Abstract

Identification of the peptides recognized by individual T cells is important for understanding and treating immune-related diseases. Current cytometry-based approaches are limited to the simultaneous screening of 10–100 distinct T-cell specificities in one sample. Here we use peptide–major histocompatibility complex (MHC) multimers labeled with individual DNA barcodes to screen >1,000 peptide specificities in a single sample, and detect low-frequency CD8 T cells specific for virus- or cancer-restricted antigens. When analyzing T-cell recognition of shared melanoma antigens before and after adoptive cell therapy in melanoma patients, we observe a greater number of melanoma-specific T-cell populations compared with cytometry-based approaches. Furthermore, we detect neoepitope-specific T cells in tumor-infiltrating lymphocytes and peripheral blood from patients with non-small cell lung cancer. Barcode-labeled pMHC multimers enable the combination of functional T-cell analysis with large-scale epitope recognition profiling for the characterization of T-cell recognition in various diseases, including in small clinical samples.

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References

  1. 1.

    et al. A sensitive ELISPOT assay to detect low-frequency human T lymphocytes. J. Immunol. Methods 210, 149–166 (1997).

  2. 2.

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

  3. 3.

    & Cytometry: today's technology and tomorrow's horizons. Methods 57, 251–258 (2012).

  4. 4.

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

  5. 5.

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

  6. 6.

    et al. Parallel detection of antigen-specific T cell responses by combinatorial encoding of MHC multimers. Nat. Protoc. 7, 891–902 (2012).

  7. 7.

    , , & Simultaneous detection of many T-cell specificities using combinatorial tetramer staining. Nat. Methods 6, 497–499 (2009).

  8. 8.

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

  9. 9.

    , & Peptides naturally presented by MHC class I molecules. Annu. Rev. Immunol. 11, 213–244 (1993).

  10. 10.

    & Quantitative aspects of T cell activation--peptide generation and editing by MHC class I molecules. Semin. Immunol. 11, 375–384 (1999).

  11. 11.

    et al. Comprehensive assessment of T-cell receptor beta-chain diversity in alphabeta T cells. Blood 114, 4099–4107 (2009).

  12. 12.

    & T-cell antigen receptor genes and T-cell recognition. Nature 334, 395–402 (1988).

  13. 13.

    et al. A single autoimmune T cell receptor recognizes more than a million different peptides. J. Biol. Chem. 287, 1168–1177 (2012).

  14. 14.

    , , & Design of 240,000 orthogonal 25mer DNA barcode probes. Proc. Natl. Acad. Sci. USA 106, 2289–2294 (2009).

  15. 15.

    et al. Counting absolute numbers of molecules using unique molecular identifiers. Nat. Methods 9, 72–74 (2011).

  16. 16.

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

  17. 17.

    et al. Generation of peptide-MHC class I complexes through UV-mediated ligand exchange. Nat. Protoc. 1, 1120–1132 (2006).

  18. 18.

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

  19. 19.

    et al. T-cell responses to oncogenic merkel cell polyomavirus proteins distinguish patients with merkel cell carcinoma from healthy donors. Clin. Cancer Res. 20, 1768–1778 (2014).

  20. 20.

    et al. Broadening the repertoire of melanoma-associated T-cell epitopes. Cancer Immunol. Immunother. 64, 609–620 (2015).

  21. 21.

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

  22. 22.

    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. Cytometry A 87, 967–975 (2015).

  23. 23.

    et al. Enhanced generation of specific tumor-reactive CTL in vitro by selected Melan-A/MART-1 immunodominant peptide analogues. J. Immunol. 160, 1750–1758 (1998).

  24. 24.

    et al. A novel population of human melanoma-specific CD8 T cells recognizes Melan-AMART-1 immunodominant nonapeptide but not the corresponding decapeptide. J. Immunol. 179, 7635–7645 (2007).

  25. 25.

    et al. Fine structural variations of alphabetaTCRs selected by vaccination with natural versus altered self-antigen in melanoma patients. J. Immunol. 183, 5397–5406 (2009).

  26. 26.

    et al. Unmodified self antigen triggers human CD8 T cells with stronger tumor reactivity than altered antigen. Proc. Natl. Acad. Sci. USA 105, 3849–3854 (2008).

  27. 27.

    et al. Long-lasting complete responses in patients with metastatic melanoma after adoptive cell therapy with tumor-infiltrating lymphocytes and an attenuated IL2 regimen. Clin. Cancer Res. 22, 3734–3745 (2016).

  28. 28.

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

  29. 29.

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

  30. 30.

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

  31. 31.

    et al. Different affinity windows for virus and cancer-specific T-cell receptors: implications for therapeutic strategies. Eur. J. Immunol. 42, 3174–3179 (2012).

  32. 32.

    et al. Comparison of peptide-major histocompatibility complex tetramers and dextramers for the identification of antigen-specific T cells. Clin. Exp. Immunol. 177, 47–63 (2014).

  33. 33.

    et al. Direct staining with major histocompatibility complex class II dextramers permits detection of antigen-specific, autoreactive CD4 T cells in situ. PLoS One 9, e87519 (2014).

  34. 34.

    , , & Linking T-cell receptor sequence to functional phenotype at the single-cell level. Nat. Biotechnol. 32, 684–692 (2014).

  35. 35.

    et al. MHC multimer-guided and cell culture-independent isolation of functional T cell receptors from single cells facilitates TCR identification for immunotherapy. PLoS One 8, e61384 (2013).

  36. 36.

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

  37. 37.

    et al. Characterization and comparison of 'standard' and 'young' tumour-infiltrating lymphocytes for adoptive cell therapy at a Danish translational research institution. Scand. J. Immunol. 75, 157–167 (2012).

  38. 38.

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

  39. 39.

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

  40. 40.

    et al. Genomic architecture and evolution of clear cell renal cell carcinomas defined by multiregion sequencing. Nat. Genet. 46, 225–233 (2014).

  41. 41.

    et al. OptiType: precision HLA typing from next-generation sequencing data. Bioinformatics 30, 3310–3316 (2014).

  42. 42.

    et al. Conditional MHC class I ligands and peptide exchange technology for the human MHC gene products HLA-A1, -A3, -A11, and -B7. Proc. Natl. Acad. Sci. USA 105, 3825–3830 (2008).

  43. 43.

    et al. High-throughput T-cell epitope discovery through MHC peptide exchange. Methods Mol. Biol. 524, 383–405 (2009).

  44. 44.

    et al. Conditional ligands for Asian HLA variants facilitate the definition of CD8+ T-cell responses in acute and chronic viral diseases. Eur. J. Immunol. 43, 1109–1120 (2013).

  45. 45.

    , & HLA-A2-peptide complexes: refolding and crystallization of molecules expressed in Escherichia coli and complexed with single antigenic peptides. Proc. Natl. Acad. Sci. USA 89, 3429–3433 (1992).

  46. 46.

    et al. NetMHCpan, a method for quantitative predictions of peptide binding to any HLA-A and -B locus protein of known sequence. PLoS One 2, e796 (2007).

  47. 47.

    , , , & SYFPEITHI: database for MHC ligands and peptide motifs. Immunogenetics 50, 213–219 (1999).

  48. 48.

    & Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).

  49. 49.

    , & edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26, 139–140 (2010).

  50. 50.

    & A scaling normalization method for differential expression analysis of RNA-seq data. Genome Biol. 11, R25 (2010).

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Acknowledgements

We would like to thank U.K. Hansen, A. Burkal and T. Seremet for technical assistance; T. Schumacher, Netherlands Cancer Institute, for scientific discussions and sharing of MHC expression plasmids; and Dr. Altman, NIH Tetramer Core Facility, for sharing expression plasmids HLA-B*1501 and HLA-B*3501. The work was funded by The Danish Cancer Society (ID:R72-A4531-13-S2), The Lundbeck Foundation Fellowship (ID: R190-2014-4178), The Danish Research Council (FSS-ID: 1331-00283 and DFF-ID:4004-00422), Familien Erichsens Mindefond, Cancer Research UK (FC001169), the UK Medical Research Council (FC001169 ), the Wellcome Trust (FC001169), the UK Medical Research Council (MR/FC001169/1) and the Novo Nordisk Foundation (ID: 16584).

Author information

Affiliations

  1. Section for Immunology and Vaccinology, National Veterinary Institute, Technical University of Denmark, Copenhagen, Denmark.

    • Amalie Kai Bentzen
    • , Rikke Lyngaa
    • , Sunil Kumar Saini
    • , Sofie Ramskov
    • , Lina Such
    • , Søren Nyboe Jakobsen
    •  & Sine Reker Hadrup
  2. Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Lyngby, Denmark.

    • Andrea Marion Marquard
    • , Zoltan Szallasi
    •  & Aron Charles Eklund
  3. Center for Cancer Immune Therapy, Department of Hematology, Herlev Hospital, University of Copenhagen, Copenhagen, Denmark.

    • Marco Donia
    • , Per thor Straten
    •  & Inge Marie Svane
  4. Department of Oncology, Herlev Hospital, University of Copenhagen, Copenhagen, Denmark.

    • Marco Donia
    •  & Inge Marie Svane
  5. CRUK Lung Cancer Center of Excellence, UCL Cancer Institute, London, UK.

    • Andrew J S Furness
    • , Nicholas McGranahan
    • , Rachel Rosenthal
    • , Charles Swanton
    •  & Sergio A Quezada
  6. Cancer Immunology Unit, UCL Cancer Institute, University College London, London, UK.

    • Andrew J S Furness
    •  & Sergio A Quezada
  7. Translational Cancer Therapeutics Laboratory, The Francis Crick Institute, London, UK.

    • Nicholas McGranahan
    • , Rachel Rosenthal
    •  & Charles Swanton
  8. Department of Immunology and Microbiology, University of Copenhagen, Copenhagen, Denmark.

    • Per thor Straten
  9. Immudex, Copenhagen, Denmark.

    • Søren Nyboe Jakobsen

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Contributions

A.K.B. conceived the concept, designed and performed experiments, analyzed data, made figures and wrote the manuscript; A.M.M. designed the in silicon analysis, analyzed data, and made figures; R.L., S.K.S., and S.R. produced MHC monomers, designed and performed experiments, analyzed data and revised the manuscript; L.S. performed experiments, M.D. and I.M.S. provided patients material and generated tumor cell lines, discussed data; P.t.S. provided administrative support, flow facility and production of MHC monomers; A.J.S.F., S.A.Q. provided patients material and peptides from NSCLC; N.M.G., R.R., C.S. identified tumor mutagenome and predicted NSCLC-associated neoepitopes; Z.S. and A.C.E., designed the in silico analysis, and guided data analyses; S.N.J. designed DNA barcodes, conceived the concept, guided data analyses and revised the manuscript; S.R.H. conceived the concept, designed experiments, analyzed data and wrote the manuscript.

Competing interests

The technology is patented (WO2015185067 and WO2015188839) by the authors (S.R.H., A.K.B., and S.N.J.), the Capital Region of Copenhagen, University Hospital Herlev and Immudex. The technology is licensed to Immudex.

Integrated supplementary information

Supplementary information

PDF files

  1. 1.

    Supplementary Text and Figures

    Supplementary Figures 1–5 and Supplementary Tables 1, 4 and 6

Excel files

  1. 1.

    Supplementary Table 2

    Oligo B's

  2. 2.

    Supplementary Table 3

    Forward primers with Sample-identification barcodes (SampleID) and Ion Torrent adaptor (A-Key) and reverse primer with Ion Torrent adaptor (P1-Key)

  3. 3.

    Supplementary Table 5

    1031 barcode-labeled MHC multimer panel

  4. 4.

    Supplementary Table 7

    110 barcode-labeled MHC multimer panel

  5. 5.

    Supplementary Table 8

    175 barcode-labeled MHC multimer panel

  6. 6.

    Supplementary Table 9

    328 barcode-labeled MHC multimer panel

About this article

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DOI

https://doi.org/10.1038/nbt.3662

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