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2,952 results for “CD8”
NanoString dataset for study: Impairment of cancer-associated fibroblasts promotes CD8+ T cell infiltration and enhances sensitivity to immune checkpoint blockade
<p>Pre-processed NanoString mRNA abundance data and associated sample sheet for study:</p> <p>Impairment of cancer-associated fibroblasts promotes CD8+ T cell infiltration and enhances sensitivity to immune checkpoint blockade</p>
Dataset of "Chronic TCR-MHC (self)-interactions limit the functional potential of TCR affinityincreased CD8 T lymphocytes"
<p><strong>Background</strong>: Affinity-optimized T cell receptor (TCR)-engineered lymphocytes targeting tumor antigens can mediate potent antitumor responses in cancer patients, but also bear substantial risks for off-target toxicities. Most preclinical studies have focused on T cell responses to antigen-specific stimulation. In contrast, little is known on the regulation of T cell responsiveness through continuous TCR triggering and consequent tonic signaling. Here, we addressed the question whether increasing the TCR affinity can lead to chronic interactions occurring directly between TCRs and MHC-(self) molecules, which may modulate the overall functional potency of tumor-redirected CD8 T cells. For this purpose, we developed two complementary human CD8 T cell models (i.e. HLA-A2 knock-in and knock-out) engineered with incremental-affinity TCRs to the HLA-A2/NY-ESO-1 tumor antigen.<br> <strong>Methods</strong>: The impact of HLA-A2 recognition, depending on TCR affinity, was assessed at the levels of the TCR/CD3 complex, regulatory receptors, and signaling, under steady-state conditions and in kinetic studies. The quality of<br> CD8 T cell responses was further evaluated by gene expression and multiplex cytokine profiling, as well as real-time quantitative cell killing, combined with co-culture assays.<br> <strong>Results</strong>: We found that HLA-A2 per se (in absence of cognate peptide) can trigger chronic activation followed by a tolerance-like state of tumor-redirected CD8 T cells with increased-affinity TCRs. HLA-A2pos but not HLA-A2neg T cells displayed an activation phenotype, associated with enhanced upregulation of c-CBL and multiple inhibitory receptors. T cell activation preceded TCR/CD3 downmodulation, impaired TCR signaling and functional<br> hyporesponsiveness. This stepwise activation-to-hyporesponsive state was dependent on TCR affinity and already detectable at the upper end of the physiological affinity range (KD ≤ 1 μM). Similar findings were made when<br> affinity-increased HLA-A2neg CD8 T cells were chronically exposed to HLA-A2pos-expressing target cells.<br> <strong>Conclusions</strong>: Our observations indicate that sustained interactions between affinity-increased TCR and self-MHC can directly adjust the functional potential of T cells, even in the absence of antigen-specific stimulation. The<br> observed tolerance-like state depends on TCR affinity and has therefore potential implications for the design of affinity-improved TCRs for adoptive T cell therapy, as several engineered TCRs currently used in clinical trials share<br> similar affinity properties.</p>
TCRb sequencing of CD4+ and CD8+ T cells from hematological patients (part 1)
<p>This dataset contains TCRb sequencing of 177 samples from patients with aplastic anemia, myelodysplastic syndrome, immune thrombocytopenia, immunodeficiency or graft-versus-host disease and healthy controls. Samples are separated CD4+ or CD8+ cells from peripheral blood or bone marrow. The data has been produced with immunoSEQ platform (Adaptive Biotechnologies). The details regarding sample processing, sequencing and metadata can be found from the publication <em>Somatic mutations associate with clonal expansion of CD8+ T cells</em> (Lundgren et al, Science Advances, in press).</p> <p>The dataset is divided in 2 parts containing 91 (part 1) and 86 (part 2) files. Data is in immunoSEQ format (v2).</p>
Single-Cell Profiling of CD8+ T Cells in Acute Myeloid Leukemia Reveals a Continuous Spectrum of Differentiation and Clonal Hyperexpansion
<p>Data for the publication <strong>Single-Cell Profiling of CD8<sup>+</sup> T Cells in Acute Myeloid Leukemia Reveals a Continuous Spectrum of Differentiation and Clonal Hyperexpansion</strong></p>
Lactate Increases Stemness of CD8+ T Cells to Augment Anti-Tumor Immunity
<p>The immunological role of lactate in antitumor immunity is not well understood. In this study, we report lactate treatment significantly augments antitumor efficacy of immune checkpoint blockade or T cell vaccine therapy in multiple tumor models. Single cell transcriptomics and flow cytometry analysis revealed an increased subpopulation of stem-like TCF-1-expressing CD8<sup>+</sup> T cells upon lactate treatment.</p>
Divergent molecular networks program functionally distinct CD8+ skin-resident memory T cells
<p>Skin-resident CD8+ T cells comprise distinct IFN-γ- (TRM1) and IL-17-producing (TRM17) subsets that differentially contribute to immune responses. However, whether these populations employ common mechanisms to establish tissue residence is unknown. Here, we show that TRM1 and TRM17 cells navigate divergent trajectories to acquire tissue residency in skin. While TRM1 cells depend on a T-bet-Hobit-IL-15 axis, TRM17 cells develop independently of these factors. Instead, c-Maf commands a tissue-resident program in TRM17 cells parallel to that induced by Hobit in TRM1 cells, with an ICOS-c-Maf-IL-7 axis pivotal to TRM17 cell commitment. Accordingly, targeting this pathway enables ablation of skin TRM17 cells without compromising their TRM1 counterparts. Thus, skin-resident T cells rely on distinct molecular circuitries, which can be exploited to strategically modulate local immunity.</p>
Cross-reactive CD8+ T cell responses to tumor-associated antigens (TAAs) and homologous microbiota-derived antigens (MoAs)
<p><strong><span>Background: </span></strong><span>We have recently shown extensive sequence and conformational homology between tumor-associated antigens (TAAs) and antigens derived from microorganisms (MoAs). The present study aimed to assess the breadth of T-cell recognition specific to MoAs and the corresponding TAAs in healthy subjects (HS) and patients with cancer (CP).</span></p> <p><strong><span>Method: </span></strong><span>A library of >100 peptide-MHC (pMHC) combinations was used to generate DNA-barcode labelled multimers. Homologous peptides were selected from the Cancer Antigenic Peptide Database, as well as Bacteroidetes/Firmicutes-derived peptides. They were incubated with CD8+ T cells from the peripheral blood of HLA-A*02:01 healthy individuals (n=10) and cancer patients (n=16). T cell recognition was identified using tetramer-staining analysis. Cytotoxicity assay was performed using as target cells TAP-deficient T2 cells loaded with MoA or the paired TuA.</span></p> <p><strong><span>Results: </span></strong><span>A total of 66 unique pMHC recognized by CD8+ T cells across all groups were identified. Of these, 21 epitopes from microbiota were identified as novel immunological targets. Reactivity against selected TAAs was observed for both HS and CP. pMHC tetramer staining confirmed CD8+ T cell populations cross-reacting with CTA SSX2 and paired microbiota epitopes. Moreover, PBMCs activated with the MoA where shown to release IFNγ as well as to exert cytotoxic activity against cells presenting the paired TuA.</span></p> <p><strong><span>Conclusions: </span></strong><span>Several predicted microbiota-derived MoAs are recognized by T cells in HS and CP. Reactivity against TAAs was observed also in HS, primed by the homologous bacterial antigens. CD8+ T cells cross-reacting with MAGE-A1 and paired microbiota epitopes were identified in three subjects. Therefore, the microbiota can elicit an extensive repertoire of natural memory T cells to TAAs, possibly able to control tumor growth (“natural anti-cancer vaccination”). In addition, non-self MoAs can be included in preventive/therapeutic off-the-shelf cancer vaccines with more potent anti-tumor efficacy than those based on TAAs.</span></p>
Datasets for: Integrative Mapping of Human CD8+ T Cell in Inflammation and Cancer
<p>Files for the integrated pan-disease CD8+ T cell atlas: </p> <ul> <li><a href="https://zenodo.org/records/13382785/files/huARdb_v2_GEX.CD8.all_genes.h5ad.gz?download=1" target="_blank" rel="noopener">huARdb_v2_GEX.CD8.all_genes.h5ad.gz</a> : 19957 genes raw matrix </li> <li><a href="https://zenodo.org/records/13382785/files/huARdb_v2_GEX.CD8.hvg4k.h5ad?download=1" target="_blank" rel="noopener">huARdb_v2_GEX.CD8.hvg4k.h5ad</a> : 4000 highly variable genes raw matrix</li> <li><a href="https://zenodo.org/records/13382785/files/huARdb_v2_GEX.CD8.hvg4k.X_gex.npy?download=1" target="_blank" rel="noopener">huARdb_v2_GEX.CD8.hvg4k.X_gex.npy</a> : scatlasavae model embedding</li> <li><a href="https://zenodo.org/records/13382785/files/huARdb_v2_GEX.CD8.clone_subtype.csv?download=1" target="_blank" rel="noopener">huARdb_v2_GEX.CD8.clone_subtype.csv</a> : clone type definition</li> <li><a href="https://zenodo.org/records/13382785/files/huARdb_v2_GEX.CD8.hvg4k.supervised.model?download=1" target="_blank" rel="noopener">huARdb_v2_GEX.CD8.hvg4k.supervised.model</a>. scatlasavae model checkpoint</li> <li><a href="https://zenodo.org/records/13382785/files/huARdb_v2_GEX.CD8.hvg4k.h5ad?download=1" target="_blank" rel="noopener">huARdb_v2_GEX.CD8.hvg4k.h5ad</a> : Tex subset of 4000 highly variable genes raw matrix</li> <li><a href="https://zenodo.org/records/13382785/files/huARdb_v2_GEX.CD8.hvg4k.Tex.supervised.model?download=1" target="_blank" rel="noopener">huARdb_v2_GEX.CD8.hvg4k.Tex.supervised.model</a>. scatlasavae model checkpoint for the Tex subset</li> </ul> <p>Files for the TILs CD8+ T cell atlas</p> <ul> <li><a href="https://zenodo.org/records/13382785/files/adata_cd8_chu.h5ad?download=1" target="_blank" rel="noopener">adata_cd8_chu.h5ad</a>. the Chu <em>et al.</em>, 2023 Dataset</li> <li><a href="https://zenodo.org/records/13382785/files/adata_cd8_zheng.h5ad?download=1" target="_blank" rel="noopener">adata_cd8_zheng.h5ad.</a> The Zheng <em>et al.</em>, 2021 Dataset</li> </ul> <p>Files for the transfer (query) datasets:</p> <ul> <li><a href="https://zenodo.org/records/13382785/files/Zhang_LC.CD8_T.h5ad?download=1" target="_blank" rel="noopener">Zhang_LC.CD8_T.h5ad</a></li> <li><a href="https://zenodo.org/records/13382785/files/Luoma_HNSCC_TIL.CD8_T.h5ad?download=1" target="_blank" rel="noopener">Luoma_HNSCC_TIL.CD8_T.h5ad</a></li> <li><a href="https://zenodo.org/records/13382785/files/Luoma_HNSCC_PBMC.CD8_T.h5ad?download=1" target="_blank" rel="noopener">Luoma_HNSCC_PBMC.CD8_T.h5ad</a></li> <li><a href="https://zenodo.org/records/13382785/files/Watson_MELA.CD8_T.h5ad?download=1" target="_blank" rel="noopener">Watson_MELA.CD8_T.h5ad</a></li> <li><a href="https://zenodo.org/records/13382785/files/Bassez_BC.cohort1.CD8_T.h5ad?download=1" target="_blank" rel="noopener">Bassez_BC.cohort1.CD8_T.h5ad</a></li> <li><a href="https://zenodo.org/records/13382785/files/Bi_RCC.CD8_T.h5ad?download=1" target="_blank" rel="noopener">Bi_RCC.CD8_T.h5ad</a></li> <li><a href="https://zenodo.org/records/13382785/files/Caushi_NSCLC.CD8_T.h5ad?download=1" target="_blank" rel="noopener">Caushi_NSCLC.CD8_T.h5ad</a></li> <li><a href="https://zenodo.org/records/13382785/files/Liu_TNBC.CD8_T.h5ad?download=1" target="_blank" rel="noopener">Liu_TNBC.CD8_T.h5ad</a></li> <li><a href="https://zenodo.org/records/13382785/files/Borra%CC%80s_2024_Colorectal_cancer.CD8_T.h5ad?download=1" target="_blank" rel="noopener">Borràs_2024_Colorectal_cancer.CD8_T.h5ad</a></li> <li><a href="https://zenodo.org/records/13382785/files/Garner_2023_MAIT.h5ad" target="_blank" rel="noopener">Garner_2023.h5ad</a></li> <li><a href="https://zenodo.org/records/13382785/files/Vorkas_2022_MAIT.h5ad?download=1" target="_blank" rel="noopener">Vorkas_2022_MAIT.h5ad</a></li> </ul>
CD8+ T cells of healthy donors sorted for Dextramer positive cells
<p>This dataset is analyzed in the study by Schneider-Hohendorf and colleagues concerning the phenotype of antigen-specific CD8+ T cells.</p>
Integrated single-cell profiling dissects cell-state-specific enhancer landscapes of human tumor-infiltrating CD8+ T cells_Supplemental_Data
<p>Processed Datasets for:</p> <p>EGA Study ID: EGAS00001006141</p> <p>EGA Dataset ID: EGAD00001008662</p> <p> </p> <p>Find processed files and arrow files</p> <p> </p> <p>Abstract:</p> <p>Despite extensive studies on the chromatin landscape of exhausted T cells, the transcriptional wiring underlying the heterogeneous functional and dysfunctional states of human tumor-infiltrating lymphocytes (TILs) is incompletely understood. Here, we identify gene-regulatory landscapes in a wide breadth of functional and dysfunctional CD8<sup>+</sup> TIL states covering four cancer entities using single-cell chromatin profiling. We map enhancer-promoter interactions in human TILs by integrating single-cell chromatin accessibility with single-cell RNA-seq data from tumor-entity-matching samples and prioritize cell-state-specific genes by super-enhancer analysis. Besides revealing entity-specific chromatin remodeling in exhausted TILs, our analyses identify a common chromatin trajectory to TIL dysfunction and determine key enhancers, transcriptional regulators, and deregulated genes involved in this process. Finally, we validate enhancer regulation at immunotherapeutically relevant loci by targeting non-coding regulatory elements with potent CRISPR activators and repressors. In summary, our study provides a framework for understanding and manipulating cell-state-specific gene-regulatory cues from human tumor-infiltrating lymphocytes.</p>
Data used in the study "mRNA vaccination boosts spike-specific T cell memory and promotes expansion of CD45RAint TEMRA-like CD8+ T cells in COVID-19 recovered individuals"
<p>Data associated with an original research study examining T cell responses to mRNA vaccination in COVID-19 recovered individuals. 10X Cell Ranger outputs, bulk TCR sequencing data, and T cell functional (ICS) data in this study have been deposited. Authors KMB and HR contributed equally to this effort. Address correspondence to EWN.</p>
Hepatitis B surface antigen reduction is associated with hepatitis B core-specific CD8+ T cell quality
<p>The file containing post QC, count matrix, containing 6 samples as following.</p> <p>(S01:CHBN001, S02:CHBN002, S03:CHBN003, S04:CHBN004, S12:CHBN005, S14:CHBN006.)</p> <p>scRNAseq Libraries generated by 10xGenomics 5'-kit were read by NovaSeq 6000 platform. </p> <p>After sequencing, raw reads were mapped to human generated by cellranger 6.1.2, then generated count matrix were subjected to QC according to Seurat manual (mitochondrial genes <10%, ribosomal genes > 0.05%), then SCT-transformed and integrated with 3000 features. Detail of QC/integration will be described in our manuscript.</p>
CyTOF and Flow Cytometry dataset assocaited with "Early-to-mid stage idiopathic Parkinson's disease shows enhanced cytotoxicity and differentiation in CD8 T-cells in females"
<p>This dataset contains all the raw mass cytometry (CyTOF) and flow cytometry fcs files associated with Capelle <i>et al</i>. '<i>Early-to-mid stage idiopathic Parkinson's disease shows enhanced cytotoxicity and differentiation in CD8 T-cells in females',</i> <i><strong>Nature Communications</strong>, <strong>2023</strong>,</i> In Press.</p><p>The dataset contains the following information:</p><p>1, The folder " CoPImmunoPD Flow Zenodo V2.zip " contains all the raw fcs files of flow cytometry analysis and the excel table with marker information of five staining panels in the initial discovery analysis using fresh blood samples. The folder also includes the fcs files of analyzing cytotoxicity potential within CD8 T cells and of validation analyses using cryopreserved samples. Single-color/fluorochrome staining files have also been provided for the relevant experiments in the given subfolders for compensation.</p><p>2, The folder "<a href="https://zenodo.org/api/files/75c910aa-3615-4eff-a201-9d2d46e33ea0/CoPImmunoPD_CyTOF_Zenodo.zip">CoPImmunoPD_CyTOF_Zenodo.zip</a>" contains all the raw fcs files generated from the CyTOF measurements in the initial discovery analysis.</p><p><strong>To reproduce our published Figures, please be assure to first read all the accompanied readme/excel information annotation files deposited in the corresponding folders within the zip files, all the Source Data files of different main and supplementary Figure subpanels, Methods and/or any other relevant sections in our manuscript.</strong></p>
CD8+ T cell-derived CD40L mediates non-canonical cytotoxicity in CD40-expressing cancer cells
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KLF2 maintains lineage fidelity and suppresses CD8 T cell exhaustion during acute LCMV infection (LCMV DSM scRNA data and ATAC-seq)
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KLF2 maintains lineage fidelity and suppresses CD8 T cell exhaustion during acute LCMV infection (PerturbSeq Data)
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Divergent molecular networks program functionally distinct CD8+ skin-resident memory T cells
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Dataset related to article "CXCR3 Identifies Human Naive CD8+ T Cells with Enhanced Effector Differentiation Potential."
<p>In mice, the ability of naive T (T<sub>N</sub>) cells to mount an effector response correlates with TCR sensitivity for self-derived Ags, which can be quantified indirectly by measuring surface expression levels of CD5. Equivalent findings have not been reported previously in humans. We identified two discrete subsets of human CD8<sup>+</sup> T<sub>N</sub> cells, defined by the absence or presence of the chemokine receptor CXCR3. The more abundant CXCR3<sup>+</sup> T<sub>N</sub> cell subset displayed an effector-like transcriptional profile and expressed TCRs with physicochemical characteristics indicative of enhanced interactions with peptide-HLA class I Ags. Moreover, CXCR3<sup>+</sup> T<sub>N</sub> cells frequently produced IL-2 and TNF in response to nonspecific activation directly ex vivo and differentiated readily into Ag-specific effector cells in vitro. Comparative analyses further revealed that human CXCR3<sup>+</sup> T<sub>N</sub> cells were transcriptionally equivalent to murine CXCR3<sup>+</sup> T<sub>N</sub> cells, which expressed high levels of CD5. These findings provide support for the notion that effector differentiation is shaped by heterogeneity in the preimmune repertoire of human CD8<sup>+</sup> T cells.</p>
Commensal bacteria maintain a Qa-1b-restricted unconventional CD8+ T population in gut epithelium
<p>Intestinal intraepithelial lymphocytes (IELs) are characterized by an unusual phenotype and developmental pathway, yet their specific ligands and functions remain largely unknown. Here by analysis of QFL T cells, a population of CD8+ T cells critical for monitoring the MHC I antigen processing pathway, we established that unconventional Qa-1b-restricted CD8+ T cells are abundant in intestinal epithelium. We found that QFL T cells showed a Qa-1b-dependent unconventional phenotype in the spleen and small intestine of naïve wild-type mice. The splenic QFL T cells showed innate-like functionality exemplified by rapid response to cytokines or antigens, while the gut population was refractory to stimuli. Microbiota was required for the maintenance, but not the initial gut homing of QFL T cells. Interestingly, monocolonization with <em>Pediococcus pentosaceus</em>, which expresses a peptide that cross-activated QFL T cells, was sufficient to maintain QFL T cells in the intestine. Thus, microbiota is critical for shaping the Qa-1b-restricted IEL landscape.</p>
Data from: Coordinated ARP2/3 and glycolytic activities regulate the morphological and functional fitness of human CD8+ T cells
<p>CD8<sup>+</sup> T cells rely on actin cytoskeleton remodeling to search for target cells and assemble the immunological synapse (IS) for lethal hit delivery. We here investigated how the energy expenditure related to actin remodeling might influence the fitness of human cytotoxic T cells. We first established that the spreading ability of CD8<sup>+</sup> T cells in conditions of LFA-1 and TCR engagement mirrored the cytotoxic potential of these cells. Morphological and functional fitness were both potentiated by IL-2, which co-stimulated the transcription of glycolytic enzymes, actin isoforms and the subunits of the ARP2/3 complex. This molecular program scaled with F-actin content and cell spreading. Blockade of glycolysis impaired F-actin remodeling at the lamellipodium, chemokine-driven motility and synaptic adhesion, while blockade of mitochondrial OXPHOS affected F-actin less severely and selectively reduced cell elongation during confined migration. Although T cells deficient for the ARP2/3 subunit ARPC1B increased their ATP content upon IL-2 exposure, their morphological and functional defects were only partially corrected, pointing to the pivotal position of ARP2/3 mediated actin polymerization as integrator of T cell energetic state. Our study therefore highlights that the ability of effector T cells to migrate, form IS and ultimately kill target cells depends on a tight coordination of their metabolic and actin remodeling activities.</p>
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Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
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