Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

HLA-independent T cell receptors for targeting tumors with low antigen density

Nature Medicine volume 28, pages 345–352 (2022)Cite this article

Subjects

Abstract

Chimeric antigen receptors (CARs) are receptors for antigen that direct potent immune responses. Tumor escape associated with low target antigen expression is emerging as one potential limitation of their efficacy. Here we edit the TRAC locus in human peripheral blood T cells to engage cell-surface targets through their T cell receptor–CD3 complex reconfigured to utilize the same immunoglobulin heavy and light chains as a matched CAR. We demonstrate that these HLA-independent T cell receptors (HIT receptors) consistently afford high antigen sensitivity and mediate tumor recognition beyond what CD28-based CARs, the most sensitive design to date, can provide. We demonstrate that the functional persistence of HIT T cells can be augmented by constitutive coexpression of CD80 and 4-1BBL. Finally, we validate the increased antigen sensitivity afforded by HIT receptors in xenograft mouse models of B cell leukemia and acute myeloid leukemia, targeting CD19 and CD70, respectively. Overall, HIT receptors are well suited for targeting cell surface antigens of low abundance.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: TRAC locus editing to create an HLA-independent TCR (HIT receptor) directs TCR–CD3 complex-mediated antigen recognition.
Fig. 2: TRAC-HIT T cells exhibit increased sensitivity for tumor cells expressing low antigen levels relative to TRAC-CAR T cells.
Fig. 3: TRAC-HIT T cells exhibit increased degranulation and rapid killing activity upon exposure to low antigen levels.
Fig. 4: TRAC-HIT T cells outperform TRAC-CAR T cells in controlling low antigen tumor cells in vivo.

Similar content being viewed by others

Data availability

All requests for raw and analyzed preclinical data and materials will be promptly reviewed by the corresponding authors (M.S. and J.M.S.) to determine if they are subject to intellectual property or confidentiality obligations. Any data and materials that can be shared will be released via a material transfer agreement (requested to Michel Sadelain). Sequences for the TRAC-HIT receptors have been submitted under patent no. WO2019157454A1 (19HIT). The TRAC-HIT sequences can be found in the Supplementary Information file.

Code availability

We have generated scripts for the automated analyses of the single-cell CTL assays as well as the actin, CAR, HIT and LAMP-1 signals in the confocal images. Request for these scripts will be promptly reviewed by the corresponding authors (M.S. and J.M.S.) to determine if they are subject to intellectual property or confidential obligations. Any script that can be shared will be released via a material transfer agreement (requested to Michel Sadelain).

References

  1. Sadelain, M., Riviere, I. & Riddell, S. Therapeutic T cell engineering. Nature 545, 423–431 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Eshhar, Z. et al. The T-body approach: potential for cancer immunotherapy. Springer Semin. Immunopathol. 18, 199–209 (1996).

    Article  CAS  PubMed  Google Scholar 

  3. Sadelain, M., Riviere, I. & Brentjens, R. Targeting tumours with genetically enhanced T lymphocytes. Nat. Rev. Cancer 3, 35–45 (2003).

    Article  CAS  PubMed  Google Scholar 

  4. Maher, J., Brentjens, R. J., Gunset, G., Riviere, I. & Sadelain, M. Human T-lymphocyte cytotoxicity and proliferation directed by a single chimeric TCRzeta /CD28 receptor. Nat. Biotechnol. 20, 70–75 (2002).

    Article  CAS  PubMed  Google Scholar 

  5. van der Stegen, S. J., Hamieh, M. & Sadelain, M. The pharmacology of second-generation chimeric antigen receptors. Nat. Rev. Drug Discov. 14, 499–509 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  6. June, C. H. & Sadelain, M. Chimeric antigen receptor therapy. N. Engl. J. Med. 379, 64–73 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Brudno, J. N. & Kochenderfer, J. N. Chimeric antigen receptor T-cell therapies for lymphoma. Nat. Rev. Clin. Oncol. 15, 31–46 (2018).

    Article  CAS  PubMed  Google Scholar 

  8. Turtle, C. J. et al. CD19 CAR-T cells of defined CD4+:CD8+ composition in adult B cell ALL patients. J. Clin. Invest. 126, 2123–2138 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  9. Fry, T. J. et al. CD22-targeted CAR T cells induce remission in B-ALL that is naive or resistant to CD19-targeted CAR immunotherapy. Nat. Med. 24, 20–28 (2018).

    Article  CAS  PubMed  Google Scholar 

  10. Brudno, J. N. et al. T cells genetically modified to express an anti-B-cell maturation antigen chimeric antigen receptor cause remissions of poor-prognosis relapsed multiple myeloma. J. Clin. Oncol.: Off. J. Am. Soc. Clin. Oncol. 36, 2267–2280 (2018).

    Article  CAS  Google Scholar 

  11. Cohen, A. D. et al. B cell maturation antigen-specific CAR T cells are clinically active in multiple myeloma. J. Clin. Invest. 129, 2210–2221 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  12. Maude, S. L. et al. Tisagenlecleucel in children and young adults with B-cell lymphoblastic leukemia. N. Engl. J. Med. 378, 439–448 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Neelapu, S. S. et al. Axicabtagene ciloleucel CAR T-cell therapy in refractory large B-cell lymphoma. N. Engl. J. Med. 377, 2531–2544 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Park, J. H. et al. Long-term follow-up of CD19 CAR therapy in acute lymphoblastic leukemia. N. Engl. J. Med. 378, 449–459 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Schuster, S. J. et al. Tisagenlecleucel in adult relapsed or refractory diffuse large B-cell lymphoma. N. Engl. J. Med. 380, 45–56 (2019).

    Article  CAS  PubMed  Google Scholar 

  16. Shah, N. N. et al. CD4/CD8 T-cell selection affects chimeric antigen receptor (CAR) T-cell potency and toxicity: updated results from a phase I anti-CD22 CAR T-cell trial. J. Clin. Oncol.: Off. J. Am. Soc. Clin. Oncol. 38, 1938–1950 (2020).

    Article  CAS  Google Scholar 

  17. Majzner, R. G. & Mackall, C. L. Tumor antigen escape from CAR T-cell therapy. Cancer Discov. 8, 1219–1226 (2018).

    Article  CAS  PubMed  Google Scholar 

  18. Libert, D. et al. Serial evaluation of CD19 surface expression in pediatric B-cell malignancies following CD19-targeted therapy. Leukemia 34, 3064–3069 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  19. Shah, N. N. & Fry, T. J. Mechanisms of resistance to CAR T cell therapy. Nat. Rev. Clin. Oncol. 16, 372–385 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Xu, X. et al. Mechanisms of relapse after CD19 CAR T-cell therapy for acute lymphoblastic leukemia and its prevention and treatment strategies. Front. Immunol. 10, 1–15 (2019).

    Article  Google Scholar 

  21. Hamieh, M. et al. CAR T cell trogocytosis and cooperative killing regulate tumour antigen escape. Nature 568, 112–116 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Majzner, R. G. et al. Tuning the antigen density requirement for CAR T-cell activity. Cancer Discov. 10, 702–723 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Priceman, S. J. et al. Co-stimulatory signaling determines tumor antigen sensitivity and persistence of CAR T cells targeting PSCA+ metastatic prostate cancer. Oncoimmunology 7, 1–13 (2018).

    Article  Google Scholar 

  24. Eyquem, J. et al. Targeting a CAR to the TRAC locus with CRISPR/Cas9 enhances tumour rejection. Nature 543, 113–117 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Feucht, J. et al. Calibration of CAR activation potential directs alternative T cell fates and therapeutic potency. Nat. Med. 25, 82–88 (2019).

    Article  CAS  PubMed  Google Scholar 

  26. Zhao, Z. et al. Structural design of engineered costimulation determines tumor rejection kinetics and persistence of CAR T cells. Cancer cell 28, 415–428 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Lee, D. W. et al. T cells expressing CD19 chimeric antigen receptors for acute lymphoblastic leukaemia in children and young adults: a phase 1 dose-escalation trial. Lancet 385, 517–528 (2015).

    Article  CAS  PubMed  Google Scholar 

  28. Purbhoo, M. A., Irvine, D. J., Huppa, J. B. & Davis, M. M. T cell killing does not require the formation of a stable mature immunological synapse. Nat. Immunol. 5, 524–530 (2004).

    Article  CAS  PubMed  Google Scholar 

  29. Sykulev, Y., Joo, M., Vturina, I., Tsomides, T. J. & Eisen, H. N. Evidence that a single peptide-MHC complex on a target cell can elicit a cytolytic T cell response. Immunity 4, 565–571 (1996).

    Article  CAS  PubMed  Google Scholar 

  30. Brentjens, R. J. et al. Eradication of systemic B-cell tumors by genetically targeted human T lymphocytes co-stimulated by CD80 and interleukin-15. Nat. Med. 9, 279–286 (2003).

    Article  CAS  PubMed  Google Scholar 

  31. Maude, S. L. et al. Chimeric antigen receptor T cells for sustained remissions in leukemia. N. Engl. J. Med. 371, 1507–1517 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  32. Gross, G., Waks, T. & Eshhar, Z. Expression of immunoglobulin T-cell receptor chimeric molecules as functional receptors with antibody-type specificity. Proc. Natl Acad. Sci. USA 86, 10024–10028 (1989).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Kuwana, Y. et al. Expression of chimeric receptor composed of immunoglobulin-derived V regions and T-cell receptor-derived C regions. Biochem. Biophys. Res. Commun. 149, 960–968 (1987).

    Article  CAS  PubMed  Google Scholar 

  34. Sher, B. T., Nairn, R., Coligan, J. E. & Hood, L. E. DNA sequence of the mouse H-2Dd transplantation antigen gene. Proc. Natl Acad. Sci USA 82, 1175–1179 (1985).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Baeuerle, P. A. et al. Synthetic TRuC receptors engaging the complete T cell receptor for potent anti-tumor response. Nat. Commun. 10, 1–12 (2019).

    Article  CAS  Google Scholar 

  36. Helsen, C. W. et al. The chimeric TAC receptor co-opts the T cell receptor yielding robust anti-tumor activity without toxicity. Nat. Commun. 9, 1–13 (2018).

    Article  CAS  Google Scholar 

  37. Xu, Y. et al. A novel antibody-TCR (AbTCR) platform combines Fab-based antigen recognition with gamma/delta-TCR signaling to facilitate T-cell cytotoxicity with low cytokine release. Cell Disco. 4, 1–13 (2018).

    Article  Google Scholar 

  38. Liu, Y. et al. Chimeric STAR receptors using TCR machinery mediate robust responses against solid tumors. Sci. Transl. Med. 13, 1–16 (2021).

    Article  Google Scholar 

  39. MacKay, M. et al. The therapeutic landscape for cells engineered with chimeric antigen receptors. Nat. Biotechnol. 38, 233–244 (2020).

    Article  CAS  PubMed  Google Scholar 

  40. Gaud, G., Lesourne, R. & Love, P. E. Regulatory mechanisms in T cell receptor signalling. Nat. Rev. Immunol. 18, 485–497 (2018).

    Article  CAS  PubMed  Google Scholar 

  41. Matza, D. et al. A scaffold protein, AHNAK1, is required for calcium signaling during T cell activation. Immunity 28, 64–74 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Schwartzberg, P. L., Mueller, K. L., Qi, H. & Cannons, J. L. SLAM receptors and SAP influence lymphocyte interactions, development and function. Nat. Rev. Immunol. 9, 39–46 (2009).

    Article  CAS  PubMed  Google Scholar 

  43. Randzavola, L. O. et al. Loss of ARPC1B impairs cytotoxic T lymphocyte maintenance and cytolytic activity. J. Clin. Invest. 129, 5600–5614 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Stephan, M. T. et al. T cell-encoded CD80 and 4-1BBL induce auto- and transcostimulation, resulting in potent tumor rejection. Nat. Med. 13, 1440–1449 (2007).

    Article  CAS  PubMed  Google Scholar 

  45. Nguyen, P. et al. Route of 41BB/41BBL costimulation determines effector function of B7-H3-CAR.CD28ζ T cells. Mol. Ther. Oncolytics 18, 202–214 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Perna, F. et al. Integrating proteomics and transcriptomics for systematic combinatorial chimeric antigen receptor therapy of AML. Cancer Cell 32, 506–519 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Riether, C. et al. Targeting CD70 with cusatuzumab eliminates acute myeloid leukemia stem cells in patients treated with hypomethylating agents. Nat. Med. 26, 1459–1467 (2020).

    Article  CAS  PubMed  Google Scholar 

  48. Brugnoni, D. et al. CD70 expression on T-cell subpopulations: study of normal individuals and patients with chronic immune activation. Immunol. Lett. 55, 99–104 (1997).

    Article  CAS  PubMed  Google Scholar 

  49. Kimachi, K., Croft, M. & Grey, H. M. The minimal number of antigen-major histocompatibility complex class II complexes required for activation of naive and primed T cells. Eur. J. Immunol. 27, 3310–3317 (1997).

    Article  CAS  PubMed  Google Scholar 

  50. Henrickson, S. E. et al. T cell sensing of antigen dose governs interactive behavior with dendritic cells and sets a threshold for T cell activation. Nat. Immunol. 9, 282–291 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Dong, R. et al. Rewired signaling network in T cells expressing the chimeric antigen receptor (CAR). EMBO J. 39, 1–14 (2020).

    Article  CAS  Google Scholar 

  52. Liu, X. et al. A chimeric switch-receptor targeting PD1 augments the efficacy of second-generation CAR T cells in advanced solid tumors. Cancer Res. 76, 1578–1590 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Oda, S. K. et al. A CD200R-CD28 fusion protein appropriates an inhibitory signal to enhance T-cell function and therapy of murine leukemia. Blood 130, 2410–2419 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Hendel, A. et al. Chemically modified guide RNAs enhance CRISPR-Cas genome editing in human primary cells. Nat. Biotechnol. 33, 985–989 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Papapetrou, E. P. et al. Genomic safe harbors permit high beta-globin transgene expression in thalassemia induced pluripotent stem cells. Nat. Biotechnol. 29, 73–78 (2011).

    Article  CAS  PubMed  Google Scholar 

  56. Rivière, I., Brose, K. & Mulligan, R. C. Effects of retroviral vector design on expression of human adenosine deaminase in murine bone marrow transplant recipients engrafted with genetically modified cells. Proc. Natl Acad. Sci. USA 92, 6733–6737 (1995).

    Article  PubMed  PubMed Central  Google Scholar 

  57. Navarrete-Perea, J., Yu, Q., Gygi, S. P. & Paulo, J. A. Streamlined tandem mass tag (SL-TMT) protocol: an efficient strategy for quantitative (phospho)proteome profiling using tandem mass tag-synchronous precursor selection-MS3. J. Proteome Res. 17, 2226–2236 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Zucchetti, A. E. et al. Tethering of vesicles to the Golgi by GMAP210 controls LAT delivery to the immune synapse. Nat. Commun. 10, 1–17 (2019).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We thank Gertrude Gunset for logistical and technical assistance. We also thank the SKI Cell Therapy and Cell Engineering (CTCEF), Molecular Cytology, Flow Cytometry, Integrated Genomics Operation, Microchemistry and Proteomics, Antitumor Assessment and Animal Core Facilities for their expert assistance. This work was supported by the Lake Road Foundation, the Lymphoma and Leukemia Society, the Pasteur-Weizmann/Servier award, the Leopold Griffuel award and the NCI Cancer Center Support Grant no. P30 CA008748. SKI cores were in part supported by the Tow Foundation, Cycle for Survival, the Marie-Josée and Henry R. Kravis Center for Molecular Oncology and NCI grant P30 CA08748. A.D., M.S. and T.G. were supported by fellowships from the Canadian Institutes of Health Research, the Fogarty Foundation and the Alexander S. Onassis Public Benefit Foundation, respectively.

Author information

Author notes

  1. Justin Eyquem

    Present address: Department of Medicine, Division of Hemato-Oncology, University of California San Francisco, San Francisco, CA, USA

  2. Judith Feucht

    Present address: Cluster of Excellence iFIT, University Children’s Hospital Tübingen, Tübingen, Germany

  3. Michelle Saetersmoen

    Present address: Department of Cancer Immunology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway

  4. Theodoros Giavridis

    Present address: Mnemo Therapeutics, New York, NY, USA

  5. These authors contributed equally: Jorge Mansilla-Soto, Justin Eyquem.

Authors and Affiliations

  1. Center for Cell Engineering, Memorial Sloan Kettering Cancer Center, New York, NY, USA

    Jorge Mansilla-Soto, Justin Eyquem, Sascha Haubner, Mohamad Hamieh, Judith Feucht, Maria Sjöstrand, Pieter L. Lindenbergh, Michelle Saetersmoen, Anton Dobrin, Archana Iyer, Andreina Garcia Angus, Zeguo Zhao, Theodoros Giavridis, Sjoukje J. C. van der Stegen, Isabelle Rivière & Michel Sadelain

  2. Immunology Program, Sloan Kettering Institute, New York, NY, USA

    Jorge Mansilla-Soto, Justin Eyquem, Sascha Haubner, Mohamad Hamieh, Judith Feucht, Maria Sjöstrand, Pieter L. Lindenbergh, Michelle Saetersmoen, Anton Dobrin, Archana Iyer, Andreina Garcia Angus, Zeguo Zhao, Theodoros Giavridis, Sjoukje J. C. van der Stegen, Fella Tamzalit, Morgan Huse & Michel Sadelain

  3. Institute Curie, Université PSL, U932 INSERM, Integrative Analysis of T cell Activation Team, Paris, France

    Noémie Paillon, Andrés Ernesto Zucchetti, Mathieu Maurin & Claire Hivroz

  4. Microchemistry and Proteomics Core Laboratory, Sloan Kettering Institute, New York, NY, USA

    Zhuoning Li, Matthew M. Miele & Ronald C. Hendrickson

  5. Cell Therapy and Cell Engineering Facility, Memorial Sloan Kettering Cancer Center, New York, NY, USA

    Isabelle Rivière

  6. Molecular Pharmacology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA

    Isabelle Rivière & Ronald C. Hendrickson

Authors
  1. Jorge Mansilla-Soto
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Justin Eyquem
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sascha Haubner
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Mohamad Hamieh
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Judith Feucht
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Noémie Paillon
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Andrés Ernesto Zucchetti
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Zhuoning Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Maria Sjöstrand
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Pieter L. Lindenbergh
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Michelle Saetersmoen
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Anton Dobrin
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Mathieu Maurin
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Archana Iyer
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Andreina Garcia Angus
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Matthew M. Miele
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Zeguo Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Theodoros Giavridis
    View author publications

    You can also search for this author in PubMed Google Scholar

  19. Sjoukje J. C. van der Stegen
    View author publications

    You can also search for this author in PubMed Google Scholar

  20. Fella Tamzalit
    View author publications

    You can also search for this author in PubMed Google Scholar

  21. Isabelle Rivière
    View author publications

    You can also search for this author in PubMed Google Scholar

  22. Morgan Huse
    View author publications

    You can also search for this author in PubMed Google Scholar

  23. Ronald C. Hendrickson
    View author publications

    You can also search for this author in PubMed Google Scholar

  24. Claire Hivroz
    View author publications

    You can also search for this author in PubMed Google Scholar

  25. Michel Sadelain
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

J.M.-S. and J.E. designed the study, performed experiments, analyzed and interpreted data and wrote the manuscript. S.H. designed and performed experiments, and analyzed data. M.H., J.F., N.P., A.E.Z., Z.L., M.S., P.L.L., M. Saetersmoen, A.D. and M.M. performed experiments and analyzed data. A.I. performed statistical analysis. A.G.A., M.M.M., Z.Z., T.G., S.J.C.v.d.S. and F.T. performed experiments. M. Huse designed experiments. I.R., R.C.H. and C.H. designed experiments and interpreted data. M.S. designed the study, analyzed and interpreted data, and wrote the manuscript.

Corresponding authors

Correspondence to Jorge Mansilla-Soto or Michel Sadelain.

Ethics declarations

Competing interests

Memorial Sloan Kettering has submitted a patent application based in part on results presented in this manuscript (WO2019157454A1, J.M.-S., J.E. and M.S. are listed among the inventors). R.C.H. reports stock ownership in Merck. M.S. reports research funding from Juno Therapeutics, Fate Therapeutics, Takeda Pharmaceuticals and Atara Biotherapeutics, unrelated to the present research. M.S., I.R. and J.E. are scientific cofounders of Mnemo Therapeutics. M.S. serves on the scientific advisory board of St. Jude Children Research Hospital. All other authors declare no competing interests.

Peer review

Peer review information

Nature Medicine thanks Cliona Rooney and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Saheli Sadanand was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 HIT receptor expression driven by the TCRα promoter rescues CD3 expression and directs lysis of CD19 + target cells.

a. Representative flow cytometry analysis showing HIT, CAR, and CD3 expression. TRAC-HIT and TRAC-CAR T cells were generated as in Fig. 1b. CD3 surface expression is only observed in TRAC-HIT T cells due to the presence of Cα and Cβ in the HIT receptor. b. HIT/CAR mean fluorescence intensity (MFI) measured by FACS using AF647-GAM. (left) HIT/CAR histograms (representative experiment) and (right) HIT/CAR MFI; n = 6 independent experiments, 3 donors. c. Representative cytotoxic activity using an 18 h bioluminescence assay, using firefly luciferase (FFL)-expressing NALM6 as targets cells (n = 2 independent experiments on 3 healthy donors). CD19-specific TRAC-HIT and TRAC-CAR T cells were generated using two different CD19-specific binding domains, SJ25C1 and FMC63. All data are mean ± s.e.m.

Extended Data Fig. 2 HIT receptors provide antigen-specific T cell-mediated cytotoxicity.

Cytotoxic activity using an 18 h bioluminescence assay, using firefly luciferase (FFL)-expressing targets cells (n = 2 independent experiments on 2 healthy donors). CD19-, BCMA-, and CD70-specific TRAC-HIT T cells, and untransduced (UT) T cell controls were incubated with either NALM6 (CD19 + ), MOLM13/CD19 (CD70 + , CD19 + ), MM1S (BCMA + , CD70 + , CD19 + ), SK-MEL-37/CD19 (CD19 + , CD70 + ), and knock-out (KO) control cell lines. CD19, BCMA, and CD70 genes were CRISPR/Cas9-edited in NALM6, MM1S, and MOLM13 cell lines, respectively. Top 4 groups show data for donor 1 (left panel), donor 2 (middle panel), and both together (right panel). All data are mean ± s.e.m.

Extended Data Fig. 3 HIT receptor elicits cytokine response upon antigen stimulation; cell surface HIT receptor expression is modulated by exposure to antigen.

a. TRAC-Untransduced (UT), TRAC-HIT (HIT) and TRAC-CAR (CAR) T cells were stimulated on CD19 + target for 24 h before supernatant were collected and analysed by flow cytometry to quantify IFNγ, IL-2, TNFα, and granzyme B (n = 3 independent experiments on 3 donors). b. TRAC-HIT and TRAC-CAR T cells stimulated on CD19 + target cells 1, 2 or 4 times over a 48 h period were analysed by flow cytometry using the GAM, CD4, and CD8 antibodies. Plots indicate relative HIT or CAR MFI (1 = MFI at 0 h) of CD4 and CD8 TRAC-HIT or TRAC-CAR T cells, respectively. (n = 3 independent experiments on 3 donors). c. Untransduced (UT), HIT and CAR T cells stimulated on CD19 + target cells either 0, 1, 2 or 4 times over a 48 h period were analysed by flow cytometry. Plots indicate the percentage of the CAR positive T cells measured by flow cytometry analysis of CD4 and CD8 (n = 3 independent experiments on 3 donors). All data are mean ± s.e.m.

Extended Data Fig. 4 Antigen binding depends on HIT receptor affinity.

a. Representative flow cytometry analysis showing CD19 binding. TRAC-HIT and TRAC-CAR T cells were incubated with a recombinant human CD19-Fc fusion, which was then detected using an anti-hFc-PE antibody. b. HIT/CAR mean fluorescence intensity (MFI) measured by FACS using AF647-goat anti human (GAH) antibody (representative experiment). c. Plot of CD19 binding (adjusted gMFI) vs CD19 binder affinity (n = 2 independent experiments). Geometric MFI for CD19 biding (PE signal from a.) was adjusted to the gMFI of the HIT/CAR receptor (AF647 signal from b.) All data are mean ± s.e.m.

Extended Data Fig. 5 HIT receptors provide greater antigen sensitivity than CARs.

a. Representative histogram of the CD19 expression in NALM6/WT, NALM6/Medium21, NALM6/Low21, and CRISPR-edited NALM6/Very Low (this study). b. NALM6/Very Low cells were used to generate single cell clones by limited dilution. CD19 expression was evaluated for each clone (blue histogram) along with the initial NALM6/Very Low cell population (red histogram); clone number indicated above the histogram plot. c. Schematics of the SIN lentiviral vector used to express low levels of CD19 in NALM6/12 cells. PGK100: short PGK promoter, which is a weak promoter24. d. Panel of NALM6 cells expressing different CD19 levels, which is represented as a histogram. NALM6/12-4 and NALM6/12-39 are derivatives of NALM6/12, which was transduced with the lentiviral vector described in c. e. Total CD19 protein quantification using mass spectrometry. Protein levels are expressed in terms of peptide abundance (A.U.), which can be compared across all samples analysed at the same time. A-D represent 4 independent analyses. AVG, average of A-D values. f. Representative cytotoxic activity using an 18 h bioluminescence assay, using FFL-expressing NALM6 as targets cells (clone numbers as in b and d); n = 2. CD19-specific TRAC-HIT and TRAC-CAR T cells were generated using two different CD19-specific binding domains, SJ25C1 and FMC63. Anova test was used to compare the CTL curves of all T cells for NALM6/2 and NALM6/7 cells. g. Representative cytotoxic activity using an 18 h bioluminescence assay, using FFL-expressing NALM6 as targets cells (same as in f); n = 2. CD19-specific TRAC-1928z, TRAC-19BBz, and TRAC-19z1 T cells were prepared as described in Materials and methods. Anova test was used to compare the CTL curves of all T cells for NALM6/2 cells. All data are mean ± s.e.m.

Extended Data Fig. 6 CD19, CD22, and BCMA HIT receptors elicit T cell-mediated lysis of multiple myeloma cells.

a. Representative flow cytometry analysis showing CD19, CD22, and BCMA expression in MM1S and NALM6/WT cells. b. Total CD19, CD22, and BCMA protein quantification using mass spectrometry. Protein levels are expressed in terms of peptide abundance (A.U.), which can be compared across all samples analysed at the same time. A-D represent 4 independent analyses. AVG, average of A-D values. c. Representative cytotoxic activity using an 18-h bioluminescence assay, using FFL-expressing MM1S as targets cells, which were incubated at the indicated E/T ratios with CD19-, CD22-, or BCMA-specific TRAC-HIT and TRAC-CAR T cells; n = 3. All data are mean ± s.e.m. Additional specificity studies are shown in Extended Data Fig. 2.

Extended Data Fig. 7 HIT T cells show increased signalling response to low antigen levels.

a. Gating strategy used to quantify ITAM3, ZAP70, and ERK1/2 phosphorylation in TRAC-HIT/CAR T cells (histograms shown in b.). b. Representative flow cytometry analysis showing histograms for intracellular phospho-ITAM3, phospho-ZAP70, and phospho-ERK1/2 in TRAC-HIT (left) and TRAC-CAR (right) T cells when incubated with NAML6/WT, NALM6/12-4, or NALM6/7 target cells at 1:2 ratio for 15 min, or with no target (No stim.). FMO: fluorescence minus one control. Geometric MFIs were obtained for each curve, and used to generate the plots presented in Fig. 2g. All data are mean ± s.e.m.

Extended Data Fig. 8 HIT T cells display increased degranulation upon stimulation.

a. Confocal and bright field images of conjugates of T cells expressing the CAR or HIT receptor and interacting for 30 min with NALM6/WT cells labeled for LAMP-1 (red channel) and Alexa Fluor 546 phalloidin (F-actin staining showed in green). Quantification of the lysosome polarity assessed as the distance to the immune synapse and compared with the average lysosomal distance to the total cortex of the T cell. This distance was normalized with the maximum distance found in the T cell and expressed as a polarity index between 1 (lysosomes at the synapse) and 0 (lysosomes at the opposite of the synapse. Data from two independent experiments; n = 59. Variance p-values were obtained by using unpaired t-test analysis. All data are mean ± s.e.m. Scale bar = 5 µm. White arrows indicate LAMP-1 signal. b. FACS plot gates used to quantify T cell degranulation (CD107a + cells). b. Representative (n = 2 independent experiments) analyses of CD107a levels in TRAC-HIT (top) and TRAC-CAR (bottom) T cells when incubated for 1 h (left) or 4 h (right) without or with NALM6 targets of different CD19 levels.

Extended Data Fig. 9 Control of low-antigen tumours by HIT T cells is enhanced by extending T cell persistence by co-expression of CD80 and 4-1BBL.

a. NALM6/12-4-bearing mice were treated with 4 × 105 TRAC-HIT T cells co-expressing the annotated costimulatory ligand. Tumour burden was quantified weekly over a 35-day period, at week 1 or week 3. Each line represents 5 mice. b. NALM6/12-4-bearing mice were treated with 4 × 105 CAR T cells (n = 5 per group; dot = one mouse) and euthanized at days 10 and 17 after infusion; bone marrow TRAC-HIT or TRAC-CAR T cells and NALM6 cells were analysed and counted by FACS. c. Same as in b, except that bone marrow TRAC-HIT or TRAC-CAR CD4 and CD8 T cells counted by FACS. Two-tailed unpaired Student’s t-tests were used for statistical analyses. All data are mean ± s.e.m. Tumor burden of individual animals are shown in Supplementary Fig. 2.

Extended Data Fig. 10 Co-expression of costimulatory ligands CD80 and 4-1BBL enhances the therapeutic potential of HIT cells.

a. Tumour burden (average radiance) of NALM6/12-4-bearing mice treated with 4 × 105 TRAC-HIT or TRAC-CAR T cells (n = 5), analysed through a 35-day period. b. Tumour burden (average radiance) of MM1S-bearing mice treated with 2 × 105 TRAC-HIT or TRAC-CAR T cells (n = 5), analysed through a 35-day period. c. Kaplan-Meier analysis of survival of MM1S-bearing mice treated with 4 × 105 BCMA-specific TRAC-HIT or TRAC-HIT + 80/BBL T cells (n = 5). d. Representative FACS plots of surface CD70 expression in activated CAR-T cells 4 days after electroporation without (mock) or with CD70-specific CRISPR/Cas9 RNP. e. Tumour burden (average radiance) of MOLM13-bearing mice treated with 4 × 105 TRAC-HIT or RV-CAR T cells (n = 5), analysed through a 35-day period. All data are mean ± s.e.m. Tumor burden of individual animals are shown in Supplementary Figs. 2,3.

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mansilla-Soto, J., Eyquem, J., Haubner, S. et al. HLA-independent T cell receptors for targeting tumors with low antigen density. Nat Med 28, 345–352 (2022). https://doi.org/10.1038/s41591-021-01621-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41591-021-01621-1

This article is cited by

Search

Advanced search

Quick links

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research