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CTLA-4 tail fusion enhances CAR-T antitumor immunity

Nature Immunology volume 24, pages 1499–1510 (2023)Cite this article

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Abstract

Chimeric antigen receptor (CAR)-T cells are powerful therapeutics; however, their efficacy is often hindered by critical hurdles. Here utilizing the endocytic feature of the cytotoxic T-lymphocyte-associated antigen-4 (CTLA-4) cytoplasmic tail, we reprogram CAR function and substantially enhance CAR-T efficacy in vivo. CAR-T cells with monomeric, duplex or triplex CTLA-4 cytoplasmic tails (CCTs) fused to the C terminus of CAR exhibit a progressive increase in cytotoxicity under repeated stimulation, accompanied by reduced activation and production of proinflammatory cytokines. Further characterization reveals that CARs with increasing CCT fusion show a progressively lower surface expression, regulated by their constant endocytosis, recycling and degradation under steady state. The molecular dynamics of reengineered CAR with CCT fusion results in reduced CAR-mediated trogocytosis, loss of tumor antigen and improved CAR-T survival. CARs with either monomeric (CAR-1CCT) or duplex CCTs (CAR-2CCT) have superior antitumor efficacy in a relapsed leukemia model. Single-cell RNA sequencing and flow cytometry analysis reveal that CAR-2CCT cells retain a stronger central memory phenotype and exhibit increased persistence. These findings illuminate a unique strategy for engineering therapeutic T cells and improving CAR-T function through synthetic CCT fusion, which is orthogonal to other cell engineering techniques.

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Fig. 1: Engineering CAR with CCT fusion increased persistent CAR-T cell function under repeated tumor stimulation.
Fig. 2: CCT fusion enables titration of CAR expression through receptor endocytosis, recycling and degradation at steady state.
Fig. 3: CCT fusion effectively decreases CAR-mediated trogocytosis and accompanying fratricide.
Fig. 4: CAR-T cells with CCT fusion show increased survival and proliferation.
Fig. 5: CAR-T with 1CCT or 2CCT fusion demonstrated improved antitumor efficacy in a relapsed leukemia mouse model with increased persistence and TCM differentiation.

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Data availability

All data generated or analyzed during this study are provided. Source data and statistics are provided in an Excel file in Supplementary Table 3. Processed data for genomic sequencing and gene expression are provided as processed quantifications in Supplementary Tables 1 and 2. Genomic sequencing raw data are deposited at the Gene Expression Omnibus under accession no. GSE234307. Source data are provided with this paper.

Code availability

The code used for data analysis and the generation of figures related to this study can be accessed from GitHub at https://github.com/Ariel-Xiaoyu/CAR-CCT.

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Acknowledgements

We thank Drs Krause, Isufi and Bersenev for discussions on cell therapy. We thank all members of the Chen laboratory, as well as various colleagues and core facility staff at Yale for assistance and/or discussions. We thank staff at the Yale West Campus Imaging Core for their support and assistance in this work. We thank R. Glen for helpful proofreading of the manuscript. S.C. is supported by Yale SBI/Genetics Startup Fund, National Institutes of Health (NIH)/National Cancer Institute/National Institute on Drug Abuse (DP2CA238295, R01CA231112, U54CA209992-8697, R33CA225498 and RF1DA048811), U.S. Department of Defense (DOD) (W81XWH-17-1-0235, W81XWH-20-1-0072, W81XWH-21-1-0514), Cancer Research Institute (CLIP), the American Association for Cancer Research (499395, 17-20-01-CHEN), Alliance for Cancer Gene Therapy, Sontag Foundation (DSA), Pershing Square Sohn Cancer Research Alliance, Dexter Lu, Ludwig Family Foundation, Blavatnik Family Foundation and Chenevert Family Foundation. P.A.R. is supported by an NIH training grant (T32GM007499) and a Lo Fellowship. M.B.D. is supported by an NIH training grant (T32GM007205). R.D.C. is supported by an NIH MSTP training grant (T32GM007205) and National Research Service Award fellowship (F30CA250249).

Author information

Author notes

  1. These authors contributed equally: Xiaoyu Zhou, Hanbing Cao.

Authors and Affiliations

  1. Department of Genetics, Yale University School of Medicine, New Haven, CT, USA

    Xiaoyu Zhou, Hanbing Cao, Shao-Yu Fang, Ryan D. Chow, Kaiyuan Tang, Medha Majety, Meizhu Bai, Matthew B. Dong, Paul A. Renauer, Kazushi Suzuki & Sidi Chen

  2. System Biology Institute, Yale University, West Haven, CT, USA

    Xiaoyu Zhou, Hanbing Cao, Shao-Yu Fang, Ryan D. Chow, Kaiyuan Tang, Medha Majety, Meizhu Bai, Matthew B. Dong, Paul A. Renauer, Xingbo Shang, Kazushi Suzuki, Andre Levchenko & Sidi Chen

  3. Center for Cancer Systems Biology, Yale University, West Haven, CT, USA

    Xiaoyu Zhou, Hanbing Cao, Shao-Yu Fang, Ryan D. Chow, Kaiyuan Tang, Medha Majety, Meizhu Bai, Matthew B. Dong, Paul A. Renauer, Xingbo Shang, Kazushi Suzuki, Andre Levchenko & Sidi Chen

  4. Molecular Cell Biology, Genetics, and Development Program, Yale University, New Haven, CT, USA

    Ryan D. Chow, Kaiyuan Tang, Paul A. Renauer & Sidi Chen

  5. MD-PhD Program, Yale University, New Haven, CT, USA

    Ryan D. Chow, Matthew B. Dong & Sidi Chen

  6. Department of Immunobiology, Yale University, New Haven, CT, USA

    Ryan D. Chow & Matthew B. Dong

  7. Yale College, New Haven, CT, USA

    Medha Majety

  8. Immunobiology Program, Yale University, New Haven, CT, USA

    Matthew B. Dong & Sidi Chen

  9. Department of Biomedical Engineering, Yale University, New Haven, CT, USA

    Xingbo Shang & Andre Levchenko

  10. Comprehensive Cancer Center, Yale University School of Medicine, New Haven, CT, USA

    Sidi Chen

  11. Stem Cell Center, Yale University School of Medicine, New Haven, CT, USA

    Sidi Chen

  12. Center for Biomedical Data Science, Yale University School of Medicine, New Haven, CT, USA

    Sidi Chen

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Contributions

X.Z. designed experiments with discussion with H.C., M.B.D. and R.D.C. X.Z. and H.C. performed most of the experiments. S.Y.F., M.M., M.B. and M.B.D. assisted with the experiments. X.Z. analyzed the high-throughput data. R.D.C., P.A.R., K.T. and K.S. assisted with data analysis. A.L. and X.S. assisted with imaging analysis. X.Z. conceived the study with high-level input from S.C. S.C. secured funding and supervised the work. X.Z., H.C., R.D.C. and S.C. prepared the paper with input from all authors.

Corresponding author

Correspondence to Sidi Chen.

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Competing interests

A patent was filed by Yale University regarding the data in this study (inventors S.C. and X.Z.), which was licensed to Cellinfinity Bio, a Yale biotech startup founded by S.C. S.C. is also a (co)founder of EvolveImmune, NumericGlobal, Chen Tech and Chen Consulting, all unrelated to this study. All other authors have no competing interests.

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Nature Immunology thanks the anonymous reviewers for their contribution to the peer review of this work. Primary Handling Editor: Stephanie Houston, in collaboration with the Nature Immunology team. Peer reviewer reports are available.

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Extended data

Extended Data Fig. 1 Characterization of CAR-T cells with CCT fusion after one round stimulation with NALM6GL cells.

a. Schematics of the workflow used to generate CAR-T cells for effector function assessment in vitro. (i) Generation of CAR-T cells. Human CD3 T cells were infected by lentiviruses carrying CAR targeting human CD22 (m971-CD28-41BB-CD3zeta). These CARs were engineered with either monomeric (CAR-1CCT), duplex (CAR-2CCT) or triplex CCTs (CAR-3CCT) fused to the C terminus of human CD22-CAR (CAR), followed by a fluorescent reporter mScarlet, separated by T2A sequences. Flag sequences were tagged at N-terminal of the CAR for surface expression detection. (ii) Round 1 co-culture. Those four groups of CAR-T cells generated in step (i) were co-culture with NALM6GL cells at variable E/T ratios for 24 hours. (iii) Round 2 co-culture. An additional round of NALM6GL cells were supplemented into the initial co-culture for 24 hours. (iv). FACS analysis. Cells from both round1 and 2 cocultures were quantified by fluorescence-activated single cell sorting (FACS). b. Representative flow cytometry results showing CD4 and CD8 staining of CAR-T cells 7 days after transduced with CAR-T constructs. c. Quantification of (b). showing the CD4 and CD8 percentage of CAR-T cells, n = 3. d. Representative flow cytometry results showing the gating strategy used in Fig. 1a–d. e. Quantification of NALM6 killing by CAR-T cells. Purified CAR-T cells were co-cultured with one round of NALM6GL cells at E/T = 1/2 for 24 hours, n = 6. f. Quantification of the increases in CAR-T cell counts after one round of NALM6GL stimulation, n = 3. g-p. Representative flow cytometry analysis and quantification of LAG3 (g,h), PD-1(i,j), TIGIT(k,l), cycling CTLA-4(m,n), recycling CTLA-4 (o) and TIM3 (p) on CAR-T cells after stimulated with NALM6GL cells at E/T = 1/2 for 24 hours. For all bar plots, data are shown as mean ± s.e.m. One-way ANOVA with Dunnett’s multiple-comparisons test is used to assess significance for figure (e), (f), (h), (j), (l) and (n). Two-way ANOVA with Tukey’s multiple-comparisons test is used to assess significance for (c) and (o). ns = p > 0.05. Exact p values are labeled. All numbers defined by ‘n’ indicate the number of biologically independent samples. Data are representative of three independent experiments performed with biological repeats.

Source data

Extended Data Fig. 2 CCT fusion enhanced CAR-T killing under repeated stimulation.

a. Representative flow cytometry analysis for Fig. 1a–d showing CAR-T killing capability under two rounds of NALM6GL stimulation. b. Quantification of input CAR-T cell counts without NALM6GL stimulation showing relatively equal amount of input CAR-T cells, n = 2, ns = p > 0.05. c. Representative flow cytometry results showing the differentiation stage, indicating by the expression of CD45RO and CD62L, of CAR-T cells after two rounds of co-culture with NALM6GL cells. d. Quantification of c. showing the CD45RO+ CD62L+ CAR-T cells in percentage, n = 6. e. Representative flow cytometry results showing the expression level of LAG3 on CAR-T cells after being stimulated with two rounds of NALM6GL. f. Quantification of (e) showing the LAG3+ CAR-T cells in percentage, n = 6. g. Representative flow cytometry analysis on the CD22 expression level of CD22high and CD22low NALM6 cells. h. Quantification of (g) showing CD22 MFI of CD22high and CD22low NALM6 cells, n = 3. i. Quantification of live NALM6 cell count after two rounds of coculturing with CAR-T cells at E/T = 1/2 by flow cytometry, n = 4. For all bar plot figures, data are shown as mean ± s.e.m. One-way ANOVA with Dunnett’s multiple-comparisons test is used to assess significance. Exact p values are labeled. All numbers defined by ‘n’ indicate the number of biologically independent samples. Data are representative of three independent experiments performed with biological repeats.

Source data

Extended Data Fig. 3 CCT fusion enables enhanced killing with low production of proinflammatory cytokines.

a. Schematics of lentiviral constructs to make CAR-T cells targeting human CD19 (FMC63-CD28-41BB-CD3zeta). CD19-CAR (19CAR) constructs were made by replacing the m971 scFv with the FMC63 scFv from Extended Data Fig. 1a. b. Representative flow cytometry analysis of 19CAR-T killing capability in vitro. c. Quantification of (b) showing CD19-CAR percentage (left panel), and counts (right panel), n = 3. d. Quantification of (b) showing NALM6GL percentage (left panel), and counts (right panel), n = 3. e. Quantification of 13 granule molecules and cytokines in CAR-T and NALM6GL cocultures. CAR-T cells were co-cultured with one round of NALM6GL cells at E/T = ½ for 24 hours. Co-culture supernatant was then collected and measured using LEGENDplex™ Human CD8/NK Panel, n = 3. f. Schematics of lentiviral constructs to make CD22 targeting CAR-T cells. In addition to the four constructs shown in Extended Data Fig. 1a, mCMV-CAR construct was generated by replacing the EFS promoter in the CAR construct with a minimal CMV promoter (mCMV). g. Representative flow cytometry analysis of CAR-T cells, pre-gated on mScarlet+ populations, showing surface expression level of CAR, indicated by Flag staining. h. Quantification of (g) showing surface flag expression in MFI, n = 3. For all bar plot figures, data are shown as mean ± s.e.m. One-way ANOVA with Dunnett’s multiple-comparisons test is used to assess significance. Exact p values are labeled. All numbers defined by ‘n’ indicate the number of biologically independent samples. Data are representative of two independent experiments performed with biological repeats.

Source data

Extended Data Fig. 4 Schematics of workflow of experiments for Fig. 2.

a. Schematics of the workflow used in Fig. 2c, d for detecting CAR endocytosis. Surface and endocytic CAR were first stained with primary anti-Flag-BV421 at 37 °C for 30 minutes, followed by a secondary anti-Rat-IgG2a-AF647 stained at 4 °C for 15 minutes. The surface, endocytic CAR and CAR- populations were differentiated based on their staining patterns of the primary and secondary antibodies. b. Schematics of the workflow used in Fig. 2e to assess the endocytosis rate of CAR. Surface CAR was initially labeled with primary anti-Flag at 4 °C, followed by incubation of CAR-T cells at 37 °C for varying durations to allow endocytosis. The remaining surface-bound CAR molecules were then stained with a secondary anti-Rat-IgG2a-AF647 antibody at 4 °C. Endocytosis was quantified by the decrease in the percentage of cells stained positive for the secondary antibody. c. Schematics of the workflow used in Fig. 2f for detecting recycling CAR. Surface and endocytic CAR were first stained with primary anti-Flag at 37 °C for 30 minutes, followed by a secondary anti-Rat-IgG2a-AF647, either stained at 4 °C for 15 minutes (baseline) or at 37 °C for 30 minutes or 60 minutes. Recycling was quantified by the increase in the percentage of cells stained positive for the secondary antibody.

Source data

Extended Data Fig. 5 CCT fusion decreased CAR-mediated trogocytosis.

a. Representative flow cytometry analysis of CAR-mediated trogocytosis. CAR-T cells were pretreated with either DMSO (control) or 1 μM Latrunculin A at 37 °C for 15 min before co-cultured with NALM6-CD22-BFP cells for 2 hours. CD22-GFP transfer onto CAR-T cells were quantified by flow cytometry. b. Quantification of (a) showing the inhibition of CD22-GFP transfer by Latrunculin A, n = 3. c. Representative flow cytometry analysis of CAR-mediated trogocytosis by CAR-J cells. CAR-J cells co-cultured with NALM6GL-CD22-BFP cells for indicated time. CD22-BFP transfer onto CAR-T cells were quantified by flow cytometry. d. Quantification of (c) showing the transfer of CD22-BFP onto CAR-J cells, n = 3. e. Schematics of the workflow used in Fig. 3h, i for detecting the degranulation of CAR-T cells. CAR-Jurkat (CAR-J) cells were co-cultured with NALM6-CD22-GFP at an E/T ratio of 1:1 for 4 hours. Both Trog+ CAR-J and Trog- CAR-J cells were sorted out based on their expression of CD22-GFP. Those cells were then co-cultured with eFluor450 labeled CAR-T cells for 2 hours for determine the expression of CD107a. f. Schematics of the CAR-T survival assay used in Fig. 4a–c. Control CAR-T cells labeled with 10 µM eFluor450 (eFluor450high), were mixed 1:1 with CAR, CAR-1CCT, CAR-2CCT or CAR-3CCT cells labeled with 1 µM eFluor450 (eFluor450low). These mixed CAR-T cells were then co-cultured with or without NALM6GL. Relative percentages of eFluor450 high and low populations gated from CAR+ (mScarlet+) cells were used for quantification of relative survival of CAR-T cells. g. Schematics of the workflow used in Fig. 4f, g. CAR-T cells were co-cultured with NALM6-CD22-GFP cells at E/T = 1/2 for 4 hours. Both Trog+ CAR-T and Trog- CAR-T cells were sorted out based on their expression of CD22-GFP, and co-cultured separately overnight before staining for Annexin V. For all bar plot figures, data are shown as mean ± s.e.m. One-way ANOVA with Dunnett’s multiple-comparisons test is used to assess significance for (d). Two-way ANOVA with Tukey’s multiple-comparisons test is used to assess significance for (b). Exact p values are labeled. All numbers defined by ‘n’ indicate the number of biologically independent samples. Data are representative of two independent experiments performed with biological repeats.

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Extended Data Fig. 6 CCT fusion enhanced CAR-T survival.

a. Representative flow cytometry results showing the expression of Fas and FasL on CAR-T cells following incubations with NALM6GL cells for 0, 4 or 24 hours. b. Quantification of (a) showing the expression of Fas on CAR-T cells, n = 4. c. Quantification of (a) showing the expression of FasL on CAR-T cells, n = 4. d. Schematics of in vivo experimental workflow used in Fig. 4h–l. NSG mice (female, 6-10 weeks old) were first inoculated with 1 million NALM6GL cells intravenously (i.v.) on day 0. CAR-T cells stained with 1 µM eFluor450 were mixed with CAR-T cells stained with 10 µM eFluor450 at 1:1 ratio. Two million of these labeled cell mixtures were transferred to the leukemia NSG models on day 4. One day post CAR-T transfer, bone marrow samples were collected for flow cytometry analysis to determine the relative percentage of eFluor450low and eFluor450high populations. e. Representative flow cytometry results showing the gating strategy used in Fig. 4h–l for quantifying the relative CAR-T survival in vivo. For all bar plot figures, data are shown as mean ± s.e.m. Two-way ANOVA with Tukey’s multiple-comparisons test is used to assess significance for (b,c). Exact p values are labeled. All numbers defined by ‘n’ indicate the number of biologically independent samples. Data are representative of two independent experiments performed with biological repeats.

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Extended Data Fig. 7 Characterization of CAR-CCT cells by bulk RNA sequencing.

a. Representative flow cytometry results showing the sorting purity of CAR-T cells before subjecting to RNA-seq. CAR-T cells after being stimulated with 2 rounds of NALM6GL cells were sorted as mScarlet+ GFP− cells. b. PCA analysis of all four groups of CAR-T cells at baseline without stimulation. c. PCA analysis of all four groups of CAR-T cells with 2 rounds of NALM6GL stimulation. d. Heatmap of differentially expressed genes in all four groups of CAR-T cells at baseline. All CAR-T cells were purified by flow cytometer at day 6 after lentivirus infection and expanded for 7 days before mRNA extraction for bulk RNA sequencing. Cutoff for determining differentially expressed genes is set to be p (adj) < 0.01 and |log2Fc|> 1. e-g. Quantification of LAG3(e), HHLA2(f), CD101(g) expression level on CAR-T cells at baseline using flow cytometry, n = 3. h. Volcano plot of bulk RNA sequencing showing differentially expressed genes in CAR-1CCT vs. CAR (left panel), CAR-2CCT vs. CAR (middle panel) and CAR-3CCT vs. CAR (right panel). Purified CAR-T cells were co-cultured with NALM6GL cells at E/T = 1/2. NALM6GL cells were repeatedly supplemented at 24 hrs after initial co-culture. CAR-T cells (mScarlet+) were then sorted at 72 hrs after initial co-culture for bulk RNA sequencing. Cutoff for determining differentially expressed genes is set to be p (adj) < 0.01 and |log2Fc|> 1. i. Pathway analysis by over representation analysis (ORA) showing top 10 pathways of upregulated DEGs in CAR-2CCT vs. CAR (left panel) and in CAR-3CCT vs. CAR (right panel). j. Venn diagram showing overlaps of upregulated genes as in (a). For all bar plots, data are shown as mean ± s.e.m. One-way ANOVA with Dunnett’s multiple-comparisons test is used to assess significance. Exact p values are labeled. All numbers defined by ‘n’ indicate the number of biologically independent samples. Data are representative of two independent experiments performed with biological repeats.

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Extended Data Fig. 8 Characterization of CAR-CCT cells in vivo via scRNA-seq.

a. Gating strategy used for analysis shown in Fig. 5e–k. b. Heatmap showing expression profiles across 12 CAR-T cell subsets. Scaled gene expression is presented by showing 100 representative cells of each subset. c. UMAP visualization of 39,151 cells CAR-T cells via scRNA-seq profiling, split by tissue type. d. Pie chart of cell proportions between four different CAR-T groups isolated from bone marrow. e. Pie chart of cell proportions between four different CAR-T groups isolated from spleen. f. Volcano plot showing differentially expressed genes in CAR-2CCT vs. CAR-3CCT in the CD4 Teff cluster from bone marrow. Data are representative of two independent experiments performed with biological repeats.

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Extended Data Fig. 9 Proposed model of titrating optimal CAR-T function with CCT fusion.

CAR fused with duplex CCTs (CAR-2CCT) demonstrated decreased surface expression, which is tightly regulated by its endocytosis, recycling, degradation in both lysosome and proteasome. Compared with the control CAR, CAR-2CCT has significant decreases in surface CAR expression, T cell activation, CAR-mediated trogocytosis, and causes less tumor antigen loss on NALM6 cells. This engineering approach effectively increases the persistence and proportion of Tcm cells in CAR-2CCT cells, leading to a remarkable improvement in their anti-tumor in vivo.

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Supplementary information

Reporting Summary

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Supplementary Table 1

Processed NGS data and analysis results for bulk RNA sequencing.

Supplementary Table 2

Compiled single-cell gene differential expression data.

Supplementary Video 1

Timelapse live cell imaging of trogocytosis and fratricide. Representative video showing trogocytosis and fratricide of CAR-T cells after introduction with NALM6GL-CD22-BFP cancer cells (corresponding to Fig. 3a). The white arrowhead labels a CAR-T cell that acquired CD22-BFP after an active engagement with a cancer cell, which subsequently rendered it susceptible to CAR-T fratricide afterwards, as indicated by the influx of SYTOX deep red dye. This white arrow-labeled cell then contacted another CAR-T cell, interacting at a region with enhanced CD22-BFP signal. Shortly after this active interaction, the white arrowhead-labeled cell was stained by the SYTOX deep red dye, indicating cell death. The time stamps on the top right of each image are represented as hour:minute. Scale bar, 10 µm.

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Zhou, X., Cao, H., Fang, SY. et al. CTLA-4 tail fusion enhances CAR-T antitumor immunity. Nat Immunol 24, 1499–1510 (2023). https://doi.org/10.1038/s41590-023-01571-5

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