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BATF and IRF4 cooperate to counter exhaustion in tumor-infiltrating CAR T cells

Nature Immunology volume 22, pages 983–995 (2021)Cite this article

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Abstract

The transcription factors nuclear factor of activated T cells (NFAT) and activator protein 1 (AP-1; Fos–Jun) cooperate to promote the effector functions of T cells, but NFAT in the absence of AP-1 imposes a negative feedback program of T cell hyporesponsiveness (exhaustion). Here, we show that basic leucine zipper ATF-like transcription factor (BATF) and interferon regulatory factor 4 (IRF4) cooperate to counter T cell exhaustion in mouse tumor models. Overexpression of BATF in CD8+ T cells expressing a chimeric antigen receptor (CAR) promoted the survival and expansion of tumor-infiltrating CAR T cells, increased the production of effector cytokines, decreased the expression of inhibitory receptors and the exhaustion-associated transcription factor TOX and supported the generation of long-lived memory T cells that controlled tumor recurrence. These responses were dependent on BATF–IRF interaction, since cells expressing a BATF variant unable to interact with IRF4 did not survive in tumors and did not effectively delay tumor growth. BATF may improve the antitumor responses of CAR T cells by skewing their phenotypes and transcriptional profiles away from exhaustion and towards increased effector function.

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Fig. 1: Antitumor effects of CAR T cells ectopically expressing bZIP transcription factors.
Fig. 2: High-dimensional single-cell characterization of pMIG- and BATF-transduced CAR TILs by mass cytometry (CyTOF).
Fig. 3: BATF-transduced CAR T cells confer a memory response against tumor rechallenge and exhibit a memory phenotype.
Fig. 4: The BATF–IRF interaction is required for CAR T cell survival, expansion and antitumor responses.
Fig. 5: Genome-wide analysis of differences in transcription and chromatin accessibility between pMIG- and BATF-transduced cells.
Fig. 6: BATF and IRF4 binding and gene expression changes in pMIG- and BATF-transduced cells.
Fig. 7: Relationship of BATF binding to chromatin accessibility and gene expression in BATF-transduced cells.
Fig. 8: Regions of high IRF4 binding in BATF-overexpressing cells are enriched in strong-consensus AICE and AICE2 motifs.

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Data availability

The RNA-seq, ATAC-seq and ChIP-seq data have been deposited at the Gene Expression Omnibus (GSE154747). Source data are provided with this paper. Other data that support the findings of this study are available from the corresponding authors upon request.

Code availability

The base code used to preprocess the ATAC-seq, RNA-seq and ChIP-seq data and the code used for the analysis of differential gene expression have been deposited in GitHub at https://github.com/Edahi/NGSDataAnalysis.

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Acknowledgements

We thank C. Kim, D. Hinz and C. Dillingham of the LJI Flow Cytometry Core Facility for the CyTOF experiments; D. Hinz, C. Dillingham, S. Ellis, M. Haynes, S. Sehic and C. Kim for cell sorting; J. Day, C. Kim and K. Tanguay of the LJI Next Generation Sequencing Facility for sequencing; the LJI DLAC and the animal facility for excellent support; and R. Nowak for excellent laboratory management. This work was funded in part by NIH R01 grants AI109842 and AI040127 (to P.G.H. and A.R.); U01 grant DE028227 (to A.R.); NIH S10 instrumentation grants RR027366 and OD018499 (to the LJI); AACR-Genentech Immuno-oncology Research Fellowship 18-40-18-SEO and Donald J. Gogel Cancer Research Institute Irvington Fellowship (to H.S.); University of California Institute for Mexico and the United States (UC MEXUS) and El Consejo Nacional de Ciencia y Tecnología (UC MEXUS/CONACYT) predoctoral fellowship (to E.G.-A.); NIH T32 predoctoral training grant in the University of California, San Diego Cardiovascular Bioengineering Training Program (to W.Z.); Cancer Research Institute Irvington Fellowship (to C.Y.); an Independent Investigator Fund (LJI/Kyowa Kirin) and a Career Transition Award from the National Cancer Institute (K22CA241290 to C.-W.J. L.).

Author information

Author notes

  1. Hyungseok Seo & Payal Ramchandani

    Present address: Novartis Institutes for BioMedical Research, Cambridge, MA, USA

  2. Chan-Wang J. Lio

    Present address: Department of Microbial Infection and Immunity, College of Medicine, The Ohio State University, Columbus, OH, USA

  3. These authors contributed equally: Hyungseok Seo, Edahí González-Avalos.

Authors and Affiliations

  1. Division of Signaling and Gene Expression, La Jolla Institute for Immunology, La Jolla, CA, USA

    Hyungseok Seo, Edahí González-Avalos, Wade Zhang, Payal Ramchandani, Chao Yang, Chan-Wang J. Lio, Anjana Rao & Patrick G. Hogan

  2. Bioinformatics and Systems Biology Graduate Program, University of California, San Diego, La Jolla, CA, USA

    Edahí González-Avalos

  3. Bioengineering Graduate Program, Bioengineering Department, University of California, San Diego, La Jolla, CA, USA

    Wade Zhang

  4. Contiguous BS/MS Program, Biology Department, University of California, San Diego, La Jolla, CA, USA

    Payal Ramchandani

  5. Department of Pharmacology, University of California, San Diego, La Jolla, CA, USA

    Anjana Rao

  6. Sanford Consortium for Regenerative Medicine, La Jolla, CA, USA

    Anjana Rao

  7. Moores Cancer Center, University of California, San Diego, La Jolla, CA, USA

    Anjana Rao & Patrick G. Hogan

  8. Center for Cancer Immunotherapy, La Jolla Institute for Immunology, La Jolla, CA, USA

    Anjana Rao & Patrick G. Hogan

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Contributions

H.S. designed and performed the experiments, analyzed the data and prepared the sequencing libraries. E.G.-A. performed the computational analyses of the genome-wide sequencing data. W.Z. cloned the plasmid vectors, performed the NFAT–AP-1 reporter screening assays and assisted with the in vivo and in vitro experiments. C.-W.J.L. provided the pMIG-BATF and IRF4 vectors. P.R. and C.Y. assisted with the in vitro experiments. A.R. and P.G.H. supervised the study. H.S., E.G.-A., A.R. and P.G.H. interpreted the data and wrote the manuscript. All authors contributed to writing and providing feedback.

Corresponding authors

Correspondence to Anjana Rao or Patrick G. Hogan.

Ethics declarations

Competing interests

A.R. and P.G.H. were recipients of a grant from Lyell Immunopharma for a separate research project related to cancer immunotherapy. The La Jolla Institute for Immunology has filed a patent application, PCT/62/976,706, covering the production and use of engineered immune cells expressing BATF and IRF4. H.S., A.R. and P.G.H. are listed as inventors. The other authors have no competing interests.

Additional information

Peer review information Nature Immunology thanks Rahul Roychoudhuri, Harinder Singh and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available. L. A. Dempsey was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

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Extended data

Extended Data Fig. 1 Identification of bZIP transcription factors capable of increasing NFAT:AP-1 reporter activity.

a, MA plots of basic region-leucine zipper (bZIP) transcription factor gene expression in TOX-depleted (TOX DKO, left) or NR4A-depleted (Nr4a TKO, right) CAR TILs5,6— which mount increased anti-tumor responses— relative to control CAR TILs. Differentially expressed genes (adjusted p-value < 0.1, log2 fold-change ≥ 0.5 or ≤ −0.5) are highlighted; selected genes are labeled. b, Basis of the experiment to identify bZIP transcription factors that activate an NFAT:AP-1 reporter through a positive feedback loop, either directly by binding adjacent to NFAT on the NFAT:AP-1 composite site or indirectly by increasing the expression or activity of NFAT or AP-1. Mouse CD8+ T cells were transduced with retroviral expression vectors encoding a Thy1.1 reporter, separated by a P2A sequence from a co-expressed bZIP transcription factor, and under the control of six tandem NFAT:AP1 sites upstream of a minimal IL-2 promoter. Transcription factors for testing were chosen based on the data analysis in a. c, Gating strategy for the experiments. d, g, Histograms of Thy1.1 expression after CD8+ T cell transduction. No Thy1.1, transduced with empty retrovirus without Thy1.1 or bZIP transcription factor; No bZIP, transduced with retroviral vector encoding Thy1.1 but no bZIP transcription factor, a condition that assesses the background induction of Thy1.1 by endogenous NFAT and AP-1; Jun, Maff, Batf, and Batf3 (d) and JunD, Fosl2, and Nfil3 (g), transduced with vector encoding the indicated bZIP transcription factor. e, h, Percentage of Thy1.1+ cells in three replicate experiments. f, i, MFI of Thy1.1 expression in these experiments. j, k, Results for each sample, normalized to those of the No bZIP control from the same experiment. Each circle in e, f, h, I, j and k represents one mouse. Data are representative of (c, d, g) or obtained from (e, f, h-k) three biological replicate experiments. Data in e and h were analyzed by one-way ANOVA. *P ≤ 0.05; **P ≤ 0.01; ***P ≤ 0.001; ****P ≤ 0.0001.

Source data

Extended Data Fig. 2 Phenotypic analyses of pMIG- and BATF-transduced CAR TILs.

a, Retroviral transduction efficiencies for CAR and MSCV-IRES-eGFP retroviral expression plasmids, assessed as expression of Thy1.1 and GFP respectively. FMO, fluorescence-minus-one control. b, Histograms showing BATF (left), JUN (middle), and MAFF (right) expression after retroviral transduction of CD8+ T cells with the corresponding retroviral expression plasmids or pMIG empty-vector control, assessed by flow cytometry with antibodies to the endogenous proteins. c, Histograms showing CAR expression (assessed by staining for the Myc tag) in pMIG- (grey), BATF- (red), JUN- (sky blue) and MAFF- (orange) transduced CAR T cells. d-e, Replicate tumor growth experiments using B16F0-hCD19 (d) and MC38-hCD19 (e) tumor cells. 1×105 tumor cells were injected subcutaneously into the left flank of C57BL/6 mice at day 0 (D0) in 100 μl phosphate-buffered saline (PBS); 3×106 control pMIG-, JUN-, MAFF-, or BATF-transduced CAR T cells were adoptively transferred by retro-orbital injection at day 7. Tumor sizes were measured by caliper. f, Histograms showing expression of the indicated markers by each group of CAR TILs, assessed by flow cytometry. g, Left panels, Histograms showing expression of CD44, CD62L, CD127 and KLRG1. Middle panels, Overlaid contour plots of CD44 and CD62L (top) and CD127 and KLRG1 (bottom) in pMIG- (grey) and BATF- (red) transduced CAR TILs. Right panel, expression of the markers quantitated as MFI. h, Left panels, Histograms showing expression of TNF, IFNγ, granzyme B, and CD107a after resting in T cell media or after stimulation with PMA and ionomycin for 4 h. Right panel, expression of the markers quantitated as MFI. i, pMIG (n = 6) and BATF (n = 6). Quantitation of TCF1+ and TCF1– CAR TILs. Each circle in g, h, and i represents one mouse, and the bar graphs represent the mean ± standard error of mean (s.e.m.). Data in d-i were obtained from two independent biological experiments. Data in g, h, and i were analyzed by two-tailed unpaired Student’s t-test.

Source data

Extended Data Fig. 3 Mass cytometric analyses.

a, Gating strategy for mass cytometry of tumor-infiltrating lymphocytes (TILs). b, UMAP plots of data from TILs of tumour-bearing mice, showing expression of CD8α (top) as a marker for all CD8+ T cells (including endogenous T cells) and Thy1.1 (bottom) as a marker for adoptively transferred pMIG- or BATF-transduced CAR T cells. c, Mass cytometric analysis of CD8+ T cells from draining lymph nodes (left) and spleens (right) of mice in the tumor rechallenge experiments (Fig. 3). Endogenous CD8+ T cells and BATF-transduced CAR T cells are clearly distinguishable in the UMAP views. d, Expression of selected surface markers on lymphocytes obtained from three groups of age-matched C57BL/6 mice: inguinal lymph nodes of completely unmanipulated, non-tumor-bearing mice (left panels); draining (inguinal) lymph nodes of mice inoculated with tumors 14 days previously (middle panels), and draining (inguinal) lymph nodes of rechallenged mice. The UMAP plots show that each marker is expressed by all or by a large fraction of lymph node CAR T cells of the rechallenged mice. Each group of samples in c and d was pooled from 5 mice. The data are representative of two independent biological experiments. e, Replicate of the experiment in Fig. 3e. 1×105 B16F0-hCD19 tumor cells were injected subcutaneously into the right flank of age-matched C57BL/6 mice (n = 3) to yield the ‘tumor-naïve’ control group, or into the right flank of the surviving tumor-free mice (n = 3) from the experiment of Extended Data Fig. 2d. In this replicate B16-hCD19 rechallenge experiment, CAR T cells accounted for ~10% of CD8+ T cells in spleen and LN of the mice, and exhibited a memory phenotype (CD44high, CD62Lhigh, TCF1high) as in the first experiment.

Extended Data Fig. 4 BATF overexpression improves effector function in human CAR T cells.

a, Histograms showing expression of human BATF (hBATF, left panel) and human CAR (hCAR [stained by Goat Anti-Armenian Hamster IgG (H + L)], right panel) in the corresponding lentivirally transduced human CD8+ T cells. FMO, fluorescence-minus-one control; TIG, control cells transduced with the empty vector. b, Left, Histograms showing CellTrace Violet (CTV) dilution in lentivirally transduced human CD8+ CAR T cells. Right, Proliferation index calculated as (Day 0 CTV MFI) / (Day 4 CTV MFI). c, Histograms showing expression of the indicated cytokines after resting in X-Vivo media or after stimulation with PMA and ionomycin for 4 h. d-e, Human CAR T cells were labeled with CellTrace Violet and co-cultured with NALM6 cells for 5 h. d, Gating strategy for in vitro cytotoxicity assay of control (TIG) or hBATF-transduced human CAR T cells. e, Histograms showing ratio between target cells (NALM6) and effector cells (human CAR T cells). Percent cytotoxicity was calculated as (1- (R5/R0)) x 100, where R5 = (target cells as % of total at 5 h) / (effector cells as % of total at 5 h), R0 = (target cells as % of total at 0 h) / (effector cells as % of total at 0 h). Each dot in b-e represents an individual donor. Data were obtained from four biological experiments and analyzed by one-tailed unpaired Student’s t-test.

Extended Data Fig. 5 Tumor growth and TIL expansion/survival in mice receiving BATF-transduced, BATF-HKE-transduced, or BATF-deficient CD8+ T cells.

a, Tumor growth curves for the individual mice from Fig. 4b,c (PBS (n = 12), pMIG (n = 16), BATF (n = 25) and HKE (n = 12)). b-f, 1×105 B16F0-hCD19 tumor cells were subcutaneously injected into the left flank of C57BL/6 mice at day 0 (D0). 100 μl of PBS, without cells or containing 1.5×106 CAR T cells transduced with retroviral expression plasmids encoding either pMIG control, BATF, or BATF HKE-mutant, were adoptively transferred into C57BL/6 recipient mice by retro-orbital injection on day 12. TILs were isolated on days 13, 16, 19, and 22. c, Expression of CAR T cell marker Thy1.1 on CD8+ TILs on the indicated days. d-f, Frequencies and MFIs of the indicated PD-1- and TIM3-expressing populations from Fig. 4j,k. g-m, 1×105 B16F0-hCD19 tumor cells were injected subcutaneously into the left flank of C57BL/6 mice at day 0 (D0). 1.5×106 wild-type (WT, n = 4) or BATF-deficient (BATF KO, n = 4) CAR T cells were adoptively transferred at day 12. Tumor-infiltrating lymphocytes were isolated at day 20. h, Tumor growth curves for individual mice (dashed lines) and average (bold lines) of all tumor growth curves in a group. i-k, Contour plots of Thy1.1 expression in CD8+ TILs (i), percentages of Thy1.1+ CAR TILs (j) and numbers of Thy1.1+ CAR TILs normalized to tumor size (k) in tumor-bearing BATF WT or BATF KO mice. l, Contour plots of PD-1 and TIM3 expression (left) and percentage of PD-1hiTIM3+ cells (right) in WT or BATF KO CAR TILs. m, Contour plots of PD-1 and TOX expression (top left), TIM3 and TCF1 expression (bottom left), and percentages of the indicated populations (right) in WT or BATF KO CAR TILs. Data in a were obtained from three independent experiments. Each circle in d-f and j-m represents one mouse, and the bar graphs represent the mean ± standard error of mean (s.e.m.). Data in d-m are representative of two independent experiments. Data in j-m were analyzed by two-tailed unpaired Student’s t-test.

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Extended Data Fig. 6 Tumor growth rates, survival curves, and phenotypic analysis of CAR TILs.

a-e, 2.5×105 B16F10-OVA tumor cells were injected subcutaneously into the left flank of C57BL/6 mice at day 0 (D0). 100 μl of PBS (n = 10), without cells or containing 1×106 OT-I T cells transduced with retroviral expression plasmids encoding pMIG control (n = 10), BATF (n = 10), IRF4 (n = 10), or BATF + IRF4 (n = 10), were adoptively transferred by retro-orbital injection at day 7. b, Averaged tumor growth curves for all mice in the indicated groups. c, Tumor sizes measured in individual mice at day 18. d, Mouse survival curves. e, Tumor growth curves in individual mice. f-m, 2.5×105 B16F10-OVA tumor cells were injected subcutaneously into the left flank of C57BL/6 mice at day 0. 1×106 pMIG control- (n = 4), BATF- (n = 5), IRF4- (n = 5), or BATF + IRF4-transduced (n = 5) OT-I cells were adoptively transferred at day 12. TILs were isolated at day 20. g, Gating strategy for flow cytometric analysis of OT-I TILs. h, Averaged tumor growth curves for all mice in the indicated groups. i, Left, Contour plots of CD8α and CD45.1 expression in OT-I TILs. Middle, Percentage of OT-I TILs in CD8+ TILs. Right, Number of OT-I TILs normalized to tumor size. j, Left, Contour plots of PD-1 and TIM3 expression in each group of OT-I TILs. Right, Percentages of the indicated PD-1- and TIM3-expressing cell populations. k, Left, Contour plots of PD-1 and TOX expression in the indicated OT-I TILs. Right, Percentage of PD-1+TOX+ cells in OT-I TILs. l, m, Left, Contour plots of expression of granzyme B (l) and the indicated cytokines (m) under resting conditions or after PMA/ionomycin stimulation for 4 h. Right, Percentages of OT-I TILs expressing granzyme B (l) or the indicated cytokines (m) under resting conditions or after PMA/ionomycin stimulation for 4 h. Data obtained from two biological experiments. n, Histograms showing JUN and BATF expression in the indicated groups of transduced OT-I T cells. o, Tumor growth curves for individual mice given pMIG control-, BATF-, JUN-, or BATF + JUN-transduced OT-1 cells (top) and averaged tumor growth curves for all mice in each group (bottom). Experimental scheme as in a. Each circle in i, j, k, l, and m represents one mouse, and the bar graphs represent the mean ± standard error of mean (s.e.m.). Data were obtained from two independent biological experiments. Data in h, j, l, and m were analyzed by two-way ANOVA test; data from i and k, by one-way ANOVA test. *P ≤ 0.05; **P ≤ 0.01; ***P  ≤ 0.001; ****P ≤ 0.0001.

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Extended Data Fig. 7 Differentially accessible regions in BATF- compared to pMIG-transduced CAR TILs.

a, Left, Venn diagrams showing the overlap of the 351 regions more accessible in BATF- versus pMIG-transduced TILs (Fig. 5c) with the exhaustion-related (top) or activation-related (bottom) regions from Mognol et al36. Right, Histograms illustrate the significance calculation by one-tailed Fisher’s exact test. b, Genomic annotation of the commonly and differentially accessible regions in CAR TILs. c, Enrichment for transcription factor binding motifs in regions differentially accessible in BATF CAR TILs. d, Heatmap of ATAC-seq signal (z-score) from BATF- and pMIG-transduced CD8+ T cells or CAR TILs, in the 640 regions more accessible in BATF-transduced compared to pMIG-transduced CD8+ T cells (left; see Fig. 5b) and in the 351 regions more accessible in BATF-transduced compared to pMIG CAR TILs (right; see Fig. 5c). Each column represents a biological replicate. Data obtained from two biological experiments.

Extended Data Fig. 8 BATF and IRF4 binding and gene expression changes in pMIG-, HKE-, and BATF-transduced cells.

a, Contour plot relating BATF ChIP-seq signals (log2(CPM)) in BATF-transduced CD8+ T cells to signals from the corresponding peaks in pMIG-transduced cells. b, Left, Distribution of BATF ChIP-seq reads in peaks in BATF-transduced cells (red) versus pMIG-transduced cells (black). Right, BATF ChIP-seq signal distribution in the ‘BATF and pMIG’ peaks common to the two conditions (blue) and in ‘BATF-new’ peaks observed only in BATF-transduced cells (red). The BATF-new peaks defined here are largely the same as the BATF-only peaks in Fig. 6a. c, Heatmaps of the IRF4 ChIP-seq signal in BATF-transduced, BATF-HKE-transduced, and pMIG-transduced cells, at IRF4 peak locations called in BATF-transduced cells. Curves at the top show the average signal taken over all peaks in the respective heatmap. d, Heatmaps of the BATF ChIP-seq signal in BATF-transduced, BATF-HKE-transduced and pMIG-transduced cells, at IRF4 peak locations called in pMIG-transduced cells. Curves at the top show the average signal taken over all peaks in the respective heatmap. e, Genome browser view of Ctla4 gene locus showing BATF and IRF4 ChIP-seq signals from pMIG-, BATF-, and HKE-transduced CD8+ T cells. f, Heatmap of normalized RNA-seq reads (as z-scores) under the indicated conditions, for the top 100 genes differentially expressed after αCD3/αCD28 stimulation of pMIG-transduced cells. Data obtained from two or three biological experiments.

Extended Data Fig. 9 Redistribution of IRF4 binding in BATF-overexpressing cells.

a, The redistribution of the normalized IRF4 ChIP-seq signal in BATF-overexpressing cells is most evident when the median deviation of the y-coordinate (αIRF4 ChIP-seq signal in BATF-overexpressing cells) from the diagonal in Fig. 7c, left, is plotted as a function of position on the x-axis (αIRF4 ChIP-seq signal in control cells). The median for all peaks in each slice of 0.1 log2(CPM) units on the x-axis was determined. The inset replicates Fig. 7c, left, with a red rectangle indicating the slice between log2(CPM) = 0.5 and log2(CPM) = 0.6 on the x-axis. b, Spurious ‘αIRF4’ ChIP-seq regions (as defined in Methods), incorporated into the graph of panel a. c, IRF4 does not redistribute in BATF-HKE-overexpressing cells. The median deviation of the y-coordinate (αIRF4 ChIP-seq signal in HKE-overexpressing cells) from the diagonal in Fig. 7c, right, is plotted as a function of position on the x-axis (αIRF4 ChIP-seq signal in control cells), as in a. d, IRF4 (left) and IRF8 (right) expression detected by flow cytometry (MFI) in pMIG- and HKE-transduced CD8+ T cells that had been expanded in vitro, at the indicated times after restimulation with αCD3/αCD28. The black symbol on the y-axis shows expression in naïve CD8+ T cells. Values for pMIG-transduced and naïve CD8+ T cells were obtained in the same experiments and are replotted from Fig. 6f. Overexpression of BATF-HKE did not attenuate IRF4 or IRF8 induction. e, Similar to Fig. 8a. Dot plot highlighting regions of the IRF4 ChIP-seq data from Fig. 7c where IRF4 binding increases (log2FC ≥ 0.75, red dots), does not change substantially (light grey dots), or decreases (log2FC ≤ -0.75, blue dots) in BATF-overexpressing relative to pMIG-transduced cells. Peaks with very low (log2(signal) < -1.25) or high (log2(signal) > 2.5) IRF4 binding in pMIG cells were judged unlikely to be informative and were omitted from the analysis. f, ATAC-seq signal (CPM) in peaks in each of the three categories defined in e. g, Similar to f, but downsampling the subsets to match the 2312 regions with increased IRF4 binding in BATF-transfected cells, for clearer visualization. Data were obtained from (a-c, e-g), or are representative of (d), two independent biological experiments.

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Seo, H., González-Avalos, E., Zhang, W. et al. BATF and IRF4 cooperate to counter exhaustion in tumor-infiltrating CAR T cells. Nat Immunol 22, 983–995 (2021). https://doi.org/10.1038/s41590-021-00964-8

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