Single-cell sequencing of tumour infiltrating T cells efficiently identifies tumour-specific T cell receptors based on the T cell activation score.

Adoptively transferred T cell receptor-engineered T cells are a promising cancer treatment strategy, and the identification of tumour-specific TCRs is essential. Previous studies reported that tumour-reactive T cells and TCRs could be isolated based on the expression of activation markers. However, since T cells with different cell states could not respond uniformly to activation but show a heterogeneous expression profile of activation and effector molecules, isolation of tumour-reactive T cells based on single activation or effector molecules could result in the absence of tumour-reactive T cells; thus, combinations of multiple activation and effector molecules could improve the efficiency of isolating tumour-specific TCRs. We enrolled two patients with lung adenocarcinoma and obtained their tumour infiltrating lymphocytes (TILs) and autologous tumour cells (ATCs). TILs were cocultured with the corresponding ATCs for 12 h and subjected to single-cell RNA sequencing. First, we identified three TCRs with the highest expression levels of IFNG and TNFRSF9 mRNA for each patient, yet only the top one or two recognized the corresponding ATCs in each patient. Next, we defined the activation score based on normalized expression levels of IFNG, IL2, TNF, IL2RA, CD69, TNFRSF9, GZMB, GZMA, GZMK, and PRF1 mRNA for each T cell and then identified three TCRs with the highest activation score for each patient. We found that all three TCRs in each patient could specifically identify corresponding ATCs. In conclusion, we established an efficient approach to isolate tumour-reactive TCRs based on combinations of multiple activation and effector molecules through single-cell RNA sequencing.

T-cell receptor diversity and allergen sensitivity in childhood asthma and atopic dermatitis.

BACKGROUND: Childhood allergies of asthma and atopic dermatitis (AD) involve an overactive T-cell immune response triggered by allergens. However, the impact of T-cell receptor (TCR) repertoires on allergen sensitization and their role in mediating different phenotypes of asthma and AD in early childhood remains unclear. METHODS: A total of 78 children, comprising 26 with asthma alone, 26 with AD alone, and 26 healthy controls (HC), were enrolled. TCR repertoire profiles were determined using a unique molecular identifier system for next-generation sequencing. Integrative analyses of their associations with allergen-specific IgE levels and allergies were performed. RESULTS: The diversity in TCR alpha variable region (TRAV) genes of TCR repertoires and complementarity determining region 3 (CDR3) clonality in TRAV/TRBV (beta) genes were significantly higher in children with AD compared with those with asthma and HC (p < .05). Compared with HC, the expression of TRAV13-1 and TRAV4 genes was significantly higher in both asthma and AD (p < .05), with a significant positive correlation with mite-specific IgE levels (p < .01). In contrast, TRBV7-9 gene expression was significantly lower in both asthma and AD (p < .01), with this gene showing a significant negative correlation with mite-specific IgE levels (p < .01). Furthermore, significantly higher TRAV8-3 gene expression, positively correlated with food-specific IgE levels, was found in children with AD compared with those with asthma (p < .05). CONCLUSION: Integrated TCR repertoires analysis provides clinical insights into the diverse TCR genes linked to antigen specificity, offering potential for precision immunotherapy in childhood allergies.

DIRMC: a database of immunotherapy-related molecular characteristics.

Cancer immunotherapy has brought about a revolutionary breakthrough in the field of cancer treatment. Immunotherapy has changed the treatment landscape for a variety of solid and hematologic malignancies. To assist researchers in efficiently uncovering valuable information related to cancer immunotherapy, we have presented a manually curated comprehensive database called DIRMC, which focuses on molecular features involved in cancer immunotherapy. All the content was collected manually from published literature, authoritative clinical trial data submitted by clinicians, some databases for drug target prediction such as DrugBank, and some experimentally confirmed high-throughput data sets for the characterization of immune-related molecular interactions in cancer, such as a curated database of T-cell receptor sequences with known antigen specificity (VDJdb), a pathology-associated TCR database (McPAS-TCR) et al. By constructing a fully connected functional network, ranging from cancer-related gene mutations to target genes to translated target proteins to protein regions or sites that may specifically affect protein function, we aim to comprehensively characterize molecular features related to cancer immunotherapy. We have developed the scoring criteria to assess the reliability of each MHC-peptide-T-cell receptor (TCR) interaction item to provide a reference for users. The database provides a user-friendly interface to browse and retrieve data by genes, target proteins, diseases and more. DIRMC also provides a download and submission page for researchers to access data of interest for further investigation or submit new interactions related to cancer immunotherapy targets. Furthermore, DIRMC provides a graphical interface to help users predict the binding affinity between their own peptide of interest and MHC or TCR. This database will provide researchers with a one-stop resource to understand cancer immunotherapy-related targets as well as data on MHC-peptide-TCR interactions. It aims to offer reliable molecular characteristics support for both the analysis of the current status of cancer immunotherapy and the development of new immunotherapy. DIRMC is available at http://www.dirmc.tech/. Database URL: http://www.dirmc.tech/.

Generation of Anti-HIV CAR-T Cells for Preclinical Research.

The inability of people living with HIV (PLWH) to eradicate human immunodeficiency virus (HIV) infection is due in part to the inadequate HIV-specific cellular immune response. The antiviral function of cytotoxic CD8+ T cells, which are crucial for HIV control, is impaired during chronic viral infection because of viral escape mutations, immune exhaustion, HIV antigen downregulation, inflammation, and apoptosis. In addition, some HIV-infected cells either localize to tissue sanctuaries inaccessible to CD8+ T cells or are intrinsically resistant to CD8+ T cell killing. The novel design of synthetic chimeric antigen receptors (CARs) that enable T cells to target specific antigens has led to the development of potent and effective CAR-T cell therapies. While initial clinical trials using anti-HIV CAR-T cells performed over 20 years ago showed limited anti-HIV effects, the improved CAR-T cell design, which enabled its success in treating cancer, has reinstated CAR-T cell therapy as a strategy for HIV cure with notable progress being made in the recent decade.Effective CAR-T cell therapy against HIV infection requires the generation of anti-HIV CAR-T cells with potent in vivo activity against HIV-infected cells. Preclinical evaluation of anti-HIV efficacy of CAR-T cells and their safety is fundamental for supporting the initiation of subsequent clinical trials in PLWH. For these preclinical studies, we developed a novel humanized mouse model supporting in vivo HIV infection, the development of viremia, and the evaluation of novel HIV therapeutics. Preclinical assessment of anti-HIV CAR-T cells using this mouse model involves a multistep process including peripheral blood mononuclear cells (PBMCs) harvested from human donors, T cell purification, ex vivo T cell activation, transduction with lentiviral vectors encoding an anti-HIV CAR, CAR-T cell expansion and infusion in mice intrasplenically injected with autologous PBMCs followed by the determination of CAR-T cell capacity for HIV suppression. Each of the steps described in the following protocol were optimized in the lab to maximize the quantity and quality of the final anti-HIV CAR-T cell products.

Predicting TCR sequences for unseen antigen epitopes using structural and sequence features.

T-cell receptor (TCR) recognition of antigens is fundamental to the adaptive immune response. With the expansion of experimental techniques, a substantial database of matched TCR-antigen pairs has emerged, presenting opportunities for computational prediction models. However, accurately forecasting the binding affinities of unseen antigen-TCR pairs remains a major challenge. Here, we present convolutional-self-attention TCR (CATCR), a novel framework tailored to enhance the prediction of epitope and TCR interactions. Our approach utilizes convolutional neural networks to extract peptide features from residue contact matrices, as generated by OpenFold, and a transformer to encode segment-based coded sequences. We introduce CATCR-D, a discriminator that can assess binding by analyzing the structural and sequence features of epitopes and CDR3-ß regions. Additionally, the framework comprises CATCR-G, a generative module designed for CDR3-ß sequences, which applies the pretrained encoder to deduce epitope characteristics and a transformer decoder for predicting matching CDR3-ß sequences. CATCR-D achieved an AUROC of 0.89 on previously unseen epitope-TCR pairs and outperformed four benchmark models by a margin of 17.4%. CATCR-G has demonstrated high precision, recall and F1 scores, surpassing 95% in bidirectional encoder representations from transformers score assessments. Our results indicate that CATCR is an effective tool for predicting unseen epitope-TCR interactions. Incorporating structural insights enhances our understanding of the general rules governing TCR-epitope recognition significantly. The ability to predict TCRs for novel epitopes using structural and sequence information is promising, and broadening the repository of experimental TCR-epitope data could further improve the precision of epitope-TCR binding predictions.

Revealing molecular and cellular heterogeneity in hypopharyngeal carcinogenesis through single-cell RNA and TCR/BCR sequencing.

Introduction: Hypopharyngeal squamous cell carcinoma (HSCC) is one of the malignant tumors with the worst prognosis in head and neck cancers. The transformation from normal tissue through low-grade and high-grade intraepithelial neoplasia to cancerous tissue in HSCC is typically viewed as a progressive pathological sequence typical of tumorigenesis. Nonetheless, the alterations in diverse cell clusters within the tissue microenvironment (TME) throughout tumorigenesis and their impact on the development of HSCC are yet to be fully understood. Methods: We employed single-cell RNA sequencing and TCR/BCR sequencing to sequence 60,854 cells from nine tissue samples representing different stages during the progression of HSCC. This allowed us to construct dynamic transcriptomic maps of cells in diverse TME across various disease stages, and experimentally validated the key molecules within it. Results: We delineated the heterogeneity among tumor cells, immune cells (including T cells, B cells, and myeloid cells), and stromal cells (such as fibroblasts and endothelial cells) during the tumorigenesis of HSCC. We uncovered the alterations in function and state of distinct cell clusters at different stages of tumor development and identified specific clusters closely associated with the tumorigenesis of HSCC. Consequently, we discovered molecules like MAGEA3 and MMP3, pivotal for the diagnosis and treatment of HSCC. Discussion: Our research sheds light on the dynamic alterations within the TME during the tumorigenesis of HSCC, which will help to understand its mechanism of canceration, identify early diagnostic markers, and discover new therapeutic targets.

Predictability of B cell clonal persistence and immunosurveillance in breast cancer.

B cells and T cells are important components of the adaptive immune system and mediate anticancer immunity. The T cell landscape in cancer is well characterized, but the contribution of B cells to anticancer immunosurveillance is less well explored. Here we show an integrative analysis of the B cell and T cell receptor repertoire from individuals with metastatic breast cancer and individuals with early breast cancer during neoadjuvant therapy. Using immune receptor, RNA and whole-exome sequencing, we show that both B cell and T cell responses seem to coevolve with the metastatic cancer genomes and mirror tumor mutational and neoantigen architecture. B cell clones associated with metastatic immunosurveillance and temporal persistence were more expanded and distinct from site-specific clones. B cell clonal immunosurveillance and temporal persistence are predictable from the clonal structure, with higher-centrality B cell antigen receptors more likely to be detected across multiple metastases or across time. This predictability was generalizable across other immune-mediated disorders. This work lays a foundation for prioritizing antibody sequences for therapeutic targeting in cancer.

Self-sufficient primary natural killer cells engineered to express T cell receptors and interleukin-15 exhibit improved effector function and persistence.

Background: NK cells can be genetically engineered to express a transgenic T-cell receptor (TCR). This approach offers an alternative strategy to target heterogenous tumors, as NK:TCR cells can eradicate both tumor cells with high expression of HLA class I and antigen of interest or HLA class I negative tumors. Expansion and survival of NK cells relies on the presence of IL-15. Therefore, autonomous production of IL-15 by NK:TCR cells might improve functional persistence of NK cells. Here we present an optimized NK:TCR product harnessed with a construct encoding for soluble IL-15 (NK:TCR/IL-15), to support their proliferation, persistence and cytotoxic capabilities. Methods: Expression of tumor-specific TCRs in peripheral blood derived NK-cells was achieved following retroviral transduction. NK:TCR/IL-15 cells were compared with NK:TCR cells for autonomous cytokine production, proliferation and survival. NK:BOB1-TCR/IL-15 cells, expressing a HLA-B*07:02-restricted TCR against BOB1, a B-cell lineage specific transcription factor highly expressed in all B-cell malignancies, were compared with control NK:BOB1-TCR and NK:CMV-TCR/IL-15 cells for effector function against TCR antigen positive malignant B-cell lines in vitro and in vivo. Results: Viral incorporation of the interleukin-15 gene into engineered NK:TCR cells was feasible and high expression of the TCR was maintained, resulting in pure NK:TCR/IL-15 cell products generated from peripheral blood of multiple donors. Self-sufficient secretion of IL-15 by NK:TCR cells enables engineered NK cells to proliferate in vitro without addition of extra cytokines. NK:TCR/IL-15 demonstrated a marked enhancement of TCR-mediated cytotoxicity as well as enhanced NK-mediated cytotoxicity resulting in improved persistence and performance of NK:BOB1-TCR/IL-15 cells in an orthotopic multiple myeloma mouse model. However, in contrast to prolonged anti-tumor reactivity by NK:BOB1-TCR/IL-15, we observed in one of the experiments an accumulation of NK:BOB1-TCR/IL-15 cells in several organs of treated mice, leading to unexpected death 30 days post-NK infusion. Conclusion: This study showed that NK:TCR/IL-15 cells secrete low levels of IL-15 and can proliferate in an environment lacking cytokines. Repeated in vitro and in vivo experiments confirmed the effectiveness and target specificity of our product, in which addition of IL-15 supports TCR- and NK-mediated cytotoxicity.

Clonal expansion of shared T cell receptors reveals the existence of immune commonality among different lesions of synchronous multiple primary lung cancer.

The increase in the detection rate of synchronous multiple primary lung cancer (MPLC) has posed remarkable clinical challenges due to the limited understanding of its pathogenesis and molecular features. Here, comprehensive comparisons of genomic and immunologic features between MPLC and solitary lung cancer nodule (SN), as well as different lesions of the same patient, were performed. Compared with SN, MPLC displayed a lower rate of EGFR mutation but higher rates of BRAF, MAP2K1, and MTOR mutation, which function exactly in the upstream and downstream of the same signaling pathway. Considerable heterogeneity in T cell receptor (TCR) repertoire exists among not only different patients but also among different lesions of the same patient. Invasive lesions of MPLC exhibited significantly higher TCR diversity and lower TCR expansion than those of SN. Intriguingly, different lesions of the same patient always shared a certain proportion of TCR clonotypes. Significant clonal expansion could be observed in shared TCR clonotypes, particularly in those existing in all lesions of the same patient. In conclusion, this study provided evidences of the distinctive mutational landscape, activation of oncogenic signaling pathways, and TCR repertoire in MPLC as compared with SN. The significant clonal expansion of shared TCR clonotypes demonstrated the existence of immune commonality among different lesions of the same patient and shed new light on the individually tailored precision therapy for MPLC.

EFHD2 regulates T cell receptor signaling and modulates T helper cell activation in early sepsis.

EFHD2 (EF-hand domain family, member D2) has been identified as a calcium-binding protein with immunomodulatory effects. In this study, we characterized the phenotype of Efhd2-deficient mice in sepsis and examined the biological functions of EFHD2 in peripheral T cell activation and T helper (Th) cell differentiation. Increased levels of EFHD2 expression accompanied peripheral CD4+ T cell activation in the early stages of sepsis. Transcriptomic analysis indicated that immune response activation was impaired in Efhd2-deficient CD4+ T cells. Further, Efhd2-deficient CD4+ T cells isolated from the spleen of septic mice showed impaired T cell receptor (TCR)-induced Th differentiation, especially Th1 and Th17 differentiation. In vitro data also showed that Efhd2-deficient CD4+ T cells exhibit impaired Th1 and Th17 differentiation. In the CD4+ T cells and macrophages co-culture model for antigen presentation, the deficiency of Efhd2 in CD4+ T cells resulted in impaired formation of immunological synapses. In addition, Efhd2-deficient CD4+ T cells exhibited reduced levels of phospho-LCK and phospho-ZAP70, and downstream transcription factors including Nfat, Nfκb and Nur77 following TCR engagement. In summary, EFHD2 may promote TCR-mediated T cell activation subsequent Th1 and Th17 differentiation in the early stages of sepsis by regulating the intensity of TCR complex formation.

ScRNA-seq reveals novel immune-suppressive T cells and investigates CMV-TCR-T cells cytotoxicity against GBM.

BACKGROUND: Glioblastoma (GBM) is a fatal primary brain malignancy in adults. Previous studies have shown that cytomegalovirus (CMV) is a risk factor for tumorigenesis and aggressiveness for glioblastoma. However, little is known about how CMV infection affects immune cells in the tumor microenvironment of GBM. Furthermore, there has been almost no engineered T-cell receptor (TCR)-T targeting CMV for GBM research to date. METHODS: We evaluated the CMV infection status of patients with GBM's tumor tissue by immune electron microscopy, immunofluorescence, and droplet digital PCR. We performed single-cell RNA sequencing for CMV-infected GBM to investigate the effects of CMV on the GBM immune microenvironment. CellChat was applied to analyze the interaction between cells in the GBM tumor microenvironment. Additionally, we conducted single-cell TCR/B cell receptor (BCR) sequencing and Grouping of Lymphocyte Interactions with Paratope Hotspots 2 algorithms to acquire specific CMV-TCR sequences. Genetic engineering was used to introduce CMV-TCR into primary T cells derived from patients with CMV-infected GBM. Flow cytometry was used to measure the proportion and cytotoxicity status of T cells in vitro. RESULTS: We identified two novel immune cell subpopulations in CMV-infected GBM, which were bipositive CD68+SOX2+ tumor-associated macrophages and FXYD6+ T cells. We highlighted that the interaction between bipositive TAMs or cancer cells and T cells was predominantly focused on FXYD6+ T cells rather than regulatory T cells (Tregs), whereas, FXYD6+ T cells were further identified as a group of novel immunosuppressive T cells. CMV-TCR-T cells showed significant therapeutic effects on the human-derived orthotopic GBM mice model. CONCLUSIONS: These findings provided an insight into the underlying mechanism of CMV infection promoting the GBM immunosuppression, and provided a novel potential immunotherapy strategy for patients with GBM.

Unified cross-modality integration and analysis of T cell receptors and T cell transcriptomes by low-resource-aware representation learning.

Single-cell RNA sequencing (scRNA-seq) and T cell receptor sequencing (TCR-seq) are pivotal for investigating T cell heterogeneity. Integrating these modalities, which is expected to uncover profound insights in immunology that might otherwise go unnoticed with a single modality, faces computational challenges due to the low-resource characteristics of the multimodal data. Herein, we present UniTCR, a novel low-resource-aware multimodal representation learning framework designed for the unified cross-modality integration, enabling comprehensive T cell analysis. By designing a dual-modality contrastive learning module and a single-modality preservation module to effectively embed each modality into a common latent space, UniTCR demonstrates versatility in connecting TCR sequences with T cell transcriptomes across various tasks, including single-modality analysis, modality gap analysis, epitope-TCR binding prediction, and TCR profile cross-modality generation, in a low-resource-aware way. Extensive evaluations conducted on multiple scRNA-seq/TCR-seq paired datasets showed the superior performance of UniTCR, exhibiting the ability of exploring the complexity of immune system.

Single-cell immune repertoire analysis.

Single-cell T cell and B cell antigen receptor-sequencing data analysis can potentially perform in-depth assessments of adaptive immune cells that inform on understanding immune cell development to tracking clonal expansion in disease and therapy. However, it has been extremely challenging to analyze and interpret T cells and B cells and their adaptive immune receptor repertoires at the single-cell level due to not only the complexity of the data but also the underlying biology. In this Review, we delve into the computational breakthroughs that have transformed the analysis of single-cell T cell and B cell antigen receptor-sequencing data.

A novel engineered IL-21 receptor arms T-cell receptor-engineered T cells (TCR-T cells) against hepatocellular carcinoma.

Strategies to improve T cell therapy efficacy in solid tumors such as hepatocellular carcinoma (HCC) are urgently needed. The common cytokine receptor γ chain (γc) family cytokines such as IL-2, IL-7, IL-15 and IL-21 play fundamental roles in T cell development, differentiation and effector phases. This study aims to determine the combination effects of IL-21 in T cell therapy against HCC and investigate optimized strategies to utilize the effect of IL-21 signal in T cell therapy. The antitumor function of AFP-specific T cell receptor-engineered T cells (TCR-T) was augmented by exogenous IL-21 in vitro and in vivo. IL-21 enhanced proliferation capacity, promoted memory differentiation, downregulated PD-1 expression and alleviated apoptosis in TCR-T after activation. A novel engineered IL-21 receptor was established, and TCR-T armed with the novel engineered IL-21 receptors (IL-21R-TCR-T) showed upregulated phosphorylated STAT3 expression without exogenous IL-21 ligand. IL-21R-TCR-T showed better proliferation upon activation and superior antitumor function in vitro and in vivo. IL-21R-TCR-T exhibited a less differentiated, exhausted and apoptotic phenotype than conventional TCR-T upon repetitive tumor antigen stimulation. The novel IL-21 receptor in our study programs powerful TCR-T and can avoid side effects induced by IL-21 systemic utilization. The novel IL-21 receptor creates new opportunities for next-generation TCR-T against HCC.

Self-supervised learning of T cell receptor sequences exposes core properties for T cell membership.

The T cell receptor (TCR) repertoire is an extraordinarily diverse collection of TCRs essential for maintaining the body's homeostasis and response to threats. In this study, we compiled an extensive dataset of more than 4200 bulk TCR repertoire samples, encompassing 221,176,713 sequences, alongside 6,159,652 single-cell TCR sequences from over 400 samples. From this dataset, we then selected a representative subset of 5 million bulk sequences and 4.2 million single-cell sequences to train two specialized Transformer-based language models for bulk (CVC) and single-cell (scCVC) TCR repertoires, respectively. We show that these models successfully capture TCR core qualities, such as sharing, gene composition, and single-cell properties. These qualities are emergent in the encoded TCR latent space and enable classification into TCR-based qualities such as public sequences. These models demonstrate the potential of Transformer-based language models in TCR downstream applications.

Enhancing comparative T cell receptor repertoire analysis in small biological samples through pooling homologous cell samples from multiple mice.

Accurate characterization and comparison of T cell receptor (TCR) repertoires from small biological samples present significant challenges. The main challenge is the low material input, which compromises the quality of bulk sequencing and hinders the recovery of sufficient TCR sequences for robust analyses. We aimed to address this limitation by implementing a strategic approach to pool homologous biological samples. Our findings demonstrate that such pooling indeed enhances the TCR repertoire coverage, particularly for cell subsets of constrained sizes, and enables accurate comparisons of TCR repertoires at different levels of complexity across T cell subsets with different sizes. This methodology holds promise for advancing our understanding of T cell repertoires in scenarios where sample size constraints are a prevailing concern.

Hyperactive STAT5 hijacks T cell receptor signaling and drives immature T cell acute lymphoblastic leukemia.

T cell acute lymphoblastic leukemia (T-ALL) is an aggressive immature T cell cancer. Mutations in IL7R have been analyzed genetically, but downstream effector functions such as STAT5A and STAT5B hyperactivation are poorly understood. Here, we studied the most frequent and clinically challenging STAT5BN642H driver in T cell development and immature T cell cancer onset and compared it with STAT5A hyperactive variants in transgenic mice. Enhanced STAT5 activity caused disrupted T cell development and promoted an early T cell progenitor-ALL phenotype, with upregulation of genes involved in T cell receptor (TCR) signaling, even in absence of surface TCR. Importantly, TCR pathway genes were overexpressed in human T-ALL and mature T cell cancers and activation of TCR pathway kinases was STAT5 dependent. We confirmed STAT5 binding to these genes using ChIP-Seq analysis in human T-ALL cells, which were sensitive to pharmacologic inhibition by dual STAT3/5 degraders or ZAP70 tyrosine kinase blockers in vitro and in vivo. We provide genetic and biochemical proof that STAT5A and STAT5B hyperactivation can initiate T-ALL through TCR pathway hijacking and suggest similar mechanisms for other T cell cancers. Thus, STAT5 or TCR component blockade are targeted therapy options, particularly in patients with chemoresistant clones carrying STAT5BN642H.

Convergence, plasticity, and tissue residence of regulatory T cell response via TCR repertoire prism.

Suppressive function of regulatory T cells (Treg) is dependent on signaling of their antigen receptors triggered by cognate self, dietary, or microbial peptides presented on MHC II. However, it remains largely unknown whether distinct or shared repertoires of Treg TCRs are mobilized in response to different challenges in the same tissue or the same challenge in different tissues. Here we use a fixed TCRß chain FoxP3-GFP mouse model to analyze conventional (eCD4) and regulatory (eTreg) effector TCRα repertoires in response to six distinct antigenic challenges to the lung and skin. This model shows highly 'digital' repertoire behavior with easy-to-track challenge-specific TCRα CDR3 clusters. For both eCD4 and eTreg subsets, we observe challenge-specific clonal expansions yielding homologous TCRα clusters within and across animals and exposure sites, which are also reflected in the draining lymph nodes but not systemically. Some CDR3 clusters are shared across cancer challenges, suggesting a response to common tumor-associated antigens. For most challenges, eCD4 and eTreg clonal response does not overlap. Such overlap is exclusively observed at the sites of certain tumor challenges, and not systematically, suggesting transient and local tumor-induced eCD4=>eTreg plasticity. This transition includes a dominant tumor-responding eCD4 CDR3 motif, as well as characteristic iNKT TCRα CDR3. In addition, we examine the homeostatic tissue residency of clonal eTreg populations by excluding the site of challenge from our analysis. We demonstrate that distinct CDR3 motifs are characteristic of eTreg cells residing in particular lymphatic tissues, regardless of the challenge. This observation reveals the tissue-resident, antigen-specific clonal Treg populations.

Single-Cell RNA Sequencing Reveals an Immune Landscape of CD4+ T Cells in Coronary Culprit Plaques With Acute Coronary Syndrome in Humans-Brief Report.

BACKGROUND: Acute coronary syndrome (ACS) involves plaque-related thrombosis, causing primary ischemic cardiomyopathy or lethal arrhythmia. We previously demonstrated a unique immune landscape of myeloid cells in the culprit plaques causing ACS by using single-cell RNA sequencing. Here, we aimed to characterize T cells in a single-cell level, assess clonal expansion of T cells, and find a therapeutic target to prevent ACS. METHODS: We obtained the culprit lesion plaques from 4 patients with chronic coronary syndrome (chronic coronary syndrome plaques) and the culprit lesion plaques from 3 patients with ACS (ACS plaques) who were candidates for percutaneous coronary intervention with directional coronary atherectomy. Live CD45+ immune cells were sorted from each pooled plaque samples and applied to the 10× platform for single-cell RNA sequencing analysis. We also extracted RNA from other 3 ACS plaque samples and conducted unbiased TCR (T-cell receptor) repertoire analysis. RESULTS: CD4+ T cells were divided into 5 distinct clusters: effector, naive, cytotoxic, CCR7+ (C-C chemokine receptor type 7) central memory, and FOXP3 (forkhead box P3)+ regulatory CD4+ T cells. The proportion of central memory CD4+ T cells was higher in the ACS plaques. Correspondingly, dendritic cells also tended to express more HLAs (human leukocyte antigens) and costimulatory molecules in the ACS plaques. The velocity analysis suggested the differentiation flow from central memory CD4+ T cells into effector CD4+ T cells and that from naive CD4+ T cells into central memory CD4+ T cells in the ACS plaques, which were not observed in the chronic coronary syndrome plaques. The bulk repertoire analysis revealed clonal expansion of TCRs in each patient with ACS and suggested that several peptides in the ACS plaques work as antigens and induced clonal expansion of CD4+ T cells. CONCLUSIONS: For the first time, we revealed single cell-level characteristics of CD4+ T cells in patients with ACS. CD4+ T cells could be therapeutic targets of ACS. REGISTRATION: URL: https://upload.umin.ac.jp/cgi-open-bin/icdr_e/ctr_view.cgi?recptno=R000046521; Unique identifier: UMIN000040747.