Cytokines dimerize two receptor chains to activate Janus kinases and signal transducer and activator of transcription (STAT) transcription factors that regulate immune cells, but they have therapeutic liabilities. We engineered "Trikines" to compel cis formation of three-chain cytokine receptor complexes at the cell surface that induce bespoke STAT transcriptional signaling programs. Trikines coactivated phosphorylation of STAT5 (pSTAT5) and pSTAT3 signatures distinct from natural cytokines by assembling trimeric combinations of interleukin-2 (IL-2), IL-10, and IL-21 receptors. In preclinical models, an IL-2-based Trikine restrained terminal differentiation of T cells, promoted stemness, and enhanced durability of tumor control without observable toxicity. An IL-10-based Trikine induced immune infiltration into poorly immunogenic tumors, showing efficacy in preclinical models of small cell lung cancer and pancreatic cancer. Trikines obviate the need for cell engineering to customize STAT signatures and may hold potential for immunotherapy.

Current US Food and Drug Administration-approved chimeric antigen receptor (CAR) T cell therapies for B cell leukemias and lymphomas target CD19, which is widely expressed across the B cell lineage, often leading to on-target, off-tumor B cell depletion, prolonged immune suppression, and antigen-negative escape in a subset of patients. In contrast, B cell receptor (BcR) signaling is essential for the survival of most mature B cell neoplasms, and BcRs carrying the immunoglobulin heavy variable gene IGHV4-34 are highly enriched in B cell malignancies compared with normal B cells. Further, self-reactive IGHV4-34+ serum autoantibodies are enriched in aggressive systemic lupus erythematosus (SLE) and other autoimmune diseases. Here, we developed CAR T cells targeting the BcR carrying IGHV4-34 (CART4-34). We found that CART4-34 showed specific cytotoxicity and cytokine secretion toward IGHV4-34+ malignant B cells. In addition, although CD19 was down-regulated upon relapse after treatment with CART19, IGHV4-34+ BcR levels remained intact upon relapse after treatment with CART4-34, suggesting reduced risk of antigen-negative escape. In IGHV4-34+ HBL1 cell line-derived xenograft mouse models, CART4-34 showed robust expansion and antitumor activity comparable to those of CART19. Optimized CAR:BcR binding using shorter CAR hinge domains improved immune synapse morphology and in vivo activity. In addition, we showed that CART4-34 could target human IGHV4-34+ SLE B cells and deplete IGHV4-34+ autoantibodies ex vivo, without targeting healthy B cells or affecting total IgG titers. In conclusion, we developed a CAR T cell product that specifically targets pathogenic B cells in lymphoid malignancies and SLE, offering potential for precision cell therapy for these indications.

Blocking the programmed cell death 1 (PD-1) pathway using monoclonal antibodies reinvigorates exhausted T cells (Tex), enhancing control of chronic viral infections and cancer. Considerable effort has focused on evaluating different PD-1 blockade agents in preclinical and clinical cancer settings, but relatively little information exists on how to optimize the pharmacodynamic effects of PD-1 pathway blockade on reinvigorating Tex. To address this question, we performed longitudinal tracking of Tex reinvigoration during chronic infection with lymphocytic choriomeningitis virus (LCMV) following different regimens of PD-1 blockade. We compared single-cycle (2 weeks of treatment), long-term continuous PD-1 pathway blockade (i.e. 3 months), or blockade followed by a drug holiday and then re-blockade (intermittent treatment). These studies revealed little benefit of continuous versus single-cycle PD-1 blockade, with both resulting in a single peak of Tex reinvigoration and similar effects on viral replication. In contrast, intermittent blockade resulted in a new cycle of secondary Tex reinvigoration upon redosing after a washout and this secondary Tex reinvigoration improved disease control. Mechanistically, long-term blockade eroded the ability of Tex progenitor cells (Tpex) to give rise to downstream, more functional Tex intermediate (Tex-Int) progeny, whereas the drug holiday restored this Tpex proliferative and differentiation capacity. Tpex from long-term treated mice showed evidence of adaptive resistance and additional layers of negative regulation, including sustained expression of the inhibitory receptor CD22. Indeed, co-blockade of PD-1 and CD22 using combination antibodies or bispecific antibody approaches improved disease control and reinvigoration of Tex. These data have implications for clinical immune pharmacodynamics of PD-1 blockade and provide insights into the biology of Tex reinvigoration. One Sentence Summary:Modifying the immunopharmacology of PD-1 blockade reveals a benefit of a drug holiday and identifies mechanisms of Tex progenitor deficiency provoked by prolonged loss of PD-1 signals including the inhibitory receptor CD22.

Selective in vivo reprogramming of cytotoxic effector CD8 T (Teff) cells holds tremendous promise as a therapeutic tool but has not yet been accomplished. Here, we demonstrate that fractalkine-conjugated mRNA lipid nanoparticles (mRNA-LNPs) can specifically target and deliver mRNA to CX3CR1+ Teff cells in vitro and in vivo. In mice, fractalkine-conjugated mRNA-LNPs targeted up to 95% of blood and splenic Teff cells. In addition, delivery of IL-2-encoding mRNA and human CD62L-encoding mRNA to mouse Teff cells enabled robust exogenous IL-2 secretion and CD62L expression. In rhesus macaques, fractalkine-conjugated mRNA-LNPs targeted up to ~100% of peripheral blood Teff cells, and delivery of human CD62L-encoding mRNA enabled cell-surface human CD62L expression on peripheral blood Teff cells and detection of human CD62L+ Teff cells in lymphoid tissue. Collectively, these data demonstrate the potential of natural receptor ligand-based targeting of mRNA-LNPs for rapid, efficient, and transient in vivo modification of Teff cells.

Chimeric antigen receptor (CAR) T-cell therapy holds great promise for patients with cancer, and the identification of predictive biomarkers is crucial in finding new ways to guide therapy. Major challenges to the application of informatics and machine learning in CAR T-cell therapy include limited sample sizes and non-uniformity in data generation across cancer indications and trials. Here we took a global, pan-haematologic cancer approach, analysing 256 patients across 5 cancer types and 13 clinical trials. We generated data using a framework that included pre-infusion clinical features, over 2 million apheresis T cells analysed by flow cytometry using 17 unique markers, ex vivo T-cell expansion during CAR T-cell manufacture, more than 90,000 measurements of 30 serum markers and serial tracking of circulating CAR T cells using qPCR. From this data resource, we demonstrate the potential of pan-cancer predictive biomarkers that capture generalizable characteristics of treatment response and non-response in CAR T-cell therapy.

Human papillomavirus-associated oropharyngeal squamous cell carcinoma (HPV+ OPC) is driven by viral E6 and E7 oncoproteins, which disrupt G1 checkpoint control and impose selective dependency on WEE1-mediated G2/M regulation. While this vulnerability confers sensitivity to WEE1 inhibition, its immunologic consequences remain poorly defined, and the challenge of eliciting antitumor immunity without compromising immune fitness has limited clinical translation. Here, we show that WEE1 inhibition elicits durable antitumor immunity in immunocompetent models of HPV+ OPC. Using murine and human preclinical systems, we demonstrate that the WEE1 inhibitor azenosertib (ZN-c3) mediates tumor control through both cell-autonomous cytotoxicity and immune-dependent mechanisms requiring T cells and conventional dendritic cells. Mechanistically, HPV+ tumor cells are deficient in STING signaling and fail to mount canonical type I interferon responses. Instead, tumor cell-intrinsic cGAS drives immune activation through STING-competent host cells within the tumor microenvironment, revealing a non-cell-autonomous relay that circumvents viral immune evasion. Intermittent WEE1 inhibition preserves T cell fitness while maintaining antitumor efficacy, and mice achieving complete responses develop immunologic memory capable of rejecting tumor rechallenge. These findings establish intermittent WEE1 inhibition as an immune-permissive therapeutic strategy that enables antigen-specific T cell responses in HPV-driven malignancies and provides a mechanistic rationale for combination with immunotherapy.

BACKGROUNDSepsis is a leading cause of morbidity and mortality in critically ill children, yet heterogeneous immune responses complicate the development of targeted therapies and the host immune factors driving sepsis pathobiology remain unclear.METHODSWe integrated deep immune phenotyping, plasma proteomics, single-cell transcriptomics, and phosphoflow cytometry in a prospective cohort of 88 critically ill children to elucidate the mechanisms underlying immune heterogeneity.RESULTSUnsupervised clustering of plasma cytokines identified 3 immunologic subgroups, including a high-severity group ("Group C") characterized by hypercytokinemia driven by IL-6 and IFN-γ. Group C exhibited distinct alterations in immune cell frequency and activation, with a strong association between hyperinflammatory cytokine signaling and lymphocyte dysfunction. Single-cell RNA-seq revealed transcriptional signatures of T cell activation and metabolic stress, with suppression of a lymphoid protective gene program across CD8+ T cell subsets. Despite increased expression of activation markers, T cell receptor repertoire analysis revealed no dominant clonotypes, consistent with bystander activation. Phosphoflow cytometry demonstrated baseline STAT1/STAT3 hyperactivation in Group C CD8+ T cells, which failed to respond to αCD3/αCD28/αCD49d stimulation.CONCLUSIONSThese findings define an IL-6/IFN-γ-driven endotype of T cell dysfunction in pediatric sepsis and highlight the JAK/STAT axis as a rational target for immunomodulatory therapy.FUNDINGK12HD047349, K23GM159013, K08AI135091, R01HD095976, Thrasher Research Fund, Burroughs Wellcome Fund, Immune Deficiency Foundation, Primary Immune Deficiency Treatment Consortium, Barbara Brodsky Foundation, CHOP Research Institute.

Abstract Breast cancer in women with germline BRCA1/2 pathogenic variants (gBRCA1/2) are generally treated with platinum-based therapies and PARP inhibitors (PARPi) with resistance commonly emerging. As the tumor microenvironment (TME) in gBRCA1 triple-negative breast cancer (TNBC) is enriched with tumor-infiltrating lymphocytes (TILs) and CD8 T cells, treatment trials have been done combining PARPi and immune checkpoint inhibitors (ICIs) in BRCA1 TNBC. This combination has not been shown to be more effective than PARPi alone. Evaluating the TME in gBRCA1/2 TNBC may help identify tumors most likely to benefit from PARPi/ICI therapy. We performed a detailed spatial proteomic analysis to characterize tumor-immune cell interactions in patients with gBRCA1/2 and wild-type (WT) TNBC with spatial tissue multiplexing (PhenoCycler) in 101 gBRCA1, 24 gBRCA2, and 30 WT TNBCs with matched RNAseq for 34 gBRCA1, 8 gBRCA2, and 16 WT TNBCs. A 43-plex antibody panel was developed featuring markers of DNA damage and repair, immune subtypes and exhaustion. We detected single tumor cells (PANCK+) in S/G2 phase (Geminin+) with double-stranded DNA breaks (yH2AX+) and DNA repair capacity (RAD51+) across all three cohorts. gBRCA1/2 TNBC patients exhibited a significantly lower proportion of tumor cells with homologous recombination proficiency (HRP) (gBRCA1 p = 0.006; gBRCA2 p = 0.007) compared to WT TNBC. CD4 & CD8 T cells, and CD20 B cells had intact DNA repair in WT and gBRCA1/2 TNBC. The frequency of CD8+ T (p=0.016) and CD20 B (p=0.003) cells was significantly higher in gBRCA1 compared to WT TNBC; BRCA2 and WT TNBC showed no differences. A detailed characterization of CD8 T cells revealed significantly increased numbers of potentially dysfunctional CD8 T cells in BRCA1 (TOX, p<0.0001; LAG-3, p=0.028; PD-1, p=0.033) and BRCA2 (LAG-3, p=0.033) compared to WT TNBC. We observed two types of TMEs in gBRCA1 TNBC: 1) CD8 low (mean<9.38%) with 1.4-fold increased immune checkpoint (PD-1) expression (mean: 15.4%) and high DNA damage in tumor cells; and 2) CD8 high (>9.38%) with reduced PD-1 and low DNA damage in tumor cells. Our findings suggest that although gBRCA1/2 variants lead to DNA damage and impaired repair in tumor cells, T cells (CD4, CD8) and B cells (CD20) retain intact DNA repair mechanisms. We also found that gBRCA1/2 TNBCs exhibit higher levels of immune checkpoint proteins LAG-3 and PD-1 on CD8 T cells compared to WT TNBC. This finding suggests the potential utility of additional ICI (LAG-3, PD-1) beyond PD-L1 blockade. Importantly, patients with gBRCA1-associated TNBC exhibit two different TMEs, suggesting that the response to ICI- and DNA-damaging-based therapies may differ between tumors, and anticipated prior to treatment. Defining treatment-naïve TME is crucial for designing personalized, targeted ICI strategies for individuals with BRCA-mutated TNBC. Citation Format: Dana Pueschl, Danielle Bragen, Jia-Ren Lin, Anupma Nayak, Derek A. Oldridge, Kate Bennett, Victoria Fang, kConFab Investigators, Kenneth Offit, Andrew K. Godwin, Paul A. James, Phuong L. Mai, Soo Hwang Teo, Antonis Antoniou, Georgia Chenevix-Trench, E. John Wherry, Susan M. Domchek, Katherine L. Nathanson. A single-cell spatial proteomic analysis of the TNBC microenvironment defines genotype-specific features [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 4966.

In cytometry, the workhorse single-cell technology of clinical immunology, every study defines its own antibody panel and cell-type vocabulary, so a classifier trained on one cannot annotate the next. Immunologists instead annotate by manual gating, splitting one parent population at a time on a two-marker plot, down an expert-defined hierarchy. We introduce CytoGate-Bench, a benchmark that reformulates this per-step procedure as a zero-shot, panel-agnostic task for large language models. It comprises 23,646 expert-annotated instances re-curated from 11 public flow- and mass-cytometry cohorts spanning eight marker panels. Across six open- and closed-weight backbones, the strongest formulation draws one rectangular gate per candidate and falls within the range of trained, panel-specialized baselines. It degrades less under distribution shift. Walking the hierarchy stepwise outperforms predicting every cell type at once. Ablations trace the signal to the data distribution shape and curated marker priors. However, adding vision or a self-verification loop systematically tightens gates.

Although inflammatory complications are common in preterm infants, the effects of these conditions on neonatal immune development remain poorly defined. We therefore investigated whether severe bronchopulmonary dysplasia (BPD) and systemic infection, 2 major complications of prematurity, produce distinct immune signatures and change immune composition over time. We performed longitudinal high-dimensional immune profiling of residual whole blood from 38 preterm infants sampled every 2 weeks, along with 10 term infants at birth. Preterm infants with severe BPD showed a progressive increase in Th17-polarized CD4 + T cells, neutrophils, and Th17-related cytokines compared with age-matched infants with moderate BPD. In contrast, some preterm infants with systemic bacterial or viral infections mounted exceptionally robust CD8 + , CD4 + , and γδ T cell responses, with oligoclonal expansion, terminal differentiation, and coordinated plasma cytokine shifts that persisted well beyond resolution of infection. These findings demonstrate that different preterm comorbidities imprint the neonatal immune system in divergent ways. Thus, comprehensive and longitudinal immune profiling may not only identify connections between clinical inflammatory complications and underlying immune pathways but also reveal potential targets for intervention.

High-dimensional flow cytometry provides rich immunological data for examining immune responses and their relationships with disease pathology, but its complexity, heterogeneity, high-dimensionality, and modest sample sizes limit translation into clinical applications. We describe a translational immune health framework that applies supervised learning algorithms to integrate high-dimensional cellular immunology data with clinical outcomes. Using COVID-19 as a clinical scenario, we applied this framework to deep immune profiles from patients to classify disease severity and predict future severity changes from baseline profiles. We built predictive models with five supervised algorithms and interpreted associations between immune features and severity outcomes with SHapley Additive exPlanations. This approach identified immune features contributing to severity predictions and provided interpretable links between cellular immune profiles and clinical outcomes. Our findings support machine learning as a practical strategy for analyzing complex immunological data and advancing predictive modeling in translational immune health.

The human immune system is composed of ~30-50 distinct cell types, each of which can exist in different states of activation or differentiation. Indeed, the mammalian immune system has evolved to sense and respond to infections, cancers, injuries, and changes in tissue or host homeostasis (1). Moreover, an increasingly large fraction of approved drugs target the immune system directly, and/or cause immune changes (2-4). A key feature of the immune system is to store some of this information, for example as innate or adaptive immune memory (5). In addition, rewiring of immune network architecture induced by disease, environmental exposures, drug treatments, and/or chronological age allows the immune system to store information in the pattern of connections and activity across populations of immune cells. This ensemble information storage, in addition to changes to individual cells, functions as a major way the immune system encodes aspects of immune history and future potential. Genetic information can identify inherited risk alleles, but cannot capture the continual remodeling of the immune system shaped by exposures, infection, inflammation, therapy, and aging (6, 7). To define and use such ensemble immunotypes, we developed a self-supervised deep learning framework that transforms high-dimensional immune profiles into representations of immune health. MAESTRO (MAsked Encoding Set TRansformer with self-distillatiOn) encodes a set of cells from an individual into an embedding that captures immune cell population-level organization. Pretrained on 1,792 peripheral blood samples comprising over 418 million immune cells across 13 clinical diagnoses, MAESTRO learns immune fingerprints that are stable within individuals yet diverse across populations, states of health, disease, and treatment, providing a quantitative basis for comparing immune states across individuals and over time. These fingerprints capture immune architecture beyond coarse cell type proportions, enabling patient-efficient clinical prediction using simple task specific models. MAESTRO model embeddings retain a temporal dimension of immune history and potential, reflecting signatures of past exposures and baseline features that predict future immune responses. Finally, we demonstrate a translational precision immunotherapy application by testing this approach in metastatic Pancreatic Ductal Adenocarcinoma (PDAC), where pretreatment immune landscape circuitry maps enable patient stratification and therapeutic response prediction. Overall, we developed a large, attention-based model that captures deep network architecture of immune states through self-supervised representations of immune cytometry data as a reusable foundation for precision immunology, converting immune complexity into clinically actionable embeddings for diagnosis, monitoring, and therapy selection.

In this Viewpoint, eight experts from the field of T cell exhaustion discuss current understanding of the self-renewing population of PD1+TCF1+TOX+ precursor and/or progenitor exhausted CD8+ T cells and controversies related to their development and function.

Precise modulation of T cell function through engineering the non-coding genome holds great promise for advancing next-generation immunotherapies. However, robust high-throughput approaches to annotate functional cis-regulatory elements (CRE) in human T cells remain limited. Here, we developed a simple and highly efficient CRISPR interference (CRISPRi) perturbation platform to systematically annotate CREs in human primary T cells. Using this platform, we identified novel CREs controlling PDCD1 , HAVCR2 , and TBX21 expression. Combinatorial CRE perturbations revealed synergistic CRE pairs that fine-tune PDCD1 and HAVCR2 expression, while Cas9-indel-based mutagenesis pinpointed the critical nucleotides within each enhancer that are essential for their activity. Functional experiments demonstrated that CRE-edited HAVCR2 outperformed conventional total gene knockout in enhancing CAR T cell anti-tumor efficacy. Moreover, CRE editing of PDCD1 and HAVCR2 repressed PD-1 and TIM-3 expression in human tumor-infiltrating lymphocyte CD8 T cells, highlighting regulatory role of these CREs in disease relevant exhausted T cells. Together, this approach offers a compact CRISPRi platform that enables high-throughput dissection of functionally relevant non-coding genomic regions in T cells, providing insights for mechanistic studies and precision genome engineering of advanced cellular therapies.

γδ T cells maintain intestinal immune homeostasis, but their contributions to human ulcerative colitis (UC) are poorly understood. We characterized γδ T cells in intestinal biopsies obtained from patients with UC and healthy donors using single-cell RNA sequencing, T cell receptor profiling, and mass cytometry. UC reduced CD103 + Vγ4Vδ1 + γδ intraepithelial lymphocytes (γδ IELs) and increased γδ T cell subsets with stemlike phenotypes expressing TCF-1 (T cell factor 1) and PD-1 (programmed cell death receptor 1) or effector-like phenotypes expressing granzyme B, perforin, and T-bet in the lamina propria. γδ T cell composition changes in UC correlated with decreased expression of epithelial BTNL3 and BTNL8 and increased BTN3A1 and BTN3A3 , suggesting altered recruitment and activation. Clinical improvement recovered γδ IELs and reduced inflammation-associated subsets. Inflammation-associated changes were observed in peripheral blood γδ T cells. Thus, distinct γδ T cell subsets in different niches exert protective or pathogenic functions in UC.

Diabetic kidney disease (DKD), the leading cause of kidney failure, is marked by clinical and molecular heterogeneity, making therapeutic development exceedingly difficult1. Here we used Xenium and CosMx single-cell spatial transcriptomics, integrated with single-nucleus RNA sequencing, to build a cross-platform kidney atlas that makes tissue architecture computable for prognosis, non-invasive detection and patient selection. Using this atlas, we defined reproducible tissue niches and injury-linked microenvironments and uncovered a profibrotic context that expands with disease and tracks with worse kidney function. Within this architecture, we identified a B cell-predominant, tertiary lymphoid structure-like immune microenvironment that defines a distinct DKD subset with accelerated progression to renal end-points. We developed tissue biomarkers and a matched plasma protein panel that capture this biology, stratify patients in a population biobank and improve risk prediction beyond clinical models-supporting their potential for biomarker-guided selection in future B cell-targeted DKD trials.

The Allen Institute for Immunology was founded in 2018 to perform deep, longitudinal profiling of the human immune system in health and disease. We established partnerships to profile healthy adults and children as well as patients at risk for rheumatoid arthritis, with inflammatory bowel disease, with multiple myeloma diagnosis, under treatment for melanoma, and with COVID-19. We sampled the same subjects longitudinally for up to two years, then performed immune profiling using scRNA-seq, 4 high-dimensional flow cytometry panels, plasma or serum proteomics, and clinical lab tests. In total, we profiled >2,300 samples from >450 subjects, including >55 million cells profiled by scRNA-seq to date. To process, analyze, and distribute this data, we developed the Human Immune System Explorer (HISE) platform, a flexible, scalable, cloud-based framework to enable storage, interactive analysis, visualization, and generation of Certificates of Reproducibility that enable inspection and replay of any step of an analysis workflow. We joined our robust, large-scale analytical platform to public-facing visualization tools, scientific context, and data releases, starting with the Human Immune Health Atlas: an expertly annotated dataset of > 1.3 million PBMCs from 108 healthy donors from 11 to 65 years of age. We invite immunologists to explore this resource and our expanding library of immunology data, insights, and tools at https://explore.allenimmunology.org/. Computational and Systems Immunology (COMP)

Rationale: Our group recently identified a novel pediatric sepsis endotype associated with dysregulated STAT3 signaling, CD8+ T cell hyperactivation, increased mortality, and higher cumulative organ dysfunction scores. T cell activation can occur via bystander activation, which is associated with off-target tissue injury, or antigen-specific activation, which is associated with pathogen control. We hypothesized that CD8+ T cell hyperactivation within the dysregulated STAT3 signaling endotype would be driven by bystander activation, which could influence treatment strategies. Methods: To analyze T cell activation and T cell receptor (TCR) repertoire within this sepsis endotype, we performed 5’ single-cell RNA sequencing (scRNAseq) and TCR sequencing (TCRseq) on CD45+ lymphocytes from 9 patients with dysregulated STAT3 signaling and 3 age-matched healthy controls. We annotated cell subsets using ScType and performed differential expression analysis using FindMarkers. We assessed CD8+ T cell activation using gene set enrichment analysis (GSEA) and cell-specific ligand-receptor interactions using CellChat. We measured TCR diversity and clonal abundance using scRepertoire. Results: Compared to healthy controls, patients with sepsis have reduced effector CD8+ T cell and increased naïve CD8+ T cell populations (p<0.0001). Perforin and granzyme expression are increased in naïve and effector CD8+ T cells from patients with the dysregulated STAT3 signaling endotype (“STAT3 endotype” patients) compared to healthy controls (all p<0.0001), suggesting increased cytotoxic activity. GSEA of CD8+ T cell subsets revealed increased IFNγ production (NES +2.27 [naïve], +2.46 [effector], both p<0.0001) and cytokine signaling (NES +1.68 [naïve], NES +1.73 [effector], both p<0.01) in STAT3 endotype patients compared to healthy controls, consistent with increased T cell activation. Ligand-receptor interaction analysis demonstrated significant interactions between HLA class I molecules and CD8A in CD8+ T cells from STAT3 endotype patients compared to healthy controls (p<0.01, Figure 1A), suggesting increased TCR signaling. TCR repertoire analysis identified increased clonal diversity in STAT3 endotype patients compared to healthy controls (p<0.0001, Figure 1B) without evidence of clonal expansion (Figure 1C). Within T cell subsets, STAT3 endotype patients demonstrated increased TCR diversity in naïve CD8+ T cells and reduced TCR diversity in effector CD8+ T cells (Figure 1D). Conclusions: Through paired scRNAseq and TCRseq analysis, we identified CD8+ T cell hyperactivation and increased TCR clonal diversity in patients with the dysregulated STAT3 signaling endotype of pediatric sepsis. Polyclonal bystander activation of CD8+ T cells may be a reversible cause of organ failure within this sepsis endotype. Dysregulated STAT3 signaling is a candidate target for precision immunomodulation in pediatric sepsis.