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TRBC1-targeting antibody–drug conjugates for the treatment of T cell cancers

Nature volume 628, pages 416–423 (2024)Cite this article

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Abstract

Antibody and chimeric antigen receptor (CAR) T cell-mediated targeted therapies have improved survival in patients with solid and haematologic malignancies1,2,3,4,5,6,7,8,9. Adults with T cell leukaemias and lymphomas, collectively called T cell cancers, have short survival10,11 and lack such targeted therapies. Thus, T cell cancers particularly warrant the development of CAR T cells and antibodies to improve patient outcomes. Preclinical studies showed that targeting T cell receptor β-chain constant region 1 (TRBC1) can kill cancerous T cells while preserving sufficient healthy T cells to maintain immunity12, making TRBC1 an attractive target to treat T cell cancers. However, the first-in-human clinical trial of anti-TRBC1 CAR T cells reported a low response rate and unexplained loss of anti-TRBC1 CAR T cells13,14. Here we demonstrate that CAR T cells are lost due to killing by the patient’s normal T cells, reducing their efficacy. To circumvent this issue, we developed an antibody–drug conjugate that could kill TRBC1+ cancer cells in vitro and cure human T cell cancers in mouse models. The anti-TRBC1 antibody–drug conjugate may provide an optimal format for TRBC1 targeting and produce superior responses in patients with T cell cancers.

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Fig. 1: Anti-TRBC1 CAR T cell activity is limited by normal T cell-mediated killing of the CAR T cells.
Fig. 2: Anti-TRBC1 antibody binding to the TRBC1+ TCR leads to antibody internalization into lysosomes.
Fig. 3: The performance of anti-TRBC1–SG3249 ADC in vitro.
Fig. 4: Anti-TRBC1–SG3249 ADC kills cancer cells in the presence of normal T cells.
Fig. 5: ADC activity in vivo.

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Data availability

The anti-TRBC1 CAR amino acid sequence, sequences of reagents used for CRISPR editing of T cells and sequence of the anti-TRBC1 chimeric antibody are available in Supplementary Tables 1–3. Plasmids generated for this study can be accessed through GenBank (PP212885 and PP212886). Source data are provided with this paper.

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Acknowledgements

We thank R. Ambinder, M. Popoli, J. Cohen, A. Tam, C. Blair, K. Judge, K. Helwig and L. Wang for scientific and technical support; and the patients and the biorepositories at the Johns Hopkins, Dana-Farber Cancer Institute and St Jude Children’s Research Hospital. The illustrations were generated using BioRender and ChemDraw. This work was supported by grants from The Virginia and D.K. Ludwig Fund for Cancer Research, Lustgarten Foundation for Pancreatic Cancer Research, Commonwealth Fund, Bloomberg~Kimmel Institute for Cancer Immunotherapy, Bloomberg Philanthropies, NIH Cancer Center Support Grant P30 CA006973. S.P. was supported by NCI grant K08CA270403, the Leukemia Lymphoma Society Translation Research Program award, the American Society of Hematology Scholar award and the Swim Across America Translational Cancer Research Award; B.J.M., S.R.D. and A.H.P. by NIH grant T32 GM136577; T.D.N. by NCI grant T32 CA153952; M.F.K. by NIH/NIAID grant 1R21AI176764-01, the Jerome Greene Foundation and the Cupid Foundation; and C.B. by NCI grant R37 CA230400.

Author information

Author notes

  1. Michael S. Hwang

    Present address: Genentech, San Francisco, CA, USA

  2. Sandra B. Gabelli

    Present address: Discovery Chemistry, Merck Research Laboratory, Merck and Co, West Point, PA, USA

Authors and Affiliations

  1. Ludwig Center and Lustgarten Laboratory, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA

    Tushar D. Nichakawade, Jiaxin Ge, Brian J. Mog, Bum Seok Lee, Alexander H. Pearlman, Michael S. Hwang, Sarah R. DiNapoli, Nicolas Wyhs, Nikita Marcou, Stephanie Glavaris, Maximilian F. Konig, Evangeline Watson, Nickolas Papadopoulos, Chetan Bettegowda, Kenneth W. Kinzler, Shibin Zhou, Surojit Sur, Bert Vogelstein & Suman Paul

  2. Howard Hughes Medical Institute, Chevy Chase, MD, USA

    Tushar D. Nichakawade, Jiaxin Ge, Brian J. Mog, Bum Seok Lee, Alexander H. Pearlman, Michael S. Hwang, Sarah R. DiNapoli, Nicolas Wyhs, Nikita Marcou, Stephanie Glavaris, Maximilian F. Konig, Evangeline Watson, Surojit Sur & Bert Vogelstein

  3. Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, USA

    Tushar D. Nichakawade

  4. Institute for NanoBioTechnology, Johns Hopkins University, Baltimore, MD, USA

    Tushar D. Nichakawade & Maximilian F. Konig

  5. Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA

    Brian J. Mog

  6. Division of Rheumatology, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD, USA

    Maximilian F. Konig

  7. Bloomberg~Kimmel Institute for Cancer Immunotherapy, Sidney Kimmel Comprehensive Cancer Center, Baltimore, MD, USA

    Sandra B. Gabelli, Drew M. Pardoll, Kenneth W. Kinzler, Shibin Zhou & Bert Vogelstein

  8. Department of Oncology, Johns Hopkins School of Medicine, Baltimore, MD, USA

    Sandra B. Gabelli, Drew M. Pardoll, Kathy Gabrielson, Nickolas Papadopoulos, Kenneth W. Kinzler, Shibin Zhou, Surojit Sur & Bert Vogelstein

  9. Division of Hematologic Malignancies and Bone Marrow Transplantation, Department of Oncology, Johns Hopkins School of Medicine, Baltimore, MD, USA

    Cole Sterling, Nina Wagner-Johnston, Lode Swinnen, Ephraim Fuchs & Suman Paul

  10. Department of Dermatology, Johns Hopkins School of Medicine, Baltimore, MD, USA

    Sima Rozati

  11. Department of Pathology, Johns Hopkins School of Medicine, Baltimore, MD, USA

    Kathy Gabrielson, Nickolas Papadopoulos & Bert Vogelstein

  12. Department of Neurosurgery, The Johns Hopkins University School of Medicine, Baltimore, MD, USA

    Chetan Bettegowda

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  1. Tushar D. Nichakawade
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Contributions

S.P., T.D.N., K.W.K., B.V., S.Z. and N.P. conceived the study. S.P., T.D.N., J.G., S.S., B.J.M. and M.S.H. developed the methods. T.D.N., J.G. and S.P. generated the CAR T cells, ADCs and conducted in vitro assays. T.D.N., J.G., E.W., B.S.L., K.G. and S.P. conducted in vivo studies. T.D.N., J.G., B.J.M., A.H.P., M.S.H., S.R.D., N.W., N.M., S.G., M.F.K., S.B.G., C.S., N.W.-J., S.R., L.S., E.F., D.M.P., N.P., C.B., K.G., K.W.K., S.Z., S.S., B.V. and S.P. assisted with analysis and interpretation of data. S.P., T.D.N. and B.V. wrote the original draft. All of the authors reviewed and edited the final manuscript. S.P. and B.V. supervised the study.

Corresponding author

Correspondence to Suman Paul.

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Competing interests

The Johns Hopkins University has filed patent applications related to technologies described in this paper on which S.P., T.D.N., B.V., K.W.K., N.P. and S.Z. are listed as inventors. S.P. is a consultant to Merck, owns equity in Gilead and received payment from IQVIA and Curio Science. B.V., K.W.K. and N.P. are founders of Thrive Earlier Detection, an Exact Sciences Company. K.W.K. and N.P. are consultants to Thrive Earlier Detection. B.V., K.W.K., N.P. and S.Z. hold equity in Exact Sciences. B.V., K.W.K., N.P. and S.Z. are founders of or consultants to and own equity in ManaT Bio, Neophore and Personal Genome Diagnostics. B.V., K.W.K. and N.P. hold equity in Haystack Oncology and CAGE Pharma. N.P. is a consultant to Vidium. M.F.K. received personal fees from Argenx, Atara Biotherapeutics, Revel Pharmaceuticals, Sana Biotechnology, Sanofi and Doximity, all unrelated to this work. B.V. is a consultant to and holds equity in Catalio Capital Management. S.Z. has a research agreement with BioMed Valley Discoveries. C.B. is a consultant to Depuy-Synthes, Bionaut Labs, Haystack Oncology, Privo Technologies and Galectin Therapeutics; a co-founder of OrisDx; and a co-founder of Belay Diagnostics. D.M.P. reports grant and patent royalties through institution from BMS, a grant from Compugen, stock from Trieza Therapeutics and Dracen Pharmaceuticals and founder equity from Potenza; being a consultant for Aduro Biotech, Amgen, Astra Zeneca (Medimmune/Amplimmune), Bayer, DNAtrix, Dynavax Technologies Corporation, Ervaxx, FLX Bio, Rock Springs Capital, Janssen, Merck, Tizona and Immunomic Therapeutics; being on the scientific advisory board of Five Prime Therapeutics, Camden Nexus II, WindMil; and being on the board of directors for Dracen Pharmaceuticals. The companies named above, as well as other companies, have licensed previously described technologies related to the work described in this paper from Johns Hopkins University. B.V., K.W.K. and N.P. are listed as inventors of some of these technologies. Licences to these technologies are or will be associated with equity or royalty payments to the inventors as well as to Johns Hopkins University. Patent applications on the work described in this paper may be filed by Johns Hopkins University. The terms of all of these arrangements are being managed by Johns Hopkins University according to its conflict of interest policies.

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Extended data figures and tables

Extended Data Fig. 1 Generation and testing of anti-TRBC1 CAR T cells.

a, b, Illustration depicting the anti-TRBC1 CAR construct c, CAR T cells were stained with anti-mouse scFv-PE antibody or anti-NGFR-APC antibody followed by analysis using flow cytometry. Control T cells indicate staining in unedited T cells. d, The aggregate data of the experiment is shown in Fig. 1a. CAR T cells were incubated with cancer cells (SUP-T1 or H9 or Jurkat cells) for 48 h. The percentage of surviving cancer cells is shown in the bar graphs. Bar graphs represent mean ± standard error of mean using three technical replicates. Number of biological replicates, n = 2. e, The aggregate data of the experiment is shown in Fig. 1c. CAR T cells were incubated with normal T cells. Flow cytometry was used to assess NGFR and TRBC1 expression after 48 h. The percentage of surviving normal TRBC1+ or TRBC2+ T cells and CAR T cells are shown in the bar graphs. Bar graphs represent mean ± standard error of mean using three technical replicates. Number of biological replicates, n = 3. f, g, Anti-TRBC1 CAR T cells (2.5 × 104) were incubated with 2.5 × 104 (1:1) or 5 × 104 (1:2) or 12.5 × 104 (1:5) Jurkat cells, in the presence or absence of normal T cells. After 48 h, flow cytometry was used to assess GFP and NGFR expression. Numbers beside flow plots show the percentage of surviving cells in each condition (f) and aggregate data from three technical replicates are shown in (g). Bar graphs represent mean ± standard error of mean. Number of biological replicates, n = 3. In (d, e, g) p values obtained by one-way ANOVA with Šidák’s multiple comparison test. The diagrams in a and b were created using BioRender.

Extended Data Fig. 2 Synthesis and characterization of anti-TRBC1 ADCs.

a, Schematic of the anti-TRBC1 antibody conjugation to SG3249. b, Hydrophobic interaction chromatography of anti-TRBC1 antibody, SG3249 and anti-TRBC1-SG3249 ADC. Number of repeated experiments, n = 4. c, The deconvoluted mass spectra of the anti-TRBC1 antibody and the anti-TRBC1-SG3249 ADC. HC = heavy chain and LC = light chain. HC+1 and HC+2 indicate heavy chains conjugated with one or two molecules of SG3249. LC+1 indicates light chain conjugated with one molecule of SG3249. Number of repeated experiments, n = 2. d, Size exclusion chromatography (SEC) of anti-TRBC1-SG3249 and anti-TRBC1 antibody. SEC standards include: A, thyroglobulin (MW 670 kDa); B, gamma globulin (MW 158 kDa); C, ovalbumin (MW 44 kDa); D, myoglobin (MW 17 kDa); E, vitamin B12 (MW 1.35 kDa). e, Schematic representation of the anti-TRBC1 antibody conjugation to MC-VC-MMAE. f, Hydrophobic interaction chromatography analysis of anti-TRBC1 antibody, MC-VC-MMAE and anti-TRBC1-MMAE ADC. Number of repeated experiments, N = 2.

Extended Data Fig. 3 Anti-TRBC1-SG3249 stability and binding epitope.

a, Anti-TRBC1-SG3249 ADC was incubated in human serum at 7 µg/mL concentration for 0, 3, and 7 days at 37 °C. After incubation with human serum, anti-TRBC1-ADC (at 100 ng/mL) was added to TRBC1+ cells (Jurkat and H9) and TRBC1- cells (HPB-ALL and SUP-T1). After 5 days, cancer cell viability was assessed using luminescence. Bar graphs represent mean ± standard error of mean using three technical replicates. Number of biological replicates n = 3. b, TRBC1 and TRBC2 amino acid sequence alignment. The distinct amino acid residues are highlighted in red. The anti-TRBC1 antibody binding epitope at position 3,4 are shown inside a box. c, Jurkat, Jurkat TCR-KO, Jurkat TRBC2+, HPBALL or HPB-ALL TRBC1+ cancer cell lines were stained with anti-TRBC1-PE antibody. The histograms of the anti-TRBC1-PE stain of the indicated cell lines are shown on the left. The nucleotide and amino acid sequences of the anti-TRBC1-antibody binding epitope are shown on the right.

Extended Data Fig. 4 Anti-TRBC1-SG3249 kills TRBC1+ cells in vivo.

a, b, Flow cytometry to assess Jurkat cells (CD3 + , GFP + , top right quadrant) on day 205, from bone marrow of mice treated with anti-TRBC1-SG3249 in Fig. 5a. For positive control, 5 mice were injected with 1 × 106 Jurkat cells followed flow cytometry from bone marrow on day 21 “Jurkat injected NSG mice no ADC”. Data from 5 mice in each group shown in (b). c, TapeStation gel image of PCR product from mouse cells (black arrowhead shows amplified mouse β2 microglobulin sequence, 343 base pairs) and Jurkat cells (grey arrowhead shows amplified IVISbrite Red-F-luc-GFP sequence in Jurkat cells, 199 base pairs). Negative control “neg control” indicates sample with no input DNA, positive control “pos control” indicates sample with input DNA from mouse EMT6 cells and Red-F-luc-GFP transduced Jurkat cells. Data from 5 mice in each group shown in (c). d, Weights of 5 mice in each group as means ± S.E.M from Fig. 5a. e, Representative sections of hematoxylin and eosin-stained skin and liver from the 5 mice treated with anti-TRBC1-SG3249 ADC as in Fig. 5a. Untreated mice used as control (NSG mice, no ADC). Number of biological replicates, n = 5. f, Bioluminescence imaging of H9-injected NSG mice used in experiment Fig. 5g. g, Weights of 5 mice in each group as means ± S.E.M from Fig. 5g. h, Timeline of in vivo experiment using NSG mice injected with Jurkat cells and normal human T cells. On day 12, mice received mIgG2a-SG3249 or anti-TRBC1-SG3249 ADC. i, j, Flow cytometry on day 20 to assess Jurkat cells (CD3 + , GFP + , top right quadrant), normal human T cells (CD3 + , GFP-, top left quadrant), and aggregate data from 3 mice shown in (f). In (b) p value by two-tailed Mann-Whitney test. In (j) p values by one-way ANOVA with Šidák’s multiple comparison test. The diagram in h was created using BioRender.

Source Data

Extended Data Fig. 5 Anti-TRBC1-SG3249 kills TRBC1+ patient-derived xenografts.

a, Jurkat, Jurkat TCR-KO, and T cell cancer PDX samples were stained with anti-TCRαβ-APC and anti-TRBC1-PE antibodies. b, Timeline of in vivo experiment using NSG mice injected with PDX cells. On day 25, mice were intravenously injected with either mIgG2a-SG3249 or anti-TRBC1-SG3249 ADC. c, d, Flow cytometry on day 21 and day 33 to assess circulating PDX cells (gated on the top right CD3 + , and TRBC1+ cells), and aggregate data from 4 mice are shown in (d). In (d) p value obtained by one-way ANOVA with Šidák’s multiple comparison test. The diagram in b was created using BioRender.

Source Data

Extended Data Fig. 6 Chimeric anti-TRBC1-SG3249 ADC has comparable cytotoxicity.

a, Schematic representation of the mouse IgG2a anti-TRBC1 antibody and chimeric IgG1 anti-TRBC1 antibody. The mouse IgG2a heavy chain (HC) and kappa light chain (LC) constant regions were replaced with human IgG1 HC and human kappa LC constant regions. b, Hydrophobic interaction chromatography analysis of chimeric anti-TRBC1 antibody and chimeric anti-TRBC1-SG3249 ADC. Number of repeated experiments n = 2. c, H9 or Jurkat cells were incubated with indicated concentrations of anti-TRBC1-SG3249 ADC or chimeric anti-TRBC1-SG3249 ADC for 5 days. The H9 and Jurkat cells expressed luciferase and luminescence was used to assess cell viability. Data plotted as means ± standard error of mean from three technical replicates. The calculated IC50 for anti-TRBC1-SG3249 and chimeric anti-TRBC1-SG3249 ADC is shown at the right of the graphs. Number of repeated experiments n = 3. The diagram in a was created using BioRender.

Extended Data Table 1 Cytotoxicity of indicated drugs in different T cell cancer cell lines
Full size table
Extended Data Table 2 The calculated drug antibody ratio (DAR) for anti-TRBC1-SG3249, anti-TRBC1-MMAE and chimeric anti-TRBC1-SG3249 antibodies
Full size table
Extended Data Table 3 Cytotoxicity of the indicated antibody-drug conjugates (ADC) in different T cell cancer cell lines
Full size table

Supplementary information

Supplementary Information

Supplementary Figs. 1–2 (flow cytometry gating strategies) and Supplementary Tables 1–3.

Reporting Summary

Supplementary Video 1

Live-cell imaging of anti-TRBC1–pHrodo antibody added to Jurkat cells.

Supplementary Video 2

Live-cell imaging of anti-TRBC1–pHrodo antibody added to Jurkat TCR-KO cells.

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Nichakawade, T.D., Ge, J., Mog, B.J. et al. TRBC1-targeting antibody–drug conjugates for the treatment of T cell cancers. Nature 628, 416–423 (2024). https://doi.org/10.1038/s41586-024-07233-2

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