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Wherry, E. J.

Publications and source records attributed to Wherry, E. J..

At least 37 records · Page 2Linked to original sources

The transcription factor BATF pioneers the differentiation program of cytolytic effector CD8+ T cells through the direct interaction with IRF4

The transcription factor BATF plays critical roles in the differentiation of various immune cells, including CD8+ T cells. Here, we demonstrated that BATF controls epigenomic and transcriptomic reprogramming of CD8+ T cells at an early phase of acute viral infection, thereby promoting the differentiation of cytolytic effector CD8+ T cells. Loss of BATF drastically perturbed gene expression, chromatin accessibility, and the bindings of key transcription factors including Jun, T-bet, and IRF4. The direct interaction with IRF4 was essential for BATF-mediated effector differentiation, as the BATF mutant lacking this interaction failed to induce proper chromatin remodeling and proliferation of antigen-specific CD8+ T cells. Notably, IRF4 binding was exhaustively dependent on BATF, whereas BATF retained binding capacity even in IRF4-deficient CD8+ T cells. Furthermore, BATF initiated chromatin remodeling in the absence of IRF4, whereas subsequent dynamic epigenomic reorganization required IRF4. Our data proposed that BATF serves as a "pioneer transcription factor" spearheading the reorganization of chromatin architecture upon antigen encounter, followed by further rearrangement of epigenomic and transcriptomic landscapes through the cooperation with IRF4.

immunology↗

Automated Cytometric Gating with Human-Level Performance Using Bivariate Segmentation

Recent advances in cytometry technology have enabled high-throughput data collection with multiple single-cell protein expression measurements. The significant biological and technical variance between samples in cytometry has long posed a formidable challenge during the gating process, especially for the initial gates which deal with unpredictable events, such as debris and technical artifacts. Even with the same experimental machine and protocol, the target population, as well as the cell population that needs to be excluded, may vary across different measurements. To address this challenge and mitigate the labor-intensive manual gating process, we propose a deep learning framework UNITO to rigorously identify the hierarchical cytometric subpopulations. The UNITO framework transformed a cell-level classification task into an image-based semantic segmentation problem. For reproducibility purposes, the framework was applied to three independent cohorts and successfully detected initial gates that were required to identify single cellular events as well as subsequent cell gates. We validated the UNITO framework by comparing its results with previous automated methods and the consensus of at least four experienced immunologists. UNITO outperformed existing automated methods and differed from human consensus by no more than each individual human. Most critically, UNITO framework functions as a fully automated pipeline after training and does not require human hints or prior knowledge. Unlike existing multi-channel classification or clustering pipelines, UNITO can reproduce a similar contour compared to manual gating for each intermediate gating to achieve better interpretability and provide post hoc visual inspection. Beyond acting as a pioneering framework that uses image segmentation to do auto-gating, UNITO gives a fast and interpretable way to assign the cell subtype membership, and the speed of UNITO will not be impacted by the number of cells from each sample. The pre-gating and gating inference takes approximately 2 minutes for each sample using our pre-defined 9 gates system, and it can also adapt to any sequential prediction with different configurations.

immunology↗

TET2 regulates early and late transitions in exhausted CD8+ T-cell differentiation and limits CAR T-cell function

CD8+ T-cell exhaustion hampers disease control in cancer and chronic infections and limits efficacy of T-cell-based therapies, such as CAR T-cells. Epigenetic reprogramming of CAR T-cells by targeting TET2, a methylcytosine dioxygenase that mediates active DNA demethylation, has shown therapeutic potential; however, the role of TET2 in exhausted T-cell (TEX) development is unclear. In CAR T-cell exhaustion models and chronic LCMV infection, TET2 drove the conversion from stem cell-like, self-renewing TEX progenitors towards terminally differentiated and effector (TEFF)-like TEX. In mouse T-cells, TET2-deficient terminally differentiated TEX retained aspects of TEX progenitor biology, alongside decreased expression of the transcription factor TOX, suggesting that TET2 potentiates terminal exhaustion. TET2 also enforced a TEFF-like terminally differentiated CD8+ T-cell state in the early bifurcation between TEFF and TEX, indicating a broad role for TET2 in mediating the acquisition of an effector biology program that could be exploited therapeutically. Finally, we developed a clinically actionable strategy for TET2- targeted CAR T-cells, using CRISPR/Cas9 editing and site-specific adeno-associated virus transduction to simultaneously knock-in a CAR at the TRAC locus and a functional safety switch within TET2. Disruption of TET2 with this safety switch in CAR T-cells restrained terminal TEX differentiation in vitro and enhanced anti-tumor responses in vivo. Thus, TET2 regulates pivotal fate transitions in TEX differentiation and can be targeted with a safety mechanism in CAR T-cells for improved tumor control and risk mitigation. One Sentence SummaryModulation of exhausted CD8+ T-cell differentiation by targeting TET2 improves therapeutic potential of CAR T-cells in cancer.

immunology↗

Single-cell Masked Autoencoder: An Accurate and Interpretable Automated Immunophenotyper

High-throughput single-cell cytometry data are crucial for understanding involvement of immune system in diseases and responses to treatment. Traditional methods for annotating cytometry data, specifically manual gating and clustering, face challenges in scalability, robustness, and accuracy. In this study, we propose a cytometry masked autoencoder (cyMAE), which offers an automated solution for immunophenotyping tasks including cell type annotation. The cyMAE model is designed to uphold user-defined cell type definitions, thereby facilitating easier interpretation and cross-study comparisons. The cyMAE model operates on a pre-train and fine-tune approach. In the pre-training phase, cyMAE employs Masked Cytometry Modelling (MCM) to learn relationships between protein markers in immune cells solely based on protein expression, without relying on prior information such as cell identity and cell type-specific marker proteins. Subsequently, the pre-trained cyMAE is fine-tuned on multiple specialized tasks via task-specific supervised learning. The pre-trained cyMAE addresses the shortcomings of manual gating and clustering methods by providing accurate and interpretable predictions. Through validation across multiple cohorts, we demonstrate that cyMAE effectively identifies co-occurrence patterns of bound labeled antibodies, delivers accurate and interpretable cellular immunophenotyping, and improves the prediction of subject metadata status. Specifically, we evaluated cyMAE for cell type annotation and imputation at the cellular-level and SARS-CoV-2 infection prediction, secondary immune response prediction against COVID-19, and prediction of the infection stage in COVID-19 progression at the subject-level. The introduction of cyMAE marks a significant step forward in immunology research, particularly in large-scale and high-throughput human immune profiling. This approach offers new possibilities for predicting and interpreting cellular-level and subject-level phenotypes in both health and disease.

bioinformatics↗

Deep Phenotyping of the Lipidomic Response in COVID and non-COVID Sepsis

Lipids may influence cellular penetrance by pathogens and the immune response that they evoke. Here we find a broad based lipidomic storm driven predominantly by secretory (s) phospholipase A2 (sPLA2) dependent eicosanoid production occurs in patients with sepsis of viral and bacterial origin and relates to disease severity in COVID-19. Elevations in the cyclooxygenase (COX) products of arachidonic acid (AA), PGD2 and PGI2, and the AA lipoxygenase (LOX) product, 12-HETE, and a reduction in the high abundance lipids, ChoE 18:3, LPC-O-16:0 and PC-O-30:0 exhibit relative specificity for COVID-19 amongst such patients, correlate with the inflammatory response and link to disease severity. Linoleic acid (LA) binds directly to SARS-CoV-2 and both LA and its di-HOME products reflect disease severity in COVID-19. AA and LA metabolites and LPC-O-16:0 linked variably to the immune response. These studies yield prognostic biomarkers and therapeutic targets for patients with sepsis, including COVID-19. An interactive purpose built interactive network analysis tool was developed, allowing the community to interrogate connections across these multiomic data and generate novel hypotheses.

systems biology↗

Signal recovery in single cell batch integration

Data integration to align cells across batches has become a cornerstone of single cell data analysis, critically affecting downstream results. Yet, how much biological signal is erased during integration? Currently, there are no guidelines for when the biological differences between samples are separable from batch effects, and thus, data integration usually involve a lot of guesswork: Cells across batches should be aligned to be "appropriately" mixed, while preserving "main cell type clusters". We show evidence that current paradigms for single cell data integration are unnecessarily aggressive, removing biologically meaningful variation. To remedy this, we present a novel statistical model and computationally scalable algorithm, CellANOVA, to recover biological signal that is lost during single cell data integration. CellANOVA utilizes a "pool-of-controls" design concept, applicable across diverse settings, to separate unwanted variation from biological variation of interest. When applied with existing integration methods, CellANOVA allows the recovery of subtle biological signals and corrects, to a large extent, the data distortion introduced by integration. Further, CellANOVA explicitly estimates cell- and gene-specific batch effect terms which can be used to identify the cell types and pathways exhibiting the largest batch variations, providing clarity as to which biological signals can be recovered. These concepts are illustrated on studies of diverse designs, where the biological signals that are recovered by CellANOVA are shown to be validated by orthogonal assays. In particular, we show that CellANOVA is effective in the challenging case of single-cell and single-nuclei data integration, where the recovered biological signals are replicated in an independent study.

bioinformatics↗

In Vitro Modeling of CD8 T Cell Exhaustion Enables CRISPR Screening to Reveal a Role for BHLHE40

Identifying novel molecular mechanisms of exhausted CD8 T cells (Tex) is a key goal of improving immunotherapy of cancer and other diseases. However, high-throughput interrogation of in vivo Tex can be costly and inefficient. In vitro models of Tex are easily customizable and quickly generate high cellular yield, offering an opportunity to perform CRISPR screening and other high-throughput assays. We established an in vitro model of chronic stimulation and benchmarked key phenotypic, functional, transcriptional, and epigenetic features against bona fide in vivo Tex. We leveraged this model of in vitro chronic stimulation in combination with pooled CRISPR screening to uncover transcriptional regulators of T cell exhaustion. This approach identified several transcription factors, including BHLHE40. In vitro and in vivo validation defined a role for BHLHE40 in regulating a key differentiation checkpoint between progenitor and intermediate subsets of Tex. By developing and benchmarking an in vitro model of Tex, we demonstrate the utility of mechanistically annotated in vitro models of Tex, in combination with high-throughput approaches, as a discovery pipeline to uncover novel Tex biology.

immunology↗

The pseudokinase Trib1 regulates the transition of exhausted T cells to a KLR+ CD8+ effector state and its deletion improves checkpoint blockade

T cell exhaustion (TEX) impairs the ability of T cells to clear chronic infection or cancer. While exhausted T cells are hypofunctional, some exhausted T cells retain effector gene signatures, a feature that is associated with expression of KLRs (killer lectin-like receptors). Although KLR+ T cells may improve control of chronic antigen, the signaling molecules regulating this population are poorly understood. Using scRNA-seq, flow cytometry, RNA velocity, and scTCR-seq, we demonstrate that deleting the pseudokinase Trib1 shifts TEX towards CX3CR1+ intermediates (TINT) with robust enrichment of KLR+CD8+ T cells (TKLR) via clonal T cell expansion. These changes are associated with globally increased KLR gene expression throughout the exhaustion program. Further, Trib1 loss augments anti-PD-L1 blockade to improve viral clearance by expanding the TKLR population. Together, these data identify Trib1 as an important regulator of T cell exhaustion whose targeting enhances the KLR+ effector state and improves the response to checkpoint inhibitor therapy.

immunology↗

Prior vaccination enhances immune responses during SARS-CoV-2 breakthrough infection with early activation of memory T cells followed by production of potent neutralizing antibodies

SARS-CoV-2 infection of vaccinated individuals is increasingly common but rarely results in severe disease, likely due to the enhanced potency and accelerated kinetics of memory immune responses. However, there have been few opportunities to rigorously study early recall responses during human viral infection. To better understand human immune memory and identify potential mediators of lasting vaccine efficacy, we used high-dimensional flow cytometry and SARS-CoV-2 antigen probes to examine immune responses in longitudinal samples from vaccinated individuals infected during the Omicron wave. These studies revealed heightened Spike-specific responses during infection of vaccinated compared to unvaccinated individuals. Spike-specific CD4 T cells and plasmablasts expanded and CD8 T cells were robustly activated during the first week. In contrast, memory B cell activation, neutralizing antibody production, and primary responses to non-Spike antigens occurred during the second week. Collectively, these data demonstrate the functionality of vaccine-primed immune memory and highlight memory T cells as rapid responders during SARS-CoV-2 infection.

immunology↗

Human T follicular helper clones seed the germinal center-resident regulatory pool

How FOXP3+ T follicular regulatory (Tfr) cells simultaneously steer antibody formation toward microbe/vaccine recognition and away from self-reactivity remains unsettled. To explore human Tfr cell provenance, function and location heterogeneity, we used paired TCRVA/TCRVB sequencing to distinguish tonsillar Tfr cells clonally related to natural Tregs (nTfr) from those likely induced from Tfh cells (iTfr). The proteins iTfr and nTfr cells differentially expressed were utilized to pinpoint their in situ locations via multi-plex microscopy and establish divergent functional roles. In-silico and tonsil organoid tracking models corroborated the existence of separate Treg-to-nTfr and Tfh-to-iTfr developmental trajectories. In total, we have identified human iTfr cells as a distinct CD38-expressing, GC-resident, Tfh-descended subset that gains suppressive function while retaining capacities for B-cell help whereas CD38- nTfr cells are elite suppressors primarily localized to follicular mantles. Interventions differentially targeting Tfr subsets may provide therapeutic opportunities to boost immunity or more precisely treat autoimmune diseases. One sentence summaryHuman tonsillar Tfr clones descend from either Treg or Tfh lineages and provenance predicts their TCR repertoires, locations and functional characteristics.

immunology↗

Distinct Heterogeneity in the Naive T cell Compartments of Children and Adults

AbstractThe naive T cell compartment undergoes multiple changes across age that associate with altered susceptibility to infection and autoimmunity. In addition to the acquisition of naive-like memory T cell subsets, mouse studies describe substantial molecular reprogramming of the naive compartment in adults compared with adolescents. However, these alterations are not well delineated in human aging. Using a new trimodal single cell technology (TEA-seq), we discovered that the composition and transcriptional and epigenetic programming of the naive T cell compartment in children (11-13 yrs) is distinct from that of older adults (55-65 yrs). Naive CD4 T cells, previously considered relatively resistant to aging, exhibited far more pronounced molecular reprogramming than naive CD8 T cells, in which alterations are preferentially driven by shifts in naive-like memory subsets. These data reveal the complex nature of the naive T cell compartment that may contribute to differential immune responses across the spectrum of human age. One Sentence SummaryThe naive CD8 and CD4 T cell compartments in humans are heterogeneous and impacted differently with age, in which naive CD8 T cell subsets dramatically shift in composition and true naive CD4 T cells display significant molecular re-programming.

immunology↗

A long interval between priming and boosting SARS-CoV-2 mRNA vaccine doses enhances B cell responses with limited impact on T cell immunity

Spacing the first two doses of SARS-CoV-2 mRNA vaccines beyond 3-4 weeks raised initial concerns about vaccine efficacy. While studies have since shown that long-interval regimens induce robust antibody responses, their impact on B and T cell immunity is poorly known. Here, we compare in SARS-CoV-2 naive donors B and T cell responses to two mRNA vaccine doses administered 3-4 versus 16 weeks apart. After boost, the longer interval results in higher magnitude and a more mature phenotype of RBD-specific B cells. While the two geographically distinct cohorts present quantitative and qualitative differences in T cell responses at baseline and after priming, the second dose led to convergent features with overall similar magnitude, phenotype and function of CD4+ and CD8+ T cell responses at post-boost memory timepoints. Therefore, compared to standard regimens, a 16-week interval has a favorable impact on the B cell compartment but minimally affects T cell immunity.

immunology↗

Induction of a CD8 T cell intrinsic DNA damage and repair response is associated with clinical response to PD-1 blockade in uterine cancer.

Despite the success of immune checkpoint blockade (ICB), many patients fail to achieve durable clinical benefit, and the underlying immunological mechanisms remain poorly understood. Here, we investigated immune reinvigoration by ICB in advanced or recurrent hypermutated or microsatellite instability-high, mismatch repair deficient (MSI-H/MMRd) uterine cancer patients treated with anti-PD-1 (nivolumab). CD8 T cells underwent rapid pharmacodynamic proliferation 2-4 weeks after initiating PD-1 blockade. This immunological response, however, did not correlate with clinical response. We hypothesized that the T cell-intrinsic response to proliferative and genotoxic stress might contribute to the disparity between immunological and clinical response. We developed a high-dimensional single cell cytometric platform to simultaneously analyze T cell differentiation with changes in DNA damage and repair (DDR) pathways. This DDR-Immune platform revealed T cell subset-specific patterns of DDR, and distinct DDR pathways induced by different types of DNA damage. Applying this platform to MSI-H/MMRd or hypermutated uterine cancer patients revealed a signature of DDR exemplified by rapid increase in phosphorylated-ATM (pATM) intrinsic to CD8 T cells proliferating in response to PD-1 blockade that distinguished clinical responders and non-responders. ATM regulated transcriptional circuits in T cells were associated with better clinical response to PD-1 blockade. These findings highlight a previously unrecognized role for CD8 T cell-intrinsic DDR as a potential determinant of immune fitness and clinical outcome of PD-1 blockade therapy. STATEMENT OF SIGNIFICANCEUsing high-dimensional immune and DNA damage response (DDR) profiling in T cell subsets we identified distinct signatures in anti-PD-1 treated MSI-H/hypermutated uterine cancer patients associated with clinical response versus non-response. Thus, T cell-intrinsic DDR is a potential determinant of immune responsiveness and clinical outcome to PD-1 blockade therapy in cancer.

immunology↗

Longitudinal single cell transcriptional and epigenetic mapping of effector, memory, and exhausted CD8 T cells reveals shared biological circuits across distinct cell fates

Naive CD8 T cells can differentiate into effector (TEFF), memory (TMEM), or exhausted (TEX) CD8 T cells. These developmental pathways are associated with distinct transcriptional and epigenetic changes that endow cells with different functional capacities and therefore therapeutic potential. The molecular circuitry underlying these developmental trajectories and the extent of heterogeneity within TEFF, TMEM, TEX populations remain poorly understood. Here, we used the lymphocytic choriomeningitis virus model of acutely-resolved and chronic infection and addressed these gaps by applying longitudinal scRNA-seq and scATAC-seq analysis. These analyses uncovered new subsets, including a subpopulation of TEX expressing NK cell-associated genes, as well as multiple distinct TCF1+ stem/progenitor-like subsets in acute and chronic infection. These data also revealed insights into the reshaping of TEX subsets following PD1 pathway blockade and identified a key role for the cell stress regulator, Btg1, in TEX differentiation. Finally, these results highlighted how the same biological circuits such as cytotoxicity or stem/progenitor pathways can be used by CD8 T cells with highly divergent underlying chromatin landscapes. Thus, this transcriptional and chromatin accessibility landscape map elucidates developmental biology and underlying mechanisms governing TEFF, TMEM, and TEX differentiation.

immunology↗

Efficient recall of Omicron-reactive B cell memory after a third dose of SARS-CoV-2 mRNA vaccine

Despite a clear role in protective immunity, the durability and quality of antibody and memory B cell responses induced by mRNA vaccination, particularly by a 3rd dose of vaccine, remains unclear. Here, we examined antibody and memory B cell responses in a cohort of individuals sampled longitudinally for [~]9-10 months after the primary 2-dose mRNA vaccine series, as well as for [~]3 months after a 3rd mRNA vaccine dose. Notably, antibody decay slowed significantly between 6- and 9-months post-primary vaccination, essentially stabilizing at the time of the 3rd dose. Antibody quality also continued to improve for at least 9 months after primary 2-dose vaccination. Spike- and RBD-specific memory B cells were stable through 9 months post-vaccination with no evidence of decline over time, and [~]40-50% of RBD-specific memory B cells were capable of simultaneously recognizing the Alpha, Beta, Delta, and Omicron variants. Omicron-binding memory B cells induced by the first 2 doses of mRNA vaccine were boosted significantly by a 3rd dose and the magnitude of this boosting was similar to memory B cells specific for other variants. Pre-3rd dose memory B cell frequencies correlated with the increase in neutralizing antibody titers after the 3rd dose. In contrast, pre-3rd dose antibody titers inversely correlated with the fold-change of antibody boosting, suggesting that high levels of circulating antibodies may limit reactivation of immunological memory and constrain further antibody boosting by mRNA vaccines. These data provide a deeper understanding of how the quantity and quality of antibody and memory B cell responses change over time and number of antigen exposures. These data also provide insight into potential immune dynamics following recall responses to additional vaccine doses or post-vaccination infections. Graphical Summary O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=123 SRC="FIGDIR/small/481163v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@123d2d9org.highwire.dtl.DTLVardef@e7db82org.highwire.dtl.DTLVardef@1fc73deorg.highwire.dtl.DTLVardef@11b21f9_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

Divergent clonal differentiation trajectories of T cell exhaustion

T cells activated by chronic antigen exposure in the setting of viral infections or cancer can adopt an exhausted T cell (Tex) state, characterized by reduced effector function and proliferative capacity, and the upregulation of inhibitory receptors. However, whether all antigen-specific T cell clones follow the same molecular and cellular Tex differentiation trajectory remains unclear. Here, we generate a single-cell multi-omic atlas of T cell exhaustion that redefines the phenotypic diversity and molecular regulation of Tex phenotypes. Longitudinal analysis during chronic viral infection identifies an early effector phenotype that is epigenetically primed for Tex differentiation and two late-stage Tex cell states with either a terminal exhaustion or a killer cell lectin-like receptor (KLR)-expressing cytotoxic gene signature. We define clonal trajectories of antigen-specific T cells using paired single-cell RNA and T cell receptor sequencing and reveal distinct differentiation trajectories resulting in terminal Tex-biased, KLR Tex-biased, or divergent clones that differentiate into both phenotypes. Comparison of Tex phenotypes among shared T cell clones that traffic to multiple organs reveals that clonal differentiation trajectories are maintained across tissues. Finally, we show that differences in clonal differentiation trajectory are driven by TCR signal strength, whereby high-affinity T cell clones preferentially adopt a terminal Tex fate, while low-affinity clones adopt an effector-like KLR Tex fate that is detectable long-term but depleted in high antigen settings. These findings reveal clonal heterogeneity in the T cell response to chronic antigen and genomic programs that underlie Tex fates and persistence. HighlightsO_LIA single-cell atlas of T cell exhaustion identifies novel early effector and KLR Tex states. C_LIO_LIClonal T cell analysis defines divergent differentiation trajectories during chronic viral infection leading to terminal and KLR Tex fates. C_LIO_LIThe heterogeneity of the Tex pool arises from three primary differentiation patterns and are differentially persistent in the setting of high antigen. C_LIO_LIClonal Tex differentiation patterns are conserved across organ sites and driven by TCR signal strength. C_LI

immunology↗

A statistical framework for differential pseudotime analysis with multiple single-cell RNA-seq samples

Pseudotime analysis with single-cell RNA-sequencing (scRNA-seq) data has been widely used to study dynamic gene regulatory programs along continuous biological processes. While many computational methods have been developed to infer the pseudo-temporal trajectories of cells within a biological sample, methods that compare pseudo-temporal patterns with multiple samples (or replicates) across different experimental conditions are lacking. Lamian is a comprehensive and statistically-rigorous computational framework for differential multi-sample pseudotime analysis. It can be used to identify changes in a biological process associated with sample covariates, such as different biological conditions, and also to detect changes in gene expression, cell density, and topology of a pseudotemporal trajectory. Unlike existing methods that ignore sample variability, Lamian draws statistical inference after accounting for cross-sample variability and hence substantially reduces sample-specific false discoveries that are not generalizable to new samples. Using both simulations and real scRNA-seq data, including an analysis of differential immune response programs between COVID-19 patients with different disease severity levels, we demonstrate the advantages of Lamian in decoding cellular gene expression programs in continuous biological processes.

genomics↗

Decade-long remissions of leukemia sustained by the persistence of activated CD4+ CAR T-cells

The adoptive transfer of T lymphocytes reprogrammed to target tumor cells has demonstrated significant potential in various malignancies. However, little is known about the long-term potential and the clonal stability of the infused cells. Here, we studied the longest persisting CD19-redirected chimeric antigen receptor (CAR) T cells to date in two chronic lymphocytic leukemia (CLL) patients who achieved a complete remission in 2010. CAR T-cells were still detectable up to 10+ years post-infusion, with sustained remission in both patients. Surprisingly, a prominent, highly activated CD4+ population developed in both patients during the years post-infusion, dominating the CAR T-cell population at the late time points. This transition was reflected in the stabilization of the clonal make-up of CAR T-cells with a repertoire dominated by few clones. Single cell multi-omics profiling via Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-Seq) with TCR sequencing of CAR T-cells obtained 9.3 years post-infusion demonstrated that these long-persisting CD4+ CAR T-cells exhibited cytotoxic characteristics along with strong evidence of ongoing functional activation and proliferation. Our data provide novel insight into the CAR T-cell characteristics associated with long-term remission in leukemia.

immunology↗