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162 results for “immune infiltrates”
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>
Immune repertoire profiling reveals that clonally expanded B and T cells infiltrating diseased human kidneys can also be tracked in the blood
<p>Recent advances in high-throughput sequencing allow for the competitive analysis of the human B and T cell immune repertoire. In this study we compared Immunoglobulin and T cell receptor repertoires of lymphocytes found in kidney and blood samples of 10 patients with various renal diseases based on next-generation sequencing data.</p>
Data used in analyses of Danaher et al. 2024 "Childhood-onset lupus nephritis is characterized by complex interactions between kidney stroma and infiltrating immune cells"
<p>CosMx 1000-plex data and R code from childhood-onset lupus nephris samples, generated for the article Danaher et al. 2024 "Childhood-onset lupus nephritis is characterized by complex interactions between kidney stroma and infiltrating immune cells".</p>
Regulatory T cell therapy is associated with distinct immune regulatory lymphocytic infiltrates in kidney transplants: Spatial transcriptomic dataset and images
<p>The outputs of the NanoString GeoMx DSP platform were concatenated into three xlsx files, each illustrating a separate experiment along with their sample annotations. This technique analyzes protein or RNA abundance within regions of interest (ROIs) or specific cell segments selected based on histological features and immunofluorescence. In this repository, the concatenated GeoMx output files are presented, along with PowerPoint presentations for each biopsy that show immunofluorescence images of the selected ROIs and/or cell segments.</p> <ul> <li><strong>Protein_Full ROI:</strong> This experiment measured the abundance of 41 proteins in discrete regions of interest (ROIs) within transplant kidney biopsies.</li> <li><strong>Protein_Rare cell:</strong> This experiment measured the abundance of 40 proteins in specific cell segments, such as CD4+FoxP3- cells vs. CD4+FoxP3+ cells, within transplant kidney biopsies.</li> <li><strong>RNA:</strong> This experiment measured the abundance of 90 genes in discrete ROIs within transplant kidney biopsies.</li> </ul>
An ssGSEA Based Immune-related Gene Prognostic Signature Combining Immune Infiltration and Immune Checkpoint for Breast Cancer Patients
<p>This is the gene expression and related clinical data of breast cancer patients obtained from TCGA. Original codes and data from GEO database could be found in GitHub via link "https://github.com/Grevilblois/R-codes-for-manuscript".</p>
A machine learning model reveals expansive downregulation of ligand-receptor interactions enhancing lymphocyte infiltration in melanoma with developed resistance to Immune Checkpoint Blockade
<p>Data repository containing the data to reproduce the results and findings that are published in:</p> <p>Sahni, S., Wang, B., Wu, D. <em>et al.</em> A machine learning model reveals expansive downregulation of ligand-receptor interactions that enhance lymphocyte infiltration in melanoma with developed resistance to immune checkpoint blockade. <em>Nat Commun</em> <strong>15</strong>, 8867 (2024). https://doi.org/10.1038/s41467-024-52555-4</p>
Data for: Preliminary study based on methylation and transcriptome gene sequencing of lncRNAs and immune infiltration in hypopharyngeal carcinoma
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Dataset related to article "Single-Cell Sequencing of Mouse Heart Immune Infiltrate in Pressure Overload-Driven Heart Failure Reveals Extent of Immune Activation."
<p>BACKGROUND:</p> <p>Inflammation is a key component of cardiac disease, with macrophages and T lymphocytes mediating essential roles in the progression to heart failure. Nonetheless, little insight exists on other immune subsets involved in the cardiotoxic response.</p> <p>METHODS:</p> <p>Here, we used single-cell RNA sequencing to map the cardiac immune composition in the standard murine nonischemic, pressure-overload heart failure model. By focusing our analysis on CD45<sup>+</sup> cells, we obtained a higher resolution identification of the immune cell subsets in the heart, at early and late stages of disease and in controls. We then integrated our findings using multiparameter flow cytometry, immunohistochemistry, and tissue clarification immunofluorescence in mouse and human.</p> <p>RESULTS:</p> <p>We found that most major immune cell subpopulations, including macrophages, B cells, T cells and regulatory T cells, dendritic cells, Natural Killer cells, neutrophils, and mast cells are present in both healthy and diseased hearts. Most cell subsets are found within the myocardium, whereas mast cells are found also in the epicardium. Upon induction of pressure overload, immune activation occurs across the entire range of immune cell types. Activation led to upregulation of key subset-specific molecules, such as oncostatin M in proinflammatory macrophages and PD-1 in regulatory T cells, that may help explain clinical findings such as the refractivity of patients with heart failure to anti-tumor necrosis factor therapy and cardiac toxicity during anti-PD-1 cancer immunotherapy, respectively.</p> <p>CONCLUSIONS:</p> <p>Despite the absence of infectious agents or an autoimmune trigger, induction of disease leads to immune activation that involves far more cell types than previously thought, including neutrophils, B cells, Natural Killer cells, and mast cells. This opens up the field of cardioimmunology to further investigation by using toolkits that have already been developed to study the aforementioned immune subsets. The subset-specific molecules that mediate their activation may thus become useful targets for the diagnostics or therapy of heart failure.</p> <p> </p> <p>This dataset is created in .ets form, we attach a pdf with the information about.</p>
Data from: CXCL17 expression predicts poor prognosis and correlates with adverse immune infiltration in hepatocellular carcinoma
CXC ligand 17 (CXCL17) is a novel CXC chemokine whose clinical significance remains largely unknown. In the present study, we characterized the prognostic value of CXCL17 in patients with hepatocellular carcinoma (HCC) and evaluated the association of CXCL17 with immune infiltration. We examined CXCL17 expression in 227 HCC tissue specimens by immunohistochemical staining, and correlated CXCL17 expression patterns with clinicopathological features, prognosis, and immune infiltrate density (CD4 T cells, CD8 T cells, B cells, natural killer cells, neutrophils, macrophages). Kaplan-Meier survival analysis showed that both increased intratumoral CXCL17 (P = 0.015 for overall survival [OS], P = 0.003 for recurrence-free survival [RFS]) and peritumoral CXCL17 (P = 0.002 for OS, P<0.001 for RFS) were associated with shorter OS and RFS. Patients in the CXCL17low group had significantly lower 5-year recurrence rate compared with patients in the CXCL17high group (peritumoral: 53.1% vs. 77.7%, P<0.001, intratumoral: 58.6% vs. 73.0%, P = 0.001, respectively). Multivariate Cox proportional hazards analysis identified peritumoral CXCL17 as an independent prognostic factor for both OS (hazard ratio [HR] = 2.066, 95% confidence interval [CI] = 1.296–3.292, P = 0.002) and RFS (HR = 1.844, 95% CI = 1.218–2.793, P = 0.004). Moreover, CXCL17 expression was associated with more CD68 and less CD4 cell infiltration (both P<0.05). The combination of CXCL17 density and immune infiltration could be used to further classify patients into subsets with different prognosis for RFS. Our results provide the first evidence that tumor-infiltrating CXCL17+ cell density is an independent prognostic factor that predicts both OS and RFS in HCC. CXCL17 production correlated with adverse immune infiltration and might be an important target for anti-HCC therapies.
Processed Seurat Object of scRNAseq data from wildtype and CaMKK2 KO immune infiltrate of CT2a preclinical murine glioma
<p>This repository contains the processed Seurat objects generated from the raw data deposited at the Gene Expression Omnibus (GEO) under GSE197879.</p> <p>Details about the experiment and sequencing are available under GSE197879.</p> <p>Information on how the Seurat objects were created can be found in this GitHub repository https://github.com/wht10/CT2A_scRNAseq_CaMKK2KOvWT .</p> <p>Notable metadata within each Seurat object:</p> <p>1. Processed_CD45_Live_Fig2b.rds</p> <ul> <li>Genotype - whether the cell is from a WT or CaMKK2 KO mouse</li> <li>HTO_maxID - The biological replicate that the cell came from (4 biological replicates per genotype)</li> <li>MouseID - A concatenation between the genotype and HTO_maxID, providing a unique identifier for each biological replicate</li> <li>Cell.Type - The cell type annotations for each cell. Can be assigned to "Idents()" to change the name of the cell identities.</li> <li>Geno.Ident - A concatenation between Genotype and Cell.Type. By re-assigning this to "Idents()" "FindMarkers()" can be used to investigate differentially expressed genes within a cell-type between genotypes. </li> </ul> <p>2. Reclustered_TILs_Fig3a.rds</p> <ul> <li>Genotype - whether the cell is from a WT or CaMKK2 KO mouse</li> <li>HTO_maxID - The biological replicate that the cell came from (4 biological replicates per genotype)</li> <li>MouseID - A concatenation between the genotype and HTO_maxID, providing a unique identifier for each biological replicate</li> <li>Celltype - The cell type annotations for each cell. Can be assigned to "Idents()" to change the name of the cell identities.</li> <li>Geno_Ident - A concatenation between Genotype and cell-type. By re-assigning this to "Idents()" "FindMarkers()" can be used to investigate differentially expressed genes within a cell-type between genotypes. </li> </ul>
Spatially variant immune infiltration scoring in human cancer tissues
<p>IMC raw dataset for cohort 1 and cohort 2 for the paper: "Spatially variant immune infiltration scoring in human cancer tissues"</p>
Single-cell heterogeneity of EGFR and CKD4 co-amplification is linked to immune infiltration in glioblastoma
<p>This upload contains RDS objects of preprocessed publicly available scRNAseq data, required to run scRNAseq analyses in the manuscript "Single cell heterogeneity of EGFR and CDK4 co-amplification is linked to immune infiltration in glioblastoma". The corresponding GitHub repo <a href="https://github.com/Michorlab/GBM_OR_immune">https://github.com/Michorlab/GBM_OR_immune</a> contains code to analyze the data here, as well as plots and tables generated on the basis of this data.</p>
Characterization of Circulating and Tumor-infiltrating Immune Cells in Malignant Brain Tumors
ClinicalTrials.gov study NCT05831631. IPD Sharing: NO. Countries: 1. Publications: 14.
A Study of Metastatic Gastrointestinal Cancers Treated With Tumor Infiltrating Lymphocytes in Which the Gene Encoding the Intracellular Immune Checkpoint CISH Is Inhibited Using CRISPR Genetic Enginee
ClinicalTrials.gov study NCT04426669. IPD Sharing: Not stated. Countries: 1. Publications: 5.
Chemotherapy and Immunotherapy as Treatment for MSS Metastatic Colorectal Cancer With High Immune Infiltrate
ClinicalTrials.gov study NCT04262687. IPD Sharing: NO. Countries: 1. Publications: 21.
Stromal Tumor-Infiltrating Lymphocyte Levels Are Associated With Immune Checkpoint Proteins In Triple Negative Breast Cancer Patients Receiving Neoadjuvant Chemotherapy
ClinicalTrials.gov study NCT06965361. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Data from: CXCL17 expression predicts poor prognosis and correlates with adverse immune infiltration in hepatocellular carcinoma
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Data from: Identification and validation of a novel immune-related signature associated with macrophages and CD8 T cell infiltration predicting overall survival for hepatocellular carcinoma
<p><b>Background:</b> Although the effects of macrophages and CD8 T cell infiltration on clinical outcomes have been widely reported, the association between immunity-associated gene with them for hepatocellular carcinoma (HCC) remains unclear.</p> <p><b>Materials and methods: </b>The ssGSEA served for quantifying the macrophages as well as CD8 T cell infiltration in the HCC samples obtained from TCGA database. Kaplan-Meier(KM) survival assay was used to determine the associations between macrophages and CD8 T cell infiltration with OS. LASSO Cox regressive method assisted in developing an immune gene signature as well as building a risk score. The performance was evaluated by the time-dependent ROC together with the KM survival analysis. The ICGC database were adopted for external verification. CIBERSORT was applied to the correlation analysis on the immune-related signature and the immunocyte infiltration. GSEA were employed exploring the underlying molecular mechanisms.</p> <p><b>Results:</b> Increased CD8+ T cell infiltration was associated with longer OS, whereas a greater infiltration of macrophages was related to shorter OS. There were 398 differential expression genes (DEGs) between the high- and low infiltration groups with the "edgeR" package. A prognostic signature consisted of 10 immune genes was built in TCGA and examined in ICGC. The uniform cutoff (0.927) was adopted for separating sufferers into the high-risk(HR) and low-risk(LR) groups. The ROC curves revealed that the AUC data for this signature predicting 1,2,3,4 and 5 year were all above 0.7 in both TCGA and ICGC cohort and patients in the HR<sub> </sub>group exhibited evidently weaker prognostic results compared with the LR group. The HR<sub> </sub>group presented evidently greater Tregs and Macrophage M0 relative to the LR group, whereas the LR group saw the enrichment of CD8 T cells.</p> <p><b>Conclusion:</b> The immune signature associated with macrophages as well as CD8 T cell infiltration has reliable prognostic and predictive value for HCC patients.</p>
Data from: Identification and validation of a novel immune-related signature associated with macrophages and CD8 T cell infiltration predicting overall survival for hepatocellular carcinoma
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Single-cell RNAseq analysis of peripheral blood and tumor infiltration immune cells in glioblastoma
GEO Series GSE247824. Homo sapiens. 37 samples. Type: Expression profiling by high throughput sequencing.
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Allen Brain Atlas
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.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.