The immunostimulatory intracellular domains (ICDs) of chimaeric antigen receptors (CARs) are essential for converting antigen recognition into antitumoural function. Although there are many possible combinations of ICDs, almost all current CARs rely on combinations of CD3𝛇, CD28 and 4-1BB. Here we show that a barcoded library of 700,000 unique CD19-specific CARs with diverse ICDs cloned into lentiviral vectors and transduced into Jurkat T cells can be screened at high throughput via cell sorting and next-generation sequencing to optimize CAR signalling for antitumoural functions. By using this screening approach, we identified CARs with new ICD combinations that, compared with clinically available CARs, endowed human primary T cells with comparable tumour control in mice and with improved proliferation, persistence, exhaustion and cytotoxicity after tumour rechallenge in vitro. The screening strategy can be adapted to other disease models, cell types and selection conditions, and could be used to improve adoptive cell therapies and to expand their utility to new disease indications.
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speedingCARs: accelerating the engineering of CAR T cells by signaling domain shuffling and single-cell sequencing
Nature Communications Open Access 02 November 2022
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The NGS selection datasets have been deposited in the Sequence Read Archive and are available under the accession number PRJNA744269. The scRNA-seq data have been deposited in the Gene Expression Omnibus under accession number GSE179767. All data generated or analysed during the study (including the DomainSeq-processed CARPOOL selection data) are included in the paper or its supplementary information.
The code used to analyse the domain composition of selected CARs can be accessed in the DomainSeq repository at https://github.com/birnbaumlab/Gordon-et-al-2022.
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We thank the Koch Institute’s Robert A. Swanson (1969) Biotechnology Center for their technical support, especially the Flow Cytometry Facility, Preclinical Modeling, Imaging and Testing Core, MIT BioMicro Center and High Throughput Sciences Core. We thank G. Paradis, P. Chamberlain, H. Holcombe, V. Spanoudaki and S. Levine for many helpful discussions and suggestions. We also thank Y. Chen for providing the sequence for the 19BB𝛇 CAR. M.E.B. was supported by a Packard Fellowship, a Pew-Stewart Scholarship and a grant from the Deshpande Center. D.J.I. was supported by the Mark Foundation, the National Institutes of Health (R01-CA247632) and the Bridge Project, a partnership between the Koch Institute for Integrative Cancer Research at MIT and the Dana-Farber/Harvard Cancer Center. D.J.I. is an investigator of the Howard Hughes Medical Institute. D.A.L. was supported by US Army Research Office Cooperative Agreement W911NF-19-2-0026 Institute for Collaborative Biotechnologies. This work was supported in part by the Koch Institute Frontier Research Program (to M.E.B. and M.T.H.), and the Koch Institute Support (core) Grant P30-CA14051 from the National Cancer Institute. This work was additionally supported by a fellowship from Human Frontier Science Program to T.K., National Science Foundation Graduate Research Fellowships to K.S.G., C.R.P. and P.V.H., a Paul and Daisy Soros Fellowship to A.R., and support from the National Institute of General Medical Sciences (T32-GM007753) to A.Q.Z. and C.K. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of General Medical Sciences or the National Institutes of Health. This research is supported in part by the National Research Foundation, Prime Minister’s Office, Singapore under its Campus for Research Excellence and Technological Enterprise (CREATE) programme, through Singapore MIT Alliance for Research and Technology (SMART): Critical Analytics for Manufacturing Personalised-Medicine (CAMP) Inter-Disciplinary Research Group.
The library approach described in this paper is the subject of a US patent application (PCT/US2020/017794) with T.K. and M.E.B. as inventors. M.E.B. is a founder, consultant and equity holder of Kelonia Therapeutics and Abata Therapeutics. T.K. is presently an employee of Gingko Bioworks. The other authors declare no competing interests.
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Related to Fig. 2b. Heatmap representing log2(fold-change) of individual ICDs, oriented by ICD position within the CAR relative to the plasma membrane. Fold-changes were normalized to frequencies in the EGFP+ sorted population prior to selection.
a, Design of CD19 targeted CAR candidates. b, CAR surface expression (n = 1), (c) internalization (n = 1), and (d) CD69 upregulation upon antigen stimulation with recombinant human CD19 (n = 6 technical replicates representative of 2 biological replicates). e, Basal CD69 (activation) and (f) PD-1 expression of unstimulated CAR-T cells (n = 7 technical replicates representative of 2 biological replicates). P values shown in panel (e) are 0.002 for Var1 vs. BB𝛇 and 0.0149 for Var2 vs. BB𝛇. P values shown in panel (f) are 0.0117 for Var1 vs. BB𝛇, 0.0110 for Var2 vs. BB𝛇, and 0.0192 for Var3 vs. BB𝛇, as determined by two-tailed unpaired student’s t tests (df = 12). Data shown are individual values in panel (c), while panel (d) shows means ± s.e.m. Panels (e,f) show individual values along with means ± s.e.m.
Related to Fig. 4d, e. a, FACS plots displaying changes in CAR-T cell memory differentiation following repeated tumour challenge (days 4 and 18 shown). b, LAG-3 expression following repeated tumour challenge on day 22 (n = 3 technical replicates representative of 2 biological replicates). P values are 0.0465 for CD4+ Var3 vs. BB𝛇, and 0.0358 for CD8+ Var1 vs. BB𝛇, and 0.0112 for CD8+ Var3 vs. BB𝛇 (df = 4 for all). P values in panel (b) were determined using an unpaired student’s t test. Data shown are means ± s.e.m.
Differential of CD4 (left) and CD8A (right) expression as determined by single cell sequencing as shown in Fig. 5. Data points shown represent individual cells.
Volcano plot showing differentially expressed genes between Var1 (n = 863 cells) and 19BB𝛇-expressing (n = 637 cells) CAR-T cells 48 hours after a third NALM6 rechallenge. P values for each gene were determined using a two-sided Wilcoxon Rank-Sum test. Genes with both a Bonferroni-corrected P value less than 0.05 and an average log2FC of > 1 are highlighted.
a, Experimental design. NSG mice were infused intravenously with 5 × 105 FLuc+ CD19+ NALM6 cells, then treated i.v. with 1 × 106 of a 1:1 mixture of human CD8+ and CD4+ CAR-T cells or untransduced control T cells (n = 5 mice for all groups). b, Kaplan-Meier curve for overall survival. Tumour burden was assessed by measuring luminescent activity. c, Quantification of total photon counts are shown. d, Weight loss following ACT was monitored routinely. Data shown in panels (c,d) are individual values.
a, Experimental design. NSG mice were infused intravenously with 5 × 105 FLuc+ CD19+ NALM6 cells, then treated i.v. with 1 × 106 of a 1:1 mixture of human CD8+ and CD4+ CAR-T cells or untransduced control T cells (n = 5 mice for all groups). Mice were then rechallenged with 5 × 105 FLuc+ CD19+ NALM6 cells on days 44 and 58 post ACT (indicated with arrows). b, Kaplan-Meier curve for overall survival. Tumour burden was assessed by measuring luminescent activity. c, Quantification of total photon counts is shown. d, Weight loss following ACT was monitored routinely. Data shown in panels (c,d) are individual values. Arrows in panels (b–d) indicate dates of NALM6 rechallenge. e, CD19+ NALM6 cells and (f) EGFP+ CAR-T cells were harvested from the peripheral blood (PB), spleen (SP), and bone marrow (BM) of a separate cohort of mice that received the same treatment regimen at day 14 post ACT and quantified via FACS analysis (n = 3). Data shown are individuals with means ± s.e.m.
Amino acid compositions of intracellular signalling domains incorporated into the CAR library.
Barcode frequencies and metadata from NGS of selected CAR-library-expressing Jurkats.
List of significantly differentially overexpressed genes in each cluster following scRNA-seq.
Differentially expressed genes between all Var1-expressing cells and all 19BBz-expressing cells.
List of T-cell-specific curated gene sets used for scGSVA analysis of transcriptional clusters.
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Gordon, K.S., Kyung, T., Perez, C.R. et al. Screening for CD19-specific chimaeric antigen receptors with enhanced signalling via a barcoded library of intracellular domains. Nat. Biomed. Eng 6, 855–866 (2022). https://doi.org/10.1038/s41551-022-00896-0