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Single-cell transcriptomic atlas-guided development of CAR-T cells for the treatment of acute myeloid leukemia

Nature Biotechnology volume 41, pages 1618–1632 (2023)Cite this article

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Abstract

Chimeric antigen receptor T cells (CAR-T cells) have emerged as a powerful treatment option for individuals with B cell malignancies but have yet to achieve success in treating acute myeloid leukemia (AML) due to a lack of safe targets. Here we leveraged an atlas of publicly available RNA-sequencing data of over 500,000 single cells from 15 individuals with AML and tissue from 9 healthy individuals for prediction of target antigens that are expressed on malignant cells but lacking on healthy cells, including T cells. Aided by this high-resolution, single-cell expression approach, we computationally identify colony-stimulating factor 1 receptor and cluster of differentiation 86 as targets for CAR-T cell therapy in AML. Functional validation of these established CAR-T cells shows robust in vitro and in vivo efficacy in cell line- and human-derived AML models with minimal off-target toxicity toward relevant healthy human tissues. This provides a strong rationale for further clinical development.

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Fig. 1: A scRNA-seq-based screening approach identifies CSF1R and CD86 as potential CAR targets in AML.
Fig. 2: CSF1R and CD86 are preferentially expressed on malignant HSPC-like cells compared to healthy HSPCs, and off-tumor expression is restricted to infiltrating or tissue-resident immune cells.
Fig. 3: mCSF1R CART do not cause toxicity in mice.
Fig. 4: Anti-target CAR-T cells are functional and efficiently lyse AML cell lines in vitro and in vivo.
Fig. 5: CSF1R and CD86 are readily detected on primary AML samples, and hCSF1R CART show efficient lysis of primary AML samples in vitro and in vivo.
Fig. 6: hCSF1R CART show better discriminatory capacity toward healthy human hematopoietic cells than CD33 CART.

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Data availability

Data from publicly available scRNA-seq studies can be found via the following accession numbers or the provided links: GSE116256 (ref. 21), https://zenodo.org/record/3345981 (ref. 39), https://www.gtexportal.org/home/datasets (ref. 27), GSE134355 (ref. 37), https://www.gutcellatlas.org/ (ref. 36), GSE131907 (ref. 28), GSE115469 (ref. 33), https://www.tissuestabilitycellatlas.org/ (ref. 31), GSE136103 (ref. 34), https://nupulmonary.org/resources/ (ref. 32), https://www.kidneycellatlas.org/ (ref. 29), https://www.synapse.org/#!Synapse:syn21041850/files/ (ref. 30) and EGAS00001002927 (ref. 35). Data from publicly available bulk sequencing studies can be found via the accession numbers E-MTAB-5214 (ref. 82) and E-MTAB-2801 (ref. 83) via the Expression Atlas (https://www.ebi.ac.uk/gxa/home). The surface gene library was obtained by integrating publicly available data23,24,25,26 using OmniPath22 (https://omnipathdb.org/). Targets of FDA-approved drugs were obtained using DrugBank (https://go.drugbank.com/). All reagents and biological material will be made available upon reasonable request to the authors given the agreement by the providing institution.

Code availability

Python scripts for replicating the figures from the scRNA-seq data as jupyter notebooks can be found in the GitHub repository at https://github.com/marrlab/CAR_T_TargetIdentification ref. 96. Count matrices of processed scRNA-seq data will be made available upon reasonable request.

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Acknowledgements

This study was supported by the Förderprogramm für Forschung und Lehre der Medizinischen Fakultät der LMU (grant number 1138 to A.G.), the Bavarian Cancer Research Center (A.G.), the Deutsche Forschungsgemeinschaft (DFG; grant number GO 3823/1-1 to A.G.; grant number KO5055/3-1 and KO5055-2-1 to S.K.), the international doctoral program ‘i-Target: immunotargeting of cancer’ (funded by the Elite Network of Bavaria; to S.K. and S.E.), the Melanoma Research Alliance (grant number 409510 to S.K.), Marie Sklodowska-Curie Training Network for the Immunotherapy of Cancer (IMMUTRAIN; funded by the Horizon 2020 program of the European Union; to S.E. and S.K.), Marie Sklodowska-Curie Training Network for Optimizing Adoptive T Cell Therapy of Cancer (funded by the Horizon 2020 program of the European Union; grant 955575 to S.K.), Else Kröner-Fresenius-Stiftung (to S.K.), German Cancer Aid (to S.K.), the Wilhelm-Sander-Stiftung (to S.K.), Ernst Jung Stiftung (to S.K.), Institutional Strategy LMUexcellent of LMU Munich (within the framework of the German Excellence Initiative; to S.E. and S.K.), the Go-Bio-Initiative (to S.K.), the m4-Award of the Bavarian Ministry for Economical Affairs (to S.E. and S.K.), Bundesministerium für Bildung und Forschung (to S.E. and S.K.), European Research Council (Starting Grant 756017 and PoC Grant 101100460 to S.K.), DFG (to S.K.), by the SFB-TRR 338/1 2021–452881907 (to S.K.), Fritz-Bender Foundation (to S.K.), Deutsche José Carreras Leukämie Stiftung (to S.K.), the Bayerische Forschungsstiftung (BAYCELLator to S.K.) and Hector Foundation (to S.K.), DFG (German Research Foundation) under Germany’s Excellence Strategy within the framework of the Munich Cluster for Systems Neurology (EXC 2145 SyNergy, ID 390857198, to E.B. and D.P.) and Alzheimer’s Association (to D.P.). M.T. is funded by the Volkswagen Foundation (project OntoTime). S.S. was supported by the Else Kröner-Fresenius Clinician Scientist Program Cancer Immunotherapy, the Munich Clinician Scientist Program and the DKTK School of Oncology. C.M. has received funding from the European Research Council under the European Union’s Horizon 2020 research and innovation program (grant agreement number 866411). Cytometry data were obtained in the Flow Cytometry Core Facility of the University Hospital, LMU Munich, using a BD LSRFortessa II or Beckman Coulter CytoFLEX. The in vivo imaging device was funded by the DFG (German Research Foundation; INST 409/231-1). We acknowledge Life Science Editors for their editing services. Figure illustrations were created with Biorender.com under a paid subscription.

Author information

Author notes

  1. These authors contributed equally: Adrian Gottschlich, Moritz Thomas, Ruth Grünmeier.

  2. These authors jointly supervised this work: Carsten Marr, Sebastian Kobold.

Authors and Affiliations

  1. Division of Clinical Pharmacology, University Hospital, LMU Munich, Member of the German Center for Lung Research (DZL), Munich, Germany

    Adrian Gottschlich, Ruth Grünmeier, Stefanie Lesch, Veronika Igl, Daria Briukhovetska, Mohamed-Reda Benmebarek, Dario Dhoqina, Florian Märkl, Öykü Umut, Christina Angeliki Tsiverioti, Emanuele Carlini, Sayantan Nandi, Thaddäus Strzalkowski, Theo Lorenzini, Sophia Stock, Philipp Jie Müller, Janina Dörr, Matthias Seifert, Bruno L. Cadilha, Ruben Brabenec, Natalie Röder, Felicitas Rataj, Manuel Nüesch, Stefan Endres & Sebastian Kobold

  2. Bavarian Cancer Research Center (BZKF), Munich, Germany

    Adrian Gottschlich

  3. Department of Medicine III, University Hospital, LMU Munich, Munich, Germany

    Adrian Gottschlich, Lisa Rohrbacher, Sophia Stock, Tobias Herold & Marion Subklewe

  4. Institute of AI for Health, Helmholtz Munich, Neuherberg, Germany

    Moritz Thomas, Ruben Brabenec & Carsten Marr

  5. School of Life Sciences Weihenstephan, Technical University of Munich, Freising, Germany

    Moritz Thomas

  6. Laboratory for Translational Cancer Immunology, Gene Center, LMU Munich, Munich, Germany

    Lisa Rohrbacher & Marion Subklewe

  7. Research Unit Apoptosis in Hematopoietic Stem Cells, Helmholtz Munich, German Research Center for Environmental Health (HMGU), Munich, Germany

    Binje Vick & Irmela Jeremias

  8. Department of Pediatrics, University Hospital, LMU Munich, Munich, Germany

    Binje Vick & Irmela Jeremias

  9. Department of Neurology, University Hospital, LMU Munich, Munich, Germany

    Sertac Dede, Katharina Müller & Tao Xu

  10. Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany

    Sophie Robinson & Dominik Paquet

  11. Munich Cluster for Systems Neurology (SyNergy), Munich, Germany

    Sophie Robinson, Eduardo Beltrán & Dominik Paquet

  12. Institute of Pathology, LMU Munich, Munich, Germany

    Andrea Sendelhofert & Heiko Schulz

  13. Institute of Clinical Neuroimmunology, University Hospital, LMU Munich, Munich, Germany

    Vladyslav Kavaka & Eduardo Beltrán

  14. Biomedical Center (BMC), Faculty of Medicine, LMU Munich, Martinsried, Germany

    Vladyslav Kavaka & Eduardo Beltrán

  15. German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany

    Sophia Stock, Tobias Herold, Irmela Jeremias, Louisa von Baumgarten, Stefan Endres, Marion Subklewe & Sebastian Kobold

  16. Department of Oncology, Hematology and Bone Marrow Transplantation with Section Pneumology, Hubertus Wald University Cancer Center, University Medical Center Hamburg-Eppendorf, Hamburg, Germany

    Franziska Modemann, Jasmin Wellbrock & Walter Fiedler

  17. Mildred Scheel Cancer Career Center, University Cancer Center Hamburg, University Medical Center Hamburg-Eppendorf Hamburg, Hamburg, Germany

    Franziska Modemann

  18. Division of Transfusion Medicine, Cell Therapeutics and Haemostaseology, University Hospital, LMU Munich, Munich, Germany

    Christian Kellner

  19. Department of Neurosurgery, LMU Munich, Munich, Germany

    Louisa von Baumgarten

  20. Einheit für Klinische Pharmakologie (EKLiP), Helmholtz Munich, Research Center for Environmental Health (HMGU), Neuherberg, Germany

    Stefan Endres & Sebastian Kobold

Authors
  1. Adrian Gottschlich
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  2. Moritz Thomas
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  3. Ruth Grünmeier
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  8. Mohamed-Reda Benmebarek
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  33. Manuel Nüesch
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  39. Tobias Herold
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  40. Dominik Paquet
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  42. Louisa von Baumgarten
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  43. Stefan Endres
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  44. Marion Subklewe
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  45. Carsten Marr
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  46. Sebastian Kobold
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Contributions

A.G., M.T., R.G., S.L., L.R., V.I., D.B., M.-R.B., S.D., K.M., T.X., D.D., F.M., S.R., A.S., H.S., Ö.U., V.K., C.A.T., E.C., S.N., T.S., T.L., S.S., P.J.M., J.D., M.S., B.L.C., R.B., N.R., F.R. and M.N. performed or assisted with the experiments. A.G., M.T., R.G., S.L., L.R., S.D., K.M., T.X., E.B. and T.H. analyzed the data and supported the project. S.R., B.V., J.W., F.M., W.F., C.K., D.P., I.J. and L.v.B. provided critical reagents, S.K., C.M. and S.E. supervised the project and acquired the funding. A.G., M.T., R.G., S.L., T.H., D.P., L.v.B, S.E., M.S., C.M. and S.K. designed the experiments. A.G., M.T., C.M. and S.K. wrote the paper. All authors critically read and approved the final paper.

Corresponding author

Correspondence to Sebastian Kobold.

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Competing interests

Parts of this work have been performed for the doctoral thesis of M.T., R.G., D.D. and S.D. at Technische Universität München and LMU München. A.G., M.T., R.G., S.L., S.E., C.M. and S.K. submitted patent applications related to this work filed by the LMU München, the University Hospital of the LMU Munich or the Helmholtz Centre Munich. S.K. has received honoraria from TCR2, Inc., Novartis, BMS and GSK. S.K. and S.E. are inventors of several patents in the field of immunooncology. S.K. and S.E. received license fees from TCR2, Inc., and Carina Biotech. A.G. received research support from Tabby Therapeutics for work unrelated to the paper. S.K. and S.E. received research support from TCR2, Inc., and Arcus Bioscience for work unrelated to the paper. F.M. received support for meeting attendance from Servier, AbbVie, Incyte, Gilead, Jazz Pharmaceuticals, Novartis, Teva, Pfizer and Amgen, received support for medical writing from Servier, received a research grant from Apis Technologies and Daiichi Sankyo and received speaker honoraria from Servier, Jazz Pharmaceuticals and AbbVie. W.F. received payment or honoraria for lectures, presentations, speakers bureaus, paper writing or educational events from Novartis, Abbvie, Pfizer and Amgen. W.F. received support for attending meetings and/or travel from Amgen, Gilead, Jazz Pharmaceuticals, Servier and Daiichi Sankyo. W.F. participates on a Data Safety Monitoring Board or Advisory Board at Amgen, ARIAD/Incyte, Pfizer, Novartis, Jazz Pharmaceuticals, Morphosys, Abbvie, Celgene, Stemline and Clinigen. The other authors declare no competing interests.

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Nature Biotechnology thanks Sarah Tasian, Li Tang and Challice Bonifant for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Summary of the cross-organ off-target transcriptomic atlas (COOTA).

(a) Top 100 overexpressed genes in AML HSPC (left) and healthy T cells (right) from differential expression analysis. Normalized expression values were logarithmized and scaled to unit variance. (b) Overview of 11 scRNA-seq datasets of various healthy tissues used to quantify off-target antigen expression. (c) UMAP plots of 11 scRNA-seq datasets with colors highlighting clustering into respective cell types. Cell annotations were provided by the authors of the respective studies. (d) Current CAR targets in AML were cross-referenced to filters used for the single cell-based target screening approach. OE HSC-/Prog-like: overexpressed on HSC-/Prog-like cells with log fold change > 2 and FDR-adjusted p ≤ 0.01, using a t-test with overestimated variance. Red cross: Antigen did not fulfill the respective threshold or criteria. Green check: Thresholds or criteria were passed.

Extended Data Fig. 2 CSF1R and CD86 are consistently expressed across multiple patients with differing molecular subtypes.

(a, c) Amount of malignant and normal cells per AML patient of van Galen et al. (a) or Petti et al. (c). (b, d) Percentage of malignant and normal cells expressing target genes CSF1R, CD86 and reference genes CD123, CD33 for each sequenced AML patient of van Galen et al. (b) or Petti et al. (d). (e) Data from van Galen et al.21 was used as a reference (top left) to map cells from Petti et al.39 (top right) using scANVI40. UMAP representation showing the mapped query and reference data together (bottom). (f) Computational CAR target antigen identification using the mapped dataset of Petti et al. by stepwise evaluation against a set of criteria for an ideal and effective CAR target antigen. The decreasing number of screened AML target genes are shown on the bottom. CSPA: Cell surface protein atlas; HPA: Human protein atlas. (g) Volcano plot showing CD86 and CSF1R target genes with their respective FDR-adjusted log10 p-value and log2 fold changes from differential expression analysis between malignant HSPC-like and healthy HSPC using a t-test with overestimated variance.

Extended Data Fig. 3 mCSF1R CART do not persist in immunocompetent mice.

(a) Construct design of mCSF1R or mEpCAM CART or mCherry T cells. (b) Representative histograms of mCSF1R or mEpCAM expression on J774A.1 cells. Staining was carried out twice. (c) Summary of treatment schedule for in vivo toxicity assessment of mCSF1R CART. (d) Mean weight curves of mice treated with 3 × 106 mCSF1R CART or mCherry T cells. n = 10 mice per group. Error bars indicate s.e.m. (e) Quantification of tissue-resident CD11b + cells (left) or mCherry+ T cells of parent population (right, parent population: CD3 and CD8 positive cells) in different organs by flow cytometry. Data are mean ± s.e.m. of n = 10 mice. (d, e) Statistical significance was calculated using two-way ANOVA with Šidák multiple comparison correction. (f) Scheme of treatment schedule for in vivo toxicity assessment of mCSF1R CART. WBI, whole body irradiation. Mice were treated with 3 × 106 mCSF1R CART or mCherry T cells per mouse. 6 × 106 mEpCAM CART were transferred as a positive control. (g) Serum levels of indicated markers one (d1) or seven (d7) days after ACT. Depicted is the fold change of serum levels of the indicated groups from the PBS-treated control group. CRP, C-reactive protein; AST, aspartate aminotransferase; ALT, alanine aminotransferase; GLDH, glutamate dehydrogenase; γ-GT, gamma-glutamyl-transferase; LDH, lactate dehydrogenase. n = 3 mice per group. Statistically significant increases in the serum of mEpCAM CART treated mice compared to mCSF1R CART or control-treated mice at day 7 were observed for GLDH (p < 0.0001). (h) Histopathological analysis of indicated organs after treatment with mEpCAM or mCSF1R CART or mCherry T cells. Representative images of n = 3 mice per group. Signs of organ damage are indicated in the picture: black arrowhead: thickening of alveolar epithel. (i) Representative maximum intensity projection of microglia (green) and macrophages (green) in CX3CR1-GFP mice on days 0 (baseline), 4, 7, 10, 14, 21 and 28 after intravenous injection of 107 mCSF1R CART (red). Depth from brain surface: 0–100 µm. Scale bars as depicted: 50 µm and 20 µm. mCSF1R CART: i.c. injection, n = 5 mice; i.v. injection, n = 3 mice; mCherry T cells: i.c./ i.v. injection = 2 mice.

Extended Data Fig. 4 Assessment of different hCSF1R CAR constructs in vitro.

(a) Construct design of all anti-human constructs used throughout the course of the study. (b) Representative flow cytometric images of construct expression on primary human T cells. (c) Activation of different hCSF1R CART after incubation with plate-bound hCSF1R protein quantified by flow cytometry. (d) T cells expressing different hCSF1R CAR constructs were cocultured with luc+ target antigen expressing AML tumor cell lines or antigen negative NALM-6 control cells for 48 hours at the indicated E:T ratios. Cell lysis was quantified by BLI. (e) Proliferation dye-labeled hCSF1R CART were cocultured with respective cell lines for 4 or 7 days at a E:T ratio of 0.5:1. Proliferation was subsequently assessed by trace dilution. One representative image of three different donors is shown. (f) Bead quantified T cell numbers. (g) Secretion of IFNγ by T cells transduced with different hCSF1R CAR constructs after co-culture with AML cell lines. (h) Secretion of IFNγ (left) or IL-2 (right) of hCSF1R, CD86 or control CART in co-culture with AML cell lines. (c, d, f - h) Data are mean ± s.e.m. of three independent donors. LTR, long terminal repeat; scFv, single chain fragment variable; TM, transmembrane, IC, intracellular, ED, extracellular domain, CTRL-transduced, control-transduced.

Extended Data Fig. 5 CSF1R is highly expressed on primary AML blasts.

(a) Representative histograms of CSF1R expression on AML cell lines after freeze and thaw cycles. (b, c) Schematic of culture methods used to cultivate primary AML samples throughout the course of the study. (d) Expression of CSF1R on primary AML samples after 24 to 48 hours of culture in cytokine rich medium. Left: Percentage positive cells gated to isotype. Each dot represents different primary AML samples. Right: Representative flow cytometric images from three different AML samples. Data are mean ± s.e.m. from six different donors. (e) Gating strategy to identify CD34+ CD38 ± malignant HSPC. (f, g) Expression of target antigens (CSF1R, f; CD86, g) on malignant HPC (top) and HSC (bottom). (h) Expression of CSF1R on PDX-388 sample at indicated time points after thawing. (i) IHC staining of human CSF1R in the bone marrow of control-treated PDX-388-bearing mice. Shown are two representative pictures (right, left) in two different magnifications (top 10x, bottom 20x). (j) CD33 CART used for i.v. injection into PDX-388-bearing mice (Fig. 5k–m) were cocultured ex vivo with luciferase+ Mv4-11 tumor cells for 48 hours at indicated E:T ratios. Specific lysis was quantified by BLI. Shown is mean ± s.e.m. of three biological replicates. Experiment was carried out twice. (k) Representative flow cytometric image of percentage of CD3+ T cells (left) and percentage of CAR (c-myc)+ T cells (right) in the blood of PDX-388-bearing mice. (l, m) Ex vivo CD33 expression on PDX-388 AML blasts in the bone marrow after treatment with CD33 CART or CTRL-transduced T cells (CD19 CART) measured by flow cytometry. Depicted are representative histograms (l) or the change of CD33-PE-Cy5 MFI in CD33 CART treated mice compared to CTRL-transduced treated mice (m). (m) Data are mean ± s.e.m. from n = 3 mice injected with CD33 CART compared to CTRL-transduced mouse. (k–m) n = 3 mice injected with CD33 CART), n = 1 mouse injected with CTRL-transuced T cells.

Extended Data Fig. 6 hCSF1R CAR T cells are effective in vivo.

(a) Treatment scheme used for PDX-372 model. (b–d) BLI images (b), BLI quantification of tumor-burden (c) and survival curves (d) of PDX-372 tumor-bearing mice injected with 2 × 106 hCSF1R, CD33 CART or control-transduced T cells (n = 5 mice per group). (b) White cross, censored mice; red cross, mice succumbed to disease. (e) IHC staining of human CSF1R in the bone marrow of control-treated PDX-372-bearing mice. Left: IHC for human CSF1R. Right: Isotype (top) and detection system control (bottom) for CSF1R IHC staining. (f) Schematic of treatment scheme used for OCI-AML3 cell line xenograft model. (g, h) BLI images (g) and survival curves (h) of OCI-AML3 tumor-bearing mice injected with 6 × 106 hCSF1R CART or control-transduced T cells (n = 3–4 mice per group). (g) Red cross, mice succumbed to disease. (a–h) Statistical significance was calculated using two-way ANOVA with Šidák multiple comparison correction. (i) log2 expression of CSF1R and CD86 target antigens or CD123 and CD33 controls in bulk RNA-sequencing dataset of the Leukemia MILE study (n = 615 different patients). HBM, healthy bone marrow. Data was obtained from bloodspot.eu. Dashed line represents the median, dotted line the interquartile ranges. Statistical significance was calculated using ordinary one-way ANOVA with Šidák multiple comparison correction. (j) Simple linear regression analysis of in vitro lysis of CAR T cells and target antigen density of the indicated AML cell line measured by flow cytometry. r = spearman correlation coefficient, p = p-value. Three independent antigen density measurements were used to perform regression analysis. For Kaplan-Meier-Curves, statistical significance was calculated with log-rank test.

Extended Data Table 1 Summary of patient characteristics of all primary human patient samples used during the study
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Gottschlich, A., Thomas, M., Grünmeier, R. et al. Single-cell transcriptomic atlas-guided development of CAR-T cells for the treatment of acute myeloid leukemia. Nat Biotechnol 41, 1618–1632 (2023). https://doi.org/10.1038/s41587-023-01684-0

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