Abstract

The promiscuous nature of T-cell receptors (TCRs) allows T cells to recognize a large variety of pathogens, but makes it challenging to understand and control T-cell recognition1. Existing technologies provide limited information about the key requirements for T-cell recognition and the ability of TCRs to cross-recognize structurally related elements2,3. Here we present a 'one-pot' strategy for determining the interactions that govern TCR recognition of peptide–major histocompatibility complex (pMHC). We measured the relative affinities of TCRs to libraries of barcoded peptide–MHC variants and applied this knowledge to understand the recognition motif, here termed the TCR fingerprint. The TCR fingerprints of 16 different TCRs were identified and used to predict and validate cross-recognized peptides from the human proteome. The identified fingerprints differed among TCRs recognizing the same epitope, demonstrating the value of this strategy for understanding T-cell interactions and assessing potential cross-recognition before selection of TCRs for clinical development.

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Acknowledgements

We would like to thank all Merkel cell carcinoma patients and healthy donors contributing material to this study; T. Joeris, W. Agace and K. Lahl (Lund University, Lund, Sweden) for sharing of splenocytes from OT-1 and OT-3 transgenic mice; B. Rotbøl and T. Tamhane for excellent technical assistance; and S.R.H.'s group for scientific discussions. This research was funded in part through the European Research Council, StG 677268 NextDART, Lundbeck Foundation Fellowship R190-2014-4178 (to S.R.H.), the Independent Research Fund Denmark (DFF 4004-00422 and DFF 7014-00055, to S.R.H. and M.N.), NIH NCI Cancer Center Support Grant P30 CA015704, K24-CA-139052 and R01 CA176841, Kelsey Dickson Team Science Courage Research Team Award, Prostate Cancer Foundation Award 15CHAS04, and the UW MCC Patient Gift Fund (to P.N.).

Author information

Author notes

    • Rikke Lyngaa
    •  & Carsten Linnemann

    Present addressess: Gilead Sciences, Copenhagen, Denmark (R.L.); Kite Pharma Europe, Amsterdam, the Netherlands (C.L.).

    • Amalie K Bentzen
    •  & Lina Such

    These authors contributed equally to this work.

Affiliations

  1. Department of Micro and Nanotechnology, Technical University of Denmark, Lyngby, Denmark.

    • Amalie K Bentzen
    • , Lina Such
    • , Andrea M Marquard
    • , Leon E Jessen
    • , Rikke Lyngaa
    •  & Sine R Hadrup
  2. Department of Bio and Health Informatics, Technical University of Denmark, Lyngby, Denmark.

    • Kamilla K Jensen
    • , Leon E Jessen
    • , Paolo Marcatili
    •  & Morten Nielsen
  3. Department of Medicine, Divisions of Dermatology, University of Washington, Seattle, Washington, USA.

    • Natalie J Miller
    • , Candice D Church
    •  & Paul Nghiem
  4. Department of Medicine, University of Washington, Seattle, Washington, USA.

    • David M Koelle
  5. Division of Vaccine and Infectious Diseases, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.

    • David M Koelle
  6. Translational Skin Cancer Research, University Hospital Essen and University of Duisburg-Essen, Essen, Germany.

    • Jürgen C Becker
  7. Department of Molecular Oncology & Immunology, Oncode Institute, The Netherlands Cancer Institute, Amsterdam, the Netherlands.

    • Carsten Linnemann
    •  & Ton N M Schumacher
  8. Instituto de Investigaciones Biotecnológicas, Universidad Nacional de San Martín, Buenos Aires, Argentina.

    • Morten Nielsen

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Contributions

A.K.B. and L.S. conceived the idea, designed and performed experiments, analyzed data, made figures and wrote the manuscript; K.K.J., A.M.M. and L.E.J. conceived the bioinformatic processing, analyzed data, made figures and revised the manuscript; N.J.M. and C.D.C. identified and established T cell clones; R.L. identified and characterized TCRs and TCR-transduced T cells; D.M.K., J.C.B. and P.N. provided patient material for TCR identification and supervised the studies; C.L. and T.N.M.S. sequenced and expressed TCRs and revised the manuscript; P.M. and M.N. conceived the bioinformatic processing, supervised data analyses and revised the manuscript; S.R.H. conceived the idea, supervised the study, designed experiments, analyzed data and wrote the manuscript.

Competing interests

A.K.B. and S.R.H. are co-inventors on a patent covering the use of DNA barcode-labeled MHC multimers (WO2015185067 and WO2015188839). N.J.M., C.D.C., D.M.K. and P.N. are co-inventors on a patent application filed by their employer, University of Washington, concerning the HLA-A*0201-restricted TCR sequences.

Corresponding author

Correspondence to Sine R Hadrup.

Integrated supplementary information

Supplementary information

PDF files

  1. 1.

    Supplementary Text and Figures

    Supplementary Figures 1–13

  2. 2.

    Life Sciences Reporting Summary

  3. 3.

    Supplementary Information

    Supplementary Data 1, 2, 5, 6, 9, 11 and 13 and Supplementary Notes 1–4

Excel files

  1. 1.

    Supplementary Data 3

    APNCYGNIPL peptide variants applied in Figure 1a–c,g and Supplementary Figures 3 and 5

  2. 2.

    Supplementary Data 4

    EWWRSGGFSF peptide variants applied in Figure 1d–f,h–k and Supplementary Figures 4 and 6

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    Supplementary Data 7

    EWWRSGGFSF double substitution variants applied in Figure 1i–k and Supplementary Figure 5. The MHC multimer panel comprised these 776 peptides and the 191 single substitution peptides listed in Supplementary Data 2.

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    Supplementary Data 8

    SIINFEKL peptide variants applied in Figure 2a–d and Supplementary Figures 10 and 11

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    Supplementary Data 10

    KLLEIAPNC peptide variants applied in Figure 2 and Supplementary Figure 12

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    Supplementary Data 12

    The 75 peptides comprising the top ten of the FIMO-based priority list that best match each of the TCR fingerprints of the 12 HLA-A*0201 MCCKLL-engaging TCRs, including the original KLLEIAPNC target. Related to Figure 3.

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DOI

https://doi.org/10.1038/nbt.4303