Skip to main content

Advertisement

SpringerLink
Log in

Strategies for Predicting Response to Checkpoint Inhibitors

  • CART and Immunotherapy (M Ruella, Section Editor)
  • Published:
Current Hematologic Malignancy Reports Aims and scope Submit manuscript

A Correction to this article was published on 08 November 2018

This article has been updated

Abstract

Purpose of Review

Despite the clinical successes of immune checkpoint blockade across multiple tumor types, many patients do not respond to these therapies or become resistant after an initial response. This underscores the need to improve our understanding of the molecular determinants of response to guide more personalized and rational utilization of these therapies. Here, we describe available biomarkers of checkpoint blockade activity by classifying them into four major categories: tumor-intrinsic, immune microenvironmental, host-related, and dynamic factors.

Recent Findings

The clinical experience accumulated thus far with checkpoint blockade now offers the opportunity to comprehensively study the molecular and immune features associated with response. This is yielding a growing set of biomarkers whose integration will be key to more accurately predict clinical outcome.

Summary

We propose a model for systematic assessment of available baseline and dynamic biomarkers in relationship with patients’ outcomes. This will improve our understanding of the tumor-immune interactions and dynamics that predict a clinical response and will provide key information to develop more personalized and effective treatment strategies.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

Change history

  • 08 November 2018

    The original version of this article unfortunately contained a mistake. The conflict of interest statement was incorrect. The corrected statement is given below.

  • 08 November 2018

    The original version of this article unfortunately contained a mistake. The conflict of interest statement was incorrect. The corrected statement is given below.

References

Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

  1. Leach DR, Krummel MF, Allison JP. Enhancement of antitumor immunity by CTLA-4 blockade. Science. 1996;271:1734–6.

    CAS  PubMed  Google Scholar 

  2. Dong H, Strome SE, Salomao DR, Tamura H, Hirano F, Flies DB, et al. Tumor-associated B7-H1 promotes T-cell apoptosis: a potential mechanism of immune evasion. Nat Med. 2002;8(8):793–800.

    CAS  PubMed  Google Scholar 

  3. Zappasodi R, Merghoub T, Wolchok JD. Emerging concepts for immune checkpoint blockade-based combination therapies. Cancer Cell. 2018;33(4):581–98.

    CAS  PubMed  PubMed Central  Google Scholar 

  4. Hodi FS, O’Day SJ, McDermott DF, Weber RW, Sosman JA, Haanen JB, et al. Improved survival with ipilimumab in patients with metastatic melanoma. N Engl J Med. 2010;363(8):711–23.

    CAS  PubMed  PubMed Central  Google Scholar 

  5. •• Robert C, Thomas L, Bondarenko I, O'Day S, Weber J, Garbe C, et al. Ipilimumab plus dacarbazine for previously untreated metastatic melanoma. N Engl J Med. 2011;364(26):2517–26. This trial together with the one reported in ref 4 demonstrated the clinical benefit of ipilimumab in metastatic melanoma patients and led to the FDA approval of ipilimumab in 2011.

    CAS  Google Scholar 

  6. Ribas A, Wolchok JD. Cancer immunotherapy using checkpoint blockade. Science. 2018;359(6382):1350–5.

    CAS  PubMed  PubMed Central  Google Scholar 

  7. • Snyder A, Makarov V, Merghoub T, Yuan J, Zaretsky JM, Desrichard A, et al. Genetic basis for clinical response to CTLA-4 blockade in melanoma. N Engl J Med. 2014;371(23):2189–99. Pivotal study defining the impact of tumor mutational load on the clinical benefit of CTLA-4 blockade in melanoma patients.

    Google Scholar 

  8. • Rizvi NA, Hellmann MD, Snyder A, Kvistborg P, Makarov V, Havel JJ, et al. Cancer immunology. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer. Science. 2015;348(6230):124–8. Pivotal study defining the impact of tumor mutational load on the clinical benefit of PD-1 blockade in NSCLC patients.

  9. Van Allen EM, Miao D, Schilling B, Shukla SA, Blank C, Zimmer L, et al. Genomic correlates of response to CTLA-4 blockade in metastatic melanoma. Science. 2015;350(6257):207–11.

    PubMed  PubMed Central  Google Scholar 

  10. Hugo W, Zaretsky JM, Sun L, Song C, Moreno BH, Hu-Lieskovan S, et al. Genomic and transcriptomic features of response to anti-PD-1 therapy in metastatic melanoma. Cell. 2016;165(1):35–44.

    CAS  PubMed  PubMed Central  Google Scholar 

  11. • Turajlic S, Litchfield K, Xu H, Rosenthal R, McGranahan N, Reading JL, et al. Insertion-and-deletion-derived tumour-specific neoantigens and the immunogenic phenotype: a pan-cancer analysis. Lancet Oncol. 2017;18(8):1009–21. This study demonstrates the importance of frameshift insertion and deletion mutations in tumor immunogenicity and response to checkpoint blockade.

    CAS  PubMed  Google Scholar 

  12. Hellmann MD, Ciuleanu TE, Pluzanski A, Lee JS, Otterson GA, Audigier-Valette C, et al. Nivolumab plus ipilimumab in lung cancer with a high tumor mutational burden. N Engl J Med. 2018;378:2093–104.

    CAS  PubMed  PubMed Central  Google Scholar 

  13. Rooney MS, Shukla SA, Wu CJ, Getz G, Hacohen N. Molecular and genetic properties of tumors associated with local immune cytolytic activity. Cell. 2015;160(1–2):48–61.

    CAS  PubMed  PubMed Central  Google Scholar 

  14. •• Alexandrov LB, Nik-Zainal S, Wedge DC, Aparicio SAJR, Behjati S, Biankin AV, et al. Signatures of mutational processes in human cancer. Nature. 2013;500:415. This study provides the widest characterization of mutational signatures in human cancers.

  15. •• Le DT, Durham JN, Smith KN, Wang H, Bartlett BR, Aulakh LK, et al. Mismatch-repair deficiency predicts response of solid tumors to PD-1 blockade. Science. 2017;357:409–13. Pivotal study that led to the FDA approval of PD-1 blockade for the treatment of microsatellite-unstable cancers of any origin in 2017.

  16. Le DT, Uram JN, Wang H, Bartlett BR, Kemberling H, Eyring AD, et al. PD-1 Blockade in tumors with mismatch-repair deficiency. N Engl J Med. 2015;372(26):2509–20.

    CAS  PubMed  PubMed Central  Google Scholar 

  17. Holloman WK. Unraveling the mechanism of BRCA2 in homologous recombination. Nat Struct Mol Biol. 2011;18(7):748–54.

    CAS  PubMed  PubMed Central  Google Scholar 

  18. Levine AJ, Oren M. The first 30 years of p53: growing ever more complex. Nat Rev Cancer. 2009;9(10):749–58.

    CAS  PubMed  PubMed Central  Google Scholar 

  19. Dong ZY, Zhong WZ, Zhang XC, Su J, Xie Z, Liu SY, et al. Potential predictive value of TP53 and KRAS mutation status for response to PD-1 blockade immunotherapy in lung adenocarcinoma. Clin Cancer Res. 2017;23(12):3012–24.

    CAS  PubMed  Google Scholar 

  20. Motzer RJ, Escudier B, McDermott DF, George S, Hammers HJ, Srinivas S, et al. Nivolumab versus everolimus in advanced renal-cell carcinoma. N Engl J Med. 2015;373(19):1803–13.

    CAS  PubMed  PubMed Central  Google Scholar 

  21. • McGranahan N, Furness AJ, Rosenthal R, Ramskov S, Lyngaa R, Saini SK, et al. Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade. Science. 2016;351(6280):1463–9. This study demonstrates the importance of tumor-associated neoantigen clonality in the response to checkpoint blockade of melanoma and NSCLC patients.

  22. Thompson RH, Kuntz SM, Leibovich BC, Dong H, Lohse CM, Webster WS, et al. Tumor B7-H1 is associated with poor prognosis in renal cell carcinoma patients with long-term follow-up. Cancer Res. 2006;66(7):3381–5.

    CAS  PubMed  Google Scholar 

  23. Ohigashi Y, Sho M, Yamada Y, Tsurui Y, Hamada K, Ikeda N, et al. Clinical significance of programmed death-1 ligand-1 and programmed death-1 ligand-2 expression in human esophageal cancer. Clin Cancer Res. 2005;11(8):2947–53.

    CAS  PubMed  Google Scholar 

  24. Wu C, Zhu Y, Jiang J, Zhao J, Zhang XG, Xu N. Immunohistochemical localization of programmed death-1 ligand-1 (PD-L1) in gastric carcinoma and its clinical significance. Acta Histochem. 2006;108(1):19–24.

    PubMed  Google Scholar 

  25. Hamanishi J, Mandai M, Iwasaki M, Okazaki T, Tanaka Y, Yamaguchi K, et al. Programmed cell death 1 ligand 1 and tumor-infiltrating CD8+ T lymphocytes are prognostic factors of human ovarian cancer. Proc Natl Acad Sci U S A. 2007;104(9):3360–5.

    CAS  PubMed  PubMed Central  Google Scholar 

  26. •• Topalian SL, Hodi FS, Brahmer JR, Gettinger SN, Smith DC, McDermott DF, et al. Safety, activity, and immune correlates of anti-PD-1 antibody in cancer. N Engl J Med. 2012;366(26):2443–54. Pivotal phase 1 trial with PD-1 blockade in melanoma patients providing the first evidence of the association between PD-L1 expression and anti-tumor activity of PD-1 blockade.

  27. Fehrenbacher L, Spira A, Ballinger M, Kowanetz M, Vansteenkiste J, Mazieres J, et al. Atezolizumab versus docetaxel for patients with previously treated non-small-cell lung cancer (POPLAR): a multicentre, open-label, phase 2 randomised controlled trial. Lancet. 2016;387(10030):1837–46.

    CAS  PubMed  Google Scholar 

  28. Rittmeyer A, Barlesi F, Waterkamp D, Park K, Ciardiello F, von Pawel J, et al. Atezolizumab versus docetaxel in patients with previously treated non-small-cell lung cancer (OAK): a phase 3, open-label, multicentre randomised controlled trial. Lancet. 2017;389(10066):255–65.

    PubMed  Google Scholar 

  29. Apolo AB, Infante JR, Balmanoukian A, Patel MR, Wang D, Kelly K, et al. Avelumab, an anti-programmed death-ligand 1 antibody, in patients with refractory metastatic urothelial carcinoma: results from a multicenter, phase Ib study. J Clin Oncol. 2017;35(19):2117–24.

    CAS  PubMed  PubMed Central  Google Scholar 

  30. Antonia SJ, Villegas A, Daniel D, Vicente D, Murakami S, Hui R, et al. Durvalumab after chemoradiotherapy in stage III non-small-cell lung cancer. N Engl J Med. 2017;377(20):1919–29.

    CAS  PubMed  Google Scholar 

  31. Hahn NM, Powles T, Massard C, Arkenau H-T, Friedlander TW, Hoimes CJ, et al. Updated efficacy and tolerability of durvalumab in locally advanced or metastatic urothelial carcinoma (UC). J Clin Oncol. 2017;35(15_suppl):4525.

    Google Scholar 

  32. Brahmer J, Reckamp KL, Baas P, Crino L, Eberhardt WE, Poddubskaya E, et al. Nivolumab versus docetaxel in advanced squamous-cell non-small-cell lung cancer. N Engl J Med. 2015;373(2):123–35.

    CAS  PubMed  PubMed Central  Google Scholar 

  33. Sharma P, Retz M, Siefker-Radtke A, Baron A, Necchi A, Bedke J, et al. Nivolumab in metastatic urothelial carcinoma after platinum therapy (CheckMate 275): a multicentre, single-arm, phase 2 trial. Lancet Oncol. 2017;18(3):312–22.

    CAS  PubMed  Google Scholar 

  34. Overman MJ, McDermott R, Leach JL, Lonardi S, Lenz HJ, Morse MA, et al. Nivolumab in patients with metastatic DNA mismatch repair-deficient or microsatellite instability-high colorectal cancer (CheckMate 142): an open-label, multicentre, phase 2 study. Lancet Oncol. 2017;18(9):1182–91.

    CAS  PubMed  PubMed Central  Google Scholar 

  35. Roemer MGM, Redd RA, Cader FZ, Pak CJ, Abdelrahman S, Ouyang J, et al. Major histocompatibility complex class II and programmed death ligand 1 expression predict outcome after programmed death 1 blockade in classic Hodgkin lymphoma. J Clin Oncol. 2018;36(10):942–50.

    PubMed  PubMed Central  Google Scholar 

  36. Postow MA, Chesney J, Pavlick AC, Robert C, Grossmann K, McDermott D, et al. Nivolumab and ipilimumab versus ipilimumab in untreated melanoma. N Engl J Med. 2015;372(21):2006–17.

    PubMed  PubMed Central  Google Scholar 

  37. •• Wolchok JD, Chiarion-Sileni V, Gonzalez R, Rutkowski P, Grob JJ, Cowey CL, et al. Overall survival with combined nivolumab and ipilimumab in advanced melanoma. N Engl J Med. 2017;377(14):1345–56. This paper summarizes the 3-year overall survival outcomes of advanced melanoma patients enrolled in a phase 3 trial comparing ipilimumab+nivolumab combination with ipilimumab and nivolumab monotherapies. Longer overall survival was found with combination therapy or with nivolumab monotherapy compared to ipilimumab alone.

  38. Garon EB, Rizvi NA, Hui R, Leighl N, Balmanoukian AS, Eder JP, et al. Pembrolizumab for the treatment of non-small-cell lung cancer. N Engl J Med. 2015;372(21):2018–28.

    PubMed  Google Scholar 

  39. Hirsch FR, McElhinny A, Stanforth D, Ranger-Moore J, Jansson M, Kulangara K, et al. PD-L1 Immunohistochemistry assays for lung cancer: results from phase 1 of the Blueprint PD-L1 IHC Assay Comparison Project. J Thorac Oncol. 2017;12(2):208–22.

    PubMed  Google Scholar 

  40. Reck M, Rodriguez-Abreu D, Robinson AG, Hui R, Csoszi T, Fulop A, et al. Pembrolizumab versus chemotherapy for PD-L1-positive non-small-cell lung cancer. N Engl J Med. 2016;375(19):1823–33.

    CAS  PubMed  Google Scholar 

  41. Marzec M, Zhang Q, Goradia A, Raghunath PN, Liu X, Paessler M, et al. Oncogenic kinase NPM/ALK induces through STAT3 expression of immunosuppressive protein CD274 (PD-L1, B7-H1). Proc Natl Acad Sci U S A. 2008;105(52):20852–7.

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Prestipino A, Emhardt AJ, Aumann K, O’Sullivan D, Gorantla SP, Duquesne S, et al. Oncogenic JAK2(V617F) causes PD-L1 expression, mediating immune escape in myeloproliferative neoplasms. Sci Transl Med. 2018;10(429):eaam7729.

    PubMed  PubMed Central  Google Scholar 

  43. Lastwika KJ, Wilson W 3rd, Li QK, Norris J, Xu H, Ghazarian SR, et al. Control of PD-L1 expression by oncogenic activation of the AKT-mTOR pathway in non-small cell lung cancer. Cancer Res. 2016;76(2):227–38.

    CAS  PubMed  Google Scholar 

  44. Casey SC, Tong L, Li Y, Do R, Walz S, Fitzgerald KN, et al. MYC regulates the antitumor immune response through CD47 and PD-L1. Science. 2016;352(6282):227–31.

    CAS  PubMed  PubMed Central  Google Scholar 

  45. Coelho MA, de Carné Trécesson S, Rana S, Zecchin D, Moore C, Molina-Arcas M, et al. Oncogenic RAS signaling promotes tumor immunoresistance by stabilizing PD-L1 mRNA. Immunity. 2017;47(6):1083–99.e6.

    CAS  PubMed  PubMed Central  Google Scholar 

  46. Parsa AT, Waldron JS, Panner A, Crane CA, Parney IF, Barry JJ, et al. Loss of tumor suppressor PTEN function increases B7-H1 expression and immunoresistance in glioma. Nat Med. 2007;13(1):84–8.

    CAS  PubMed  Google Scholar 

  47. Green MR, Monti S, Rodig SJ, Juszczynski P, Currie T, O’Donnell E, et al. Integrative analysis reveals selective 9p24.1 amplification, increased PD-1 ligand expression, and further induction via JAK2 in nodular sclerosing Hodgkin lymphoma and primary mediastinal large B-cell lymphoma. Blood. 2010;116(17):3268–77.

    CAS  PubMed  PubMed Central  Google Scholar 

  48. Kataoka K, Shiraishi Y, Takeda Y, Sakata S, Matsumoto M, Nagano S, et al. Aberrant PD-L1 expression through 3’-UTR disruption in multiple cancers. Nature. 2016;534(7607):402–6.

    CAS  PubMed  Google Scholar 

  49. •• Ansell SM, Lesokhin AM, Borrello I, Halwani A, Scott EC, Gutierrez M, et al. PD-1 blockade with nivolumab in relapsed or refractory Hodgkin’s lymphoma. N Engl J Med. 2015;372(4):311–9. Pivotal phase I study of nivolumab in relapsed/refractory Hodgkin lymphoma patients demonstrating activity of PD-1 blockade in this disease associated with particularly high PD-L1 and PD-L2 expression levels on Reed-Stenberg Hodgkin lymphoma cells.

    Google Scholar 

  50. Chen R, Zinzani PL, Fanale MA, Armand P, Johnson NA, Brice P, et al. Phase II study of the efficacy and safety of pembrolizumab for relapsed/refractory classic Hodgkin lymphoma. J Clin Oncol. 2017;35(19):2125–32.

    CAS  PubMed  PubMed Central  Google Scholar 

  51. Bach EA, Aguet M, Schreiber RD. The IFN gamma receptor: a paradigm for cytokine receptor signaling. Annu Rev Immunol. 1997;15:563–91.

    CAS  PubMed  Google Scholar 

  52. Fish EN, Platanias LC. Interferon receptor signaling in malignancy: a network of cellular pathways defining biological outcomes. Mol Cancer Res. 2014;12(12):1691–703.

    CAS  PubMed  PubMed Central  Google Scholar 

  53. Dunn GP, Sheehan KCF, Old LJ, Schreiber RD. IFN unresponsiveness in LNCaP cells due to the lack of <em>JAK1</em> gene expression. Cancer Res. 2005;65(8):3447–53.

    CAS  PubMed  Google Scholar 

  54. Gao J, Shi LZ, Zhao H, Chen J, Xiong L, He Q, et al. Loss of IFN-gamma pathway genes in tumor cells as a mechanism of resistance to anti-CTLA-4 therapy. Cell. 2016;167(2):397–404. e9

    CAS  PubMed  PubMed Central  Google Scholar 

  55. Shin DS, Zaretsky JM, Escuin-Ordinas H, Garcia-Diaz A, Hu-Lieskovan S, Kalbasi A, et al. Primary resistance to PD-1 blockade mediated by <em>JAK1/2</em> mutations. Cancer Discovery. 2017;7(2):188–201.

    CAS  PubMed  Google Scholar 

  56. Sade-Feldman M, Jiao YJ, Chen JH, Rooney MS, Barzily-Rokni M, Eliane J-P, et al. Resistance to checkpoint blockade therapy through inactivation of antigen presentation. Nat Commun. 2017;8(1):1136.

    PubMed  PubMed Central  Google Scholar 

  57. • Zaretsky JM, Garcia-Diaz A, Shin DS, Escuin-Ordinas H, Hugo W, Hu-Lieskovan S, et al. Mutations associated with acquired resistance to PD-1 blockade in melanoma. N Engl J Med. 2016;375(9):819–29. This study provides evidence in vivo of clonal selection and outgrowth of tumors with defects in the interferon-receptor signaling pathway and antigen presentation in metastatic melanoma patients developing resistance to PD-1 blockade.

    CAS  Google Scholar 

  58. Gettinger S, Choi J, Hastings K, Truini A, Datar I, Sowell R, et al. Impaired HLA class I antigen processing and presentation as a mechanism of acquired resistance to immune checkpoint inhibitors in lung cancer. Cancer Discovery. 2017;7(12):1420–35.

    CAS  PubMed  PubMed Central  Google Scholar 

  59. Patel SJ, Sanjana NE, Kishton RJ, Eidizadeh A, Vodnala SK, Cam M, et al. Identification of essential genes for cancer immunotherapy. Nature. 2017;548(7669):537–42.

    CAS  PubMed  PubMed Central  Google Scholar 

  60. Manguso RT, Pope HW, Zimmer MD, Brown FD, Yates KB, Miller BC, et al. In vivo CRISPR screening identifies Ptpn2 as a cancer immunotherapy target. Nature. 2017;547(7664):413–8.

    CAS  PubMed  PubMed Central  Google Scholar 

  61. Ozcan M, Janikovits J, von Knebel Doeberitz M, Kloor M. Complex pattern of immune evasion in MSI colorectal cancer. Oncoimmunology. 2018;7(7):e1445453.

    PubMed  PubMed Central  Google Scholar 

  62. McGranahan N, Rosenthal R, Hiley CT, Rowan AJ, Watkins TBK, Wilson GA, et al. Allele-specific HLA loss and immune escape in lung cancer evolution. Cell. 2017;171(6):1259–71. e11

    CAS  PubMed  PubMed Central  Google Scholar 

  63. Sucker A, Zhao F, Pieper N, Heeke C, Maltaner R, Stadtler N, et al. Acquired IFNγ resistance impairs anti-tumor immunity and gives rise to T-cell-resistant melanoma lesions. Nat Commun. 2017;8:15440.

    CAS  PubMed  PubMed Central  Google Scholar 

  64. Vey N, Karlin L, Sadot-Lebouvier S, Broussais F, Berton-Rigaud D, Rey J, et al. A phase 1 study of lirilumab (antibody against killer immunoglobulin-like receptor antibody KIR2D; IPH2102) in patients with solid tumors and hematologic malignancies. Oncotarget. 2018;9(25):17675–88.

    PubMed  PubMed Central  Google Scholar 

  65. Dunn GP, Old LJ, Schreiber RD. The three Es of cancer immunoediting. Annu Rev Immunol. 2004;22:329–60.

    CAS  PubMed  Google Scholar 

  66. Taube JM, Anders RA, Young GD, Xu H, Sharma R, McMiller TL, et al. Colocalization of inflammatory response with B7-h1 expression in human melanocytic lesions supports an adaptive resistance mechanism of immune escape. Sci Transl Med. 2012;4(127):127ra37.

    PubMed  PubMed Central  Google Scholar 

  67. Spranger S, Luke JJ, Bao R, Zha Y, Hernandez KM, Li Y, 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 U S A. 2016;113(48):E7759–E68.

    CAS  PubMed  PubMed Central  Google Scholar 

  68. Bindea G, Mlecnik B, Tosolini M, Kirilovsky A, Waldner M, Obenauf AC, et al. Spatiotemporal dynamics of intratumoral immune cells reveal the immune landscape in human cancer. Immunity. 2013;39(4):782–95.

    CAS  PubMed  Google Scholar 

  69. Fridman WH, Pages F, Sautes-Fridman C, Galon J. The immune contexture in human tumours: impact on clinical outcome. Nat Rev Cancer. 2012;12(4):298–306.

    CAS  PubMed  Google Scholar 

  70. Pages F, Kirilovsky A, Mlecnik B, Asslaber M, Tosolini M, Bindea G, et al. In situ cytotoxic and memory T cells predict outcome in patients with early-stage colorectal cancer. J Clin Oncol. 2009;27(35):5944–51.

    CAS  PubMed  Google Scholar 

  71. Galon J, Costes A, Sanchez-Cabo F, Kirilovsky A, Mlecnik B, Lagorce-Pages C, et al. Type, density, and location of immune cells within human colorectal tumors predict clinical outcome. Science. 2006;313(5795):1960–4.

    CAS  PubMed  Google Scholar 

  72. Mlecnik B, Bindea G, Angell HK, Maby P, Angelova M, Tougeron D, et al. Integrative analyses of colorectal cancer show immunoscore is a stronger predictor of patient survival than microsatellite instability. Immunity. 2016;44(3):698–711.

    CAS  PubMed  Google Scholar 

  73. • Pages F, Mlecnik B, Marliot F, Bindea G, Ou FS, Bifulco C, et al. International validation of the consensus Immunoscore for the classification of colon cancer: a prognostic and accuracy study. Lancet. 2018;391(10135):2128–39. This study provides confirmatory evidence on a large-scale basis of the prognostic value of the Immunoscore in colorectal carcinoma patients.

  74. • Tumeh PC, Harview CL, Yearley JH, Shintaku IP, Taylor EJ, Robert L, et al. PD-1 blockade induces responses by inhibiting adaptive immune resistance. Nature. 2014;515(7528):568–71. This study demonstrates the importance of baseline T-cell density and localization in the tumor bed in the response of metastatic melanoma patients to PD-1/PD-L1 blockade.

    CAS  PubMed  PubMed Central  Google Scholar 

  75. Hamid O, Schmidt H, Nissan A, Ridolfi L, Aamdal S, Hansson J, et al. A prospective phase II trial exploring the association between tumor microenvironment biomarkers and clinical activity of ipilimumab in advanced melanoma. J Transl Med. 2011;9(1):204.

    CAS  PubMed  PubMed Central  Google Scholar 

  76. Ji R-R, Chasalow SD, Wang L, Hamid O, Schmidt H, Cogswell J, et al. An immune-active tumor microenvironment favors clinical response to ipilimumab. Cancer Immunol Immunother. 2012;61(7):1019–31.

    CAS  PubMed  Google Scholar 

  77. Kitano S, Postow MA, Ziegler CG, Kuk D, Panageas KS, Cortez C, et al. Computational algorithm-driven evaluation of monocytic myeloid-derived suppressor cell frequency for prediction of clinical outcomes. Cancer Immunology Research. 2014;2(8):812–21.

    CAS  PubMed  PubMed Central  Google Scholar 

  78. Westin JR, Chu F, Zhang M, Fayad LE, Kwak LW, Fowler N, et al. Safety and activity of PD1 blockade by pidilizumab in combination with rituximab in patients with relapsed follicular lymphoma: a single group, open-label, phase 2 trial. Lancet Oncol. 2014;15(1):69–77.

    CAS  PubMed  Google Scholar 

  79. Powles T, Eder JP, Fine GD, Braiteh FS, Loriot Y, Cruz C, et al. MPDL3280A (anti-PD-L1) treatment leads to clinical activity in metastatic bladder cancer. Nature. 2014;515(7528):558–62.

    CAS  PubMed  Google Scholar 

  80. De Henau O, Rausch M, Winkler D, Campesato LF, Liu C, Cymerman DH, et al. Overcoming resistance to checkpoint blockade therapy by targeting PI3Kgamma in myeloid cells. Nature. 2016;539(7629):443–7.

    PubMed  PubMed Central  Google Scholar 

  81. Holmgaard RB, Zamarin D, Lesokhin A, Merghoub T, Wolchok JD. Targeting myeloid-derived suppressor cells with colony stimulating factor-1 receptor blockade can reverse immune resistance to immunotherapy in indoleamine 2,3-dioxygenase-expressing tumors. EBioMedicine. 2016;6:50–8.

    PubMed  PubMed Central  Google Scholar 

  82. Kroemer G, Zitvogel L. The breakthrough of the microbiota. Nat Rev Immunol. 2018;18:87.

    CAS  PubMed  Google Scholar 

  83. Gopalakrishnan V, Helmink BA, Spencer CN, Reuben A, Wargo JA. The influence of the gut microbiome on cancer, immunity, and cancer immunotherapy. Cancer Cell. 2018;33(4):570–80.

    CAS  PubMed  PubMed Central  Google Scholar 

  84. • Vetizou M, Pitt JM, Daillere R, Lepage P, Waldschmitt N, Flament C, et al. Anticancer immunotherapy by CTLA-4 blockade relies on the gut microbiota. Science. 2015;350(6264):1079–84. Landmark study (together with Ref 85) showing the impact of gut microbiome on the anti-tumor activity of checkpoint blockade in mice.

    CAS  PubMed  PubMed Central  Google Scholar 

  85. • Sivan A, Corrales L, Hubert N, Williams JB, Aquino-Michaels K, Earley ZM, et al. Commensal Bifidobacterium promotes antitumor immunity and facilitates anti-PD-L1 efficacy. Science. 2015;350(6264):1084–9. Landmark study (together with Ref 84) showing the impact of gut microbiome on the anti-tumor activity of checkpoint blockade in mice.

    CAS  PubMed  PubMed Central  Google Scholar 

  86. Routy B, Le Chatelier E, Derosa L, Duong CPM, Alou MT, Daillere R, et al. Gut microbiome influences efficacy of PD-1-based immunotherapy against epithelial tumors. Science. 2018;359(6371):91–7.

    CAS  PubMed  Google Scholar 

  87. Chaput N, Lepage P, Coutzac C, Soularue E, Le Roux K, Monot C, et al. Baseline gut microbiota predicts clinical response and colitis in metastatic melanoma patients treated with ipilimumab. Ann Oncol. 2017;28(6):1368–79.

    CAS  PubMed  Google Scholar 

  88. Frankel AE, Coughlin LA, Kim J, Froehlich TW, Xie Y, Frenkel EP, 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. 2017;19(10):848–55.

    CAS  PubMed  PubMed Central  Google Scholar 

  89. Gopalakrishnan V, Spencer CN, Nezi L, Reuben A, Andrews MC, Karpinets TV, et al. Gut microbiome modulates response to anti-PD-1 immunotherapy in melanoma patients. Science. 2018;359(6371):97–103.

    CAS  PubMed  Google Scholar 

  90. Matson V, Fessler J, Bao R, Chongsuwat T, Zha Y, Alegre ML, et al. The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients. Science. 2018;359(6371):104–8.

    CAS  PubMed  PubMed Central  Google Scholar 

  91. Dubin K, Callahan MK, Ren B, Khanin R, Viale A, Ling L, et al. Intestinal microbiome analyses identify melanoma patients at risk for checkpoint-blockade-induced colitis. Nat Commun. 2016;7:10391.

    CAS  PubMed  PubMed Central  Google Scholar 

  92. Mellor JD, Brown MP, Irving HR, Zalcberg JR, Dobrovic A. A critical review of the role of Fc gamma receptor polymorphisms in the response to monoclonal antibodies in cancer. J Hematol Oncol. 2013;6:1.

    CAS  PubMed  PubMed Central  Google Scholar 

  93. Bulliard Y, Jolicoeur R, Windman M, Rue SM, Ettenberg S, Knee DA, et al. Activating Fc gamma receptors contribute to the antitumor activities of immunoregulatory receptor-targeting antibodies. J Exp Med. 2013;210(9):1685–93.

    CAS  PubMed  PubMed Central  Google Scholar 

  94. Simpson TR, Li F, Montalvo-Ortiz W, Sepulveda MA, Bergerhoff K, Arce F, et al. Fc-dependent depletion of tumor-infiltrating regulatory T cells co-defines the efficacy of anti-CTLA-4 therapy against melanoma. J Exp Med. 2013;210(9):1695–710.

    CAS  PubMed  PubMed Central  Google Scholar 

  95. Romano E, Kusio-Kobialka M, Foukas PG, Baumgaertner P, Meyer C, Ballabeni P, et al. Ipilimumab-dependent cell-mediated cytotoxicity of regulatory T cells ex vivo by nonclassical monocytes in melanoma patients. Proc Natl Acad Sci U S A. 2015;112(19):6140–5.

    CAS  PubMed  PubMed Central  Google Scholar 

  96. Tarhini AA, Edington H, Butterfield LH, Lin Y, Shuai Y, Tawbi H, et al. Immune monitoring of the circulation and the tumor microenvironment in patients with regionally advanced melanoma receiving neoadjuvant ipilimumab. PLoS One. 2014;9(2):e87705.

    PubMed  PubMed Central  Google Scholar 

  97. Arce Vargas F, Furness AJS, Litchfield K, Joshi K, Rosenthal R, Ghorani E, et al. Fc effector function contributes to the activity of human anti-CTLA-4 antibodies. Cancer Cell. 2018;33(4):649–63. e4

    CAS  PubMed  PubMed Central  Google Scholar 

  98. Robinson J, Halliwell JA, Hayhurst JD, Flicek P, Parham P, Marsh SG. The IPD and IMGT/HLA database: allele variant databases. Nucleic Acids Res. 2015;43(Database issue):D423–31.

    CAS  PubMed  Google Scholar 

  99. Chowell D, Morris LGT, Grigg CM, Weber JK, Samstein RM, Makarov V, et al. Patient HLA class I genotype influences cancer response to checkpoint blockade immunotherapy. Science. 2018;359(6375):582–7.

    CAS  PubMed  Google Scholar 

  100. Delyon J, Mateus C, Lefeuvre D, Lanoy E, Zitvogel L, Chaput N, et al. Experience in daily practice with ipilimumab for the treatment of patients with metastatic melanoma: an early increase in lymphocyte and eosinophil counts is associated with improved survival. Ann Oncol. 2013;24(6):1697–703.

    CAS  PubMed  Google Scholar 

  101. Ku GY, Yuan J, Page DB, Schroeder SE, Panageas KS, Carvajal RD, et al. Single-institution experience with ipilimumab in advanced melanoma patients in the compassionate use setting: lymphocyte count after 2 doses correlates with survival. Cancer. 2010;116(7):1767–75.

    CAS  PubMed  Google Scholar 

  102. Martens A, Wistuba-Hamprecht K, Yuan J, Postow MA, Wong P, Capone M, et al. Increases in absolute lymphocytes and circulating CD4+ and CD8+ T cells are associated with positive clinical outcome of melanoma patients treated with ipilimumab. Clin Cancer Res. 2016;22(19):4848–58.

    CAS  PubMed  PubMed Central  Google Scholar 

  103. Wang W, Yu D, Sarnaik AA, Yu B, Hall M, Morelli D, et al. Biomarkers on melanoma patient T Cells associated with ipilimumab treatment. J Transl Med. 2012;10(1):146.

    CAS  PubMed  PubMed Central  Google Scholar 

  104. Carthon BC, Wolchok JD, Yuan J, Kamat A, Ng Tang DS, Sun J, et al. Preoperative CTLA-4 blockade: tolerability and immune monitoring in the setting of a presurgical clinical trial. Clin Cancer Res. 2010;16(10):2861–71.

    CAS  PubMed  PubMed Central  Google Scholar 

  105. Ng Tang D, Shen Y, Sun J, Wen S, Wolchok JD, Yuan J, et al. Increased frequency of ICOS+ CD4 T cells as a pharmacodynamic biomarker for anti-CTLA-4 therapy. Cancer Immunology Research. 2013;1(4):229–34.

    PubMed  Google Scholar 

  106. Cassidy MR, Wolchok RE, Zheng J, Panageas KS, Wolchok JD, Coit D, et al. Neutrophil to lymphocyte ratio is associated with outcome during ipilimumab treatment. EBioMedicine. 2017;18:56–61.

    PubMed  PubMed Central  Google Scholar 

  107. Huang AC, Postow MA, Orlowski RJ, Mick R, Bengsch B, Manne S, et al. T-cell invigoration to tumour burden ratio associated with anti-PD-1 response. Nature. 2017;545(7652):60–5.

    CAS  PubMed  PubMed Central  Google Scholar 

  108. Zappasodi R, Budhu S, Hellmann MD, Postow MA, Senbabaoglu Y, Manne S, et al. Non-conventional inhibitory CD4(+)Foxp3(−)PD-1(hi) T cells as a biomarker of immune checkpoint blockade activity. Cancer Cell. 2018;33(6):1017–32. e7

    CAS  PubMed  PubMed Central  Google Scholar 

  109. Cha E, Klinger M, Hou Y, Cummings C, Ribas A, Faham M, et al. Improved survival with T cell clonotype stability after anti-CTLA-4 treatment in cancer patients. Sci Transl Med. 2014;6(238):238ra70.

    PubMed  PubMed Central  Google Scholar 

  110. Robert L, Tsoi J, Wang X, Emerson R, Homet B, Chodon T, et al. CTLA4 blockade broadens the peripheral T-cell receptor repertoire. Clin Cancer Res. 2014;20(9):2424–32.

    CAS  PubMed  PubMed Central  Google Scholar 

  111. Postow MA, Manuel M, Wong P, Yuan J, Dong Z, Liu C, et al. Peripheral T cell receptor diversity is associated with clinical outcomes following ipilimumab treatment in metastatic melanoma. J Immunother Cancer. 2015;3:23.

    PubMed  PubMed Central  Google Scholar 

  112. Hosoi A, Takeda K, Nagaoka K, Iino T, Matsushita H, Ueha S, et al. Increased diversity with reduced “diversity evenness” of tumor infiltrating T-cells for the successful cancer immunotherapy. Sci Rep. 2018;8(1):1058.

    PubMed  PubMed Central  Google Scholar 

  113. Oh DY, Cham J, Zhang L, Fong G, Kwek SS, Klinger M, et al. Immune toxicities elicted by CTLA-4 blockade in cancer patients are associated with early diversification of the T-cell repertoire. Cancer Res. 2017;77(6):1322–30.

    CAS  PubMed  Google Scholar 

  114. Chen P-L, Roh W, Reuben A, Cooper ZA, Spencer CN, Prieto PA, 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 Discovery. 2016;6:827–37.

    PubMed  PubMed Central  Google Scholar 

  115. Riaz N, Havel JJ, Makarov V, Desrichard A, Urba WJ, Sims JS, et al. Tumor and microenvironment evolution during immunotherapy with nivolumab. Cell. 2017;171(4):934–49. e15

    CAS  PubMed  PubMed Central  Google Scholar 

  116. Wartewig T, Kurgyis Z, Keppler S, Pechloff K, Hameister E, Ollinger R, et al. PD-1 is a haploinsufficient suppressor of T cell lymphomagenesis. Nature. 2017;552(7683):121–5.

    CAS  PubMed  PubMed Central  Google Scholar 

  117. Ratner L, Waldmann TA, Janakiram M, Brammer JE. Rapid progression of adult T-cell leukemia–lymphoma after PD-1 inhibitor therapy. N Engl J Med. 2018;378(20):1947–8.

    PubMed  Google Scholar 

  118. Jimenez-Sanchez A, Memon D, Pourpe S, Veeraraghavan H, Li Y, Vargas HA, et al. Heterogeneous tumor-immune microenvironments among differentially growing metastases in an ovarian cancer patient. Cell. 2017;170(5):927–38. e20

    CAS  PubMed  PubMed Central  Google Scholar 

  119. Blank CU, Haanen JB, Ribas A, Schumacher TN. Cancer immunology. The “cancer immunogram”. Science. 2016;352(6286):658–60.

    CAS  PubMed  Google Scholar 

Download references

Acknowledgements

We would like to thank the Swim Across America, Ludwig Institute for Cancer Research, the Parker Institute for Cancer Immunotherapy, and the NIH/NCI Cancer Center Support Grant (P30 CA008748) for their support.

Author information

Authors and Affiliations

  1. Ludwig Collaborative and Swim Across America Laboratory, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA

    Roberta Zappasodi, Jedd D. Wolchok & Taha Merghoub

  2. Parker Institute for Cancer Immunotherapy, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA

    Roberta Zappasodi, Jedd D. Wolchok & Taha Merghoub

  3. Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA

    Jedd D. Wolchok & Taha Merghoub

  4. Weill Cornell Medicine, New York, NY, 10065, USA

    Jedd D. Wolchok

Authors
  1. Roberta Zappasodi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jedd D. Wolchok
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Taha Merghoub
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Taha Merghoub.

Ethics declarations

Conflict of Interest

The authors declare that they have no conflict of interest.

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by any of the authors.

Additional information

This article is part of the Topical Collection on CART and Immunotherapy

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zappasodi, R., Wolchok, J.D. & Merghoub, T. Strategies for Predicting Response to Checkpoint Inhibitors. Curr Hematol Malig Rep 13, 383–395 (2018). https://doi.org/10.1007/s11899-018-0471-9

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11899-018-0471-9

Keywords

Search

Navigation