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Annual Review of Immunology

Volume 40, 2022

Resistance Mechanisms to Anti-PD Cancer Immunotherapy

Abstract

The transformative success of antibodies targeting the PD-1 (programmed death 1)/B7-H1 (B7 homolog 1) pathway (anti-PD therapy) has revolutionized cancer treatment. However, only a fraction of patients with solid tumors and some hematopoietic malignancies respond to anti-PD therapy, and the reason for failure in other patients is less known. By dissecting the mechanisms underlying this resistance, current studies reveal that the tumor microenvironment is a major location for resistance to occur. Furthermore, the resistance mechanisms appear to be highly heterogeneous. Here, we discuss recent human cancer data identifying mechanisms of resistance to anti-PD therapy. We review evidence for immune-based resistance mechanisms such as loss of neoantigens, defects in antigen presentation and interferon signaling, immune inhibitory molecules, and exclusion of T cells. We also review the clinical evidence for emerging mechanisms of resistance to anti-PD therapy, such as alterations in metabolism, microbiota, and epigenetics. Finally, we discuss strategies to overcome anti-PD therapy resistance and emphasize the need to develop additional immunotherapies based on the concept of normalization cancer immunotherapy.

Keyword(s): anti-PD-1/PD-L1 therapy, immunotherapy resistance, normalization cancer immunotherapy, PD-1/B7-H1
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/content/journals/10.1146/annurev-immunol-070621-030155
2022-04-26
2024-04-28
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Literature Cited

  1. 1. 
    Waterhouse P, Penninger JM, Timms E, Wakeham A, Shahinian A et al. 1995. Lymphoproliferative disorders with early lethality in mice deficient in Ctla-4. Science 270:985–88
     [Google Scholar]
  2. 2. 
    Leach DR, Krummel MF, Allison JP. 1996. Enhancement of antitumor immunity by CTLA-4 blockade. Science 271:1734–36
     [Google Scholar]
  3. 3. 
    Alderson MR, Smith CA, Tough TW, Davis-Smith T, Armitage RJ et al. 1994. Molecular and biological characterization of human 4–1BB and its ligand. Eur. J. Immunol. 24:2219–27
     [Google Scholar]
  4. 4. 
    Melero I, Shuford WW, Newby SA, Aruffo A, Ledbetter JA et al. 1997. Monoclonal antibodies against the 4–1BB T-cell activation molecule eradicate established tumors. Nat. Med. 3:682–85
     [Google Scholar]
  5. 5. 
    Dong H, Zhu G, Tamada K, Chen L 1999. B7-H1, a third member of the B7 family, co-stimulates T-cell proliferation and interleukin-10 secretion. Nat. Med. 5:1365–69
     [Google Scholar]
  6. 6. 
    Dong H, Strome SE, Salomao DR, Tamura H, Hirano F et al. 2002. Tumor-associated B7-H1 promotes T-cell apoptosis: a potential mechanism of immune evasion. Nat. Med. 8:793–800
     [Google Scholar]
  7. 7. 
    Ishida Y, Agata Y, Shibahara K, Honjo T 1992. Induced expression of PD-1, a novel member of the immunoglobulin gene superfamily, upon programmed cell death. EMBO J 11:3887–95
     [Google Scholar]
  8. 8. 
    Krummel MF, Allison JP. 1995. CD28 and CTLA-4 have opposing effects on the response of T cells to stimulation. J. Exp. Med. 182:459–65
     [Google Scholar]
  9. 9. 
    Freeman GJ, Long AJ, Iwai Y, Bourque K, Chernova T et al. 2000. Engagement of the PD-1 immunoinhibitory receptor by a novel B7 family member leads to negative regulation of lymphocyte activation. J. Exp. Med. 192:1027–34
     [Google Scholar]
  10. 10. 
    Chen L, Ashe S, Brady WA, Hellstrom I, Hellstrom KE et al. 1992. Costimulation of antitumor immunity by the B7 counterreceptor for the T lymphocyte molecules CD28 and CTLA-4. Cell 71:1093–102
     [Google Scholar]
  11. 11. 
    Ribas A, Wolchok JD. 2018. Cancer immunotherapy using checkpoint blockade. Science 359:1350–55
     [Google Scholar]
  12. 12. 
    Miller JF, Sadelain M. 2015. The journey from discoveries in fundamental immunology to cancer immunotherapy. Cancer Cell 27:439–49
     [Google Scholar]
  13. 13. 
    Zou W, Wolchok JD, Chen L. 2016. PD-L1 (B7-H1) and PD-1 pathway blockade for cancer therapy: mechanisms, response biomarkers, and combinations. Sci. Transl. Med. 8:328rv4
     [Google Scholar]
  14. 14. 
    Hodi FS, O'Day SJ, McDermott DF, Weber RW, Sosman JA et al. 2010. Improved survival with ipilimumab in patients with metastatic melanoma. N. Engl. J. Med. 363:711–23
     [Google Scholar]
  15. 15. 
    Topalian SL, Hodi FS, Brahmer JR, Gettinger SN, Smith DC et al. 2012. Safety, activity, and immune correlates of anti-PD-1 antibody in cancer. N. Engl. J. Med. 366:2443–54
     [Google Scholar]
  16. 16. 
    Topalian SL, Sznol M, McDermott DF, Kluger HM, Carvajal RD et al. 2014. Survival, durable tumor remission, and long-term safety in patients with advanced melanoma receiving nivolumab. J. Clin. Oncol. 32:1020–30
     [Google Scholar]
  17. 17. 
    Hanahan D, Weinberg RA. 2000. The hallmarks of cancer. Cell 100:57–70
     [Google Scholar]
  18. 18. 
    Vesely MD, Kershaw MH, Schreiber RD, Smyth MJ. 2011. Natural innate and adaptive immunity to cancer. Annu. Rev. Immunol. 29:235–71
     [Google Scholar]
  19. 19. 
    Hanahan D, Weinberg RA. 2011. Hallmarks of cancer: the next generation. Cell 144:646–74
     [Google Scholar]
  20. 20. 
    Taube JM, Anders RA, Young GD, Xu H, Sharma R et al. 2012. Colocalization of inflammatory response with B7-H1 expression in human melanocytic lesions supports an adaptive resistance mechanism of immune escape. Sci. Transl. Med. 4:127ra37
     [Google Scholar]
  21. 21. 
    Sznol M, Chen L. 2013. Antagonist antibodies to PD-1 and B7-H1 (PD-L1) in the treatment of advanced human cancer—response. Clin. Cancer Res. 19:5542
     [Google Scholar]
  22. 22. 
    Taube JM, Klein A, Brahmer JR, Xu H, Pan X et al. 2014. Association of PD-1, PD-1 ligands, and other features of the tumor immune microenvironment with response to anti-PD-1 therapy. Clin. Cancer Res. 20:5064–74
     [Google Scholar]
  23. 23. 
    Chen L, Han X 2015. Anti-PD-1/PD-L1 therapy of human cancer: past, present, and future. J. Clin. Investig. 125:3384–91
     [Google Scholar]
  24. 24. 
    Sanmamed MF, Chen L. 2018. A paradigm shift in cancer immunotherapy: from enhancement to normalization. Cell 175:313–26
     [Google Scholar]
  25. 25. 
    Vesely MD, Chen L. 2020. Normalization cancer immunotherapy for melanoma. J. Investig Dermatol. 140:1134–42
     [Google Scholar]
  26. 26. 
    Xin Yu J, Hodge JP, Oliva C, Neftelinov ST et al. 2020. Trends in clinical development for PD-1/PD-L1 inhibitors. Nat. Rev. Drug Discov. 19:163–64
     [Google Scholar]
  27. 27. 
    Upadhaya S, Neftelino ST, Hodge JP, Oliva C, Campbell JR, Yu JX. 2021. Combinations take centre stage in PD1/PDL1 inhibitor clinical trials. Nat. Rev. Drug Discov. 20:3168–69
     [Google Scholar]
  28. 28. 
    Hegde PS, Chen DS. 2020. Top 10 challenges in cancer immunotherapy. Immunity 52:17–35
     [Google Scholar]
  29. 29. 
    Kim TK, Herbst RS, Chen L. 2018. Defining and understanding adaptive resistance in cancer immunotherapy. Trends Immunol 39:624–31
     [Google Scholar]
  30. 30. 
    Sharma P, Hu-Lieskovan S, Wargo JA, Ribas A. 2017. Primary, adaptive, and acquired resistance to cancer immunotherapy. Cell 168:707–23
     [Google Scholar]
  31. 31. 
    Topalian SL, Drake CG, Pardoll DM. 2015. Immune checkpoint blockade: a common denominator approach to cancer therapy. Cancer Cell 27:450–61
     [Google Scholar]
  32. 32. 
    Kluger HM, Tawbi HA, Ascierto ML, Bowden M, Callahan MK et al. 2020. Defining tumor resistance to PD-1 pathway blockade: recommendations from the first meeting of the SITC Immunotherapy Resistance Taskforce. J. Immunother. Cancer 8:1e000398
     [Google Scholar]
  33. 33. 
    Schoenfeld AJ, Hellmann MD. 2020. Acquired resistance to immune checkpoint inhibitors. Cancer Cell 37:443–55
     [Google Scholar]
  34. 34. 
    Herbst RS, Soria JC, Kowanetz M, Fine GD, Hamid O et al. 2014. Predictive correlates of response to the anti-PD-L1 antibody MPDL3280A in cancer patients. Nature 515:563–67
     [Google Scholar]
  35. 35. 
    Chen DS, Mellman I. 2013. Oncology meets immunology: the cancer-immunity cycle. Immunity 39:11–10
     [Google Scholar]
  36. 36. 
    Han X, Vesely MD 2019. Stimulating T cells against cancer with agonist immunostimulatory monoclonal antibodies. Int. Rev. Cell Mol. Biol. 342:1–25
     [Google Scholar]
  37. 37. 
    Tumeh PC, Harview CL, Yearley JH, Shintaku IP, Taylor EJ et al. 2014. PD-1 blockade induces responses by inhibiting adaptive immune resistance. Nature 515:568–71
     [Google Scholar]
  38. 38. 
    Zhang Y, Chen L. 2016. Classification of advanced human cancers based on Tumor Immunity in the MicroEnvironment (TIME) for cancer immunotherapy. JAMA Oncol 2:1403–4
     [Google Scholar]
  39. 39. 
    Velcheti V, Schalper KA, Carvajal DE, Anagnostou VK, Syrigos KN et al. 2014. Programmed death ligand-1 expression in non-small cell lung cancer. Lab. Investig. 94:107–16
     [Google Scholar]
  40. 40. 
    Schalper KA, Carvajal-Hausdorf D, McLaughlin J, Altan M, Velcheti V et al. 2017. Differential expression and significance of PD-L1, IDO-1, and B7-H4 in human lung cancer. Clin. Cancer Res. 23:370–78
     [Google Scholar]
  41. 41. 
    Teng MW, Ngiow SF, Ribas A, Smyth MJ 2015. Classifying cancers based on T-cell infiltration and PD-L1. Cancer Res 75:2139–45
     [Google Scholar]
  42. 42. 
    O'Donnell JS, Teng MWL, Smyth MJ 2019. Cancer immunoediting and resistance to T cell-based immunotherapy. Nat. Rev. Clin. Oncol. 16:151–67
     [Google Scholar]
  43. 43. 
    Chen DS, Mellman I. 2017. Elements of cancer immunity and the cancer-immune set point. Nature 541:321–30
     [Google Scholar]
  44. 44. 
    Binnewies M, Roberts EW, Kersten K, Chan V, Fearon DF et al. 2018. Understanding the tumor immune microenvironment (TIME) for effective therapy. Nat. Med. 24:541–50
     [Google Scholar]
  45. 45. 
    Smyth MJ, Ngiow SF, Ribas A, Teng MW 2016. Combination cancer immunotherapies tailored to the tumour microenvironment. Nat. Rev. Clin. Oncol. 13:143–58
     [Google Scholar]
  46. 46. 
    Martin CJ, Datta A, Littlefield C, Kalra A, Chapron C et al. 2020. Selective inhibition of TGFβ1 activation overcomes primary resistance to checkpoint blockade therapy by altering tumor immune landscape. Sci. Transl. Med. 12:eaay8456
     [Google Scholar]
  47. 47. 
    Fankhauser M, Broggi MAS, Potin L, Bordry N, Jeanbart L et al. 2017. Tumor lymphangiogenesis promotes T cell infiltration and potentiates immunotherapy in melanoma. Sci. Transl. Med. 9:eaal4712
     [Google Scholar]
  48. 48. 
    McDermott DF, Huseni MA, Atkins MB, Motzer RJ, Rini BI et al. 2018. Clinical activity and molecular correlates of response to atezolizumab alone or in combination with bevacizumab versus sunitinib in renal cell carcinoma. Nat. Med. 24:749–57
     [Google Scholar]
  49. 49. 
    Joyce JA, Fearon DT. 2015. T cell exclusion, immune privilege, and the tumor microenvironment. Science 348:74–80
     [Google Scholar]
  50. 50. 
    Ford K, Hanley CJ, Mellone M, Szyndralewiez C, Heitz F et al. 2020. NOX4 inhibition potentiates immunotherapy by overcoming cancer-associated fibroblast-mediated CD8 T-cell exclusion from tumors. Cancer Res 80:1846–60
     [Google Scholar]
  51. 51. 
    Mirlekar B, Michaud D, Lee SJ, Kren NP, Harris C et al. 2020. B cell-derived IL35 drives STAT3-dependent CD8+ T-cell exclusion in pancreatic cancer. Cancer Immunol. Res. 8:292–308
     [Google Scholar]
  52. 52. 
    Nambiar DK, Aguilera T, Cao H, Kwok S, Kong C et al. 2019. Galectin-1-driven T cell exclusion in the tumor endothelium promotes immunotherapy resistance. J. Clin. Investig. 129:5553–67
     [Google Scholar]
  53. 53. 
    Spranger S, Gajewski TF. 2018. Impact of oncogenic pathways on evasion of antitumour immune responses. Nat. Rev. Cancer 18:139–47
     [Google Scholar]
  54. 54. 
    Peng W, Chen JQ, Liu C, Malu S, Creasy C et al. 2016. Loss of PTEN promotes resistance to T cell-mediated immunotherapy. Cancer Discov 6:202–16
     [Google Scholar]
  55. 55. 
    George S, Miao D, Demetri GD, Adeegbe D, Rodig SJ et al. 2017. Loss of PTEN is associated with resistance to anti-PD-1 checkpoint blockade therapy in metastatic uterine leiomyosarcoma. Immunity 46:197–204
     [Google Scholar]
  56. 56. 
    Trujillo JA, Luke JJ, Zha Y, Segal JP, Ritterhouse LL et al. 2019. Secondary resistance to immunotherapy associated with beta-catenin pathway activation or PTEN loss in metastatic melanoma. J. Immunother. Cancer 7:295
     [Google Scholar]
  57. 57. 
    Spranger S, Bao R, Gajewski TF 2015. Melanoma-intrinsic beta-catenin signalling prevents anti-tumour immunity. Nature 523:231–35
     [Google Scholar]
  58. 58. 
    Jerby-Arnon L, Shah P, Cuoco MS, Rodman C, Su MJ et al. 2018. A cancer cell program promotes T cell exclusion and resistance to checkpoint blockade. Cell 175:984–97.e24
     [Google Scholar]
  59. 59. 
    Dunn GP, Koebel CM, Schreiber RD. 2006. Interferons, immunity and cancer immunoediting. Nat. Rev. Immunol. 6:836–48
     [Google Scholar]
  60. 60. 
    Kaplan DH, Shankaran V, Dighe AS, Stockert E, Aguet M et al. 1998. Demonstration of an interferon gamma-dependent tumor surveillance system in immunocompetent mice. PNAS 95:7556–61
     [Google Scholar]
  61. 61. 
    Dunn GP, Bruce AT, Sheehan KC, Shankaran V, Uppaluri R et al. 2005. A critical function for type I interferons in cancer immunoediting. Nat. Immunol. 6:722–29
     [Google Scholar]
  62. 62. 
    Shankaran V, Ikeda H, Bruce AT, White JM, Swanson PE et al. 2001. IFNγ and lymphocytes prevent primary tumour development and shape tumour immunogenicity. Nature 410:1107–11
     [Google Scholar]
  63. 63. 
    Meraz MA, White JM, Sheehan KC, Bach EA, Rodig SJ et al. 1996. Targeted disruption of the Stat1 gene in mice reveals unexpected physiologic specificity in the JAK-STAT signaling pathway. Cell 84:431–42
     [Google Scholar]
  64. 64. 
    Rodig SJ, Meraz MA, White JM, Lampe PA, Riley JK et al. 1998. Disruption of the Jak1 gene demonstrates obligatory and nonredundant roles of the Jaks in cytokine-induced biologic responses. Cell 93:373–83
     [Google Scholar]
  65. 65. 
    Zerdes I, Matikas A, Bergh J, Rassidakis GZ, Foukakis T. 2018. Genetic, transcriptional and post-translational regulation of the programmed death protein ligand 1 in cancer: biology and clinical correlations. Oncogene 37:4639–61
     [Google Scholar]
  66. 66. 
    Dunn GP, Sheehan KC, Old LJ, Schreiber RD. 2005. IFN unresponsiveness in LNCaP cells due to the lack of JAK1 gene expression. Cancer Res 65:3447–53
     [Google Scholar]
  67. 67. 
    Zaretsky JM, Garcia-Diaz A, Shin DS, Escuin-Ordinas H, Hugo W et al. 2016. Mutations associated with acquired resistance to PD-1 blockade in melanoma. N. Engl. J. Med. 375:819–29
     [Google Scholar]
  68. 68. 
    Shin DS, Zaretsky JM, Escuin-Ordinas H, Garcia-Diaz A, Hu-Lieskovan S et al. 2017. Primary resistance to PD-1 blockade mediated by JAK1/2 mutations. Cancer Discov 7:188–201
     [Google Scholar]
  69. 69. 
    Sucker A, Zhao F, Pieper N, Heeke C, Maltaner R et al. 2017. Acquired IFNγ resistance impairs anti-tumor immunity and gives rise to T-cell-resistant melanoma lesions. Nat. Commun. 8:15440
     [Google Scholar]
  70. 70. 
    Schreiber RD, Old LJ, Smyth MJ. 2011. Cancer immunoediting: integrating immunity's roles in cancer suppression and promotion. Science 331:1565–70
     [Google Scholar]
  71. 71. 
    Dunn GP, Old LJ, Schreiber RD. 2004. The three Es of cancer immunoediting. Annu. Rev. Immunol. 22:329–60
     [Google Scholar]
  72. 72. 
    Matsushita H, Vesely MD, Koboldt DC, Rickert CG, Uppaluri R et al. 2012. Cancer exome analysis reveals a T-cell-dependent mechanism of cancer immunoediting. Nature 482:400–4
     [Google Scholar]
  73. 73. 
    Gubin MM, Zhang X, Schuster H, Caron E, Ward JP et al. 2014. Checkpoint blockade cancer immunotherapy targets tumour-specific mutant antigens. Nature 515:577–81
     [Google Scholar]
  74. 74. 
    Vesely MD, Schreiber RD. 2013. Cancer immunoediting: antigens, mechanisms, and implications to cancer immunotherapy. Ann. N. Y. Acad. Sci. 1284:1–5
     [Google Scholar]
  75. 75. 
    Schumacher TN, Schreiber RD. 2015. Neoantigens in cancer immunotherapy. Science 348:69–74
     [Google Scholar]
  76. 76. 
    Tran E, Robbins PF, Rosenberg SA. 2017. ‘Final common pathway’ of human cancer immunotherapy: targeting random somatic mutations. Nat. Immunol. 18:255–62
     [Google Scholar]
  77. 77. 
    Jia Q, Wu W, Wang Y, Alexander PB, Sun C et al. 2018. Local mutational diversity drives intratumoral immune heterogeneity in non-small cell lung cancer. Nat. Commun. 9:5361
     [Google Scholar]
  78. 78. 
    McGranahan N, Furness AJ, Rosenthal R, Ramskov S, Lyngaa R et al. 2016. Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade. Science 351:1463–69
     [Google Scholar]
  79. 79. 
    Goodman AM, Kato S, Bazhenova L, Patel SP, Frampton GM et al. 2017. Tumor mutational burden as an independent predictor of response to immunotherapy in diverse cancers. Mol. Cancer Ther. 16:2598–608
     [Google Scholar]
  80. 80. 
    Rizvi NA, Hellmann MD, Snyder A, Kvistborg P, Makarov V et al. 2015. Cancer immunology: Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer. Science 348:124–28
     [Google Scholar]
  81. 81. 
    Tran E, Turcotte S, Gros A, Robbins PF, Lu YC et al. 2014. Cancer immunotherapy based on mutation-specific CD4+ T cells in a patient with epithelial cancer. Science 344:641–45
     [Google Scholar]
  82. 82. 
    Verdegaal EM, de Miranda NF, Visser M, Harryvan T, van Buuren MM et al. 2016. Neoantigen landscape dynamics during human melanoma-T cell interactions. Nature 536:91–95
     [Google Scholar]
  83. 83. 
    Rosenthal R, Cadieux EL, Salgado R, Bakir MA, Moore DA et al. 2019. Neoantigen-directed immune escape in lung cancer evolution. Nature 567:479–85
     [Google Scholar]
  84. 84. 
    Anagnostou V, Smith KN, Forde PM, Niknafs N, Bhattacharya R et al. 2017. Evolution of neoantigen landscape during immune checkpoint blockade in non-small cell lung cancer. Cancer Discov 7:264–76
     [Google Scholar]
  85. 85. 
    Shukla SA, Rooney MS, Rajasagi M, Tiao G, Dixon PM et al. 2015. Comprehensive analysis of cancer-associated somatic mutations in class I HLA genes. Nat. Biotechnol. 33:1152–58
     [Google Scholar]
  86. 86. 
    McGranahan N, Rosenthal R, Hiley CT, Rowan AJ, Watkins TBK et al. 2017. Allele-specific HLA loss and immune escape in lung cancer evolution. Cell 171:1259–71.e11
     [Google Scholar]
  87. 87. 
    Gettinger S, Choi J, Hastings K, Truini A, Datar I et al. 2017. Impaired HLA class I antigen processing and presentation as a mechanism of acquired resistance to immune checkpoint inhibitors in lung cancer. Cancer Discov 7:1420–35
     [Google Scholar]
  88. 88. 
    Sade-Feldman M, Jiao YJ, Chen JH, Rooney MS, Barzily-Rokni M et al. 2017. Resistance to checkpoint blockade therapy through inactivation of antigen presentation. Nat. Commun. 8:1136
     [Google Scholar]
  89. 89. 
    Le DT, Durham JN, Smith KN, Wang H, Bartlett BR et al. 2017. Mismatch repair deficiency predicts response of solid tumors to PD-1 blockade. Science 357:409–13
     [Google Scholar]
  90. 90. 
    Klein B, Klein T, Figer A, Bleiberg M, Shapira J et al. 1991. Soluble histocompatibility antigen class I in breast cancer patients in relation to tumor burden. Cancer 67:2295–99
     [Google Scholar]
  91. 91. 
    Arce Vargas F, Furness AJS, Solomon I, Joshi K, Mekkaoui L et al. 2017. Fc-optimized anti-CD25 depletes tumor-infiltrating regulatory T cells and synergizes with PD-1 blockade to eradicate established tumors. Immunity 46:577–86
     [Google Scholar]
  92. 92. 
    Veglia F, Perego M, Gabrilovich D. 2018. Myeloid-derived suppressor cells coming of age. Nat. Immunol. 19:108–19
     [Google Scholar]
  93. 93. 
    Mantovani A, Marchesi F, Malesci A, Laghi L, Allavena P. 2017. Tumour-associated macrophages as treatment targets in oncology. Nat. Rev. Clin. Oncol. 14:399–416
     [Google Scholar]
  94. 94. 
    Shang B, Liu Y, Jiang SJ, Liu Y. 2015. Prognostic value of tumor-infiltrating FoxP3+ regulatory T cells in cancers: a systematic review and meta-analysis. Sci. Rep. 5:15179
     [Google Scholar]
  95. 95. 
    Liyanage UK, Moore TT, Joo HG, Tanaka Y, Herrmann V et al. 2002. Prevalence of regulatory T cells is increased in peripheral blood and tumor microenvironment of patients with pancreas or breast adenocarcinoma. J. Immunol. 169:2756–61
     [Google Scholar]
  96. 96. 
    Ichihara F, Kono K, Takahashi A, Kawaida H, Sugai H, Fujii H. 2003. Increased populations of regulatory T cells in peripheral blood and tumor-infiltrating lymphocytes in patients with gastric and esophageal cancers. Clin. Cancer Res. 9:4404–8
     [Google Scholar]
  97. 97. 
    Hiraoka N, Onozato K, Kosuge T, Hirohashi S 2006. Prevalence of FOXP3+ regulatory T cells increases during the progression of pancreatic ductal adenocarcinoma and its premalignant lesions. Clin. Cancer Res. 12:5423–34
     [Google Scholar]
  98. 98. 
    Curiel TJ, Coukos G, Zou L, Alvarez X, Cheng P et al. 2004. Specific recruitment of regulatory T cells in ovarian carcinoma fosters immune privilege and predicts reduced survival. Nat. Med. 10:942–49
     [Google Scholar]
  99. 99. 
    Wing K, Onishi Y, Prieto-Martin P, Yamaguchi T, Miyara M et al. 2008. CTLA-4 control over Foxp3+ regulatory T cell function. Science 322:271–75
     [Google Scholar]
  100. 100. 
    Kuehn HS, Ouyang W, Lo B, Deenick EK, Niemela JE et al. 2014. Immune dysregulation in human subjects with heterozygous germline mutations in CTLA4. Science 345:1623–27
     [Google Scholar]
  101. 101. 
    Du X, Tang F, Liu M, Su J, Zhang Y et al. 2018. A reappraisal of CTLA-4 checkpoint blockade in cancer immunotherapy. Cell Res 28:416–32
     [Google Scholar]
  102. 102. 
    Simpson TR, Li F, Montalvo-Ortiz W, Sepulveda MA, Bergerhoff K et al. 2013. Fc-dependent depletion of tumor-infiltrating regulatory T cells co-defines the efficacy of anti-CTLA-4 therapy against melanoma. J. Exp. Med. 210:1695–710
     [Google Scholar]
  103. 103. 
    Du X, Liu M, Su J, Zhang P, Tang F et al. 2018. Uncoupling therapeutic from immunotherapy-related adverse effects for safer and effective anti-CTLA-4 antibodies in CTLA4 humanized mice. Cell Res 28:433–47
     [Google Scholar]
  104. 104. 
    Romano E, Kusio-Kobialka M, Foukas PG, Baumgaertner P, Meyer C et al. 2015. Ipilimumab-dependent cell-mediated cytotoxicity of regulatory T cells ex vivo by nonclassical monocytes in melanoma patients. PNAS 112:6140–45
     [Google Scholar]
  105. 105. 
    Koh J, Hur JY, Lee KY, Kim MS, Heo JY et al. 2020. Regulatory (FoxP3+) T cells and TGF-beta predict the response to anti-PD-1 immunotherapy in patients with non-small cell lung cancer. Sci. Rep. 10:18994
     [Google Scholar]
  106. 106. 
    Weide B, Martens A, Zelba H, Stutz C, Derhovanessian E et al. 2014. Myeloid-derived suppressor cells predict survival of patients with advanced melanoma: comparison with regulatory T cells and NY-ESO-1- or melan-A–specific T cells. Clin. Cancer Res. 20:1601–9
     [Google Scholar]
  107. 107. 
    Ai L, Mu S, Wang Y, Wang H, Cai L et al. 2018. Prognostic role of myeloid-derived suppressor cells in cancers: a systematic review and meta-analysis. BMC Cancer 18:1220
     [Google Scholar]
  108. 108. 
    Okla K, Czerwonka A, Wawruszak A, Bobinski M, Bilska M et al. 2019. Clinical relevance and immunosuppressive pattern of circulating and infiltrating subsets of myeloid-derived suppressor cells (MDSCs) in epithelial ovarian cancer. Front. Immunol. 10:691
     [Google Scholar]
  109. 109. 
    Hou A, Hou K, Huang Q, Lei Y, Chen W. 2020. Targeting myeloid-derived suppressor cell, a promising strategy to overcome resistance to immune checkpoint inhibitors. Front. Immunol. 11:783
     [Google Scholar]
  110. 110. 
    Molgora M, Esaulova E, Vermi W, Hou J, Chen Y et al. 2020. TREM2 modulation remodels the tumor myeloid landscape enhancing anti-PD-1 immunotherapy. Cell 182:886–900.e17
     [Google Scholar]
  111. 111. 
    De Henau O, Rausch M, Winkler D, Campesato LF, Liu C et al. 2016. Overcoming resistance to checkpoint blockade therapy by targeting PI3Kγ in myeloid cells. Nature 539:443–47
     [Google Scholar]
  112. 112. 
    Neubert NJ, Schmittnaegel M, Bordry N, Nassiri S, Wald N et al. 2018. T cell-induced CSF1 promotes melanoma resistance to PD1 blockade. Sci. Transl. Med. 10:eaan3311
     [Google Scholar]
  113. 113. 
    Long GV, Dummer R, Hamid O, Gajewski TF, Caglevic C et al. 2019. Epacadostat plus pembrolizumab versus placebo plus pembrolizumab in patients with unresectable or metastatic melanoma (ECHO-301/KEYNOTE-252): a phase 3, randomised, double-blind study. Lancet Oncol 20:1083–97
     [Google Scholar]
  114. 114. 
    Yao S, Zhu Y, Chen L. 2013. Advances in targeting cell surface signalling molecules for immune modulation. Nat. Rev. Drug Discov. 12:130–46
     [Google Scholar]
  115. 115. 
    Triebel F, Jitsukawa S, Baixeras E, Roman-Roman S, Genevee C et al. 1990. LAG-3, a novel lymphocyte activation gene closely related to CD4. J. Exp. Med. 171:1393–405
     [Google Scholar]
  116. 116. 
    Baixeras E, Huard B, Miossec C, Jitsukawa S, Martin M et al. 1992. Characterization of the lymphocyte activation gene 3-encoded protein: a new ligand for human leukocyte antigen class II antigens. J. Exp. Med. 176:327–37
     [Google Scholar]
  117. 117. 
    Chihara N, Madi A, Kondo T, Zhang H, Acharya N et al. 2018. Induction and transcriptional regulation of the co-inhibitory gene module in T cells. Nature 558:454–59
     [Google Scholar]
  118. 118. 
    Williams JB, Horton BL, Zheng Y, Duan Y, Powell JD, Gajewski TF 2017. The EGR2 targets LAG-3 and 4–1BB describe and regulate dysfunctional antigen-specific CD8+ T cells in the tumor microenvironment. J. Exp. Med. 214:381–400
     [Google Scholar]
  119. 119. 
    Andrews LP, Yano H, Vignali DAA. 2019. Inhibitory receptors and ligands beyond PD-1, PD-L1 and CTLA-4: breakthroughs or backups. Nat. Immunol. 20:1425–34
     [Google Scholar]
  120. 120. 
    Koyama S, Akbay EA, Li YY, Herter-Sprie GS, Buczkowski KA et al. 2016. Adaptive resistance to therapeutic PD-1 blockade is associated with upregulation of alternative immune checkpoints. Nat. Commun. 7:10501
     [Google Scholar]
  121. 121. 
    Wang J, Sanmamed MF, Datar I, Su TT, Ji L et al. 2019. Fibrinogen-like protein 1 is a major immune inhibitory ligand of LAG-3. Cell 176:334–47.e12
     [Google Scholar]
  122. 122. 
    Wang L, Rubinstein R, Lines JL, Wasiuk A, Ahonen C et al. 2011. VISTA, a novel mouse Ig superfamily ligand that negatively regulates T cell responses. J. Exp. Med. 208:577–92
     [Google Scholar]
  123. 123. 
    Flies DB, Wang S, Xu H, Chen L 2011. Cutting edge: A monoclonal antibody specific for the programmed death-1 homolog prevents graft-versus-host disease in mouse models. J. Immunol. 187:1537–41
     [Google Scholar]
  124. 124. 
    ElTanbouly MA, Schaafsma E, Noelle RJ, Lines JL 2020. VISTA: coming of age as a multi-lineage immune checkpoint. Clin. Exp. Immunol. 200:120–30
     [Google Scholar]
  125. 125. 
    Johnston RJ, Su LJ, Pinckney J, Critton D, Boyer E et al. 2019. VISTA is an acidic pH-selective ligand for PSGL-1. Nature 574:565–70
     [Google Scholar]
  126. 126. 
    Le Mercier I, Chen W, Lines JL, Day M, Li J et al. 2014. VISTA regulates the development of protective antitumor immunity. Cancer Res 74:1933–44
     [Google Scholar]
  127. 127. 
    Kakavand H, Jackett LA, Menzies AM, Gide TN, Carlino MS et al. 2017. Negative immune checkpoint regulation by VISTA: a mechanism of acquired resistance to anti-PD-1 therapy in metastatic melanoma patients. Mod. Pathol. 30:1666–76
     [Google Scholar]
  128. 128. 
    Wang J, Sun J, Liu LN, Flies DB, Nie X et al. 2019. Siglec-15 as an immune suppressor and potential target for normalization cancer immunotherapy. Nat. Med. 25:656–66
     [Google Scholar]
  129. 129. 
    Li B, Zhang B, Wang X, Zeng Z, Huang Z et al. 2020. Expression signature, prognosis value, and immune characteristics of Siglec-15 identified by pan-cancer analysis. OncoImmunology 9:1807291
     [Google Scholar]
  130. 130. 
    Schalper KA, Carleton M, Zhou M, Chen T, Feng Y et al. 2020. Elevated serum interleukin-8 is associated with enhanced intratumor neutrophils and reduced clinical benefit of immune-checkpoint inhibitors. Nat. Med. 26:688–92
     [Google Scholar]
  131. 131. 
    Cerezo-Wallis D, Contreras-Alcalde M, Troule K, Catena X, Mucientes C et al. 2020. Midkine rewires the melanoma microenvironment toward a tolerogenic and immune-resistant state. Nat. Med. 26:1865–77
     [Google Scholar]
  132. 132. 
    Derynck R, Turley SJ, Akhurst RJ. 2021. TGFβ biology in cancer progression and immunotherapy. Nat. Rev. Clin. Oncol. 18:9–34
     [Google Scholar]
  133. 133. 
    Calon A, Lonardo E, Berenguer-Llergo A, Espinet E, Hernando-Momblona X et al. 2015. Stromal gene expression defines poor-prognosis subtypes in colorectal cancer. Nat. Genet. 47:320–29
     [Google Scholar]
  134. 134. 
    Dominguez CX, Muller S, Keerthivasan S, Koeppen H, Hung J et al. 2020. Single-cell RNA sequencing reveals stromal evolution into LRRC15+ myofibroblasts as a determinant of patient response to cancer immunotherapy. Cancer Discov 10:232–53
     [Google Scholar]
  135. 135. 
    Mariathasan S, Turley SJ, Nickles D, Castiglioni A, Yuen K et al. 2018. TGFβ attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells. Nature 554:544–48
     [Google Scholar]
  136. 136. 
    Turcotte M, Spring K, Pommey S, Chouinard G, Cousineau I et al. 2015. CD73 is associated with poor prognosis in high-grade serous ovarian cancer. Cancer Res 75:4494–503
     [Google Scholar]
  137. 137. 
    Vijayan D, Young A, Teng MWL, Smyth MJ 2017. Targeting immunosuppressive adenosine in cancer. Nat. Rev. Cancer 17:709–24
     [Google Scholar]
  138. 138. 
    Tasdogan A, Faubert B, Ramesh V, Ubellacker JM, Shen B et al. 2020. Metabolic heterogeneity confers differences in melanoma metastatic potential. Nature 577:115–20
     [Google Scholar]
  139. 139. 
    Faubert B, Solmonson A, DeBerardinis RJ. 2020. Metabolic reprogramming and cancer progression. Science 368:eaaw5473
     [Google Scholar]
  140. 140. 
    Oh MH, Sun IH, Zhao L, Leone RD, Sun IM et al. 2020. Targeting glutamine metabolism enhances tumor-specific immunity by modulating suppressive myeloid cells. J. Clin. Investig. 130:3865–84
     [Google Scholar]
  141. 141. 
    Leone RD, Powell JD. 2020. Metabolism of immune cells in cancer. Nat. Rev. Cancer 20:516–31
     [Google Scholar]
  142. 142. 
    Kaymak I, Williams KS, Cantor JR, Jones RG. 2021. Immunometabolic interplay in the tumor microenvironment. Cancer Cell 39:28–37
     [Google Scholar]
  143. 143. 
    Frauwirth KA, Riley JL, Harris MH, Parry RV, Rathmell JC et al. 2002. The CD28 signaling pathway regulates glucose metabolism. Immunity 16:769–77
     [Google Scholar]
  144. 144. 
    Wang R, Dillon CP, Shi LZ, Milasta S, Carter R et al. 2011. The transcription factor Myc controls metabolic reprogramming upon T lymphocyte activation. Immunity 35:871–82
     [Google Scholar]
  145. 145. 
    Chang CH, Curtis JD, Maggi LB Jr., Faubert B, Villarino AV et al. 2013. Posttranscriptional control of T cell effector function by aerobic glycolysis. Cell 153:1239–51
     [Google Scholar]
  146. 146. 
    Buck MD, O'Sullivan D, Klein Geltink RI, Curtis JD, Chang CH et al. 2016. Mitochondrial dynamics controls T cell fate through metabolic programming. Cell 166:63–76
     [Google Scholar]
  147. 147. 
    Ho PC, Bihuniak JD, Macintyre AN, Staron M, Liu X et al. 2015. Phosphoenolpyruvate is a metabolic checkpoint of anti-tumor T cell responses. Cell 162:1217–28
     [Google Scholar]
  148. 148. 
    Geiger R, Rieckmann JC, Wolf T, Basso C, Feng Y et al. 2016. L-Arginine modulates T cell metabolism and enhances survival and anti-tumor activity. Cell 167:829–42.e13
     [Google Scholar]
  149. 149. 
    Yang W, Bai Y, Xiong Y, Zhang J, Chen S et al. 2016. Potentiating the antitumour response of CD8+ T cells by modulating cholesterol metabolism. Nature 531:651–55
     [Google Scholar]
  150. 150. 
    Leone RD, Zhao L, Englert JM, Sun IM, Oh MH et al. 2019. Glutamine blockade induces divergent metabolic programs to overcome tumor immune evasion. Science 366:1013–21
     [Google Scholar]
  151. 151. 
    Liu X, Bao X, Hu M, Chang H, Jiao M et al. 2020. Inhibition of PCSK9 potentiates immune checkpoint therapy for cancer. Nature 588:693–98
     [Google Scholar]
  152. 152. 
    Bengsch B, Johnson AL, Kurachi M, Odorizzi PM, Pauken KE et al. 2016. Bioenergetic insufficiencies due to metabolic alterations regulated by the inhibitory receptor PD-1 are an early driver of CD8+ T cell exhaustion. Immunity 45:358–73
     [Google Scholar]
  153. 153. 
    Chang CH, Qiu J, O'Sullivan D, Buck MD, Noguchi T et al. 2015. Metabolic competition in the tumor microenvironment is a driver of cancer progression. Cell 162:1229–41
     [Google Scholar]
  154. 154. 
    Xiao Z, Dai Z, Locasale JW. 2019. Metabolic landscape of the tumor microenvironment at single cell resolution. Nat. Commun. 10:3763
     [Google Scholar]
  155. 155. 
    Hartmann FJ, Mrdjen D, McCaffrey E, Glass DR, Greenwald NF et al. 2021. Single-cell metabolic profiling of human cytotoxic T cells. Nat. Biotechnol. 39:186–97
     [Google Scholar]
  156. 156. 
    Ringel AE, Drijvers JM, Baker GJ, Catozzi A, García-Cañaveras JC et al. 2020. Obesity shapes metabolism in the tumor microenvironment to suppress anti-tumor immunity. Cell 183:1848–66.e26
     [Google Scholar]
  157. 157. 
    Wu W, Shi X, Xu C. 2016. Regulation of T cell signalling by membrane lipids. Nat. Rev. Immunol. 16:690–701
     [Google Scholar]
  158. 158. 
    Ma X, Bi E, Lu Y, Su P, Huang C et al. 2019. Cholesterol induces CD8+ T cell exhaustion in the tumor microenvironment. Cell Metab 30:143–56.e5
     [Google Scholar]
  159. 159. 
    Ma X, Xiao L, Liu L, Ye L, Su P et al. 2021. CD36-mediated ferroptosis dampens intratumoral CD8+ T cell effector function and impairs their antitumor ability. Cell Metab 33:1001–12.e5
     [Google Scholar]
  160. 160. 
    Bian Y, Li W, Kremer DM, Sajjakulnukit P, Li S et al. 2020. Cancer SLC43A2 alters T cell methionine metabolism and histone methylation. Nature 585:277–82
     [Google Scholar]
  161. 161. 
    Uyttenhove C, Pilotte L, Theate I, Stroobant V, Colau D et al. 2003. Evidence for a tumoral immune resistance mechanism based on tryptophan degradation by indoleamine 2,3-dioxygenase. Nat. Med. 9:1269–74
     [Google Scholar]
  162. 162. 
    Spranger S, Koblish HK, Horton B, Scherle PA, Newton R, Gajewski TF 2014. Mechanism of tumor rejection with doublets of CTLA-4, PD-1/PD-L1, or IDO blockade involves restored IL-2 production and proliferation of CD8+ T cells directly within the tumor microenvironment. J. Immunother. Cancer 2:3
     [Google Scholar]
  163. 163. 
    Beatty GL, O'Dwyer PJ, Clark J, Shi JG, Bowman KJ et al. 2017. First-in-human phase I study of the oral inhibitor of indoleamine 2,3-dioxygenase-1 epacadostat (INCB024360) in patients with advanced solid malignancies. Clin. Cancer Res. 23:3269–76
     [Google Scholar]
  164. 164. 
    Mitchell TC, Hamid O, Smith DC, Bauer TM, Wasser JS et al. 2018. Epacadostat plus pembrolizumab in patients with advanced solid tumors: phase I results from a multicenter, open-label phase I/II trial (ECHO-202/KEYNOTE-037). J. Clin. Oncol. 36:3223–30
     [Google Scholar]
  165. 165. 
    Moesta AK, Li XY, Smyth MJ 2020. Targeting CD39 in cancer. Nat. Rev. Immunol. 20:739–55
     [Google Scholar]
  166. 166. 
    Jiang Z, Hsu JL, Li Y, Hortobagyi GN, Hung MC. 2020. Cancer cell metabolism bolsters immunotherapy resistance by promoting an immunosuppressive tumor microenvironment. Front. Oncol. 10:1197
     [Google Scholar]
  167. 167. 
    Hooper LV, Littman DR, Macpherson AJ. 2012. Interactions between the microbiota and the immune system. Science 336:1268–73
     [Google Scholar]
  168. 168. 
    Lathrop SK, Bloom SM, Rao SM, Nutsch K, Lio CW et al. 2011. Peripheral education of the immune system by colonic commensal microbiota. Nature 478:250–54
     [Google Scholar]
  169. 169. 
    Sivan A, Corrales L, Hubert N, Williams JB, Aquino-Michaels K et al. 2015. Commensal Bifidobacterium promotes antitumor immunity and facilitates anti-PD-L1 efficacy. Science 350:1084–89
     [Google Scholar]
  170. 170. 
    Vetizou M, Pitt JM, Daillere R, Lepage P, Waldschmitt N et al. 2015. Anticancer immunotherapy by CTLA-4 blockade relies on the gut microbiota. Science 350:1079–84
     [Google Scholar]
  171. 171. 
    Chaput N, Lepage P, Coutzac C, Soularue E, Le Roux K et al. 2017. Baseline gut microbiota predicts clinical response and colitis in metastatic melanoma patients treated with ipilimumab. Ann. Oncol. 28:1368–79
     [Google Scholar]
  172. 172. 
    Frankel AE, Coughlin LA, Kim J, Froehlich TW, Xie Y et al. 2017. Metagenomic shotgun sequencing and unbiased metabolomic profiling identify specific human gut microbiota and metabolites associated with immune checkpoint therapy efficacy in melanoma patients. Neoplasia 19:848–55
     [Google Scholar]
  173. 173. 
    Gopalakrishnan V, Spencer CN, Nezi L, Reuben A, Andrews MC et al. 2018. Gut microbiome modulates response to anti-PD-1 immunotherapy in melanoma patients. Science 359:97–103
     [Google Scholar]
  174. 174. 
    Matson V, Fessler J, Bao R, Chongsuwat T, Zha Y et al. 2018. The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients. Science 359:104–8
     [Google Scholar]
  175. 175. 
    Routy B, Le Chatelier E, Derosa L, Duong CPM, Alou MT et al. 2018. Gut microbiome influences efficacy of PD-1-based immunotherapy against epithelial tumors. Science 359:91–97
     [Google Scholar]
  176. 176. 
    Derosa L, Hellmann MD, Spaziano M, Halpenny D, Fidelle M et al. 2018. Negative association of antibiotics on clinical activity of immune checkpoint inhibitors in patients with advanced renal cell and non-small-cell lung cancer. Ann. Oncol. 29:1437–44
     [Google Scholar]
  177. 177. 
    Peng Z, Cheng S, Kou Y, Wang Z, Jin R et al. 2020. The gut microbiome is associated with clinical response to anti-PD-1/PD-L1 immunotherapy in gastrointestinal cancer. Cancer Immunol. Res. 8:1251–61
     [Google Scholar]
  178. 178. 
    Tomita Y, Ikeda T, Sakata S, Saruwatari K, Sato R et al. 2020. Association of probiotic Clostridium butyricum therapy with survival and response to immune checkpoint blockade in patients with lung cancer. Cancer Immunol. Res. 8:1236–42
     [Google Scholar]
  179. 179. 
    Hakozaki T, Richard C, Elkrief A, Hosomi Y, Benlaifaoui M et al. 2020. The gut microbiome associates with immune checkpoint inhibition outcomes in patients with advanced non–small cell lung cancer. Cancer Immunol. Res. 8:1243–50
     [Google Scholar]
  180. 180. 
    Salgia NJ, Bergerot PG, Maia MC, Dizman N, Hsu J et al. 2020. Stool microbiome profiling of patients with metastatic renal cell carcinoma receiving anti-PD-1 immune checkpoint inhibitors. Eur. Urol. 78:498–502
     [Google Scholar]
  181. 181. 
    Pinato DJ, Howlett S, Ottaviani D, Urus H, Patel A et al. 2019. Association of prior antibiotic treatment with survival and response to immune checkpoint inhibitor therapy in patients with cancer. JAMA Oncol 5:1774–78
     [Google Scholar]
  182. 182. 
    Gopalakrishnan V, Helmink BA, Spencer CN, Reuben A, Wargo JA 2018. The influence of the gut microbiome on cancer, immunity, and cancer immunotherapy. Cancer Cell 33:570–80
     [Google Scholar]
  183. 183. 
    Routy B, Gopalakrishnan V, Daillere R, Zitvogel L, Wargo JA, Kroemer G. 2018. The gut microbiota influences anticancer immunosurveillance and general health. Nat. Rev. Clin. Oncol. 15:382–96
     [Google Scholar]
  184. 184. 
    Baruch EN, Youngster I, Ben-Betzalel G, Ortenberg R, Lahat A et al. 2021. Fecal microbiota transplant promotes response in immunotherapy-refractory melanoma patients. Science 371:602–9
     [Google Scholar]
  185. 185. 
    Davar D, Dzutsev AK, McCulloch JA, Rodrigues RR, Chauvin JM et al. 2021. Fecal microbiota transplant overcomes resistance to anti-PD-1 therapy in melanoma patients. Science 371:595–602
     [Google Scholar]
  186. 186. 
    Mager LF, Burkhard R, Pett N, Cooke NCA, Brown K et al. 2020. Microbiome-derived inosine modulates response to checkpoint inhibitor immunotherapy. Science 369:1481–89
     [Google Scholar]
  187. 187. 
    Tanoue T, Morita S, Plichta DR, Skelly AN, Suda W et al. 2019. A defined commensal consortium elicits CD8 T cells and anti-cancer immunity. Nature 565:600–5
     [Google Scholar]
  188. 188. 
    Riquelme E, Zhang Y, Zhang L, Montiel M, Zoltan M et al. 2019. Tumor microbiome diversity and composition influence pancreatic cancer outcomes. Cell 178:795–806.e12
     [Google Scholar]
  189. 189. 
    Nejman D, Livyatan I, Fuks G, Gavert N, Zwang Y et al. 2020. The human tumor microbiome is composed of tumor type-specific intracellular bacteria. Science 368:973–80
     [Google Scholar]
  190. 190. 
    Fluckiger A, Daillere R, Sassi M, Sixt BS, Liu P et al. 2020. Cross-reactivity between tumor MHC class I-restricted antigens and an enterococcal bacteriophage. Science 369:936–42
     [Google Scholar]
  191. 191. 
    Kalaora S, Nagler A, Nejman D, Alon M, Barbolin C et al. 2021. Identification of bacteria-derived HLA-bound peptides in melanoma. Nature 592:138–43
     [Google Scholar]
  192. 192. 
    Kakaradov B, Arsenio J, Widjaja CE, He Z, Aigner S et al. 2017. Early transcriptional and epigenetic regulation of CD8+ T cell differentiation revealed by single-cell RNA sequencing. Nat. Immunol. 18:422–32
     [Google Scholar]
  193. 193. 
    Peng D, Kryczek I, Nagarsheth N, Zhao L, Wei S et al. 2015. Epigenetic silencing of TH1-type chemokines shapes tumour immunity and immunotherapy. Nature 527:249–53
     [Google Scholar]
  194. 194. 
    Zhao E, Maj T, Kryczek I, Li W, Wu K et al. 2016. Cancer mediates effector T cell dysfunction by targeting microRNAs and EZH2 via glycolysis restriction. Nat. Immunol. 17:95–103
     [Google Scholar]
  195. 195. 
    Gonda TA, Fang J, Salas M, Do C, Hsu E et al. 2020. A DNA hypomethylating drug alters the tumor microenvironment and improves the effectiveness of immune checkpoint inhibitors in a mouse model of pancreatic cancer. Cancer Res 80:4754–67
     [Google Scholar]
  196. 196. 
    Chiappinelli KB, Strissel PL, Desrichard A, Li H, Henke C et al. 2015. Inhibiting DNA methylation causes an interferon response in cancer via dsRNA including endogenous retroviruses. Cell 162:974–86
     [Google Scholar]
  197. 197. 
    Terranova-Barberio M, Thomas S, Ali N, Pawlowska N, Park J et al. 2017. HDAC inhibition potentiates immunotherapy in triple negative breast cancer. Oncotarget 8:114156–72
     [Google Scholar]
  198. 198. 
    Zingg D, Arenas-Ramirez N, Sahin D, Rosalia RA, Antunes AT et al. 2017. The histone methyltransferase Ezh2 controls mechanisms of adaptive resistance to tumor immunotherapy. Cell Rep 20:854–67
     [Google Scholar]
  199. 199. 
    Pauken KE, Sammons MA, Odorizzi PM, Manne S, Godec J et al. 2016. Epigenetic stability of exhausted T cells limits durability of reinvigoration by PD-1 blockade. Science 354:1160–65
     [Google Scholar]
  200. 200. 
    Arenas-Ramirez N, Sahin D, Boyman O 2018. Epigenetic mechanisms of tumor resistance to immunotherapy. Cell Mol. Life Sci. 75:4163–76
     [Google Scholar]
  201. 201. 
    Wang Z, Wu X 2020. Study and analysis of antitumor resistance mechanism of PD1/PD-L1 immune checkpoint blocker. Cancer Med 9:8086–121
     [Google Scholar]
  202. 202. 
    Kim HJ, Cantor H, Cosmopoulos K. 2020. Overcoming immune checkpoint blockade resistance via EZH2 inhibition. Trends Immunol 41:948–63
     [Google Scholar]
  203. 203. 
    Olino K, Park T, Ahuja N 2020. Exposing hidden targets: combining epigenetic and immunotherapy to overcome cancer resistance. Semin. Cancer Biol. 65:114–22
     [Google Scholar]
  204. 204. 
    He S, Liu Y, Meng L, Sun H, Wang Y et al. 2017. Ezh2 phosphorylation state determines its capacity to maintain CD8+ T memory precursors for antitumor immunity. Nat. Commun. 8:2125
     [Google Scholar]
  205. 205. 
    Gunawan M, Venkatesan N, Loh JT, Wong JF, Berger H et al. 2015. The methyltransferase Ezh2 controls cell adhesion and migration through direct methylation of the extranuclear regulatory protein talin. Nat. Immunol. 16:505–16
     [Google Scholar]
  206. 206. 
    Krieg C, Nowicka M, Guglietta S, Schindler S, Hartmann FJ et al. 2018. High-dimensional single-cell analysis predicts response to anti-PD-1 immunotherapy. Nat. Med. 24:144–53
     [Google Scholar]
  207. 207. 
    Sade-Feldman M, Yizhak K, Bjorgaard SL, Ray JP, de Boer CG et al. 2018. Defining T cell states associated with response to checkpoint immunotherapy in melanoma. Cell 175:998–1013.e20
     [Google Scholar]
  208. 208. 
    Miller BC, Sen DR, Al Abosy R, Bi K, Virkud YV et al. 2019. Subsets of exhausted CD8+ T cells differentially mediate tumor control and respond to checkpoint blockade. Nat. Immunol. 20:326–36
     [Google Scholar]
  209. 209. 
    Giesen C, Wang HA, Schapiro D, Zivanovic N, Jacobs A et al. 2014. Highly multiplexed imaging of tumor tissues with subcellular resolution by mass cytometry. Nat. Methods 11:417–22
     [Google Scholar]
  210. 210. 
    Angelo M, Bendall SC, Finck R, Hale MB, Hitzman C et al. 2014. Multiplexed ion beam imaging of human breast tumors. Nat. Med. 20:436–42
     [Google Scholar]
  211. 211. 
    Goltsev Y, Samusik N, Kennedy-Darling J, Bhate S, Hale M et al. 2018. Deep profiling of mouse splenic architecture with CODEX multiplexed imaging. Cell 174:968–81.e15
     [Google Scholar]
  212. 212. 
    Jackson HW, Fischer JR, Zanotelli VRT, Ali HR, Mechera R et al. 2020. The single-cell pathology landscape of breast cancer. Nature 578:615–20
     [Google Scholar]
  213. 213. 
    Keren L, Bosse M, Marquez D, Angoshtari R, Jain S et al. 2018. A structured tumor-immune microenvironment in triple negative breast cancer revealed by multiplexed ion beam imaging. Cell 174:1373–87.e19
     [Google Scholar]
  214. 214. 
    Schurch CM, Bhate SS, Barlow GL, Phillips DJ, Noti L et al. 2020. Coordinated cellular neighborhoods orchestrate antitumoral immunity at the colorectal cancer invasive front. Cell 182:1341–59.e19
     [Google Scholar]
  215. 215. 
    Merritt CR, Ong GT, Church SE, Barker K, Danaher P et al. 2020. Multiplex digital spatial profiling of proteins and RNA in fixed tissue. Nat. Biotechnol. 38:586–99
     [Google Scholar]
  216. 216. 
    Stahl PL, Salmen F, Vickovic S, Lundmark A, Navarro JF et al. 2016. Visualization and analysis of gene expression in tissue sections by spatial transcriptomics. Science 353:78–82
     [Google Scholar]
  217. 217. 
    Toki MI, Merritt CR, Wong PF, Smithy JW, Kluger HM et al. 2019. High-plex predictive marker discovery for melanoma immunotherapy-treated patients using digital spatial profiling. Clin. Cancer Res. 25:5503–12
     [Google Scholar]
  218. 218. 
    Berglund E, Maaskola J, Schultz N, Friedrich S, Marklund M et al. 2018. Spatial maps of prostate cancer transcriptomes reveal an unexplored landscape of heterogeneity. Nat. Commun. 9:2419
     [Google Scholar]
  219. 219. 
    Ji AL, Rubin AJ, Thrane K, Jiang S, Reynolds DL et al. 2020. Multimodal analysis of composition and spatial architecture in human squamous cell carcinoma. Cell 182:497–514.e22
     [Google Scholar]
  220. 220. 
    Galon J, Costes A, Sanchez-Cabo F, Kirilovsky A, Mlecnik B et al. 2006. Type, density, and location of immune cells within human colorectal tumors predict clinical outcome. Science 313:1960–64
     [Google Scholar]
  221. 221. 
    Harlin H, Meng Y, Peterson AC, Zha Y, Tretiakova M et al. 2009. Chemokine expression in melanoma metastases associated with CD8+ T-cell recruitment. Cancer Res 69:3077–85
     [Google Scholar]
  222. 222. 
    Gajewski TF. 2015. The next hurdle in cancer immunotherapy: overcoming the non-T-cell-inflamed tumor microenvironment. Semin. Oncol. 42:663–71
     [Google Scholar]
  223. 223. 
    Havel JJ, Chowell D, Chan TA 2019. The evolving landscape of biomarkers for checkpoint inhibitor immunotherapy. Nat. Rev. Cancer 19:133–50
     [Google Scholar]
  224. 224. 
    Hugo W, Zaretsky JM, Sun L, Song C, Moreno BH et al. 2016. Genomic and transcriptomic features of response to anti-PD-1 therapy in metastatic melanoma. Cell 165:35–44
     [Google Scholar]
  225. 225. 
    Nirschl CJ, Suarez-Farinas M, Izar B, Prakadan S, Dannenfelser R et al. 2017. IFNγ-dependent tissue-immune homeostasis is co-opted in the tumor microenvironment. Cell 170:127–41.e15
     [Google Scholar]
  226. 226. 
    Liu D, Schilling B, Liu D, Sucker A, Livingstone E et al. 2019. Integrative molecular and clinical modeling of clinical outcomes to PD1 blockade in patients with metastatic melanoma. Nat. Med. 25:1916–27
     [Google Scholar]
  227. 227. 
    Auslander N, Zhang G, Lee JS, Frederick DT, Miao B et al. 2018. Robust prediction of response to immune checkpoint blockade therapy in metastatic melanoma. Nat. Med. 24:1545–49
     [Google Scholar]
  228. 228. 
    Jardim DL, Goodman A, de Melo Gagliato D, Kurzrock R. 2021. The challenges of tumor mutational burden as an immunotherapy biomarker. Cancer Cell 39:2154–73
     [Google Scholar]
  229. 229. 
    Larkin J, Chiarion-Sileni V, Gonzalez R, Grob JJ, Cowey CL et al. 2015. Combined nivolumab and ipilimumab or monotherapy in untreated melanoma. N. Engl. J. Med. 373:23–34
     [Google Scholar]
  230. 230. 
    Kooshkaki O, Derakhshani A, Hosseinkhani N, Torabi M, Safaei S et al. 2020. Combination of ipilimumab and nivolumab in cancers: from clinical practice to ongoing clinical trials. Int. J. Mol. Sci. 21:4427
     [Google Scholar]
  231. 231. 
    Larkin J, Chiarion-Sileni V, Gonzalez R, Grob JJ, Rutkowski P et al. 2019. Five-year survival with combined nivolumab and ipilimumab in advanced melanoma. N. Engl. J. Med. 381:1535–46
     [Google Scholar]
  232. 232. 
    Upadhaya S, Hubbard-Lucey VM, Yu JX. 2020. Immuno-oncology drug development forges on despite COVID-19. Nat. Rev. Drug Discov. 19:751–52
     [Google Scholar]
  233. 233. 
    Ribas A, Medina T, Kummar S, Amin A, Kalbasi A et al. 2018. SD-101 in combination with pembrolizumab in advanced melanoma: results of a phase Ib, multicenter study. Cancer Discov 8:1250–57
     [Google Scholar]
  234. 234. 
    Marquez-Rodas I, Longo F, Rodriguez-Ruiz ME, Calles A, Ponce S et al. 2020. Intratumoral nanoplexed poly I:C BO-112 in combination with systemic anti–PD-1 for patients with anti–PD-1–refractory tumors. Sci. Transl. Med. 12:eabb0391
     [Google Scholar]
/content/journals/10.1146/annurev-immunol-070621-030155
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Resistance Mechanisms to Anti-PD Cancer Immunotherapy
Annual Review of Immunology 40, 45 (2022); https://doi.org/10.1146/annurev-immunol-070621-030155
/content/journals/10.1146/annurev-immunol-070621-030155
/content/journals/10.1146/annurev-immunol-070621-030155
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  • Article Type: Review Article

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