    Article  CAS  PubMed  Google Scholar 

  66. Ahn, J. J., Selvanantham, T., Zhang, M. A., Mallevaey, T. & Dunn, S. E. Experimental infection with Listeria monocytogenes as a model for studying host interferon-γ responses. J. Vis. Exp. 16, 54554 (2016).

    Google Scholar 

  67. Yoo, S. H. et al. A noncanonical E-box enhancer drives mouse Period2 circadian oscillations in vivo. Proc. Natl Acad. Sci. USA 102, 2608–2613 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Giacomelli, A. O. et al. Mutational processes shape the landscape of TP53 mutations in human cancer. Nat. Genet. 50, 1381–1387 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Cheng, J. et al. Cancer-cell-derived fumarate suppresses the anti-tumor capacity of CD8+ T cells in the tumor microenvironment. Cell Metab. 35, 961–978 (2023).

    Article  CAS  PubMed  Google Scholar 

  70. Scolaro, T. et al. Nucleotide metabolism in cancer cells fuels a UDP-driven macrophage cross-talk, promoting immunosuppression and immunotherapy resistance. Nat. Cancer 5, 1206–1226 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Zhang, B. et al. B cell-derived GABA elicits IL-10+ macrophages to limit anti-tumour immunity. Nature 599, 471–476 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank H. Wu for discussions, Z. Chang and the Animal Facility of Tsinghua University for help with mouse care and surgery and Y. Liu and the Tsinghua University Branch of China National Center for Protein Sciences (Beijing) and Tsinghua University Technology Center for flow cytometry support. We thank Z. Dong for kindly providing the L. monocytogenes strain that expresses the OVA epitope. We thank M. M. Xu for kindly providing P14 CD45.1 mice. LCMV strains Armstrong and clone 13 were kindly provided by L. Ye. We are also grateful to W. Zeng for the reagents and technical support. This research was supported by the National Natural Science Foundation of China (82125030 and 82341022) to P.J. T.P. and C.L. were supported by National Natural Science Foundation of China (32288102 and 32025006) and National Key Research and Development Program of China (2021YFA1100300). Part of the data analysis was performed on the High-Performance Computing Platform of the Center for Life Sciences, Peking University. H.Z. was supported by the National Science Foundation of China (82100193), J.C. was supported by the National Science Foundation of China (82403315), and Y.Q. was supported by the National Natural Science Foundation of China (82373235).

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Author notes

  1. These authors contributed equally: Jie Cheng, Yifeng Xiao, Ting Peng, Zijian Zhang, You Qin.

Authors and Affiliations

  1. State Key Laboratory of Molecular Oncology, School of Life Sciences, Tsinghua-Peking Center for Life Sciences, Tsinghua University, Beijing, China

    Jie Cheng, Yifeng Xiao, Jinxin Yan, Zhijun He & Peng Jiang

  2. Department of Pathology, School of Basic Medicine, Tongji Medical College and State Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Huazhong University of Science and Technology, Wuhan, China

    Jie Cheng

  3. State Key Laboratory of Molecular Oncology, Beijing Key Laboratory of Carcinogenesis and Translational Research, Department of Molecular Oncology, Peking University Cancer Hospital & Institute, Beijing, China

    Ting Peng

  4. Institute of Biology and Medicine, College of Life and Health Sciences, Wuhan University of Science and Technology, Wuhan, China

    Zijian Zhang, Jiangzhou Shi & Haichuan Zhu

  5. Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China

    You Qin

  6. School of Pharmaceutical Sciences, Tsinghua University, Beijing, China

    Yuqian Wang & Jianwei Wang

  7. School of Life Sciences, Center for Statistical Science, Peking University, Beijing, China

    Zihao Zhao, Liangtao Zheng, Zemin Zhang & Cheng Li

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Contributions

J.C. and P.J. designed the experiments with the help of C.L. and H.Z. J.C. and Y.X. performed most experiments except those mentioned below. T.P., Z. Zhao, L.Z., Zemin Zhang and C.L. performed bioinformatics analyses and provided insightful discussion. Zijian Zhang performed the CAR T cell experiments. J.C. and Y.Q. performed patient sample collection and clinical analysis. Y.W., J.S., J.Y., Z.H. and J.W. provided technical assistance. J.C. organized and analyzed the data. P.J. supervised the research. J.C. and P.J. wrote the manuscript. All authors commented on the manuscript.

Corresponding authors

Correspondence to Zemin Zhang, Cheng Li, Haichuan Zhu or Peng Jiang.

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Competing interests

P.J. and J.C. report a patent application related to this study. The other authors declare no competing interests.

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Nature Cancer thanks Nabil Ahmed, Gregory Verdeil and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 ETV7 expression is robustly upregulated in exhausted CD8+ T cells in tumors and effect of ETV7 on the expression of memory and exhaustion genes CD8+ T cells.

a, Expression levels of memory and exhaustion genes along the differentiation trajectory of tumor-infiltrating CD8+ T cells. Cluster annotation is shown in Fig. 2d. b, Chromatin accessibility of memory and exhaustion score as well as signature genes along the differentiation trajectory of tumor-infiltrating CD8+ T cells from basal cell carcinoma samples. The cluster annotation is shown in Fig. 2b. c, Human naive CD8+ T cells were stimulated with anti-CD3/CD28 antibodies 4 times every 2 days or not (naive). ETV7 mRNA levels and protein expression (percentage of CD8+ T cells and mean fluorescence intensity, MFI) were determined by RT-PCR and FACS analysis, respectively (n = 4 biological independent replicates). d-f, Human naive CD8+ T cells were stimulated with anti-CD3/CD28 antibodies 4 times every 2 days or not (naive). The mRNA levels (d) and protein expression (e) (percentage of CD8+ T cells and mean fluorescence intensity, MFI) of memory and exhaustion genes were determined by RT-PCR and FACS analysis, respectively (n = 4 biological independent replicates). The mRNA levels of TFs were determined by RT-PCR analysis (f) (n = 4 biological independent replicates). g-j, Mouse naive CD8+ T cells were stimulated with anti-mouse CD3/CD28 antibodies for 24 hours and then transfected with lentivirus to overexpress the five candidates. The cells were then stimulated 3 times every two days and analyzed. The mRNA (g-h) and protein expression (i-j) in CD8+ T cells were determined by RT-PCR and FACS analysis, respectively (n = 4 biological independent replicates). All data are the mean ± SD. P-values are indicated. Significance was calculated by two-sided unpaired Student’s t-test.

Source data

Extended Data Fig. 2 Enhanced chromatin accessibility and expression of ETV7 during T cell terminal differentiation and a role for IFNβ and TCR stimulation in promoting ETV7 expression.

a, Genomic traces of aggregated bulk ATAC-seq data showing chromatin accessibility around ETV7 in different CD8+ T-cell clusters from melanoma (MELA) samples. Tex, exhausted T cells. The shaded bars in graphs mark peaks with the binding motif of ETV7. b, Correlation between ETV7 expression level and memory score (top panel) or exhaustion score (bottom panel) in ETV7+ CD8+ T cells from ESCA (esophageal cancer) and UCEC (uterine cervical endometrial cancer). p value was calculated by Pearson correlation analysis. c-e, JURKAT cells were cultured with IFNs or IFNβ (U/ml) for the indicated times. mRNA (c, d) and proteins (e) were analyzed by RT-PCR (n = 4 independent wells) or Western blot (the experiment was independently repeated three times with similar results). f, JURKAT cells were activated and treated with IFNβ for different concentrations and time. ETV7 proteins were analyzed by FACS (n = 4 biological independent replicates). g, Human CD8+ T cells were enriched from PBMCs and then activated. Then cells were treated with IFNβ. ETV7 proteins were analyzed by FACS (n = 4 biological independent replicates). h-j, Human CD8+ T cells were enriched from PBMCs and then activated for 24 hours. The mRNA and proteins were analyzed by RT-PCR or western blot and FACS, respectively. The experiment in (i) was independently repeated three times with similar results. k,l, Human CD8+ T cells were enriched from PBMCs and then activated for 24 hours. Then cells were treated with anti-CD3 antibody or/and IFNβ for different concentrations and time. The mRNA and proteins were analyzed by RT-PCR (k) or FACS (l), respectively. m, Human CD8+ T cells were enriched from PBMCs and then activated for 24 hours. Then ETV7 were overexpressed or knocked out. After three days, the mRNA was analyzed by RT-PCR (n = 4 biological independent replicates). All data are the mean ± SD. P-values are indicated. Significance was calculated by two-sided unpaired Student’s t-test.

Source data

Extended Data Fig. 3 Effect of ETV7 on the expression of memory and exhaustion genes in mouse and human CD8+ T cells.

a-d, Mouse naïve CD8+ T cells were stimulated with anti-mouse CD3/CD28 antibodies for 24 hours, then transfected with lentivirus expressing ETV7 or vector control and induced to terminal exhaustion as described in Fig. 1f. The protein level of ETV7 (percentage of CD8+ T cells and MFI) was determined by FACS analysis (a). mRNA was detected by RT-PCR (b) (memory genes, left panel; exhaustion genes, right panel). The protein expression of memory genes (c) and exhaustion genes (d) were determined by FACS analysis. n = 4 biological independent replicates). The experiment was independently repeated three times with similar results. e-h, Human naive CD8+ T cells were enriched from peripheral blood mononuclear cells and then stimulated with anti-human CD3/CD28 antibodies for 24 hours. Cells were transfected with shETV7 lentiviruses or vector control (shCtrl) virus and induced to terminal exhaustion. Cells were stimulated three times every two days and ETV7 protein levels were determined by FACS analysis (e). RT-PCR analysis was used to detect mRNA levels (f) (n = 4 biological independent replicates). and FACS analysis was used to detect protein levels of memory (g) and exhaustion (h) proteins (n = 4 biological independent replicates). All data are the mean ± SD. P-values are indicated. Significance was calculated by two-sided unpaired Student’s t-test.

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Extended Data Fig. 4 ETV7 promotes CD8+ T cell exhaustion in vivo during acute infections.

a-d, Experimental schemes for Listeria monocytogenes infection. Naïve OT-1 CD8+ T cells were enriched from OT-1 mice and transfected with lentivirus expressing ETV7 or vector control. The cells were then adoptively transferred into CD45.1 host mice. After infusion, the mice were infected with Lm-OVA. CD45.2 OT-1 CD8+ T cells from the spleen were analyzed on days 0 to 22 post infection (a). Memory markers (CXCR4, CXCR5 and TCF1) (b), exhaustion markers (PD1, TOX, TIM3 and LAG3) (c), and CD45.1+CD8+ T cells (d) were analyzed by FACS (n = 4 biological independent replicates). e-g, Experimental schemes for infection with Armstrong. Naïve CD45.1 P14 CD8+ T cells were enriched from P14 mice and transfected with lentivirus expressing ETV7 or vector control. The cells were then adoptively transferred into CD45.2 host mice. After infusion, mice were infected with Armstrong. CD45.1 P14 CD8+ T cells from the spleen were analyzed on days 0 to 22 post infection (e). Memory markers (CXCR4, CXCR5 and TCF1) (left panel) and exhaustion markers (PD1, TOX, TIM3 and LAG3) (right panel) were analyzed by FACS (f). TCF1+TIM3−CD8+T cells and TCF1−TIM3+CD8+ T cells were analyzed by FACS (g) (n = 4 biological independent replicates). All data are the mean ± SD. P-values are indicated. Significance was calculated by two-sided unpaired Student’s t-test.

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Extended Data Fig. 5 ETV7 increases functional exhaustion of CD8+ T cells during infection in mice and humans.

a-c, Related to Extended Data Fig. 4e. Naïve CD45.1 P14 CD8+ T cells were enriched from P14 mice and transfected with lentivirus expressing ETV7 or vector control. The cells were then adoptively transferred into CD45.2 host mice. After infusion, mice were infected with Armstrong. CD45.1 P14 CD8+ T cells from the spleen were analyzed on days 0 to 22 post infection. GP33 tetramer+CD45.1+ cells (a) and cytokine expression (IFNγ and TNFα) (b) were analyzed by FACS after infected by Armstrong. Viral load in spleen were detected by RT-PCR according to previous protocol127 (c). n = 4 mice per group. The experiment was independently repeated three times with similar results. d, Naïve CD45.1 P14 CD8+ T cells were enriched from P14 mice and transfected with lentivirus expressing ETV7 or vector control. The cells were then adoptively transferred into CD45.2 host mice. After infusion, mice were infected with Clone 13. TCF1 + TIM3−CD8+ T cells and TCF1−TIM3+CD8+ T cells were analyzed by FACS (n = 4 mice per group). The experiment was independently repeated three times with similar results. e, f, UMAP visualization showing the level of memory score (left panel), exhaustion score (middle panel), and expression level of ETV7 (right panel) in CD8+ T cell clusters from scRNA-seq datasets of COVID-19 infected patients (e). Correlation between the mean expression level of ETV7 and mean memory score (left panel) or exhaustion score (right panel) in all CD8+ T cells from scRNA-seq datasets of COVID-19 infected patients (f). P-values were calculated using Pearson correlation analysis and are indicated. All data are the mean ± SD. Significance was calculated by two-sided unpaired Student’s t-test.

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Extended Data Fig. 6 ETV7 impacts mouse and human CD8+ T cell function in vitro.

a-e, Mouse naive CD8+ T cells were stimulated and transfected with lentivirus for overexpression of ETV7 or vector as control. Cells were stimulated with different concentrations of antibodies (1x, 3.5 µgml−1 anti-CD3 and 1 µgml−1 anti-CD28 antibodies; 0.5x, 1.75 µgml−1 anti-CD3 and 0.5 µgml−1 anti-CD28 antibodies; 0.25x, 0.875 µgml−1 anti-CD3 and 0.25 µgml−1 anti-CD28 antibodies) for three times every two days. ETV7 protein levels were determined by FACS analysis (a). Expressions of exhaustion genes were detected by RT-PCR (b) or FACS analysis (c). The number of cells before each stimulation was counted (d), Ki67 protein level was analyzed by FACS (e) (n = 4 biological independent replicates). g, Mouse naive OT-I CD8+ T cells were stimulated with a OVA257-264 peptide and transfected with lentivirus, then stimulated with different concentrations of OVA257-264 peptide for two times every two days. Then OT-I cells were co-cultured with B16-OVA cells. The relative cytotoxicity was determined by measuring the LDHA release (left panel, n = 4 biological independent replicates). The percentage of Annexin V + B16-OVA cells (relative to total B16-OVA cells) were determined by FACS analysis (right panel, n = 4 biological independent replicates). f,h,i, Mouse naive CD8+ T cells were stimulated with different concentrations of antibodies as in a-f and subjected to RT-PCR (h) or FACS (f, i) analysis to determine cytokine levels (n = 4 biological independent replicates). j,k, Mouse naive CD8+ T cells were stimulated and transfected. Cell death was determined by 7AAD (j) and Annexin V staining (k) (n = 4 biological independent replicates). l-n, Human naive CD8+ T cells were enriched from PBMCs and stimulated. Cells were transfected with shETV7 lentiviruses or vector control (shCtrl) virus. Cells were stimulated with different concentrations of antibodies as in a-f. The number of cells before each stimulation was counted (m). The mRNA (l) and protein (n) levels of cytokines were detected by RT-PCR or FACS analysis (n = 4 biological independent replicates). All data are the mean ± SD. P-values are indicated. Significance was calculated by two-sided unpaired Student’s t-test.

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Extended Data Fig. 7 ETV7 drives CD8+ T cell exhaustion program in MC38 OVA tumor model and effect of CD4+ T cells and identification in bone marrow chimera experiment.

a-c, C57BL/6 mice were injected subcutaneously with 2 × 105 MC38 OVA cells and immunodepleted by irradiation (2.5 Gy, twice). Naive OT-I CD8+ T cells were stimulated with OVA257-264 peptide for 24 hours and transfected with lentivirus for overexpression of ETV7 or vector as control (a). OT-I CD8+ T cells were then adoptively transferred by tail vein injection (i.v.) and injected intraperitoneally (i.p.). Tumor loads were measured (b). Protein expression (the percentage of CD8+ T cells as well as MFI) in tumor-infiltrating CD8+ T cells, including ETV7 (a), memory proteins, and exhaustion proteins was measured by FACS analysis (c) (n = 6 mice per group). d-f, C57BL/6 mice were injected intraperitoneally (i.p.) with 200 μg of α-CD4 antibody (clone GK1.5) or PBS twice a week to deplete CD4+ T cells or not. 7 days later, the mice were subcutaneously injected with 2×106 B16-OVA cells. Naive OT-I CD8+ T cells were stimulated with OVA257-264 peptide for 24 hours and transfected with lentivirus for overexpression of ETV7 or vector as control. After 3 days, OT-I CD8+ T cells were adoptively transferred by tail vein injection (i.v.). CD4+ T cells in spleen were analyzed by FACS (d). Tumors were photographed and weighed (e). The percentage and MFI of memory proteins and exhaustion proteins (f) were measured by FACS analysis (n = 5 mice per group). g, Related to Fig. 6. Mice were treated as described in Fig. 6a. Peripheral blood (10 µl) was collected and analyzed for lineage distribution and of B cells (B220+), T cells (CD3+), and myeloid cells (B220− CD3−) were analyzed by FACS at the 1st and 2nd month (n = 5 mice per group). Data are the mean ± SD. P-values are indicated. Significance was calculated by two-sided unpaired Student’s t-test.

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Extended Data Fig. 8 Expression of ETV7 in different types of cells in tumors and correlation of its expression levels with survival in human cancer patients.

a,b, Related to Fig. 6a. LSK (Lineage− Sca1+ cKit+) cells were enriched and sorted and subjected by lentiviral transduction of ETV7 overexpression or vector as control. 72 h later, 2×104 GFP+ cells (CD45.2) were sorted and injected into lethally irradiated recipients (10 Gy) recipient mice (CD45.1/2). At the 2nd month, mice were subcutaneously injected with 5 × 105 B16 cells. Protein expression of ETV7 in tumor-infiltrating CD8+ T cells (a) as well as CD8+ T cells in tumor-draining lymph nodes (Td-LN) and spleens (b) were analyzed by FACS (n = 4 biological independent replicates). c, Percentage of ETV7+ T cells across different cancer types. Tex, exhausted T cells. d, Mean expression level of ETV7 in different cell types from ESCA (left panel) and UCEC (right panel) tumor tissues. e-g, The Kaplan-Meier curve plot shows that PAAD (e, ETV7 high, n = 91; ETV7 low, n = 92), LGG (f, ETV7 high, n = 81; ETV7 low, n = 82) and LAML (g, ETV7 high, n = 264; ETV7 low, n = 265) patients with higher expression of ETV7 had worse overall survival compared to those in the ETV7 low group. The p-value shown in the figure is the log-rank p-value. h, Mean expression level of ETV7 in CD8+ T cells of melanoma patients after anti-PD1 treatment were evaluated and grouped. R, response (n = 5), NR, non-response (n = 13). The p-value shown in the figure is the Wilcoxon rank sum test p-value. Detailed information in Supplementary Table 3. All data are the mean ± SD. P-values are indicated. Significance was calculated by two-sided unpaired Student’s t-test.

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Extended Data Fig. 9 ETV7 orchestrates memory and exhaustion gene expression in CD8+ T cells of tumor patients and HCV infection patients.

a, b, Genomic traces of aggregated scATAC-seq data from basal cell carcinoma and renal cell carcinoma patients showing chromatin accessibility around CXCR4, EOMES, CXCR5, HAVCR2 and CXCL13 in memory and exhausted T (Tex) cell clusters. The location of the predicted binding motifs of ETV7 is marked at the bottom (a). The shaded bars in graphs mark peaks with the binding motif of ETV7. The p-value and location of the predicted binding motifs of ETV7 (b). c, Heatmap of opened and closed peaks with ETV7 binding motif from naïve, memory to exhaustion of CD8+ T cells from HCV infected patients. Targeted memory genes and exhaustion genes as well as ETV7 were shown (CCR4, TCF7, CTLA4, and TOX).

Extended Data Fig. 10 The expression of ETV7 is correlated with the expression of memory genes and exhaustion marker genes and generation of anti-MSLN CAR T-shETV7 therapeutic system.

a-c, Related to Fig. 7f and g. Mouse naive CD8+ T cells were stimulated with anti-mouse CD3/CD28 antibodies for 24 hours and then transfected with lentivirus for overexpression of ETV7 or vector control (Ctrl). The cells were then stimulated 3 times every two days to induce exhaustion. The mRNA levels (b) and protein (percentage of CD8+ T cells and MFI) (a, c) expression of TCF1, CTLA4, TOX, CXCR4, EOMES, CXCR5, CXCL13, LAG3, TIM3, and TNFRSF9 in CD8+ T cells were determined by RT-PCR and FACS analysis, respectively (n = 4 biological independent replicates). d, Pearson correlation coefficient between expression level of ETV7 and memory, exhaustion genes across different cancer types. e, Schematic illustration of the anti-MSLN CAR T-shCtrl, anti-MSLN CAR T-shETV7 constructs. f, Anti-MSLN CAR T cells stably overexpressing ETV7 shRNA (shRTV7) or vector control (shCtrl) were lysed for RT-PCR (n = 3 biological independent replicates) and WB. The experiment was independently repeated three times with similar results. g, Total number of cells at the time of transduction with anti-MSLN CAR T-shCtrl and anti-MSLN CAR T-shETV7 (n = 3 biological independent replicates). h, Calcein release assay was used for in vitro cytotoxicity testing at 3 different effectors: target ratios on K562 overexpressing human MSLN stability cell lines as indicated (n = 3 biological independent replicates). i-k, Related to Fig. 8g–k. Schematic of the mouse model experiment (i). OVCAR8 cells were subcutaneously implanted into the flanks of NCG mice to establish a xenograft tumor model. The mice were then treated with 3×106 anti-MSLN CAR T-shCtrl cells, 3×106 anti-MSLN CAR T-shETV7 or T cells per mouse on day 8 after tumor cell injection. Tumor burden was monitored twice weekly using Vernier calipers (j) (n = 5–7 mice per group) Kaplan-Meier survival curves of OVCAR8 xenograft mice treated with anti-MSLN CAR T-shCtrl cells, anti-MSLN CAR T-shETV7 or T cells (k) (n = 7 mice per group). All data are the mean ± SD. P-values are indicated. Significance was calculated by two-sided unpaired Student’s t-test.

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Supplementary information

Supplementary Information

Supplementary Fig. 1. Gating strategies used in FACS analysis.

Reporting Summary

Supplementary Tables 1–6

Supplementary Table 1. Antibodies. Supplementary Table 2. Commercial reagents. Supplementary Table 3. Cell lines, mice, bacteria and virus strains. Supplementary Table 4. Oligonucleotides. Supplementary Table 5. Software, algorithms and databases. Supplementary Table 6. Characteristics of all enrolled individuals.

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Cheng, J., Xiao, Y., Peng, T. et al. ETV7 limits the antiviral and antitumor efficacy of CD8+ T cells by diverting their fate toward exhaustion. Nat Cancer 6, 338–356 (2025). https://doi.org/10.1038/s43018-024-00892-0

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