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In vivo CRISPR screening in CD8 T cells with AAV–Sleeping Beauty hybrid vectors identifies membrane targets for improving immunotherapy for glioblastoma

Nature Biotechnology volume 37, pages 1302–1313 (2019)Cite this article

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Abstract

Targeting membrane proteins could improve the efficacy of T cell–based immunotherapies. To facilitate the identification of T cell targets, we developed a hybrid genetic screening system where the Sleeping Beauty (SB) transposon and single guide RNA cassette are nested in an adeno-associated virus (AAV). SB-mediated genomic integration of the single guide RNA cassette enables efficient gene editing in primary murine T cells as well as a screen readout. We performed in vivo AAV–SB-CRISPR screens for membrane protein targets in CD8+ T cells in mouse models of glioblastoma (GBM). We validated screen hits by demonstrating that adoptive transfer of CD8+ T cells with Pdia3, Mgat5, Emp1 or Lag3 gene editing enhances the survival of GBM-bearing mice in both syngeneic and T-cell receptor transgenic models. Transcriptome profiling, single cell sequencing, cytokine assays and T cell signaling analysis showed that Pdia3 editing in T cells enhances effector functions. Engineered PDIA3 mutant EGFRvIII chimeric antigen T cells are more potent in antigen-specific killing of human GBM cells.

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Fig. 1: In vivo AAV–SB-CRISPR CD8+ T-cell screen of membrane proteome knockouts in GBM.
Fig. 2: In vivo validation of top candidates by adoptive transfer of mutant CD8+ T cells in mouse models of GBM.
Fig. 3: Single-cell RNA-seq and bulk mRNA-seq analysis of Pdia3 knockout in CD8+ T cells.
Fig. 4: Mechanistic analysis and preclinical efficacy testing of Pdia3 knockout in CD8+ T cells.
Fig. 5: Human CD8+ T-cell PDIA3 knockout and effector function analysis.
Fig. 6: Human PDIA3−/−-EGFRvIII CAR-T-cell establishment and GBM cell killing.

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Data availability

Source data and statistics for non-NGS experiments such as tumor studies, flow cytometry, T7E1, qPCR, protein experiments and coculture assays are provided in an Excel table as Source Data. Genome sequencing data are deposited to the Sequence Read Archive with accession number PRJNA553676. Other data, reagents, methods, computational code and materials that support the findings of this research are available from the corresponding author upon reasonable request.

Code availability

Custom code used to support the findings of this research is available from the corresponding author upon reasonable request.

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Acknowledgements

We thank C. Fuchs, D. Hafler, R. Montgomery, D. Rimm and M. Gunel for discussions. We thank S. Lam, L. Shen, Z. Bai, H. Ye, R. Kim and other members of the Chen laboratory, as well as various colleagues in the Department of Genetics, Systems Biology Institute, Cancer Systems Biology Center, MCGD Program, Immunobiology Program, BBS Program, Cancer Center and Stem Cell Center at Yale for assistance and/or discussion. We thank the Center for Genome Analysis, the Center for Molecular Discovery, Pathology Tissue Services, Histology Services, the High Performance Computing Center, West Campus Analytical Chemistry Core and West Campus Imaging Core, the Mass Cytometry Core and Keck Biotechnology Resource Laboratory at Yale for technical support. S.C. is supported by Yale SBI/Genetics Startup Fund, the NIH/NCI (grant nos. DP2CA238295, R01CA231112, U54CA209992-8697, R33CA225498, RF1048811, P50CA196530-A10805, P50CA121974-A08306), the Damon Runyon Dale Frey Award (grant no. DFS-13-15), the Melanoma Research Alliance (grant nos. 412806, 16-003524), St-Baldrick’s Foundation (grant no. 426685), the Breast Cancer Alliance, the Cancer Research Institute (CLIP), AACR (grant nos. 499395, 17-20-01-CHEN), The Mary Kay Foundation (grant no. 017-81), The V Foundation (grant no. V2017-022), the Ludwig Family Foundation, DoD (grant no. W81XWH-17-1-0235), the Sontag Foundation and the Chenevert Family Foundation. G.W. is supported by CRI Irvington and RJ Anderson Fellowships. X.D. is supported by a Revson Fellowship. M.B.D., R.D.C. and J.J.P. are supported by the Yale MSTP training grant from the NIH (grant no. T32GM007205).

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Author notes

  1. These authors contributed equally: Lupeng Ye, Jonathan J. Park, Matthew B. Dong.

Authors and Affiliations

  1. System Biology Institute, Integrated Science & Technology Center, West Haven, CT, USA

    Lupeng Ye, Jonathan J. Park, Matthew B. Dong, Quanjun Yang, Ryan D. Chow, Lei Peng, Yaying Du, Jianjian Guo, Xiaoyun Dai, Guangchuan Wang, Youssef Errami & Sidi Chen

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

    Lupeng Ye, Jonathan J. Park, Matthew B. Dong, Quanjun Yang, Ryan D. Chow, Lei Peng, Yaying Du, Jianjian Guo, Xiaoyun Dai, Guangchuan Wang, Youssef Errami & Sidi Chen

  3. Center for Cancer Systems Biology, Integrated Science & Technology Center, West Haven, CT, USA

    Lupeng Ye, Jonathan J. Park, Matthew B. Dong, Quanjun Yang, Ryan D. Chow, Lei Peng, Yaying Du, Jianjian Guo, Xiaoyun Dai, Guangchuan Wang, Youssef Errami & Sidi Chen

  4. Yale M.D.–Ph.D. Program, Yale University School of Medicine, New Haven, CT, USA

    Jonathan J. Park, Matthew B. Dong, Ryan D. Chow & Sidi Chen

  5. Immunobiology Program, Yale University School of Medicine, New Haven, CT, USA

    Matthew B. Dong & Sidi Chen

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

    Matthew B. Dong

  7. Department of Neurosurgery, Yale University School of Medicine, New Haven, CT, USA

    Sidi Chen

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

    Sidi Chen

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

    Sidi Chen

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

    Sidi Chen

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

    Sidi Chen

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Contributions

L.Y. designed the AAV–SB–CRISPR vector, developed the screening system and performed the majority of experiments in this study. J.J.P. analyzed the CRISPR screen and other high-throughput data. M.B.D. generated transgenic mice and optimized the screen. R.D.C. designed the Surf library. Q.Y., L.P., Y.D., J.G., G.W. and Y.E. assisted with various experiments. Y.D. and X.D. designed and generated the EGFRvIII CAR-T system. S.C. conceived the study, secured funding and supervised the work. L.Y., J.J.P. and S.C. prepared the manuscript with input from all of the other authors.

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Correspondence to Sidi Chen.

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Integrated supplementary information

Supplementary Figure 1 Splinkerette PCR identify genome integration of Sleeping Beauty transposon.

(a) Nextera indel analysis for Mll3 and B2m knock-out in mouse CD8+ T cells using AAV-sgRNA vectors. Representative mutations and their frequencies were shown around predicted sgRNA target sites. (b) Schematics of splinkerette PCR procedures. The steps include genomic DNA isolation, restriction enzyme digestion, adaptor ligation, PCR, NGS library prep, and sequencing. (c) Electrophoresis of the splinkerette PCR products. The gel within red dash line was gel purified for the Nextera library preparation and sequencing. (d) Representative SB transposon integration sites in the mouse genome. (e) A bar plot of splinkerette PCR read distribution for the number of integration sites along mouse chromosomes. (f) A bar plot showed splinkerette PCR read distribution for the number of integration sites according to functional annotation of genomic regions.

Supplementary Figure 2 Single cell RT-qPCR estimation of functional MOI of AAV-SB-CRISPR screen.

Single cell RT-qPCR detection of single T cell expressing functional sgRNAs, for the estimation of functional MOI with exact transduction parameters in the AAV-Surf screen. PBS treated single T cells were used as a negative control. Numbers of wells without T cells, with sgRNA- T cells and with sgRNA+ T cells were determined to estimate MOI.

Supplementary Figure 3 Penetrance estimation of intracranial brain tumor induction using GL261 and derivatives cell lines.

(a) Bar plot of mortality rate of mouse after intracranial GBM induction. Different GBM cell lines, GL261, GL261-Luc-Ova, and GL261-Luc, were used for brain injection, and each cell line injected with different cell number. (b) Bar plot of number of mice that met euthanasia endpoint due to brain tumor.

Supplementary Figure 4 AAV-Surf library transduced mouse CD8+ T cell surface phenotypes and TCR repertoires before and after adoptive transfer.

(a) Flow cytometry analysis of surface PD-1, Lag3, and Tim-3 expression after transduced with AAV-Vector and AAV-Surf virus. Result from one experiment. (b-c) Flow cytometry analysis of proportion of PD-1+ TILs. ns, non-significant. Data are shown as mean ± s.e.m., with individual data points. The p-values and number of mice used in each group are indicated in the plots and/or in a supplemental excel table. (d) A bar plot of T cell clonal composition from TCR sequencing. Pre injection, mouse CD8+ T cells transduced with AAV-Surf virus and cultured for 5 days; Post injection (TIL), AAV-Surf transduced T cells i.v. injected into GBM-bearing mice and isolated as TILs at day 6 after T cell injection. (e) A ring plot of TCR distribution for T cells before i.v. injection. Top TCR sequences were labeled in the plot. (f) A ring plot of TCR distribution for T cells after i.v. injection (TILs). Top TCR sequences were labeled in the plot.

Source data

Supplementary Figure 5 AAV-CRISPR CD8+ T cell screens of membrane bound proteome knockouts in GBM.

(a) Schematics of hybrid AAV-SB-CRIPSR CD8+ T cell screen in a syngeneic mouse model of GBM, showing steps of naïve CD8+ T cell isolation, AAV library transduction, GBM cell transplantation, adoptive T cell transfer, brain and tumor isolation, and sgRNA readout by deep sequencing. (b) Representative in vivo imaging illustrating the growth of GL261-FLuc tumors in the brains of C57BL/6 mice. (c) Representative photos of mice after GBM transplantation and T cell treatment. Red circles indicated macrocephaly suggestive of growing brain tumors. (d) Survival plot of mice after GBM engraftment and adoptive transfer. C57BL/6J mice were transplanted with 1.2 x 106 GL261-FLuc into the lateral ventricle (LV). 4 x 106 OT-I;Cas9β CD8+ T cells were injected after 10 days of tumor engraftment. Survival significance was assessed by a log-rank Mantel-Cox test. The p-values and number of mice used in each group was indicated in the plots. The group of mice receiving adoptive transfer of T cells has significantly enhanced survival, where the effect of AAV-Surf is slightly stronger than Vector. DPI, days post tumor implantation. (e) Representative H&E stained brain sections from PBS, AAV-Vector and AAV-Surf groups. Areas within red dashed lines indicate brain tumors. Scale bar, 2 mm for whole brain sections, and 100 μm for zoom-in sections. These are representative images at the endpoint of survival thus not quantitative for comparison in terms of tumor burden. One experiment, n = 3 individual mice for PBS, n = 5 mice for vector, n = 11 mice for AAV-Surf. (f) Scatterplot of brain vs. cell sgRNA library representation of AAV-Surf shorter term screen experiment (max survival 20 days post injection). The most enriched sgRNAs in the brain are highlighted. Purple dash line, y = x curve; blue dash line, linear regression of the distribution of the 1,000 NTCs between the brain and cell samples. (g) Scatterplot of brain vs. cell sgRNA library representation of AAV-Surf longer term screen experiment (max survival 92 days post injection). The most enriched sgRNAs in the brain are highlighted. Purple dash line, y = x curve; blue dash line, linear regression of the distribution of the 1,000 NTCs between the brain and cell samples. The p-values and number of mice used in each group are indicated in the plots and/or in a supplemental excel table.

Source data

Supplementary Figure 6 Clonal GBM cell line generation and representative mouse GBM histology with single gene knockout adoptive transfer.

(a) Flow cytometry analysis of GL261-FLuc-mCh-cOVA clones for cOVA expression level. Two independent experiments. (b) T7EI assay indicated gene editing of Mgat5 and Pdia3 with AAV-SB100x vector. Multiple, at least five independent experiments. (c) T7EI assay for mouse T cells treated with sgPdia3 on top 4 predicted off-target sites. Two experiments. (d) RT-qPCR of Mgat5 and Pdia3 after infected with AAV6 carrying specific gene-targeting sgRNAs in AAV-SB100x vector. Unpaired t test was used for the significance assessment, AAV-Vector vs. AAV-sgMgat5, p = 0.0242. * p < 0.05. (e) Schematic of the therapeutic efficacy testing strategy for top candidates identified from the AAV-Surf screens, using adoptive transfer of single gene edited CD8+ T cells in a syngeneic mouse model of GBM. (f) Survival plots of the top candidate validations in a syngeneic mouse model of GBM. C57BL/6J mice were engrafted with 2 x 105 GL261 cancer cells, and adoptive transfer treatment was performed after 10 days of tumor engraftment by intravenous injection of 6 x 105 Cas9β CD8+ T cells infected with AAV-Vector, AAV-sgLag3, AAV-sgMgat5, and AAV-sgPdia3. Survival significance was assessed by a log-rank Mantel-Cox test. (g) Representative H&E stained brain sections from AAV-Vector and AAV-sgRNA single knockout groups in C57BL/6J mice. Scale bar, 100 μm. These are representative images at the endpoint of survival thus not quantitative for comparison in terms of tumor burden. One experiment, n = 8 individual mice for each group. (h) Representative H&E stained brain sections from AAV-Vector and AAV-sgRNA single knockout groups in Rag1-/- mice. Scale bar, 100 μm. These are representative images at the endpoint of survival thus not quantitative for comparison in terms of tumor burden. One experiment, n = 8 mice for AAV-Vector, n = 10 mice for AAV-sgMgat5, n = 9 for AAV-sgPdia3, and n = 8 for AAV-sgEmp1. The p-values and number of mice used in each group are indicated in the plots and/or in a supplemental excel table.

Source data

Supplementary Figure 7 Representative luciferase imaging for tumor burden quantification.

(a) Quantification of tumor burden as total luciferase flux at days 12, 16, and 18. Day 20 and 22 data points were not used for statistics because most mice in the AAV-Vector group had already reached endpoint. Mice being imaged, n = 8 for Vector, n = 8 for sgMgat5, n = 5 for sgPdia3. Data are shown as mean ± s.e.m. plus individual data points on bar graphs. (b) Quantification of tumor burden as total luciferase flux at days 14, 15, 17, 19, and 22 after tumor induction. Mice being imaged, n = 7 for Vector, n = 7 for sgMgat5, n = 8 for sgPdia3, n = 8 for sgMgat5+sgPdia3. Data are shown as mean ± s.e.m. plus individual data points on bar graphs. The numbers of mice that had reached endpoint, euthanized, and therefore removed from the imaging group are indicated on the top table.

Source data

Supplementary Figure 8 Single cell RNA-seq profiling of Pdia3 KO CD8+ T cells.

(a) t-SNE plot of hierarchical clustering of scRNA-seq results. (b) Volcano plot of scRNA-seq of mouse CD8+ T cells after Pdia3 knockout. Pdia3 is a significantly downregulated gene after infection with AAV-sgPdia3. A total 9,193 single cells were captured and their transcriptomes were sequenced for the AAV-sgPdia3 (n = 4,549 single cells) and AAV-Vector (n = 4,644 single cells) treated CD8 T cells. Two-sided Wilcoxon signed-rank test by gene, with p-values adjusted by Benjamini & Hochberg.

Supplementary Figure 9 Immune marker analysis of PDIA3 KO human CD8+ T cells by CyTOF.

(a) t-SNE plot clustered by samples, showing that the 3 PDIA3 KO samples grouped with each other, the 3 WT samples also grouped with each other, and that PDIA3 KO samples and WT samples formed distinct groups. (b) t-SNE plot of CyTOF data with k-means clustering revealing 10 major clusters. (c) t-SNE and violin plots of CyTOF data of CD127 / IL7R, FAS / CD95, 4-1BB / CD137 and TIM-3 / HAVCR2 at the surface protein level, for both PDIA3 KO and wildtype single human CD8+ T cells (n = 3 replicates each, sampled 7,000 cells per replicate for comparison). Violins show kernel probability density on side, and boxplot is standard, i.e. middle band is median, hinges/ends of box are interquartile range (25% and 75% quantiles), lower whisker = smallest observation greater than or equal to lower hinge - 1.5 * IQR, upper whisker = largest observation less than or equal to upper hinge + 1.5 * IQR. Wilcoxon test, two-sided, p value adjusted by Benjamini & Hochberg method. KO vs WT: p = 1.91e-81 for CD127 / IL7R, p = 0.1147 for FAS / CD95, p = 6.75e-83 for 4-1BB / CD137, and p = 0 for TIM-3 / HAVCR2.

Supplementary Figure 10 TIDE analysis of PDIA3-related T cell dysfunction in human cancer patients.

(a–c) Analyses of PDIA3 expression signatures linked to in cytotoxic T lymphocyte (CTL) – associated survival benefits in patients, where high-level of PDIA3 abolishes or weakens the overall survival benefit of CTL-high patients with GBM (a), TNBC (b), or LUAD (c). X-axis is overall survival in months. Y-axis is survival fraction. Specific statistical tests using TIDE (Methods). (d) Analyses of PDIA3 expression signatures linked to survival benefits of patients treated with an immune-checkpoint antibody (Ipilimumab, anti-CTLA4), in melanoma. X-axis is overall survival in days. Y-axis is survival fraction. Specific statistical tests were performed using TIDE (Methods).

Supplementary Figure 11 Representative flow cytometry gating.

(a) Gating of mouse Ifnγ+ CD8+ T cells. (b) Gating of human IFNγ+ CD8+ T cells.

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Supplementary Figs. 1–11 and Methods.

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Supplementary Tables 1–11.

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Source Data for Figs. 1–6 and Supplementary Figs. 4–7

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Ye, L., Park, J.J., Dong, M.B. et al. In vivo CRISPR screening in CD8 T cells with AAV–Sleeping Beauty hybrid vectors identifies membrane targets for improving immunotherapy for glioblastoma. Nat Biotechnol 37, 1302–1313 (2019). https://doi.org/10.1038/s41587-019-0246-4

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