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T cell antigen discovery via signaling and antigen-presenting bifunctional receptors

Nature Methods volume 16, pages 191–198 (2019)Cite this article

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Abstract

CD8+ T cells recognize and eliminate tumors in an antigen-specific manner. Despite progress in characterizing the antitumor T cell repertoire and function, the identification of target antigens remains a challenge. Here we describe the use of chimeric receptors called signaling and antigen-presenting bifunctional receptors (SABRs) in a cell-based platform for T cell receptor (TCR) antigen discovery. SABRs present an extracellular complex comprising a peptide and major histocompatibility complex (MHC), and induce intracellular signaling via a TCR-like signal after binding with a cognate TCR. We devised a strategy for antigen discovery using SABR libraries to screen thousands of antigenic epitopes. We validated this platform by identifying the targets recognized by public TCRs of known specificities. Moreover, we extended this approach for personalized neoantigen discovery.

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Fig. 1: Signaling and antigen-presenting bifunctional receptors.
Fig. 2: Different modes of antigen presentation by SABRs.
Fig. 3: SABRs induce a bona fide TCR signal.
Fig. 4: Proof of concept of using SABR libraries for TCR antigen discovery.
Fig. 5: Personalized neoantigen discovery using SABR libraries.

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Data availability

The data that support the findings of this study are available from the corresponding author upon request. The raw data for Figs. 1–5 and Supplementary Figs. 1, 3, 4, 7, and 8 can be found in the Source Data files. The list of epitopes in the SABR libraries can be found in Supplementary Tables 3 and 4. The plasmids for HLA-A*0201-SABR backbone (pCCLc-MND-A0201-SABR-Backbone; ID 119050), HLA-B*2705-SABR backbone (pCCLc-MND-B2705-SABR-Backbone; ID 119051), A2-Mart1-SABR (pCCLc-MND-A0201-Mart1-SABR; ID 119052), and B27-KK10-SABR (pCCLc-MND-B2705-KK10-SABR; ID 119053) are available through Addgene. The sequencing data have been deposited in the Sequence Read Archive (SRR8207921, amplicon sequencing of A2-SABR-library co-incubated with F5 TCR; SRR8207922, amplicon sequencing of A2-SABR-library co-incubated with SL9 TCR; SRR8207923, amplicon sequencing of A2-SABR-library co-incubated with no TCR; SRR8207924, amplicon sequencing of A2-NeoAg-library co-incubated with neoTCR; SRR8207925, amplicon sequencing of A2-NeoAg-library co-incubated with no TCR). The code used to analyze sequences has been deposited in GitHub (https://github.com/Baltimore-Lab/nat-methods-SABR-trogo).

References

  1. Shankaran, V. et al. IFN-γ and lymphocytes prevent primary tumour development and shape tumour immunogenicity. Nature 410, 1107–1111 (2001).

    Article  CAS  Google Scholar 

  2. Lollini, P. L., Cavallo, F., Nanni, P. & Forni, G. Vaccines for tumour prevention. Nat. Rev. Cancer 6, 204–216 (2006).

    Article  CAS  Google Scholar 

  3. Leach, D. R., Krummel, M. F. & Allison, J. P. Enhancement of antitumor immunity by CTLA-4 blockade. Science 271, 1734–1736 (1996).

    Article  CAS  Google Scholar 

  4. Dong, H. et al. Tumor-associated B7-H1 promotes T-cell apoptosis: a potential mechanism of immune evasion. Nat. Med. 8, 793–800 (2002).

    Article  CAS  Google Scholar 

  5. Yee, C. et al. Adoptive T cell therapy using antigen-specific CD8+ T cell clones for the treatment of patients with metastatic melanoma: in vivo persistence, migration, and antitumor effect of transferred T cells. Proc. Natl Acad. Sci. USA 99, 16168–16173 (2002).

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

  7. Weiss, A. & Littman, D. R. Signal transduction by lymphocyte antigen receptors. Cell 76, 263–274 (1994).

    Article  CAS  Google Scholar 

  8. Bethune, M. T. & Joglekar, A. V. Personalized T cell-mediated cancer immunotherapy: progress and challenges. Curr. Opin. Biotechnol. 48, 142–152 (2017).

    Article  CAS  Google Scholar 

  9. Woodsworth, D. J., Castellarin, M. & Holt, R. A. Sequence analysis of T-cell repertoires in health and disease. Genome Med. 5, 98 (2013).

    Article  Google Scholar 

  10. Buchholz, V. R., Schumacher, T. N. & Busch, D. H. T cell fate at the single-cell level. Annu. Rev. Immunol. 34, 65–92 (2016).

    Article  CAS  Google Scholar 

  11. Klenerman, P., Cerundolo, V. & Dunbar, P. R. Tracking T cells with tetramers: new tales from new tools. Nat. Rev. Immunol. 2, 263–272 (2002).

    Article  CAS  Google Scholar 

  12. Castle, J. C. et al. Exploiting the mutanome for tumor vaccination. Cancer Res. 72, 1081–1091 (2012).

    Article  CAS  Google Scholar 

  13. Boon, T. & van der Bruggen, P. Human tumor antigens recognized by T lymphocytes. J. Exp. Med. 183, 725–729 (1996).

    Article  CAS  Google Scholar 

  14. Matsushita, H. et al. Cancer exome analysis reveals a T-cell-dependent mechanism of cancer immunoediting. Nature 482, 400–404 (2012).

    Article  CAS  Google Scholar 

  15. Gee, M. H. et al. Antigen identification for orphan T cell receptors expressed on tumor-infiltrating lymphocytes. Cell 172, 549–563 (2018).

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

  17. Yu, Y. Y., Netuschil, N., Lybarger, L., Connolly, J. M. & Hansen, T. H. Cutting edge: single-chain trimers of MHC class I molecules form stable structures that potently stimulate antigen-specific T cells and B cells. J. Immunol. 168, 3145–3149 (2002).

    Article  CAS  Google Scholar 

  18. Morgan, R. A. et al. Cancer regression in patients after transfer of genetically engineered lymphocytes. Science 314, 126–129 (2006).

    Article  CAS  Google Scholar 

  19. Joglekar, A. V. et al. T cell receptors for the HIV KK10 epitope from patients with differential immunologic control are functionally indistinguishable. Proc. Natl Acad. Sci. USA 115, 1877–1882 (2018).

    Article  CAS  Google Scholar 

  20. Bennett, M. S., Joseph, A., Ng, H. L., Goldstein, H. & Yang, O. O. Fine-tuning of T-cell receptor avidity to increase HIV epitope variant recognition by cytotoxic T lymphocytes. AIDS 24, 2619–2628 (2010).

    Article  CAS  Google Scholar 

  21. Bethune, M. T., Comin-Anduix, B., Hwang Fu, Y. H., Ribas, A. & Baltimore, D. Preparation of peptide-MHC and T-cell receptor dextramers by biotinylated dextran doping. Biotechniques 62, 123–130 (2017).

    Article  CAS  Google Scholar 

  22. Sahin, U. et al. Personalized RNA mutanome vaccines mobilize poly-specific therapeutic immunity against cancer. Nature 547, 222–226 (2017).

    Article  CAS  Google Scholar 

  23. Vita, R. et al. The immune epitope database (IEDB) 3.0. Nucleic Acids Res. 43, D405–D412 (2015).

    Article  CAS  Google Scholar 

  24. Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25, 1754–1760 (2009).

    Article  CAS  Google Scholar 

  25. Yokomaku, Y. et al. Impaired processing and presentation of cytotoxic-T-lymphocyte (CTL) epitopes are major escape mechanisms from CTL immune pressure in human immunodeficiency virus type 1 infection. J. Virol. 78, 1324–1332 (2004).

    Article  CAS  Google Scholar 

  26. Dorrell, L. et al. Distinct recognition of non-clade B human immunodeficiency virus type 1 epitopes by cytotoxic T lymphocytes generated from donors infected in Africa. J. Virol. 73, 1708–1714 (1999).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. Li, G. S. W. et al. T cell antigen discovery via trogocytosis. Nat. Methods https://doi.org/10.1038/s41592-018-0305-7 (2019).

  28. Peakman, M. et al. T cell clones generated from patients with type 1 diabetes using interleukin-2 proliferate to human islet antigens. Autoimmunity 17, 31–39 (1994).

    Article  CAS  Google Scholar 

  29. Tang, Q. & Bluestone, J. A. The Foxp3+ regulatory T cell: a jack of all trades, master of regulation. Nat. Immunol. 9, 239–244 (2008).

    Article  CAS  Google Scholar 

  30. Garcia, K. C. et al. Structural basis of plasticity in T cell receptor recognition of a self peptide-MHC antigen. Science 279, 1166–1172 (1998).

    Article  CAS  Google Scholar 

  31. Suwandi, J. S., Nikolic, T. & Roep, B. O. Translating mechanism of regulatory action of tolerogenic dendritic cells to monitoring endpoints in clinical trials. Front. Immunol. 8, 1598 (2017).

    Article  Google Scholar 

  32. 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  Google Scholar 

  33. Tran, E. et al. Cancer immunotherapy based on mutation-specific CD4+ T cells in a patient with epithelial cancer. Science 344, 641–645 (2014).

    Article  CAS  Google Scholar 

  34. Baltimore, D. et al. A cell-based platform for T cell antigen discovery: engineered antigen presenting cells expressing signaling and antigen presenting bifunctional receptors (SABRs). Protocol Exchange https://doi.org/10.1038/protex.2018.126 (2019).

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Acknowledgements

We thank I. Antoshechkin at the Millard and Muriel Jacobs Genetics and Genomics Laboratory for Illumina sequencing, and A. Spalla at the Analytical Cytometry Core at the City of Hope for help with FACS. NFAT-GFP-Jurkat cells were a gift from A. Weiss (University of California, San Francisco, San Francisco, CA, USA) and Y. Chen (University of California, Los Angeles, Los Angeles, CA, USA). GXR-B27+ cells were a gift from B.D. Walker (Ragon Institute of Massachusetts General Hospital, Massachusetts Institute of Technology, and Harvard, Cambridge, MA, USA). J3 chimeric antigen receptor was a gift from P. Wang (University of Southern California, Los Angeles, CA, USA). The pCCLc-MND-X backbone and pCMV-RD8.9 were gifts from D.B. Kohn (University of California, Los Angeles, Los Angeles, CA, USA). MSCV-based shuttle plasmid was a gift from R.A. Morgan (National Institutes of Health, Bethesda, MD, USA). This work was funded by the California Institute for Regenerative Medicine (award DISC2-09123 to D.B.), the Caltech Rothenberg Innovation Initiative (to D.B.), and the US National Cancer Institute (grant 1U54 CA199090-01 to J.R.H.).

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Authors and Affiliations

  1. Department of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA

    Alok V. Joglekar, Michael T. Leonard, John D. Jeppson, Margaret Swift, Guideng Li, Stephanie Wong, Michael T. Bethune & David Baltimore

  2. Center of Systems Medicine, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China

    Guideng Li

  3. Suzhou Institute of Systems Medicine, Suzhou, China

    Guideng Li

  4. Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA, USA

    Songming Peng & James R. Heath

  5. Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA

    Jesse M. Zaretsky & Antoni Ribas

  6. Parker Institute for Cancer Immunotherapy (PICI), University of California, Los Angeles and California Institute of Technology, Pasadena, CA, USA

    James R. Heath, Antoni Ribas & David Baltimore

  7. Division of Hematology & Oncology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA

    Antoni Ribas

  8. Department of Surgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA

    Antoni Ribas

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  1. Alok V. Joglekar
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Contributions

A.V.J. designed and performed experiments, analyzed and interpreted the data, and wrote the manuscript. M.T.L. designed and performed experiments, performed computational analyses, and interpreted the data. M.S. and J.D.J. designed and performed experiments, and analyzed the data. G.L., S.W., S.P., J.M.Z., and M.T.B. designed and performed experiments, and contributed reagents. J.R.H. and A.R. contributed reagents and supervised experiments. D.B. supervised the experiments, analyzed and interpreted the data, and wrote the manuscript.

Corresponding authors

Correspondence to Alok V. Joglekar or David Baltimore.

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Competing interests

A.V.J., M.T.L., M.T.B., and D.B. are named as co-inventors on a patent application concerning the described technology. D.B. is a consultant of PACT and head of their scientific advising board. J.R.H. and A.R. are directors and consultants of PACT; M.T.B. and S.P. are employees of PACT; J.M.Z. is a consultant of PACT; and each of the foregoing individuals has equity interests in PACT.

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Integrated supplementary information

Supplementary Figure 1 Variants of SABR constructs.

a. Schematics showing the SABR-F and SABR-E constructs. SABR-F contains the transmembrane domain from HLA (black rectangle), whereas SABR-E contains the transmembrane domain from CD3ζ (teal rectangle). The two horizontal lines indicate two leaflets of the plasma membrane. b. Representative flow cytometry plots showing GFP expression in coculture assays from Fig 1b. The experiments were performed at n = 3 biologically independent cell culture replicates. c. GFP expression in coculture assays comparing SABR-F and SABR-E. The lines and error bars indicate mean ± s.d. from n = 12 biologically independent cell culture replicates.

Source Data

Supplementary Figure 2 Time course of GFP expression induced by SABRs.

Representative flow cytometry plots from the F5+A2-MART1 experiment enumerated in Fig 1e are shown. The rectangle in the right bottom corners shows the gate for counting GFP+ cells. The time at which each sample was collected is shown as hours. The frequency of cells in the GFP+ gate is indicated as a percentage.

Supplementary Figure 3 Recognition of low-affinity TCRs by SABRs.

GFP expression in coculture assays using F5 and M1 TCRs with A2-MART1-SABR. The dots indicate individual values from n = 2 biologically independent cell culture replicates.

Source Data

Supplementary Figure 4 Empty SABR vector constructs and recognition of low-affinity pMHC–TCR interactions.

a. Schematic showing SCT, SABRs, empty SABRs, and TMGs. EP, epitope; S, signal sequence; MITD, MHC class I trafficking signal; numbers 1–6 indicate Gly–Ser linkers. b. Correlation of functional avidity of interaction of EC27 TCR with variants of KK10 peptides with their ability to initiate signal through SABRs. The indicated peptides are variants of the KK10 epitope. R2T, KTWIILGLNK; R2I, KIWIILGLNK; R2G, KGWIILGLNK; R2K, KKWIILGLNK; WT, KRWIILGLNK; R2Q, KQWIILGLNK.

Source Data

Supplementary Figure 5 Strategy to clone custom oligonucleotides into SABR vectors.

SABR vector constructs with a stuffer fragment showing BsmBI sites (top), and cloning strategy using double-stranded oligonucleotides with encoding the epitope flanked by overlaps.

Supplementary Figure 6 SABR library screen for antigen discovery.

a. Schematic showing the pipeline to construct custom SABR libraries. EP, epitope. The left panel shows the procedure to obtain and synthesize a list of epitopes. The right panel shows the schematic of the SABR library. b. Schematic showing coculture experiment to select cells from SABR library that are recognized by an orphan TCR. Left panel shows a SABR library presenting numerous unique epitopes. The middle panel shows antigen-presenting cells (APCs) showing reporter expression induced by SABRs presenting the cognate epitope for the orphan TCR. Right panel shows processing of the selected cells. c. Flowchart showing the computational analysis pipeline.

Supplementary Figure 7 Enrichment of EAAGIGILTV and SLYNTVATL analogs in SABR library screen.

a. Average ranks for all the EAAGIGILTV analogs in the A2-SABR library. b. Average ranks for all the SLYNTVATL analogs in the A2-SABR library. The ranks were calculated as described in the manuscript. The data are averaged from three biologically independent cell culture replicates.

Source Data

Supplementary Figure 8 Enrichment of USP7 neoepitopes in SABR library screen.

Average ranks for all the USP7-derived epitopes in the NeoAg-SABR library. The data are averaged from three biologically independent cell culture replicates.

Source Data

Supplementary Figure 9 Gating strategy used in flow cytometry.

a. Gating strategy used in coculture assays to measure GFP expression. b. Gating strategy used in coculture assays to measure GFP and CD69 expression. c. Gating strategy used in cytotoxicity assays.

Supplementary information

Supplementary Text and Figures

Supplementary Figs. 1–9 and Supplementary Tables 1 and 2

Reporting Summary

Supplementary Protocol

A cell-based platform for T cell antigen discovery: engineered antigen-presenting cells expressing signaling and antigen-presenting bifunctional receptors (SABRs).

Supplementary Table 3

The list of epitopes in the A2-SABR library.

Supplementary Table 4

The list of epitopes in the A2-NeoAg library.

Source Data

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Joglekar, A.V., Leonard, M.T., Jeppson, J.D. et al. T cell antigen discovery via signaling and antigen-presenting bifunctional receptors. Nat Methods 16, 191–198 (2019). https://doi.org/10.1038/s41592-018-0304-8

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