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  • Perspective
  • Published:

Determining T-cell specificity to understand and treat disease

A Publisher Correction to this article was published on 02 January 2018

This article has been updated

Abstract

Adaptive immune responses and immunopathogeneses are based on the ability of T cells to respond to specific antigens. Consequently, understanding T-cell recognition patterns in health and disease involves studying the complexity and genetic heterogeneity of the antigen recognition pathway, which includes both T-cell receptors and the antigen-presentation machinery. In this Perspective, we overview the development and use of technologies for assessing T-cell recognition in a clinical context, and discuss how knowledge of T-cell recognition pathways can be critical before, during and after disease treatment. The ability to assess T-cell-mediated immunity in individual patients during disease progression might enable the identification of patient-specific biomarkers that predict therapeutic efficacy and response. Effective strategies for the complex analysis of T-cell specificity in clinical settings are highly desirable and could complement current approaches for the monitoring of therapy responses.

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Fig. 1: Antigen presentation and T-cell recognition pathways.
Fig. 2: MHC multimer technology for probing antigen specificity.
Fig. 3: Using epitope mapping to gain insights into disease mechanisms.
Fig. 4: Translational applications.

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Change history

  • 02 January 2018

    In the version of this Perspective originally published, in Fig. 4, in the schematic for the DNA barcoded multimers, the barcodes were missing; they have now been included and the figure updated in all versions of the Perspective.

References

  1. Chien, Y. H. & Davis, M. M. How alpha beta T-cell receptors ‘see’ peptide/MHC complexes. Immunol. Today 14, 597–602 (1993).

    Article  CAS  PubMed  Google Scholar 

  2. Germain, R. N. MHC-dependent antigen processing and peptide presentation: providing ligands for T lymphocyte activation. Cell 76, 287–299 (1994).

    Article  CAS  PubMed  Google Scholar 

  3. Pape, K. A. et al. Use of adoptive transfer of T-cell-antigen-receptor-transgenic T cell for the study of T-cell activation in vivo. Immunol. Rev. 156, 67–78 (1997).

    Article  CAS  PubMed  Google Scholar 

  4. Hogquist, K. A. et al. T cell receptor antagonist peptides induce positive selection. Cell 76, 17–27 (1994).

    Article  CAS  PubMed  Google Scholar 

  5. Robey, E. A. et al. The level of CD8 expression can determine the outcome of thymic selection. Cell 69, 1089–1096 (1992).

    Article  CAS  PubMed  Google Scholar 

  6. Akram, A. & Inman, R. D. Immunodominance: a pivotal principle in host response to viral infections. Clin. Immunol. 143, 99–115 (2012).

    Article  CAS  PubMed  Google Scholar 

  7. Altman, J. D. et al. Phenotypic analysis of antigen-specific T lymphocytes. Science 274, 94–96 (1996).

    Article  CAS  PubMed  Google Scholar 

  8. Davis, M. M., Altman, J. D. & Newell, E. W. Interrogating the repertoire: broadening the scope of peptide-MHC multimer analysis. Nat. Rev. Immunol. 11, 551–558 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Bentzen, A. K. & Hadrup, S. R. Evolution of MHC-based technologies used for detection of antigen-responsive T cells. Cancer Immunol. Immunother. 66, 657–666 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Robbins, P. F. et al. Tumor regression in patients with metastatic synovial cell sarcoma and melanoma using genetically engineered lymphocytes reactive with NY-ESO-1. J. Clin. Oncol. 29, 917–924 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  11. Morgan, R. A. et al. Cancer regression and neurological toxicity following anti-MAGE-A3 TCR gene therapy. J. Immunother. 36, 133–151 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Neuenhahn, M. et al. Transfer of minimally manipulated CMV-specific T cells from stem cell or third-party donors to treat CMV infection after allo-HSCT. Leukemia https://doi.org/10.1038/leu.2017.16 (2017).

  13. Cobbold, M. et al. Adoptive transfer of cytomegalovirus-specific CTL to stem cell transplant patients after selection by HLA-peptide tetramers. J. Exp. Med. 202, 379–386 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Wambre, E. et al. Specific immunotherapy modifies allergen-specific CD4+ T-cell responses in an epitope-dependent manner. J. Allergy Clin. Immunol. 133, 872–879.e7 (2014).

    Article  CAS  PubMed  Google Scholar 

  15. Odegard, J. M., Nepom, G. T. & Wambre, E. Biomarkers for antigen immunotherapy in allergy and type 1 diabetes. Clin. Immunol. 161, 44–50 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Radvanyi, L. G. et al. Specific lymphocyte subsets predict response to adoptive cell therapy using expanded autologous tumor-infiltrating lymphocytes in metastatic melanoma patients. Clin. Cancer Res. 18, 6758–6770 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Darrah, P. A. et al. Multifunctional TH1 cells define a correlate of vaccine-mediated protection against Leishmania major. Nat. Med. 13, 843–850 (2007).

    Article  CAS  PubMed  Google Scholar 

  18. Lee, P. P. et al. Characterization of circulating T cells specific for tumor-associated antigens in melanoma patients. Nat. Med. 5, 677–685 (1999).

    Article  CAS  PubMed  Google Scholar 

  19. Coulie, P. G., Van den Eynde, B. J., van der Bruggen, P. & Boon, T. Tumour antigens recognized by T lymphocytes: at the core of cancer immunotherapy. Nat. Rev. Cancer 14, 135–146 (2014).

    Article  CAS  PubMed  Google Scholar 

  20. Coulie, P. G. et al. A new gene coding for a differentiation antigen recognized by autologous cytolytic T lymphocytes on HLA-A2 melanomas. J. Exp. Med. 180, 35–42 (1994).

    Article  CAS  PubMed  Google Scholar 

  21. Van Nuffel, A. M. T. et al. Intravenous and intradermal TriMix-dendritic cell therapy results in a broad T-cell response and durable tumor response in a chemorefractory stage IV-M1c melanoma patient. Cancer Immunol. Immunother. 61, 1033–1043 (2012).

    Article  PubMed  Google Scholar 

  22. 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 

  23. 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 

  24. Rizvi, N. A. et al. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer. Science 348, 124–128 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. 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  CAS  Google Scholar 

  26. 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 (2014).

    Article  CAS  Google Scholar 

  27. Van Allen, E. M. et al. Genomic correlates of response to CTLA-4 blockade in metastatic melanoma. Science 350, 207–211 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  28. Strønen, E. et al. Targeting of cancer neoantigens with donor-derived T cell receptor repertoires. Science 352, 1337–1341 (2016).

    Article  PubMed  CAS  Google Scholar 

  29. 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  Google Scholar 

  30. McGranahan, N. et al. Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade. Science 351, 1463–1469 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. van Rooij, N. et al. Tumor exome analysis reveals neoantigen-specific T-cell reactivity in an ipilimumab-responsive melanoma. J. Clin. Oncol. 31, e439–e442 (2013).

    Article  PubMed  Google Scholar 

  32. 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 

  33. Bentzen, A. K. et al. Large-scale detection of antigen-specific T cells using peptide-MHC-I multimers labeled with DNA barcodes. Nat. Biotechnol. 34, 1037–1045 (2016).

    Article  CAS  PubMed  Google Scholar 

  34. Wick, D. A. et al. Surveillance of the tumor mutanome by T cells during progression from primary to recurrent ovarian cancer. Clin. Cancer Res. 20, 1125–1134 (2014).

    Article  CAS  PubMed  Google Scholar 

  35. Rajasagi, M. et al. Systematic identification of personal tumor-specific neoantigens in chronic lymphocytic leukemia. Blood 124, 453–462 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Verdegaal, E. M. E. et al. Neoantigen landscape dynamics during human melanoma–T cell interactions. Nature 536, 91–95 (2016).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  38. Rizvi, N. A. et al. Cancer immunology. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer. Science 348, 124–128 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Gubin, M. M. et al. Checkpoint blockade cancer immunotherapy targets tumour-specific mutant antigens. Nature 515, 577–581 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. 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 

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

    Article  CAS  PubMed  Google Scholar 

  42. 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 

  43. Gerlinger, M. et al. Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. N. Engl. J. Med. 366, 883–892 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Palmer, D. C. et al. Cish actively silences TCR signaling in CD8+ T cells to maintain tumor tolerance. J. Exp. Med. 212, 2095–2113 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Chidrawar, S. et al. Cytomegalovirus-seropositivity has a profound influence on the magnitude of major lymphoid subsets within healthy individuals. Clin. Exp. Immunol. 155, 423–432 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Gordon, C. L. et al. Tissue reservoirs of antiviral T cell immunity in persistent human CMV infection. J. Exp. Med. 214, 651–667 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  47. Colugnati, F. A. B., Staras, S. A. S., Dollard, S. C. & Cannon, M. J. Incidence of cytomegalovirus infection among the general population and pregnant women in the United States. BMC Infect. Dis. 7, 71 (2007).

    Article  PubMed  PubMed Central  Google Scholar 

  48. Hadrup, S. R. et al. Longitudinal studies of clonally expanded CD8 T cells reveal a repertoire shrinkage predicting mortality and an increased number of dysfunctional cytomegalovirus-specific T cells in the very elderly. J. Immunol. 176, 2645–2653 (2006).

    Article  CAS  PubMed  Google Scholar 

  49. Furman, D. et al. Cytomegalovirus infection enhances the immune response to influenza. Sci. Transl. Med. 7, 281ra43 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  50. Kamphorst, A. O. et al. Rescue of exhausted CD8 T cells by PD-1-targeted therapies is CD28-dependent. Science 355, 1423–1427 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Williams, M. A. et al. Cutting edge: persistent viral infection prevents tolerance induction and escapes immune control following CD28/CD40 blockade-based regimen. J. Immunol. 169, 5387–5391 (2002).

    Article  CAS  PubMed  Google Scholar 

  52. Lanzavecchia, A. & Sallusto, F. Understanding the generation and function of memory T cell subsets. Curr. Opin. Immunol. 17, 326–332 (2005).

    Article  CAS  PubMed  Google Scholar 

  53. Sylwester, A. W. et al. Broadly targeted human cytomegalovirus-specific CD4+ and CD8+ T cells dominate the memory compartments of exposed subjects. J. Exp. Med. 202, 673–685 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Lindestam Arlehamn, C. S. et al. A quantitative analysis of complexity of human pathogen-specific CD4 T cell responses in healthy M. tuberculosis infected South Africans. PLoS Pathog. 12, e1005760 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  55. Lindestam Arlehamn, C. S., Lewinsohn, D., Sette, A. & Lewinsohn, D. Antigens for CD4 and CD8 T cells in tuberculosis. Cold Spring Harb. Perspect. Med. 4, a018465 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  56. Höhn, H. et al. MHC class II tetramer guided detection of Mycobacterium tuberculosis-specific CD4+ T cells in peripheral blood from patients with pulmonary tuberculosis. Scand. J. Immunol. 65, 467–478 (2007).

    Article  PubMed  CAS  Google Scholar 

  57. Newell, E. W. et al. Combinatorial tetramer staining and mass cytometry analysis facilitate T-cell epitope mapping and characterization. Nat. Biotechnol. 31, 623–629 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Kracht, M. J. L. et al. Autoimmunity against a defective ribosomal insulin gene product in type 1 diabetes. Nat. Med. 23, 501–507 (2017).

    Article  CAS  PubMed  Google Scholar 

  59. Roep, B. O., Kracht, M. J., van Lummel, M. & Zaldumbide, A. A roadmap of the generation of neoantigens as targets of the immune system in type 1 diabetes. Curr. Opin. Immunol. 43, 67–73 (2016).

    Article  CAS  PubMed  Google Scholar 

  60. Salou, M., Nicol, B., Garcia, A. & Laplaud, D.-A. Involvement of CD8+ T cells in multiple sclerosis. Front. Immunol. 6, 604 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  61. McGinty, J. W. et al. Recognition of posttranslationally modified GAD65 epitopes in subjects with type 1 diabetes. Diabetes 63, 3033–3040 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  62. Rondas, D. et al. Citrullinated glucose-regulated protein 78 is an autoantigen in type 1 diabetes. Diabetes 64, 573–586 (2015).

    Article  CAS  PubMed  Google Scholar 

  63. McLaughlin, R. J., Spindler, M. P., van Lummel, M. & Roep, B. O. Where, how, and when: positioning posttranslational modification within type 1 diabetes pathogenesis. Curr. Diab. Rep. 16, 63 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  64. Suárez-Fueyo, A., Bradley, S. J. & Tsokos, G. C. T cells in systemic Lupus Erythematosus. Curr. Opin. Immunol. 43, 32–38 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  65. Carvalheiro, H., da Silva, J. A. P. & Souto-Carneiro, M. M. Potential roles for CD8+ T cells in rheumatoid arthritis. Autoimmun. Rev. 12, 401–409 (2013).

    Article  CAS  PubMed  Google Scholar 

  66. Andersen, R. S. et al. High frequency of T cells specific for cryptic epitopes in melanoma patients. Oncoimmunology 2, e25374 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  67. Spath, S. et al. Dysregulation of the cytokine GM-CSF induces spontaneous phagocyte invasion and immunopathology in the central nervous system. Immunity 46, 245–260 (2017).

    Article  CAS  PubMed  Google Scholar 

  68. Yang, J. et al. Expression of HLA-DP0401 molecules for identification of DP0401 restricted antigen specific T cells. J. Clin. Immunol. 25, 428–436 (2005).

    Article  CAS  PubMed  Google Scholar 

  69. Archila, L. L. D. & Kwok, W. W. Tetramer-guided epitope mapping: a rapid approach to identify HLA-restricted T-cell epitopes from composite allergens. Methods Mol. Biol. 1592, 199–209 (2017).

    Article  PubMed  Google Scholar 

  70. Hinz, D. et al. Lack of allergy to timothy grass pollen is not a passive phenomenon but associated with the allergen-specific modulation of immune reactivity. Clin. Exp. Allergy 46, 705–719 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Wambre, E., James, E. A. & Kwok, W. W. Characterization of CD4+ T cell subsets in allergy. Curr. Opin. Immunol. 24, 700–706 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Lu, Y.-C. et al. Efficient identification of mutated cancer antigens recognized by T cells associated with durable tumor regressions. Clin. Cancer Res. 20, 3401–3410 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Birnbaum, M. E., Dong, S. & Garcia, K. C. Diversity-oriented approaches for interrogating T-cell receptor repertoire, ligand recognition, and function. Immunol. Rev. 250, 82–101 (2012).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  74. Birnbaum, M. E. et al. Deconstructing the peptide-MHC specificity of T cell recognition. Cell 157, 1073–1087 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Yadav, M. et al. Predicting immunogenic tumour mutations by combining mass spectrometry and exome sequencing. Nature 515, 572–576 (2014).

    Article  CAS  PubMed  Google Scholar 

  76. Newell, E. W. Higher throughput methods of identifying T cell epitopes for studying outcomes of altered antigen processing and presentation. Front. Immunol. 4, 430 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  77. Vigneron, N. et al. An antigenic peptide produced by peptide splicing in the proteasome. Science 304, 587–590 (2004).

    Article  CAS  PubMed  Google Scholar 

  78. Liepe, J. et al. A large fraction of HLA class I ligands are proteasome-generated spliced peptides. Science 354, 354–358 (2016).

    Article  CAS  PubMed  Google Scholar 

  79. Schumacher, T. N. M. et al. Peptide selection by MHC class I molecules. Nature 350, 703–706 (1991).

    Article  CAS  PubMed  Google Scholar 

  80. Nielsen, M., Justesen, S., Lund, O., Lundegaard, C. & Buus, S. NetMHCIIpan-2.0—Improved pan-specific HLA-DR predictions using a novel concurrent alignment and weight optimization training procedure. Immunome Res. 6, 9 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  81. Andreatta, M. et al. Accurate pan-specific prediction of peptide-MHC class II binding affinity with improved binding core identification. Immunogenetics 67, 641–650 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Braendstrup, P. et al. MHC class II tetramers made from isolated recombinant α and β chains refolded with affinity-tagged peptides. PLoS ONE 8, e73648 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Crawford, F., Kozono, H., White, J., Marrack, P. & Kappler, J. Detection of antigen-specific T cells with multivalent soluble class II MHC covalent peptide complexes. Immunity 8, 675–682 (1998).

    Article  CAS  PubMed  Google Scholar 

  84. Rahim, A. et al. Potent T cell activation with dimeric peptide–major histocompatibility complex class II ligand: the role of CD4 coreceptor. J. Exp. Med. 188, 1633–1640 (1998).

    Article  Google Scholar 

  85. Toebes, M. et al. Design and use of conditional MHC class I ligands. Nat. Med. 12, 246–251 (2006).

    Article  CAS  PubMed  Google Scholar 

  86. Saini, S. K. et al. Dipeptides catalyze rapid peptide exchange on MHC class I molecules. Proc. Natl Acad. Sci. USA 112, 202–207 (2015).

    Article  CAS  PubMed  Google Scholar 

  87. Leisner, C. et al. One-pot, mix-and-read peptide-MHC tetramers. PLoS ONE 3, e1678 (2008).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  88. Day, C. L. et al. Ex vivo analysis of human memory CD4 T cells specific for hepatitis C virus using MHC class II tetramers. J. Clin. Invest. 112, 831–842 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  89. Landais, E. et al. New design of MHC class II tetramers to accommodate fundamental principles of antigen presentation. J. Immunol. 183, 7949–7957 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Hadrup, S. R. et al. Parallel detection of antigen-specific T-cell responses by multidimensional encoding of MHC multimers. Nat. Methods 6, 520–526 (2009).

    Article  CAS  PubMed  Google Scholar 

  91. Newell, E. W., Klein, L. O., Yu, W. & Davis, M. M. Simultaneous detection of many T-cell specificities using combinatorial tetramer staining. Nat. Methods 6, 497–499 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  92. Kvistborg, P. et al. Thinking outside the gate: single-cell assessments in multiple dimensions. Immunity 42, 591–592 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  93. Appay, V., Van Lier, R. A. W., Sallusto, F. & Roederer, M. Phenotype and function of human T lymphocyte subsets: consensus and issues. Cytometry Part A 73, 975–983 (2008).

    Article  Google Scholar 

  94. Ornatsky, O. I., Baranov, V. I., Bandura, D. R., Tanner, S. D. & Dick, J. Messenger RNA detection in leukemia cell lines by novel metal-tagged in situ hybridization using inductively coupled plasma mass spectrometry. Transl. Oncogenomics 1, 1–9 (2006).

    PubMed  PubMed Central  Google Scholar 

  95. Bandura, D. R. et al. Mass cytometry: technique for real time single cell multitarget immunoassay based on inductively coupled plasma time-of-flight mass spectrometry. Anal. Chem. 81, 6813–6822 (2009).

    Article  CAS  PubMed  Google Scholar 

  96. Bendall, S. C. et al. Single-cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum. Science 332, 687–696 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  97. Cheng, Y. & Newell, E. W. Deep profiling human T cell heterogeneity by mass cytometry. Adv. Immunol. 131, 101–134 (2016).

    Article  CAS  PubMed  Google Scholar 

  98. Mair, F. et al. The end of gating? An introduction to automated analysis of high dimensional cytometry data. Eur. J. Immunol. 46, 34–43 (2016).

    Article  CAS  PubMed  Google Scholar 

  99. Newell, E. W. & Cheng, Y. Mass cytometry: blessed with the curse of dimensionality. Nat. Immunol. 17, 890–895 (2016).

    Article  CAS  PubMed  Google Scholar 

  100. Spitzer, M. H. & Nolan, G. P. Mass cytometry: single cells, many features. Cell 165, 780–791 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  101. Wong, M. T. et al. A high-dimensional atlas of human T cell diversity reveals tissue-specific trafficking and cytokine signatures. Immunity 45, 442–456 (2015).

    Article  CAS  Google Scholar 

  102. Newell, E. W., Sigal, N., Bendall, S. C., Nolan, G. P. & Davis, M. M. Cytometry by time-of-flight shows combinatorial cytokine expression and virus-specific cell niches within a continuum of CD8+ T cell phenotypes. Immunity 36, 142–152 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  103. Cheng, Y., Wong, M. T., van der Maaten, L. & Newell, E. W. Categorical analysis of human T cell heterogeneity with one-dimensional soli-expression by nonlinear stochastic embedding. J. Immunol. 196, 924–932 (2016).

    Article  CAS  PubMed  Google Scholar 

  104. Wistuba-Hamprecht, K. et al. Establishing high dimensional immune signatures from peripheral blood via mass cytometry in a discovery cohort of stage IV melanoma patients. J. Immunol. 198, 927–936 (2017).

  105. Krams, S. M., Schaffert, S., Lau, A. H. & Martinez, O. M. Applying mass cytometry to the analysis of lymphoid populations in transplantation. Am. J. Transplant. 17, 1992–1999 (2017).

    Article  CAS  PubMed  Google Scholar 

  106. Brooks, M. Insulinoma and abdominal tuberculosis. Scott. Med. J. 33, 207–208 (1988).

    Article  CAS  PubMed  Google Scholar 

  107. Xu, Q., Schlabach, M. R., Hannon, G. J. & Elledge, S. J. Design of 240,000 orthogonal 25mer DNA barcode probes. Proc. Natl Acad. Sci. USA 106, 2289–2294 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  108. MacBeath, G. & Schreiber, S. L. Printing proteins as microarrays for high-throughput function determination. Science 289, 1760–1763 (2000).

    CAS  PubMed  Google Scholar 

  109. Soen, Y., Chen, D. S., Kraft, D. L., Davis, M. M. & Brown, P. O. Detection and characterization of cellular immune responses using peptide-MHC microarrays. PLoS Biol. 1, e65 (2003).

    Article  PubMed  PubMed Central  Google Scholar 

  110. Stone, J. D., Demkowicz, W. E. & Stern, L. J. HLA-restricted epitope identification and detection of functional T cell responses by using MHC-peptide and costimulatory microarrays. Proc. Natl Acad. Sci. USA 102, 3744–3749 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  111. Chen, D. S. et al. Marked differences in human melanoma antigen-specific T cell responsiveness after vaccination using a functional microarray. PLoS Med. 2, e265 (2005).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  112. Deviren, G., Gupta, K., Paulaitis, M. E. & Schneck, J. P. Detection of antigen-specific T cells on p/MHC microarrays. J. Mol. Recognit. 20, 32–38 (2007).

    Article  CAS  PubMed  Google Scholar 

  113. Kwong, G. A. et al. Modular nucleic acid assembled p/MHC microarrays for multiplexed sorting of antigen-specific T cells. J. Am. Chem. Soc. 131, 9695–9703 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  114. Brooks, S. E. et al. Application of the pMHC array to characterise tumour antigen specific T cell populations in leukaemia patients at disease diagnosis. PLoS ONE 10, e0140483 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  115. Klinger, M. et al. Multiplex identification of antigen-specific T cell receptors using a combination of immune assays and immune receptor sequencing. PLoS ONE 10, e0141561 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  116. Novak, E. J. et al. Tetramer-guided epitope mapping: rapid identification and characterization of immunodominant CD4+ T cell epitopes from complex antigens. J. Immunol. 166, 6665–6670 (2001).

    Article  CAS  PubMed  Google Scholar 

  117. Robins, H. S. et al. Comprehensive assessment of T-cell receptor β-chain diversity in αβ T cells. Blood 114, 4099–4107 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  118. Davis, M. M. & Bjorkman, P. J. T-cell antigen receptor genes and T-cell recognition. Nature 334, 395–402 (1988).

    Article  CAS  PubMed  Google Scholar 

  119. van Buuren, M. M. et al. HLA micropolymorphisms strongly affect peptide-MHC multimer-based monitoring of antigen-specific CD8+ T cell responses. J. Immunol. 192, 641–648 (2014).

    Article  PubMed  CAS  Google Scholar 

  120. Frøsig, T. M. et al. Design and validation of conditional ligands for HLA-B*08:01, HLA-B*15:01, HLA-B*35:01, and HLA-B*44:05. Cytom. Part A 87, 967–975 (2015).

    Article  CAS  Google Scholar 

  121. Mason, D. A very high level of crossreactivity is an essential feature of the T-cell receptor. Immunol. Today 19, 395–404 (1998).

    Article  CAS  PubMed  Google Scholar 

  122. Márquez, A. C. & Horwitz, M. S. The role of latently infected B cells in CNS autoimmunity. Front. Immunol. 6, 544 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  123. Lundegaard, C., Lund, O., Buus, S. & Nielsen, M. Major histocompatibility complex class I binding predictions as a tool in epitope discovery. Immunology 130, 309–318 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  124. Abelin, J. G. et al. Mass spectrometry profiling of HLA-associated peptidomes in mono-allelic cells enables more accurate epitope prediction. Immunity 46, 315–326 (2017).

    Article  CAS  PubMed  Google Scholar 

  125. Malaker, S. A. et al. Identification and characterization of complex glycosylated peptides presented by the MHC class II processing pathway in melanoma. J. Proteome Res. 16, 228–237 (2017).

    Article  CAS  PubMed  Google Scholar 

  126. Fritsch, E. F. et al. HLA-binding properties of tumor neoepitopes in humans. Cancer Immunol. Res. 2, 522–529 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  127. The problem with neoantigen prediction. Nat. Biotechnol. 35, 97 (2017).

  128. Liu, X. S. & Mardis, E. R. Applications of immunogenomics to cancer. Cell 168, 600–612 (2017).

    Article  CAS  PubMed  Google Scholar 

  129. Osborne, G. W., Andersen, S. B. & Battye, F. L. Development of a novel cell sorting method that samples population diversity in flow cytometry. Cytometry. A 87, 1047–1051 (2015).

    Article  CAS  PubMed  Google Scholar 

  130. Klein, A. M. et al. Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells. Cell 161, 1187–1201 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  131. Macosko, E. Z. et al. Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell 161, 1202–1214 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  132. Stoeckius, M. et al. Simultaneous epitope and transcriptome measurement in single cells. Nat. Methods 14, 865–868 (2017).

  133. van Buggenum, J. A. G. L. et al. A covalent and cleavable antibody-DNA conjugation strategy for sensitive protein detection via immuno-PCR. Sci. Rep. 6, 22675 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  134. Moon, J. J. et al. Naive CD4+ T cell frequency varies for different epitopes and predicts repertoire diversity and response magnitude. Immunity 27, 203–213 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  135. Yu, W. et al. Clonal deletion prunes but does not eliminate self-specific αβ CD8+ T lymphocytes. Immunity 42, 929–941 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  136. Zoete, V., Irving, M., Ferber, M., Cuendet, M. A. & Michielin, O. Structure-based, rational design of T cell receptors. Front. Immunol. 4, 268 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  137. Dash, P. et al. Quantifiable predictive features define epitope-specific T cell receptor repertoires. Nature 547, 89–93 (2017).

    Article  CAS  PubMed  Google Scholar 

  138. Glanville, J. et al. Identifying specificity groups in the T cell receptor repertoire. Nature 547, 94–98 (2017).

    Article  CAS  PubMed  Google Scholar 

  139. Sela-culang, I. et al. Resource using a combined computational-experimental approach to predict antibody-specific B cell epitopes. Struct. Des. 22, 646–657 (2014).

    Article  CAS  Google Scholar 

  140. Furman, D. et al. Expression of specific inflammasome gene modules stratifies older individuals into two extreme clinical and immunological states. Nat. Med. 23, 174–184 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  141. Sette, A. & Peters, B. Immune epitope mapping in the post-genomic era: lessons for vaccine development. Curr. Opin. Immunol. 19, 106–110 (2007).

    Article  CAS  PubMed  Google Scholar 

  142. Anderson, R. P. & Jabri, B. Vaccine against autoimmune disease: antigen-specific immunotherapy. Curr. Opin. Immunol. 25, 410–417 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  143. Czerkinsky, C. C., Nilsson, L. A., Nygren, H., Ouchterlony, O. & Tarkowski, A. A solid-phase enzyme-linked immunospot (ELISPOT) assay for enumeration of specific antibody-secreting cells. J. Immunol. Methods 65, 109–121 (1983).

    Article  CAS  PubMed  Google Scholar 

  144. Draenert, R. et al. Comparison of overlapping peptide sets for detection of antiviral CD8 and CD4 T cell responses. J. Immunol. Methods 275, 19–29 (2003).

    Article  CAS  PubMed  Google Scholar 

  145. Waldrop, S. L., Pitcher, C. J., Peterson, D. M., Maino, V. C. & Picker, L. J. Determination of antigen-specific memory/effector CD4+ T cell frequencies by flow cytometry: evidence for a novel, antigen-specific homeostatic mechanism in HIV-associated immunodeficiency. J. Clin. Invest. 99, 1739–1750 (1997).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  146. Bacher, P. et al. Antigen-reactive T cell enrichment for direct, high-resolution analysis of the human naive and memory Th cell repertoire. J. Immunol. 190, 3967–3976 (2013).

    Article  CAS  PubMed  Google Scholar 

  147. Bacher, P. et al. Regulatory T cell specificity directs tolerance versus allergy against aeroantigens in humans. Cell 167, 1067–1078e16 (2016).

    Article  CAS  PubMed  Google Scholar 

  148. Appay, V. & Rowland-Jones, S. L. The assessment of antigen-specific CD8+ T cells through the combination of MHC class I tetramer and intracellular staining. J. Immunol. Methods 268, 9–19 (2002).

    Article  CAS  PubMed  Google Scholar 

  149. Geiger, R., Duhen, T., Lanzavecchia, A. & Sallusto, F. Human naive and memory CD4+ T cell repertoires specific for naturally processed antigens analyzed using libraries of amplified T cells. J. Exp. Med. 206, 1525–1534 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  150. Becattini, S. et al. T cell immunity. Functional heterogeneity of human memory CD4+ T cell clones primed by pathogens or vaccines. Science 347, 400–406 (2015).

    Article  CAS  PubMed  Google Scholar 

  151. Cox, A. L. et al. Identification of a peptide recognized by five melanoma-specific human cytotoxic T cell lines. Science 264, 716–719 (1994).

    Article  CAS  PubMed  Google Scholar 

  152. Robbins, P. D. & Morelli, A. E. Regulation of immune responses by extracellular vesicles. Nat. Rev. Immunol. 14, 195–208 (2014).

    Article  CAS  PubMed  Google Scholar 

  153. Amir, E. D. et al. viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia. Nat. Biotechnol. 31, 545–552 (2013).

    Article  CAS  PubMed Central  Google Scholar 

  154. Kozono, H., White, J., Clements, J., Marrack, P. & Kappler, J. Production of soluble MHC class II proteins with covalently bound single peptides. Nature 369, 151–154 (1994).

    Article  CAS  PubMed  Google Scholar 

  155. Bankovich, A. J., Girvin, A. T., Moesta, A. K. & Garcia, K. C. Peptide register shifting within the MHC groove: theory becomes reality. Mol. Immunol. 40, 1033–1039 (2004).

    Article  CAS  PubMed  Google Scholar 

  156. Lin, H. H., Zhang, G. L., Tongchusak, S., Reinherz, E. L. & Brusic, V. Evaluation of MHC-II peptide binding prediction servers: applications for vaccine research. BMC Bioinformatics 9(Suppl. 12), S22 (2008).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  157. Su, L. F., Kidd, B. A., Han, A., Kotzin, J. J. & Davis, M. M. Virus-specific CD4+ memory-phenotype T cells are abundant in unexposed adults. Immunity 38, 373–383 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  158. Uchtenhagen, H. et al. Efficient ex vivo analysis of CD4+ T-cell responses using combinatorial HLA class II tetramer staining. Nat. Commun. 7, 12614 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  159. Lissina, A. et al. Protein kinase inhibitors substantially improve the physical detection of T-cells with peptide-MHC tetramers. J. Immunol. Methods 340, 11–24 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  160. Xie, J. et al. Photocrosslinkable pMHC monomers stain T cells specifically and cause ligand-bound TCRs to be ‘preferentially’ transported to the cSMAC. Nat. Immunol. 13, 674–680 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

The work was funded by the European Research Council (ERC), ERC starting grant and the Lundbeck Foundation fellowship (S.R.H.) and the Singapore Immunology Network (SIgN) (E.W.N.).

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S.R.H. and E.W.N. conceived and wrote this Perspective.

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Correspondence to Sine Reker Hadrup.

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E.W.N. is a board director and shareholder of immunoSCAPE Pte. Ltd. S.R.H. is a co-founder of Immumap Services.

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A correction to this article is available online at https://doi.org/10.1038/s41551-017-0176-8.

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Hadrup, S.R., Newell, E. Determining T-cell specificity to understand and treat disease. Nat Biomed Eng 1, 784–795 (2017). https://doi.org/10.1038/s41551-017-0143-4

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