The identification of mechanisms to promote memory T (Tmem) cells has important implications for vaccination and anti-cancer immunotherapy1,2,3,4. Using a CRISPR-based screen for negative regulators of Tmem cell generation in vivo5, here we identify multiple components of the mammalian canonical BRG1/BRM-associated factor (cBAF)6,7. Several components of the cBAF complex are essential for the differentiation of activated CD8+ T cells into T effector (Teff) cells, and their loss promotes Tmem cell formation in vivo. During the first division of activated CD8+ T cells, cBAF and MYC8 frequently co-assort asymmetrically to the two daughter cells. Daughter cells with high MYC and high cBAF display a cell fate trajectory towards Teff cells, whereas those with low MYC and low cBAF preferentially differentiate towards Tmem cells. The cBAF complex and MYC physically interact to establish the chromatin landscape in activated CD8+ T cells. Treatment of naive CD8+ T cells with a putative cBAF inhibitor during the first 48 h of activation, before the generation of chimeric antigen receptor T (CAR-T) cells, markedly improves efficacy in a mouse solid tumour model. Our results establish cBAF as a negative determinant of Tmem cell fate and suggest that manipulation of cBAF early in T cell differentiation can improve cancer immunotherapy.
Your institute does not have access to this article
Subscribe to Nature+
Get immediate online access to the entire Nature family of 50+ journals
Subscribe to Journal
Get full journal access for 1 year
only $3.90 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Tax calculation will be finalised during checkout.
Get time limited or full article access on ReadCube.
All prices are NET prices.
The data supporting the findings of this study are available in the Article and the Supplementary Information. All RNA-seq, ATAC-seq, CUT&RUN and microarray data supporting the findings of this study have been deposited in the Gene Expression Omnibus under accession number GSE183619. The publicly available databases used in this study are available from the Molecular Signatures Database (http://www.broadinstitute.org/gsea/msigdb/). Source data are provided with this paper.
Kaech, S. M., Wherry, E. J. & Ahmed, R. Effector and memory T-cell differentiation: implications for vaccine development. Nat. Rev. Immunol. 2, 251–262 (2002).
Seder, R. A., Darrah, P. A. & Roederer, M. T-cell quality in memory and protection: implications for vaccine design. Nat. Rev. Immunol. 8, 247–258 (2008).
Lugli, E., Galletti, G., Boi, S. K. & Youngblood, B. A. Stem, effector, and hybrid states of memory CD8+ T cells. Trends Immunol. 41, 17–28 (2020).
Okla, K., Farber, D. L. & Zou, W. Tissue-resident memory T cells in tumor immunity and immunotherapy. J. Exp. Med. 218, e20201605 (2021).
Huang, H. et al. In vivo CRISPR screening reveals nutrient signaling processes underpinning CD8+ T cell fate decisions. Cell 184, 1245–1261(2021).
Centore, R. C., Sandoval, G. J., Soares, L. M. M., Kadoch, C. & Chan, H. M. Mammalian SWI/SNF chromatin remodeling complexes: emerging mechanisms and therapeutic strategies. Trends Genet. 36, 936–950 (2020).
Mittal, P. & Roberts, C. W. M. The SWI/SNF complex in cancer—biology, biomarkers and therapy. Nat. Rev. Clin. Oncol. 17, 435–448 (2020).
Verbist, K. C. et al. Metabolic maintenance of cell asymmetry following division in activated T lymphocytes. Nature 532, 389–393 (2016).
Joshi, N. S. et al. Inflammation directs memory precursor and short-lived effector CD8+ T cell fates via the graded expression of T-bet transcription factor. Immunity 27, 281–295 (2007).
Omilusik, K. D. & Goldrath, A. W. Remembering to remember: T cell memory maintenance and plasticity. Curr. Opin. Immunol. 58, 89–97 (2019).
Hodges, C., Kirkland, J. G. & Crabtree, G. R. The many roles of BAF (mSWI/SNF) and PBAF complexes in cancer. Cold Spring Harb. Perspect. Med. 6, a026930 (2016).
Mashtalir, N. et al. Modular organization and assembly of SWI/SNF family chromatin remodeling complexes. Cell 175, 1272–1288 (2018).
Mashtalir, N. et al. Chromatin landscape signals differentially dictate the activities of mSWI/SNF family complexes. Science 373, 306–315 (2021).
Chi, T. H. et al. Reciprocal regulation of CD4/CD8 expression by SWI/SNF-like BAF complexes. Nature 418, 195–199 (2002).
Astori, A. et al. ARID1a associates with lymphoid-restricted transcription factors and has an essential role in T cell development. J. Immunol. 205, 1419–1432 (2020).
Chi, T. H. et al. Sequential roles of Brg, the ATPase subunit of BAF chromatin remodeling complexes, in thymocyte development. Immunity 19, 169–182 (2003).
Kaech, S. M. & Cui, W. Transcriptional control of effector and memory CD8+ T cell differentiation. Nat. Rev. Immunol. 12, 749–761 (2012).
Wherry, E. J. et al. Lineage relationship and protective immunity of memory CD8 T cell subsets. Nat. Immunol. 4, 225–234 (2003).
Huang, C. Y., Bredemeyer, A. L., Walker, L. M., Bassing, C. H. & Sleckman, B. P. Dynamic regulation of c-Myc proto-oncogene expression during lymphocyte development revealed by a GFP-c-Myc knock-in mouse. Eur. J. Immunol. 38, 342–349 (2008).
Kassabov, S. R., Zhang, B., Persinger, J. & Bartholomew, B. SWI/SNF unwraps, slides, and rewraps the nucleosome. Mol. Cell 11, 391–403 (2003).
Hargreaves, D. C. & Crabtree, G. R. ATP-dependent chromatin remodeling: genetics, genomics and mechanisms. Cell Res. 21, 396–420 (2011).
Chen, X. et al. ATAC-see reveals the accessible genome by transposase-mediated imaging and sequencing. Nat. Methods 13, 1013–1020 (2016).
Sammak, S., Allen, M. D., Hamdani, N., Bycroft, M. & Zinzalla, G. The structure of INI1/hSNF5 RPT1 and its interactions with the c-MYC:MAX heterodimer provide insights into the interplay between MYC and the SWI/SNF chromatin remodeling complex. FEBS J. 285, 4165–4180 (2018).
Cheng, S. W. et al. c-MYC interacts with INI1/hSNF5 and requires the SWI/SNF complex for transactivation function. Nat. Genet. 22, 102–105 (1999).
Stojanova, A. et al. MYC interaction with the tumor suppressive SWI/SNF complex member INI1 regulates transcription and cellular transformation. Cell Cycle 15, 1693–1705 (2016).
Meers, M. P., Bryson, T. D., Henikoff, J. G. & Henikoff, S. Improved CUT&RUN chromatin profiling tools. eLife 8, e46314 (2019).
Wang, R. et al. The transcription factor Myc controls metabolic reprogramming upon T lymphocyte activation. Immunity 35, 871–882 (2011).
Gattinoni, L., Klebanoff, C. A. & Restifo, N. P. Paths to stemness: building the ultimate antitumour T cell. Nat. Rev. Cancer 12, 671–684 (2012).
Klebanoff, C. A. et al. Central memory self/tumor-reactive CD8+ T cells confer superior antitumor immunity compared with effector memory T cells. Proc. Natl Acad. Sci. USA 102, 9571–9576 (2005).
Marian, C. A. et al. Small molecule targeting of specific BAF (mSWI/SNF) complexes for HIV latency reversal. Cell Chem. Biol. 25, 1443–1455 (2018).
Chory, E. J. et al. Chemical inhibitors of a selective SWI/SNF function synergize with ATR inhibition in cancer cell killing. ACS Chem. Biol. 15, 1685–1696 (2020).
Dykhuizen, E. C., Carmody, L. C., Tolliday, N., Crabtree, G. R. & Palmer, M. A. Screening for inhibitors of an essential chromatin remodeler in mouse embryonic stem cells by monitoring transcriptional regulation. J. Biomol. Screen. 17, 1221–1230 (2012).
Lim, W. A. & June, C. H. The principles of engineering immune cells to treat cancer. Cell 168, 724–740 (2017).
Haydar, D. et al. Cell-surface antigen profiling of pediatric brain tumors: B7-H3 is consistently expressed and can be targeted via local or systemic CAR T-cell delivery. Neuro-oncology 23, 999–1011 (2021).
Zhao, S. et al. NKD2, a negative regulator of Wnt signaling, suppresses tumor growth and metastasis in osteosarcoma. Oncogene 34, 5069–5079 (2015).
Caldwell, K. J. et al. Immune competent pediatric sarcoma models for the preclinical evaluation of B7-H3-CAR T-Cell therapy. Mol. Ther. 29, 326–326 (2021).
Mitchell, D. M., Ravkov, E. V. & Williams, M. A. Distinct roles for IL-2 and IL-15 in the differentiation and survival of CD8+ effector and memory T cells. J. Immunol. 184, 6719–6730 (2010).
Lu, C. & Allis, C. D. SWI/SNF complex in cancer. Nat. Genet. 49, 178–179 (2017).
Weissmiller, A. M. et al. Inhibition of MYC by the SMARCB1 tumor suppressor. Nat. Commun. 10, 2014 (2019).
Wang, S. C. et al. SWI/SNF component ARID1A restrains pancreatic neoplasia formation. Gut 68, 1259–1270 (2019).
Chapman, N. M., Boothby, M. R. & Chi, H. Metabolic coordination of T cell quiescence and activation. Nat. Rev. Immunol. 20, 55–70 (2020).
Hogquist, K. A. et al. T cell receptor antagonist peptides induce positive selection. Cell 76, 17–27 (1994).
Chang, J. T., Wherry, E. J. & Goldrath, A. W. Molecular regulation of effector and memory T cell differentiation. Nat. Immunol. 15, 1104–1115 (2014).
Madden, M. Z. & Rathmell, J. C. The complex integration of T-cell metabolism and immunotherapy. Cancer Discov. 11, 1636–1643 (2021).
Henning, A. N., Roychoudhuri, R. & Restifo, N. P. Epigenetic control of CD8+ T cell differentiation. Nat. Rev. Immunol. 18, 340–356 (2018).
Bagert, J. D. et al. Oncohistone mutations enhance chromatin remodeling and alter cell fates. Nat. Chem. Biol. 17, 403–411 (2021).
Wan, L. et al. Impaired cell fate through gain-of-function mutations in a chromatin reader. Nature 577, 121–126 (2020).
Kakaradov, B. et al. Early transcriptional and epigenetic regulation of CD8+ T cell differentiation revealed by single-cell RNA sequencing. Nat. Immunol. 18, 422–432 (2017).
Chang, J. T. et al. Asymmetric T lymphocyte division in the initiation of adaptive immune responses. Science 315, 1687–1691 (2007).
Li, J. et al. Epigenetic driver mutations in ARID1A shape cancer immune phenotype and immunotherapy. J. Clin. Invest. 130, 2712–2726 (2020).
Mathur, R. et al. ARID1A loss impairs enhancer-mediated gene regulation and drives colon cancer in mice. Nat. Genet. 49, 296–302 (2017).
Gao, X. et al. ES cell pluripotency and germ-layer formation require the SWI/SNF chromatin remodeling component BAF250a. Proc. Natl Acad. Sci. USA 105, 6656–6661 (2008).
Badea, T. C., Wang, Y. & Nathans, J. A noninvasive genetic/pharmacologic strategy for visualizing cell morphology and clonal relationships in the mouse. J. Neurosci. 23, 2314–2322 (2003).
Wurster, A. L. et al. IL-10 transcription is negatively regulated by BAF180, a component of the SWI/SNF chromatin remodeling enzyme. BMC Immunol. 13, 9 (2012).
de Alboran, I. M. et al. Analysis of C-MYC function in normal cells via conditional gene-targeted mutation. Immunity 14, 45–55 (2001).
Hughes, E. D. et al. Genetic variation in C57BL/6 ES cell lines and genetic instability in the Bruce4 C57BL/6 ES cell line. Mamm. Genome 18, 549–558 (2007).
Cao, Y. A. et al. Shifting foci of hematopoiesis during reconstitution from single stem cells. Proc. Natl Acad. Sci. USA 101, 221–226 (2004).
Connelly, J. P. & Pruett-Miller, S. M. CRIS.py: a versatile and high-throughput analysis program for CRISPR-based genome editing. Sci. Rep. 9, 4194 (2019).
Sanson, K. R. et al. Optimized libraries for CRISPR-Cas9 genetic screens with multiple modalities. Nat. Commun. 9, 5416 (2018).
Wei, J. et al. Targeting REGNASE-1 programs long-lived effector T cells for cancer therapy. Nature 576, 471–476 (2019).
Seaman, S. et al. Eradication of tumors through simultaneous ablation of CD276/B7-H3-positive tumor cells and tumor vasculature. Cancer Cell 31, 501–515 (2017).
Kochenderfer, J. N., Yu, Z., Frasheri, D., Restifo, N. P. & Rosenberg, S. A. Adoptive transfer of syngeneic T cells transduced with a chimeric antigen receptor that recognizes murine CD19 can eradicate lymphoma and normal B cells. Blood 116, 3875–3886 (2010).
Valencia, A. M. et al. Recurrent SMARCB1 mutations reveal a nucleosome acidic patch interaction site that potentiates mSWI/SNF complex chromatin remodeling. Cell 179, 1342–1356 (2019).
Ritchie, M. E. et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 43, e47 (2015).
Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA 102, 15545–15550 (2005).
Buenrostro, J. D., Wu, B., Chang, H. Y. & Greenleaf, W. J. ATAC-seq: a method for assaying chromatin accessibility genome-wide. Curr. Protoc. Mol. Biol. 109, 21.29.1–21.29.9 (2015).
Ewels, P. A. et al. The nf-core framework for community-curated bioinformatics pipelines. Nat. Biotechnol. 38, 276–278 (2020).
Amemiya, H. M., Kundaje, A. & Boyle, A. P. The ENCODE blacklist: identification of problematic regions of the genome. Sci. Rep. 9, 9354 (2019).
Li, B. & Dewey, C. N. RSEM: accurate transcript quantification from RNA-seq data with or without a reference genome. BMC Bioinform. 12, 323 (2011).
Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).
Risso, D., Ngai, J., Speed, T. P. & Dudoit, S. Normalization of RNA-seq data using factor analysis of control genes or samples. Nat. Biotechnol. 32, 896–902 (2014).
We thank P. Fitzgerald, K. Verbist, S. Sirasanagandla, L. Harris, P. Zhou and S. Liu for technical assistance; C. Guy for microscope imaging assistance; N. Chapman for reading and editing the manuscript; the staff at the St Jude Immunology Flow Cytometry Core Facility for cell sorting; the staff at the Hartwell Center for genome sequencing; the staff at the Center for Advanced Genome Engineering for targeted sequencing; and B. Sleckman for providing MYC–GFP mice. Illustrations were created using BioRender. This work was supported by National Institutes of Health grants AI123322 and CA231620 to D.R.G., CA253188 to H.C., National Cancer Institute grant K99CA256262 to D.H. and NCI Cancer Center Support Grant P30 CA021765.
D.R.G. consults for Ventus Therapeutics and Inzen Therapeutics. H.C. consults for Kumquat Biosciences. J.T.Y. consults for Twister Biotech.
Peer review information
Nature thanks Gerald Crabtree, Dean Felsher and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data figures and tables
a, Venn diagram of the overlapping candidates negatively regulating Tmem generation from enriched genes in MP relative to TE cells at day 7.5 post-infection and in total cells at day 36 relative to total cells at day 7.5. b, Flow cytometry plot of TE (KLRG1highCD127low), MP (KLRG1lowCD127high), KLRG1highCX3CR1high, CD62L+, and CXCR3highCD27high CD8+ T cells in sgNTC- and the indicated sgRNA-transduced OT-I cells at day 7.5 post Lm-Ova infection (n = 6 mice). c, Quantification of splenic TE and MP cell numbers at day 7.5 post Lm-Ova infection (n = 5 mice). d, Transcriptome profiling by microarray of sgNTC and the indicated sgRNA-transduced OT-I cells at day 7.5 post Lm-ova infection in vivo (n = 4 mice). e, f, CellTrace Violet labelled WT and Arid1a−/− naïve CD8+ T cells were activated by anti-CD3/CD28 plus ICAM1 for 36 h, and first-division cells were sorted for RNA-seq (n = 5 mice). e, Volcano plot of differentially expressed genes assessed by RNA-seq in WT and Arid1a−/− first-division CD8+ T cells. Teff and Tmem associated genes are highlighted in red and green respectively. f, Gene set enrichment analysis (GSEA) of RNAseq results from WT and Arid1a−/− first-division CD8+ T cells using the C7 immunological collections. Shown are all enriched Teff-associated or Tmem-associated gene sets. Data are shown as mean±s.e.m. *P < 0.05, **P < 0.01, ***P < 0.001; two-tailed paired Student’s t-test (c); two-sided Wald test and adjusted with Benjamini-Hochberg procedure (e); two-sided permutation test and adjusted with Benjamini-Hochberg procedure (f).
a, Diagram of experimental approach to evaluate Tmem function. p.i., post-infection. b, Quantification of numbers of OT-I cells expressing the indicated sgRNA in multiple tissues at day >30 post-infection (n = 5 mice per group). c, Flow cytometry analysis (left) and quantification (right) of the mean fluorescence intensity (MFI) of CellTrace Violet (CTV) dilution in donor-derived OT-I cells. Splenic Tmem OT-I cells transduced with either sgNTC (GFP+ spike cells) or the indicated sgRNA (Ametrine+) were isolated from mice that were challenged with Lm-Ova at day >30 prior, labelled with CTV, mixed at a 1:1 ratio, and transferred to Rag1-deficient recipients. Cells were analysed at day 7 post-transfer (n = 3 mice per group). d, e, Splenic Tmem OT-I cells transduced with sgNTC (GFP+ spike cells) or the indicated sgRNA (Ametrine+) were isolated from mice that were challenged with Lm-Ova at day >30 prior, mixed at a 1:1 ratio, and transferred to naïve C57BL/6 recipients followed by Lm-Ova re-challenge. The cells were analysed at day 6 after re-challenge. d, Flow cytometry plot and quantification of cells expressing both interferon-γ (IFNγ) and TNFα after ovalbumin peptide stimulation for 5 h in the presence of monensin (n = 5 per group). e, Quantification of Granzyme B (GZMB) MFI (n = 5 per group). Data are compiled from at least two independent experiments (b–e). Data are shown as mean±s.e.m. *P < 0.05, **P < 0.01; two-tailed paired Student’s t-test (b, c, d, e).
a, Immunoblot of PBRM1 in naïve CD8+ T cells from Pbrm1fl/fl and Cd4CrePbrm1fl/fl mice. b−e Pbrm1fl/fl and Cd4CrePbrm1fl/fl mice were challenged with Lm-Ova and analysed at day 7.5 (b, c) or at day >30 post-infection (d, e). b, Flow cytometry analysis (left) and quantification (right) of the frequencies and numbers of total CD8+ T cells (upper) and Ova-specific CD8+ T cells (lower) (Pbrm1fl/fl, n = 8 mice; Cd4CrePbrm1fl/fl, n = 6 mice). c, Flow cytometry analysis (left) and quantification (right) of Ova-specific TE (KLRG1highCD127low), MP (KLRG1lowCD127high), CXCR1highKLRG1high and CD62L+ cells in spleen (n = 6 per group). d, Flow cytometry analysis (left) and quantification (right) of Ova-specific Tmem cells in the spleen and indicated organs (Pbrm1fl/fl, n = 5 mice; Cd4CrePbrm1fl/fl, n = 8 mice). e, Percentage of splenic CD62L+ TCM population (Pbrm1fl/fl, n = 5 mice; Cd4CrePbrm1fl/fl, n = 8 mice). f, Flow cytometry analysis of splenic TE (KLRG1highCD127low), MP (KLRG1lowCD127high) and CD62L+ OT-I cells transduced with sgNTC or the indicated sgRNA targeting ncBAF complex components at day 7.5 post Lm-Ova infection (sgNTC, n = 4 mice; sgBrd9-1, n = 5 mice; sgBrd9-2, n = 4; sgBrd9-3, n = 3; sgBicra-1, n = 5 mice; sgBicra-2, n = 4 mice; sgBicra-3, n =4 mice). g, Flow cytometry analysis of splenic TE (KLRG1highCD127low), MP (KLRG1lowCD127high) and CD62L+ OT-I cells transduced with sgNTC or the indicated sgRNA at day 7.5 post Lm-Ova infection (sgNTC, n = 5 mice; sgBrg1-1, n = 4 mice; sgBrg1-2, n = 4 mice; sgBrm-1, n = 5 mice; sgBrm-2, n = 5 mice; sgSmarcc1-1, n = 3 mice; sgSmarcc1-2, n = 3 mice). Data are compiled from two (b−e) or representative of two (a, f, g) independent experiments. Data are shown as mean±s.e.m. **P < 0.01, NS, not significant; two-tailed unpaired Student’s t-test (b−g).
Extended Data Fig. 4 cBAF components asymmetrically segregate to daughter cells during the first division after activation.
a, Representative images (left) of conjoined first-division daughter MYC-GFP-expressing CD8+ T cells, stained for Hoechst (blue), PBRM1 (red) and Tubulin (white); and quantification (right) of asymmetric index (difference in fluorescence intensity/total) (n = 12 cells). Arrows mark tubulin bridges. Scale bar: 5 μm. b, Sorting strategy for first-division MYC-GFPhigh and MYC-GFPlow CD8+ T cells. Naïve CD8+ T cells were labelled with CellTrace Violet (CTV) and activated with anti-CD3ε (2 μg/ml), anti-CD28 (1 μg/ml) plus ICAM1 (0.5 μg/ml) for 36 h prior to sorting. c, d, Immunoblot of BAF components in MYC-GFPhigh and MYC-GFPlow (c) or CD98high and CD98low (d) first-division CD8+ T cells. e, Principal component analysis of the ATAC-seq data in sorted MYC-GFPhigh and MYC-GFPlow daughter cells from first-division stage (n = 3 biological replicates). f, Heatmap of open chromatin regions in sorted MYC-GFPhigh and MYC-GFPlow CD8+ T cells at the promoter, intron and intergenic regions (n = 3 biological replicates). g, Teff and Tmem cell-associated gene sets identified by enrichment analysis of differentially accessible chromatin peaks between MYC-GFPhigh and MYC-GFPlow CD8+ T cells (n = 3 biological replicates). h, Diagram of deletion of Arid1a in sorted MYC-GFPhigh and MYC-GFPlow OT-I cells prior to IAV-Ova infection (related to Fig. 2f, g). Data are representative of one (e−g) or at least two independent experiments (a, c, d). Data are shown as mean±s.e.m. **P < 0.01, NS, not significant; one-way ANOVA (a).
Extended Data Fig. 5 The cBAF complex shares binding sites with MYC in T cell differentiation-associated chromatin loci.
a–d, WT and Arid1a−/− naïve CD8+ T cells were activated by anti-CD3/CD28 plus ICAM1 for 36 h, and first-division CD8+ T cells were sorted for CUT&RUN assay. a, Venn diagram of the overlap between CUT&RUN peaks in WT first-division CD8+ T cells for ARID1A and BRG1 (n = 2 biological replicates). b, Relative locations of MYC peaks to BAF components peaks in chromatin. c, Enrichment analysis of BRG1 and MYC shared binding sites in first-division WT CD8+ T cells using Hallmark gene sets (upper) and Gene ontology gene sets (lower). The co-bound sites were annotated to the nearest genes and enrichment was calculated with over-representation approach. d, Genome browser tracks of MYC and cBAF shared binding sites at Gzmb, Il2ra and Tbx21 loci. The overlapping peaks are highlighted. Data are representative of one experiment (a−d). The P-value was calculated by hypergeometric distribution, one-sided and adjusted with Benjamini-Hochberg procedure (c).
Extended Data Fig. 6 Arid1a deletion reduces chromatin accessibility to sites associated with the Teff gene signature.
a, Volcano plot of ATAC-seq peaks from WT and Arid1a−/− first-division CD8+ T cells (n = 3 biological replicates). b, Teff and Tmem cell-associated gene sets as analysed by enrichment analysis of differentially accessible chromatin peaks between first-division WT and Arid1a−/− CD8+ T cells (n = 3 biological replicates). c, Genome browser tracks of chromatin accessibility at Gzma, Il2 and Klrg1 loci (n = 3 biological replicates). d, Gene set enrichment analysis of MYC targets and mTORC1 signalling gene sets in WT and Arid1a−/− first-division CD8+ T cells from RNA-seq (n = 3 biological replicates). e, Normalized read count of Myc mRNA from RNA-seq (left), and immunoblot for MYC (right) in WT and Arid1a−/− activated CD8+ T cells. (n = 3 biological replicates) P-value was calculated with two-sided Wilcoxon test. Data are representative of one (a−e, RNA-seq) or three (e, immunoblot) experiments. The P-value was calculated with Wald test, two-sided and adjusted with Benjamini-Hochberg procedure (a) or permutation test, two-sided and adjusted with Benjamini-Hochberg procedure (d).
a, b, Naïve CD8+ T cells from Rosa26creERT2Mycfl/fl and Mycfl/wt littermates were treated with 4OHT overnight in IL-2-containing medium prior to activation with anti-CD3/CD28 plus ICAM1 for 36 h. a, Volcano plot of gene profiles in Myc−/− versus WT activated CD8+ T cells as determined by RNA-seq analysis. BAF components are highlighted (n = 5 biological replicates). b, Immunoblot of BAF components in WT and Myc−/− CD8+ T cells. c, d, Naïve CD8+ T cells from WT and Myc+/− mice were activated by anti-CD3/CD28 plus ICAM1 for 28 h before immunofluorescent staining. Representative image (c) and quantification (d) of conjoined WT and Myc+/− daughter CD8+ T cells that were fixed and stained for Hoechst (blue), ATAC-see (red), Lamin B1 (green) and Tubulin (white). Scale bar: 5 μm. Asymmetric index = (fluorescence intensity in daughter cell 1−fluorescence intensity in daughter cell 2)/(fluorescent intensity in daughter cell 1+ fluorescence intensity in daughter cell 2). e, Quantification of the normalized CX3CR1highKLRG1high (left) or CD27highCXCR3high (right) ratio in OT-I cells at day 7.5 post Lm-Ova infection. sgNTC (GFP+ spike)- and the indicated constructs (GFP+Ametrine+)-transduced OT-I cells were mixed at a 1:1 ratio and transferred to C57BL/6 hosts followed by Lm-Ova infection. The normalized cell ratio was calculated by dividing the proportions of CX3CR1highKLRG1high cells or CD27highCXCR3high cells in GFP+Ametrine+ cells by their proportions in GFP+ spike cells. Data are representative of one (a) or two (b, c) or compiled from two independent experiments (d, e). Data are shown as mean±s.e.m. *P < 0.05, **P < 0.01, ***P < 0.001; NS, not significant; two-tailed unpaired Student’s t-test (d, e), two-sided Wald test and adjusted with Benjamini-Hochberg procedure (a).
Extended Data Fig. 8 Pharmacological or genetic inhibition of cBAF promotes CD8+ Tmem generation and tumour control.
a, Diagram of tumour rechallenge assay used in Fig. 4a. b, Gene set enrichment analysis of Arid1a knockout (KO) upregulated gene sets and Arid1a KO downregulated gene sets in CD8+ T cells activated for 48 h in the presence of BD98 versus vehicle. Arid1a KO upregulated and downregulated genes sets were inferred as differentially expressed genes from RNA-seq data of Arid1a KO versus WT activated CD8+ T cells, with thresholds FDR < 0.05, fold change>2. c, Peak set enrichment analysis of Arid1a KO upregulated and downregulated chromatin accessibility signatures in CD8+ T cells activated for 48 h in the presence of BD98 versus vehicle. Arid1a KO upregulated and downregulated ATAC-seq peaks sets were inferred as differentially accessible regions from ATAC-seq of Arid1a KO versus WT activated CD8+ T cells with thresholds FDR < 0.05, fold change>2, the top 500 down-regulated peaks (ranked by fold change) were used to avoid inaccurate normalization. d, Representative flow cytometry plot of the frequency of CD44+CD62L+ cells among OT-I CD8+ T cells treated with DMSO or BD98 during anti-CD3/CD28 stimulation with IL-2 for 48 h, followed by culturing in IL-2 containing medium for another 2 days. e, Scheme of murine B7-H3-CAR and STOP-CAR constructs. H/TM: hinge/transmembrane domain. f, Flow cytometry analysis of B7-H3 expression in F420 and GL261 cell lines. The percentage of B7-H3-expressing cells is indicated. g, Diagram of CAR-T cell experiment. h, Flow plot (left) and quantification (right) of B7-H3 CAR expression at day 8 with or without BD98 pretreatment (n = 5 biological replicates). Data are representative of at least three independent experiments (d, f, h). Data are shown as mean±s.e.m. NS, not significant; two-tailed unpaired Student’s t-test (h). The P-value was calculated from permutation test, two-sided and adjusted with Benjamini-Hochberg procedure (b,c).
Extended Data Fig. 9 Pharmacological inhibition of cBAF promotes CD8+ Tmem generation and tumour control with lymphodepleting chemotherapy.
a, Diagram of CAR-T cell experiments with lymphodepleting chemotherapy. Murine osteosarcoma cell line F420 was injected subcutaneously into naïve B6 (b–d) or B6 albino mice (e, f). At 7 days after tumour inoculation, cyclophosphamide was injected i.p. (200 mg/kg), and CAR-T cells were transferred 2 days after cyclophosphamide treatment. b, Tumour growth and survival curves of F420 tumour-bearing mice treated with B7-H3 CAR-T cells pre-treated with or without BD98 during the first 48 h of T cell activation (n = 5 mice per group). STOP CAR-T: a control CAR containing only the scFv fragment, as a negative control for CAR-T. c, Flow cytometry plots (left) and quantification (right) of intratumoral CD45.1+CD45.2- donor-derived CAR-T cells in F420 tumour bearing mice at day 37 after tumour challenge (day 28 after adoptive transfer of CAR-T cells) (n = 5 mice). d, Quantification of GZMB, TNFα, IFNγ and B7-H3 CAR expression levels in intratumoral CAR-T cells (n = 5 mice). e, f, Representative bioluminescence images (e) and quantification (f) for CAR-T cells expansion in vivo. The CAR-T cells expressing luciferase were generated from naïve CD8+ T cells isolated from the spleens of CAG-luc-eGFP L2G85 transgenic mice and transferred 2 days after cyclophosphamide injection. Data are representative of one (e, f) or at least two independent experiments (b–d). Data are shown as mean±s.e.m. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.001; two-tailed unpaired Student’s t-test (c, d), two-way ANOVA (b, f); and log-rank (Mantel-Cox) test was performed to compare survival curves (b).
Extended Data Fig. 10 A putative Arid1a inhibitor promotes human CD8+ TCM and TSCM formation following activation.
a, b, Flow cytometry plot of human TCM (CD45RA−CCR7+), TEM (CD45RA−CCR7−) and TSCM (CD45RA+CCR7+CD27+CD95+) populations. Human naïve CD8+ T cells from healthy donors were enriched and stimulated with anti-CD3/CD28 for 2 days and culturing in IL-15 (a) or IL-2 (b) containing medium. BD98 was added at indicated time points, and the cells were assessed at day 8. c, Quantification of the percentages of TCM, TEM and TSCM cells in (b) (n = 6 biological replicates). d, Representative flow cytometry plot of total human CD8+ T cells (upper) in the spleen of NSG mice at day 30 after adoptive transfer, and percentage of TCM-like (CD45RA-CD62L+) cells (lower) in total human CD8+ T cells (n = 12 mice per group). Data are representative of two (a, b, d) or compiled from two (c) independent experiments. Data are shown as mean±s.e.m. *P < 0.05, **P < 0.01, ***P < 0.001; one-way ANOVA(c).
About this article
Cite this article
Guo, A., Huang, H., Zhu, Z. et al. cBAF complex components and MYC cooperate early in CD8+ T cell fate. Nature 607, 135–141 (2022). https://doi.org/10.1038/s41586-022-04849-0