An intrinsic role of IL-33 in Treg cell–mediated tumor immunoevasion

Abstract

Regulatory T (Treg) cells accumulate into tumors, hindering the success of cancer immunotherapy. Yet, therapeutic targeting of Treg cells shows limited efficacy or leads to autoimmunity. The molecular mechanisms that guide Treg cell stability in tumors remain elusive. In the present study, we identify a cell-intrinsic role of the alarmin interleukin (IL)-33 in the functional stability of Treg cells. Specifically, IL-33-deficient Treg cells demonstrated attenuated suppressive properties in vivo and facilitated tumor regression in a suppression of tumorigenicity 2 receptor (ST2) (IL-33 receptor)-independent fashion. On activation, Il33−/− Treg cells exhibited epigenetic re-programming with increased chromatin accessibility of the Ifng locus, leading to elevated interferon (IFN)-γ production in a nuclear factor (NF)-κB–T-bet-dependent manner. IFN-γ was essential for Treg cell defective function because its ablation restored Il33−/− Treg cell-suppressive properties. Importantly, genetic ablation of Il33 potentiated the therapeutic effect of immunotherapy. Our findings reveal a new and therapeutically important intrinsic role of IL-33 in Treg cell stability in cancer.

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Fig. 1: IL-33 deficiency promotes anti-tumor immunity and inhibits tumor growth.
Fig. 2: Host-derived IL-33 role in tumor regression.
Fig. 3: Impaired suppressive function of IL-33-deficient Treg cells in vivo.
Fig. 4: IL-33-deficient Treg cells acquire a fragile phenotype.
Fig. 5: Role of IFN-γ in the impaired suppressive function of Il33−/− Treg cells.
Fig. 6: Increased NF-κB activation and T-bet expression promote IFN-γ production in Il33−/− Foxp3+ Treg cells.
Fig. 7: IL-33 deficiency potentiated immunotherapy efficacy.

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request. The RNAseq and ATACseq data have been deposited in the Gene Expression Omnibus with the accession code GSE138874.

References

  1. 1.

    Sakaguchi, S., Yamaguchi, T., Nomura, T. & Ono, M. Regulatory T cells and immune tolerance. Cell 133, 775–787 (2008).

  2. 2.

    Hatzioannou, A., Alissafi, T. & Verginis, P. Myeloid-derived suppressor cells and T regulatory cells in tumors: unraveling the dark side of the force. J. Leukoc. Biol. 102, 407–421 (2017).

  3. 3.

    Zou, W. Regulatory T cells, tumour immunity and immunotherapy. Nat. Rev. Immunol. 6, 295–307 (2006).

  4. 4.

    Abdel-Wahab, N., Shah, M. & Suarez-Almazor, M. E. Adverse events associated with immune checkpoint blockade in patients with cancer: a systematic review of case reports. PLoS One 11, e0160221 (2016).

  5. 5.

    Jenkins, R. W., Barbie, D. A. & Flaherty, K. T. Mechanisms of resistance to immune checkpoint inhibitors. Br. J. Cancer 118, 9–16 (2018).

  6. 6.

    Liew, F. Y., Girard, J. P. & Turnquist, H. R. Interleukin-33 in health and disease. Nat. Rev. Immunol. 16, 676–689 (2016).

  7. 7.

    Cayrol, C. & Girard, J. P. Interleukin-33 (IL-33): a nuclear cytokine from the IL-1 family. Immunol. Rev. 281, 154–168 (2018).

  8. 8.

    Schiering, C. et al. The alarmin IL-33 promotes regulatory T-cell function in the intestine. Nature 513, 564–568 (2014).

  9. 9.

    Overacre-Delgoffe, A. E. et al. Interferon-γ drives Treg fragility to promote anti-tumor immunity. Cell 169, 1130–1141.e11 (2017).

  10. 10.

    Overacre-Delgoffe, A. E. & Vignali, D. A. A. Treg fragility: a prerequisite for effective antitumor immunity? Cancer Immunol. Res. 6, 882–887 (2018).

  11. 11.

    Andersson, P. et al. Molecular mechanisms of IL-33-mediated stromal interactions in cancer metastasis. JCI Insight 3, e122375 (2018).

  12. 12.

    Setiady, Y. Y., Coccia, J. A. & Park, P. U. In vivo depletion of CD4 +FOXP3+ Treg cells by the PC61 anti-CD25 monoclonal antibody is mediated by FcγRIII + phagocytes. Eur. J. Immunol. 40, 780–786 (2010).

  13. 13.

    Braun, H., Afonina, I. S., Mueller, C. & Beyaert, R. Dichotomous function of IL-33 in health and disease: from biology to clinical implications. Biochem. Pharm. 148, 238–252 (2018).

  14. 14.

    Toker, A. et al. Active demethylation of the Foxp3 locus leads to the generation of stable regulatory T cells within the thymus. J. Immunol. 190, 3180–3188 (2013).

  15. 15.

    Zeng, H. et al. mTORC1 couples immune signals and metabolic programming to establish Treg-cell function. Nature 499, 485–490 (2013).

  16. 16.

    Balasubramani, A. et al. Modular utilization of distal cis-regulatory elements controls Ifng gene expression in T cells activated by distinct stimuli. Immunity 33, 35–47 (2010).

  17. 17.

    Ali, S. et al. The dual function cytokine IL-33 interacts with the transcription factor NF-κB to dampen NF-κB-stimulated gene transcription. J. Immunol. 187, 1609–1616 (2011).

  18. 18.

    Lin, L., Spoor, M. S., Gerth, A. J., Brody, S. L. & Peng, S. L. Modulation of Th1 activation and inflammation by the NF-κB repressor Foxj1. Science 303, 1017–1020 (2004).

  19. 19.

    Grinberg-Bleyer, Y. et al. NF-κB c-Rel Is crucial for the regulatory T cell immune checkpoint in cancer. Cell 170, 1096–1108 e1013 (2017).

  20. 20.

    Hori, S. Lineage stability and phenotypic plasticity of Foxp3+ regulatory T cells. Immunol. Rev. 259, 159–172 (2014).

  21. 21.

    Apostolidis, S. A. et al. Phosphatase PP2A is requisite for the function of regulatory T cells. Nat. Immunol. 17, 556–564 (2016).

  22. 22.

    Huynh, A. et al. Control of PI3 kinase in Treg cells maintains homeostasis and lineage stability. Nat. Immunol. 16, 188–196 (2015).

  23. 23.

    Delgoffe, G. M. et al. The kinase mTOR regulates the differentiation of helper T cells through the selective activation of signaling by mTORC1 and mTORC2. Nat. Immunol. 12, 295–303 (2011).

  24. 24.

    Shrestha, S. et al. Treg cells require the phosphatase PTEN to restrain TH1 and TFH cell responses. Nat. Immunol. 16, 178–187 (2015).

  25. 25.

    Wei, J. et al. Autophagy enforces functional integrity of regulatory T cells by coupling environmental cues and metabolic homeostasis. Nat. Immunol. 17, 277–285 (2016).

  26. 26.

    Yu, X. et al. Metabolic control of regulatory T cell stability and function by TRAF3IP3 at the lysosome. J. Exp. Med 215, 2463–2476 (2018).

  27. 27.

    McClymont, S. A. et al. Plasticity of human regulatory T cells in healthy subjects and patients with type 1 diabetes. J. Immunol. 186, 3918–3926 (2011).

  28. 28.

    Dominguez-Villar, M., Baecher-Allan, C. M. & Hafler, D. A. Identification of T helper type 1-like, Foxp3+ regulatory T cells in human autoimmune disease. Nat. Med. 17, 673–675 (2011).

  29. 29.

    Oldenhove, G. et al. Decrease of Foxp3+ Treg cell number and acquisition of effector cell phenotype during lethal infection. Immunity 31, 772–786 (2009).

  30. 30.

    Di Pilato, M. et al. Targeting the CBM complex causes Treg cells to prime tumours for immune checkpoint therapy. Nature 570, 112–116 (2019).

  31. 31.

    Ouyang, W. et al. Novel Foxo1-dependent transcriptional programs control Treg cell function. Nature 491, 554–559 (2012).

  32. 32.

    Lee, J. H., Elly, C., Park, Y. & Liu, Y. C. E3 ubiquitin ligase VHL regulates hypoxia-inducible factor-1α to maintain regulatory T cell stability and suppressive capacity. Immunity 42, 1062–1074 (2015).

  33. 33.

    Koch, M. A. et al. The transcription factor T-bet controls regulatory T cell homeostasis and function during type 1 inflammation. Nat. Immunol. 10, 595–602 (2009).

  34. 34.

    Szabo, S. J. et al. A novel transcription factor, T-bet, directs Th1 lineage commitment. Cell 100, 655–669 (2000).

  35. 35.

    Levine, A. G. et al. Stability and function of regulatory T cells expressing the transcription factor T-bet. Nature 546, 421–425 (2017).

  36. 36.

    Yu, F., Sharma, S., Edwards, J., Feigenbaum, L. & Zhu, J. Dynamic expression of transcription factors T-bet and GATA-3 by regulatory T cells maintains immunotolerance. Nat. Immunol. 16, 197–206 (2015).

  37. 37.

    Sekimata, M. et al. CCCTC-binding factor and the transcription factor T-bet orchestrate T helper 1 cell-specific structure and function at the interferon-γlocus. Immunity 31, 551–564 (2009).

  38. 38.

    Zhou, J., Fan, J. Y., Rangasamy, D. & Tremethick, D. J. The nucleosome surface regulates chromatin compaction and couples it with transcriptional repression. Nat. Struct. Mol. Biol. 14, 1070–1076 (2007).

  39. 39.

    Roussel, L., Erard, M., Cayrol, C. & Girard, J. P. Molecular mimicry between IL-33 and KSHV for attachment to chromatin through the H2A-H2B acidic pocket. EMBO Rep. 9, 1006–1012 (2008).

  40. 40.

    Carriere, V. et al. IL-33, the IL-1-like cytokine ligand for ST2 receptor, is a chromatin-associated nuclear factor in vivo. Proc. Natl Acad. Sci. USA 104, 282–287 (2007).

  41. 41.

    Choi, Y. S. et al. Nuclear IL-33 is a transcriptional regulator of NF-κB p65 and induces endothelial cell activation. Biochem. Biophys. Res. Commun. 421, 305–311 (2012).

  42. 42.

    Travers, J. et al. Chromatin regulates IL-33 release and extracellular cytokine activity. Nat. Commun. 9, 3244 (2018).

  43. 43.

    Polesso, F., Sarker, M., Anderson, A., Parker, D. C. & Murray, S. E. Constitutive expression of NF-κB inducing kinase in regulatory T cells impairs suppressive function and promotes instability and pro-inflammatory cytokine production. Sci. Rep. 7, 14779 (2017).

  44. 44.

    Oh, H. et al. An NF-κB transcription-factor-dependent lineage-specific transcriptional program promotes regulatory T cell identity and function. Immunity 47, 450–465.e5 (2017).

  45. 45.

    Kim, J. M., Rasmussen, J. P. & Rudensky, A. Y. Regulatory T cells prevent catastrophic autoimmunity throughout the lifespan of mice. Nat. Immunol. 8, 191–197 (2007).

  46. 46.

    Alissafi, T., Hatzioannou, A., Legaki, A. I., Varveri, A. & Verginis, P. Balancing cancer immunotherapy and immune-related adverse events: the emerging role of regulatory T cells. J. Autoimmun. 104, 102310 (2019).

  47. 47.

    Liu, Z. et al. Modifying the cancer-immune set point using vaccinia virus expressing re-designed interleukin-2. Nat. Commun. 9, 4682 (2018).

  48. 48.

    Ishizuka, J. J. et al. Loss of ADAR1 in tumours overcomes resistance to immune checkpoint blockade. Nature 565, 43–48 (2019).

  49. 49.

    Postow, M. A., Callahan, M. K. & Wolchok, J. D. Immune checkpoint blockade in cancer therapy. J. Clin. Oncol. 33, 1974–1982 (2015).

  50. 50.

    Wei, S. C. et al. Distinct cellular mechanisms underlie anti-CTLA-4 and anti-PD-1 checkpoint blockade. Cell 170, 1120–1133.e17 (2017).

  51. 51.

    Martin, P. et al. Disease severity in K/BxN serum transfer-induced arthritis is not affected by IL-33 deficiency. Arthritis Res. Ther. 15, R13 (2013).

  52. 52.

    Hatzioannou, A. et al. Intratumoral accumulation of podoplanin-expressing lymph node stromal cells promote tumor growth through elimination of CD4+ tumor-infiltrating lymphocytes. Oncoimmunology 5, e1216289 (2016).

  53. 53.

    Gong, Y. et al. lncRNA-screen: an interactive platform for computationally screening long non-coding RNAs in large genomics datasets. BMC Genomics 18, 434 (2017).

  54. 54.

    Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).

  55. 55.

    Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).

  56. 56.

    Buenrostro, J. D., Giresi, P. G., Zaba, L. C., Chang, H. Y. & Greenleaf, W. J. Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nat. Methods 10, 1213–1218 (2013).

  57. 57.

    Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with bowtie 2. Nat. Methods 9, 357–359 (2012).

  58. 58.

    Zhang, Y. et al. Model-based analysis of ChIP-Seq (MACS). Genome Biol. 9, R137 (2008).

  59. 59.

    Makridakis, M. & Vlahou, A. GeLC-MS: a sample preparation method for proteomics analysis of minimal amount of tissue. Methods Mol. Biol. 1788, 165–175 (2018).

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Acknowledgements

We thank T. Alissafi for fruitful conversations and critical reading of the manuscript, R.M. Barouni for technical assistance, P. Alexakos for technical assistance on animal handling and maintenance and A. Apostolidou for technical assistance on flow cytometry and cell sorting. We also thank M. Makridakis and G. Kontostathi for PRM analysis. This work was supported by grants from the GGSRT (no. Aristeia II 3468 to P.V.). M.B. was funded by the German Research Foundation (grant no. BE 4427/3-1) and is a member of the excellence cluster ImmunoSensation. T.C. was supported by the ERC (grant no. DEMETINL-683145) and the German Research Foundation (grant no. SFB 1181, CO7). D.B. was supported by the ERC under the European Union’s Horizon 2020 research and innovation program (grant agreement no. 742390). A.Hatzioannou is supported by IKY Fellowships of Excellence for Postgraduate Studies in Greece, Siemens Program and ‘Stratigos’ grant of the Hellenic Society of Melanoma Study. A.B. is financed by Greece and the European Union (European Social Fund) through the Operational Program ‘Human Resources Development, Education and Lifelong Learning’ in the context of the project ‘Reinforcement of Postdoctoral Researchers’ (no. MIS-5001552), implemented by the State Scholarships Foundation. D.B. and P.V. were supported by the European Union’s Horizon 2020 research and innovation program (grant agreement no. 733100).

Author information

A.Hatzioannou and A.B. designed and performed experiments, analyzed the data, generated the figures and wrote the manuscript. C.F., M.-S.V., M.K., K.H. and A.Henriques performed experiments and analyzed the data. L.B. generated and provided critical reagents. T.S. and A.Tsirigos assisted with mRNA-seq and ATAC-seq data analysis and interpretation. T.S. generated the figures. J.Z. and A.Termentzi performed and analyzed the targeted proteomics experiments. V.K., P.G. and M.B. contributed to the data analysis and interpretation. T.C. and D.B. interpreted the data. P.V. designed and supervised the study, performed the data analysis and wrote the manuscript.

Correspondence to Panayotis Verginis.

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Peer review information L. A. Dempsey was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

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Hatzioannou, A., Banos, A., Sakelaropoulos, T. et al. An intrinsic role of IL-33 in Treg cell–mediated tumor immunoevasion. Nat Immunol 21, 75–85 (2020). https://doi.org/10.1038/s41590-019-0555-2

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