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.

  • Review Article
  • Published:

Mechanisms of immune activation and regulation: lessons from melanoma

Nature Reviews Cancer volume 22, pages 195–207 (2022)Cite this article

Subjects

Abstract

Melanoma, a skin cancer that develops from pigment cells, has been studied intensively, particularly in terms of the immune response to tumours, and has been used as a model for the development of immunotherapy. This is due, in part, to the high mutational burden observed in melanomas, which increases both their immunogenicity and the infiltration of immune cells into the tumours, compared with other types of cancers. The immune response to melanomas involves a complex set of components and interactions. As the tumour evolves, it accumulates an increasing number of genetic and epigenetic alterations, some of which contribute to the immunogenicity of the tumour cells and the infiltration of immune cells. However, tumour evolution also enables the development of resistance mechanisms, which, in turn, lead to tumour immune escape. Understanding the interactions between melanoma tumour cells and the immune system, and the evolving changes within the melanoma tumour cells, the immune system and the microenvironment, is essential for the development of new cancer therapies. However, current research suggests that other extrinsic factors, such as the microbiome, may play a role in the immune response to melanomas. Here, we review the mechanisms underlying the immune response in the tumour and discuss recent advances as well as strategies for treatment development.

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

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

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

Fig. 1: Tumour-intrinsic mechanisms and their effect on the antitumour immune response.
Fig. 2: Effect of immune and stromal cells on melanoma tumours.
Fig. 3: Summary of mechanisms affecting antitumour immunity in melanoma and potential therapeutic modalities.

Similar content being viewed by others

References

  1. Cancer Genome Atlas Network. Genomic classification of cutaneous melanoma. Cell 161, 1681–1696 (2015).

    Article  Google Scholar 

  2. Long, G. V. et al. Dabrafenib and trametinib versus dabrafenib and placebo for Val600 BRAF-mutant melanoma: a multicentre, double-blind, phase 3 randomised controlled trial. Lancet 386, 444–451 (2015).

    Article  CAS  PubMed  Google Scholar 

  3. Salgaller, M. L., Weber, J. S., Koenig, S., Yannelli, J. R. & Rosenberg, S. A. Generation of specific anti-melanoma reactivity by stimulation of human tumor-infiltrating lymphocytes with MAGE-1 synthetic peptide. Cancer Immunol. Immunother. 39, 105–116 (1994).

    Article  CAS  PubMed  Google Scholar 

  4. Blass, E. & Ott, P. A. Advances in the development of personalized neoantigen-based therapeutic cancer vaccines. Nat. Rev. Clin. Oncol. 18, 215–229 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  5. Callahan, M. K. et al. Nivolumab plus ipilimumab in patients with advanced melanoma: updated survival, response, and safety data in a phase I dose-escalation study. J. Clin. Oncol. 36, 391–398 (2018).

    Article  CAS  PubMed  Google Scholar 

  6. Fridman, W. H., Pages, F., Sautes-Fridman, C. & Galon, J. The immune contexture in human tumours: impact on clinical outcome. Nat. Rev. Cancer 12, 298–306 (2012).

    Article  CAS  PubMed  Google Scholar 

  7. Gajewski, T. F. Failure at the effector phase: immune barriers at the level of the melanoma tumor microenvironment. Clin. Cancer Res. 13, 5256–5261 (2007).

    Article  CAS  PubMed  Google Scholar 

  8. Anichini, A., Vegetti, C. & Mortarini, R. The paradox of T-cell-mediated antitumor immunity in spite of poor clinical outcome in human melanoma. Cancer Immunol. Immunother. 53, 855–864 (2004).

    Article  PubMed  Google Scholar 

  9. Larkin, J. et al. Combined nivolumab and ipilimumab or monotherapy in untreated melanoma. N. Engl. J. Med. 373, 23–34 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  10. Robert, C. et al. Pembrolizumab versus ipilimumab in advanced melanoma. N. Engl. J. Med. 372, 2521–2532 (2015).

    Article  CAS  PubMed  Google Scholar 

  11. Wolchok, J. D. et al. Overall survival with combined nivolumab and ipilimumab in advanced melanoma. N. Engl. J. Med. 377, 1345–1356 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Larkin, J. et al. Five-year survival with combined nivolumab and ipilimumab in advanced melanoma. N. Engl. J. Med. 381, 1535–1546 (2019).

    Article  CAS  PubMed  Google Scholar 

  13. Tran, E., Robbins, P. F. & Rosenberg, S. A. ‘Final common pathway’ of human cancer immunotherapy: targeting random somatic mutations. Nat. Immunol. 18, 255–262 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Haen, S. P., Loffler, M. W., Rammensee, H. G. & Brossart, P. Towards new horizons: characterization, classification and implications of the tumour antigenic repertoire. Nat. Rev. Clin. Oncol. 17, 595–610 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  15. Lu, Y. C. et al. Mutated PPP1R3B is recognized by T cells used to treat a melanoma patient who experienced a durable complete tumor regression. J. Immunol. 190, 6034–6042 (2013).

    Article  CAS  PubMed  Google Scholar 

  16. Kalaora, S. et al. Combined analysis of antigen presentation and T-cell recognition reveals restricted immune responses in melanoma. Cancer Discov. 8, 1366–1375 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Lawrence, M. S. et al. Mutational heterogeneity in cancer and the search for new cancer-associated genes. Nature 499, 214–218 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Schumacher, T. N. & Schreiber, R. D. Neoantigens in cancer immunotherapy. Science 348, 69–74 (2015).

    Article  CAS  PubMed  Google Scholar 

  19. Yamamoto, T. N., Kishton, R. J. & Restifo, N. P. Developing neoantigen-targeted T cell-based treatments for solid tumors. Nat. Med. 25, 1488–1499 (2019).

    Article  CAS  PubMed  Google Scholar 

  20. Wolf, Y. et al. UVB-induced tumor heterogeneity diminishes immune response in melanoma. Cell 179, 219–235.e21 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Reuben, A. et al. Genomic and immune heterogeneity are associated with differential responses to therapy in melanoma. NPJ Genom. Med. 2, 10 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  22. Lin, Z. et al. Intratumor heterogeneity correlates with reduced immune activity and worse survival in melanoma patients. Front. Oncol. 10, 596493 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  23. Williams, J. B. et al. Tumor heterogeneity and clonal cooperation influence the immune selection of IFN-γ-signaling mutant cancer cells. Nat. Commun. 11, 602 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Schiavetti, F., Thonnard, J., Colau, D., Boon, T. & Coulie, P. G. A human endogenous retroviral sequence encoding an antigen recognized on melanoma by cytolytic T lymphocytes. Cancer Res. 62, 5510–5516 (2002).

    CAS  PubMed  Google Scholar 

  25. Kalaora, S. et al. Identification of bacteria-derived HLA-bound peptides in melanoma. Nature 592, 138–143 (2021).

    Article  CAS  PubMed  Google Scholar 

  26. Bach, E. A., Aguet, M. & Schreiber, R. D. The IFNγ receptor: a paradigm for cytokine receptor signaling. Annu. Rev. Immunol. 15, 563–591 (1997).

    Article  CAS  PubMed  Google Scholar 

  27. Paucker, K., Henle, W. & Cantell, K. Quantitative studies on viral interference in suspended L cells. 3. Effect of interfering viruses and interferon on growth rate of cells. Virology 17, 324–334 (1962).

    Article  CAS  PubMed  Google Scholar 

  28. Sucker, A. et al. Acquired IFNγ resistance impairs anti-tumor immunity and gives rise to T-cell-resistant melanoma lesions. Nat. Commun. 8, 15440 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Cole, K. E. et al. Interferon-inducible T cell α chemoattractant (I-TAC): a novel non-ELR CXC chemokine with potent activity on activated T cells through selective high affinity binding to CXCR3. J. Exp. Med. 187, 2009–2021 (1998).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Farber, J. M. A macrophage messenger-RNA selectively induced by γ-interferon encodes a member of the platelet factor-IV family of cytokines. Proc. Natl Acad. Sci. USA 87, 5238–5242 (1990).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Luster, A. D., Unkeless, J. C. & Ravetch, J. V. γ-Interferon transcriptionally regulates an early-response gene containing homology to platelet proteins. Nature 315, 672–676 (1985).

    Article  CAS  PubMed  Google Scholar 

  32. Basham, T. Y. & Merigan, T. C. Recombinant interferon-γ increases HLA-DR synthesis and expression. J. Immunol. 130, 1492–1494 (1983).

    CAS  PubMed  Google Scholar 

  33. King, D. P. & Jones, P. P. Induction of Ia and H-2 antigens on a macrophage cell line by immune interferon. J. Immunol. 131, 315–318 (1983).

    CAS  PubMed  Google Scholar 

  34. Kalaora, S. et al. Immunoproteasome expression is associated with better prognosis and response to checkpoint therapies in melanoma. Nat. Commun. 11, 896 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Benci, J. L. et al. Tumor interferon signaling regulates a multigenic resistance program to immune checkpoint blockade. Cell 167, 1540–1554.e12 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Zaretsky, J. M. et al. Mutations associated with acquired resistance to PD-1 blockade in melanoma. N. Engl. J. Med. 375, 819–829 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Manguso, R. T. et al. In vivo CRISPR screening identifies Ptpn2 as a cancer immunotherapy target. Nature 547, 413–418 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Patel, S. J. et al. Identification of essential genes for cancer immunotherapy. Nature 548, 537–542 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Pan, D. et al. A major chromatin regulator determines resistance of tumor cells to T cell-mediated killing. Science 359, 770–775 (2018). Together with Manguso et al. (2017) and Patel et al. (2017), this paper describes CRISPR screens that identify tumour-intrinsic mechanisms of resistance to immunotherapy using in vitro co-culture of melanoma cells and tumour-specific T cells.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. D’Urso, C. M. et al. Lack of HLA class I antigen expression by cultured melanoma cells FO-1 due to a defect in B2m gene expression. J. Clin. Invest. 87, 284–292 (1991).

    Article  PubMed  PubMed Central  Google Scholar 

  41. Sucker, A. et al. Genetic evolution of T-cell resistance in the course of melanoma progression. Clin. Cancer Res. 20, 6593–6604 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Restifo, N. P. et al. Loss of functional β2-microglobulin in metastatic melanomas from five patients receiving immunotherapy. J. Natl Cancer Inst. 88, 100–108 (1996).

    Article  CAS  PubMed  Google Scholar 

  43. Sahin, U. et al. Personalized RNA mutanome vaccines mobilize poly-specific therapeutic immunity against cancer. Nature 547, 222–226 (2017).

    Article  CAS  PubMed  Google Scholar 

  44. Sade-Feldman, M. et al. Resistance to checkpoint blockade therapy through inactivation of antigen presentation. Nat. Commun. 8, 1136 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  45. Huang, L. et al. The RNA-binding protein MEX3B mediates resistance to cancer immunotherapy by downregulating HLA-A expression. Clin. Cancer Res. 24, 3366–3376 (2018).

    Article  CAS  PubMed  Google Scholar 

  46. Rodig, S. J. et al. MHC proteins confer differential sensitivity to CTLA-4 and PD-1 blockade in untreated metastatic melanoma. Sci. Transl. Med. 10, eaar3342 (2018).

    Article  PubMed  Google Scholar 

  47. Johnson, D. B. et al. Melanoma-specific MHC-II expression represents a tumour-autonomous phenotype and predicts response to anti-PD-1/PD-L1 therapy. Nat. Commun. 7, 10582 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Johnson, D. B. et al. Tumor-specific MHC-II expression drives a unique pattern of resistance to immunotherapy via LAG-3/FCRL6 engagement. JCI Insight 3, e120360 (2018).

    Article  PubMed Central  Google Scholar 

  49. Donia, M. et al. Aberrant expression of MHC class II in melanoma attracts inflammatory tumor-specific CD4+ T-cells, which dampen CD8+ T-cell antitumor reactivity. Cancer Res. 75, 3747–3759 (2015).

    Article  CAS  PubMed  Google Scholar 

  50. Ott, P. A. et al. An immunogenic personal neoantigen vaccine for patients with melanoma. Nature 547, 217–221 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Hu, Z. T. et al. Personal neoantigen vaccines induce persistent memory T cell responses and epitope spreading in patients with melanoma. Nat. Med. 27, 515–525 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Boni, A. et al. Selective BRAFV600E inhibition enhances T-cell recognition of melanoma without affecting lymphocyte function. Cancer Res. 70, 5213–5219 (2010).

    Article  CAS  PubMed  Google Scholar 

  53. Frederick, D. T. et al. BRAF inhibition is associated with enhanced melanoma antigen expression and a more favorable tumor microenvironment in patients with metastatic melanoma. Clin. Cancer Res. 19, 1225–1231 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Sapkota, B., Hill, C. E. & Pollack, B. P. Vemurafenib enhances MHC induction in BRAFV600E homozygous melanoma cells. Oncoimmunology 2, e22890 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  55. Acquavella, N. et al. Type I cytokines synergize with oncogene inhibition to induce tumor growth arrest. Cancer Immunol. Res. 3, 37–47 (2015).

    Article  CAS  PubMed  Google Scholar 

  56. Sumimoto, H., Imabayashi, F., Iwata, T. & Kawakami, Y. The BRAF–MAPK signaling pathway is essential for cancer-immune evasion in human melanoma cells. J. Exp. Med. 203, 1651–1656 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Peng, W. et al. Loss of PTEN promotes resistance to T cell-mediated immunotherapy. Cancer Discov. 6, 202–216 (2016).

    Article  CAS  PubMed  Google Scholar 

  58. Yaguchi, T. et al. Immune suppression and resistance mediated by constitutive activation of Wnt/β-catenin signaling in human melanoma cells. J. Immunol. 189, 2110–2117 (2012).

    Article  CAS  PubMed  Google Scholar 

  59. Spranger, S., Bao, R. Y. & Gajewski, T. F. Melanoma-intrinsic β-catenin signalling prevents anti-tumour immunity. Nature 523, 231–235 (2015).

    Article  CAS  PubMed  Google Scholar 

  60. Spranger, S., Dai, D., Horton, B. & Gajewski, T. F. Tumor-residing Batf3 dendritic cells are required for effector T cell trafficking and adoptive T cell therapy. Cancer Cell 31, 711–723.e4 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Chen, C. F. et al. ATR mutations promote the growth of melanoma tumors by modulating the immune microenvironment. Cell Rep. 18, 2331–2342 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Mehta, A. et al. Immunotherapy resistance by inflammation-induced dedifferentiation. Cancer Discov. 8, 935–943 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Lee, J. H. et al. Transcriptional downregulation of MHC class I and melanoma de-differentiation in resistance to PD-1 inhibition. Nat. Commun. 11, 1897 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Paijens, S. T., Vledder, A., de Bruyn, M. & Nijman, H. W. Tumor-infiltrating lymphocytes in the immunotherapy era. Cell Mol. Immunol. 18, 842–859 (2021).

    Article  CAS  PubMed  Google Scholar 

  65. Tirosh, I. et al. Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq. Science 352, 189–196 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Waldman, A. D., Fritz, J. M. & Lenardo, M. J. A guide to cancer immunotherapy: from T cell basic science to clinical practice. Nat. Rev. Immunol. 20, 651–668 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Ribas, A. & Wolchok, J. D. Cancer immunotherapy using checkpoint blockade. Science 359, 1350–1355 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Yang, R. et al. Galectin-9 interacts with PD-1 and TIM-3 to regulate T cell death and is a target for cancer immunotherapy. Nat. Commun. 12, 832 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Wolf, Y., Anderson, A. C. & Kuchroo, V. K. TIM3 comes of age as an inhibitory receptor. Nat. Rev. Immunol. 20, 173–185 (2020).

    Article  CAS  PubMed  Google Scholar 

  70. Sade-Feldman, M. et al. Defining T cell states associated with response to checkpoint immunotherapy in melanoma. Cell 176, 404 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. da Silva, I. P. et al. Reversal of NK-cell exhaustion in advanced melanoma by Tim-3 blockade. Cancer Immunol. Res. 2, 410–422 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  72. Fourcade, J. et al. CD8+ T cells specific for tumor antigens can be rendered dysfunctional by the tumor microenvironment through upregulation of the inhibitory receptors BTLA and PD-1. Cancer Res. 72, 887–896 (2012).

    Article  CAS  PubMed  Google Scholar 

  73. Qin, S. et al. Novel immune checkpoint targets: moving beyond PD-1 and CTLA-4. Mol. Cancer 18, 155 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  74. Quandt, D., Fiedler, E., Boettcher, D., Marsch, W. & Seliger, B. B7-H4 expression in human melanoma: its association with patients’ survival and antitumor immune response. Clin. Cancer Res. 17, 3100–3111 (2011).

    Article  CAS  PubMed  Google Scholar 

  75. Kuklinski, L. F. et al. VISTA expression on tumor-infiltrating inflammatory cells in primary cutaneous melanoma correlates with poor disease-specific survival. Cancer Immunol. Immunother. 67, 1113–1121 (2018).

    Article  CAS  PubMed  Google Scholar 

  76. Young, A. et al. Targeting adenosine in BRAF-mutant melanoma reduces tumor growth and metastasis. Cancer Res. 77, 4684–4696 (2017).

    Article  CAS  PubMed  Google Scholar 

  77. Lee, Y. H. et al. Inhibition of the B7-H3 immune checkpoint limits tumor growth by enhancing cytotoxic lymphocyte function. Cell Res. 27, 1034–1045 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Lee, H. et al. Targeting NK cells to enhance melanoma response to immunotherapies. Cancers (Basel) 13, e1363 (2021).

    Article  Google Scholar 

  79. Zhou, P. et al. In vivo discovery of immunotherapy targets in the tumour microenvironment. Nature 506, 52–57 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Shifrut, E. et al. Genome-wide CRISPR screens in primary human T cells reveal key regulators of immune function. Cell 175, 1958–1971.e15 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Cabrita, R. et al. Tertiary lymphoid structures improve immunotherapy and survival in melanoma. Nature 577, 561–565 (2020).

    Article  CAS  PubMed  Google Scholar 

  82. Helmink, B. A. et al. B cells and tertiary lymphoid structures promote immunotherapy response. Nature 577, 549–555 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Ferrari de Andrade, L. et al. Antibody-mediated inhibition of MICA and MICB shedding promotes NK cell-driven tumor immunity. Science 359, 1537–1542 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. He, W. et al. Naturally activated Vγ4 γδ T cells play a protective role in tumor immunity through expression of eomesodermin. J. Immunol. 185, 126–133 (2010).

    Article  CAS  PubMed  Google Scholar 

  85. Exley, M. A. et al. Adoptive transfer of invariant NKT cells as immunotherapy for advanced melanoma: a phase I clinical trial. Clin. Cancer Res. 23, 3510–3519 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  86. Petley, E. V. et al. MAIT cells regulate NK cell-mediated tumor immunity. Nat. Commun. 12, 4746 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Yan, J. et al. MAIT cells promote tumor initiation, growth, and metastases via tumor MR1. Cancer Discov. 10, 124–141 (2020).

    Article  CAS  PubMed  Google Scholar 

  88. Miracco, C. et al. Utility of tumour-infiltrating CD25+FOXP3+ regulatory T cell evaluation in predicting local recurrence in vertical growth phase cutaneous melanoma. Oncol. Rep. 18, 1115–1122 (2007).

    PubMed  Google Scholar 

  89. Gambichler, T., Bindsteiner, M., Hoxtermann, S., Terras, S. & Kreuter, A. Circulating CD4+CD25highCD127low regulatory T cells are an independent predictor of advanced melanoma. Pigment. Cell Melanoma Res. 26, 280–283 (2013).

    Article  CAS  PubMed  Google Scholar 

  90. Halaby, M. J. et al. GCN2 drives macrophage and MDSC function and immunosuppression in the tumor microenvironment. Sci. Immunol. 4, eaax8189 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Ziani, L. et al. Melanoma-associated fibroblasts decrease tumor cell susceptibility to NK cell-mediated killing through matrix-metalloproteinases secretion. Oncotarget 8, 19780–19794 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  92. Huse, M. Mechanical forces in the immune system. Nat. Rev. Immunol. 17, 679–690 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  93. Winkler, J., Abisoye-Ogunniyan, A., Metcalf, K. J. & Werb, Z. Concepts of extracellular matrix remodelling in tumour progression and metastasis. Nat. Commun. 11, 5120 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  94. Kaur, A. et al. Remodeling of the collagen matrix in aging skin promotes melanoma metastasis and affects immune cell motility. Cancer Discov. 9, 64–81 (2019).

    Article  CAS  PubMed  Google Scholar 

  95. Feng, M. et al. Phagocytosis checkpoints as new targets for cancer immunotherapy. Nat. Rev. Cancer 19, 568–586 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  96. Chang, C. H. et al. Posttranscriptional control of T cell effector function by aerobic glycolysis. Cell 153, 1239–1251 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  97. Vander Heiden, M. G., Cantley, L. C. & Thompson, C. B. Understanding the Warburg effect: the metabolic requirements of cell proliferation. Science 324, 1029–1033 (2009).

    Article  Google Scholar 

  98. Swamy, M. et al. Glucose and glutamine fuel protein O-GlcNAcylation to control T cell self-renewal and malignancy. Nat. Immunol. 17, 712–720 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  99. Munn, D. H. et al. Inhibition of T cell proliferation by macrophage tryptophan catabolism. J. Exp. Med. 189, 1363–1372 (1999).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  100. Munn, D. H. et al. GCN2 kinase in T cells mediates proliferative arrest and anergy induction in response to indoleamine 2,3-dioxygenase. Immunity 22, 633–642 (2005).

    Article  CAS  PubMed  Google Scholar 

  101. Sundrud, M. S. et al. Halofuginone inhibits TH17 cell differentiation by activating the amino acid starvation response. Science 324, 1334–1338 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  102. Husain, Z., Huang, Y., 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).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  104. Chang, C. H. et al. Metabolic competition in the tumor microenvironment is a driver of cancer progression. Cell 162, 1229–1241 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  105. Stearn, E. W., Sturdivant, B. F. & Stearn, A. E. The life history of a micro-parasite isolated from carcinomatous growths. Proc. Natl Acad. Sci. USA 11, 662–669 (1925).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  106. Nejman, D. et al. The human tumor microbiome is composed of tumor type-specific intracellular bacteria. Science 368, 973–980 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  107. Schwabe, R. F. & Jobin, C. The microbiome and cancer. Nat. Rev. Cancer 13, 800–812 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  108. Mehta, R. S. et al. Association of dietary patterns with risk of colorectal cancer subtypes classified by fusobacterium nucleatum in tumor tissue. JAMA Oncol. 3, 921–927 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  109. Garrett, W. S. Cancer and the microbiota. Science 348, 80–86 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  110. Geller, L. T. et al. Potential role of intratumor bacteria in mediating tumor resistance to the chemotherapeutic drug gemcitabine. Science 357, 1156–1160 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  111. Yu, T. et al. Fusobacterium nucleatum promotes chemoresistance to colorectal cancer by modulating autophagy. Cell 170, 548–563.e16 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  112. Chaput, N. et al. Baseline gut microbiota predicts clinical response and colitis in metastatic melanoma patients treated with ipilimumab. Ann. Oncol. 30, 2012 (2019).

    Article  CAS  PubMed  Google Scholar 

  113. Frankel, A. E. et al. Metagenomic shotgun sequencing and unbiased metabolomic profiling identify specific human gut microbiota and metabolites associated with immune checkpoint therapy efficacy in melanoma patients. Neoplasia 19, 848–855 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  114. Gopalakrishnan, V. et al. Gut microbiome modulates response to anti-PD-1 immunotherapy in melanoma patients. Science 359, 97–103 (2018).

    Article  CAS  PubMed  Google Scholar 

  115. Matson, V. et al. The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients. Science 359, 104–108 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  116. Routy, B. et al. Gut microbiome influences efficacy of PD-1-based immunotherapy against epithelial tumors. Science 359, 91–97 (2018). Together with Gopalakrishnan et al. (2018) and Matson et al. (2018), this paper demonstrates how the diversity and composition of gut microbiome can influence the response to ICIs in melanoma and epithelial tumours. The papers also present mouse models for faecal microbiota transplant.

    Article  CAS  PubMed  Google Scholar 

  117. Sivan, A. et al. Commensal Bifidobacterium promotes antitumor immunity and facilitates anti-PD-L1 efficacy. Science 350, 1084–1089 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  118. Vetizou, M. et al. Anticancer immunotherapy by CTLA-4 blockade relies on the gut microbiota. Science 350, 1079–1084 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  119. Baruch, E. N. et al. Fecal microbiota transplant promotes response in immunotherapy-refractory melanoma patients. Science 371, 602–609 (2021).

    Article  CAS  PubMed  Google Scholar 

  120. Davar, D. et al. Fecal microbiota transplant overcomes resistance to anti-PD-1 therapy in melanoma patients. Science 371, 595–602 (2021). Together with Baruch et al. (2021), this paper demonstrates clinical benefits to patients with melanoma of faecal microbiota transplantation to overcome ICI resistance.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  121. Uribe-Herranz, M. et al. Gut microbiota modulates adoptive cell therapy via CD8α dendritic cells and IL-12. JCI Insight. 3, e94952 (2018).

    Article  PubMed Central  Google Scholar 

  122. Tanoue, T. et al. A defined commensal consortium elicits CD8 T cells and anti-cancer immunity. Nature 565, 600–605 (2019).

    Article  CAS  PubMed  Google Scholar 

  123. Poore, G. D. et al. Microbiome analyses of blood and tissues suggest cancer diagnostic approach. Nature 579, 567–574 (2020). Together with Nejman et al. (2020) and Geller et al. (2017), this paper demonstrates the presence of bacteria in human tumour samples using experimental or computational methods. Geller et al. (2017) also present a bacteria-driven resistance mechanism to chemotherapy.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  124. Zhu, G. et al. Intratumour microbiome associated with the infiltration of cytotoxic CD8+ T cells and patient survival in cutaneous melanoma. Eur. J. Cancer 151, 25–34 (2021).

    Article  CAS  PubMed  Google Scholar 

  125. Pushalkar, S. et al. The pancreatic cancer microbiome promotes oncogenesis by induction of innate and adaptive immune suppression. Cancer Discov. 8, 403–416 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  126. Gur, C. et al. Binding of the Fap2 protein of Fusobacterium nucleatum to human inhibitory receptor TIGIT protects tumors from immune cell attack. Immunity 42, 344–355 (2015). This study presents mechanisms by which F. nucleatum evades the immune response in the melanoma TME.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  127. Hamada, T. et al. Fusobacterium nucleatum in colorectal cancer relates to immune response differentially by tumor microsatellite instability status. Cancer Immunol. Res. 6, 1327–1336 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  128. Thomas, N. E. et al. Tumor-infiltrating lymphocyte grade in primary melanomas is independently associated with melanoma-specific survival in the population-based genes, environment and melanoma study. J. Clin. Oncol. 31, 4252–4259 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  129. Chen, P. L. et al. Analysis of immune signatures in longitudinal tumor samples yields insight into biomarkers of response and mechanisms of resistance to immune checkpoint blockade. Cancer Discov. 6, 827–837 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  130. Tumeh, P. C. et al. PD-1 blockade induces responses by inhibiting adaptive immune resistance. Nature 515, 568–571 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  131. Riaz, N. et al. Tumor and microenvironment evolution during immunotherapy with nivolumab. Cell 171, 934–949.e16 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  132. Rooney, M. S., Shukla, S. A., Wu, C. J., Getz, G. & Hacohen, N. Molecular and genetic properties of tumors associated with local immune cytolytic activity. Cell 160, 48–61 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  133. Sade-Feldman, M. et al. Defining T cell states associated with response to checkpoint immunotherapy in melanoma. Cell 175, 998–1013.e20 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  134. Yost, K. E. et al. Clonal replacement of tumor-specific T cells following PD-1 blockade. Nat. Med. 25, 1251–1259 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  135. Topalian, S. L. et al. Safety, activity, and immune correlates of anti-PD-1 antibody in cancer. N. Engl. J. Med. 366, 2443–2454 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  136. Wolchok, J. D. et al. Nivolumab plus ipilimumab in advanced melanoma. N. Engl. J. Med. 369, 122–133 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  137. Robert, C. et al. Nivolumab in previously untreated melanoma without BRAF mutation. N. Engl. J. Med. 372, 320–330 (2015).

    Article  CAS  PubMed  Google Scholar 

  138. Grasso, C. S. et al. Conserved interferon-γ signaling drives clinical response to immune checkpoint blockade therapy in melanoma. Cancer Cell 38, 500–515.e3 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  139. Ayers, M. et al. IFN-γ-related mRNA profile predicts clinical response to PD-1 blockade. J. Clin. Inves. 127, 2930–2940 (2017).

    Article  Google Scholar 

  140. Snyder, A. et al. Genetic basis for clinical response to CTLA-4 blockade in melanoma. N. Engl. J. Med. 371, 2189–2199 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  141. Spranger, S. et al. Density of immunogenic antigens does not explain the presence or absence of the T-cell-inflamed tumor microenvironment in melanoma. Proc. Natl Acad. Sci. USA 113, E7759–E7768 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  142. Hugo, W. et al. Genomic and transcriptomic features of response to anti-PD-1 therapy in metastatic melanoma. Cell 165, 35–44 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  143. Ribas, A. et al. Combined BRAF and MEK inhibition with PD-1 blockade immunotherapy in BRAF-mutant melanoma. Nat. Med. 25, 1319–1319 (2019).

    Article  CAS  PubMed  Google Scholar 

  144. Ascierto, P. A. et al. Dabrafenib, trametinib and pembrolizumab or placebo in BRAF-mutant melanoma. Nat. Med. 25, 941–946 (2019).

    Article  CAS  PubMed  Google Scholar 

  145. Sullivan, R. J. et al. Atezolizumab plus cobimetinib and vemurafenib in BRAF-mutated melanoma patients. Nat. Med. 25, 929–935 (2019).

    Article  CAS  PubMed  Google Scholar 

  146. Ribas, A. et al. Oncolytic virotherapy promotes intratumoral T cell infiltration and improves anti-PD-1 immunotherapy. Cell 170, 1109–1119 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  147. Singh, M. et al. Intratumoral CD40 activation and checkpoint blockade induces T cell-mediated eradication of melanoma in the brain. Nat. Commun. 8, 1447 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  148. Sahin, U. et al. An RNA vaccine drives immunity in checkpoint-inhibitor-treated melanoma. Nature 585, 107–112 (2020). Together with Sahin et al. (2017), Ott et al. (2017) and Hu et al. (2021), this paper describes the use of peptide and RNA vaccines with mutated antigens or tumour-associated antigens in patients with melanoma. The success of these studies demonstrates the power of selecting the right antigens and using them for vaccines.

    Article  CAS  PubMed  Google Scholar 

  149. Apetoh, L. et al. Toll-like receptor 4-dependent contribution of the immune system to anticancer chemotherapy and radiotherapy. Nat. Med. 13, 1050–1059 (2007).

    Article  CAS  PubMed  Google Scholar 

  150. Twyman-Saint Victor, C. et al. Radiation and dual checkpoint blockade activate non-redundant immune mechanisms in cancer. Nature 520, 373–377 (2015).

    Article  CAS  PubMed  Google Scholar 

  151. Morgan, R. A. et al. Cancer regression in patients after transfer of genetically engineered lymphocytes. Science 314, 126–129 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  152. Stadtmauer, E. A. et al. CRISPR-engineered T cells in patients with refractory cancer. Science. 367, eaba7365 (2020).

    Article  CAS  PubMed  Google Scholar 

  153. Wargo, J. A. Modulating gut microbes. Science 369, 1302–1303 (2020).

    Article  CAS  PubMed  Google Scholar 

  154. Harlin, H. et al. Chemokine expression in melanoma metastases associated with CD8+ T-cell recruitment. Cancer Res. 69, 3077–3085 (2009).

    Article  CAS  PubMed  Google Scholar 

  155. Rosenberg, S. A. IL-2: the first effective immunotherapy for human cancer. J. Immunol. 192, 5451–5458 (2014).

    Article  CAS  PubMed  Google Scholar 

  156. Zhang, S. et al. Systemic interferon-γ increases MHC class I expression and T-cell infiltration in cold tumors: results of a phase 0 clinical trial. Cancer Immunol. Res. 7, 1237–1243 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  157. Sun, Z. et al. A next-generation tumor-targeting IL-2 preferentially promotes tumor-infiltrating CD8+ T-cell response and effective tumor control. Nat. Commun. 10, 3874 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  158. Ribas, A. et al. SD-101 in combination with pembrolizumab in advanced melanoma: results of a phase Ib, multicenter study. Cancer Discov. 8, 1250–1257 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  159. Andre, P. et al. Anti-NKG2A mAb is a checkpoint inhibitor that promotes anti-tumor immunity by unleashing both T and NK cells. Cell 175, 1731–1743.e13 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  160. Godfrey, D. I., Le Nours, J., Andrews, D. M., Uldrich, A. P. & Rossjohn, J. Unconventional T cell targets for cancer immunotherapy. Immunity 48, 453–473 (2018).

    Article  CAS  PubMed  Google Scholar 

  161. Klebanoff, C. A., Rosenberg, S. A. & Restifo, N. P. Prospects for gene-engineered T cell immunotherapy for solid cancers. Nat. Med. 22, 26–36 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  162. Liu, E. L. et al. Use of CAR-transduced natural killer cells in CD19-positive lymphoid tumors. N. Engl. J. Med. 382, 545–553 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  163. Klichinsky, M. et al. Human chimeric antigen receptor macrophages for cancer immunotherapy. Nat. Biotechnol. 38, 947–953 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  164. Cho, J. H. et al. Engineering advanced logic and distributed computing in human CAR immune cells. Nat. Commun. 12, 792 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  165. Kalaora, S. et al. Use of HLA peptidomics and whole exome sequencing to identify human immunogenic neo-antigens. Oncotarget 7, 5110–5117 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  166. Bassani-Sternberg, M. et al. Direct identification of clinically relevant neoepitopes presented on native human melanoma tissue by mass spectrometry. Nat. Commun. 7, 13404 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  167. Pritchard, A. L. et al. Exploration of peptides bound to MHC class I molecules in melanoma. Pigment. Cell Melanoma Res. 28, 281–294 (2015).

    Article  CAS  PubMed  Google Scholar 

  168. Robbins, P. F. et al. Mining exomic sequencing data to identify mutated antigens recognized by adoptively transferred tumor-reactive T cells. Nat. Med. 19, 747–752 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  169. Gros, A. et al. Prospective identification of neoantigen-specific lymphocytes in the peripheral blood of melanoma patients. Nat. Med. 22, 433–438 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  170. Prickett, T. D. et al. Durable complete response from metastatic melanoma after transfer of autologous T cells recognizing 10 mutated tumor antigens. Cancer Immunol. Res. 4, 669–678 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  171. Lennerz, V. et al. The response of autologous T cells to a human melanoma is dominated by mutated neoantigens. Proc. Natl Acad. Sci. USA 102, 16013–16018 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  172. Linnemann, C. et al. High-throughput epitope discovery reveals frequent recognition of neo-antigens by CD4+ T cells in human melanoma. Nat. Med. 21, 81–85 (2015).

    Article  CAS  PubMed  Google Scholar 

  173. Andersen, R. S. et al. Dissection of T-cell antigen specificity in human melanoma. Cancer Res. 72, 1642–1650 (2012).

    Article  CAS  PubMed  Google Scholar 

  174. Kvistborg, P. et al. TIL therapy broadens the tumor-reactive CD8+ T cell compartment in melanoma patients. Oncoimmunology 1, 409–418 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  175. Cohen, C. J. et al. Isolation of neoantigen-specific T cells from tumor and peripheral lymphocytes. J. Clin. Invest. 125, 3981–3991 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  176. The Human Microbiome Project Consortium. A framework for human microbiome research. Nature 486, 215–221 (2012).

    Article  Google Scholar 

  177. DeSantis, T. Z. et al. Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl. Env. Microbiol. 72, 5069–5072 (2006).

    Article  CAS  Google Scholar 

  178. Quast, C. et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 41, D590–D596 (2013).

    Article  CAS  PubMed  Google Scholar 

  179. Cole, J. R. et al. Ribosomal Database Project: data and tools for high throughput rRNA analysis. Nucleic Acids Res. 42, D633–D642 (2014).

    Article  CAS  PubMed  Google Scholar 

  180. Zhang, J. et al. Evaluation of different 16S rRNA gene V regions for exploring bacterial diversity in a eutrophic freshwater lake. Sci. Total. Env. 618, 1254–1267 (2018).

    Article  CAS  Google Scholar 

  181. Bashiardes, S., Zilberman-Schapira, G. & Elinav, E. Use of metatranscriptomics in microbiome research. Bioinform Biol. Insights 10, 19–25 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  182. Seng, P. et al. Ongoing revolution in bacteriology: routine identification of bacteria by matrix-assisted laser desorption ionization time-of-flight mass spectrometry. Clin. Infect. Dis. 49, 543–551 (2009).

    Article  CAS  PubMed  Google Scholar 

  183. Clark, A. E., Kaleta, E. J., Arora, A. & Wolk, D. M. Matrix-assisted laser desorption ionization-time of flight mass spectrometry: a fundamental shift in the routine practice of clinical microbiology. Clin. Microbiol. Rev. 26, 547–603 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

This work was supported by the Intramural Research Programs of the National Cancer Institute. Y.S. is supported by the Israel Science Foundation grant No. 696/17, the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. 754282), the ERC (CoG-770854), the Melanoma Research Alliance (MRA) (#622106), a grant from the CNIO-Weizmann Institute–Ramon Areces Foundation cooperation program, International Collaboration Grant from the Jacki and Bruce Barron Cancer Research Scholars’ Program, a partnership of the ICRF and City of Hope, as supported by The Harvey L. Miller Family Foundation, the Minerva Foundation with funding from the Federal German Ministry for Education and Research, the Rising Tide Foundation, the Henry Chanoch Krenter Institute for Biomedical Imaging and Genomics, the Estate of Alice Schwarz-Gardos, the Estate of John Hunter, the Knell Family, the Peter and Patricia Gruber Award, and the Hamburger Family. J.A.W. is supported by generous philanthropic contributions to the University of Texas MD Anderson Moon Shots Program for support of tumour-line generation.

Author information

Author notes

  1. These authors contributed equally: Shelly Kalaora, Adi Nagler.

Authors and Affiliations

  1. Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel

    Shelly Kalaora, Adi Nagler & Yardena Samuels

  2. Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

    Jennifer A. Wargo

  3. Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

    Jennifer A. Wargo

Authors
  1. Shelly Kalaora
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Adi Nagler
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jennifer A. Wargo
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yardena Samuels
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors researched data for the article, contributed substantially to discussion of the content, wrote the article, and reviewed and/or edited the manuscript before submission.

Corresponding author

Correspondence to Yardena Samuels.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Reviews Cancer thanks Genevieve Boland and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Publisher’s note

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

Related links

Cancer Antigenic Peptide Database: https://caped.icp.ucl.ac.be/

Glossary

Immune checkpoint

An immune system pathway that acts as a ‘gatekeeper’ of the immune response. Checkpoint receptors are located on the immune cell surface and play a critical role in regulating the balance between immune cell activation and inhibition, resulting in self-tolerance and prevention of the immune system from attacking self-cells indiscriminately.

Tumour-infiltrating lymphocytes

(TILs). Lymphocytes comprising mainly CD8+ and CD4+ T cells, but also containing B cells and natural killer cells (NK cells).

Natural killer T cells

(NKT cells). Members of the family of unconventional T cells that recognize glycolipid antigens in the context of the non-polymorphic major histocompatibility complex class I (MHC-I)-like molecule CD1D. NKT cells are characterized by their capacity to rapidly produce a large amount of immunoregulatory cytokines and may play a role in antitumour immunity, particularly via their secretion of interferon-γ (IFNγ), which cross-activates natural killer cells (NK cells).

Dendritic cells

(DCs). Antigen-presenting cells (APCs) that present tumour antigens to CD4+ and CD8+ T cells. Antigen presentation is done efficiently only by mature DCs. DC maturation is affected by different factors in the tumour microenvironment (TME), for example tumour-associated macrophages (TAMs) limit DC maturation and are therefore able to evade the host immune response. In addition, DCs are mediators of immune tolerance and regulatory T cell (Treg cell) expansion.

Natural killer cells

(NK cells). NK cell activation relies on signals derived from multiple activating and inhibitory receptors and does not require antigen specificity. NK cell function is partially complementary to T cells, as NK cells target and lyse major histocompatibility complex class I (MHC-I)-deficient cells and, therefore, play an essential role in cancer immunosurveillance.

Tumour immuno-editing

Immuno-editing that occurs during tumour progression to allow the immune system to initially constrain but later promote tumour development. Initially, the immune system recognizes the transformed cells and eliminates them. Tumour cells that are not eliminated can progress to an equilibrium phase. Edited tumours can then escape the immune system and exhibit unrestrained growth.

Pattern-recognition receptors

Receptors that are expressed by innate immune cells and recognize molecules expressed on the surface of pathogens, apoptotic host cells and damaged senescent cells. These receptors induce immuno-protective effects, such as anti-infection and antitumour effects, and participate in initiation of the immune response.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kalaora, S., Nagler, A., Wargo, J.A. et al. Mechanisms of immune activation and regulation: lessons from melanoma. Nat Rev Cancer 22, 195–207 (2022). https://doi.org/10.1038/s41568-022-00442-9

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41568-022-00442-9

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