EP4665363A1 - Compositions and methods of preventing t cell exhaustion - Google Patents

Compositions and methods of preventing t cell exhaustion

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Publication number
EP4665363A1
EP4665363A1 EP24757829.7A EP24757829A EP4665363A1 EP 4665363 A1 EP4665363 A1 EP 4665363A1 EP 24757829 A EP24757829 A EP 24757829A EP 4665363 A1 EP4665363 A1 EP 4665363A1
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EP
European Patent Office
Prior art keywords
cell
cells
snf
swi
panel
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
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EP24757829.7A
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German (de)
French (fr)
Inventor
Cigall Kadoch
Iannis Aifantis
Elena BATTISTELLO
Kimberlee HIXON
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Dana Farber Cancer Institute Inc
New York University NYU
Original Assignee
Dana Farber Cancer Institute Inc
New York University NYU
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Application filed by Dana Farber Cancer Institute Inc, New York University NYU filed Critical Dana Farber Cancer Institute Inc
Publication of EP4665363A1 publication Critical patent/EP4665363A1/en
Pending legal-status Critical Current

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    • A61P35/00—Antineoplastic agents
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    • A61K35/00—Medicinal preparations containing materials or reaction products thereof with undetermined constitution
    • A61K35/12—Materials from mammals; Compositions comprising non-specified tissues or cells; Compositions comprising non-embryonic stem cells; Genetically modified cells
    • A61K35/14—Blood; Artificial blood
    • A61K35/17—Lymphocytes; B-cells; T-cells; Natural killer cells; Interferon-activated or cytokine-activated lymphocytes
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    • A61K—PREPARATIONS FOR MEDICAL, DENTAL OR TOILETRY PURPOSES
    • A61K40/00—Cellular immunotherapy
    • A61K40/10—Cellular immunotherapy characterised by the cell type used
    • A61K40/11—T-cells, e.g. tumour infiltrating lymphocytes [TIL] or regulatory T [Treg] cells; Lymphokine-activated killer [LAK] cells
    • A—HUMAN NECESSITIES
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    • A61K40/00—Cellular immunotherapy
    • A61K40/30—Cellular immunotherapy characterised by the recombinant expression of specific molecules in the cells of the immune system
    • A61K40/31—Chimeric antigen receptors [CAR]
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61K—PREPARATIONS FOR MEDICAL, DENTAL OR TOILETRY PURPOSES
    • A61K40/00—Cellular immunotherapy
    • A61K40/40—Cellular immunotherapy characterised by antigens that are targeted or presented by cells of the immune system
    • A61K40/41—Vertebrate antigens
    • A61K40/42—Cancer antigens
    • A61K40/4202—Receptors, cell surface antigens or cell surface determinants
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    • C07K14/705—Receptors; Cell surface antigens; Cell surface determinants
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    • C07K16/28—Immunoglobulins [IG], e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants
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    • C12N15/09—Recombinant DNA-technology
    • C12N15/11—DNA or RNA fragments; Modified forms thereof; Non-coding nucleic acids having a biological activity
    • C12N15/113—Non-coding nucleic acids modulating the expression of genes, e.g. antisense oligonucleotides; Antisense DNA or RNA; Triplex- forming oligonucleotides; Catalytic nucleic acids, e.g. ribozymes; Nucleic acids used in co-suppression or gene silencing
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    • C12N15/1137—Non-coding nucleic acids modulating the expression of genes, e.g. antisense oligonucleotides; Antisense DNA or RNA; Triplex- forming oligonucleotides; Catalytic nucleic acids, e.g. ribozymes; Nucleic acids used in co-suppression or gene silencing against enzymes
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    • A61K39/00—Medicinal preparations containing antigens or antibodies
    • A61K2039/505—Medicinal preparations containing antigens or antibodies comprising antibodies
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61K—PREPARATIONS FOR MEDICAL, DENTAL OR TOILETRY PURPOSES
    • A61K2239/00—Indexing codes associated with cellular immunotherapy of group A61K40/00
    • A61K2239/10—Indexing codes associated with cellular immunotherapy of group A61K40/00 characterized by the structure of the chimeric antigen receptor [CAR]
    • A61K2239/11—Antigen recognition domain
    • A61K2239/13—Antibody-based
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
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    • C12N2310/00—Structure or type of the nucleic acid
    • C12N2310/10—Type of nucleic acid
    • C12N2310/20—Type of nucleic acid involving clustered regularly interspaced short palindromic repeats [CRISPR]
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    • C12N9/00—Enzymes; Proenzymes; Compositions thereof; Processes for preparing, activating, inhibiting, separating or purifying enzymes
    • C12N9/14—Hydrolases (3)
    • C12N9/16—Hydrolases (3) acting on ester bonds (3.1)
    • C12N9/22—Ribonucleases [RNase]; Deoxyribonucleases [DNase]
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    • C12Y—ENZYMES
    • C12Y306/00—Hydrolases acting on acid anhydrides (3.6)
    • C12Y306/04—Hydrolases acting on acid anhydrides (3.6) acting on acid anhydrides; involved in cellular and subcellular movement (3.6.4)

Definitions

  • T cell exhaustion a dysfunctional state in which T cells exhibit poor effector function, reduced proliferative capacity, sustained expression of inhibitory receptors, and altered cytokine production.
  • CAR chimeric antigen receptor
  • T cell exhaustion has formed the basis for numerous studies in the context of both chimeric antigen receptor (CAR)-T cell generation and checkpoint blockade efficacy.
  • CAR chimeric antigen receptor
  • the molecular mechanisms governing T cell activation and exhaustion as well as the factors directing the expression of key state-specific biomarkers remain poorly understood, representing a major barrier to progress. Indeed, understanding such mechanisms bears significant impact on the potential for therapeutic accentuation of CAR-T cell treatments, tumor immunotherapy, and responses against infection.
  • the method comprises treating T cells with a SWI/SNF complex modulator.
  • treating comprises incubating a population of T cells with the modulator.
  • the modulator comprises an inhibitor or a degrader.
  • the modulator comprises a chromatin modifying agent.
  • the modulator comprises a modulator of a cBAF subunit.
  • the modulator comprises ARID1A, ARID1B, DPF2, DPF3, BCL11A, BCL11B, or any combination thereof.
  • the modulator comprises an ATPase modulator.
  • the modulator comprises a SWI/SNF ATPase modulator.
  • the SWI/SNF ATPase comprises SMARCA2, SMARCA4, or both.
  • the SWI/SNF complex comprises canonical BAF (cBAF), polybromo-associated BAF (PBAF), or non-canonical BAF (ncBAF).
  • the SWI/SNF complex modulator comprises a degrader directed to the SWI/SNF complex, a nucleic acid molecule targeting the SWI/SNF complex, a compound or prodrug thereof that binds to the SWI/SNF complex, or a pharmaceutically acceptable salt or ester of said compound or prodrug.
  • the degrader is directed to cBAF
  • the nucleic acid is targeted to cBAF
  • the compound or prodrug binds to cBAF.
  • T cell exhaustion is indicated by decreased proliferation, increased expression of immune checkpoint molecules, decreased cytokine production, increased expression and/or protein levels of transcription factors, or any combination thereof.
  • the transcription factors comprise HNF1B, TOX, NFATC1, IRF4, BATF, MYB NR4A1/2, SOX4, PRDM1, or any combination thereof.
  • the modulator targets SMARCA4, ARID1A, SS18, PBRM1, H3K27Ac, or any combination thereof.
  • the nucleic acid molecule comprises a siRNA, miRNA, shRNA, antisense RNA, guide RNA (gRNA), single guide RNA (sgRNA), modified forms thereof, or combination thereof.
  • the compound comprises a structure according to: DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 Formula I, or a derivative or analog thereof.
  • the compound comprises: Cl DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 or a [0020]
  • the T cell is CD4+, CD8+, CD3+ panT cells, or any combination thereof.
  • the T cell comprises a chimeric antigen receptor (CAR) T cell.
  • the CAR T cell comprises a CD19-CAR-T cell.
  • the method comprises an in vitro, ex vivo, or in vivo method.
  • Aspects of the invention are further drawn to methods of modulating T cell activation.
  • the method comprises treating T cells with a SWI/SNF complex modulator described herein.
  • treating can comprise incubating a population of T cells with the modulator.
  • T cell activation is indicated by increased proliferation, increased cytokine production, increased expression and/or protein levels of transcription factors, or any combination thereof.
  • transcription factors comprise NFAT, NFkB, AP-1, GATA3, t-BET, AP-1, BATF, or any combination thereof.
  • T cell exhaustion is indicated by decreased proliferation, increased expression of immune checkpoint molecules, decreased cytokine production, increased expression and/or protein levels of transcription factors, or any combination thereof.
  • transcription factors comprise HNF1B, TOX, NFATC1, IRF4, BATF, MYB NR4A1/2, SOX4, PRDM1, or any combination thereof.
  • aspects of the invention are further drawn to methods of treating a subject afflicted with a disease or disorder exacerbated by T cell exhaustion.
  • the method comprises administering to the subject a T cell described herein.
  • aspects of the invention are drawn towards a cellular therapy comprising the T cell described herein and a pharmaceutically acceptable carrier, excipient, or diluent.
  • aspects of the invention are drawn towards a kit comprising the T cell described herein or the cellular therapy described herein.
  • aspects of the invention are drawn towards methods of preventing T cell exhaustion in a subject, the method comprising administering to the subject a therapeutically effective amount of a SWI/SNF complex modulator.
  • the subject is afflicted with a disease or disorder exacerbated by T cell exhaustion.
  • the disease or disorder comprises a cancer or an infection.
  • aspects of the invention are drawn towards methods of improving T cell expansion in a subject, the method comprising treating the T cells with an effective amount of a SWI/SNF complex modulator.
  • the method further comprises obtaining T cells isolated from a subject prior to the treating step.
  • the method further comprises treating the T cells with the modulator.
  • the method further comprises administering the treated T cells to the subject.
  • aspects of the invention are further drawn to methods of treating a subject afflicted with a disease or disorder exacerbated by T cell exhaustion.
  • the method comprises administering to the subject a therapeutically effective amount of a SWI/SNF complex modulator.
  • the modulator prevents T cell exhaustion.
  • FIG.1 shows stepwise changes in mSWI/SNF complex targeting and chromatin accessibility during CD8 + T cell activation and exhaustion.
  • Panel A provides a schematic for CD3/CD28 bead-based stimulation of human CD8 + T cells.
  • Panel B provides FACS- based profiling of PD1 and TIM3 markers indicating putative na ⁇ ve/memory, activated, and exhausted T cell populations.
  • Panel C provides principal component analyses (PCA) for mSWI/SNF subunit and H3K27Ac histone mark Cut&Tag and ATAC-seq profiles across time course.
  • PCA principal component analyses
  • Panel D provides K-means clustering for SMARCA4, SS18, H3K37Ac, and ATAC-seq performed over merged SMARCA4, SS18, H3K27ac and ATAC-seq peaks; heatmap intensity depicts quantile-normalized Log2-transformed RPKM values that are transformed into Z-scores.
  • Panel E provides Venn diagrams showing overlap between SMARCA4/SS18 merged, H3K27Ac C&T peaks with ATAC-seq peaks across time points shown.
  • FIG.2 shows state-specific transcription factor motif enrichment of mSWI/SNF complex occupancy and activity during T cell activation and exhaustion.
  • Panel A shows fractional motif enrichment in clusters C1-C9 (relative to sites).
  • Panel B provides LOLA enrichment of 15 selected transcription factors across C2-C9.
  • Panel C provides differential motif accessibility between time points indicated (top 40 coefficients of logistic regression models).
  • Panel D shows PCA performed on RNA-seq datasets from T cells isolated from 2 independent donors at each time point.
  • Panel E provides a Z-scored heatmap reflecting the top 25% most variable genes across the activation/exhaustion time course, partitioned into 8 groups by K-means clustering with select genes labeled.
  • Panel F provides plots representing state (cluster(s)-specific) TF fractional motif enrichment (y-axis) and gene expression (x- DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 axis).
  • Panel G provides representative SMARCA4, SS18, H3K27ac C&T and ATAC-seq tracks over the IFNG, CXCL13 and ENTPD1 loci.
  • FIG.3 shows exhaustion-associated gene expression and chromatin targeting is partially mediated by the HNF1B transcription factor.
  • Panel A provides pie charts representing fractions of top 10% differentially expressed genes near sites within clusters indicated.
  • Panel B provides lollipop plots representing the gene expression (LogCPM) of key marker genes for na ⁇ ve, memory, activation and exhaustion states throughout the activation/exhaustion time course with mSWI/SNF-bound genes indicated.
  • Panel C shows enrichment of C6-associated genes across exhaustion signatures from published scRNA-seq datasets.
  • Panel D provides UMAP projections of 12643 CD8 + T cells from basal cell carcinoma (BCC) tumor biopsies, clustered by phenotype (left) or colored by the enrichment of HNF1B motifs assessed by ChromVar (right).
  • Panel E provides UMAP projection of 13613 CD8 + T cells from clear cell renal cell carcinoma (ccRCC) tumor biopsies, clustered by phenotype (left) or colored by the enrichment of HNF1B motifs assessed by ChromVar (right).
  • Panel F shows enrichment of HNF1B (CUT&TAG performed on Day9-Ch T cells) across clusters.
  • Panel G provides representative tracks over the ENTPD1 locus.
  • Panel H shows motif enrichment over HNF1B target sites in (top) Cluster 6 HNF1B target sites and (bottom) HNF1B target sites.
  • Panel I provides a Western blot for HNF1B and beta-actin performed on total protein isolated from Day9-Ch sgCTRL and sgHNF1B T cells.
  • Panel J provides PD1 and TIM3 immunoprofiling on sgCTRL and sgHNF1B T cells in the Day9-Ch condition.
  • Panel K provides a volcano plot depicting differential gene expression (RNA-seq) in sgCTRL and sgHNF1B T cells.
  • Panel L shows metascape analysis performed over (top) C6 sites with predicted HNF1B binding (>2 motifs) and (bottom) C6 sites with CUT&TAG HNF1B binding, BAF complex occupancy and accessibility.
  • FIG.4 shows chromatin-focused CRISPR/Cas9 screens identify cBAF components as regulators of T cell exhaustion.
  • Panel A provides a schematic for CD8 + PD1 + /TIM3 + T cell screening using a custom sgRNA library of chromatin regulators.
  • Panel D provides FACS plots depicting PD1 + /TIM3 + T cell populations in control and mSWI/SNF subunit gene KO conditions.
  • Panel E provides a bar graph depicting RFP + cells (% cells of Day 3 value) for control, pan-mSWI/SNF, cBAF and PBAF genes.
  • Panel F DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 provides a bar graph depicting RFP+ cells (% cells of Day 3 value) for chronic (+B16+OVA) and transient (+B16) stimulation of OT-1 T cells in each sgRNA condition.
  • Panel G provides FACS plots depicting PD1 + /TIM3 + T cell populations in control and sgSRMARCA4 KO conditions in human CD8 + T cells.
  • Panel H provides a bar graph depicting cell proliferation of human sgCTRL or sgSMARCA4 CD8 + T cells.
  • FIG.5 shows pharmacologic disruption of mSWI/SNF complexes attenuates human T cell exhaustion.
  • Panel A provides a schematic for small molecule inhibitor and degrader experiments with compounds added at day 3 and refreshed (with stimulation) every 3 days.
  • Panel B provides FACS plots depicting PD1/TIM3 populations in CD8+ T cells at Day 9 treated with 50nm and 100nM of SMARCA4/2 degraders and inhibitors.
  • Panel C provides a bar graph depicting % of CD8+ T cells in PD1-/TIM3-, PD1 + TIM3-, and PD1 + TIM3 + populations in DMSO, ACBI1, and AU-15330 conditions. Error bars represent mean ⁇ SEM of 3 or 4 independent CD8 + T cell donors. Statistical analysis was performed using an unpaired T test. (Right) Bar graph depicting % of CD8 + T cells in PD1-/TIM3-, PD1+TIM3-, and PD1 + TIM3 + populations in DMSO, CMP14 and FHT-1015 conditions. Error bars represent mean ⁇ SEM of 3 independent CD8 + T cell donors. Statistical analysis was performed using an unpaired T test.
  • Panel A provides principal component analyses (PCA) of ATAC-seq profiles of Control (CHR), and ACBI1, AU-15330, CMP14 or FHT-1015-treated human CD8 + T cells (100nM), at Day9.
  • CTRL-1 and CTRL-2 are the controls for the ACBI1/AU-15330 and CMP14/FHT-1015 experiments, respectively.
  • Panel B provides a Venn diagram showing the overlap in sites with decreased accessibility (LogFC ⁇ -1) upon treatment with ACBI1, AU-15330, CMP14 or FHT-1015 (100nM).
  • Panel C shows top 40 coefficients of logistic regression models fitting motif counts across sites to changes in accessibility for indicated comparisons.
  • Panel D provides a heatmap showing the log2 fold-change of chromatin accessibility upon ACBI1, AU-15330, CMP14 or FHT-1015 treatment compared to control in the 9 clusters identified in Figure 1.
  • Panel E shows quantification of chromatin accessibility (quantile-normalized Log2 DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 RPKM) at sites within Clusters 3 & 4 and Cluster 6.
  • CTRL-1 and CTRL-2 are the controls for the ACBI1/AU-15330 and CMP14/FHT-1015 experiments, respectively. P-values were computed using standard t-tests.
  • Panel F provides pie charts representing percentages of down-regulated genes after treatment near Cluster 6 (C6) sites with strong decreases in accessibility (Log2FC ⁇ -1).
  • Panel G provides GSEA analysis of exhaustion and memory signatures derived from scRNAseq datasets in the selected comparisons.
  • Panel H provides representative SMARCA4, SS18, H3K27ac C&T and ATAC-seq tracks over the IFNG, CXCL13 and ENTPD1 loci.
  • FIG.7 shows mSWI/SNF targeting improves T-cell based cancer immunotherapy approaches.
  • Panel A provides FACS plots depicting PD1/TIM3 populations in DMSO, ACBI1, AU-15330, CMP14 and FHT-1015 conditions (100nM), at Day9, for one human CD4 + T cell donor.
  • Panel B provides a FACS plot depicting the profiling of CD39 in human CD4 + T cells treated with DMSO, ACBI1, AU-15330, CMP14 or FHT-1015 (100nM), at Day 9.
  • Panel C provides a bar graph depicting human CD4+ T cell number upon treatment with DMSO, ACBI1, AU-15330, CMP14 or FHT-1015 (100nM). Error bars represent mean ⁇ SEM of 3 technical replicates of one donor.
  • Panel D provides a schematic for CD19-CAR-T cell generation, stimulation and treatments.
  • Panel E provides FACS plots depicting CD19-CAR-T-GFP cells identification and PD1/TIM3 populations, in cells treated with ACBI1 or AU-15330.
  • Panel F provides FACS histograms of LAG-3 and CD39 expression in CAR-T cells treated with DMSO, ACBI1 or AU-15330.
  • Panel G provides bar graphs depicting CAR-T cell number upon treatment with DMSO, ACBI1 or AU-15330 (100nM). Error bars represent mean for each donor.
  • Panel I shows in vivo B16 melanoma tumor growth curves in mice injected with DMSO or FHT-1015-treated CD8+ OT-1 T cells.
  • FIG.8 shows establishment and characterization of human and mouse CD8+ T cell activation and exhaustion using cell culture systems.
  • Panel A shows fold expansion for human CD8+ T cells in the chronic or transient stimulation conditions across the Day 0, 3, 6, and 9 time points. Bar graphs represent mean ⁇ SEM from 3-4 independent CD8+ T cell donors.
  • Panel B provides FACS plots depicting the profiling of CD25, CD45RA and CCR7, CD39, IFN ⁇ , TNF ⁇ and GZM ⁇ across the activation and exhaustion time course.
  • Panel C DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 shows fold expansion for mouse CD8+ T cells in the chronic or transient stimulation conditions across the no stim, and Day 3, 6, and 9 time points. Day 0, 3, 6, and 9 time points. Bar graphs represent mean ⁇ SEM from 3-5 independent mice.
  • Panel D provides FACS- based profiling of PD1 and TIM3 markers indicating putative na ⁇ ve/memory, activated, and exhausted T cell populations in mouse CD8+ T cell studies.
  • FIG.9 shows chromatin occupancy and accessibility profiling of human CD8+ T cells during activation and exhaustion.
  • Panel A provides raw peak counts for SMARCA4, SS18, ARID1A, PBRM1, and H3K27Ac C&T experiments performed across time course, for 2 independent human donors (denoted as D1,D2).
  • Panel B provides Venn diagrams reflecting pairwise comparisons of peak numbers for SS18 mSWI/SNF complex subunit C&T across time points (Donor 1 shown).
  • Panel C shows pairwise correlations between samples for SMARCA4, SS18, ARID1A, PBRM1, and H3K27Ac C&T occupancy levels within merged peaks.
  • Panel D shows principal component analyses (PCA) for ARID1A (cBAF) and PBRM1 (PBAF) Cut&Tag and ATAC-seq profiles throughout the activation/exhaustion time course.
  • PCA principal component analyses
  • Panel E provides peak counts for ATAC-seq experiments performed across time course, for 2 independent human donors.
  • Panel F provides pairwise correlations between samples for ATAC-seq experiments.
  • Panel G shows K-means clustering for ARID1A and PBRM1 peaks as in Figure 1D; Quantile-normalized Log2-Transformed RPKMs are presented in the heatmap as Z-scores.
  • Panel H provides a distance-to-TSS plot for Clusters 1- 9 from Figure 1D.
  • Panel I provides a Venn diagram reflecting overlap between ATAC-seq accessible peaks, mSWI/SNF complexes (SS18/SMARCA4 merged) and H3K27Ac.
  • Panel J provides heatmaps reflecting K-means clustering of quantile-normalized log2-transformed RPKMs from Smarca4, Ss18, H3K27ac, and ATAC-seq merged peaks from mouse CUT&TAG and ATAC-seq experiments.
  • FIG.10 shows mSWI/SNF targeting and accessibility over TF target genes during human T cell activation and exhaustion.
  • Panel A shows fractional motif enrichment in clusters (relative to sites) for select archetype motifs with high occurrence and variability.
  • Panel B provides HOMER motif enrichment analysis across indicated clusters.
  • Panel C shows differential motif accessibility between time points indicated (top 40 coefficients of logistic regression models).
  • Panel E provides a plot representing state (cluster-specific) TF fractional motif enrichment (y-axis) and gene expression (x-axis) at the intermediate activation (C4) state.
  • Panel F provides gene expression levels (logCPMs) of 80 select TF genes with high expression and variability during T-cell activation and exhaustion are shown in the lollipop plot.
  • Panel G provides enrichment (-log10(p-value)) of mSWI/SNF-bound genes at different time points across human tumor exhaustion signatures derived from published scRNAseq datasets.
  • Panel H shows correlations between expression changes for genes in C6 (Cluster 6) and exhaustion signatures for each published study. R correlation values and p values are indicated.
  • Panel I shows HNF1B motif enrichment across cell types in the Satpathy et al. scATAC-seq dataset.
  • Panel J shows HNF1B motif enrichment across cell types in the Kourtis et al.
  • Panel K provides HNF1B gene expression (CPM) in human and mouse T cells across the activation/exhaustion time course.
  • Panel L provides HNF1B CUT&TAG raw peak numbers in Day9-Ch and Day9-Tr conditions.
  • Panel M provides motif enrichment analysis performed on HNF1B CUT&TAG in Day9-Chr condition.
  • Panel N provides T cell proliferation in sgCTRL and sgHNF1B conditions.
  • Panel O provides a Venn diagram reflecting overlap between SMARCA4/SS18 CUT&TAG, HNF1B CUT&TAG and ATAC-seq peaks in the Day9-Ch condition.
  • Panel P provides top 40 coefficients of logistic regression models fitting motif counts across sites to changes in accessibility for selected time point comparisons in mouse T-cells during activation and exhaustion.
  • Panel Q provides archetype motif fractional enrichment for sites of gained accessibility (LogFC > 0,) relative to sites in human and mouse CD8+ T cell settings. Selected motifs are labeled in red.
  • FIG.11 shows contributions of mSWI/SNF (cBAF) complexes to T cell exhaustion in two independent CRISPR-Cas9-based screens in mouse CD8+ T cells.
  • Panel A shows number of mapped reads (right) and Gini index representing the evenness of sgRNA reads (left) for the PD1+TIM3+ CRISPR screen.
  • Panel B provides number of significantly depleted hits (Log2FC ⁇ -1, FDR ⁇ 0.05) within the indicated classed of chromatin writers, erasers or readers.
  • Panel C provides a bar graph indicating the expression levels (RPKM) or ARID1A and ARID1B in mouse and human CD8+ T cells.
  • Panel D provides quantification of the PD1+TIM3+ population in cells infected with sgRNAs targeting the indicated genes, normalized to the sgRNA-negative population in the same culture, at Day9 of chronic stimulation. Different sgRNAs for the same gene are labeled with different shapes. Bar graphs represent mean ⁇ SEM from 2-5 independent biological replicates.
  • Panel E provides quantification of the CD62L+ CD44+ population in cells DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 infected with sgRNAs targeting the indicated genes, normalized to the sgRNA-negative population in the same culture, at Day9 of chronic stimulation. Different sgRNAs for the same gene are labeled with different shapes. Bar graphs represent mean ⁇ SEM from 2-4 independent biological replicates.
  • Panel F shows in vitro killing efficiency of B16-OVA cells by OT-1 T cells transduced with the indicated sgRNAs, at Day9 of chronic stimulation. B16- OVA cells and OT-1 T cells were co-incubated for 48 hours at the indicated Target-to- Effector (T:E) ratios.
  • T:E Target-to- Effector
  • Panel G provides sorting strategy for the TIM3 High vs Low screen using a custom sgRNA library of chromatin regulators.
  • Panel H provides number of mapped reads (right) and Gini index representing the evenness of sgRNA reads (left) for the TIM3 High vs Low CRISPR screen.
  • Panel J provides number of significantly depleted hits (Log2FC ⁇ -1, FDR ⁇ 0.05) within the indicated classed of chromatin writers, erasers or readers in the TIM3 High vs Low CRISPR screen.
  • Panel L provides a schematic for stimulation of mouse OT-1 CD8+ T cells based on co-culture with B16 or B16-OVA cells to profile early activation, transient stimulation, and chronic stimulation/exhaustion states.
  • Panel M provides a fold expansion for mouse OT-1 CD8+ T cells in the chronic or transient stimulation conditions across the Day 3, 5, 5, 9 time points. Bar graphs represent mean ⁇ SEM from 9 independent mice.
  • Panel N provides a FACS-based profiling of PD1, TIM3, CD62L and CD44 at Day9 of transient or chronic stimulation in mouse OT-1 CD8+ T cell studies.
  • Panel O provides a FACS-based profiling of PD1, TIM3, CD62L and CD44 at Day9 of chronic stimulation in control and mSWI/SNF subunit gene KO conditions.
  • Panel P provides a western blot analysis of SMARCA4 levels in sgCTRL or sgSMARCA4 human CD8+ T cells, profiled at Day 9 of the chronic stimulation protocol, compared to actin as loading control.
  • FIG.12 shows evaluation of mSWI/SNF small molecule inhibitors and degraders in human T cells.
  • Panel A provides western blot analysis of SMARCA4 levels in control, ACBI- or AU-15330- treated human CD8+ T cells at the indicated concentrations, profiled at Day 9 of the chronic stimulation protocol, compared to actin as loading control.
  • Panel B provides FACS plots depicting PD1/TIM3 populations in CD8+ T cells from the indicated donors at Day 9 of chronic stimulation, treated with 50nm and 100nM of SMARCA4/2 degraders and inhibitors.
  • Panel C provides FACS plots and associated MFI quantifications of DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 CD39 surface levels in CD8+ T cells from the indicated donors at Day 9 of chronic stimulation, treated with 50nm and 100nM of SMARCA4/2 degraders (top) and inhibitors (bottom).
  • Panel D provides FACS plots depicting CD45RA/CCR7 populations in CD8+ T cells from the indicated donors at Day 9 of chronic stimulation, treated with 50nm and 100nM of SMARCA4/2 degraders and inhibitors.
  • Panel E provides a bar graph depicting % of CD8+ T cells in Na ⁇ ve (N), Effector (E), Effector Memory (EM) and Central Memory (CM) populations based on CD45RA and CCR7 surface levels, in DMSO, ACBI1, and AU- 15330 conditions. Error bars represent mean ⁇ SEM of 2-3 independent CD8+ T cell donors.
  • Panel F provides a bar graph depicting % of CD8+ T cells in Na ⁇ ve (N), Effector (E), Effector Memory (EM) and Central Memory (CM) populations based on CD45RA and CCR7 surface levels, in DMSO, CMP14 and FHT1015 conditions. Error bars represent mean ⁇ SEM of 2-3 independent CD8+ T cell donors.
  • FIG.13 shows mSWI/SNF pharmacologic inhibition attenuates exhaustion of human and mouse T cells.
  • Panel A provides FACS plots depicting IFN ⁇ /TNF ⁇ populations in CD8+ T cells from the indicated donors at Day 9 of chronic stimulation, treated with 50nm and 100nM of SMARCA4/2 degraders and inhibitors.
  • Panel B provides bar graphs depicting the percentage of alive cells at Days 3, 6, 9, 13 and 16 of chronic stimulation, for the indicated donors, treated with 50nm and 100nM of SMARCA4/2 degraders (left) and inhibitors (right). Error bars represent mean ⁇ SEM of three technical replicates.
  • Panel C provides quantification of the percentage of apoptotic cells indicated by AnnexinV staining, at Day 16 of the chronic stimulation protocol, for the indicated donors treated with 50nm and 100nM of SMARCA4/2 degraders.
  • Panel D provides bar graphs depicting cell number upon treatment with ACBI1, AU-15330 or FHT-1015 (10 ⁇ 6 cells/10 ⁇ 6 cells at Day 0), initiated at the indicated time points, in one human CD8+ T cell donor.
  • Panel E provides quantification of the PD1+TIM3+ population in human CD8+ T cells upon treatment with ACBI1, AU- 15330 or FHT-1015, initiated at the indicated time points. Data from one CD8+ T cell donor are represented.
  • Panel F provides FACS plots depicting PD1/TIM3 (right) and IFN ⁇ /TNF ⁇ (left) populations in mouse CD8+ T cells at Day 9 of chronic stimulation, treated with the indicated concentrations of SMARCA4/2 inhibitors.
  • FIG.14 shows chromatin accessibility, gene expression and T cell effector functional profiling in human and mouse T cells treated with mSWI/SNF inhibitors and degraders.
  • Panel D provides principal component analyses (PCA) of RNA-seq profiles of Control (CHR), and ACBI1, AU-15330, CMP14 or FHT-1015-treated human CD8+ T cells (100nM), at Day9.
  • CHR.1 and CHR.2 are the controls for the ACBI1/AU-15330 and CMP14/FHT-1015 experiments, respectively.
  • Panel E provides volcano plots of changes in gene expression upon treatment with the indicated compounds (100nM).
  • Significantly up-regulated and down-regulated genes are colored in red and blue, respectively.
  • Panel F provides a Venn diagram showing the overlap in down-regulated genes (LogFC ⁇ -1) upon treatment with ACBI1, AU-15330, CMP14 or FHT-1015 (100nM).
  • Panel G provides hierarchical-clustered heatmaps of gene expression changes upon treatment with the indicated compounds (100nM). The top 1000 differentially expressed genes are shown.
  • Panel G provides a heatmap depicting gene expression changes in the indicated genes across treatment conditions.
  • Panel H provides gene ontology analysis of the 580 down-regulated genes shared among treatment with ACBI1, AU-15330, CMP14 and FHT-1015.
  • Panel I provides a Z-scored heatmap reflecting the expression of selected genes following mSWI/SNF inhibitor or degrader treatments.
  • Panel J provides representative ATAC-seq tracks of untreated (CTRL) or treated T cells over the IRF1 locus with corresponding RNAseq gene expression levels.
  • Panel K provides top 40 coefficients of logistic regression models fitting motif counts across sites to changes in accessibility upon treatment with CMP14 or FHT-1015 in mouse CD8+ T cells.
  • Panel L provides a heatmap displaying ATAC-Seq log2 fold change values upon treatment with CMP14 or FHT-1015, with clusters from Fig. S3a indicated.
  • Panel M provides a schematic of anti-CD19 CAR-T construct used for CAR-T cell studies.
  • Panel N shows in vitro killing efficiency of B16-OVA cells by OT-1 T cells treated with FHT-1015 (100nM), at Day9 of chronic stimulation.
  • B16-OVA cells and OT-1 T cells were co-incubated for 24 hours (left) or 48 hours (right) at the indicated Target-to-Effector (T:E) ratios. Means ⁇ SEM from 4 technical replicates are shown.
  • ex vivo can refer to outside a living subject.
  • ex vivo cell populations include in vitro cell cultures and biological samples such as fluid or tissue samples from humans or animals. Such samples can be obtained by methods well known in the art. Exemplary biological fluid samples include blood, cerebrospinal fluid, urine, saliva. Exemplary tissue samples include tumors and biopsies thereof. In this context, the compounds can be in numerous applications, both therapeutic and experimental. [0063] Aspects of the invention are drawn to methods of preventing T cell exhaustion.
  • T cell exhaustion can refer to a loss of T cell function, which can occur as a result of an infection (e.g., a chronic infection) or a disease (e.g., cancer). T cell exhaustion is associated with increased expression of PD-1, TIM-3, and LAG-3, apoptosis, and reduced cytokine secretion.
  • an infection e.g., a chronic infection
  • a disease e.g., cancer
  • T cell exhaustion is associated with increased expression of PD-1, TIM-3, and LAG-3, apoptosis, and reduced cytokine secretion.
  • the terms “ameliorate T cell exhaustion,” “inhibit T cell exhaustion,” “reduce T cell exhaustion” and the like refer to a condition of restored functionality of T cells characterized by one or more of the following: decreased expression and/or level of one or more of PD-1, TIM-3, and LAG-3; increased memory cell formation and/or maintenance of memory markers (e.g., CD62L); prevention of apoptosis; increased antigen-induced cytokine (e.g., IL-2) production and/or secretion; enhanced killing capacity; increased recognition of tumor targets with low surface antigen; enhanced proliferation in response to antigen.
  • memory markers e.g., CD62L
  • antigen-induced cytokine e.g., IL-2
  • T cell exhaustion is indicated by decreased proliferation, increased expression of immune checkpoint molecules, decreased cytokine production, increased expression and/or protein levels of transcription factors, or any combination thereof.
  • transcription factors can comprise HNF1B, TOX, NFATC1, IRF4, BATF, MYB NR4A1/2, SOX4, PRDM1, or any combination thereof.
  • Activation can refer to a process whereby a cell transitions from a resting state to an active state. This process can comprise a response to an antigen, migration, and/or a phenotypic or genetic change to a functionally active state.
  • activation can refer to the stepwise process of T cell activation.
  • a T cell can require at least two signals to become fully activated.
  • the first signal can occur after engagement of a TCR by the antigen-MHC complex, and the second signal can occur by engagement of co-stimulatory molecules.
  • Anti-CD3 can mimic the first signal and anti-CD28 can mimic the second signal in vitro.
  • T cell activation is indicated by increased proliferation, increased cytokine production, increased expression and/or protein levels of transcription factors, or any combination thereof.
  • CAR T-cell therapies redirect a patient’s T-cells to kill tumor cells by the exogenous expression of a CAR.
  • a CAR can be a membrane spanning fusion protein that links the antigen recognition domain of an antibody to the intracellular signaling domains of the T-cell receptor and co-receptor.
  • Solid tumors offer unique challenges for CAR-T therapies. Unlike blood cancers, tumor-associated target proteins are overexpressed between the tumor and healthy tissue resulting in on-target/off-tumor T-cell killing of healthy tissues. Furthermore, immune repression in the tumor microenvironment (TME) limits the activation of CAR-T cells towards killing the tumor.
  • TEE tumor microenvironment
  • the cell can then be introduced to a cancer patient in need of a treatment.
  • the cancer patient can have a cancer of any of the types as disclosed herein.
  • the cell e.g., a T cell
  • the cell can be, for instance, a tumor-infiltrating T lymphocyte, a CD4+ T cell, a CD8+ T cell, CD3+ panT cells, or the combination thereof, without limitation.
  • the T cell comprises a chimeric antigen receptor (CAR) T cell.
  • the CAR T cell comprises a CD19-CAR-T cell.
  • T cell exhaustion can occur as a result of an infection.
  • the infection can be a viral infection.
  • Non-limiting examples of viral infections comprise influenza, RSV, parainfluenza, viral pneumonia, viral bronchitis, chicken pox, shingles, and human papillomavirus.
  • the virus can infect a human.
  • the virus cannot infect a human.
  • the virus can infect a human cell.
  • a viral infection can be an “active” infection.
  • An active infection can refer to one in which the virus is replicating in a cell or a subject. Active infections can be characterized by the spread of the virus to other cells, tissues, and/or organs, from the cells, tissues, and/or organs initially infected by the virus.
  • the viral infection can be a “latent” infection.
  • a latent infection can refer to one in which the virus is not actively replicating in the infected host.
  • a “variant” can refer to any virus having one or more mutations as compared to a known virus.
  • a strain is a genetic variant or subtype of a virus. The terms 'strain', 'variant', and 'isolate' can be used interchangeably.
  • a variant has developed a “specific group of mutations” that causes the variant to behave differently than that of the strain it originated from.
  • the viral infection comprises a drug-resistant viral infection.
  • a “drug-resistant viral infection” can refer to viral infections which are resistant to antiviral drugs.
  • the viral infection can be a remdesivir-resistant viral infection.
  • T cell exhaustion can occur as a result of a cancer.
  • cancer or “tumor” or “hyperproliferative disorder” can refer to the presence of cells possessing characteristics typical of cancer-causing cells, such as uncontrolled proliferation, immortality, metastatic potential, rapid growth and proliferation rate, and certain characteristic morphological features. Cancer is associated with uncontrolled cell growth, invasion of such cells to adjacent tissues, and the spread of such cells to other organs of the body by vascular and lymphatic means.
  • Cancer invasion occurs when cancer cells intrude on and cross the normal boundaries of adjacent tissue, which can be measured by assaying cancer cell migration, enzymatic destruction of basement membranes by cancer cells, and the like.
  • a particular stage of cancer is relevant and such stages can include the time period before and/or after angiogenesis, cellular invasion, and/or metastasis.
  • Cancer cells are often in the form of a solid tumor, but such cells can exist alone within an animal, or can be a non-tumorigenic cancer cell, such as a leukemia cell.
  • Cancers include, but are not limited to, B cell cancer, e.g., multiple myeloma, Waldenstrom's macroglobulinemia, the heavy chain diseases, such as, for example, alpha chain disease, gamma chain disease, and mu chain disease, benign mono clonal gammopathy, and immunocytic amyloidosis, melanomas, breast cancer, lung cancer, bronchus cancer, colorectal cancer, prostate cancer, pancreatic cancer, stomach cancer, ovarian cancer, urinary bladder cancer, brain or cancer, esophageal cancer, cervical cancer, uterine or endometrial cancer, cancer of the oral cavity or pharynx, liver cancer, kidney cancer, testicular cancer, biliary tract cancer, small bowel or appendix cancer, salivary gland cancer, thyroid gland cancer, adrenal gland cancer, osteosarcoma, chondrosarcoma, cancer of hematological tissues, and the like.
  • the heavy chain diseases such as, for example, alpha chain disease,
  • cancers applicable to the methods encompassed by the invention include human sarcomas and carcinomas, e.g., fibrosarcoma, myxosarcoma, liposarcoma, chondrosarcoma, osteogenic sarcoma, chordoma, angiosarcoma, endotheliosarcoma, lymphangiosarcoma, DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 lymphangioendotheliosarcoma, synovioma, mesothelioma, Ewing's tumor, leiomyosarcoma, rhabdomyosarcoma, colon carcinoma, colorectal cancer, pancreatic cancer, breast cancer, ovarian cancer, prostate cancer, squamous cell carcinoma, basal cell carcinoma, adenocarcinoma, sweat gland carcinoma, sebaceous gland carcinoma, papillary carcinoma, papillary adeno
  • treat can refer to the management and care of a subject for the purpose of combating a condition, disease or disorder, such as a cancer or an infection, in any manner in which one or more of the symptoms of a disease or disorder are ameliorated or otherwise beneficially altered.
  • one or more of the following effects can result from the administration of a therapy or a combination of therapies as described herein: (i) the reduction or amelioration of the severity of a viral infection and/or a symptom associated therewith; (ii) the reduction in the duration of a viral infection and/or a symptom associated therewith; (iii) the regression of a viral infection and/or a symptom associated therewith; (iv) the reduction of the titer of a virus; (v) the reduction in organ failure associated with a viral infection; (vi) the reduction in hospitalization of a subject; (vii) the reduction in hospitalization length; (viii) the increase in the survival of a subject; (ix) the elimination of a virus infection; (x) the inhibition of the progression of a viral infection and/or a symptom associated therewith; (xi) the prevention of the spread of a virus from a cell, tissue or subject to another cell, tissue or subject; and/or (xii) the enhancement or improvement the
  • therapies and/or “therapy” can refer to any protocol(s), method(s), compositions, formulations, and/or agent(s) that can be used in the prevention, treatment, management, or amelioration of a disease or disorder or a symptom associated therewith.
  • the terms “therapies” and “therapy” can refer to biological therapy, supportive therapy, and/or other therapies useful in treatment, management, prevention, or amelioration of a disease or disorder or a symptom associated therewith known to one of skill in the art.
  • therapeutic agent and “therapeutic agents” can refer to any agent(s) which can be used in the prevention, treatment and/or management of a disease or disorder or a symptom associated therewith.
  • Embodiments as described herein can comprise administering to a subject a therapeutically effective amount of a mammalian SWI/SNF complex inhibitor or degrader.
  • the SWI/SNF complex can refer to an evolutionarily conserved ATP-dependent complex that comprises multiple subunits.
  • the subunits are assembled in to three main types or subcomplexes, termed canonical BAF (cBAF), polybromo-associated BAF (PBAF), and non-canonical BAF (ncBAF).
  • cBAF canonical BAF
  • PBAF polybromo-associated BAF
  • ncBAF non-canonical BAF
  • mSWI/SNF ATPase inhibitors targeted against SMARCA4 and/or SMARCA2 can inhibit three forms of these complexes.
  • the modulator comprises a canonincal BAF (cBAF) inhibitor or degrader.
  • cBAF can refer to at least one type of mammalian SWI/SNF complex. Its nucleosome remodeling activity can be reconstituted with a set of four core subunits (BRG1/SMARCA4, SNF5/SMARCB1, BAF155/SMARCC1, and BAF170/SMARCC2), which have orthologs in the yeast complex.
  • mammalian SWI/SNF contains several subunits not found in the yeast counterpart, which can provide interaction surfaces for chromatin (for example, acetyl-lysine recognition by bromodomains) or transcription factors and thus contribute to the genomic targeting of the complex.
  • a key attribute of mammalian SWI/SNF is the heterogeneity of subunit configurations that can exist in different tissues and even in a single cell type (for example, as BAF, PBAF, neural progenitor BAF (npBAF), neuron BAF (nBAF), embryonic stem cell BAF (esBAF), etc.).
  • the BAF complex described herein refers to one type of mammalian SWI/SNF complexes, which is different from PBAF complexes.
  • the cBAF complex is a mammalian cBAF complex.
  • the cBAF complex is a human cBAF complex.
  • the components of the cBAF complex can include, for example, SMARCC1/2, SMARCD1/2/3, SMARCB1, SMARCE1, ARID1A/B, DPF1/2/3, ACTL6A/B, beta-Actin, BCL7A/B/C, SMARCA2/4, and SS18/L1.
  • the modulator comprises a chromatin modifying agent.
  • a "chromatin modifying agent" can refer to an agent that can modify genomic DNA, in the context of nuclear chromatin.
  • genomic DNA can be modified in a detectable manner.
  • Modulating can refer to regulating or adjusting the degree of activity of a process or the degree of an effect. “Modulating” includes activation, inhibition, degradation, amplification, attenuation, and suppression, for example.
  • modulating the activity of the SWI/SNF complex can refer to altering the level or activity of the SWI/SNF complex, component thereof, or a related downstream effect.
  • the activity level of a BAF complex can be measured using any method known in the art.
  • a “modulator” can refer to an agent that agonizes (activates or enhances) or antagonizes (inhibits or reduces) the function of a biological target.
  • the SWI/SNF complex modulator can comprise an inhibitor or a degrader.
  • An “inhibitor” can refer to any agent which reduces the level and/or activity of a protein or protein complex, such as the SWI/SNF complex.
  • the term “inhibiting” can refer to decrease, limiting, and/or blocking a particular action, function, or interaction.
  • Non-limiting examples of inhibitors include small molecule inhibitors, degraders, antibodies, enzymes, or polynucleotides (e.g., siRNA).
  • a “degrader” can refer to a molecule, such as a compound, that interacts with a protein (e.g., a protein of the SWI/SNF complex) in a way which results in degradation of the protein. For example, binding of the degrader results in at least 5% reduction of the level of the protein, e.g., in a cell or subject.
  • the degrader can comprise a degradation moiety, which can refer to a moiety whose binding results in degradation of a protein.
  • the degradation moiety can bind to a protease or a ubiquitin ligase that metabolizes the protein.
  • small molecule can refer to a molecule that is less than about 1000 molecular weight or less than about 500 molecular weight. In one embodiment, a small molecule is an inhibitor. In another embodiment, a small molecule is a degrader. [0086] “Determining the level of a protein” can refer to the detection of a protein, or an mRNA encoding the protein, by methods known in the art, directly or indirectly. “Directly determining” can refer to performing a process (e.g., performing an assay or test on a sample or “analyzing a sample” as that term is defined herein) to obtain the physical entity or value.
  • a process e.g., performing an assay or test on a sample or “analyzing a sample” as that term is defined herein
  • “Indirectly determining” can refer to receiving the physical entity or value from another party or source (e.g., a third-party laboratory that directly acquired the physical entity or value).
  • methods to measure protein level can include, but are not limited to, western blotting, immunoblotting, enzyme-linked immunosorbent assay (ELISA), radioimmunoassay (RIA), immunoprecipitation, immunofluorescence, surface plasmon resonance, chemiluminescence, fluorescent polarization, phosphorescence, immunohistochemical DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 analysis, matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry, liquid chromatography (LC)-mass spectrometry, microcytometry, microscopy, fluorescence activated cell sorting (FACS), and flow cytometry, as well as assays based on a property of a protein including, but not limited to, enzy
  • “Reducing the level” of the SWI/SNF complex or component thereof can refer to decreasing the level of the complex or component, such as a SWI/SNF ATPase, in a cell or subject.
  • the level of SWI/SNF complex or component thereof can be measured using any method known in the art.
  • “Level” can refer to a level of a protein, or mRNA encoding the protein, as compared to a reference. The reference can be any useful reference, as defined herein.
  • a “decreased level” or an “increased level” of a protein is meant a decrease or increase in protein level, as compared to a reference (e.g., a decrease or an increase by about 5%, about 1 0%, about 15%, about 20%, about 25%, about 30%, about 35%, about 40%, about 45%, about 50%, about 55%, about 60%, about 65%, about 70%, about 75%, about 80%, about 85%, about 90%, about 95%, about 100%, about 150%, about 200%, about 300%, about 400%, about 500%, or more; a decrease or an increase of more than about 10%, about 15%, about 20%, about 50%, about 75%, about 100%, or about 200%, as compared to a reference; a decrease or an increase by less than about 0.01 -fold, about 0.02-fold, about 0.1 -fold, about 0.3-fold, about 0.5-fold, about 0.8-fold, or less; or an increase by more than about 1.2-fold, about 1.4-fold,
  • a level of a protein can be expressed in mass/vol (e.g., g/dL, mg/mL, pg/mL, ng/ml_) or percentage relative to total protein or mRNA in a sample.
  • “Reducing the activity” of the SWI/SNF complex can refer to dereasing the level of an activity related to the SWI/SNF complex, a component thereof, or a related downstream effect.
  • the activity level of the SWI/SNF complex can be measured using any method known in the art.
  • an agent which reduces the activity of the SWI/SNF complex is a small molecule inhibitor.
  • an agent which reduces the activity of the SWI/SNF complex is a small molecule degrader.
  • the modulator comprises an ATPase modulator.
  • An “ATPase modulator” can refer to a molecule which binds to ATPase and inhibits or reduces the ATP- hydrolyzing activity of ATPase.
  • the modulator can comprise a SWI/SNF DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 ATPase inhibitor or degrader.
  • the SWI/SNF ATPase modulator can inhibit SMARCA2 and SMARCA4.
  • SMARCA2 can refer to SWI/SNF related, matrix associated, actin dependent regulator of chromatin, subfamily a, member 2, a member of the SWI/SNF family of proteins and is highly similar to the brahma protein of Drosophila.
  • Members of this family have helicase and ATPase activities and can regulate transcription of certain genes by altering the chromatin structure around those genes.
  • the encoded protein is part of the large ATP- dependent chromatin remodeling complex SNF/SWI, which is required for transcriptional activation of genes normally repressed by chromatin.
  • SMARCA2 is a component of SWI/SNF chromatin remodeling complexes that carry out key enzymatic activities, changing chromatin structure by altering DNA-histone contacts within a nucleosome in an ATP- dependent manner. SMARCA2 binds DNA non-specifically (Euskichen et al. (2012) J Biol Chem 287:30987-30905; Kadoch et al. (2015) Sci Adv 1(5):e1500447). SMARCA2 belongs to the neural progenitors-specific chromatin remodeling complex (npBAF complex) and the neuron-specific chromatin remodeling complex (nBAF complex).
  • npBAF complex neural progenitors-specific chromatin remodeling complex
  • nBAF complex neuron-specific chromatin remodeling complex
  • npBAF neuron-specific complexes
  • the npBAF complex is essential for the self-renewal/proliferative capacity of the multipotent neural stem cells.
  • the nBAF complex along with CREST plays a role regulating the activity of genes essential for dendrite growth.
  • Human SMARCA2 protein has 1590 amino acids and a molecular mass of 181279 Da.
  • the known binding partners of SMARCA2 include, e.g., PHF10/BAF45A, CEBPB, TOPBPl, and CEBPA.
  • SMARCA4 can refer to SWI/SNF related,matrix associated, actin dependent regulator of chromatin, subfamily a, member 4, a member of the SWI/SNF family of proteins and is highly similar to the brahma protein of Drosophila. Members of this family have helicase and ATPase activities and can regulate transcription of certain genes by altering the chromatin structure around those genes. The encoded protein is part of the large ATP- dependent chromatin remodeling complex SNF/SWI, which is required for transcriptional activation of genes normally repressed by chromatin.
  • this protein can bind DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 BRCAl, as well as regulate the expression of the tumorigenic protein CD44. Mutations in this gene cause rhabdoid tumor predisposition syndrome type 2.
  • SMARCA4 is a component of SWI/SNF chromatin remodeling complexes that carry out key enzymatic activities, changing chromatin structure by altering DNA-histone contacts within a nucleosome in an ATP- dependent manner.
  • SMARCA4 is a component of the CREST-BRGl complex, a multiprotein complex that regulates promoter activation by orchestrating a calcium-dependent release of a repressor complex and a recruitment of an activator complex.
  • SMARCA4 belongs to the neural progenitors-specific chromatin remodeling complex (npBAF complex) and the neuron-specific chromatin remodeling complex (nBAF complex).
  • npBAF complex neural progenitors-specific chromatin remodeling complex
  • nBAF complex neuron-specific chromatin remodeling complex
  • npBAF complexes which contain ACTL6A/BAF53A and PHF 10/BAF 45A, are exchanged for homologous alternative ACTL6B/BAF53B and DPF1/BAF45B or DPF3/BAF45C subunits in neuron-specific complexes (nBAF).
  • the npBAF complex is essential for the self-renewal/proliferative capacity of the multipotent neural stem cells.
  • the nBAF complex along with CREST plays a role regulating the activity of genes essential for dendrite growth.
  • SMARCA4/BAF190A promote neural stem cell self-renewal/proliferation by enhancing Notch-dependent proliferative signals, while concurrently making the neural stem cell insensitive to SHH-dependent differentiating cues.
  • SMARCA4 acts as a corepressor of ZEB1 to regulate E-cadherin transcription and is required for induction of epithelial- mesenchymal transition (EMT) by ZEB1.
  • EMT epithelial- mesenchymal transition
  • Human SMARCA4 protein has 1647 amino acids and a molecular mass of 184646 Da.
  • the known binding partners of SMARCA4 include, e.g., PHFl0/ BAF45A, MYOG, IKFZl, ZEB1, NR3Cl, PGR, SMARDl, TOPBPl and ZMIM2/ZIMP7.
  • the catalytic core of the SWI/SNF complex can be one of two closely related ATPases, SMARCA2 (BRM) or SMARCA4 (BRG1).
  • BRM SMARCA2
  • BRG1 SMARCA4
  • SMARCA2 BRG1
  • BRG1 SMARCA4
  • BRG1 targets and can override SMARCA4 (BRG1) - dependent activation of the osteocalcin promoter, due to its interaction with different ARID family members (Flowers et al. (2009), supra).
  • BAF250A or "ARIDlA” refers to AT-rich interactive domain- containing protein IA, a subunit of the SWI/SNF complex, which can be find in BAF but not PBAF complex.
  • BAF250A/ARID1A In humans there are two BAF250 isoforms, BAF250A/ARID1A and BAF250B/ARID1B. They can be E3 ubiquitin ligases that target hi stone H2B (Li et al. (2010) Mal. Cell. Biol.30:1673-1688).
  • ARIDlA is highly expressed in the spleen, thymus, prostate, testes, ovaries, small intestine, colon and peripheral leukocytes.
  • ARID1A is involved in transcriptional activation and repres-sion of select genes by chromatin remodeling. It is also involved in vitamin D-coupled transcription regulation by associating with the WINAC complex, a chromatin-remod-eling complex recruited by vitamin D receptor.
  • ARIDlA belongs to the neural progenitors-specific chromatin remod-eling (npBAF) and the neuron-specific chromatin remodel-ing (nBAF) complexes, which are involved in switching developing neurons from stem/progenitors to post-mitotic chromatin remodeling as they exit the cell cycle and become committed to their adult state.
  • ARID1A also plays key roles in maintaining embryonic stem cell pluripotency and in cardiac development and function (Lei et al. (2012) J. Biol. Chem.287:24255-24262; Gao et al. (2008) Proc. Natl. Acad. Sci. U.S.A.105:6656-6661).
  • Human ARIDlA protein has 2285 amino acids and a molecular mass of 242045 Da, with at least a DNA-binding domain that can specifically bind an AT-rich DNA sequence, recognized by a SWI/SNF complex at the beta-globin locus, and a C-terminus domain for glucocorticoid receptor-depen-dent transcriptional activation.
  • ARID IA has been shown to interact with proteins such as SMARCB1/BAF47 (Kato et al. (2002) J. Biol. Chem.277:5498-505; Wang et al. (1996) EMBO J.15:5370-5382) and SMARCA4/BRG1 (Wang et al. (1996), supra; Zhao et al.
  • BAF250B or "ARIDlB” refers to AT-rich interactive domain- containing protein lB, a subunit of the SWI/SNF complex, which can be find in BAF but not PBAF complex.
  • ARIDlB and ARID IA are alternative and mutually exclusive ARID-subunits of the SWI/SNF com-plex.
  • Germline mutations in ARIDlB are associated with Coffin-Siris syndrome (Tsurusaki et al. (2012) Nat. Genet.44:376-378; Santen et al. (2012) Nat. Genet.
  • Somatic mutations in ARIDlB are associated with several cancer subtypes, indicating that it is a tumor suppressor gene (Shai and Pollack (2013) PLoS ONE 8:e55119; Sausen et al. (2013) Nat. Genet.45:12-17; Shain et al. (2012) Proc. Natl. Acad. Sci. U.S.A. 109:E252-E259; Fujimoto et al. (2012) Nat. Genet.44:760-764).
  • Human ARID IA protein has 2236 amino acids and a molecular mass of 236123 Da, with at least a DNA-binding domain that can specifically bind an AT-rich DNA sequence, recognized by a SWI/SNF complex at the beta-globin locus, and a C-terminus domain for glucocorticoid receptor- dependent transcriptional activa-tion.
  • ARIDlB has been shown to interact with SMARCA4/ BRGl (Hurlstone et al. (2002) Biochem. J.364:255-264; Inoue et al. (2002) J. Biol. Chem. 277:41674-41685 and SMARCA2/BRM (Inoue et al. (2002), supra).
  • the term “therapeutic effect” can refer to a local or systemic effect in animals, particularly mammals, and more particularly humans, caused by a pharmacologically active substance. “Therapeutic effect” can refer to any substance intended for use in the diagnosis, cure, mitigation, treatment or prevention of disease or in the enhancement of desirable physical or mental development and conditions in an animal or human. [0097]
  • the term "therapeutically effective amount” can refer to that amount of an embodiment of the composition or pharmaceutical composition being administered that will relieve to some extent one or more of the symptoms of the disease or condition being treated, and/or that amount that will prevent, to some extent, one or more of the symptoms of the condition or disease that the subject being treated has or is at risk of developing.
  • a therapeutically effective amount can comprise less than about 0.1 mg/kg, about 0.1 mg/kg, about 0.5 mg/kg, about 1.0 mg/kg, about 2.5 mg/kg, about 5 mg/kg, about 7.5 mg/kg, about 10 mg/kg, about 15 mg/kg, about 20 mg/kg, about 25 mg/kg, about 30 mg/kg, about 35 mg/kg, about 40 mg/kg, about 45 mg/kg, about 50 mg/kg, about 55 mg/kg, about 60 mg/kg, about 70 mg/kg, about 80 mg/kg, about 90 mg/kg, about 100 mg/kg, about 120 mg/kg, about 135 mg/kg, about 150 mg/kg, about 175 mg/kg, about 200 mg/kg, about 225 mg/kg, about 250 mg/kg, about 275 mg/kg, about 300 mg/kg, about 325 mg/kg
  • the therapeutically effective amount comprises less than about 0.1 mg, about 0.1 mg, about 0.5 mg, about 1.0 mg, about 2.5 mg, about 5 mg, about 7.5 mg, about 10 mg, about 15 mg, about 20 mg, about 25 mg, about 30 mg, about 35 mg, about 40 mg, about 45 mg, about 50 mg, about 55 mg, about 60 mg, about 70 mg, about 80 mg, about 90 mg, about 100 mg, about 120 mg, about 135 mg, about 150 mg, about 175 mg, about 200 mg, about 225 mg, about 250 mg, about 275 mg, about 300 mg, about 325 mg, about 350 mg, about 375 mg, about 400 mg, about 425 mg, about 450 mg, about 475 mg, about 500 mg, about 525 mg, about 550 mg, about 575 mg, about 600 mg, about 625 mg, about 650 mg, about 675 mg, about 700 mg, about 725 mg, about 750 mg, about 775 mg, about 800 mg, about 825 mg, about 850 mg, about 8
  • a wide variety of subjects will be suitable, e.g., livestock such as cattle, sheep, goats, cows, swine, and the like; poultry such as chickens, ducks, geese, turkeys, and the like; and domesticated animals for example pets such as dogs and cats.
  • livestock such as cattle, sheep, goats, cows, swine, and the like
  • poultry such as chickens, ducks, geese, turkeys, and the like
  • domesticated animals for example pets such as dogs and cats.
  • mammals including rodents (e.g., mice, rats, hamsters), rabbits, primates, and swine such as inbred pigs and the like.
  • rodents e.g., mice, rats, hamsters
  • rabbits primates, and swine
  • primates primates
  • swine such as inbred pigs and the like.
  • living subject can refer to a subject noted herein or another organism that is alive.
  • the term “living subject” can refer to the entire subject or organism and not just a part excised (e.g., a liver or other organ) from the living subject.
  • the SWI/SNF complex inhibitor and/or degrader can comprise an antibody DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 directed to the SWI/SNF complex, a nucleic acid molecule targeting the SWI/SNF complex, a compound or prodrug thereof that binds to the SWI/SNF complex, or a pharmaceutically acceptable salt or ester of said compound or prodrug.
  • a nucleic acid molecule can refer to DNA molecules and RNA molecules.
  • a compound can refer to any chemical entity, pharmaceutical, drug, and the like that can be used to treat or prevent a disease, illness, sickness, or disorder of bodily function (for example, viral infection).
  • the term “compound” as used herein can include but is not limited to peptides, nucleic acids, carbohydrates, natural product extract libraries, organic molecules, such as small organic molecules, inorganic molecules, including but not limited to chemicals, metals, and organometallic molecules.
  • non-limiting examples of a compound comprise: , DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 [00104] acceptable salts.
  • “Pharmaceutically acceptable derivatives” of a compound can include salts, esters, enol ethers, enol esters, acetals, ketals, orthoesters, hemiacetals, hemiketals, acids, bases, solvates, hydrates or prodrugs thereof. Such derivatives can be readily prepared by those of skill in this art using known methods for such derivatization. The compounds produced can be administered to animals or humans without substantial toxic effects as pharmaceutically active compounds or as prodrugs. [00106] In embodiments, the compound can be an antagonist.
  • composition or a “pharmaceutical formulation” can refer to a composition or pharmaceutical composition suitable for administration to a subject, such as a mammal, especially a human and that can refer to the combination of an active agent(s), or ingredient with a pharmaceutically acceptable carrier or excipient, making the composition suitable for diagnostic, therapeutic, or preventive use in vitro, in vivo, or ex vivo.
  • a “pharmaceutical composition” can be sterile and can be free of contaminants that can elicit an undesirable response within the subject (e.g., the compound(s) in the pharmaceutical composition is pharmaceutical grade).
  • compositions can be designed for administration to subjects or patients in need thereof via a number of different routes of administration including oral, intranasal, topical, intravenous, buccal, rectal, parenteral, intraperitoneal, intradermal, intratracheal, intramuscular, subcutaneous, by stent-eluting devices, catheters- eluting devices, intravascular balloons, inhalational and the like.
  • a "pharmaceutically acceptable excipient,” “pharmaceutically acceptable diluent,” “pharmaceutically acceptable carrier,” or “pharmaceutically acceptable adjuvant” can refer to an excipient, diluent, carrier, and/or adjuvant that are useful in preparing a pharmaceutical composition that are safe, non-toxic and neither biologically nor otherwise undesirable, and include an excipient, diluent, carrier, and adjuvant that are acceptable for DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 veterinary use and/or human pharmaceutical use.
  • a pharmaceutically acceptable excipient, diluent, carrier and/or adjuvant can include one and more such excipients, diluents, carriers, and adjuvants.
  • Pharmaceutical composition can also be included, or packaged, with other non-toxic compounds, such as pharmaceutically acceptable carriers, excipients, diluents, binders and fillers including, but not limited to, glucose, lactose, gum acacia, gelatin, mannitol, xanthan gum, locust bean gum, galactose, oligosaccharides and/or polysaccharides, starch paste, magnesium trisilicate, talc, corn starch, starch fragments, keratin, colloidal silica, potato starch, urea, dextrans, dextrins, and the like.
  • Pharmaceutically acceptable salts can include, but are not limited to, amine salts, such as but not limited to N,N'-dibenzylethylenediamine, chloroprocaine, choline, ammonia, diethanolamine and other hydroxyalkylamines, ethylenediamine, N- methylglucamine, procaine, N-benzylphenethylamine, 1-para-chlorobenzyl-2-pyrrolidin-1'- ylmethylbenzimidazole, diethylamineand other alkylamines, piperazine and tris(hydroxymethyl) aminomethane; alkali metal salts, such as but not limited to lithium, potassium and sodium; alkali earth metal salts, such as but not limited to barium, calcium and magnesium; transition metal salts, such as but not limited to zinc; and other metal salts, such as but not limited to sodium hydrogen phosphate and disodium phosphate; and also including, but not limited to, salts of mineral acids, such as but not limited to hydroch
  • Embodiments of the composition or pharmaceutical composition can be formulated into pressurized acceptable propellants such as dichiorodifluoromethane, propane, nitrogen and the like.
  • Unit dosage forms for oral administration such as syrups, elixirs, and suspensions, can be provided wherein each dosage unit, for example, teaspoonful, tablespoonful, tablet or suppository, contains a predetermined amount of the composition containing one or more compositions.
  • unit dosage forms for injection or intravenous administration can comprise the pharmaceutical composition as a solution in sterile water, normal saline or another pharmaceutically acceptable carrier.
  • the term "administering" can refer to introducing a substance into a subject.
  • the compound can be administered alone, or can be administered as a pharmaceutical composition together with other compounds, excipients, carriers, diluents, fillers, binders, or other vehicles selected based upon the chosen route of administration and standard pharmaceutical practice.
  • Dosages for a given compound are readily determinable by a variety of means.
  • dosages can be determined by standard clinical techniques.
  • in vitro or in vivo assays can be employed to help identify optimal dosage ranges.
  • the precise dose to be employed can also depend on the route of administration and can be decided according to the judgment of the practitioner and each patient's circumstances.
  • multiple doses of the pharmaceutical composition can be administered.
  • the frequency of administration and the duration of administration of the pharmaceutical composition can vary depending on any of a variety of factors, e.g., patient response, severity of the symptoms, and the like.
  • the pharmaceutical composition can be administered in combination with one or more additional active agents.
  • a first agent e.g., a prophylactic or therapeutic agent
  • a second agent e.g., a prophylactic or therapeutic agent
  • Embodiments as described herein further comprises administering one or more additional active agents to a subject together with the SWI/SNF modulator.
  • additional active agents can comprise an anti-viral agent (e.g., remdesivir, molunpiravir, paxlovid, or any combination thereof), a vaccine, an anti-inflammatory agent, anti-cancer agents, (e.g., an immunotherapy, a chemotherapy, a radiotherapy), a pain reliever, a steroid, or any combination thereof.
  • co-administration can refer to the administration of a first active agent and at least one additional active agent to a single subject, and is intended to include treatment regimens in which the compounds and/or agents are administered by the same or different route of administration, in the same or a different dosage form, and at the same or different time.
  • in combination can refer to the use of more than one therapies (e.g., one or more prophylactic and/or therapeutic agents). The use of the term “in combination” does not restrict the order in which therapies are administered to a subject with a disease or disorder, or the route of administration.
  • the term “bodily fluid” can refer to any fluid produced by a biologic entity or subject and includes, amniotic fluid, aqueous humour, vitreous humour, bile, blood, blood serum, breast milk, cerebrospinal fluid, cerumen (earwax), chyle, chyme, endolymph, perilymph, exudates, feces, female ejaculate, gastric acid, gastric juice, lymph, mucus (including nasal drainage and phlegm), pericardial fluid, peritoneal fluid, pleural fluid, pus, rheum, saliva, sebum (skin oil), semen, sputum, synovial fluid, sweat, tears, urine, vaginal secretion, vomit, exhalant (respiratory), and mixtures of one or more thereof.
  • Fragments of the transcribed polynucleotide, the translated polypeptide, or polynucleotide and/or polypeptide modifications can also be regarded as expressed whether they originate from a transcript generated by alternative splicing or a degraded transcript, or from a post-translational processing of the polypeptide, for example, by proteolysis.
  • “Expressed genes” can include those that are transcribed into a polynucleotide as mRNA and then translated into a polypeptide, and also those that are transcribed into RNA but not translated into a polypeptide (for example, transfer and ribosomal RNAs).
  • “Increased expression,” “increased expression level,” “increased levels,” “elevated expression,” “elevated expression levels,” or “elevated levels” can refer to an increased expression or increased levels of a biomarker in a subject or biological sample isolated from a subject relative to a control, such as a subject or subjects who are not suffering from the disease or disorder (for example, a disease or disorder exacerbated by T cell exhaustion) or an internal control (for example, a housekeeping biomarker).
  • “Decreased expression,” “decreased expression level,” “decreased levels,” “reduced expression,” “reduced expression levels,” or “reduced levels” can refer to a decrease expression or decreased levels of a biomarker in a subject or biological sample isolated from a subject relative to a control, such as a subject or subjects who are not suffering from the disease or disorder (for example, a disease or disorder exacerbated by T cell exhaustion) or an internal control (for example, a housekeeping biomarker).
  • “Amplification” can refer to the process of producing multiple copies of a sequence. “Multiple copies” can refer to at least two copies.
  • copies does not necessarily mean perfect sequence complementarity or identity to the template sequence.
  • copies can include nucleotide analogs such as deoxyinosine, intentional sequence alterations (such as sequence alterations introduced through a primer comprising a sequence that is hybridizable, but not complementary, to the template), and/or sequence errors that occur during amplification.
  • primary cells can undergo amplification in order to be tested for the impact of ATPase inhibition.
  • the nucleic acid amplification can include polymerase chain reaction (PCR), reverse-transcription PCR, quantitative PCR, real-time PCR, isothermal amplification, linear amplification, or isothermal linear amplification, quantitative fluorescent PCR (QF-PCR), multiplex fluorescent PCR (MF-PCR), single cell PCR, restriction fragment length polymorphism PCR(PCR-RFLP), PCR-RFLP/RT-PCR-RFLP, hot start PCR, nested PCR, in situ colony PCR, in situ rolling circle amplification (RCA), bridge PCR (bPCR), picotiter PCR, digital PCR, droplet digital PCR, or emulsion PCR (emPCR).
  • PCR polymerase chain reaction
  • QF-PCR quantitative fluorescent PCR
  • MF-PCR multiplex fluorescent PCR
  • PCR-RFLP multiplex fluorescent PCR
  • PCR-RFLP multiplex fluorescent PCR
  • PCR-RFLP multiplex fluorescent PCR
  • hot start PCR hot start PCR
  • LCR oligonucleotide ligase amplification
  • CPT cycling probe technology
  • MIP molecular inversion probe
  • CP-PCR consensus sequence primed polymerase chain reaction
  • AP-PCR arbitrarily primed polymerase chain reaction
  • TMA transcription mediated amplification
  • DOP-PCR transcription mediated amplification
  • MDA multiple-displacement amplification
  • SDA strand displacement amplification
  • NABS A nucleic acid based sequence amplification
  • PCR can be used to amplify specific RNA sequences, specific DNA sequences from total genomic DNA, and cDNA transcribed from total cellular RNA, bacteriophage, or plasmid sequences, etc. See Mullis et al., Cold Spring Harbor Symp. Quant. Biol. 51: 263 (1987) and Erlich, ed., PCR Technology, (Stockton Press, NY, 1989).
  • PCR is one, but not the only, example of a nucleic acid polymerase reaction method for DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 amplifying a nucleic acid test sample, comprising the use of a known nucleic acid (DNA or RNA) as a primer and utilizes a nucleic acid polymerase to amplify or generate a specific piece of nucleic acid or to amplify or generate a specific piece of nucleic acid which is complementary to a nucleic acid.
  • DNA or RNA DNA or RNA
  • multiplex-PCR can refer to a single PCR reaction carried out on nucleic acid obtained from a single source (e.g., an individual) using more than one primer set for the purpose of amplifying two or more DNA sequences in a single reaction.
  • qRT-PCR quantitative real-time polymerase chain reaction
  • This technique has been described in various publications including, for example, Cronin et al., Am. J. Pathol.164 (1): 35-42 (2004) and Ma et al., Cancer Cell 5 : 607-616 (2004).
  • nucleic acid amplification can include digital PCR.
  • digital PCR can include any method, process, and/or protocol, using instruments and/or kits associated with performing such, that can discretely amplify and quantitate a nucleic acid(s) within individual partitions of a sample.
  • the individual partitions for a digital PCR can be generated by a microfluidic process, such as by using a microfluidic device, and/or by a droplet generating process.
  • Droplet digital PCR Generation of individual partitions by a microfluidic process, such as by using a microfluidic device, and/or a droplet generating process to provide a plurality of partitions in the form of droplets and performing nucleic acid amplification thereon has been described in the art as "droplet digital PCR.”
  • the droplets generated for droplet digital PCR can be provided in, for example, a water-in-oil emulsion.
  • nucleic acid amplification includes droplet digital PCR (ddPCRTM) using Bio-Rad's QX100TM or QX200TM Droplet Digital PCR systems, and analysis of nucleic acid amplification products produced by the same, but is not limited thereto.
  • ddPCRTM droplet digital PCR
  • Sequence determination can refer to biochemical methods that can be used to determine the order of nucleotide bases in a nucleic acid.
  • Targeted sequencing can include the ability to detect complex variation, avoiding clonal errors, and analysis that is less computationally burdensome (e.g., de novo sequencing). There are several embodiments of targeted sequencing. DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 [00143]
  • the term “targeted sequencing” can refer to efficient sequencing of a small subset of the genome. In clinical settings, sequencing a subset of the genome not only reduce costs, but also focuses on the relevant regions.
  • kits such as kits comprising compositions as described herein.
  • the kit can comprise therapeutic combination compositions described herein.
  • the kit includes (a) a T cell, such as that described herein, or (b) the cellular therapy, such as that described herein, and optionally (c) informational material.
  • the informational material can be descriptive, instructional, marketing or other material that is drawn to the methods described herein and/or the use of the agents for therapeutic benefit.
  • the kit includes two or more agents.
  • the kit includes a container comprising a SWI/SNF complex modulator, and a second container comprising a second active agent.
  • the kit further comprises a third container comprising a third active agent.
  • the informational material of the kits is not limited in its form.
  • the informational material can include information about production of the compound, molecular weight of the compound, concentration, date of expiration, batch or production site information, and so forth.
  • the informational material comprises methods of administering the therapeutic combination composition, e.g., in a suitable dose, dosage form, or mode of administration (e.g., a dose, dosage form, or mode of administration described herein), to treat a subject who has a nerve disconnectivity disorder).
  • the information can be provided in a variety of formats, include printed text, computer readable material, video recording, or audio recording, or information that provides a link or address to substantive material.
  • the composition in the kit can include other ingredients, such as a solvent or buffer, a stabilizer, or a preservative.
  • the SWI/SNF complex modulator can be provided in any form, e.g., liquid, dried or lyophilized form, or for example, substantially pure and/or sterile.
  • the agents are provided in a liquid solution, the liquid solution is an aqueous solution.
  • reconstitution can be by the addition of a suitable solvent.
  • the solvent e.g., sterile water or buffer, can optionally be provided in the kit.
  • the kit can include one or more containers for the composition or compositions containing the agents.
  • the kit contains separate containers, dividers or compartments for the composition and informational material.
  • the composition can be contained in a bottle, vial, or syringe, and the informational material can be contained in a plastic sleeve or packet.
  • the separate elements of the kit are contained within a single, undivided container.
  • the composition is contained in a bottle, vial or syringe that has attached thereto the informational material in the form of a label.
  • the kit includes a plurality (e.g., a pack) of individual containers, each containing one or more unit dosage forms (e.g., a dosage form described herein) of the agents.
  • the containers can include a combination unit dosage, e.g., in a given ratio.
  • the kit includes a plurality of syringes, ampules, foil packets, blister packs, or medical devices, e.g., each containing a single combination unit dose.
  • the containers of the kits can be airtight, waterproof (e.g., impermeable to changes in moisture or evaporation), and/or light-tight.
  • the kit optionally includes a device suitable for administration of the composition, e.g., a syringe or other suitable delivery device.
  • the device can be provided pre-loaded with one or both of the agents or can be empty, but suitable for loading.
  • T cells undergo dynamic cell morphologic and gene regulatory changes upon acute or sustained exposure to antigen 1-5 .
  • chronic antigen stimulation causes T cells to enter a dysfunctional state known as T cell exhaustion in which T cells exhibit poor effector function, reduced proliferative capacity, sustained expression of inhibitory receptors, and altered cytokine production 6 .
  • T cell exhaustion has formed the basis for numerous studies in the context of both chimeric antigen receptor (CAR)-T cell generation and checkpoint blockade efficacy 7-13 .
  • CAR chimeric antigen receptor
  • TFs critical transcription factors
  • NFAT NFAT
  • NFkB NFkB
  • AP-1 AP-1
  • GATA3 GATA3
  • t-BET T cell receptor
  • TOX T cell receptor
  • NFATC1 NFATC1
  • IRF4 BATF
  • MYB MYB
  • Efforts to target such factors directly are challenged by high-affinity TF-DNA interactions and functional redundancy between multiple TFs, making inhibition or depletion of a single TF often insufficient to generate a desired programmatic response.
  • unbiased genome-scale CRISPR screens have identified components of the mammalian SWI/SNF (mSWI/SNF) family of ATP-dependent chromatin remodeling complexes as potential mediators of specific states, such as regulatory T cell and exhausted states 37,38 .
  • mSWI/SNF mammalian SWI/SNF family of ATP-dependent chromatin remodeling complexes as potential mediators of specific states, such as regulatory T cell and exhausted states 37,38 .
  • Our group and others have shown that a wide range of human TFs interact transiently with mSWI/SNF complexes resulting in their site-specific targeting genome-wide 39-42 .
  • mSWI/SNF complexes are heterogeneous, multi-subunit entities that alter DNA- nucleosome contacts, generating chromatin accessibility and coordinating the timely and appropriate binding of transcriptional machinery required for proper gene expression 43-47 .
  • mSWI/SNF complexes exist in three final form assemblies, termed canonical BAF (cBAF), polybromo-associated BAF (PBAF), and non-canonical BAF (ncBAF), each demarcated by the incorporation of distinct subunits and unique association with chromatin landscape features 43,50,51 .
  • cBAF canonical BAF
  • PBAF polybromo-associated BAF
  • ncBAF non-canonical BAF
  • Cluster 1 (C1) sites contained TSS-proximal targets of varied targeting and accessibility across conditions and cluster 9 (C9) sites encompassed TSS-distal sites of lower accessibility and with highest mSWI/SNF targeting signal prior to and at early stimulation (FIG.1, panel D; FIG.9, panel H).
  • C1 sites contained TSS-proximal targets of varied targeting and accessibility across conditions and cluster 9 (C9) sites encompassed TSS-distal sites of lower accessibility and with highest mSWI/SNF targeting signal prior to and at early stimulation (FIG.1, panel D; FIG.9, panel H).
  • mSWI/SNF complex occupancy, H3K27Ac signal, and accessibility overlapped substantially genome-wide, with mSWI/SNF complex-bound sites representing a fraction of the total accessible sites (FIG.1, panel E; FIG.9, panel I).
  • TF motifs enriched in mSWI/SNF-bound, DNA-accessible sites at the middle to late activation stages included those for ATF3, BCL6, CREB1, JUND and TBX1 (FIG.2, panels A-B).
  • Motifs in the exhaustion-associated C6 included those for MYB/MYBL1, TCF7 (TCF1), which have been implicated CD8 + T cell stemness and/or exhaustion, as well as CUX2, POU5F1 and SOX3/10 TFs, which to date remain less well characterized in the context of T cell activation and differentiation but have been suggested to interact with mSWI/SNF complexes (FIG.2, panels A-B; FIG.10, panel B) 6,16,73-78 .
  • BAF complexes are bound and active over HNF1B TF binding sites genome-wide in exhausted T cells
  • examining the top 10% differentially upregulated genes across activation, intermediate activation, late activation, exhaustion, and memory states we found that 23%, 14%, 29%, 40%, and 24% of upregulated gene loci, respectively, were occupied by mSWI/SNF complexes (FIG.3, panel A; FIG.10, panel F).
  • mSWI/SNF occupancy was present over the greatest of percentage (40%) of loci corresponding to differentially upregulated genes in the exhaustion cell state (FIG.3, panel A), indicating a heightened role for mSWI/SNF complexes in the establishment and maintenance of the exhaustion transcriptional signature.
  • Monitoring the gene expression changes of key mSWI/SNF target sites with high fractional enrichment as well as those genes within regions of increased accessibility revealed several hallmark genes of na ⁇ ve, activated and exhausted T cells (FIG. 3, panel B).
  • Genes known to be expressed in na ⁇ ve T cells had the highest expression at the no stimulation (0hr) time point, while levels of hallmark activation genes such as IFNG, IL2, PDCD1, CXCL13, GZMB, and LAG3 were most elevated at the 3- 72h time points (FIG.3, panel B; FIG.10, panels D,F).
  • key target genes most strongly upregulated in the exhaustion-like state (D6, D9-Ch) and which are used as clinically-relevant biomarkers of T cell dysfunction included TOX, ENTPD1, ITGA2 and TIGIT, bound by mSWI/SNF.
  • HNF1B occupancy (CUT&TAG signal) from Day9-Ch T cells was most enriched over C6 (exhausted) BAF- bound accessible sites (FIG.3, panel F; FIG.10, panel L), exemplified at the ENTPD1 gene locus (FIG.3, panel G).
  • Archetype and non-archetype motif enrichment analyses performed over HNF1B target sites and over HNF1B sites within C6 revealed co-enrichment of other exhaustion-associated TFs such as BATF, NR4A1/2, SOX4, PRDM1 and others (FIG.3, panel H; FIG.10, panel M).
  • sgRNA-mediated knockout of HNF1B in human CD8 + T cells resulted in reduced TIM3 + PD1 + putative exhausted cells coupled with a doubling of activated/progenitor exhausted T cells (PD1 + TIM3-) (FIG.3, panels I-J).
  • HNF1B KO failed to generate a proliferative advantage (FIG.10, panel N).
  • RNA-seq analyses performed on Day9-Ch WT and HNF1B KO T cells revealed substantial downregulation of exhaustion-associated NR4A1-3 genes, and differential expression of cytokine genes such as GLNY (FIG.3, panel K).
  • Chromatin-focused CRISPR/Cas9 screens identify cBAF components regulators of T cell exhaustion [00183]
  • depleted hits included genes encoding the mSWI/SNF complexes (Arid1a, Dpf2, Smarcc1, Smarca4), chromatin regulators involved in histone acetylation (Kat5, Kat8, Ep300, Hdac3), methylation (Kmt2d, Prmt5, Ezh2, Kdm1a, Kdm6a), and other processes, highlighting a range of epigenetic mechanisms playing potential roles in immune checkpoints associated with T cell exhaustion (FIG.4, panel B; FIG.11, panel B).
  • Arid1b the paralog for Arid1a, was moderately depleted, but to a lesser extent given its lower expression and lower stoichiometric abundance in cBAF complexes in mouse T cells (FIG.11, panel C).
  • PBAF- and ncBAF-specific subunits such as Arid2, Pbrm1, and Brd9 were also depleted, but to a more minimal extent.
  • these data highlight unbiasedly the role for the mSWI/SNF complexes, specifically, Arid1a- and Dpf2- containing cBAF complexes, as among the most significant determinants of exhausted-like cell state.
  • pan- mSWI/SNF and cBAF subunit knock-out cells While no significant differences in percent sgRNA-RFP + cells were identified before Day 9, pan- mSWI/SNF and cBAF subunit knock-out cells (but not PBAF or ncBAF KO cells) exhibited sustained proliferation at Day 9, indicating increased T cell persistence (FIG.4, panel E) as well as slight increases in the percentage of cells with a central memory (CM) phenotype (CD44 + CD62L + ) cells (FIG.11, panel E) and a decrease in the killing capacity in the B16- OVA/OT-1 system at increasing Target-Effector (T-E) ratios, confirming a memory-like phenotype (FIG.11, panel F).
  • CM central memory
  • T-E Target-Effector
  • CD8 + T cells from human PBMCs and electroporated the Cas9 ribonucleoprotein, and control (CTRL) or SMARCA4-targeting sgRNAs.
  • CTR Cas9 ribonucleoprotein, and control
  • SMARCA4-targeting sgRNAs Importantly, in the setting of SMARCA4 KO (FIG.11, panel P), we observed a decrease in the percentage of exhausted PD1 + TIM3 + T cells (FIG.4, panel G) as well as increased persistence of human CD8 + T cells over time (FIG.4, panel H).
  • profiling of CD45RA and CCR7 indicated a decrease in the effector T cell pool, and an increase in both Effector Memory (EM) and Central Memory (CM) cells upon treatment with any ATPase-targeting compounds (FIG.12, DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 panels D-F).
  • EM Effector Memory
  • CM Central Memory
  • C6 exhaustion-associated sites exhibited decreases in accessibility of highest significance and magnitude, while C3 and C4 sites, which included sites broadly accessible during activation and exhaustion, decreased with lower fold changes (FIG.6, panels D-E), indicating that mSWI/SNF ATPase inhibition most strongly suppressed the accessibility over genomic regions enriched for exhaustion- associated genes as well as selected activation-associated genes (FIG.6, panel F).
  • mSWI/SNF disruption moderately impacted accessibility (both increases and decreases) over na ⁇ ve/memory-associated sites (C7 and C8), consistent with the fact that these cells gain memory-like features.
  • CAR-T cells are routinely generated from both CD4 + DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 and CD8 + T cells at variable ratios and expanded using beads similar to those used in our in vitro exhaustion experiments 103,104 .
  • CD4 + T cells have been implicated to be longer- lasting relative to CD8 + cells, detected even decades after tumor remission, we sought to understand whether CD4 + T cells displayed similar persistence and anti-exhaustion features as CD8 + T cells in response to mSWI/SNF inhibition 105,106 102 .
  • OT-1 T cells pre-treatment of CD8 + OT-1 T cells with the FHT-1015 SMARCA4/2 ATPase inhibitors resulted in decreased levels of Day9 in vitro cell killing at 24 and 48 hour time points across a range of target:effector ratios relative to control treated T cells (FIG.14, panel N), consistent with results using cBAF subunit genetic depletion experiments.
  • OT-1 T cells pretreated with FHT-1015 significantly attenuated B16-OVA tumor growth in vivo relative to DMSO control-treated cells (FIG.7, panel I).
  • the FHT-1015 compound is an analog of the Phase I compound, FHD-286, currently being evaluated in the setting of human AML, MDS, and uveal melanoma 94 .
  • HNF1B is a heterodimeric TF (heterodimerizes with HNF1A) and was originally identified as a monogenic diabetes gene and characterized for its functions in the development of the pancreas, liver and in controlling insulin production 115 .
  • HNF1B is not expressed in mouse T cells (FIG.10, panel K), which can reconcile why HNF1B was not previously identified in any CRISPR screen, which have been performed in the mouse T cell setting.
  • DOCKET NO: 5031461-000146-WO1 DATE OF FILING February 19, 2024 HNF1B in particular, mice with heterozygous mutations in HNF1B show no phenotype relative to that seen in humans 115 .
  • HNF1B regulates glucose uptake, glucose metabolism and mitochondrial 103,104,116-119 .
  • Chronically stimulated T cells are known to have rewired glucose metabolism, a higher rate of glycolysis and impaired OxPhos 104 .
  • GO analysis of predicted HNF1B directed targets (based on the identification of HNF1B motif in their promoter or regulatory regions) and of loci bound by both mSWI/SNF and HNF1B identified the MAPK signaling pathway as well as metabolic pathways as enriched processes (FIG.3, panel L), pointing toward a connection between HNF1B and T cell metabolism that can be further explored in functional studies to probe this chromatin remodeler-TF axis.
  • PBMCs Human peripheral blood mononuclear cells isolated from 20- to 25- year-old male and female healthy donors were obtained through the New York Blood Center (NYBC). These de-identified human PBMC samples were collected under an IRB-exempt protocol with donors providing written consent for banking and research of their specimens.
  • CD8+ T cells were then purified by two subsequent rounds of isolation: first, T cells were enriched using the Pan T Cell Isolation kit (Miltenyi Biotec, Cat# 130-096-535); then, negative CD8 T cell isolation was performed with the CD8+ T Cell Isolation Kit, human (Miltenyi Biotec, Cat# 130-096-495) or negative CD4 T cell isolation was performed with the CD4+ T Cell Isolation Kit, human (Miltenyi Biotec, Cat# 130-096- 533).
  • CD8 T cell purity was assessed by FACS staining using mouse or human anti-CD3 and anti-CD8 antibodies at 1:100 dilution (PE/Cyanine7 anti-human CD3, BioLegend, # Cat317333; APC/Cyanine7 anti-mouse CD8a, BioLegend, Cat# 100714; FITC anti-human CD3, ThermoFisher Scientific, Cat#11-0038-42; PE/Cy7 anti-human CD8, Biolegend, Cat# 344712).
  • Human CD4+ T cell purity was assessed using the A700 anti- human CD4 antibody, Biolegend, Cat# 317426 at 1:100 dilution.
  • Mouse CD8+ T cell isolation [00216] Mouse CD8+ T cell isolation [00217] Mouse CD8+ T cells were isolated from spleens and lymph nodes of male and female 8-12 weeks old C57BL/6J mice (Jackson strain #000664), C57BL/6- Tg(TcraTcrb)1100Mjb/J (OT-1 mice) (Jackson strain #003831), Gt(ROSA)26Sortm1.1(CAG-cas9*,-EGFP)Fezh/J (Cas9 mice) (Jackson strain #024858). Cas9-OT-1 mice were obtained by breeding OT-1 and Cas9 strains, and both Cas9 homozygous and heterozygous mice were used for experiments.
  • Negative CD8+ T cell isolation was then performed with the CD8a+ T Cell Isolation Kit, mouse (Miltenyi Biotech, Cat #130-104-075), following the manufacturer’s instructions, utilizing an AutoMACS machine.
  • In vitro T cell activation and exhaustion [00219] Mouse or human CD8+ T cells were cultured in RPMI media supplemented with 10% FBS, 1% Pen/Strep, 1X GlutaMAX (Life Technologies Cat# 35050061), 1X Non- essential Amino Acids (Life Technologies Cat# 11140050), 1X Sodium Pyruvate (Thermo Fisher Scientific Cat# MT25000CI) and 10mM 2-Mercaptoethanol (Life Technologies Cat# 21985023).
  • Non-activated cells were maintained in culture for maximum 3 days in presence of 1ng/ ⁇ l mouse or human IL7 (Murine IL-7, Peprotech, Inc., Cat# 217-17-50UG; Recombinant Human IL-7, Peprotech, Inc., Cat# 200-07-50UG), while activated cells were supplemented with 30U/ml mouse or human IL2 (Recombinant Murine IL-2, Peprotech, Inc., Cat# 212-12-50UG; Recombinant Human IL-2, Peprotech, Inc., Cat# 200-02-1MG).
  • RNA-seq RNA-seq
  • ATAC- seq and C&T profiling cells were harvested at 0h, 3h, 24h, 48h, 72h, 6 Days and 9 Days along this protocol.
  • cells were replated at 1M/ml on day 9 in presence of new beads at 1:1 ratio, then split 1:2 on day 10. Beads were removed on day 12 or 13 and cells were replated at 1M/ml in presence of new beads at 1:1 ratio. Cells were then harvested on day 15 or 16.
  • FACS staining For surface FACS staining, cells were harvested, washed in PBS 2% FBS (FACS buffer), incubated in Fc Block Solution (Human TruStain FcXTM, BioLegend Cat# DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 422302) for 5 minutes, then incubated for 30 minutes at 4°C in FACS buffer with antibodies targeting the proteins of interest.
  • cytokine profiling For intracellular cytokine profiling, cells were stimulated with Cell Stimulation Cocktail (Affymetrix, Cat# 00-4970-93) and supplemented with Brefeldin A (eBioscience Brefeldin A Solution, Life Technologies, Cat# 00-4506-51) for 3h at 37°C to block cytokine secretion. Cells were then harvested and stained with Zombie dyes for live/dead cell discrimination (Zombie AquaTM Fixable Viability Kit, BioLegend, Cat# 423101 or Zombie VioletTM Fixable Viability Kit, BioLegend, Cat# 423113), following the manufacturer’s instructions.
  • Annexin staining was performed with APC Annexin V (BioLegend, Cat# 640920). Samples were analyzed using a Fortessa cytometer.
  • Chromatin-focused CRISPR screen [00226] Library design. For designing a chromatin-focused CRISPR library, a list of epigenetic modifiers was first compiled based on literature search 120,121 . Domain-focused sgRNA sequences were then designed using the Sanjana lab software, accessible through http://guides.sanjanalab.org/#/, with the option to target protein domains selected, and expression data and average data from tissues were used to pick and define exons.
  • a target of 6 sgRNAs were generated per gene.60 non-targeting sgRNAs, as well as Pdcd1 and Havcr2 sgRNAs were added as controls. A ‘G’ was added at the 5’ of every sgRNA, if not already present. The following overhangs were then added: DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 AGGCACTTGCTCGTACGACGCGTCTCACACC – (sgRNA 20 nt) – GTTTCGAGACGATGTGGGCCCGGCACCTTAA. The final library consisted of 1928 sgRNAs targeting 310 protein-coding genes. [00227] Library cloning.
  • sgRNA sequences were cloned in the pLKO5.sgRNA.EFS.tRFP plasmid (Addgene, Cat #57823)
  • the plasmid was a gift from Bejamin Ebert. Briefly, plasmid restriction was performed with BsmBI-v2 (NEB, Cat# R0739L) for 2h at 55°C, then the digested plasmid was run on a 1% agarose gel and purified using the QIAquick Gel Extraction Kit (Qiagen, Cat# 28706X4).
  • the sgRNA library was diluted to 1ng/ ⁇ l in H20, then PCR amplified using the Phusion High-Fidelity PCR Kit (Life Technologies, Cat# F553S), with the following primers: Forward primer: AGGCACTTGCTCGTACGACG, Reverse primer: ATGTGGGCCCGGCACCTTAA. Two ng per reaction were used and five total (50 ⁇ l) reactions were performed to ensure the maintenance of library representation. PCR conditions were the following: 30 seconds at 98 °C, then 10 seconds at 98 °C, 30 seconds at 53 °C, 30 seconds at 72 °C, for 24 cycles, then 5 minutes at 72 °C.
  • the PCR product was then run on a 1% agarose gel and purified using the QIAquick Gel Extraction Kit (Qiagen, Cat# 28706X4). Cloning into the library vector was then performed using Golden Gate cloning, with the following protocol: 5 ⁇ g digested vector, 500 ng PCR insert, 5 ⁇ l Anza Esp1 enzyme (Life Technologies, Cat# IVGN0136), 5 ⁇ l T4 DNA ligase (New England Biolabs, Cat# M0202L), 20ul Anza Buffer, 20 ⁇ l 10mM ATP (New England Biolabs, Cat# PO756S), and H20 to 200ul final volume.
  • 5 ⁇ g digested vector 500 ng PCR insert
  • 5 ⁇ l Anza Esp1 enzyme (Life Technologies, Cat# IVGN0136)
  • 5 ⁇ l T4 DNA ligase New England Biolabs, Cat# M0202L
  • 20ul Anza Buffer 20 ⁇ l 10mM ATP (New England Biolab
  • the reaction was incubated for 30 minutes at 37 °C, then 30 minutes at 16 °C for 25 cycles.
  • Samples were incubated with 1 ⁇ l of Plasmid safe ATP-dependent Dnase (Thermo Fisher Scientific, Cat# E3101K) and incubated at 37 °C for 15 minutes.
  • Reaction cleanup was then performed using the MinElute Reaction Cleanup Kit (Qiagen, Cat# 28204), and the elution product was electroporated into MegaX DH10B electro-competent bacteria (Life Technologies, Cat# C640003) using a BioRad Gene Pulser II Electroporation system.
  • bacteria were plated in 4x24cm square LB plates containing Ampicillin and grown at 30°C for ⁇ 20h. The next day, bacteria were harvested from the plates and grown for 2 hours in 500ml liquid LB media with Ampicillin. Plasmid DNA was harvested using the PureLinkTM HiPure Plasmid Filter Maxiprep Kit (Thermo Fisher Scientific, Cat#K21001). Library representation was checked by amplifying 200ng of library using the TaKaRa Ex Taq DNA Polymerase (Takara Bio, Cat# RR001B) for 15 cycles, and sequencing 10 million reads on a MiSeq 2 instrument, followed by alignment and QC using MAGECK.
  • HEK293T cells were plated in five 15 cm dishes (9 million cells each), in DMEM media supplemented with 10% FBS, 1% Pen/Strep and 1X Glutamax (Life Technologies, Cat# 35050061).
  • PEI Polyethylenimine, Linear, Thermo Fisher Scientific, Cat# NC1014320
  • plasmids 15 ⁇ g psPAX2 (Addgene, Cat#12260), 10 ⁇ g pMD2G (Addgene, Cat#12259), and 20 ⁇ g library plasmid.
  • Genomic DNA was purified using the QIAamp DNA Mini Kit (Qiagen, Cat# 51304) and sgRNA sequences were amplified from genomic DNA using the TaKaRa Ex Taq DNA Polymerase (Takara Bio, Cat# RR001B). Five reactions per condition, each containing 1 ⁇ g of genomic DNA, were performed to maintain library representation.
  • P5 primers equimolar mix of: For_01:AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGACGCTCT TCCGATCTCTTGTGGAAAGGACGAAACACC, For_02:AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGACGCTCT TCCGATCTACTTGTGGAAAGGACGAAACACC, For_03:AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGACGCTCT TCCGATCTGACTTGTGGAAAGGACGAAACACC, For_04:AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGACGCTCTCT TCCGATCTCGACTTGTGGAAAGGACGAAACACC, DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 For_05:AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGACGCTCTCTTCCGATCTCGACTTG
  • PCR conditions were the following: 1 minute at 95 °C, then 30 seconds at 95 °C, 30 seconds at 52 °C, 10 minutes at 72 °C, for 22 cycles, then 10 minutes at 72 °C.
  • PCR product purification and size selection were performed using Ampure beads (Thermo Fisher Scientific, Cat# NC9933872), with right selection using beads at 0.4x ratio and left selection with beads at 0.6x ratio. Samples were sequenced at 10 million single-end reads each on a NextSeq500 instrument.
  • sgRNA oligos were phosphorylated and annealed by incubation in T4 PNK (New England Biolabs, Cat# VWR #101228-174) and T4 ligase buffer at 37°C for 30 minutes. Temperature was then gradually decreased (-1°C/minute) until room temperature. Oligos were diluted 1:200 in H20 and 1 ⁇ l of diluted oligos were ligated with 25ng of digested vector for 1h at room temperature with T4 ligase (New England Biolabs, Cat# M0202M).
  • Viral supernatant was collected 48h and 72h after transfection, filtered through a 0.45 ⁇ M filter and used to spin-infect pre-activated mouse CD8+ T cells at 1500g, for 60 minutes at 32°C.
  • RFP% was assessed using Fortessa machine at 3 day intervals post- activation in parallel with the in vitro exhaustion protocol.
  • the SMARCA4-targeting sgRNA sequences were the following: ACUCCAGACCCACCCCUGGG, CCCUAGCCCGGGUCCCUCGC, GUCCUGCUGAGGGCGGCCCU.
  • the HNF1B-targeting sgRNA sequences were the following: AGCCCUCGUCGCCGGACAAG, GGCCGAGCCCGACACCAAGC, CGGGGUCACCAAGGAGGUGC.
  • Cas9-GFP ribonucleoprotein Integrated DNA Technologies, Cat#10008100
  • B16-OVA in vitro exhaustion model [00242] B16-F10 and B16-F10-OVA cell lines used for co-culture mediated T cell exhaustion were a gift of Dr. Weber’s lab.
  • splenocytes were harvested from OT-1/Cas9 mice and cultured at a concentration of 10 million/ml in T cell media in the presence of 1 ⁇ M SIINKEFL peptide (OVA 257-264, Invivogen # vac-sin).
  • CD8+ T cells were purified with the CD8a+ T Cell Isolation Kit, mouse (Miltenyi Biotech, Cat #130-104-075), following the manufacturer’s instructions.
  • T cells were plated on 6-well plates containing B16 or B16-OVA cells, pretreated for 24h with 1ng/ ⁇ l IFNg to promote MHCI expression. T cells were passaged on new B16 or B16-OVA plates, pre-treated with IFNg, every 48 hours.
  • CRISPR KO experiments in this model cells were transduced as previously described following T cell purification, then cultured on B16 or B16-OVA plates and profiled 9 days after activation.
  • Western blots [00244] Western blots were performed as described previously 122 .
  • proteins were isolated in RIPA buffer, quantified and loaded on 4%-12% Bis-Tris polyacrylamide gels (Thermo Fisher Scientific). Proteins were then transferred onto PVDF membranes (Millipore) and probed using the SMARCA4 antibody (Cell Signaling Technology Cat# 49360T, 1:1000 dilution), the anti-HNF1B antibody Proteintech Cat# 12533-1-AP, 1:1000 dilution) or the anti-Actin (Millipore Cat# MAB1501, 1:10000 dilution). Following incubation with horseradish peroxidase-conjugated secondary antibodies (GE Healthcare), chemiluminescence was assessed with ECL (Life Technologies).
  • Killing assays were performed in 96-well plates, by mixing 50000 B16 or B16-OVA cells (Target) and serial dilutions of OT-1 T cells (Effector) at Day9 of the chronic stimulation protocol, in 200 ul of RPMI media supplemented with 10% FBS, 1% Pen/Strep, 1X GlutaMAX (Life Technologies Cat# 35050061), 1X Non-essential Amino Acids (Life Technologies Cat# 11140050), 1X Sodium Pyruvate (Thermo Fisher Scientific Cat# MT25000CI) and 10mM 2-Mercaptoethanol (Life Technologies Cat# 21985023).
  • the single-chain variable fragment was derived from the murine FMC63 anti-human antibody, that has high affinity and specificity for CD19 and it is utilized in clinical trials.
  • the complete CAR construct is driven by an EF1 ⁇ promoter and contains the internal ribosome entry site (IRES)- GFP signal for cell selection.
  • the CAR-T vector was cloned in house in the Perna Lab (Indiana University).
  • peripheral blood was obtained from de- identified healthy human volunteers under IRB-exempt protocol with written consent for banking and research of their specimens given for each donor.
  • PBMCs Peripheral blood mononuclear cells
  • cells were transduced with lentiviruses encoding anti-CD19 CAR and GFP genes, in presence of polybrene. Transduction efficiencies were assessed by FACS and were ranging from 20 to 50%. Then, cells were counted and plated (0.5 million/ml) in the presence of beads, and DMSO or PROTACS, ACBI1 or AU-15330 (100nM). The same process was repeated at 3-4 days intervals. At Day 10, beads were removed and immunophenotype was analyzed by flow-cytometry using the following markers: CCR7, CD45RA, PD1, TIM3, LAG-3, CD39 (vendors and catalogs previously stated in methods).
  • 50.000 to 0.5 million cells were harvested on ice and washed in cold PBS. RNA extraction was then performed using the Rneasy Plus Mini Kit (Qiagen Cat#74136), following the manufacturer’s instructions.
  • Poly-A selection was performed using the the Nebnext Poly(A) mRNA Magnetic Isolation Module (New England Biolabs Cat#E7490) for RNAseq experiments, except the RNAseq upon PROTAC treatment experiment, where NEXTFLEX® Poly(A) Beads 2.0, (Perkin Elmer Cat#NOVA-512991) were used.
  • Library preparation was performed using the Nebnext Ultra II Directional RNA Library Prep Kit (New England Biolabs Cat# E7760), or NEXTFLEX® Rapid Directional RNA-Seq Kit 2.0 (Perkin Elmer Cat#NOVA-5198-01) for PROTAC experiments. For libraries, quality was assessed by Tapestation.
  • ATAC-seq Cells were harvested at 0h, 3h, 24h, 48h, 72h, Day6 and Day9. ATAC-seq experiments were completed and samples were prepared into libraries using the previously described methodology 67,68,123 . Cells (50,000) were collected in media and washed in cold PBS. Cells were spun at 500rcf for 5 minutes to form a pellet and PBS was removed. Cold lysis buffer was added and cells were gently resuspended by pipetting. Resuspended cells were incubated on ice for three minutes.
  • Lysis was quenched by adding wash buffer and mixing by inverting the tube three times. Lysed material was pelleted at 400 rcf for 10 minutes, and supernatant was discarded. The pelleted DNA was resuspended in transposition reaction buffer and the transposition reaction was carried out for 30 minutes at 37°C with gentle shaking at 1,000 rpm on a thermomixer. The resultant tagmented DNA was purified using Qiagen MinElute Reaction clean up kit (Qiagen Cat# 28206) and eluted in dH20. Tagmented DNA libraries were amplified with 7 total cycles using a standard ATAC-seq amplification protocol and custom PCR primers.
  • ATAC-seq libraries were sequenced on the Illumina NextSeq500 with 35 base-pair paired end sequencing parameters and using the NextSeqTM 500/550 High output flow cell kit (Illumina Cat# 20024906).
  • Cut & Tag [00258] The epicypher protocol for Cleavage under targets and tagmentation was used with slight modifications 66 . Concanavalin A (ConA, BioMag®Plus Cat# 86057) beads were activated with bead activation buffer and stored on ice until further use. Cells (100,000) were collected and washed with cold PBS. Cells were spun at 300rcf for 5 minutes at 4°C and PBS supernatant was removed from the cell pellet.
  • Nuclear extraction buffer was added to the tube and the pellet was gently resuspended by pipetting to lyse cells and extract nuclei.
  • the nuclei-conjugated bead complexes were resuspended in antibody binding buffer and add primary antibody rotating on a nutator overnight at 4°C (Added 2.5, 0.5, 0.25, 0.25, 0.67 and 0.25 ug of IgG, kH3K27Ac, Brg1, SS18, ARID1A, and PBRM1 respectively).
  • nuclei-bead complexes were incubated with 0.5 ⁇ g secondary antibody in digitonin 150 buffer for 1 hour at room temperature on the nutator. After secondary antibody incubation, samples were washed with digitonin 150 buffer and resuspended in digitonin 300 buffer supplemented with 2 microliters of CUTANA pAG- Tn5 (Epicycpher Cat#15-1117) added per sample. Samples were incubated with Tn5 for 1 hour at room temperature on the nutator. Digitonin 300 buffer was added two times to remove excess enzyme from samples. Targeted chromatin tagmentation was completed following the epicypher protocol.
  • RNA-seq data analysis output gene count tables from STAR based on alignments to the hg19 reflat annotation were used as input into edgeR v3.12.1 133 to obtain normalized DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 log CPM values and to evaluate differential gene expression.
  • K-means clustering was applied in a semi-unsupervised manor to partition the SMARCA4, SS18, H3K27ac and ATAC-seq data into the 9 groups or clusters, which are exhibited in FIG.1, panel D, followed by transformation into Z-scores across timepoints to highlight the differences within clusters among time points.
  • CUT&TAG datasets from two independent human T cell donors were merged and RPKM values were computed for SMARCA4, SS18, H3K27Ac and IgG samples for each timepoint across the T cell activation and exhaustion time course (described herein).
  • the RPKM values for each mark were log2- transformed and individually subjected to quantile normalization.
  • Quantile-normalized IgG signals were then subtracted from the SMARCA4, SS18, and H3K27Ac quantile-normalized signals. From here, for selected figure panels, quantile-normalized, IgG-subtracted signal values were separately transformed into Z-scores for timepoints.
  • Transcription Factor Motif and Archetype Analyses were carried out by the LOLA v1.12.0 140 and HOMER v4.9 141 software packages, respectively. In addition to using HOMER to analyze motif enrichment, for several motif enrichment analyses conducted in this study, we determined the number of motif occurrences for 286 non-redundant archetype consensus motifs 142 within +/- 250 base pairs of peak centers for each peak within given peak sets. The coordinates of these archetype motifs as well as non-archetype motifs across the entire human and mouse genomes can be downloaded from the following resource https://www.vierstra.org/resources/motif_clustering#downloads.
  • Cluster ‘Y’ Motif ‘X’ Fractional Enrichment [Cluster ‘Y’ Motif ‘X’ Density Difference] / [Total Motif ‘X’ Density] [00286]
  • These archetype motif fraction enrichment values in clusters were also plotted against corresponding TF gene log fold change values for several stepwise comparisons across the T-cell activation and exhaustion time course.
  • scRNAseq and scATACseq datasets and analyses [00291] scRNA-seq. scRNAseq signatures consisted of the marker genes identified in exhausted or memory cells from the several literature sources 81,82,84,85,145 . These gene lists were used as “gene set” inputs into GSEA along with log2 fold change values from edgeR for expressed genes for several given comparisons , and the GseaPreranked tool was run with default settings to measure gene set enrichment 134 . A positive score indicates an enrichment of genes within a given gene set that have increasing expression, while a negative score indicates an enrichment of genes within a given gene set that have decreasing expression.
  • GSEA output normalized enrichment scores or regular enrichment scores were displayed in DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 heatmaps. Negative log base 10 p-values from select the indicated gene sets were displayed in barplots. [00292] scATAC-seq. To assess the TF activity toward SWI/SNF bound regions in tumor infiltrating human CD8+ T cells, we used publicly available scATAC-seq datasets (GSE181062, GSE181064) 22,61 . From the raw data, we used read counts that fall into the peak coordinate defined as SWI/SNF bound regions in this study. We then used the Viestra et. Al.
  • TOX is a critical regulator of tumour-specific T cell differentiation. Nature 571, 270-274. 10.1038/s41586-019-1324-y. [00322] 29.
  • Transcription Factor IRF4 Promotes CD8+ T Cell Exhaustion and Limits the Development of Memory-like T Cells during Chronic Infection. Immunity 47, 1129-1141.e1125. https://doi.org/10.1016/j.immuni.2017.11.021. [00326] 33.
  • Chromatin landscape signals differentially dictate the activities of mSWI/SNF family complexes. Science 373, 306-315. doi:10.1126/science.abf8705. [00344] 51.
  • ARID1A loss impairs enhancer-mediated gene regulation and drives colon cancer in mice. Nature Genetics 49, 296-302.10.1038/ng.3744. [00348] 55.
  • ARID1B is a specific vulnerability in ARID1A-mutant cancers. Nature Medicine 20, 251-254. 10.1038/nm.3480. [00349] 56.
  • ARID1A determines luminal identity and therapeutic response in estrogen-receptor-positive breast cancer. Nature Genetics 52, 198-207.10.1038/s41588-019-0554-0. [00350] 57. Pan, J., McKenzie, Z.M., D’Avino, A.R., Mashtalir, N., Lareau, C.A., St.
  • the transcription factor BATF operates as an essential differentiation checkpoint in early effector CD8+ T cells. Nature Immunology 15, 373-383.10.1038/ni.2834. [00363] 70.
  • Lineage tracking reveals dynamic relationships of T cells in colorectal cancer. Nature 564, 268-272.10.1038/s41586-018-0694- x. [00376] 83.
  • HNF-1 ⁇ Hepatocyte nuclear factor-1 ⁇
  • Trimmomatic a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114-2120. 10.1093/bioinformatics/btu170. [00420] 127. Langmead, B., and Salzberg, S.L. (2012). Fast gapped-read alignment with Bowtie 2. Nature Methods 9, 357-359.10.1038/nmeth.1923. [00421] 128. Picard. (http://broadinstitute.github.io/picard/ or https://github.com/broadinstitute/picard). [00422] 129.
  • CUT&RUNTools a flexible pipeline for CUT&RUN processing and footprint analysis. Genome Biology 20, 192.10.1186/s13059-019-1802-4. [00426] 133. Robinson, M.D., McCarthy, D.J., and Smyth, G.K. (2009). edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26, 139-140.10.1093/bioinformatics/btp616. [00427] 134.

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Abstract

The present invention is directed to methods of preventing T cell exhaustion using a SWI/SNF complex modulator.

Description

DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 COMPOSITIONS AND METHODS OF PREVENTING T CELL EXHAUSTION [0001] This application claims priority to U.S. Provisional Application No.63/446,640, filed on February 17, 2023, the entire contents of each of which are incorporated herein by reference. [0002] All patents, patent applications and publications cited herein are hereby incorporated by reference in their entirety. The disclosures of these publications in their entireties are hereby incorporated by reference into this application in order to more fully describe the state of the art as known to those skilled therein as of the date of the invention described and claimed herein. [0003] This patent disclosure contains material that is subject to copyright protection. The copyright owner has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure as it appears in the U.S. Patent and Trademark Office patent file or records, but otherwise reserves any and all copyright rights. FIELD OF THE INVENTION [0004] This invention is directed to compositions and methods of preventing T cell exhaustion. For example, aspects of the invention are drawn to methods of preventing T cell exhaustion using a SWI/SNF complex modulator. BACKGROUND OF THE INVENTION [0005] T cells undergo dynamic cell morphologic and gene regulatory changes upon acute or sustained exposure to antigen. Importantly, chronic antigen stimulation causes T cells to enter a dysfunctional state known as T cell exhaustion in which T cells exhibit poor effector function, reduced proliferative capacity, sustained expression of inhibitory receptors, and altered cytokine production. As such, targeting T cell exhaustion has formed the basis for numerous studies in the context of both chimeric antigen receptor (CAR)-T cell generation and checkpoint blockade efficacy. However, the molecular mechanisms governing T cell activation and exhaustion as well as the factors directing the expression of key state-specific biomarkers remain poorly understood, representing a major barrier to progress. Indeed, understanding such mechanisms bears significant impact on the potential for therapeutic accentuation of CAR-T cell treatments, tumor immunotherapy, and responses against infection. DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 SUMMARY OF THE INVENTION [0006] Aspects of the invention are directed to methods of preventing T cell exhaustion. In embodiments, the method comprises treating T cells with a SWI/SNF complex modulator. [0007] In embodiments, treating comprises incubating a population of T cells with the modulator. [0008] In embodiments, the modulator comprises an inhibitor or a degrader. [0009] In embodiments, the modulator comprises a chromatin modifying agent. [0010] In embodiments, the modulator comprises a modulator of a cBAF subunit. For example, the modulator comprises ARID1A, ARID1B, DPF2, DPF3, BCL11A, BCL11B, or any combination thereof. [0011] In embodiments, the modulator comprises an ATPase modulator. For example, the modulator comprises a SWI/SNF ATPase modulator. [0012] In embodiments, the SWI/SNF ATPase comprises SMARCA2, SMARCA4, or both. [0013] In embodiments, the SWI/SNF complex comprises canonical BAF (cBAF), polybromo-associated BAF (PBAF), or non-canonical BAF (ncBAF). [0014] In embodiments, the SWI/SNF complex modulator comprises a degrader directed to the SWI/SNF complex, a nucleic acid molecule targeting the SWI/SNF complex, a compound or prodrug thereof that binds to the SWI/SNF complex, or a pharmaceutically acceptable salt or ester of said compound or prodrug. For example, the degrader is directed to cBAF, the nucleic acid is targeted to cBAF, or the compound or prodrug binds to cBAF. [0015] In embodiments, T cell exhaustion is indicated by decreased proliferation, increased expression of immune checkpoint molecules, decreased cytokine production, increased expression and/or protein levels of transcription factors, or any combination thereof. For example, the transcription factors comprise HNF1B, TOX, NFATC1, IRF4, BATF, MYB NR4A1/2, SOX4, PRDM1, or any combination thereof. [0016] In embodiments, the modulator targets SMARCA4, ARID1A, SS18, PBRM1, H3K27Ac, or any combination thereof. [0017] In embodiments, the nucleic acid molecule comprises a siRNA, miRNA, shRNA, antisense RNA, guide RNA (gRNA), single guide RNA (sgRNA), modified forms thereof, or combination thereof. [0018] In embodiments, the compound comprises a structure according to: DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 Formula I, or a derivative or analog thereof. [0019] In embodiments, the compound comprises: Cl DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 or a [0020] In embodiments, the T cell is CD4+, CD8+, CD3+ panT cells, or any combination thereof. [0021] In embodiments, the T cell comprises a chimeric antigen receptor (CAR) T cell. [0022] In embodiments, the CAR T cell comprises a CD19-CAR-T cell. [0023] In embodiments, the method comprises an in vitro, ex vivo, or in vivo method. DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 [0024] Aspects of the invention are further drawn to methods of modulating T cell activation. In embodiments, the method comprises treating T cells with a SWI/SNF complex modulator described herein. For example, treating can comprise incubating a population of T cells with the modulator. [0025] In embodiments, T cell activation is indicated by increased proliferation, increased cytokine production, increased expression and/or protein levels of transcription factors, or any combination thereof. For example, transcription factors comprise NFAT, NFkB, AP-1, GATA3, t-BET, AP-1, BATF, or any combination thereof. [0026] Aspects of the invention are further drawn to a T cell produced by the method described herein, wherein T cell exhaustion is indicated by decreased proliferation, increased expression of immune checkpoint molecules, decreased cytokine production, increased expression and/or protein levels of transcription factors, or any combination thereof. For example, transcription factors comprise HNF1B, TOX, NFATC1, IRF4, BATF, MYB NR4A1/2, SOX4, PRDM1, or any combination thereof. [0027] Aspects of the invention are further drawn to methods of treating a subject afflicted with a disease or disorder exacerbated by T cell exhaustion. In embodiments, the method comprises administering to the subject a T cell described herein. [0028] Still further, aspects of the invention are drawn towards a cellular therapy comprising the T cell described herein and a pharmaceutically acceptable carrier, excipient, or diluent. [0029] Still further, aspects of the invention are drawn towards a kit comprising the T cell described herein or the cellular therapy described herein. [0030] Still further, aspects of the invention are drawn towards methods of preventing T cell exhaustion in a subject, the method comprising administering to the subject a therapeutically effective amount of a SWI/SNF complex modulator. [0031] In embodiments, the subject is afflicted with a disease or disorder exacerbated by T cell exhaustion. For example, the disease or disorder comprises a cancer or an infection. [0032] Still further, aspects of the invention are drawn towards methods of improving T cell expansion in a subject, the method comprising treating the T cells with an effective amount of a SWI/SNF complex modulator. [0033] In embodiments, the method further comprises obtaining T cells isolated from a subject prior to the treating step. [0034] In embodiments, the method further comprises treating the T cells with the modulator. DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 [0035] In embodiments, the method further comprises administering the treated T cells to the subject. [0036] Still further, aspects of the invention are further drawn to methods of treating a subject afflicted with a disease or disorder exacerbated by T cell exhaustion. In embodiments, the method comprises administering to the subject a therapeutically effective amount of a SWI/SNF complex modulator. [0037] In embodiments, the modulator prevents T cell exhaustion. [0038] Other objects and advantages of this invention will become readily apparent from the ensuing description. BRIEF DESCRIPTION OF THE FIGURES [0039] FIG.1 shows stepwise changes in mSWI/SNF complex targeting and chromatin accessibility during CD8+ T cell activation and exhaustion. Panel A provides a schematic for CD3/CD28 bead-based stimulation of human CD8+ T cells. Panel B provides FACS- based profiling of PD1 and TIM3 markers indicating putative naïve/memory, activated, and exhausted T cell populations. Panel C provides principal component analyses (PCA) for mSWI/SNF subunit and H3K27Ac histone mark Cut&Tag and ATAC-seq profiles across time course. Panel D provides K-means clustering for SMARCA4, SS18, H3K37Ac, and ATAC-seq performed over merged SMARCA4, SS18, H3K27ac and ATAC-seq peaks; heatmap intensity depicts quantile-normalized Log2-transformed RPKM values that are transformed into Z-scores. Panel E provides Venn diagrams showing overlap between SMARCA4/SS18 merged, H3K27Ac C&T peaks with ATAC-seq peaks across time points shown. [0040] FIG.2 shows state-specific transcription factor motif enrichment of mSWI/SNF complex occupancy and activity during T cell activation and exhaustion. Panel A shows fractional motif enrichment in clusters C1-C9 (relative to sites). Panel B provides LOLA enrichment of 15 selected transcription factors across C2-C9. Panel C provides differential motif accessibility between time points indicated (top 40 coefficients of logistic regression models). Panel D shows PCA performed on RNA-seq datasets from T cells isolated from 2 independent donors at each time point. Panel E provides a Z-scored heatmap reflecting the top 25% most variable genes across the activation/exhaustion time course, partitioned into 8 groups by K-means clustering with select genes labeled. Panel F provides plots representing state (cluster(s)-specific) TF fractional motif enrichment (y-axis) and gene expression (x- DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 axis). Panel G provides representative SMARCA4, SS18, H3K27ac C&T and ATAC-seq tracks over the IFNG, CXCL13 and ENTPD1 loci. [0041] FIG.3 shows exhaustion-associated gene expression and chromatin targeting is partially mediated by the HNF1B transcription factor. Panel A provides pie charts representing fractions of top 10% differentially expressed genes near sites within clusters indicated. Panel B provides lollipop plots representing the gene expression (LogCPM) of key marker genes for naïve, memory, activation and exhaustion states throughout the activation/exhaustion time course with mSWI/SNF-bound genes indicated. Panel C shows enrichment of C6-associated genes across exhaustion signatures from published scRNA-seq datasets. Panel D provides UMAP projections of 12643 CD8+ T cells from basal cell carcinoma (BCC) tumor biopsies, clustered by phenotype (left) or colored by the enrichment of HNF1B motifs assessed by ChromVar (right). Panel E provides UMAP projection of 13613 CD8+ T cells from clear cell renal cell carcinoma (ccRCC) tumor biopsies, clustered by phenotype (left) or colored by the enrichment of HNF1B motifs assessed by ChromVar (right). Panel F shows enrichment of HNF1B (CUT&TAG performed on Day9-Ch T cells) across clusters. Panel G provides representative tracks over the ENTPD1 locus. Panel H shows motif enrichment over HNF1B target sites in (top) Cluster 6 HNF1B target sites and (bottom) HNF1B target sites. Panel I provides a Western blot for HNF1B and beta-actin performed on total protein isolated from Day9-Ch sgCTRL and sgHNF1B T cells. Panel J provides PD1 and TIM3 immunoprofiling on sgCTRL and sgHNF1B T cells in the Day9-Ch condition. Panel K provides a volcano plot depicting differential gene expression (RNA-seq) in sgCTRL and sgHNF1B T cells. Panel L shows metascape analysis performed over (top) C6 sites with predicted HNF1B binding (>2 motifs) and (bottom) C6 sites with CUT&TAG HNF1B binding, BAF complex occupancy and accessibility. [0042] FIG.4 shows chromatin-focused CRISPR/Cas9 screens identify cBAF components as regulators of T cell exhaustion. Panel A provides a schematic for CD8+ PD1+/TIM3+ T cell screening using a custom sgRNA library of chromatin regulators. Panel B provides a rank plot depicting Log2FC scores (average of n=6 guides) targeting chromatin regulator genes and negative/positive controls. Depleted genes are highlighted in black; positive controls are highlighted in gray; mSWI/SNF complex genes are highlighted in orange. Panel C shows Log2FC values for n=6 independent guides in PD1+TIM3+ cells. Panel D provides FACS plots depicting PD1+/TIM3+ T cell populations in control and mSWI/SNF subunit gene KO conditions. Panel E provides a bar graph depicting RFP+ cells (% cells of Day 3 value) for control, pan-mSWI/SNF, cBAF and PBAF genes. Panel F DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 provides a bar graph depicting RFP+ cells (% cells of Day 3 value) for chronic (+B16+OVA) and transient (+B16) stimulation of OT-1 T cells in each sgRNA condition. Panel G provides FACS plots depicting PD1+/TIM3+ T cell populations in control and sgSRMARCA4 KO conditions in human CD8+ T cells. Panel H provides a bar graph depicting cell proliferation of human sgCTRL or sgSMARCA4 CD8+ T cells. [0043] FIG.5 shows pharmacologic disruption of mSWI/SNF complexes attenuates human T cell exhaustion. Panel A provides a schematic for small molecule inhibitor and degrader experiments with compounds added at day 3 and refreshed (with stimulation) every 3 days. Panel B provides FACS plots depicting PD1/TIM3 populations in CD8+ T cells at Day 9 treated with 50nm and 100nM of SMARCA4/2 degraders and inhibitors. Panel C (Left) provides a bar graph depicting % of CD8+ T cells in PD1-/TIM3-, PD1+TIM3-, and PD1+TIM3+ populations in DMSO, ACBI1, and AU-15330 conditions. Error bars represent mean ± SEM of 3 or 4 independent CD8+ T cell donors. Statistical analysis was performed using an unpaired T test. (Right) Bar graph depicting % of CD8+ T cells in PD1-/TIM3-, PD1+TIM3-, and PD1+TIM3+ populations in DMSO, CMP14 and FHT-1015 conditions. Error bars represent mean ± SEM of 3 independent CD8+ T cell donors. Statistical analysis was performed using an unpaired T test. Panel D (Left) provides bar graphs depicting cell number upon treatment with ACBI1 or AU-15330 across n=3 independent donors (Donors 4,5,6); (Right) Bar graphs depicting cell number (10^6 cells/10^ 6 cells at Day 0) upon treatment with CMP14 or FHT-1015 across n=3 independent donors (Donors 7,8,9). Error bars represent mean ± SEM of 3 technical replicates per donor. *p < 0.05, **p < 0.01, ***p < 0.001. ****p < 0.0001. [0044] FIG.6 shows mSWI/SNF pharmacological disruption alters chromatin accessibility and TFs recruitment at key T cell activation and exhaustion sites. Panel A provides principal component analyses (PCA) of ATAC-seq profiles of Control (CHR), and ACBI1, AU-15330, CMP14 or FHT-1015-treated human CD8+ T cells (100nM), at Day9. CTRL-1 and CTRL-2 are the controls for the ACBI1/AU-15330 and CMP14/FHT-1015 experiments, respectively. Panel B provides a Venn diagram showing the overlap in sites with decreased accessibility (LogFC <-1) upon treatment with ACBI1, AU-15330, CMP14 or FHT-1015 (100nM). Panel C shows top 40 coefficients of logistic regression models fitting motif counts across sites to changes in accessibility for indicated comparisons. Panel D provides a heatmap showing the log2 fold-change of chromatin accessibility upon ACBI1, AU-15330, CMP14 or FHT-1015 treatment compared to control in the 9 clusters identified in Figure 1. Panel E shows quantification of chromatin accessibility (quantile-normalized Log2 DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 RPKM) at sites within Clusters 3 & 4 and Cluster 6. CTRL-1 and CTRL-2 are the controls for the ACBI1/AU-15330 and CMP14/FHT-1015 experiments, respectively. P-values were computed using standard t-tests. Panel F provides pie charts representing percentages of down-regulated genes after treatment near Cluster 6 (C6) sites with strong decreases in accessibility (Log2FC < -1). Panel G provides GSEA analysis of exhaustion and memory signatures derived from scRNAseq datasets in the selected comparisons. Panel H provides representative SMARCA4, SS18, H3K27ac C&T and ATAC-seq tracks over the IFNG, CXCL13 and ENTPD1 loci. [0045] FIG.7 shows mSWI/SNF targeting improves T-cell based cancer immunotherapy approaches. Panel A provides FACS plots depicting PD1/TIM3 populations in DMSO, ACBI1, AU-15330, CMP14 and FHT-1015 conditions (100nM), at Day9, for one human CD4+ T cell donor. Panel B provides a FACS plot depicting the profiling of CD39 in human CD4+ T cells treated with DMSO, ACBI1, AU-15330, CMP14 or FHT-1015 (100nM), at Day 9. Panel C provides a bar graph depicting human CD4+ T cell number upon treatment with DMSO, ACBI1, AU-15330, CMP14 or FHT-1015 (100nM). Error bars represent mean ± SEM of 3 technical replicates of one donor. Panel D provides a schematic for CD19-CAR-T cell generation, stimulation and treatments. Panel E provides FACS plots depicting CD19-CAR-T-GFP cells identification and PD1/TIM3 populations, in cells treated with ACBI1 or AU-15330. Panel F provides FACS histograms of LAG-3 and CD39 expression in CAR-T cells treated with DMSO, ACBI1 or AU-15330. Panel G provides bar graphs depicting CAR-T cell number upon treatment with DMSO, ACBI1 or AU-15330 (100nM). Error bars represent mean for each donor. Panel H provides bar graphs depicting cell number upon treatment with ACBI1, AU-15330, or FHT-1015 (all 100nM) at Day 3 onward or at Day 3 with treatment washout at Day 9, across n=3 independent donors. Panel I shows in vivo B16 melanoma tumor growth curves in mice injected with DMSO or FHT-1015-treated CD8+ OT-1 T cells. P-value for comparison between the two groups means at Day19: p< 0.05. [0046] FIG.8 shows establishment and characterization of human and mouse CD8+ T cell activation and exhaustion using cell culture systems. Panel A shows fold expansion for human CD8+ T cells in the chronic or transient stimulation conditions across the Day 0, 3, 6, and 9 time points. Bar graphs represent mean ± SEM from 3-4 independent CD8+ T cell donors. Panel B provides FACS plots depicting the profiling of CD25, CD45RA and CCR7, CD39, IFN ^, TNF ^ and GZM ^ across the activation and exhaustion time course. Panel C DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 shows fold expansion for mouse CD8+ T cells in the chronic or transient stimulation conditions across the no stim, and Day 3, 6, and 9 time points. Day 0, 3, 6, and 9 time points. Bar graphs represent mean ± SEM from 3-5 independent mice. Panel D provides FACS- based profiling of PD1 and TIM3 markers indicating putative naïve/memory, activated, and exhausted T cell populations in mouse CD8+ T cell studies. [0047] FIG.9 shows chromatin occupancy and accessibility profiling of human CD8+ T cells during activation and exhaustion. Panel A provides raw peak counts for SMARCA4, SS18, ARID1A, PBRM1, and H3K27Ac C&T experiments performed across time course, for 2 independent human donors (denoted as D1,D2). Panel B provides Venn diagrams reflecting pairwise comparisons of peak numbers for SS18 mSWI/SNF complex subunit C&T across time points (Donor 1 shown). Panel C shows pairwise correlations between samples for SMARCA4, SS18, ARID1A, PBRM1, and H3K27Ac C&T occupancy levels within merged peaks. Panel D shows principal component analyses (PCA) for ARID1A (cBAF) and PBRM1 (PBAF) Cut&Tag and ATAC-seq profiles throughout the activation/exhaustion time course. Panel E provides peak counts for ATAC-seq experiments performed across time course, for 2 independent human donors. Panel F provides pairwise correlations between samples for ATAC-seq experiments. Panel G shows K-means clustering for ARID1A and PBRM1 peaks as in Figure 1D; Quantile-normalized Log2-Transformed RPKMs are presented in the heatmap as Z-scores. Panel H provides a distance-to-TSS plot for Clusters 1- 9 from Figure 1D. Panel I provides a Venn diagram reflecting overlap between ATAC-seq accessible peaks, mSWI/SNF complexes (SS18/SMARCA4 merged) and H3K27Ac. Panel J provides heatmaps reflecting K-means clustering of quantile-normalized log2-transformed RPKMs from Smarca4, Ss18, H3K27ac, and ATAC-seq merged peaks from mouse CUT&TAG and ATAC-seq experiments. [0048] FIG.10 shows mSWI/SNF targeting and accessibility over TF target genes during human T cell activation and exhaustion. Panel A shows fractional motif enrichment in clusters (relative to sites) for select archetype motifs with high occurrence and variability. Panel B provides HOMER motif enrichment analysis across indicated clusters. Panel C shows differential motif accessibility between time points indicated (top 40 coefficients of logistic regression models). Panel D provides volcano plots of step-wise changes in gene expression throughout the activation/exhaustion time course. Significantly up-regulated and down-regulated genes (Abs Log2FC > 1, FDR < 0.01) are colored in red and blue, respectively. The top 20 most significantly differentially expressed genes in every comparison are labeled. Differential expression was calculated from n=2 independent human DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 CD8+ T cell donors. Panel E provides a plot representing state (cluster-specific) TF fractional motif enrichment (y-axis) and gene expression (x-axis) at the intermediate activation (C4) state. Panel F provides gene expression levels (logCPMs) of 80 select TF genes with high expression and variability during T-cell activation and exhaustion are shown in the lollipop plot. Panel G provides enrichment (-log10(p-value)) of mSWI/SNF-bound genes at different time points across human tumor exhaustion signatures derived from published scRNAseq datasets. Panel H shows correlations between expression changes for genes in C6 (Cluster 6) and exhaustion signatures for each published study. R correlation values and p values are indicated. Panel I shows HNF1B motif enrichment across cell types in the Satpathy et al. scATAC-seq dataset. Panel J shows HNF1B motif enrichment across cell types in the Kourtis et al. scATAC-seq dataset. Panel K provides HNF1B gene expression (CPM) in human and mouse T cells across the activation/exhaustion time course. Panel L provides HNF1B CUT&TAG raw peak numbers in Day9-Ch and Day9-Tr conditions. Panel M provides motif enrichment analysis performed on HNF1B CUT&TAG in Day9-Chr condition. Panel N provides T cell proliferation in sgCTRL and sgHNF1B conditions. Panel O provides a Venn diagram reflecting overlap between SMARCA4/SS18 CUT&TAG, HNF1B CUT&TAG and ATAC-seq peaks in the Day9-Ch condition. Panel P provides top 40 coefficients of logistic regression models fitting motif counts across sites to changes in accessibility for selected time point comparisons in mouse T-cells during activation and exhaustion. Panel Q provides archetype motif fractional enrichment for sites of gained accessibility (LogFC > 0,) relative to sites in human and mouse CD8+ T cell settings. Selected motifs are labeled in red. [0049] FIG.11 shows contributions of mSWI/SNF (cBAF) complexes to T cell exhaustion in two independent CRISPR-Cas9-based screens in mouse CD8+ T cells. Panel A shows number of mapped reads (right) and Gini index representing the evenness of sgRNA reads (left) for the PD1+TIM3+ CRISPR screen. Panel B provides number of significantly depleted hits (Log2FC < -1, FDR<0.05) within the indicated classed of chromatin writers, erasers or readers. Panel C provides a bar graph indicating the expression levels (RPKM) or ARID1A and ARID1B in mouse and human CD8+ T cells. Panel D provides quantification of the PD1+TIM3+ population in cells infected with sgRNAs targeting the indicated genes, normalized to the sgRNA-negative population in the same culture, at Day9 of chronic stimulation. Different sgRNAs for the same gene are labeled with different shapes. Bar graphs represent mean ± SEM from 2-5 independent biological replicates. Panel E provides quantification of the CD62L+ CD44+ population in cells DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 infected with sgRNAs targeting the indicated genes, normalized to the sgRNA-negative population in the same culture, at Day9 of chronic stimulation. Different sgRNAs for the same gene are labeled with different shapes. Bar graphs represent mean ± SEM from 2-4 independent biological replicates. Panel F shows in vitro killing efficiency of B16-OVA cells by OT-1 T cells transduced with the indicated sgRNAs, at Day9 of chronic stimulation. B16- OVA cells and OT-1 T cells were co-incubated for 48 hours at the indicated Target-to- Effector (T:E) ratios. Means ± SEM from 4 technical replicates are shown. Panel G provides sorting strategy for the TIM3 High vs Low screen using a custom sgRNA library of chromatin regulators. Panel H provides number of mapped reads (right) and Gini index representing the evenness of sgRNA reads (left) for the TIM3 High vs Low CRISPR screen. Panel I provides rank plot depicting Log2FC scores (average of n=6 guides) targeting chromatin regulator genes and negative/positive controls. Depleted genes are highlighted in black; positive controls are highlighted in gray; mSWI/SNF complex genes are highlighted in orange. Panel J provides number of significantly depleted hits (Log2FC < -1, FDR<0.05) within the indicated classed of chromatin writers, erasers or readers in the TIM3 High vs Low CRISPR screen. Panel K provides log2FC values for n=6 independent guides in the TIM3 High vs Low CRISPR screen. Panel L provides a schematic for stimulation of mouse OT-1 CD8+ T cells based on co-culture with B16 or B16-OVA cells to profile early activation, transient stimulation, and chronic stimulation/exhaustion states. Panel M provides a fold expansion for mouse OT-1 CD8+ T cells in the chronic or transient stimulation conditions across the Day 3, 5, 5, 9 time points. Bar graphs represent mean ± SEM from 9 independent mice. Panel N provides a FACS-based profiling of PD1, TIM3, CD62L and CD44 at Day9 of transient or chronic stimulation in mouse OT-1 CD8+ T cell studies. Panel O provides a FACS-based profiling of PD1, TIM3, CD62L and CD44 at Day9 of chronic stimulation in control and mSWI/SNF subunit gene KO conditions. Panel P provides a western blot analysis of SMARCA4 levels in sgCTRL or sgSMARCA4 human CD8+ T cells, profiled at Day 9 of the chronic stimulation protocol, compared to actin as loading control. [0050] FIG.12 shows evaluation of mSWI/SNF small molecule inhibitors and degraders in human T cells. Panel A provides western blot analysis of SMARCA4 levels in control, ACBI- or AU-15330- treated human CD8+ T cells at the indicated concentrations, profiled at Day 9 of the chronic stimulation protocol, compared to actin as loading control. Panel B provides FACS plots depicting PD1/TIM3 populations in CD8+ T cells from the indicated donors at Day 9 of chronic stimulation, treated with 50nm and 100nM of SMARCA4/2 degraders and inhibitors. Panel C provides FACS plots and associated MFI quantifications of DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 CD39 surface levels in CD8+ T cells from the indicated donors at Day 9 of chronic stimulation, treated with 50nm and 100nM of SMARCA4/2 degraders (top) and inhibitors (bottom). Panel D provides FACS plots depicting CD45RA/CCR7 populations in CD8+ T cells from the indicated donors at Day 9 of chronic stimulation, treated with 50nm and 100nM of SMARCA4/2 degraders and inhibitors. Panel E provides a bar graph depicting % of CD8+ T cells in Naïve (N), Effector (E), Effector Memory (EM) and Central Memory (CM) populations based on CD45RA and CCR7 surface levels, in DMSO, ACBI1, and AU- 15330 conditions. Error bars represent mean ± SEM of 2-3 independent CD8+ T cell donors. Panel F provides a bar graph depicting % of CD8+ T cells in Naïve (N), Effector (E), Effector Memory (EM) and Central Memory (CM) populations based on CD45RA and CCR7 surface levels, in DMSO, CMP14 and FHT1015 conditions. Error bars represent mean ± SEM of 2-3 independent CD8+ T cell donors. Error bars represent mean ± SEM of 3 technical replicates per donor. *p < 0.05, **p < 0.01, ***p < 0.001. ****p < 0.0001. [0051] FIG.13 shows mSWI/SNF pharmacologic inhibition attenuates exhaustion of human and mouse T cells. Panel A provides FACS plots depicting IFN ^/TNF ^ populations in CD8+ T cells from the indicated donors at Day 9 of chronic stimulation, treated with 50nm and 100nM of SMARCA4/2 degraders and inhibitors. Panel B provides bar graphs depicting the percentage of alive cells at Days 3, 6, 9, 13 and 16 of chronic stimulation, for the indicated donors, treated with 50nm and 100nM of SMARCA4/2 degraders (left) and inhibitors (right). Error bars represent mean ± SEM of three technical replicates. Panel C provides quantification of the percentage of apoptotic cells indicated by AnnexinV staining, at Day 16 of the chronic stimulation protocol, for the indicated donors treated with 50nm and 100nM of SMARCA4/2 degraders. Panel D provides bar graphs depicting cell number upon treatment with ACBI1, AU-15330 or FHT-1015 (10^6 cells/10^ 6 cells at Day 0), initiated at the indicated time points, in one human CD8+ T cell donor. Panel E provides quantification of the PD1+TIM3+ population in human CD8+ T cells upon treatment with ACBI1, AU- 15330 or FHT-1015, initiated at the indicated time points. Data from one CD8+ T cell donor are represented. Panel F provides FACS plots depicting PD1/TIM3 (right) and IFN ^/TNF ^ (left) populations in mouse CD8+ T cells at Day 9 of chronic stimulation, treated with the indicated concentrations of SMARCA4/2 inhibitors. [0052] FIG.14 shows chromatin accessibility, gene expression and T cell effector functional profiling in human and mouse T cells treated with mSWI/SNF inhibitors and degraders. Panel A provides volcano plots of changes in accessibility upon mSWI/SNF DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 disruption (100nM); inhibitors and degraders are grouped. Significantly up-regulated and down-regulated genes (Abs Log2FC> 1, adjP< 0.05) are colored in red and blue, respectively. Differential accessibility was calculated from n=2 independent human CD8+ T cell donors. Panel B provides a hierarchical-clustered heatmap of ATAC-seq sites changes upon treatment with the indicated compounds (100nM). The top 5% most significant differentially accessible peaks are shown. Panel C provides K-means clustering (n=2) of ATAC-seq log2 fold changes upon treatment with the four inhibitors/degraders relative to DMSO control (averaged independent donors). Panel D provides principal component analyses (PCA) of RNA-seq profiles of Control (CHR), and ACBI1, AU-15330, CMP14 or FHT-1015-treated human CD8+ T cells (100nM), at Day9. CHR.1 and CHR.2 are the controls for the ACBI1/AU-15330 and CMP14/FHT-1015 experiments, respectively. Panel E provides volcano plots of changes in gene expression upon treatment with the indicated compounds (100nM). Significantly up-regulated and down-regulated genes (Abs Log2FC > 1, adjp< 0.05) are colored in red and blue, respectively. Differential expression was calculated from n=2 independent human CD8+ T cell donors. Panel F provides a Venn diagram showing the overlap in down-regulated genes (LogFC <-1) upon treatment with ACBI1, AU-15330, CMP14 or FHT-1015 (100nM). Panel G provides hierarchical-clustered heatmaps of gene expression changes upon treatment with the indicated compounds (100nM). The top 1000 differentially expressed genes are shown. Panel G provides a heatmap depicting gene expression changes in the indicated genes across treatment conditions. Panel H provides gene ontology analysis of the 580 down-regulated genes shared among treatment with ACBI1, AU-15330, CMP14 and FHT-1015. Panel I provides a Z-scored heatmap reflecting the expression of selected genes following mSWI/SNF inhibitor or degrader treatments. Panel J provides representative ATAC-seq tracks of untreated (CTRL) or treated T cells over the IRF1 locus with corresponding RNAseq gene expression levels. Panel K provides top 40 coefficients of logistic regression models fitting motif counts across sites to changes in accessibility upon treatment with CMP14 or FHT-1015 in mouse CD8+ T cells. Panel L provides a heatmap displaying ATAC-Seq log2 fold change values upon treatment with CMP14 or FHT-1015, with clusters from Fig. S3a indicated. Panel M provides a schematic of anti-CD19 CAR-T construct used for CAR-T cell studies. Panel N shows in vitro killing efficiency of B16-OVA cells by OT-1 T cells treated with FHT-1015 (100nM), at Day9 of chronic stimulation. B16-OVA cells and OT-1 T cells were co-incubated for 24 hours (left) or 48 hours (right) at the indicated Target-to-Effector (T:E) ratios. Means ± SEM from 4 technical replicates are shown. DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 DETAILED DESCRIPTION OF THE INVENTION [0053] Aspects of the invention are drawn to methods of preventing T cell exhaustion. [0054] Detailed descriptions of one or more embodiments are provided herein. It is to be understood, however, that the invention can be embodied in various forms. Therefore, specific details disclosed herein are not to be interpreted as limiting, but rather as a basis for the claims and as a representative basis for teaching one skilled in the art to employ the invention in any appropriate manner. [0055] The singular forms “a”, “an” and “the” include plural reference unless the context clearly dictates otherwise. The use of the word “a” or “an” when used in conjunction with the term “comprising” in the claims and/or the specification can mean “one,” but it is also consistent with the meaning of “one or more,” “at least one,” and “one or more than one.” [0056] Wherever any of the phrases “for example,” “such as,” “including” and the like are used herein, the phrase “and without limitation” is understood to follow unless explicitly stated otherwise. Similarly, “an example,” “exemplary” and the like are understood to be nonlimiting. [0057] The term “substantially” allows for deviations from the descriptor that do not negatively impact the intended purpose. Descriptive terms are understood to be modified by the term “substantially” even if the word “substantially” is not explicitly recited. [0058] The terms “comprising” and “including” and “having” and “involving” (and similarly “comprises”, “includes,” “has,” and “involves”) and the like are used interchangeably and have the same meaning. Specifically, each of the terms is defined consistent with the common United States patent law definition of “comprising” and is therefore interpreted to be an open term meaning “at least the following,” and is also interpreted not to exclude additional features, limitations, aspects, etc. Thus, for example, “a process involving steps a, b, and c” means that the process includes at least steps a, b and c. Wherever the terms “a” or “an” are used, “one or more” is understood, unless such interpretation is nonsensical in context. [0059] The term “about” is used herein to mean approximately, roughly, around, or in the region of. When the term “about” is used in conjunction with a numerical range, it modifies that range by extending the boundaries above and below the numerical values set forth. In general, the term “about” is used herein to modify a numerical value above and below the stated value by a variance of 20 percent up or down (higher or lower). [0060] The term “in vivo” can refer to an event that takes place in a subject's body. DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 [0061] The term “in vitro” can refer to an event that takes places outside of a subject's body. [0062] The term “ex vivo” can refer to outside a living subject. Examples of ex vivo cell populations include in vitro cell cultures and biological samples such as fluid or tissue samples from humans or animals. Such samples can be obtained by methods well known in the art. Exemplary biological fluid samples include blood, cerebrospinal fluid, urine, saliva. Exemplary tissue samples include tumors and biopsies thereof. In this context, the compounds can be in numerous applications, both therapeutic and experimental. [0063] Aspects of the invention are drawn to methods of preventing T cell exhaustion. [0064] “T cell exhaustion” can refer to a loss of T cell function, which can occur as a result of an infection (e.g., a chronic infection) or a disease (e.g., cancer). T cell exhaustion is associated with increased expression of PD-1, TIM-3, and LAG-3, apoptosis, and reduced cytokine secretion. Accordingly, the terms “ameliorate T cell exhaustion,” “inhibit T cell exhaustion,” “reduce T cell exhaustion” and the like refer to a condition of restored functionality of T cells characterized by one or more of the following: decreased expression and/or level of one or more of PD-1, TIM-3, and LAG-3; increased memory cell formation and/or maintenance of memory markers (e.g., CD62L); prevention of apoptosis; increased antigen-induced cytokine (e.g., IL-2) production and/or secretion; enhanced killing capacity; increased recognition of tumor targets with low surface antigen; enhanced proliferation in response to antigen. In embodiments, T cell exhaustion is indicated by decreased proliferation, increased expression of immune checkpoint molecules, decreased cytokine production, increased expression and/or protein levels of transcription factors, or any combination thereof. For example, transcription factors can comprise HNF1B, TOX, NFATC1, IRF4, BATF, MYB NR4A1/2, SOX4, PRDM1, or any combination thereof. [0065] “Activation” can refer to a process whereby a cell transitions from a resting state to an active state. This process can comprise a response to an antigen, migration, and/or a phenotypic or genetic change to a functionally active state. For example, the term “activation” can refer to the stepwise process of T cell activation. For example, a T cell can require at least two signals to become fully activated. The first signal can occur after engagement of a TCR by the antigen-MHC complex, and the second signal can occur by engagement of co-stimulatory molecules. Anti-CD3 can mimic the first signal and anti-CD28 can mimic the second signal in vitro. In embodiments, T cell activation is indicated by increased proliferation, increased cytokine production, increased expression and/or protein levels of transcription factors, or any combination thereof. For example, the transcription DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 factors comprise NFAT, NFkB, AP-1, GATA3, t-BET, AP-1, BATF, or any combination thereof. [0066] Cellular therapies, such as chimeric antigen receptor (CAR) T-cell therapies, are also provided herein. CAR T-cell therapies redirect a patient’s T-cells to kill tumor cells by the exogenous expression of a CAR. A CAR can be a membrane spanning fusion protein that links the antigen recognition domain of an antibody to the intracellular signaling domains of the T-cell receptor and co-receptor. Solid tumors offer unique challenges for CAR-T therapies. Unlike blood cancers, tumor-associated target proteins are overexpressed between the tumor and healthy tissue resulting in on-target/off-tumor T-cell killing of healthy tissues. Furthermore, immune repression in the tumor microenvironment (TME) limits the activation of CAR-T cells towards killing the tumor. Upon such contact or engineering, the cell can then be introduced to a cancer patient in need of a treatment. The cancer patient can have a cancer of any of the types as disclosed herein. The cell (e.g., a T cell) can be, for instance, a tumor-infiltrating T lymphocyte, a CD4+ T cell, a CD8+ T cell, CD3+ panT cells, or the combination thereof, without limitation. In embodiments, the T cell comprises a chimeric antigen receptor (CAR) T cell. In embodiments, the CAR T cell comprises a CD19-CAR-T cell. [0067] T cell exhaustion can occur as a result of an infection. For example, the infection can be a viral infection. The term “viral infection” can refer to the invasion by, multiplication and/or presence of a virus in a cell or a subject. In one embodiment, the viral infection can be caused by a virus such as a coronavirus, adenovirus, herpes, pox, papilloma, hepatitis, orthomyxoviruses (including influenza), paramyxoviruses (including respiratory syncytial virus), alphaviruses, flaviviruses (including West Nile Virus), bunyaviruses, picornaviruses, caliciviruses, lyssaviruses, henipaviruses, retroviruses or other viruses which cause human disease, including the common cold. Non-limiting examples of viral infections comprise influenza, RSV, parainfluenza, viral pneumonia, viral bronchitis, chicken pox, shingles, and human papillomavirus. In embodiments, the virus can infect a human. In embodiments, the virus cannot infect a human. In embodiments, the virus can infect a human cell. [0068] In one embodiment, a viral infection can be an “active” infection. An active infection can refer to one in which the virus is replicating in a cell or a subject. Active infections can be characterized by the spread of the virus to other cells, tissues, and/or organs, from the cells, tissues, and/or organs initially infected by the virus. [0069] In embodiments, the viral infection can be a “latent” infection. A latent infection can refer to one in which the virus is not actively replicating in the infected host. DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 [0070] A “variant” can refer to any virus having one or more mutations as compared to a known virus. A strain is a genetic variant or subtype of a virus. The terms 'strain', 'variant', and 'isolate' can be used interchangeably. In certain embodiments, a variant has developed a “specific group of mutations” that causes the variant to behave differently than that of the strain it originated from. [0071] In some non-limiting embodiments, the viral infection comprises a drug-resistant viral infection. A “drug-resistant viral infection” can refer to viral infections which are resistant to antiviral drugs. For example, the viral infection can be a remdesivir-resistant viral infection. [0072] T cell exhaustion can occur as a result of a cancer. The terms "cancer” or “tumor” or “hyperproliferative disorder” can refer to the presence of cells possessing characteristics typical of cancer-causing cells, such as uncontrolled proliferation, immortality, metastatic potential, rapid growth and proliferation rate, and certain characteristic morphological features. Cancer is associated with uncontrolled cell growth, invasion of such cells to adjacent tissues, and the spread of such cells to other organs of the body by vascular and lymphatic means. Cancer invasion occurs when cancer cells intrude on and cross the normal boundaries of adjacent tissue, which can be measured by assaying cancer cell migration, enzymatic destruction of basement membranes by cancer cells, and the like. In some embodiments, a particular stage of cancer is relevant and such stages can include the time period before and/or after angiogenesis, cellular invasion, and/or metastasis. Cancer cells are often in the form of a solid tumor, but such cells can exist alone within an animal, or can be a non-tumorigenic cancer cell, such as a leukemia cell. Cancers include, but are not limited to, B cell cancer, e.g., multiple myeloma, Waldenstrom's macroglobulinemia, the heavy chain diseases, such as, for example, alpha chain disease, gamma chain disease, and mu chain disease, benign mono clonal gammopathy, and immunocytic amyloidosis, melanomas, breast cancer, lung cancer, bronchus cancer, colorectal cancer, prostate cancer, pancreatic cancer, stomach cancer, ovarian cancer, urinary bladder cancer, brain or cancer, esophageal cancer, cervical cancer, uterine or endometrial cancer, cancer of the oral cavity or pharynx, liver cancer, kidney cancer, testicular cancer, biliary tract cancer, small bowel or appendix cancer, salivary gland cancer, thyroid gland cancer, adrenal gland cancer, osteosarcoma, chondrosarcoma, cancer of hematological tissues, and the like. Other non-limiting examples of types of cancers applicable to the methods encompassed by the invention include human sarcomas and carcinomas, e.g., fibrosarcoma, myxosarcoma, liposarcoma, chondrosarcoma, osteogenic sarcoma, chordoma, angiosarcoma, endotheliosarcoma, lymphangiosarcoma, DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 lymphangioendotheliosarcoma, synovioma, mesothelioma, Ewing's tumor, leiomyosarcoma, rhabdomyosarcoma, colon carcinoma, colorectal cancer, pancreatic cancer, breast cancer, ovarian cancer, prostate cancer, squamous cell carcinoma, basal cell carcinoma, adenocarcinoma, sweat gland carcinoma, sebaceous gland carcinoma, papillary carcinoma, papillary adenocarcinomas, cystadenocarcinoma, medullary carcinoma bronchogenic carcinoma, renal cell carcinoma, hepatoma, bile duct carcinoma, liver cancer, choriocarcinoma, seminoma, embryonal carcinoma, Wilms ' tumor, cervical cancer, bone cancer, brain tumor, testicular cancer, lung carcinoma, small cell lung carcinoma, bladder carcinoma, epithelial carcinoma, glioma, astrocytoma, medulloblastoma, craniopharyngioma, ependymoma, pinealoma, hemangioblastoma, acoustic neuroma, oligodendroglioma, meningioma, melanoma, neuroblastoma, retinoblastoma; leukemias, e.g., acute lymphocytic leukemia and acute myelocytic leukemia (myeloblastic, promyelocytic, myelomonocytic, monocytic and erythroleukemia ); chronic leukemia (chronic myelocytic (granulocytic) leukemia and chronic lymphocytic leukemia); and polycythemia vera, lymphoma (Hodgkin's disease and non-Hodgkin's disease), multiple myeloma, Waldenstrom’s macroglobulinemia, and heavy chain disease. [0073] As described herein, aspects of the invention are drawn to compositions and methods of preventing T cell exhaustion in a subject. The terms “prevent,” “preventing” and/or “prevention” can refer to the prevention of the onset, recurrence or spread of a disease or disorder, or of one or more symptoms thereof. In embodiments, the terms refer to the treatment with or administration of a compound provided herein, with or without other additional active compound, prior to the onset of symptoms, such as to patients at risk of diseases or disorders provided herein. The terms encompass the inhibition or reduction of a symptom of the disease. [0074] Aspects of the invention are also drawn to compositions and methods of treating a subject afflicted with a disease or disorder exacerbated by T cell exhaustion. The terms “treat,” “treatment,” and “treating” can refer to the management and care of a subject for the purpose of combating a condition, disease or disorder, such as a cancer or an infection, in any manner in which one or more of the symptoms of a disease or disorder are ameliorated or otherwise beneficially altered. The term can include the full spectrum of treatments for a given condition from which the patient is suffering, such as administration of the active compound for the purpose of: alleviating or relieving symptoms or complications; delaying the progression of the condition, disease or disorder; curing or eliminating the condition, disease or disorder; and/or preventing the condition, disease or disorder, wherein DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 "preventing" or "prevention" can refer to the management and care of a patient for the purpose of hindering the development of the condition, disease or disorder, and includes the administration of the active compounds to prevent or reduce the risk of the onset of symptoms or complications. [0075] For example, one or more of the following effects can result from the administration of a therapy or a combination of therapies as described herein: (i) the reduction or amelioration of the severity of a viral infection and/or a symptom associated therewith; (ii) the reduction in the duration of a viral infection and/or a symptom associated therewith; (iii) the regression of a viral infection and/or a symptom associated therewith; (iv) the reduction of the titer of a virus; (v) the reduction in organ failure associated with a viral infection; (vi) the reduction in hospitalization of a subject; (vii) the reduction in hospitalization length; (viii) the increase in the survival of a subject; (ix) the elimination of a virus infection; (x) the inhibition of the progression of a viral infection and/or a symptom associated therewith; (xi) the prevention of the spread of a virus from a cell, tissue or subject to another cell, tissue or subject; and/or (xii) the enhancement or improvement the therapeutic effect of another therapy. [0076] The terms “therapies” and/or “therapy” can refer to any protocol(s), method(s), compositions, formulations, and/or agent(s) that can be used in the prevention, treatment, management, or amelioration of a disease or disorder or a symptom associated therewith. In embodiments, the terms “therapies” and “therapy” can refer to biological therapy, supportive therapy, and/or other therapies useful in treatment, management, prevention, or amelioration of a disease or disorder or a symptom associated therewith known to one of skill in the art. [0077] The terms “therapeutic agent”, and “therapeutic agents” can refer to any agent(s) which can be used in the prevention, treatment and/or management of a disease or disorder or a symptom associated therewith. [0078] Embodiments as described herein can comprise administering to a subject a therapeutically effective amount of a mammalian SWI/SNF complex inhibitor or degrader. The SWI/SNF complex can refer to an evolutionarily conserved ATP-dependent complex that comprises multiple subunits. In embodiments, the subunits are assembled in to three main types or subcomplexes, termed canonical BAF (cBAF), polybromo-associated BAF (PBAF), and non-canonical BAF (ncBAF). mSWI/SNF ATPase inhibitors targeted against SMARCA4 and/or SMARCA2 can inhibit three forms of these complexes. The SWI/SNF complex has a key role in chromatin remodeling and regulation of transcription by recruitment of transcription factors, coactivators and repressors and histone modifiers. These DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 complexes consist of one of the two mutually exclusive catalytic ATPase subunits: SMARCA2 (Brahma or BRM) or SMARCA4 (BRG1), and other subunits such as SMARCB1, SMARCC1, and SMARCC2. PBAF complexes can be distinguished from BAF complexes because the former contains PBRM1 and ARID2 but lack ARID1A/B and DPF1/2/3. SWI/SNF complexes regulate chromatin access by controlling the processes of histone dimer ejection, nucleosome ejection, and repositioning of nucleosomes by sliding. ARID1A binds DNA and can regulate the chromatin remodeling activity of the SWI/SNF complex through recruitment and binding of transcriptional factors. ARID subunits help with binding of the ATPase subcomplex. PBRM1 is essential for the stability of the SWI/SNF chromatin remodeling complex SWI/SNF-B (PBAF). ACTL6A, an actin domain, SMARCE1, and DPF1/2/3 are accessory subunits common to both BAF and PBAF and are rarely mutated in cancers. [0079] In embodiments, the modulator comprises a canonincal BAF (cBAF) inhibitor or degrader. cBAF can refer to at least one type of mammalian SWI/SNF complex. Its nucleosome remodeling activity can be reconstituted with a set of four core subunits (BRG1/SMARCA4, SNF5/SMARCB1, BAF155/SMARCC1, and BAF170/SMARCC2), which have orthologs in the yeast complex. However, mammalian SWI/SNF contains several subunits not found in the yeast counterpart, which can provide interaction surfaces for chromatin (for example, acetyl-lysine recognition by bromodomains) or transcription factors and thus contribute to the genomic targeting of the complex. A key attribute of mammalian SWI/SNF is the heterogeneity of subunit configurations that can exist in different tissues and even in a single cell type (for example, as BAF, PBAF, neural progenitor BAF (npBAF), neuron BAF (nBAF), embryonic stem cell BAF (esBAF), etc.). In some embodiments, the BAF complex described herein refers to one type of mammalian SWI/SNF complexes, which is different from PBAF complexes. In one embodiment, the cBAF complex is a mammalian cBAF complex. In one embodiment, the cBAF complex is a human cBAF complex. The components of the cBAF complex can include, for example, SMARCC1/2, SMARCD1/2/3, SMARCB1, SMARCE1, ARID1A/B, DPF1/2/3, ACTL6A/B, beta-Actin, BCL7A/B/C, SMARCA2/4, and SS18/L1. [0080] In embodiments, the modulator comprises a chromatin modifying agent. A "chromatin modifying agent" can refer to an agent that can modify genomic DNA, in the context of nuclear chromatin. In embodiments, genomic DNA can be modified in a detectable manner. DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 [0081] “Modulating” can refer to regulating or adjusting the degree of activity of a process or the degree of an effect. “Modulating” includes activation, inhibition, degradation, amplification, attenuation, and suppression, for example. For example, modulating the activity of the SWI/SNF complex can refer to altering the level or activity of the SWI/SNF complex, component thereof, or a related downstream effect. The activity level of a BAF complex can be measured using any method known in the art. [0082] A “modulator” can refer to an agent that agonizes (activates or enhances) or antagonizes (inhibits or reduces) the function of a biological target. In embodiments, the SWI/SNF complex modulator can comprise an inhibitor or a degrader. [0083] An “inhibitor” can refer to any agent which reduces the level and/or activity of a protein or protein complex, such as the SWI/SNF complex. The term “inhibiting” can refer to decrease, limiting, and/or blocking a particular action, function, or interaction. Non-limiting examples of inhibitors include small molecule inhibitors, degraders, antibodies, enzymes, or polynucleotides (e.g., siRNA). [0084] A “degrader” can refer to a molecule, such as a compound, that interacts with a protein (e.g., a protein of the SWI/SNF complex) in a way which results in degradation of the protein. For example, binding of the degrader results in at least 5% reduction of the level of the protein, e.g., in a cell or subject. In embodiments, the degrader can comprise a degradation moiety, which can refer to a moiety whose binding results in degradation of a protein. For example, the degradation moiety can bind to a protease or a ubiquitin ligase that metabolizes the protein. [0085] The term “small molecule” can refer to a molecule that is less than about 1000 molecular weight or less than about 500 molecular weight. In one embodiment, a small molecule is an inhibitor. In another embodiment, a small molecule is a degrader. [0086] “Determining the level of a protein” can refer to the detection of a protein, or an mRNA encoding the protein, by methods known in the art, directly or indirectly. “Directly determining” can refer to performing a process (e.g., performing an assay or test on a sample or “analyzing a sample” as that term is defined herein) to obtain the physical entity or value. “Indirectly determining” can refer to receiving the physical entity or value from another party or source (e.g., a third-party laboratory that directly acquired the physical entity or value). For example, methods to measure protein level can include, but are not limited to, western blotting, immunoblotting, enzyme-linked immunosorbent assay (ELISA), radioimmunoassay (RIA), immunoprecipitation, immunofluorescence, surface plasmon resonance, chemiluminescence, fluorescent polarization, phosphorescence, immunohistochemical DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 analysis, matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry, liquid chromatography (LC)-mass spectrometry, microcytometry, microscopy, fluorescence activated cell sorting (FACS), and flow cytometry, as well as assays based on a property of a protein including, but not limited to, enzymatic activity or interaction with other protein partners. Methods to measure mRNA levels are known in the art. [0087] “Reducing the level” of the SWI/SNF complex or component thereof can refer to decreasing the level of the complex or component, such as a SWI/SNF ATPase, in a cell or subject. The level of SWI/SNF complex or component thereof can be measured using any method known in the art. [0088] “Level” can refer to a level of a protein, or mRNA encoding the protein, as compared to a reference. The reference can be any useful reference, as defined herein. By a “decreased level” or an “increased level” of a protein is meant a decrease or increase in protein level, as compared to a reference (e.g., a decrease or an increase by about 5%, about 1 0%, about 15%, about 20%, about 25%, about 30%, about 35%, about 40%, about 45%, about 50%, about 55%, about 60%, about 65%, about 70%, about 75%, about 80%, about 85%, about 90%, about 95%, about 100%, about 150%, about 200%, about 300%, about 400%, about 500%, or more; a decrease or an increase of more than about 10%, about 15%, about 20%, about 50%, about 75%, about 100%, or about 200%, as compared to a reference; a decrease or an increase by less than about 0.01 -fold, about 0.02-fold, about 0.1 -fold, about 0.3-fold, about 0.5-fold, about 0.8-fold, or less; or an increase by more than about 1.2-fold, about 1.4-fold, about 1.5-fold, about 1.8-fold, about 2.0-fold, about 3.0-fold, about 3.5-fold, about 4.5-fold, about 5.0-fold, about 10-fold, about 15-fold, about 20-fold, about 30-fold, about 40-fold, about 50-fold, about 100-fold, about 1000-fold, or more). A level of a protein can be expressed in mass/vol (e.g., g/dL, mg/mL, pg/mL, ng/ml_) or percentage relative to total protein or mRNA in a sample. [0089] “Reducing the activity” of the SWI/SNF complex can refer to dereasing the level of an activity related to the SWI/SNF complex, a component thereof, or a related downstream effect. The activity level of the SWI/SNF complex can be measured using any method known in the art. In embodiments, an agent which reduces the activity of the SWI/SNF complex is a small molecule inhibitor. In embodiments, an agent which reduces the activity of the SWI/SNF complex is a small molecule degrader. [0090] In embodiments, the modulator comprises an ATPase modulator. An “ATPase modulator” can refer to a molecule which binds to ATPase and inhibits or reduces the ATP- hydrolyzing activity of ATPase. For example, the modulator can comprise a SWI/SNF DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 ATPase inhibitor or degrader. For example, the SWI/SNF ATPase modulator can inhibit SMARCA2 and SMARCA4. [0091] The term "SMARCA2" can refer to SWI/SNF related, matrix associated, actin dependent regulator of chromatin, subfamily a, member 2, a member of the SWI/SNF family of proteins and is highly similar to the brahma protein of Drosophila. Members of this family have helicase and ATPase activities and can regulate transcription of certain genes by altering the chromatin structure around those genes. The encoded protein is part of the large ATP- dependent chromatin remodeling complex SNF/SWI, which is required for transcriptional activation of genes normally repressed by chromatin. SMARCA2 is a component of SWI/SNF chromatin remodeling complexes that carry out key enzymatic activities, changing chromatin structure by altering DNA-histone contacts within a nucleosome in an ATP- dependent manner. SMARCA2 binds DNA non-specifically (Euskichen et al. (2012) J Biol Chem 287:30987-30905; Kadoch et al. (2015) Sci Adv 1(5):e1500447). SMARCA2 belongs to the neural progenitors-specific chromatin remodeling complex (npBAF complex) and the neuron-specific chromatin remodeling complex (nBAF complex). During neural development a switch from a stem/progenitor to a postmitotic chromatin remodeling mechanism occurs as neurons exit the cell cycle and become committed to their adult state. The transition from proliferating neural stem/progenitor cells to postmitotic neurons requires a switch in subunit composition of the npBAF and nBAF complexes. As neural progenitors exit mitosis and differentiate into neurons, npBAF complexes which contain ACTL6A/BAF53Aand PHF10/BAF45A, are exchanged for homologous alternative ACTL6B/BAF53B and DPFl/BAF45B or DPF3/BAF45C subunits in neuron-specific complexes (nBAF). The npBAF complex is essential for the self-renewal/proliferative capacity of the multipotent neural stem cells. The nBAF complex along with CREST plays a role regulating the activity of genes essential for dendrite growth. Human SMARCA2 protein has 1590 amino acids and a molecular mass of 181279 Da. The known binding partners of SMARCA2 include, e.g., PHF10/BAF45A, CEBPB, TOPBPl, and CEBPA. [0092] The term "SMARCA4" can refer to SWI/SNF related,matrix associated, actin dependent regulator of chromatin, subfamily a, member 4, a member of the SWI/SNF family of proteins and is highly similar to the brahma protein of Drosophila. Members of this family have helicase and ATPase activities and can regulate transcription of certain genes by altering the chromatin structure around those genes. The encoded protein is part of the large ATP- dependent chromatin remodeling complex SNF/SWI, which is required for transcriptional activation of genes normally repressed by chromatin. In addition, this protein can bind DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 BRCAl, as well as regulate the expression of the tumorigenic protein CD44. Mutations in this gene cause rhabdoid tumor predisposition syndrome type 2. SMARCA4 is a component of SWI/SNF chromatin remodeling complexes that carry out key enzymatic activities, changing chromatin structure by altering DNA-histone contacts within a nucleosome in an ATP- dependent manner. SMARCA4 is a component of the CREST-BRGl complex, a multiprotein complex that regulates promoter activation by orchestrating a calcium-dependent release of a repressor complex and a recruitment of an activator complex. In resting neurons, transcription of the c-FOS promoter is inhibited by BRG1-dependent recruitment of a phospho-RBl- HDAC repressor complex. Upon calcium influx, RBI is dephosphorylated by calcineurin, which leads to release of the repressor complex. At the same time, there is increased recruitment of CREBBP to the promoter by a CREST-dependent mechanism, which leads to transcriptional activation. The CREST-BRGl complex also binds to the NR2B promoter, and activity-dependent induction of NR2B expression involves a release of HDACl and recruitment of CREBBP. SMARCA4 belongs to the neural progenitors-specific chromatin remodeling complex (npBAF complex) and the neuron-specific chromatin remodeling complex (nBAF complex). During neural development a switch from a stem/progenitor to a postmitotic chromatin remodeling mechanism occurs as neurons exit the cell cycle and become committed to their adult state. The transition from proliferating neural stem/progenitor cells to postmitotic neurons requires a switch in subunit composition of the npBAF and nBAF complexes. As neural progenitors exit mitosis and differentiate into neurons, npBAF complexes which contain ACTL6A/BAF53A and PHF 10/BAF 45A, are exchanged for homologous alternative ACTL6B/BAF53B and DPF1/BAF45B or DPF3/BAF45C subunits in neuron-specific complexes (nBAF). The npBAF complex is essential for the self-renewal/proliferative capacity of the multipotent neural stem cells. The nBAF complex along with CREST plays a role regulating the activity of genes essential for dendrite growth. SMARCA4/BAF190A promote neural stem cell self-renewal/proliferation by enhancing Notch-dependent proliferative signals, while concurrently making the neural stem cell insensitive to SHH-dependent differentiating cues. SMARCA4 acts as a corepressor of ZEB1 to regulate E-cadherin transcription and is required for induction of epithelial- mesenchymal transition (EMT) by ZEB1. Human SMARCA4 protein has 1647 amino acids and a molecular mass of 184646 Da. The known binding partners of SMARCA4 include, e.g., PHFl0/ BAF45A, MYOG, IKFZl, ZEB1, NR3Cl, PGR, SMARDl, TOPBPl and ZMIM2/ZIMP7. DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 [0093] The catalytic core of the SWI/SNF complex can be one of two closely related ATPases, SMARCA2 (BRM) or SMARCA4 (BRG1). The choice of alternative subunits can be a key determinant of specificity. Instead of impeding differentiation as was seen with SMARCA4 (BRG1) depletion, depletion of SMARCA2 (BRM) caused accelerated progression to the differentiation phenotype. SMARCA2 (BRM) was found to regulate genes different from those as SMARCA4 (BRG1) targets and can override SMARCA4 (BRG1) - dependent activation of the osteocalcin promoter, due to its interaction with different ARID family members (Flowers et al. (2009), supra). [0094] The term "BAF250A" or "ARIDlA" refers to AT-rich interactive domain- containing protein IA, a subunit of the SWI/SNF complex, which can be find in BAF but not PBAF complex. In humans there are two BAF250 isoforms, BAF250A/ARID1A and BAF250B/ARID1B. They can be E3 ubiquitin ligases that target hi stone H2B (Li et al. (2010) Mal. Cell. Biol.30:1673-1688). ARIDlA is highly expressed in the spleen, thymus, prostate, testes, ovaries, small intestine, colon and peripheral leukocytes. ARID1A is involved in transcriptional activation and repres-sion of select genes by chromatin remodeling. It is also involved in vitamin D-coupled transcription regulation by associating with the WINAC complex, a chromatin-remod-eling complex recruited by vitamin D receptor. ARIDlA belongs to the neural progenitors-specific chromatin remod-eling (npBAF) and the neuron-specific chromatin remodel-ing (nBAF) complexes, which are involved in switching developing neurons from stem/progenitors to post-mitotic chromatin remodeling as they exit the cell cycle and become committed to their adult state. ARID1A also plays key roles in maintaining embryonic stem cell pluripotency and in cardiac development and function (Lei et al. (2012) J. Biol. Chem.287:24255-24262; Gao et al. (2008) Proc. Natl. Acad. Sci. U.S.A.105:6656-6661). Loss of BAF250a expression was seen in 42% of the ovarian clear cell carcinoma samples and 21 % of the endometrioid carcinoma samples, compared with just 1 % of the high-grade serous carcinoma samples. ARIDlA deficiency also impairs the DNA damage checkpoint and sensitizes cells to PARP inhibitors (Shen et al. (2015) Cancer Discov.5:752-767). Human ARIDlA protein has 2285 amino acids and a molecular mass of 242045 Da, with at least a DNA-binding domain that can specifically bind an AT-rich DNA sequence, recognized by a SWI/SNF complex at the beta-globin locus, and a C-terminus domain for glucocorticoid receptor-depen-dent transcriptional activation. ARID IA has been shown to interact with proteins such as SMARCB1/BAF47 (Kato et al. (2002) J. Biol. Chem.277:5498-505; Wang et al. (1996) EMBO J.15:5370-5382) and SMARCA4/BRG1 (Wang et al. (1996), supra; Zhao et al. (1998) Cell 95:625-636), etc. DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 [0095] The term "BAF250B" or "ARIDlB" refers to AT-rich interactive domain- containing protein lB, a subunit of the SWI/SNF complex, which can be find in BAF but not PBAF complex. ARIDlB and ARID IA are alternative and mutually exclusive ARID-subunits of the SWI/SNF com-plex. Germline mutations in ARIDlB are associated with Coffin-Siris syndrome (Tsurusaki et al. (2012) Nat. Genet.44:376-378; Santen et al. (2012) Nat. Genet. 44:379-380). Somatic mutations in ARIDlB are associated with several cancer subtypes, indicating that it is a tumor suppressor gene (Shai and Pollack (2013) PLoS ONE 8:e55119; Sausen et al. (2013) Nat. Genet.45:12-17; Shain et al. (2012) Proc. Natl. Acad. Sci. U.S.A. 109:E252-E259; Fujimoto et al. (2012) Nat. Genet.44:760-764). Human ARID IA protein has 2236 amino acids and a molecular mass of 236123 Da, with at least a DNA-binding domain that can specifically bind an AT-rich DNA sequence, recognized by a SWI/SNF complex at the beta-globin locus, and a C-terminus domain for glucocorticoid receptor- dependent transcriptional activa-tion. ARIDlB has been shown to interact with SMARCA4/ BRGl (Hurlstone et al. (2002) Biochem. J.364:255-264; Inoue et al. (2002) J. Biol. Chem. 277:41674-41685 and SMARCA2/BRM (Inoue et al. (2002), supra). [0096] The term “therapeutic effect” can refer to a local or systemic effect in animals, particularly mammals, and more particularly humans, caused by a pharmacologically active substance. “Therapeutic effect” can refer to any substance intended for use in the diagnosis, cure, mitigation, treatment or prevention of disease or in the enhancement of desirable physical or mental development and conditions in an animal or human. [0097] The term "therapeutically effective amount" can refer to that amount of an embodiment of the composition or pharmaceutical composition being administered that will relieve to some extent one or more of the symptoms of the disease or condition being treated, and/or that amount that will prevent, to some extent, one or more of the symptoms of the condition or disease that the subject being treated has or is at risk of developing. For example, certain compounds encompassed by the methods of the invention can be administered in a sufficient amount to produce a reasonable benefit/risk ratio applicable to such treatment. [0098] In embodiments, a therapeutically effective amount can comprise less than about 0.1 mg/kg, about 0.1 mg/kg, about 0.5 mg/kg, about 1.0 mg/kg, about 2.5 mg/kg, about 5 mg/kg, about 7.5 mg/kg, about 10 mg/kg, about 15 mg/kg, about 20 mg/kg, about 25 mg/kg, about 30 mg/kg, about 35 mg/kg, about 40 mg/kg, about 45 mg/kg, about 50 mg/kg, about 55 mg/kg, about 60 mg/kg, about 70 mg/kg, about 80 mg/kg, about 90 mg/kg, about 100 mg/kg, about 120 mg/kg, about 135 mg/kg, about 150 mg/kg, about 175 mg/kg, about 200 mg/kg, about 225 mg/kg, about 250 mg/kg, about 275 mg/kg, about 300 mg/kg, about 325 mg/kg, DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 about 350 mg/kg, about 375 mg/kg, about 400 mg/kg, about 425 mg/kg, about 450 mg/kg, about 475 mg/kg, about 500 mg/kg, about 525 mg/kg, about 550 mg/kg, about 575 mg/kg, about 600 mg/kg, about 625 mg/kg, about 650 mg/kg, about 675 mg/kg, about 700 mg/kg, about 725 mg/kg, about 750 mg/kg, about 775 mg/kg, about 800 mg/kg, about 825 mg/kg, about 850 mg/kg, about 875 mg/kg, about 900 mg/kg, about 1.0 g/kg, about 1.5 g/kg, about 2.0 g/kg, about 2.5 g/kg, about 5 g/kg, about 10 g/kg, about 25 g/kg, about 50 g/kg, or more than 50 g/kg of compound per body weight of a subject. [0099] In embodiments, the therapeutically effective amount comprises less than about 0.1 mg, about 0.1 mg, about 0.5 mg, about 1.0 mg, about 2.5 mg, about 5 mg, about 7.5 mg, about 10 mg, about 15 mg, about 20 mg, about 25 mg, about 30 mg, about 35 mg, about 40 mg, about 45 mg, about 50 mg, about 55 mg, about 60 mg, about 70 mg, about 80 mg, about 90 mg, about 100 mg, about 120 mg, about 135 mg, about 150 mg, about 175 mg, about 200 mg, about 225 mg, about 250 mg, about 275 mg, about 300 mg, about 325 mg, about 350 mg, about 375 mg, about 400 mg, about 425 mg, about 450 mg, about 475 mg, about 500 mg, about 525 mg, about 550 mg, about 575 mg, about 600 mg, about 625 mg, about 650 mg, about 675 mg, about 700 mg, about 725 mg, about 750 mg, about 775 mg, about 800 mg, about 825 mg, about 850 mg, about 875 mg, about 900 mg, about 1.0 g, about 1.5 g, about 2.0 g, about 2.5 g, about 5 g, about 10 g, about 25 g, about 50 g, or more than 50 g. [00100] A therapeutically effective amount of the SWI/SNF complex modulator will depend on the age and weight of the subject and the concentration and/or formulation of the inhibitor. [00101] The term “subject” or “patient” can refer to any organism to which aspects of the invention can be administered, e.g., for experimental, diagnostic, prophylactic, and/or therapeutic purposes. For example, subjects to which compounds of the disclosure can be administered include animals, such as mammals. Non-limiting examples of mammals include primates, such as humans. For veterinary applications, a wide variety of subjects will be suitable, e.g., livestock such as cattle, sheep, goats, cows, swine, and the like; poultry such as chickens, ducks, geese, turkeys, and the like; and domesticated animals for example pets such as dogs and cats. For diagnostic or research applications, a wide variety of mammals will be suitable subjects, including rodents (e.g., mice, rats, hamsters), rabbits, primates, and swine such as inbred pigs and the like. The term “living subject” can refer to a subject noted herein or another organism that is alive. The term “living subject” can refer to the entire subject or organism and not just a part excised (e.g., a liver or other organ) from the living subject. In embodiments, the SWI/SNF complex inhibitor and/or degrader can comprise an antibody DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 directed to the SWI/SNF complex, a nucleic acid molecule targeting the SWI/SNF complex, a compound or prodrug thereof that binds to the SWI/SNF complex, or a pharmaceutically acceptable salt or ester of said compound or prodrug. [00102] A nucleic acid molecule can refer to DNA molecules and RNA molecules. A nucleic acid molecule can be single-stranded or double-stranded. In embodiments, the nucleic acid molecule is single stranded. In embodiments, the nucleic acid molecule is double- stranded DNA. As used herein, the term “isolated nucleic acid molecule” can refer to a nucleic acid molecule in which the nucleotide sequences are free of other nucleotide sequences, which other sequences can naturally flank the nucleic acid in human genomic DNA. Non-limiting examples of a nucleic acid molecule comprise a siRNA, miRNA, shRNA, antisense RNA, guide RNA (gRNA), single-guide RNA (sgRNA), modified forms thereof, or combination thereof. [00103] A compound can refer to any chemical entity, pharmaceutical, drug, and the like that can be used to treat or prevent a disease, illness, sickness, or disorder of bodily function (for example, viral infection). The term “compound” as used herein can include but is not limited to peptides, nucleic acids, carbohydrates, natural product extract libraries, organic molecules, such as small organic molecules, inorganic molecules, including but not limited to chemicals, metals, and organometallic molecules. For example, non-limiting examples of a compound comprise: , DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 [00104] acceptable salts. “Pharmaceutically acceptable salts” can refer to a salt prepared by combining a compound of the invention with an acid whose anion, or a base whose cation, is considered suitable for human consumption. Non-limiting examples of pharmaceutically acceptable salts DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 comprise mineral acid salts, such as hydrochlorides, hydrobromides, phosphates and sulphates, or salts of organic acids, such as acetates, propionates, malonates and benzoates. [00105] "Pharmaceutically acceptable derivatives" of a compound can include salts, esters, enol ethers, enol esters, acetals, ketals, orthoesters, hemiacetals, hemiketals, acids, bases, solvates, hydrates or prodrugs thereof. Such derivatives can be readily prepared by those of skill in this art using known methods for such derivatization. The compounds produced can be administered to animals or humans without substantial toxic effects as pharmaceutically active compounds or as prodrugs. [00106] In embodiments, the compound can be an antagonist. The term “antagonist” can refer to a compound or composition that can decrease, block, inhibit, abrogate, or interfere with a biological response by binding to or blocking a cellular constituent. [00107] In embodiments, the compound can be an agonist. The term “agonist” can refer to a compound or composition that interacts with a cellular constituent and elicits an observable response. For example, an agonist can stimulate an activity at a receptor or receptors normally stimulated by naturally occurring substances, thus triggering a response. [00108] Aspects of the invention can comprise administering to a subject pharmaceutical compositions comprising a SWI/SNF complex modulator. The phrase "pharmaceutical composition" or a “pharmaceutical formulation” can refer to a composition or pharmaceutical composition suitable for administration to a subject, such as a mammal, especially a human and that can refer to the combination of an active agent(s), or ingredient with a pharmaceutically acceptable carrier or excipient, making the composition suitable for diagnostic, therapeutic, or preventive use in vitro, in vivo, or ex vivo. A “pharmaceutical composition” can be sterile and can be free of contaminants that can elicit an undesirable response within the subject (e.g., the compound(s) in the pharmaceutical composition is pharmaceutical grade). Pharmaceutical compositions can be designed for administration to subjects or patients in need thereof via a number of different routes of administration including oral, intranasal, topical, intravenous, buccal, rectal, parenteral, intraperitoneal, intradermal, intratracheal, intramuscular, subcutaneous, by stent-eluting devices, catheters- eluting devices, intravascular balloons, inhalational and the like. [00109] A "pharmaceutically acceptable excipient," "pharmaceutically acceptable diluent," "pharmaceutically acceptable carrier," or "pharmaceutically acceptable adjuvant" can refer to an excipient, diluent, carrier, and/or adjuvant that are useful in preparing a pharmaceutical composition that are safe, non-toxic and neither biologically nor otherwise undesirable, and include an excipient, diluent, carrier, and adjuvant that are acceptable for DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 veterinary use and/or human pharmaceutical use. "A pharmaceutically acceptable excipient, diluent, carrier and/or adjuvant" as used herein can include one and more such excipients, diluents, carriers, and adjuvants. [00110] Pharmaceutical composition can also be included, or packaged, with other non-toxic compounds, such as pharmaceutically acceptable carriers, excipients, diluents, binders and fillers including, but not limited to, glucose, lactose, gum acacia, gelatin, mannitol, xanthan gum, locust bean gum, galactose, oligosaccharides and/or polysaccharides, starch paste, magnesium trisilicate, talc, corn starch, starch fragments, keratin, colloidal silica, potato starch, urea, dextrans, dextrins, and the like. For example, the pharmaceutically acceptable carriers, excipients, binders, and fillers for use in the practice of the invention are those which render the compounds of the invention amenable to intranasal delivery, oral delivery, parenteral delivery, intravitreal delivery, intraocular delivery, ocular delivery, subretinal delivery, intrathecal delivery, intravenous delivery, subcutaneous delivery, transcutaneous delivery, intracutaneous delivery, intracranial delivery, topical delivery and the like. Moreover, the packaging material can be biologically inert or lack bioactivity, such as plastic polymers or silicone, and can be processed internally by the subject without affecting the effectiveness of the composition/formulation packaged and/or delivered therewith. [00111] In embodiments, the pharmaceutical compositions can comprise pharmaceutically acceptable salts. Pharmaceutically acceptable salts can include, but are not limited to, amine salts, such as but not limited to N,N'-dibenzylethylenediamine, chloroprocaine, choline, ammonia, diethanolamine and other hydroxyalkylamines, ethylenediamine, N- methylglucamine, procaine, N-benzylphenethylamine, 1-para-chlorobenzyl-2-pyrrolidin-1'- ylmethylbenzimidazole, diethylamineand other alkylamines, piperazine and tris(hydroxymethyl) aminomethane; alkali metal salts, such as but not limited to lithium, potassium and sodium; alkali earth metal salts, such as but not limited to barium, calcium and magnesium; transition metal salts, such as but not limited to zinc; and other metal salts, such as but not limited to sodium hydrogen phosphate and disodium phosphate; and also including, but not limited to, salts of mineral acids, such as but not limited to hydrochlorides and sulfates; and salts of organic acids, such as but not limited to acetates, lactates, malates, tartrates, citrates, ascorbates, succinates, butyrates, valerates and fumarates. [00112] Different forms of the pharmaceutical composition can be calibrated in order to adapt both to different subjects and to the different needs of a single subject. However, the pharmaceutical composition need not counter every cause in every subject. Rather, by DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 countering the necessary causes, the pharmaceutical composition will restore the body to its normal function. Then the body will correct the remaining deficiencies. [00113] For oral preparations, the pharmaceutical composition can be used alone or in combination with appropriate additives to make tablets, powders, granules or capsules, for example, with conventional additives, such as lactose, mannitol, corn starch or potato starch; with binders, such as crystalline cellulose, cellulose derivatives, acacia, corn starch or gelatins; with disintegrators, such as corn starch, potato starch or sodium carboxymethylcellulose; with lubricants, such as talc or magnesium stearate; and optionally, with diluents, buffering agents, moistening agents, preservatives and flavoring agents. [00114] Embodiments of the pharmaceutical composition can be formulated into preparations for injection by dissolving, suspending, or emulsifying them in an aqueous or non- aqueous solvent, such as vegetable or other similar oils, synthetic aliphatic acid glycerides, esters of higher aliphatic acids or propylene glycol; and optionally, with conventional additives such as solubilizers, isotonic agents, suspending agents, emulsifying agents, stabilizers and preservatives. [00115] Embodiments of the composition or pharmaceutical composition can be utilized in aerosol formulation to be administered via inhalation. Embodiments of the composition or pharmaceutical composition can be formulated into pressurized acceptable propellants such as dichiorodifluoromethane, propane, nitrogen and the like. [00116] Unit dosage forms for oral administration, such as syrups, elixirs, and suspensions, can be provided wherein each dosage unit, for example, teaspoonful, tablespoonful, tablet or suppository, contains a predetermined amount of the composition containing one or more compositions. Similarly, unit dosage forms for injection or intravenous administration can comprise the pharmaceutical composition as a solution in sterile water, normal saline or another pharmaceutically acceptable carrier. [00117] The term "administering" can refer to introducing a substance into a subject. Any route of administration can be utilized including, for example, intranasal, topical, oral, parenteral, intravitreal, intraocular, ocular, subretinal, intrathecal, intravenous, subcutaneous, transcutaneous, intracutaneous, intracranial and the like administration. For example, “parenteral administration” can refer to administration via injection or infusion. Parenteral administration includes, but is not limited to, subcutaneous administration, intravenous administration, and intramuscular administration. For example, the inhibitor and/or degrader can be administered intranasally, by inhalation, intrapulmonarily, or by injection (e.g., intravenous or subcutaneous). DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 [00118] In embodiments, "administering" can also refer to providing a therapeutically effective amount of a formulation or pharmaceutical composition to a subject. The formulation or pharmaceutical compound can be administered alone, but can be administered with other compounds, excipients, fillers, binders, carriers or other vehicles selected based upon the chosen route of administration and standard pharmaceutical practice. [00119] Administration can be by way of carriers or vehicles, such as injectable solutions, including sterile aqueous or non-aqueous solutions, or saline solutions; creams; lotions; capsules; tablets; granules; pellets; powders; suspensions, emulsions, or microemulsions; patches; micelles; liposomes; vesicles; implants, including microimplants; eye drops; other proteins and peptides; synthetic polymers; microspheres; nanoparticles; and the like. [00120] In embodiments, the compound can be administered alone, or can be administered as a pharmaceutical composition together with other compounds, excipients, carriers, diluents, fillers, binders, or other vehicles selected based upon the chosen route of administration and standard pharmaceutical practice. Administration can be by way of carriers or vehicles, such as injectable solutions, including sterile aqueous or non-aqueous solutions, or saline solutions; creams; lotions; capsules; tablets; granules; pellets; powders; suspensions, emulsions, or microemulsions; patches; micelles; liposomes; vesicles; implants, including microimplants; eye drops; other proteins and peptides; synthetic polymers; microspheres; nanoparticles; and the like. [00121] Embodiments can be administered to a subject in one or more doses. The dose level can vary as a function of the specific composition or pharmaceutical composition administered, the severity of the symptoms and the susceptibility of the subject to side effects. Dosages for a given compound are readily determinable by a variety of means. For example, dosages can be determined by standard clinical techniques. In addition, in vitro or in vivo assays can be employed to help identify optimal dosage ranges. The precise dose to be employed can also depend on the route of administration and can be decided according to the judgment of the practitioner and each patient's circumstances. [00122] In an embodiment, multiple doses of the pharmaceutical composition can be administered. The frequency of administration and the duration of administration of the pharmaceutical composition can vary depending on any of a variety of factors, e.g., patient response, severity of the symptoms, and the like. For example, in an embodiment, the pharmaceutical composition can be administered once per month, twice per month, three times per month, every other week (qow), once per week (qw), twice per week (biw), three times per week (tiw), four times per week, five times per week, six times per week, every other day (qod), DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 daily (ad), twice a day (qid), three times a day (tid), or four times a day. In an embodiment, the pharmaceutical composition can be administered 1 to 4 times a day over a period of time, such as 1 to 10-day time period, or longer than a 10-day period of time. [00123] In embodiments, the pharmaceutical composition can be administered in combination with one or more additional active agents. For example, a first agent (e.g., a prophylactic or therapeutic agent) can be administered prior to (e.g., 5 minutes, 15 minutes, 30 minutes, 45 minutes, 1 hour, 2 hours, 4 hours, 6 hours, 12 hours, 24 hours, 48 hours, 72 hours, 96 hours, 1 week, 2 weeks, 3 weeks, 4 weeks, 5 weeks, 6 weeks, 8 weeks, or 12 weeks before), concomitantly with, or subsequent to (e.g., 5 minutes, 15 minutes, 30 minutes, 45 minutes, 1 hour, 2 hours, 4 hours, 6 hours, 12 hours, 24 hours, 48 hours, 72 hours, 96 hours, 1 week, 2 weeks, 3 weeks, 4 weeks, 5 weeks, 6 weeks, 8 weeks, or 12 weeks after) the administration of a second agent (e.g., a prophylactic or therapeutic agent) to a subject with a disease or disorder or a symptom thereof. [00124] Embodiments as described herein further comprises administering one or more additional active agents to a subject together with the SWI/SNF modulator. Non-limiting examples of such additional active agents can comprise an anti-viral agent (e.g., remdesivir, molunpiravir, paxlovid, or any combination thereof), a vaccine, an anti-inflammatory agent, anti-cancer agents, (e.g., an immunotherapy, a chemotherapy, a radiotherapy), a pain reliever, a steroid, or any combination thereof. [00125] In embodiments, the pharmaceutical composition comprising SWI/SNF inhibitor and/or degrader and a second active agent can be administered sequentially, such as one before the other, or concurrently or simultaneously, such as at about the same time. [00126] The term “simultaneous administration” can refer to a first agent and a second agent, when together in the therapeutic combination therapy, are administered less than about 15 minutes, e.g., less than about 10, 5, or 1 minute. When the first agent and the second agent are administered simultaneously, the first and second treatments can be in the same composition (e.g., a composition comprising both the first and second therapeutic agents) or separately (e.g., the first therapeutic agent is contained in one composition and the second treatment is contained in another composition). [00127] The term “sequential administration” can refer to a first agent and a second agent administered to a subject greater than about 15 minutes apart, such as greater than about 20, 30, 40, 50, 60 minutes, or greater than 60 minutes apart. Any agent can be administered first. For example, the first agent and the second agent can be included in separate compositions, which can be included in the same or different packages or kits. DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 [00128] The terms “co-administration” or the like, as used herein, can refer to the administration of a first active agent and at least one additional active agent to a single subject, and is intended to include treatment regimens in which the compounds and/or agents are administered by the same or different route of administration, in the same or a different dosage form, and at the same or different time. [00129] The term “in combination” can refer to the use of more than one therapies (e.g., one or more prophylactic and/or therapeutic agents). The use of the term “in combination” does not restrict the order in which therapies are administered to a subject with a disease or disorder, or the route of administration. [00130] The term “expression profile” can refer to a genomic expression profile. Profiles can be generated by any convenient means for determining a level of a nucleic acid sequence, non- limiting examples of which include quantitative hybridization of microRNA, labeled microRNA, amplified microRNA, cRNA, quantitative PCR, ELISA for quantitation, and the like. Expression profiles can allow for the analysis of differential gene expression between two samples. In embodiments, a subject or patient sample, e.g., cells or collections thereof, e.g., tissues, can be assayed. Samples can be collected by any convenient method, as known in the art. [00131] The term “microarray” can refer to an ordered arrangement of hybridizable array elements, such as polynucleotide probes, on a substrate. [00132] The terms “level of expression” or “expression level” can be used interchangeably and can refer to the amount of a biomarker in a biological sample. A “biological sample” can refer to a sample that is of biologic origin or contains biologic elements. A biologic sample can contain whole cells (live or dead), parts of cells, cell debris, cell products (intracellular cell products or those that are secreted or excreted from a cell), compounds produced by a biologic entity or cell(s) thereof. The biological sample can be, contain, or be derived from a “bodily fluid” or “bodily gas”. The term “bodily fluid” can refer to any fluid produced by a biologic entity or subject and includes, amniotic fluid, aqueous humour, vitreous humour, bile, blood, blood serum, breast milk, cerebrospinal fluid, cerumen (earwax), chyle, chyme, endolymph, perilymph, exudates, feces, female ejaculate, gastric acid, gastric juice, lymph, mucus (including nasal drainage and phlegm), pericardial fluid, peritoneal fluid, pleural fluid, pus, rheum, saliva, sebum (skin oil), semen, sputum, synovial fluid, sweat, tears, urine, vaginal secretion, vomit, exhalant (respiratory), and mixtures of one or more thereof. Biologic gasses include, but are not limited to exhalant (respiratory), flatulence, decomposition gasses, and the like. Biological samples include cell cultures, bodily fluids, cell cultures from bodily fluids. DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 Bodily fluids, gasses, or other biological samples can be obtained by any suitable collection method and/or technique, including but not limited to, those described in greater detail elsewhere herein, biopsy, puncturing (e.g., venous puncture), swabbing, scraping, plucking, pinching, cutting, catching (e.g., free catching urine or saliva after spitting by a subject), scooping, squeezing, expressing, extracting, sucking, passive sampling, and combinations thereof. Biologic samples can also those obtained from the environment, but contain cells or cell products secreted, released, or excreted from a subject. For example, methods as described herein can comprise detecting an analyte mRNA, protein, or genomic DNA in a biological sample in vitro as well as in vivo. [00133] “Expression" can refer to the process by which information (for example, gene- encoded and/or epigenetic information) is converted into the structures and operating in the cell. For example, “expression" can refer to transcription into a polynucleotide, translation into a polypeptide, or even polynucleotide and/or polypeptide modifications (for example, posttranslational modifications of a polypeptide). Fragments of the transcribed polynucleotide, the translated polypeptide, or polynucleotide and/or polypeptide modifications (for example, posttranslational modification of a polypeptide) can also be regarded as expressed whether they originate from a transcript generated by alternative splicing or a degraded transcript, or from a post-translational processing of the polypeptide, for example, by proteolysis. “Expressed genes” can include those that are transcribed into a polynucleotide as mRNA and then translated into a polypeptide, and also those that are transcribed into RNA but not translated into a polypeptide (for example, transfer and ribosomal RNAs). [00134] “Increased expression,” “increased expression level,” “increased levels," “elevated expression," "elevated expression levels,” or “elevated levels” can refer to an increased expression or increased levels of a biomarker in a subject or biological sample isolated from a subject relative to a control, such as a subject or subjects who are not suffering from the disease or disorder (for example, a disease or disorder exacerbated by T cell exhaustion) or an internal control (for example, a housekeeping biomarker). [00135] “Decreased expression," "decreased expression level," "decreased levels,” “reduced expression,” “reduced expression levels,” or “reduced levels” can refer to a decrease expression or decreased levels of a biomarker in a subject or biological sample isolated from a subject relative to a control, such as a subject or subjects who are not suffering from the disease or disorder (for example, a disease or disorder exacerbated by T cell exhaustion) or an internal control (for example, a housekeeping biomarker). DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 [00136] “Amplification” can refer to the process of producing multiple copies of a sequence. “Multiple copies” can refer to at least two copies. A “copy” does not necessarily mean perfect sequence complementarity or identity to the template sequence. For example, copies can include nucleotide analogs such as deoxyinosine, intentional sequence alterations (such as sequence alterations introduced through a primer comprising a sequence that is hybridizable, but not complementary, to the template), and/or sequence errors that occur during amplification. [00137] In embodiments, primary cells can undergo amplification in order to be tested for the impact of ATPase inhibition. In embodiments, the nucleic acid amplification can include polymerase chain reaction (PCR), reverse-transcription PCR, quantitative PCR, real-time PCR, isothermal amplification, linear amplification, or isothermal linear amplification, quantitative fluorescent PCR (QF-PCR), multiplex fluorescent PCR (MF-PCR), single cell PCR, restriction fragment length polymorphism PCR(PCR-RFLP), PCR-RFLP/RT-PCR-RFLP, hot start PCR, nested PCR, in situ colony PCR, in situ rolling circle amplification (RCA), bridge PCR (bPCR), picotiter PCR, digital PCR, droplet digital PCR, or emulsion PCR (emPCR). Other suitable amplification methods include ligase chain reaction (LCR (oligonucleotide ligase amplification (OLA)), transcription amplification, cycling probe technology (CPT), molecular inversion probe (MIP)PCR, self-sustained sequence replication, selective amplification of target polynucleotide sequences, consensus sequence primed polymerase chain reaction (CP-PCR), arbitrarily primed polymerase chain reaction (AP-PCR), transcription mediated amplification (TMA), degenerate oligonucleotide-primed PCR (DOP-PCR), multiple-displacement amplification (MDA), strand displacement amplification (SDA), and nucleic acid based sequence amplification (NABS A). [00138] The technique of “polymerase chain reaction” or “PCR” a procedure wherein minute amounts of a specific piece of nucleic acid, RNA and/or DNA, are amplified as described, for example, in U.S. Pat. No.4, 683, 195. In embodiments, sequence information from the ends of the region of interest or beyond is available, such that oligonucleotide primers can be designed; these primers will be identical or similar in sequence to opposite strands of the template to be amplified. The 5' terminal nucleotides of the two primers can coincide with the ends of the amplified material. PCR can be used to amplify specific RNA sequences, specific DNA sequences from total genomic DNA, and cDNA transcribed from total cellular RNA, bacteriophage, or plasmid sequences, etc. See Mullis et al., Cold Spring Harbor Symp. Quant. Biol. 51: 263 (1987) and Erlich, ed., PCR Technology, (Stockton Press, NY, 1989). As used herein, PCR is one, but not the only, example of a nucleic acid polymerase reaction method for DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 amplifying a nucleic acid test sample, comprising the use of a known nucleic acid (DNA or RNA) as a primer and utilizes a nucleic acid polymerase to amplify or generate a specific piece of nucleic acid or to amplify or generate a specific piece of nucleic acid which is complementary to a nucleic acid. [00139] The term “multiplex-PCR” can refer to a single PCR reaction carried out on nucleic acid obtained from a single source (e.g., an individual) using more than one primer set for the purpose of amplifying two or more DNA sequences in a single reaction. [00140] “Quantitative real-time polymerase chain reaction" or “qRT-PCR” can refer to a form of PCR wherein the amount of PCR product is measured at each step in a PCR reaction. This technique has been described in various publications including, for example, Cronin et al., Am. J. Pathol.164 (1): 35-42 (2004) and Ma et al., Cancer Cell 5 : 607-616 (2004). [00141] In some embodiments, nucleic acid amplification can include digital PCR. It will be appreciated that digital PCR can include any method, process, and/or protocol, using instruments and/or kits associated with performing such, that can discretely amplify and quantitate a nucleic acid(s) within individual partitions of a sample. In some embodiments, the individual partitions for a digital PCR can be generated by a microfluidic process, such as by using a microfluidic device, and/or by a droplet generating process. Generation of individual partitions by a microfluidic process, such as by using a microfluidic device, and/or a droplet generating process to provide a plurality of partitions in the form of droplets and performing nucleic acid amplification thereon has been described in the art as "droplet digital PCR." The droplets generated for droplet digital PCR can be provided in, for example, a water-in-oil emulsion. In some embodiments, the methods, processes, and/or protocols, and instruments and/or kits for performing nucleic acid amplification on partitions in the form of droplets generated using a microfluidic device/process and/or a droplet generating process, are commercially available, for example, but not limited to, those provided by Bio-Rad, 10X Genomics, Qiagen, and/or ThermoFisher. In an exemplary embodiment, nucleic acid amplification includes droplet digital PCR (ddPCR™) using Bio-Rad's QX100™ or QX200™ Droplet Digital PCR systems, and analysis of nucleic acid amplification products produced by the same, but is not limited thereto. [00142] "Sequencing", "sequence determination" and the like can refer to biochemical methods that can be used to determine the order of nucleotide bases in a nucleic acid. Targeted sequencing can include the ability to detect complex variation, avoiding clonal errors, and analysis that is less computationally burdensome (e.g., de novo sequencing). There are several embodiments of targeted sequencing. DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 [00143] The term “targeted sequencing” can refer to efficient sequencing of a small subset of the genome. In clinical settings, sequencing a subset of the genome not only reduce costs, but also focuses on the relevant regions. The main challenge for clinical targeted resequencing methods is obtaining complete and uniform coverage of target regions. Methods for target enrichment rely on lengthy and inefficient hybrid capture or multiplexed PCR techniques, resulting in lower coverage and more off-target sequencing reads. [00144] The terms “whole genome sequencing,” “full genome sequencing”, “complete genome sequencing”, and “entire genome sequencing” can refer to a laboratory process that determines the complete DNA sequence of an organism's genome at a single time. This entails sequencing of an organism's chromosomal DNA as well as DNA contained in the mitochondria and, for plants, in the chloroplast. [00145] Aspects of the invention are also directed towards kits, such as kits comprising compositions as described herein. For example, the kit can comprise therapeutic combination compositions described herein. [00146] In one embodiment, the kit includes (a) a T cell, such as that described herein, or (b) the cellular therapy, such as that described herein, and optionally (c) informational material. The informational material can be descriptive, instructional, marketing or other material that is drawn to the methods described herein and/or the use of the agents for therapeutic benefit. [00147] In an embodiment, the kit includes two or more agents. For example, the kit includes a container comprising a SWI/SNF complex modulator, and a second container comprising a second active agent. [00148] In embodiments, the kit further comprises a third container comprising a third active agent. [00149] The informational material of the kits is not limited in its form. In one embodiment, the informational material can include information about production of the compound, molecular weight of the compound, concentration, date of expiration, batch or production site information, and so forth. In one embodiment, the informational material comprises methods of administering the therapeutic combination composition, e.g., in a suitable dose, dosage form, or mode of administration (e.g., a dose, dosage form, or mode of administration described herein), to treat a subject who has a nerve disconnectivity disorder). The information can be provided in a variety of formats, include printed text, computer readable material, video recording, or audio recording, or information that provides a link or address to substantive material. DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 [00150] The composition in the kit can include other ingredients, such as a solvent or buffer, a stabilizer, or a preservative. The SWI/SNF complex modulator can be provided in any form, e.g., liquid, dried or lyophilized form, or for example, substantially pure and/or sterile. When the agents are provided in a liquid solution, the liquid solution is an aqueous solution. When the agents are provided as a dried form, reconstitution can be by the addition of a suitable solvent. The solvent, e.g., sterile water or buffer, can optionally be provided in the kit. [00151] The kit can include one or more containers for the composition or compositions containing the agents. In some embodiments, the kit contains separate containers, dividers or compartments for the composition and informational material. For example, the composition can be contained in a bottle, vial, or syringe, and the informational material can be contained in a plastic sleeve or packet. In other embodiments, the separate elements of the kit are contained within a single, undivided container. For example, the composition is contained in a bottle, vial or syringe that has attached thereto the informational material in the form of a label. In some embodiments, the kit includes a plurality (e.g., a pack) of individual containers, each containing one or more unit dosage forms (e.g., a dosage form described herein) of the agents. The containers can include a combination unit dosage, e.g., in a given ratio. For example, the kit includes a plurality of syringes, ampules, foil packets, blister packs, or medical devices, e.g., each containing a single combination unit dose. The containers of the kits can be airtight, waterproof (e.g., impermeable to changes in moisture or evaporation), and/or light-tight. The kit optionally includes a device suitable for administration of the composition, e.g., a syringe or other suitable delivery device. The device can be provided pre-loaded with one or both of the agents or can be empty, but suitable for loading. [00152] Other Embodiments [00153] While the invention has been described in conjunction with the detailed description thereof, the foregoing description is intended to illustrate and not limit the scope of the invention, which is defined by the scope of the appended claims. Other aspects, advantages, and modifications are within the scope of the following claims. [00154] The invention will be further described in the following examples, which do not limit the scope of the invention described in the claims. DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 EXAMPLES [00155] Examples are provided herein to facilitate a more complete understanding of the invention. The following examples illustrate the exemplary modes of making and practicing the invention. However, the scope of the invention is not limited to specific embodiments disclosed in these Examples, which are for purposes of illustration only, since alternative methods can be utilized to obtain similar results. EXAMPLE 1 [00156] Highly coordinated changes in gene expression underlie T cell activation and exhaustion. However, the mechanisms by which such programs are regulated and how these can be leveraged for therapeutic benefit remain poorly understood. Here, we comprehensively profile the genomic occupancy of mSWI/SNF chromatin remodeling complexes throughout acute and chronic T cell stimulation, finding that stepwise changes in localization over transcription factor binding sites direct site-specific chromatin accessibility and gene activation leading to distinct phenotypes. Notably, perturbation of mSWI/SNF complexes using genetic strategies and clinically-relevant small molecule inhibitors and degraders enhances persistence of T cells with attenuated exhaustion hallmarks and increased memory features in vitro and in vivo. Finally, pharmacologic mSWI/SNF inhibition improves CAR-T expansion and results in improved anti-tumor control in vivo. These findings reveal the central role for mSWI/SNF complexes in the coordination of T cell activation and exhaustion, and indicate applications for the improvement of current immunotherapeutic approaches. [00157] This approach is distinguished because it uses small molecule agents (now generated and in the clinic in Phase I clinical trials) to enhance the a) generation/manufacturing of CAR-T cells and b) the efficacy of CAR-T cells. Using agents that alter the ATPase activity or other activities of the canonical BAF (cBAF) mSWI/SNF chromatin remodeling complexes. [00158] Applications of this approach include but are not limited to: 1) CAR-T cell manufacturing and generation, 2) Combination therapy with CAR-T cells, and 3) Combination therapy with PD1/Anti-PD1 agents. EXAMPLE 2 DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 [00159] Stepwise activities of mSWI/SNF family chromatin remodeling complexes direct T cell activation and exhaustion [00160] Summary [00161] Highly coordinated changes in gene expression underlie T cell activation, exhaustion and effector function. However, the mechanisms by which such programs are regulated and how these can be targeted for therapeutic benefit remain poorly understood. Here, we comprehensively profile the genomic occupancy of mSWI/SNF chromatin remodeling complexes throughout acute and chronic T cell stimulation, finding that stepwise changes in localization over transcription factor binding sites direct site-specific chromatin accessibility and gene activation leading to distinct phenotypes. Notably, perturbation of mSWI/SNF complexes using genetic and clinically-relevant chemical strategies enhances persistence of T cells with attenuated exhaustion hallmarks and increased memory features in vitro and in vivo. Finally, pharmacologic mSWI/SNF inhibition improves CAR-T expansion and results in improved anti-tumor control in vivo. These findings reveal the central role for mSWI/SNF complexes in the coordination of T cell activation and exhaustion and nominate small molecule-based strategies for the improvement of current immunotherapy protocols. [00162] Introduction [00163] T cells undergo dynamic cell morphologic and gene regulatory changes upon acute or sustained exposure to antigen 1-5. Importantly, chronic antigen stimulation causes T cells to enter a dysfunctional state known as T cell exhaustion in which T cells exhibit poor effector function, reduced proliferative capacity, sustained expression of inhibitory receptors, and altered cytokine production 6. As such, targeting T cell exhaustion has formed the basis for numerous studies in the context of both chimeric antigen receptor (CAR)-T cell generation and checkpoint blockade efficacy 7-13. However, the molecular mechanisms governing T cell activation and exhaustion as well as the factors directing the expression of key state-specific biomarkers remain poorly understood, representing a major barrier to progress. Indeed, understanding such mechanisms bears significant impact on the potential for therapeutic accentuation of CAR-T cell treatments, tumor immunotherapy, and responses against infection. [00164] Over the past several years, studies in both mouse and human settings have defined chromatin-level changes during T cell activation and exhaustion, including linking locus-specific accessibility changes with anti-tumor responses 14-22. By way of these efforts, species-level differences have also been identified owing to the fact that a number of gene regulatory networks differ between mouse and human cells, obviating the need for increased DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 understanding of human T cells and strategies to modulate their activities 18. Studies aiming to identify strategies to prevent or reverse exhaustion and to define which T cell populations (i.e. terminally differentiated exhausted versus progenitor exhausted) can be targeted represent active areas of investigation23-25. [00165] Several critical transcription factors (TFs) that contribute to distinct stages of T cell activation, from initial acute activation to exhaustion, have been identified 3,24, including NFAT, NFkB, AP-1, GATA3, and t-BET, as critical mediators of activation, and elevated T cell receptor (TCR)-responsive TFs such as TOX, NFATC1, IRF4, BATF, MYB and others in exhausted states 6,25-33. Efforts to target such factors directly are challenged by high-affinity TF-DNA interactions and functional redundancy between multiple TFs, making inhibition or depletion of a single TF often insufficient to generate a desired programmatic response. Indeed, for several specific T cell states, networks that encompass multiple TFs (among other nuclear factors) have been identified, yet strategies to conclusively ‘rank’ or prioritize which play ‘master regulatory’ or directing roles and which are secondary remain challenging. With few exceptions, the role for chromatin regulatory complexes and epigenetic modifiers as targets to combat T cell dysfunction remain less clear 8,15,34. However, in recent months, several CRISPR screens have been performed in mouse T cell contexts, revealing chromatin regulatory proteins and protein complexes as potential mediators of exhausted T cell programs 35,36. In particular, unbiased genome-scale CRISPR screens have identified components of the mammalian SWI/SNF (mSWI/SNF) family of ATP-dependent chromatin remodeling complexes as potential mediators of specific states, such as regulatory T cell and exhausted states 37,38. [00166] Our group and others have shown that a wide range of human TFs interact transiently with mSWI/SNF complexes resulting in their site-specific targeting genome-wide 39-42. mSWI/SNF complexes are heterogeneous, multi-subunit entities that alter DNA- nucleosome contacts, generating chromatin accessibility and coordinating the timely and appropriate binding of transcriptional machinery required for proper gene expression 43-47. The genes encoding the 29 total subunits are collectively mutated in over 20% of human cancers, in some cases representing hallmark drivers 44,48 and have been implicated in both cellular differentiation and cell-state changes, however mSWI/SNF mechanisms remain understudied in the context of immune cells49. mSWI/SNF complexes exist in three final form assemblies, termed canonical BAF (cBAF), polybromo-associated BAF (PBAF), and non-canonical BAF (ncBAF), each demarcated by the incorporation of distinct subunits and unique association with chromatin landscape features 43,50,51. While the importance of DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 mSWI/SNF complexes as regulators of appropriate chromatin accessibility in the tumor- intrinsic setting represents an active area of investigation, the role for these regulators in governing immune cell function alone or within the tumor microenvironment remains less clear 52-60. Results from studies aiming to understand the role for mSWI/SNF-directed chromatin remodeling across T cell states in particular, therefore, is of uniquely high biological significance, given that such cells often need to undergo multiple stepwise, dynamic changes to carry out specific functions and to orchestrate anti-tumor immune responses. [00167] Results [00168] Stepwise rewiring of mSWI/SNF complex occupancy and chromatin accessibility during acute and chronic human T cell stimulation [00169] To study chromatin-level changes across CD8+ T cells states from early T cell activation to exhaustion, we developed a cell-based system for antigen-independent TCR stimulation of human CD8+ T cells (FIG.1, panel A). CD8+ cytotoxic T cells were profiled without stimulation (0h) or at 3h, 24h, 48h and 72h (3 days) following stimulation to capture a range of time points during early T cell activation. To profile changes related to chronic antigen stimulation, cells were replated in presence of new beads every 3 days on Days 3, 6 and 9 following initial activation (‘Chronic’, Ch, condition). In addition, a ‘Transient’ (Tr) stimulation condition, in which CD3/CD28-coated beads were removed after the initial 3-day incubation, was used to control for chronic TCR stimulation-independent changes and to mimic a memory phenotype. We monitored T cell proliferation, immunophenotype, and functionality across these stages (FIG.1, panel A, FIG.8, panels A-B). Stimulated T cells displayed sustained proliferation during the first 6 days after activation and lack of stimulation over time led to a reduction in the proliferative capability of transiently stimulated T cells. We also observed a decrease in the proliferative capacity of chronically- activated cells at the Day 9 timepoint (third round of stimulation), indicating the acquisition of an exhausted-like state (FIG.8, panel A). FACS-based analyses performed at the early (acute) activation (3hr, 24hr), activation (48hr, 72hr), exhaustion-like (Day6-Day9-Ch), or memory (Day9-Tr) stages revealed acquisition of markers consistent with these phenotypes (FIG. 8, panel B), such as the CD25 activation marker at 24 hours, sustained up-regulation of the PD1 immune checkpoint, and elevated terminal exhaustion markers, TIM-3 and CD39, at Days 6 and 9 of the chronic but not transiently stimulated condition (FIG.8, panel B). Chronically-activated T cells expressed low levels of CCR7 and CD45RA and displayed hallmark signs of dysfunction, such as reduced IFN ^, TNF ^ and GZM ^ staining upon re- DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 stimulation (FIG.8, panel B). In addition, we established a similar system using mouse CD8+ T cells, with highly consistent proliferation and immunophenotyping results (FIG.8, panels C-D). [00170] Owing to the long-held concept that T cells undergo major rearrangement in their nuclear architecture and chromatin accessibility during T cell activation and exhaustion61, we next sought to characterize the chromatin occupancy of the mSWI/SNF family of ATP-dependent chromatin remodeling complexes, which are well established to play directive roles in generating DNA accessibility over target loci 57,59,61-63. Indeed, these complexes have been implicated in various T cell contexts, from dysfunction to the generation of T regulatory cells, however, comprehensive profiling of their genome-wide occupancy and activities across T cell populations has not been examined 35,37,61,64. To achieve this, we performed CUT&TAG experiments using antibodies targeting the ATPase subunit, SMARCA4, which is in the three subcomplexes within the mSWI/SNF family (cBAF, PBAF, and ncBAF) 43,65,66. Further, we used antibodies against SS18 (a member of cBAF and ncBAF), as well as ARID1A (cBAF-specific) and PBRM1 (PBAF-specific), in parallel with H3K27Ac, a marker of active chromatin. We observed striking increases in total mSWI/SNF and histone peak numbers over early activation time points (peak at 48-72 hours), with results consistent between cells isolated from two independent human donors (FIG.9, panels A-C). Principal component analyses (PCA) revealed concordant timepoint- and cell state-specific changes in mSWI/SNF as well as H3K27Ac genomic occupancy from both human donors across the full-time course (FIG.1, panel C; FIG.9, panel D). In parallel, we characterized chromatin landscape accessibility across T cell activation and exhaustion using assay for transposase-accessible chromatin (ATAC)-seq 67,68, which revealed similar changes and directionality upon PCA analysis as with mSWI/SNF complex members and H3K27Ac (FIG.1, panel C; FIG.9, panels E-F)). [00171] We next merged the mSWI/SNF complex occupancy and accessibility data and performed k-means clustering analyses to reveal changes in complex localization and accessibility across the activation-exhaustion time course. Combination of SMARCA4-SS18- H3K27Ac-ATAC-seq-merged peaks (quantile normalized, log2-transformed RPKM values transformed into Z-scores) revealed nine (n=9) distinct clusters of mSWI/SNF occupancy and DNA accessibility (FIG.1, panel D; FIG.9, panel G). Integrating these data with immune profiling results (FIG.8, panel B), we found that early activation was highlighted in cluster 2 (C2), activation and exhaustion in clusters 3 and 4 (C3, C4), late activation in cluster 5 (C5), exhaustion in cluster 6 (C6), and memory phenotype in clusters 7 and 8 (C7, C8) (FIG.1, DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 panel D; FIG.8, panel B; FIG.9, panel G). Cluster 1 (C1) sites contained TSS-proximal targets of varied targeting and accessibility across conditions and cluster 9 (C9) sites encompassed TSS-distal sites of lower accessibility and with highest mSWI/SNF targeting signal prior to and at early stimulation (FIG.1, panel D; FIG.9, panel H). Across time points, mSWI/SNF complex occupancy, H3K27Ac signal, and accessibility overlapped substantially genome-wide, with mSWI/SNF complex-bound sites representing a fraction of the total accessible sites (FIG.1, panel E; FIG.9, panel I). Further, mSWI/SNF-bound sites represented increasingly lower fractions of total accessible sites across activation to exhaustion, indicating an increasingly specific or limited group of sites potentially directing the chromatin accessibility and gene regulatory programs hallmark to these states (FIG.1, panel E). Finally, we identified similar results in the mouse setting, albeit with a less enhanced set of differences between D9-Ch and D9-Tr conditions (FIG.9, panel J). Taken together, these studies establish mSWI/SNF complex binding and chromatin accessibility profiles throughout T cell activation and dysfunction, enabling dissection of their roles in mediating state-specific T cell transcriptional networks. [00172] Differential, state-specific targeting and activity of mSWI/SNF complexes over transcription factor binding sites during T cell activation and exhaustion [00173] We next performed motif analyses using HOMER and archetype-based calling across the 9 clusters of mSWI/SNF-bound, accessible sites (FIG.2, panel A; FIG.10, panels A-B). Similarly, locus overlap analysis (LOLA) performed across the activation- exhaustion time course revealed state-specific TF binding enrichment over mSWI/SNF- occupied and accessible sites (FIG.2, panel B). Sites corresponding to early activation were enriched in AP-1 (JUN/FOS), BATF, NFkB and NFAT motifs, corresponding to TFs known to play critical roles in early T cell activation (FIG.2, panels A-B; FIG.10, panels A-B) 69- 72. TF motifs enriched in mSWI/SNF-bound, DNA-accessible sites at the middle to late activation stages included those for ATF3, BCL6, CREB1, JUND and TBX1 (FIG.2, panels A-B). Motifs in the exhaustion-associated C6 (Day 6 and D9-Ch time points) included those for MYB/MYBL1, TCF7 (TCF1), which have been implicated CD8+ T cell stemness and/or exhaustion, as well as CUX2, POU5F1 and SOX3/10 TFs, which to date remain less well characterized in the context of T cell activation and differentiation but have been suggested to interact with mSWI/SNF complexes (FIG.2, panels A-B; FIG.10, panel B) 6,16,73-78. Intriguingly, we identified significant enrichment of mSWI/SNF complex occupancy over motifs corresponding to HNF1B (Hepatocyte nuclear factor-1-beta) not previously implicated in T cell biology (FIG.2, panels A-B; FIG.10, panels A-B). DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 [00174] Further, TF motifs identified under mSWI/SNF-occupied sites specifically at memory-like/naïve T cell clusters (C7/C8) included ETS factors (ETS1, ERG), RUNX1/2, GATA3, STAT factors, and others (FIG.2, panels A-B). Several of these factors have been reported by our group and others to interact with mSWI/SNF complexes in cancer and other contexts 39,40,79,80. Finally, TF motifs uniquely enriched at mSWI/SNF target sites prior to and at early stimulation, as well as at Day 6, D9-Tr and D9-Ch (C9) time points were nearly exclusively those for CTCF, the motif exclusively targeted by the ncBAF mSWI/SNF subcomplex (FIG.2, panel A; FIG.10, panel B) 51,52. [00175] To define putative direct mSWI/SNF genomic targets as well as secondarily (downstream) accessible sites, we next used ATAC-seq data in isolation to identify TF motifs under mSWI/SNF-bound and -unbound accessible genomic regions at time points across the activation-exhaustion continuum, relative to unstimulated (FIG.2, panel C; FIG.10, panel C). In addition to strong enrichment of TF motifs shared with those identified at mSWI-SNF- bound sites (FIG.2, panel C), we also identified enrichment of TF motifs at sites of gained accessibility lacking mSWI/SNF complex occupancy, including motifs corresponding to early activation targets such as ZNF and DMRT, and exhaustion targets such as AIRE, MEF2, HLTF and ZIM3 (FIG.2, panel C). These data indicate that specific sites and genes are made accessible and activated, respectively, following initial mSWI/SNF targeting, which in turn generate secondarily accessible regions genome-wide that amplify state-specific programs. [00176] We next integrated gene expression profiling by RNA-seq at each time point with mSWI/SNF complex binding and accessibility. PCA analyses performed on RNA-seq data again indicated clear, stepwise changes in expression profiles, with greatest shifts between 0h/3h and 24h early activation (PC1) and exhaustion (PC2) (FIG.2, panels D-E; FIG.10, panel D). Given that TFs are considered as the main directive factors governing transcriptional programs in T cells, we first focused on the impact of mSWI/SNF complex occupancy and accessibility generation over expression of TF genes themselves. By integrating gene expression changes with fractional mSWI/SNF complex occupancy (i.e. enrichment of mSWI/SNF binding over a given TF motif genome-wide, relative to others), we identified AP-1 TF genes FOS, FOSB, FOSL1, ATF3 and BATF3 as upregulated mSWI/SNF targets during early activation and with reduced gene activation but retained fractional mSWI/SNF occupancy at late activation time points (FIG.2, panel F; FIG.10, panel E). Interestingly, in the exhausted state, we identified uniquely high mSWI/SNF occupancy at HNF1B motifs and significant changes in expression of the HNF1B gene (>3 DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 log2FC). In the memory-like state, we identified more subtle changes in TF gene expression, of RUNX1, STAT4, STAT6, TCF7L1, IRF1 genes coupled with more subtle changes in mSWI/SNF fractional enrichment (FIG.2, panel F; FIG.10, panel F). Lastly, visualization of mSWI/SNF complexes (SMARCA4, SS18), H3K27ac and ATAC-seq signal over key genes for activation (IFNG) and early and late exhaustion (CXCL13 and ENTPD1, encoding CD39) confirmed concomitant regulatory region and/or promoter mSWI/SNF binding and chromatin opening (FIG.2, panel G). [00177] BAF complexes are bound and active over HNF1B TF binding sites genome-wide in exhausted T cells [00178] Notably, examining the top 10% differentially upregulated genes across activation, intermediate activation, late activation, exhaustion, and memory states, we found that 23%, 14%, 29%, 40%, and 24% of upregulated gene loci, respectively, were occupied by mSWI/SNF complexes (FIG.3, panel A; FIG.10, panel F). Of note, mSWI/SNF occupancy was present over the greatest of percentage (40%) of loci corresponding to differentially upregulated genes in the exhaustion cell state (FIG.3, panel A), indicating a heightened role for mSWI/SNF complexes in the establishment and maintenance of the exhaustion transcriptional signature. Monitoring the gene expression changes of key mSWI/SNF target sites with high fractional enrichment as well as those genes within regions of increased accessibility revealed several hallmark genes of naïve, activated and exhausted T cells (FIG. 3, panel B). Genes known to be expressed in naïve T cells (such as IL7R, TCF7, SELL) had the highest expression at the no stimulation (0hr) time point, while levels of hallmark activation genes such as IFNG, IL2, PDCD1, CXCL13, GZMB, and LAG3 were most elevated at the 3- 72h time points (FIG.3, panel B; FIG.10, panels D,F). Importantly, key target genes most strongly upregulated in the exhaustion-like state (D6, D9-Ch) and which are used as clinically-relevant biomarkers of T cell dysfunction included TOX, ENTPD1, ITGA2 and TIGIT, bound by mSWI/SNF. Of note, additional key regulators such as HAVCR2, PRDM1 and CTLA4 were upregulated as secondary (non-mSWI/SNF bound) target genes (FIG.2, panel B). These studies therefore inform the chromatin landscape and gene regulatory signatures across T cell states, highlighting potential mSWI/SNF-directed changes, as well as those that occur as downstream consequences of altered mSWI/SNF occupancy and activity. [00179] Given the uniquely abundant collection of mSWI/SNF target genes hallmark to genes upregulated in the exhaustion-like state (FIG.3, panels A-B), we next compared the changes in gene expression across the time course with exhaustion and memory signatures derived from single-cell human tumor microenvironment transcriptomic datasets DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 81-85. Across single-cell datasets evaluated, exhaustion signatures were the most highly enriched over D6 and D9-Ch time point gene expression profiles derived from our T-cell stimulation system, while single-cell memory signatures were enriched in the naïve (unstimulated) and D9-Tr time points (FIG.10, panel G). Remarkably, Cluster 6 genes, genes with mSWI/SNF occupancy specifically at exhaustion time points (Day6 and Day9-ch, strongly enriched in HNF1B motifs) displayed significant enrichment in single-cell exhaustion signatures, indicating that a collection of genes expressed during exhaustion in the context of primary human tumors are mSWI/SNF targets (FIG.3, panel C; FIG.10, panels G-H). Further, we extracted single-cell chromatin accessibility profiles of intra-tumoral T cells from human basal cell carcinoma (BCC, Satpathy et al.) and clear cell renal cell carcinoma (ccRCC, Kourtis et al.) samples. UMAP projections identify distinct T cell subsets (FIG.3, panels D-E) and ChromVar analyses revealed enrichment of the HNF1B motif specifically in exhausted T cell states (FIG.3, panels D-E; FIG.10, panels I-J)22,61. [00180] Owing to these findings, we next profiled the occupancy of HNF1B using CUT&TAG at Day9-Ch and Day9-Tr T cell populations, which exhibit high and low expression of HNF1B, respectively (FIG.10, panel K). Indeed, HNF1B occupancy (CUT&TAG signal) from Day9-Ch T cells was most enriched over C6 (exhausted) BAF- bound accessible sites (FIG.3, panel F; FIG.10, panel L), exemplified at the ENTPD1 gene locus (FIG.3, panel G). Archetype and non-archetype motif enrichment analyses performed over HNF1B target sites and over HNF1B sites within C6 revealed co-enrichment of other exhaustion-associated TFs such as BATF, NR4A1/2, SOX4, PRDM1 and others (FIG.3, panel H; FIG.10, panel M). In line with this, sgRNA-mediated knockout of HNF1B in human CD8+ T cells resulted in reduced TIM3+PD1+ putative exhausted cells coupled with a doubling of activated/progenitor exhausted T cells (PD1+TIM3-) (FIG.3, panels I-J). However, HNF1B KO failed to generate a proliferative advantage (FIG.10, panel N). Further, RNA-seq analyses performed on Day9-Ch WT and HNF1B KO T cells revealed substantial downregulation of exhaustion-associated NR4A1-3 genes, and differential expression of cytokine genes such as GLNY (FIG.3, panel K). Other genes less well- characterized in the context of T cell exhaustion such as SASH1 and RHOU were strongly down-regulated. Finally, analysis of genes near C6 sites with HNF1B motif density and those containing HNF1B binding exhibiting reduced expression included those involved in metabolism, MAPK signaling, and immune system development (FIG.3, panel L; FIG.10, panel O). DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 [00181] Lastly, we identified TF motifs with accessibility gains or losses across the time course (relative to no stimulation) in the setting of mouse CD8+ T cells. Importantly, while the majority of TF motifs enriched under sites of mSWI/SNF occupancy were enriched similarly in human and mouse settings, a few notable exceptions included the exhaustion state (C6)-enriched HNF1B (homeodomain-containing Hd.10 factors) motifs, which were selectively enriched in the human setting (FIG.10, panels P-Q). Taken together, these data define the targeting specificities of mSWI/SNF complexes in a range of T cell states, indicating their potential roles in orchestrating the exhaustion expression signature. [00182] Chromatin-focused CRISPR/Cas9 screens identify cBAF components regulators of T cell exhaustion [00183] We next set out to comprehensively and unbiasedly characterize the potential roles for chromatin regulatory factors in modulating the exhaustion hallmarks of chronically- stimulated T cells 86-90. We generated constructs expressing RFP and a custom sgRNA library targeting 310 known epigenetic regulators, containing 6 sgRNAs per gene, non-targeting sgRNAs as negative controls, and sgRNAs targeting PD1 and HAVCR2 (TIM3) as positive controls (total: 1928 sgRNAs) for lentiviral infection. We then performed a CRISPR-Cas9- based screen in mouse CD8+ splenic T cells purified from Rosa26Cas9-EGFP mice (FIG.4, panel A) in which cells were activated for 24h, then transduced with the sgRNAs library, ensuring a proper library expression by day 3 of the activation protocol, then cultured according to the chronic stimulation protocol. At day 9, sgRNA-RFP+, PD1+TIM3+ T cells were sorted and sgRNA library representation was compared with the initial library representation. Quality control analyses of deep-sequenced sgRNAs libraries confirmed efficient capture of sgRNAs (97.6-99% of sgRNAs) and an even distribution of sgRNA sequences (Gini indexes: 0.05-0.09) (FIG.11, panel A). We then analyzed the genes whose sgRNAs were enriched or depleted in the PD1+TIM3+ population (FIG.4, panel B). Interestingly, most of the significant hits (abs Log2FC >1, FDR<0.05) were depleted (n=27), while only 2 hits in total were enriched, highlighting the wide-spanning, diverse chromatin- level contributions to T cell dysfunction. In addition to positive controls PD1 and Havcr2, depleted hits included genes encoding the mSWI/SNF complexes (Arid1a, Dpf2, Smarcc1, Smarca4), chromatin regulators involved in histone acetylation (Kat5, Kat8, Ep300, Hdac3), methylation (Kmt2d, Prmt5, Ezh2, Kdm1a, Kdm6a), and other processes, highlighting a range of epigenetic mechanisms playing potential roles in immune checkpoints associated with T cell exhaustion (FIG.4, panel B; FIG.11, panel B). Intriguingly, genes encoding mSWI/SNF complex subunits were among the top-scoring genes depleted in the PD1+/TIM3+ DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 population (Arid1a= rank 2, Dpf2= rank , 6, Smarcc1= rank 10 and Smarca4= rank 15), specifically, the cBAF complex43 (FIG.4, panels B-C; FIG.11, panel B). Arid1b, the paralog for Arid1a, was moderately depleted, but to a lesser extent given its lower expression and lower stoichiometric abundance in cBAF complexes in mouse T cells (FIG.11, panel C). PBAF- and ncBAF-specific subunits such as Arid2, Pbrm1, and Brd9 were also depleted, but to a more minimal extent. Taken together, these data highlight unbiasedly the role for the mSWI/SNF complexes, specifically, Arid1a- and Dpf2- containing cBAF complexes, as among the most significant determinants of exhausted-like cell state. [00184] To functionally validate top hits, we transduced two independent sgRNA-RFP plasmids into Cas9-EGFP T cells and evaluated for PD1+ and TIM3+ populations. We observed a reduction in the percentage of fully exhausted T cells (PD1+TIM3+) in the conditions of sgRNA-mediated depletion of pan-mSWI/SNF and cBAF-specific components at Day 9 post stimulation. In contrast, depletion of Arid2 resulted in similarly limited changes as in the sgROSA control condition (FIG.4, panel D; FIG.11, panel D). While no significant differences in percent sgRNA-RFP+ cells were identified before Day 9, pan- mSWI/SNF and cBAF subunit knock-out cells (but not PBAF or ncBAF KO cells) exhibited sustained proliferation at Day 9, indicating increased T cell persistence (FIG.4, panel E) as well as slight increases in the percentage of cells with a central memory (CM) phenotype (CD44+ CD62L+) cells (FIG.11, panel E) and a decrease in the killing capacity in the B16- OVA/OT-1 system at increasing Target-Effector (T-E) ratios, confirming a memory-like phenotype (FIG.11, panel F). Finally, to further evaluate these findings, we performed a second CRISPR screen in mouse CD8+ T cells in which we sorted for the top and bottom 15% TIM-3-expressing cells (FIG.11, panels G-H), which revealed similar results (FIG.11, panels I-K). [00185] We next sought to validate these findings using an independent system, based on chronic stimulation of mouse OT-1 CD8+ T cells through co-culture with B16 cells expressing the model antigen OVA (chronic stimulation) or B16 WT cells as control (transient stimulation) (FIG.11, panel L). Splenocytes from Rosa26Cas9-EGFP-OT-1 mice were incubated with the MHC-I-specific OVA peptide SIINFEKL for 48h to achieve T cell activation, then CD8+ T cells were purified, infected with sgRNAs, and co-cultured with B16 or B16-OVA cells (FIG.11, panel L). Here again, we observed a global decrease in T cell proliferation at Day9 of stimulation (FIG.11, panel M), upregulated PD1 and TIM3, and an effector phenotype (CD44+ CD62L-), indicative of exhaustion-like features (FIG.11, panel N). Consistent with our previous findings, silencing of Smarca4, Smarcc1 and Dpf2 led to DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 decreases in the percentage of PD1+TIM3+ cells and an increase in the CM population (CD44+/CD62L+) (FIG.11, panel O). Additionally, in this model we also detected increased persistence of chronically-, but not transiently-, stimulated T cells at days 9 and 11 upon sgRNA-mediated depletion of Smarcc1, Smarca4, and Dpf2 components (FIG.4, panel F). Finally, to validate these findings in human CD8+ T cells, we isolated CD8+ T cells from human PBMCs and electroporated the Cas9 ribonucleoprotein, and control (CTRL) or SMARCA4-targeting sgRNAs. Importantly, in the setting of SMARCA4 KO (FIG.11, panel P), we observed a decrease in the percentage of exhausted PD1+ TIM3+ T cells (FIG.4, panel G) as well as increased persistence of human CD8+ T cells over time (FIG.4, panel H). Taken together, these studies highlight the unique role for mSWI/SNF complexes, particularly cBAF complexes, in T cell exhaustion in concordance with the high degree of mSWI/SNF complex targeting and activity over genes central to the exhaustion program. [00186] Diverse mSWI/SNF ATPase-specific inhibitors and degraders attenuate T cell exhaustion and increase memory phenotypes [00187] We next sought to evaluate the impact of pharmacologic mSWI/SNF perturbation, using both small molecule allosteric inhibitors of SMARCA4/2 ATPase activity, CMP14 and FHT-1015, as well as degraders of the SMARCA4/2 ATPase protein subunits, ACBI1 and AU-15330, which result in the degradation of the entire 5-subunit ATPase module of mSWI/SNF complexes, in both human and mouse T cell systems43,57,91-94 . Of note, an analog of FHT-1015, FHD-286, recently entered Phase I clinical trials in the settings of hematologic and solid tumors (NCT04891757 and NCT04879017). [00188] We stimulated CD8+ T cells with CD3/CD28 beads for 3 days and added DMSO (control) or one of the four mSWI/SNF SMARCA4/2-targeting compounds at two different concentrations (50nM and 100nM) for an additional 6 days coupled with consistent stimulation, harvesting cells on day 9 post initial stimulation (FIG.5, panel A; FIG.12, panel A). Treatment with compounds (ACBI1, AU-15330, CMP14, and FHT-1015) resulted in statistically significant reductions of PD1+/TIM3+ exhausted T cell populations at 51.5%, 51.5%, 20%, and 50%, respectively, of exhausted T cells in the DMSO control treated conditions, consistently across donors (FIG.5, panels B-C; FIG.12, panel B). This was coupled with statistically significant increases in activated/progenitor exhausted T cells (PD1+/TIM3-) and lower levels of CD39, an additional marker of terminal exhaustion (FIG. 5, panels B-C; FIG.12, panels B-C). In addition, profiling of CD45RA and CCR7 indicated a decrease in the effector T cell pool, and an increase in both Effector Memory (EM) and Central Memory (CM) cells upon treatment with any ATPase-targeting compounds (FIG.12, DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 panels D-F). We also observed decreases in the expression of cytokines (IFN ^, TNF ^ or both) of T cells treated with compounds relative to DMSO-treated cells (FIG.13, panel A). Remarkably, while SMARCA4/2 degrader treatments did not significantly impact cell proliferation or viability until Day 9, we observed an increase in persistence in treated cells in culture across further stimulations (Fold differences: ACBI1: 6 to 20-fold; AU-15330: 5 to 13-fold; CMP14: 5 to 17-fold; FHT-1015: 2 to 5-fold) and a decrease in the percentage of Annexin-positive apoptotic cells in the treated conditions (FIG.5, panel D; FIG.13, panels B-C). [00189] To test whether mSWI/SNF PROTACs or inhibitors cannot only prevent the onset of exhaustion but also revert it, we activated human T cells, and treated with mSWI/SNF inhibitors or degraders at Day 3, 6 or 9. Intriguingly, while treatment starting at Day3 attenuated the onset of exhaustion, as assessed by FACS and cell proliferation, impact was reduced or absent if treatment was initiated at Day 6 or Day 9, respectively (FIG.13, panels D-E), indicating a narrowing window amenable to chromatin landscape modification during the progenitor exhausted-like (Day 6) to terminal exhaustion-like (Day 9) states. [00190] Finally, we performed parallel experiments using mouse OT-1 CD8+ T cells. Once more, in the mouse T cell context, treatment with CMP14 and FHT-1015 SMARCA4/2 ATPase inhibitors led to a reduction of PD1+TIM3+ cells and in markers reflecting cytokine secretion capabilities (FIG.13, panel F). Taken together, these results indicate that pharmacologic targeting of the SWI/SNF complex attenuates the onset of exhaustion hallmarks and promotes increased persistence and memory phenotypic features of both human and mouse T cells. [00191] Pharmacologic disruption of mSWI/SNF complex activity alters accessibility over TF motif sites and inhibits T cell exhaustion [00192] To dissect the mechanistic basis for the observed phenotypes following mSWI/SNF disruption in human T cells, we performed ATAC-seq and RNA-seq upon treatment with SMARCA4/2 ATPase degraders and inhibitors. Notably, PCA analyses performed on Day 9 (following three rounds of antigenic stimulation every 3 days, two of which were coupled with mSWI/SNF ATPase disruption (Days 3 and 6)) revealed dramatic differences in chromatin accessibility between control and treated cells, largely consistent between independent donors, with PC1 capturing the impact of SMARCA4/2 pharmacologic perturbation (FIG.6, panel A; FIG.14, panel A). Treatment with these compounds resulted in genome-wide decreases in accessibility, with sites affected being highly consistently DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 impacted across four compound treatment settings relative to control (FIG.6, panel B; FIG. 14, panels A-C). Notably, sites decreased in accessibility were most strongly enriched for motifs corresponding to the HNF1B TF, underscoring the function of mSWI/SNF complexes in mediating accessibility over genomic regions enriched in HNF1B sequences in an exhaustion state-specific manner (FIG.6, panel C). In addition, motifs corresponding to BATF, AP1, NFKB and FOX were also enriched over sites exhibiting decreased accessibility (ATAC-seq signal) following treatment (FIG.6, panel C). [00193] Chromatin accessibility changes upon treatment with ACBI1, AU-15330, CMP14 or FHT-1015 compared to control were highly concordant across the 9 clusters identified (FIG.1; FIG.6, panels D-E). Importantly, C6 exhaustion-associated sites exhibited decreases in accessibility of highest significance and magnitude, while C3 and C4 sites, which included sites broadly accessible during activation and exhaustion, decreased with lower fold changes (FIG.6, panels D-E), indicating that mSWI/SNF ATPase inhibition most strongly suppressed the accessibility over genomic regions enriched for exhaustion- associated genes as well as selected activation-associated genes (FIG.6, panel F). Interestingly, mSWI/SNF disruption moderately impacted accessibility (both increases and decreases) over naïve/memory-associated sites (C7 and C8), consistent with the fact that these cells gain memory-like features. Reflecting this, genes near sites increased for accessibility included TCF7, ID3, and KLF2, and those near sites reduced in accessibility upon SWI/SNF inhibition included SELL and BHLHE40 genes (FIG.6, panels D-F). Intriguingly, chromatin accessibility was markedly increased over genes within C1 and C9 clusters, perhaps in agreement with previous findings that cBAF complex perturbations result in enhanced abundance and function of ncBAF complexes over CTCF motifs, which we demonstrated were strongly enriched in the C9 cluster (FIG.2, panels A-B; FIG.10, panel B) 57. [00194] To further investigate the impact of mSWI/SNF pharmacologic inhibition on the attenuation of exhaustion-like T cell states, we next performed RNA-seq analyses to reveal changes in gene expression programs (FIG.14, panels D-E). PCA analysis revealed similarly changed profiles and high concordance between differentially-expressed genes across treatment conditions (FIG.14, panels F-G). Downregulated genes were enriched for those involved in immune-related pathways, key activation and exhaustion transcription factors, IFN ^ response and TNFα signaling via NfKB (FIG.14, panel H). Intriguingly, a subset of genes downregulated upon mSWI/SNF inhibition were those contained within DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 genomic regions losing DNA accessibility upon compound treatment (30.5% -49.6%) a subset of which (8%-16.3% of total downregulated genes) were genes whose loci were occupied by mSWI/SNF complexes in the exhausted state (C6) (FIG.6, panel F). Examples included ENTPD1, TIGIT, IFNG, and GZMB genes central to chronic activation and exhaustion, which demonstrated decreased accessibility and gene expression upon compound treatment (FIG.14, panel I). Interestingly, we also observed chromatin opening and enhanced gene expression at a smaller set of sites (FIG.14, panels A-C, E-I), exemplified over genes such as IRF1 (FIG.14, panel J), which can indicate a set of factors that facilitate the increased T cell persistence 95. [00195] Finally, we applied the Cluster 6 (C6) mSWI/SNF ATPase perturbation signature to differentially accessible and differentially expressed genes with the exhaustion and memory signatures derived from human single-cell tumor microenvironment transcriptomic datasets 41,81,83-85. Remarkably, treatment with four distinct mSWI/SNF- disrupting compounds showed negative enrichment of genes that define exhausted T cells, with a concomitant increase in gene expression related to memory genes (FIG.6, panels G- H). These data support a mechanism whereby mSWI/SNF inhibition or degradation attenuates the activation threshold of T cells, preventing them from undergoing exhaustion, and allows for maintenance of the memory-like phenotype with sustained proliferation capability over time. [00196] Finally, we performed ATAC-seq profiling in mouse CD8+ T cell treated with SMARCA4/2 ATPase inhibitors and found that sites reduced in accessibility were enriched for similar motifs, such as those corresponding to BATF, MYB, E2F, NFY factors, but not for HNF1B, once more confirming the specificity for a substantial collection of BAF target sites and TF activity in the human setting. Importantly, examining the gene expression changes across clusters of mSWI/SNF occupancy and accessibility in mouse cells (FIG.9, panel J), we identified the most strongly downregulated genes were again those in C6 (Day 9 stimulation), corresponding to the exhaustion-like state (FIG.14, panels K-L). [00197] Pharmacologic disruption of mSWI/SNF increases in vitro persistence during CAR-T cell generation and enhances T cell mediated anti-tumor efficacy in vivo [00198] CAR-T infusion products displaying decreased exhaustion and increased memory hallmarks have been demonstrated to have increased efficacy in vivo90,96-101. With the results described herein, we reasoned that pharmacologic mSWI/SNF complex perturbation can represent a viable approach to improve T cell fitness and prevent exhaustion during CAR-T cell manufacturing 102. CAR-T cells are routinely generated from both CD4+ DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 and CD8+ T cells at variable ratios and expanded using beads similar to those used in our in vitro exhaustion experiments 103,104. As CD4+ T cells have been implicated to be longer- lasting relative to CD8+ cells, detected even decades after tumor remission, we sought to understand whether CD4+ T cells displayed similar persistence and anti-exhaustion features as CD8+ T cells in response to mSWI/SNF inhibition 105,106 102. Treatment with the mSWI/SNF ATPase inhibitor and degrader compounds led to a significant reduction in exhaustion-associated PD1+TIM3+ and CD39+ populations and led to increased CD4+ T cell persistence (FIG.7, panels A-C), indicating that these treatments have the same outcome in both CD8+ and CD4+ lineages. [00199] We then generated CD19-CAR-T cells using total CD3+ T cells isolated from independent human donors and engineered to express CD19 CAR-T constructs, targeting the CD19 antigen on the surface of B cell neoplasms (FIG.7, panel D; FIG.14, panel M). Cells were expanded for 2 additional days, then treated with DMSO, SMARCA4/2 degraders ACBI1 or AU15330, and analyzed by flow cytometry for markers of T cell exhaustion at day10 (FIG.7, panels D-F). Remarkably, treatment of CAR-T cells with mSWI/SNF ATPase degraders resulted in marked depletion of exhaustion-associated PD1+TIM3+ and CD39+ populations (FIG.7, panels D-F), and increased persistence of CAR-T cells across two independent human T cell donors (FIG.7, panel G). These results indicate potential approaches in which CAR-T cells are expanded in the presence of SMARCA4/2 degraders or inhibitors, prior to infusion into patients. In an attempt to assess the potential duration of proliferative advantage of treated T cells once injected in vivo (where no inhibitor can be present), we released treatment at Day9 and monitored T cell proliferation. Cells retained a significant proliferation advantage compared to untreated cells for at least one week after treatment release (FIG.7, panel H). [00200] Finally, to assess the anti-tumor functionality of mSWI/SNF-inhibited T cells, we implemented an OVA antigen-expressing melanoma model (B16) with subsequent infusion of CD8+ T cells from OT-1 TCR transgenic mice. Intriguingly, pre-treatment of CD8+ OT-1 T cells with the FHT-1015 SMARCA4/2 ATPase inhibitors resulted in decreased levels of Day9 in vitro cell killing at 24 and 48 hour time points across a range of target:effector ratios relative to control treated T cells (FIG.14, panel N), consistent with results using cBAF subunit genetic depletion experiments. Importantly, OT-1 T cells pretreated with FHT-1015 significantly attenuated B16-OVA tumor growth in vivo relative to DMSO control-treated cells (FIG.7, panel I). Collectively, these experiments demonstrate DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 that T cells subjected to mSWI/SNF pharmacologic inhibition exhibit increased persistence coupled with enhanced anti-tumoral activities. [00201] Discussion [00202] In this study, we dissected the contribution of mSWI/SNF family complex targeting and activity to gene expression programs and functional phenotypes during a series of stepwise, distinct stages of T cell activation and exhaustion. Our efforts to probe the mechanistic contributions of mSWI/SNF chromatin remodeling complexes specifically were inspired by the recently-observed changes in genome-wide accessibility during T cell differentiation and in CAR-T cell populations 14-22, coupled with work by our group and others establishing mSWI/SNF complexes as major—perhaps the major— mediators of the establishment and maintenance of tissue-specific chromatin accessibility 57,59,63,107,108. Further, recent CRISPR-based screening studies begun to reveal roles for mSWI/SNF complexes in T cell exhaustion35,36, presenting opportunities to define their functional contributions. [00203] Our studies describe the chromatin, gene regulatory, phenotypic, and in vitro and in vivo functional impact of four independent small molecule inhibitors and degraders that have been biochemically and structurally confirmed to specifically target the mSWI/SNF SMARCA2/4 ATPases. Of note, and underscoring the clinical relevance of our findings, the FHT-1015 compound is an analog of the Phase I compound, FHD-286, currently being evaluated in the setting of human AML, MDS, and uveal melanoma 94. With these agents, we find highly similar chromatin accessibility and gene regulatory impacts, indicating that mSWI/SNF catalytic activity (ATPase and nucleosome remodeling) is equivalent to assembly and function of the entire ATPase module in this context. Degradation of SMARCA4/2 prevents assembly of ACTL6A, beta-actin, SS18, and BCL7 family subunits on to mSWI/SNF family complexes 43,109,110. [00204] Contrary to the challenges and associated safety concerns with respect to ectopic expression of cytokine receptors or DNMT3A deletion 8,111,112, we demonstrate here that mSWI/SNF complex perturbation can be achieved by small molecules, representing a potentially more facile, lower-cost, and safer approach to improve T cell fitness during the preparation of engineered T cells for cancer immunotherapy. Intriguingly, in both of our screens, Dnmt3a, which has been shown to contribute to T cell exhaustion in different model systems, was not depleted relative to mSWI/SNF genes, perhaps indicating relative contributions of these distinct epigenetic regulators to T cell exhaustion (log2FC PD1/TIM3 DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 screen, TIM3 screen only (DNMT3A)= 0.3, -0.2 vs ARID1A= -5.6, -3.1 and SMARCA4= - 2.6, -1.1) (FIG.4; FIG.11) 8,34,113,114. [00205] Based on a range of studies by our group and others, a model we put forward is one in which the precise activities of mSWI/SNF complexes are controlled, in large part, by the repertoire of TFs expressed in a given cell type, which collectively guide the positioning of complexes as a function of their protein-level abundance. Here, indeed, pharmacologic inhibition of mSWI/SNF complexes results in preferential closing of previously-accessible, complex-targeted regions that are enriched in DNA sequences (motifs) corresponding to highly specific TFs (FIG.6, panels C-D). In addition, small molecule inhibition resulted in minimal cell viability or apoptosis-related impacts at the time points assayed, further underscoring the preferential, skewed role for mSWI/SNF complex localization and activity over sites, in this case, that are instrumental in maintaining the T cell exhaustion program rather than those supporting cell homeostatic or proliferative programs (FIG.5, panel D; FIG.7, panels D-H; FIG.13, panels B-C). These data, coupled with immunophenotyping indicating decreased T cell exhaustion, indicate the favorable potential utility of mSWI/SNF inhibitors in the setting of ex vivo-manipulated CAR-T cells. Of note, our studies presented here center on evaluating whether mSWI/SNF inhibition (pre- treatment) can prevent exhaustion, however our studies indicate that they cannot revert exhaustion (FIG.13, panels D-E). This indicates that mSWI/SNF complexes can facilitate the stable binding of important TFs to genomic regions involved in T cell exhaustion; once the exhaustion program has been triggered, mSWI/SNF inhibition cannot be sufficient to displace those TFs. Additional studies employing a range of timepoints at which mSWI/SNF inhibitors are introduced and evaluated will be needed to more comprehensively address whether mSWI/SNF perturbation can revert the exhausted phenotype and restore the effector- function of tumor-infiltrating T cells in vitro and in vivo. [00206] We identify here several previously unknown, unexpected genomic features of the exhausted T cell state as well as determinants of exhaustion-specific mSWI/SNF targeting, such as the connection between mSWI/SNF occupancy and the uniquely strong enrichment of HNF1B transcription factor binding sequences. HNF1B is a heterodimeric TF (heterodimerizes with HNF1A) and was originally identified as a monogenic diabetes gene and characterized for its functions in the development of the pancreas, liver and in controlling insulin production 115. Of note, we found that HNF1B is not expressed in mouse T cells (FIG.10, panel K), which can reconcile why HNF1B was not previously identified in any CRISPR screen, which have been performed in the mouse T cell setting. Intriguingly, for DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 HNF1B in particular, mice with heterozygous mutations in HNF1B show no phenotype relative to that seen in humans 115. In solid tumors, HNF1B regulates glucose uptake, glucose metabolism and mitochondrial103,104,116-119. Chronically stimulated T cells are known to have rewired glucose metabolism, a higher rate of glycolysis and impaired OxPhos 104. GO analysis of predicted HNF1B directed targets (based on the identification of HNF1B motif in their promoter or regulatory regions) and of loci bound by both mSWI/SNF and HNF1B identified the MAPK signaling pathway as well as metabolic pathways as enriched processes (FIG.3, panel L), pointing toward a connection between HNF1B and T cell metabolism that can be further explored in functional studies to probe this chromatin remodeler-TF axis. [00207] In summary, our study shows the first comprehensive dissection of the mechanisms by which mSWI/SNF complexes regulate T cell activation and exhaustion, with chromatin profiling and small molecule inhibition experiments performed in human and mouse contexts, serving as a valuable set of resources for the field in dissecting chromatin regulatory determinants of T cell states and advancing new clinically-relevant strategies for improvement of adoptive cell therapy and immunotherapy. [00208] STAR Methods [00209] Key Resource Table REAGENT or RESOURCE SOURCE IDENTIFIER Antibodies 7 5 9 DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 PE/Cyanine7 anti-mouse IFN-γ BioLegend Cat# 505825; RRID:AB_1595591 PE/Cyanine7 anti-human CD3 BioLegend Cat# 317333; rg DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 Polybrene Santa Cruz Cat# SC-134220; Biotechnology CAS: 28728-55-4 TaKaRa Ex Taq DNA Polymerase Takara Bio Cat# RR001B 8- 8 6 1 01 0 0 DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 Cas9 Mice (Gt(ROSA)26Sortm1.1(CAG-cas9*,- The Jackson Jackson strain EGFP)Fezh/J) Laboratory #024858; RRID:IMSR_JAX:02 0 os ts g sp ut- g sp ut- 8 2 2 DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 Software and algorithms MAGECK MAGeCKFlute https://sourceforge.n package144 et/p/mageck/wiki/Ho al 3 a el 6 ab m 8 t/i 8 b d; 5 ur 5 je 1 c. 0 re 2 r. s ht 2 d 9 r. s 2. 7 ck .h dt / r. s a 8 DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 LOLA v1.12.0 Sheffield and Bock.140 https://bioconductor. org/packages/releas e/bioc/html/LOLA.ht 2 d 1 a. f_ or 5 .g /i [00210] EXPERIMENTAL MODEL AND SUBJECT DETAILS [00211] Primary cell lines [00212] Human peripheral blood mononuclear cells (PBMCs) isolated from 20- to 25- year-old male and female healthy donors were obtained through the New York Blood Center (NYBC). These de-identified human PBMC samples were collected under an IRB-exempt protocol with donors providing written consent for banking and research of their specimens. DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 For selected experiments in which high cell numbers were needed (Figures 1 and 4), CD8+ T cells isolated from healthy donors PBCMCs were purchased from StemCell (StemCell Technologies Inc, Cat# 70027). [00213] METHOD DETAILS [00214] Human CD8+ and CD4+ T cell isolation [00215] For T cell isolation, blood samples were diluted with 1 volume of PBS 2% FBS, then the diluted blood was added dropwise to 1 volume of Lymphoprep (Stemcell Technologies Inc, Cat# 07811) at room temperature. Samples were centrifuged at 800g for 20 minutes at 22 °C, then the PBMCs layer was harvested, washed two times in PBS 2% FBS, and resuspended in PBS 2% FBS. CD8+ T cells were then purified by two subsequent rounds of isolation: first, T cells were enriched using the Pan T Cell Isolation kit (Miltenyi Biotec, Cat# 130-096-535); then, negative CD8 T cell isolation was performed with the CD8+ T Cell Isolation Kit, human (Miltenyi Biotec, Cat# 130-096-495) or negative CD4 T cell isolation was performed with the CD4+ T Cell Isolation Kit, human (Miltenyi Biotec, Cat# 130-096- 533). Both enrichment steps were performed using an AutoMACS machine. For both mouse and human cells, CD8 T cell purity was assessed by FACS staining using mouse or human anti-CD3 and anti-CD8 antibodies at 1:100 dilution (PE/Cyanine7 anti-human CD3, BioLegend, # Cat317333; APC/Cyanine7 anti-mouse CD8a, BioLegend, Cat# 100714; FITC anti-human CD3, ThermoFisher Scientific, Cat#11-0038-42; PE/Cy7 anti-human CD8, Biolegend, Cat# 344712). Human CD4+ T cell purity was assessed using the A700 anti- human CD4 antibody, Biolegend, Cat# 317426 at 1:100 dilution. [00216] Mouse CD8+ T cell isolation [00217] Mouse CD8+ T cells were isolated from spleens and lymph nodes of male and female 8-12 weeks old C57BL/6J mice (Jackson strain #000664), C57BL/6- Tg(TcraTcrb)1100Mjb/J (OT-1 mice) (Jackson strain #003831), Gt(ROSA)26Sortm1.1(CAG-cas9*,-EGFP)Fezh/J (Cas9 mice) (Jackson strain #024858). Cas9-OT-1 mice were obtained by breeding OT-1 and Cas9 strains, and both Cas9 homozygous and heterozygous mice were used for experiments. Animals used were bred and maintained at NYU School of Medicine and experiments were performed in accordance with the Guidelines for the Care and Use of Laboratory Animals and approved by the Institutional Animal Care and Use Committees at NYU. For T cell isolation, organs were harvested and single cell suspensions were obtained by smashing and filtering through a 40 ^M strainer. In spleen samples, red blood cell lysis was performed by incubation in ACK lysis buffer DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 (Quality Biological Inc, Cat# 118156101C) for 1 minute, followed by resuspension in FACS buffer (PBS 2% FBS). Negative CD8+ T cell isolation was then performed with the CD8a+ T Cell Isolation Kit, mouse (Miltenyi Biotech, Cat #130-104-075), following the manufacturer’s instructions, utilizing an AutoMACS machine. [00218] In vitro T cell activation and exhaustion [00219] Mouse or human CD8+ T cells were cultured in RPMI media supplemented with 10% FBS, 1% Pen/Strep, 1X GlutaMAX (Life Technologies Cat# 35050061), 1X Non- essential Amino Acids (Life Technologies Cat# 11140050), 1X Sodium Pyruvate (Thermo Fisher Scientific Cat# MT25000CI) and 10mM 2-Mercaptoethanol (Life Technologies Cat# 21985023). Non-activated cells were maintained in culture for maximum 3 days in presence of 1ng/ ^l mouse or human IL7 (Murine IL-7, Peprotech, Inc., Cat# 217-17-50UG; Recombinant Human IL-7, Peprotech, Inc., Cat# 200-07-50UG), while activated cells were supplemented with 30U/ml mouse or human IL2 (Recombinant Murine IL-2, Peprotech, Inc., Cat# 212-12-50UG; Recombinant Human IL-2, Peprotech, Inc., Cat# 200-02-1MG). [00220] For in vitro T cell activation and exhaustion experiments, cells were thawed and plated at 1 million/ml in presence of Mouse T-Activator CD3/CD28 Dynabeads (Thermo Fisher Scientific, Cat# 11453D) or Human T-Activator CD3/CD28 Dynabeads (Thermo Fisher Scientific, Cat# 11132D) at 1:1 beads-to-cells ratio. After 2 days, cells were split 1:2 by adding fresh media. Beads were removed on day 3 and cells were replated at 0.5M/ml in presence of new beads at 1:1 ratio. Cells were split 1:3 on day 4 and 1:2 on day.5. Beads were removed again on day 6 and cells were replated at 0.5 million/ml in presence of new beads at 1:1 ratio. Cells were split 1:2 on day 7 and collected on day 9. For RNA-seq, ATAC- seq and C&T profiling, cells were harvested at 0h, 3h, 24h, 48h, 72h, 6 Days and 9 Days along this protocol. [00221] For long-term experiments in the presence of inhibitors or with genetic KO lines, cells were replated at 1M/ml on day 9 in presence of new beads at 1:1 ratio, then split 1:2 on day 10. Beads were removed on day 12 or 13 and cells were replated at 1M/ml in presence of new beads at 1:1 ratio. Cells were then harvested on day 15 or 16. At every time point, alive and dead cells were counted by diluting 10 ^l of cell suspension with 10ul of Trypan blue and analyzed on a Countess machine (Thermo Fisher Scientific). [00222] FACS staining [00223] For surface FACS staining, cells were harvested, washed in PBS 2% FBS (FACS buffer), incubated in Fc Block Solution (Human TruStain FcX™, BioLegend Cat# DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 422302) for 5 minutes, then incubated for 30 minutes at 4°C in FACS buffer with antibodies targeting the proteins of interest. Cells were washed two times in FACS buffer and diluted in FACS buffer supplemented with DAPI for live/dead cell exclusion. The following antibodies were used at 1:100 dilution unless stated otherwise: Brilliant Violet 605™ anti-human CD279 (PD-1) (BioLegend, Cat# 329923), APC/Cyanine7 anti-human CD366 (Tim-3) (BioLegend, Cat# 345025), Brilliant Violet 605™ anti-human CD197 (CCR7) (BioLegend, Cat# 353223), APC/Cyanine7 anti-human CD45RA (BioLegend, Cat# 304127), APC anti- human CD39 (BioLegend, Cat# 328209), APC/Cyanine7 anti-mouse CD279 (PD-1) (BioLegend, Cat# 135223, 1:200 dilution), PerCP/Cyanine5.5 anti-mouse CD366 (Tim-3) (BioLegend, Cat# 119717), APC anti-mouse CD62L (BioLegend, Cat# 104411, 1:400 dilution), PerCP/Cyanine5.5 anti-mouse/human CD44 (BioLegend, Cat# 103032). [00224] For intracellular cytokine profiling, cells were stimulated with Cell Stimulation Cocktail (Affymetrix, Cat# 00-4970-93) and supplemented with Brefeldin A (eBioscience Brefeldin A Solution, Life Technologies, Cat# 00-4506-51) for 3h at 37°C to block cytokine secretion. Cells were then harvested and stained with Zombie dyes for live/dead cell discrimination (Zombie Aqua™ Fixable Viability Kit, BioLegend, Cat# 423101 or Zombie Violet™ Fixable Viability Kit, BioLegend, Cat# 423113), following the manufacturer’s instructions. Fixation and permeabilization were then performed using the eBioscience Foxp3/Transcription Factor Staining Buffer Set kit (Life Technologies, Cat# 00- 5523-00), according to the manufacturer’s instructions. The following antibodies for intracellular FACS analyses were used at 1:100 dilution: PE anti-human TNF-α (BioLegend, Cat# 502908), Alexa Fluor® 700 anti-human IFN-γ (BioLegend, Cat# 506515), APC anti- mouse TNF-α (BioLegend, Cat# 506307), PE/Cyanine7 anti-mouse IFN-γ (BioLegend, Cat# 505825). Annexin staining was performed with APC Annexin V (BioLegend, Cat# 640920). Samples were analyzed using a Fortessa cytometer. [00225] Chromatin-focused CRISPR screen [00226] Library design. For designing a chromatin-focused CRISPR library, a list of epigenetic modifiers was first compiled based on literature search 120,121. Domain-focused sgRNA sequences were then designed using the Sanjana lab software, accessible through http://guides.sanjanalab.org/#/, with the option to target protein domains selected, and expression data and average data from tissues were used to pick and define exons. A target of 6 sgRNAs were generated per gene.60 non-targeting sgRNAs, as well as Pdcd1 and Havcr2 sgRNAs were added as controls. A ‘G’ was added at the 5’ of every sgRNA, if not already present. The following overhangs were then added: DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 AGGCACTTGCTCGTACGACGCGTCTCACACC – (sgRNA 20 nt) – GTTTCGAGACGATGTGGGCCCGGCACCTTAA. The final library consisted of 1928 sgRNAs targeting 310 protein-coding genes. [00227] Library cloning. sgRNA sequences were cloned in the pLKO5.sgRNA.EFS.tRFP plasmid (Addgene, Cat #57823) The plasmid was a gift from Bejamin Ebert. Briefly, plasmid restriction was performed with BsmBI-v2 (NEB, Cat# R0739L) for 2h at 55°C, then the digested plasmid was run on a 1% agarose gel and purified using the QIAquick Gel Extraction Kit (Qiagen, Cat# 28706X4). The sgRNA library was diluted to 1ng/ ^l in H20, then PCR amplified using the Phusion High-Fidelity PCR Kit (Life Technologies, Cat# F553S), with the following primers: Forward primer: AGGCACTTGCTCGTACGACG, Reverse primer: ATGTGGGCCCGGCACCTTAA. Two ng per reaction were used and five total (50 ^l) reactions were performed to ensure the maintenance of library representation. PCR conditions were the following: 30 seconds at 98 °C, then 10 seconds at 98 °C, 30 seconds at 53 °C, 30 seconds at 72 °C, for 24 cycles, then 5 minutes at 72 °C. The PCR product was then run on a 1% agarose gel and purified using the QIAquick Gel Extraction Kit (Qiagen, Cat# 28706X4). Cloning into the library vector was then performed using Golden Gate cloning, with the following protocol: 5 ^g digested vector, 500 ng PCR insert, 5 ^l Anza Esp1 enzyme (Life Technologies, Cat# IVGN0136), 5 ^l T4 DNA ligase (New England Biolabs, Cat# M0202L), 20ul Anza Buffer, 20 ^l 10mM ATP (New England Biolabs, Cat# PO756S), and H20 to 200ul final volume. The reaction was incubated for 30 minutes at 37 °C, then 30 minutes at 16 °C for 25 cycles. Samples were incubated with 1 ^l of Plasmid safe ATP-dependent Dnase (Thermo Fisher Scientific, Cat# E3101K) and incubated at 37 °C for 15 minutes. Reaction cleanup was then performed using the MinElute Reaction Cleanup Kit (Qiagen, Cat# 28204), and the elution product was electroporated into MegaX DH10B electro-competent bacteria (Life Technologies, Cat# C640003) using a BioRad Gene Pulser II Electroporation system. Following incubation at 37 °C for 1h, bacteria were plated in 4x24cm square LB plates containing Ampicillin and grown at 30°C for ~20h. The next day, bacteria were harvested from the plates and grown for 2 hours in 500ml liquid LB media with Ampicillin. Plasmid DNA was harvested using the PureLink™ HiPure Plasmid Filter Maxiprep Kit (Thermo Fisher Scientific, Cat#K21001). Library representation was checked by amplifying 200ng of library using the TaKaRa Ex Taq DNA Polymerase (Takara Bio, Cat# RR001B) for 15 cycles, and sequencing 10 million reads on a MiSeq 2 instrument, followed by alignment and QC using MAGECK. DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 [00228] CRISPR screen. For lentivirus production, HEK293T cells were plated in five 15 cm dishes (9 million cells each), in DMEM media supplemented with 10% FBS, 1% Pen/Strep and 1X Glutamax (Life Technologies, Cat# 35050061). The next day, cells were transfected using PEI (Polyethylenimine, Linear, Thermo Fisher Scientific, Cat# NC1014320) with the following plasmids (ug per plate): 15 ^g psPAX2 (Addgene, Cat#12260), 10 ^g pMD2G (Addgene, Cat#12259), and 20 ^g library plasmid. Media was changed 6h after transfection with HEK293T media, and again 24h after transfection with T cell media.48h after transfection, the viral supernatant was filtered through a 0.45 ^M filter and added dropwise to mouse CD8+ T cells pre-activated for 24h, in the presence of 5 ^g/ml Polybrene (Santa Cruz Biotechnology, Cat# SC-134220). The viral supernatant from each 15 cm dish was pooled and used to transduce 16 million T cells. Spin infection was performed by centrifuging at 1500g, for 60 minutes at 32°C. A second viral collection was performed 72h after transfection and a second round of spin infection was performed. After 2 days, cells were harvested, beads were removed, cells were washed two times in PBS and resuspended in media supplemented with DAPI. RFP+ cells were sorted using a SY3200 Cell Sorter. One million cells were then harvested to assess initial library representation (coverage = ~500x). Cells were then cultured as described in the ‘In vitro T cell activation and exhaustion’ section. At Day 9, cells were harvested and stained with PD1 and TIM3 antibodies and PD1 high TIM3 high or TIM3 low/high populations were sorted (1 to 2 million cells = coverage ~500-1000x). Genomic DNA was purified using the QIAamp DNA Mini Kit (Qiagen, Cat# 51304) and sgRNA sequences were amplified from genomic DNA using the TaKaRa Ex Taq DNA Polymerase (Takara Bio, Cat# RR001B). Five reactions per condition, each containing 1 ^g of genomic DNA, were performed to maintain library representation. The primers used were: [00229] P5 primers: equimolar mix of: For_01:AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGACGCTCT TCCGATCTCTTGTGGAAAGGACGAAACACC, For_02:AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGACGCTCT TCCGATCTACTTGTGGAAAGGACGAAACACC, For_03:AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGACGCTCT TCCGATCTGACTTGTGGAAAGGACGAAACACC, For_04:AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGACGCTCT TCCGATCTCGACTTGTGGAAAGGACGAAACACC, DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 For_05:AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGACGCTCT TCCGATCTACGACTTGTGGAAAGGACGAAACACC; [00230] P7 primers (indexed): [00231] IDX1:CAAGCAGAAGACGGCATACGAGATTCGCCTTGGTGACTGGAG TTCAGACGTGTGCTCTTCCGATCTCTCTACTATTCTTTCCCCTGCACTGT, [00232] IDX2:CAAGCAGAAGACGGCATACGAGATATAGCGTCGTGACTGGA GTTCAGACGTGTGCTCTTCCGATCTCTCTACTATTCTTTCCCCTGCACTGT, [00233] IDX4:CAAGCAGAAGACGGCATACGAGATATTCTAGGGTGACTGGA GTTCAGACGTGTGCTCTTCCGATCTCTCTACTATTCTTTCCCCTGCACTGT, [00234] IDX8:CAAGCAGAAGACGGCATACGAGATTTGAATAGGTGACTGGA GTTCAGACGTGTGCTCTTCCGATCTCTCTACTATTCTTTCCCCTGCACTGT. [00235] PCR conditions were the following: 1 minute at 95 °C, then 30 seconds at 95 °C, 30 seconds at 52 °C, 10 minutes at 72 °C, for 22 cycles, then 10 minutes at 72 °C. PCR product purification and size selection were performed using Ampure beads (Thermo Fisher Scientific, Cat# NC9933872), with right selection using beads at 0.4x ratio and left selection with beads at 0.6x ratio. Samples were sequenced at 10 million single-end reads each on a NextSeq500 instrument. [00236] Mouse CRISPR sgRNAs knock-out experiments [00237] For single gRNAs validations, two sgRNA sequences with the greatest efficiency per gene were identified within the CRISPR library, and individually cloned in the pLKO5.sgRNA.EFS.tRFP plasmid (Addgene, Cat #57823). Briefly, the plasmid was digested with BsmBI-v2 (NEB, Cat# R0739L) for 2h at 55°C, then run on a 1% agarose gel, followed by isolation from the gel band using the QIAquick Gel Extraction Kit (Qiagen, Cat# 28706X4). sgRNA oligos were phosphorylated and annealed by incubation in T4 PNK (New England Biolabs, Cat# VWR #101228-174) and T4 ligase buffer at 37°C for 30 minutes. Temperature was then gradually decreased (-1°C/minute) until room temperature. Oligos were diluted 1:200 in H20 and 1 ^l of diluted oligos were ligated with 25ng of digested vector for 1h at room temperature with T4 ligase (New England Biolabs, Cat# M0202M). Following transformation in Stbl3 cells, single colonies were analyzed by Sanger sequencing using a primer targeting the U6 promoter (sequence: GACTATCATATGCTTACCGT), expanded and purified using the PureLink™ HiPure Plasmid Filter Maxiprep Kit (Thermo Fisher Scientific, Cat#K21001). Lentiviral transduction was performed by transfecting HEK293T cells with 3.75 ^g psPAX2 (Addgene, Cat#12260), 2 ^g pMD2G (Addgene, Cat#12259), and DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 5 ^g library plasmid. Viral supernatant was collected 48h and 72h after transfection, filtered through a 0.45 ^M filter and used to spin-infect pre-activated mouse CD8+ T cells at 1500g, for 60 minutes at 32°C. RFP% was assessed using Fortessa machine at 3 day intervals post- activation in parallel with the in vitro exhaustion protocol. [00238] Human CRISPR sgRNAs knock-out experiments [00239] For sgSMARCA4 and sgHNF1B KO experiments in human cells, three CTRL or SMARCA4- or HNF1B-targeting sgRNAs were designed and synthetized by Synthego (https://www.synthego.com/products/crispr-kits/gene-knockout-kit). The Synthego-optimized multi-sgRNA approach was used, where the three different sgRNAs were co-electroporated in one reaction to increase knock-out efficiency. The SMARCA4-targeting sgRNA sequences were the following: ACUCCAGACCCACCCCUGGG, CCCUAGCCCGGGUCCCUCGC, GUCCUGCUGAGGGCGGCCCU. The HNF1B-targeting sgRNA sequences were the following: AGCCCUCGUCGCCGGACAAG, GGCCGAGCCCGACACCAAGC, CGGGGUCACCAAGGAGGUGC. [00240] Human CD8+ T cells were activated for 48h, then beads were removed, and 200,000 T cells were electroporated with a mix consisting of 1.5 ug of Cas9-GFP ribonucleoprotein (Integrated DNA Technologies, Cat#10008100) and 1ug of sgRNAs, using the Neon transfection system (1,200V, Width=40, 1 pulse). After electroporation cells were plated at 1 million/ml in antibiotics-free media. After 4 hours, cells were harvested and GFP+ cells were sorted. Cells were then replated at 1 million/ml with activation beads, and expanded through the in vitro exhaustion protocol. [00241] B16-OVA in vitro exhaustion model [00242] B16-F10 and B16-F10-OVA cell lines used for co-culture mediated T cell exhaustion were a gift of Dr. Weber’s lab. For B16-T cells co-cultures, splenocytes were harvested from OT-1/Cas9 mice and cultured at a concentration of 10 million/ml in T cell media in the presence of 1 ^M SIINKEFL peptide (OVA 257-264, Invivogen # vac-sin). After 48h, CD8+ T cells were purified with the CD8a+ T Cell Isolation Kit, mouse (Miltenyi Biotech, Cat #130-104-075), following the manufacturer’s instructions. Purified T cells were plated on 6-well plates containing B16 or B16-OVA cells, pretreated for 24h with 1ng/ ^l IFNg to promote MHCI expression. T cells were passaged on new B16 or B16-OVA plates, pre-treated with IFNg, every 48 hours. For CRISPR KO experiments in this model, cells were transduced as previously described following T cell purification, then cultured on B16 or B16-OVA plates and profiled 9 days after activation. DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 [00243] Western blots [00244] Western blots were performed as described previously 122. Briefly, proteins were isolated in RIPA buffer, quantified and loaded on 4%-12% Bis-Tris polyacrylamide gels (Thermo Fisher Scientific). Proteins were then transferred onto PVDF membranes (Millipore) and probed using the SMARCA4 antibody (Cell Signaling Technology Cat# 49360T, 1:1000 dilution), the anti-HNF1B antibody Proteintech Cat# 12533-1-AP, 1:1000 dilution) or the anti-Actin (Millipore Cat# MAB1501, 1:10000 dilution). Following incubation with horseradish peroxidase-conjugated secondary antibodies (GE Healthcare), chemiluminescence was assessed with ECL (Life Technologies). [00245] Cell killing assays [00246] Killing assays were performed in 96-well plates, by mixing 50000 B16 or B16-OVA cells (Target) and serial dilutions of OT-1 T cells (Effector) at Day9 of the chronic stimulation protocol, in 200 ul of RPMI media supplemented with 10% FBS, 1% Pen/Strep, 1X GlutaMAX (Life Technologies Cat# 35050061), 1X Non-essential Amino Acids (Life Technologies Cat# 11140050), 1X Sodium Pyruvate (Thermo Fisher Scientific Cat# MT25000CI) and 10mM 2-Mercaptoethanol (Life Technologies Cat# 21985023). Four replicates were seeded per condition, and controls containing B16 or B16-OVA without T cells were included. After 24h or 48h incubation at 37°C, media was removed, wells were washed twice in 200 ^l of PBS, then 100ul of PBS per well were added. CellTiterGlo (Promega Cat# G7571) was then added (100 ^l/well), plates were incubated for 10 minutes protected from light, and measured luminescence. [00247] CD19-CAR-T cell experiments [00248] For CAR-T experiments, we generated an anti-CD19 CAR lentiviral vector incorporating a 41BB co-stimulatory domain and CD3ζ activation domain. The single-chain variable fragment (scFv) was derived from the murine FMC63 anti-human antibody, that has high affinity and specificity for CD19 and it is utilized in clinical trials. The complete CAR construct is driven by an EF1α promoter and contains the internal ribosome entry site (IRES)- GFP signal for cell selection. The CAR-T vector was cloned in house in the Perna Lab (Indiana University). For CAR-Ts preparation, peripheral blood was obtained from de- identified healthy human volunteers under IRB-exempt protocol with written consent for banking and research of their specimens given for each donor. Peripheral blood mononuclear cells (PBMCs) were isolated by density gradient centrifugation, purified using the Human Pan T Cell Isolation Kit (Miltenyi Biotec, Cat#130-096-535), stimulated with CD3/CD28 T DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 cell activator Dynabeads (Thermo Fisher Scientific, Cat# 11132D) for 2 days and cultured in X-VIVO-15 media (Lonza Cat#BE02-060Q) supplemented with human serum (5%) and IL-2 (200U/ml). After 24 hours of activation, cells were transduced with lentiviruses encoding anti-CD19 CAR and GFP genes, in presence of polybrene. Transduction efficiencies were assessed by FACS and were ranging from 20 to 50%. Then, cells were counted and plated (0.5 million/ml) in the presence of beads, and DMSO or PROTACS, ACBI1 or AU-15330 (100nM). The same process was repeated at 3-4 days intervals. At Day 10, beads were removed and immunophenotype was analyzed by flow-cytometry using the following markers: CCR7, CD45RA, PD1, TIM3, LAG-3, CD39 (vendors and catalogs previously stated in methods). To assess in vitro persistence, cells were incubated with fresh beads at 3- days intervals and counted at Day 13 and 16. [00249] In vivo B16-OVA killing assays [00250] For in vivo experiments, 8-12 weeks-old Rag1KO mice B6.129S7- Rag1<tm1Mom>/J (Jackson # 002216), were injected subcutaneously with 0.5 million B16- OVA cells in 100 ^l PBS. The same day, mouse CD8+ OT-1 T cells were purified from 8-12 week old OT-1 mice, and activated in vitro with CD3/CD28 Dynabeads at 1:1 ratio. After 72h, beads were removed, cells were counted and plated with fresh beads at 1:1 ratio in presence of DMSO or FHT-1015 at 100nM. Cells were split 1:2 or 1:3 every day by adding fresh media and DMSO or FHT-1015. At Day 7, T cells were washed in PBS, counted and 2 million cells were injected intravenously into tumor bearing mice. Tumor growth was assessed by caliper measurement every 3 days. [00251] SMARCA4/SMARCA2 Inhibitor and Degrader Small Molecule Treatment Studies [00252] For inhibitor and small-molecule PROTAC treatments, mouse or human T cells were activated for 3 days as previously described. At Day 3, cells were counted and plated at 0.5 million /ml in presence of DMSO, 50nM or 100nM of inhibitor or PROTAC. At every subsequent time point (Days 6, 9, 12, 16), beads were removed and cells were replated at 0.5M/ml in presence of inhibitors or PROTACs and fresh beads at 1:1 ratio. Cells were diluted 1:2 or 1:3 in between time points by adding media containing the corresponding concentration of inhibitor or PROTAC. The drugs used were: ACBI1 (SelleckChem, Cat#S9612), AU-15330 (MedChem Express Llc, Cat #HY-145388), CMP14 (synthesized), FHT-1015 (synthesized). [00253] RNA-seq DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 [00254] For RNAseq experiments, 50.000 to 0.5 million cells were harvested on ice and washed in cold PBS. RNA extraction was then performed using the Rneasy Plus Mini Kit (Qiagen Cat#74136), following the manufacturer’s instructions. Poly-A selection was performed using the the Nebnext Poly(A) mRNA Magnetic Isolation Module (New England Biolabs Cat#E7490) for RNAseq experiments, except the RNAseq upon PROTAC treatment experiment, where NEXTFLEX® Poly(A) Beads 2.0, (Perkin Elmer Cat#NOVA-512991) were used. Library preparation was performed using the Nebnext Ultra II Directional RNA Library Prep Kit (New England Biolabs Cat# E7760), or NEXTFLEX® Rapid Directional RNA-Seq Kit 2.0 (Perkin Elmer Cat#NOVA-5198-01) for PROTAC experiments. For libraries, quality was assessed by Tapestation. Samples were sequenced on NovaSeq6000 and NextSeq500 machines (Illumina) at sequencing depth of 30 million reads per sample. [00255] ATAC-seq [00256] Cells were harvested at 0h, 3h, 24h, 48h, 72h, Day6 and Day9. ATAC-seq experiments were completed and samples were prepared into libraries using the previously described methodology 67,68,123. Cells (50,000) were collected in media and washed in cold PBS. Cells were spun at 500rcf for 5 minutes to form a pellet and PBS was removed. Cold lysis buffer was added and cells were gently resuspended by pipetting. Resuspended cells were incubated on ice for three minutes. Lysis was quenched by adding wash buffer and mixing by inverting the tube three times. Lysed material was pelleted at 400 rcf for 10 minutes, and supernatant was discarded. The pelleted DNA was resuspended in transposition reaction buffer and the transposition reaction was carried out for 30 minutes at 37°C with gentle shaking at 1,000 rpm on a thermomixer. The resultant tagmented DNA was purified using Qiagen MinElute Reaction clean up kit (Qiagen Cat# 28206) and eluted in dH20. Tagmented DNA libraries were amplified with 7 total cycles using a standard ATAC-seq amplification protocol and custom PCR primers. ATAC-seq libraries were sequenced on the Illumina NextSeq500 with 35 base-pair paired end sequencing parameters and using the NextSeq™ 500/550 High output flow cell kit (Illumina Cat# 20024906). [00257] Cut & Tag [00258] The epicypher protocol for Cleavage under targets and tagmentation was used with slight modifications 66. Concanavalin A (ConA, BioMag®Plus Cat# 86057) beads were activated with bead activation buffer and stored on ice until further use. Cells (100,000) were collected and washed with cold PBS. Cells were spun at 300rcf for 5 minutes at 4°C and PBS supernatant was removed from the cell pellet. Nuclear extraction buffer was added to the tube and the pellet was gently resuspended by pipetting to lyse cells and extract nuclei. Activated DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 ConA beads and nuceli were incubated were mixed and incubated at room temperature for 10 minutes. The nuclei-conjugated bead complexes were resuspended in antibody binding buffer and add primary antibody rotating on a nutator overnight at 4°C (Added 2.5, 0.5, 0.25, 0.25, 0.67 and 0.25 ug of IgG, kH3K27Ac, Brg1, SS18, ARID1A, and PBRM1 respectively). Primary antibody mixture was removed, and nuclei-bead complexes were incubated with 0.5 ^g secondary antibody in digitonin 150 buffer for 1 hour at room temperature on the nutator. After secondary antibody incubation, samples were washed with digitonin 150 buffer and resuspended in digitonin 300 buffer supplemented with 2 microliters of CUTANA pAG- Tn5 (Epicycpher Cat#15-1117) added per sample. Samples were incubated with Tn5 for 1 hour at room temperature on the nutator. Digitonin 300 buffer was added two times to remove excess enzyme from samples. Targeted chromatin tagmentation was completed following the epicypher protocol. Libraries were amplified with 14 PCR cycles and purified by single sided 1.3x AMPure bead purification. The NextSeq500 and 35 base-pair paired end sequencing parameters were used for library sequencing. [00259] QUANTIFICATION AND STATISTICAL ANALYSIS [00260] NGS Data Processing [00261] Cut and Tag, ATAC-Seq, and RNA-Seq samples were sequenced with the Illumina technology, and output data were demultiplexed using the bcl2fastq software tool. RNA-Seq reads were aligned to the hg19 genome with STAR v2.5.2b 124, and tracks were generated using the deepTools v2.5.3 bamCoverage function 125. For ATAC-Seq data, quality read trimming was carried out by Trimmomatic v0.36126, followed by alignment, duplicate read removal, and read quality filtering using Bowtie2 v2.29127, Picard v2.8.0128, and SAMtools v 0.1.19129, respectively, and ATAC-seq broad peaks were called with the MACS2 v2.1.1 software 130 using the BAMPE option and a broad peak cutoff of 0.001. For ATAC-Seq track generation, output BAM files were converted into BigWig files using MACS2 and UCSC utilities 131 in order to display coverage throughout the genome in RPM values. For Cut and Tag libraries, the CutRunTools pipeline was leveraged to perform read trimming, quality filtering, alignment, peak calling, and track building using default parameters 132. Sequencing data analyzed in this study have been deposited at NCBI’s Gene Expression Omnibus under accession number GSE212357. [00262] RNA-seq data analysis [00263] For RNA-seq data, output gene count tables from STAR based on alignments to the hg19 reflat annotation were used as input into edgeR v3.12.1133 to obtain normalized DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 log CPM values and to evaluate differential gene expression. Log2 fold change values from edgeR were used as input into GSEA 134, and the GseaPreranked tool was run with default settings to measure gene set enrichment. For day 9 treatment comparisons, the DESeq2 v1.30.1 R software package was used to evaluate differential gene expression 135. For heatmaps displaying differentially expressed genes, log CPMs were transformed into Z- scores followed by hierarchical or K-means clustering. In order analyze gene set enrichment for select subsets of genes, hypergeometric tests were performed on overlaps with various MSIGDB gene sets and select enriched gene sets were displayed. Principle components analysis was performed using the wt.scale and fast.svd functions from the corpcor R package on RPKM values 136,137, which were quantified using median length isoforms and total mapped read counts computed by the Samtools idxstats function. [00264] Cut & Tag and ATAC-seq Data Analysis and Integration [00265] The Bedtools multiIntersectBed and mergeBed functions were used for peak merging 138, and the R package, ChIPpeakAnno v3.17.0139, was used to visualize peak overlaps. Distance-to-TSS peak distributions were computed utilizing Ensembl protein- coding gene coordinates. To generate the heatmap in Figure 1D, which served as a platform for several downstream analyses, first, 32 sets of peaks derived from the SS18 and SMARCA4 samples (called by the CutRunTools pipeline) from both donors and from time points were merged with the Bedtools multiIntersectBed function. Since there wsere two donors for every timepoint, we removed any peaks or parts of peaks that did not overlap with at least one peak to remove outlier peaks and outlier peak segments. This overlap information from the 32 sets of peaks was provided by the output of the Bedtools multiIntersectBed function. After the outlier peaks and outlier peak segments were removed, the Bedtools mergeBed function was used to merge the filtered peaks. In an identical manner, the peaks of the H3K27ac and ATAC-seq samples were separately merged. Second, these three sets of merged peaks from time points were overlapped and merged to generate the Venn Diagram in Figure S2I, which represent the sites in the Figure 1D heatmap. Third, the Cut & Tag and ATAC-seq RPKM data from the merged peaks were log2 transformed, followed by the separate quantile normalization of each BAF subunit, H3K27ac, and ATAC- seq data across time points. Finally, K-means clustering was applied in a semi-unsupervised manor to partition the SMARCA4, SS18, H3K27ac and ATAC-seq data into the 9 groups or clusters, which are exhibited in FIG.1, panel D, followed by transformation into Z-scores across timepoints to highlight the differences within clusters among time points. DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 [00266] IgG control subtraction and data normalization. CUT&TAG datasets from two independent human T cell donors were merged and RPKM values were computed for SMARCA4, SS18, H3K27Ac and IgG samples for each timepoint across the T cell activation and exhaustion time course (described herein). The RPKM values for each mark were log2- transformed and individually subjected to quantile normalization. Quantile-normalized IgG signals were then subtracted from the SMARCA4, SS18, and H3K27Ac quantile-normalized signals. From here, for selected figure panels, quantile-normalized, IgG-subtracted signal values were separately transformed into Z-scores for timepoints. Finally, IgG control peaks that were present and overlapped SMARCA4, SS18 and H3K27Ac merged sites were removed, while maintaining the order of the non-overlapping sites. Heatmaps were generated from the resultant non-overlapping and IgG-subtracted sites. [00267] Principle component analyses (PCA) were also performed on these quantile- normalized log2-transformed RPKM values. For day 9 treatment analyses, DESeq2 was used to evaluate differential accessibility, and quantile-normalized log2 RPKM values were transformed into Z-scores following by hierarchical clustering to display differentially accessible sites. [00268] Transcription Factor Motif and Archetype Analyses [00269] Transcription factor enrichment and motif analyses were carried out by the LOLA v1.12.0140 and HOMER v4.9141 software packages, respectively. In addition to using HOMER to analyze motif enrichment, for several motif enrichment analyses conducted in this study, we determined the number of motif occurrences for 286 non-redundant archetype consensus motifs 142 within +/- 250 base pairs of peak centers for each peak within given peak sets. The coordinates of these archetype motifs as well as non-archetype motifs across the entire human and mouse genomes can be downloaded from the following resource https://www.vierstra.org/resources/motif_clustering#downloads. [00270] Average archetype and non-archetype motif occurrences and densities within sites and within clusters of sites were also determined, and fractional enrichment values relative to sites were displayed for select motifs with high occurrence and variability. The following formulas were used to compute motif densities and enrichment. [00271] 1. [00272] Site Motif ‘X’ Occurrence [00273] = # of Motif X Counts within +/- 250 base pairs within center of Site [00274] 2. [00275] Total Motif ‘X’ Density DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 [00276] = [Total Sum of Motif X Counts at All Sites] / [Total # of All Sites] [00277] 3. [00278] Cluster ‘Y’ Motif ‘X’ Density [00279] = [Total Sum of Motif X Counts at Cluster Y Sites] / [Total # of Cluster ‘Y’ Sites] [00280] 4. [00281] Cluster ‘Y’ Motif ‘X’ Density Difference = [00282] = [Cluster ‘Y’ Motif ‘X’ Density] – [Total Motif ‘X’ Density] [00283] 5. [00284] Cluster ‘Y’ Motif ‘X’ Fractional Enrichment [00285] = [Cluster ‘Y’ Motif ‘X’ Density Difference] / [Total Motif ‘X’ Density] [00286] [00287] These archetype motif fraction enrichment values in clusters were also plotted against corresponding TF gene log fold change values for several stepwise comparisons across the T-cell activation and exhaustion time course. For logistic regression analyses on archetype motifs, matrices of motif counts for given merged peaks were generated, and the R software program GLMnet 143 was used to produce logistic regression models to fit the motif counts to binomial vectors where 1’s represented sites with BAF or ATACseq log2 fold changes > 0. Divergent barplots were used to display large coefficients in output models to estimate the influence of motifs on BAF occupancy or accessibility in terms of magnitude, directionality and predictability. [00288] CRISPR screen data analysis [00289] Data analysis was performed using MAGECK 144, following the standard analysis pipeline reported in https://sourceforge.net/p/mageck/wiki/Home/. Data visualization was performed using the Bioconductor MAGeCKFlute package. [00290] scRNAseq and scATACseq datasets and analyses [00291] scRNA-seq. scRNAseq signatures consisted of the marker genes identified in exhausted or memory cells from the several literature sources 81,82,84,85,145. These gene lists were used as “gene set” inputs into GSEA along with log2 fold change values from edgeR for expressed genes for several given comparisons , and the GseaPreranked tool was run with default settings to measure gene set enrichment134. A positive score indicates an enrichment of genes within a given gene set that have increasing expression, while a negative score indicates an enrichment of genes within a given gene set that have decreasing expression. GSEA output normalized enrichment scores or regular enrichment scores were displayed in DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 heatmaps. Negative log base 10 p-values from select the indicated gene sets were displayed in barplots. [00292] scATAC-seq. 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Nature Methods 14, 975-978.10.1038/nmeth.4401. ***** EQUIVALENTS [00440] Those skilled in the art will recognize, or be able to ascertain, using no more than routine experimentation, numerous equivalents to the specific substances and procedures described herein. Such equivalents are considered to be within the scope of this invention, and are covered by the following claims.

Claims

DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 What is claimed: 1. A method of preventing T cell exhaustion, the method comprising treating T cells with a SWI/SNF complex modulator. 2. A method of modulating T cell activation, the method comprising treating T cells with a SWI/SNF complex modulator. 3. A method of preventing T cell exhaustion in a subject, the method comprising administering to the subject a therapeutically effective amount of a SWI/SNF complex modulator. 4. A method of improving T cell expansion in a subject, the method comprising treating the T cells with an effective amount of a SWI/SNF complex modulator. 5. A method of treating a subject afflicted with a disease or disorder exacerbated by T cell exhaustion, the method comprising administering to the subject a therapeutically effective amount of a SWI/SNF complex modulator. 6. The method of any one of claims 1, 2, or 4, wherein treating comprises incubating a population of T cells with the SWI/SNF complex modulator. 7. The method of any one of claims 1-5, wherein the SWI/SNF complex modulator comprises an inhibitor or a degrader. 8. The method of any one of claims 1-5, wherein the SWI/SNF complex modulator comprises a chromatin modifying agent. 9. The method of any one of claims 1-5, wherein the SWI/SNF complex modulator comprises a modulator of a cBAF subunit. 10. The method of any one of claims 1-5, wherein the SWI/SNF complex modulator comprises ARID1A, ARID1B, DPF2, DPF3, BCL11A, BCL11B, or any combination thereof. DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 11. The method of any one of claims 1-5, wherein the SWI/SNF complex modulator comprises an ATPase modulator. 12. The method of claim 11, wherein the ATPase comprises SMARCA2, SMARCA4, or both. 13. The method of any one of claims 1-5, wherein the SWI/SNF complex modulator comprises a degrader directed to the SWI/SNF complex, a nucleic acid molecule targeting the SWI/SNF complex, a compound or prodrug thereof that binds to the SWI/SNF complex, or a pharmaceutically acceptable salt or ester of said compound or prodrug. 14. The method of any one of claims 1-5, wherein the SWI/SNF complex comprises canonical BAF (cBAF), polybromo-associated BAF (PBAF), or non-canonical BAF (ncBAF). 15. The method of any one of claims 1, 3 or 5, wherein T cell exhaustion is indicated by decreased proliferation, increased expression of immune checkpoint molecules, decreased cytokine production, increased expression and/or protein levels of transcription factors, or any combination thereof. 16. The method of claim 15, wherein the transcription factors comprise HNF1B, TOX, NFATC1, IRF4, BATF, MYB NR4A1/2, SOX4, PRDM1, or any combination thereof. 17. The method of claim 13, wherein the SWI/SNF complex modulator targets SMARCA4, ARID1A, SS18, PBRM1, or any combination thereof. 18. The method of claim 13, wherein the nucleic acid molecule comprises a siRNA, miRNA, shRNA, antisense RNA, guide RNA (gRNA), single guide RNA (sgRNA), modified forms thereof, or any combination thereof. 19. The method of claim 13, wherein the compound comprises a structure according to: DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 R1 N O S N F F or a derivative or analog thereof. 20. The method of claim 13, wherein the compound comprises: Cl N O S N F ,
DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 or or a derivative or analog thereof. 21. The method of any one of claim 1, 2, or 4, wherein the T cell is CD4+, CD8+, CD3+ panT cells, or any combination thereof. 22. The method of any one of claim 1, 2, or 4, wherein the T cell comprises a chimeric antigen receptor (CAR) T cell. 23. The method of claim 22, wherein the CAR T cell comprises a CD19-CAR-T cell. 24. The method of any one of claims 1-5, wherein the method comprises an in vitro, ex vivo, or in vivo method. 25. A T cell produced by the method of claim 1 or claim 2. DOCKET NO: 5031461-000146-WO1 DATE OF FILING: February 19, 2024 26. A cellular therapy comprising the T cell of claim 25 and a pharmaceutically acceptable carrier, excipient, or diluent. 27. A method of treating a subject afflicted with a disease or disorder exacerbated by T cell exhaustion, the method comprising administering to a subject the T cell of claim 25 or the cellular therapy of claim 26. 28. A kit comprising the T cell of claim 25 or the cellular therapy of claim 26. 29. The method of any one of claims 3, 4 or 5, wherein the subject is afflicted with a disease or disorder exacerbated by T cell exhaustion. 30. The method of any one of claims 3, 4 or 5, wherein the disease or disorder comprises a cancer or an infection. 31. The method of claim 4, wherein the method further comprises obtaining T cells isolated from a subject prior to the treating step. 32. The method of 4, wherein the method further comprises treating the T cells with the modulator. 33. The method of claim 4, wherein the method further comprises administering the treated T cells to the subject.
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