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1,395 results for “Tumor immunity”
Combined tumor and immune signals from genomes or transcriptomes predict outcomes of checkpoint inhibition in melanoma
<p>Code and data for manuscript "Combined tumor and immune signals from genomes or transcriptomes predict outcomes of checkpoint inhibition in melanoma"</p>
Immune selection determines tumor antigenicity and influences response to checkpoint inhibitors
<p>R markdown files and source data to reproduce figures from the manuscript "Immune selection determines tumor antigenicity and influences response to checkpoint inhibitors"</p>
Immune selection determines tumor antigenicity and influences response to checkpoint inhibitors - Dataset
<p>Dataset used from the publication "Tumor and Microenvironment Evolution during Immunotherapy with Nivolumab" published in </p> <p>Cell. 2017 Nov 2;171(4):934-949.e16.</p> <p> doi: 10.1016/j.cell.2017.09.028. Epub 2017 Oct 12.</p>
Data from: Desmoplastic stroma restricts T cell extravasation and mediates immune exclusion and immunosuppression in solid tumors
<p>In this study, we used our modified <span>precision-cut tumor slice assay of tumors treated with CAR T cells <em>in vivo </em></span><span>prior to harvest and harvested at different time-points post-treatment, which can better reflect the behavior of CAR T cells in the TME </span><em>in vivo</em><span>.</span></p>
Arginase Inhibitor INCB001158 as a Single Agent and in Combination With Immune Checkpoint Therapy in Patients With Advanced/Metastatic Solid Tumors
ClinicalTrials.gov study NCT02903914. IPD Sharing: NO. Countries: 4. Publications: 2.
Association of BAL Fluid T-Cell Immune Activity With Tumor PD-L1 Expression and Its Prognostic Value: A Prospective Observational Study
ClinicalTrials.gov study NCT07331701. IPD Sharing: NO. Countries: 1. Publications: 7.
METIMMOX: Colorectal Cancer METastasis - Shaping Anti-tumor IMMunity by OXaliplatin
ClinicalTrials.gov study NCT03388190. IPD Sharing: NO. Countries: 1. Publications: 13.
Integrated Discovery of New Immuno-Molecular Actionable Biomarkers for Tumors With Immune-suppressed Environment
ClinicalTrials.gov study NCT03706625. IPD Sharing: YES. Countries: 1. Publications: 0.
Data from: DGKα/ζ inhibition lowers the TCR affinity threshold and potentiates anti-tumor immunity
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Mutant IDH1 inhibition induces dsDNA sensing to activate tumor immunity
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Data from: Desmoplastic stroma restricts T cell extravasation and mediates immune exclusion and immunosuppression in solid tumors
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YY1 enhances HIF-1α stability in tumor-associated macrophages to suppress anti-tumor immunity of prostate cancer
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BAF155 Methylation Drives Metastasis By Hijacking Super-enhancers and Subverting Anti-tumor Immunity
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Mitochondrial respiratory complex III sustains IL-10 production in activated macrophages and promotes tumor-mediated immune evasion
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IL4I1 Is a Metabolic Immune Checkpoint that Activates the AHR and Promotes Tumor Progression
<p>These data objects were generated for the manuscript " IL4I1 Is a Metabolic Immune Checkpoint that Activates the AHR and Promotes Tumor Progression".</p>
Data generated for the manuscript: "Increased 'selfness' in the tumor emerges as a possible immune scuplting mechanism: A pan-cancer data analysis of 32 solid tumors in TCGA"
<p>This submission has processed data generated for the manuscript: "Increased 'selfness' in the tumor emerges as a possible immune scuplting mechanism: A pan-cancer data analysis of 32 solid tumors in TCGA".</p> <p>The `data` folder contains processed information for the Human Protein Atlas (HPA) and The Cancer Genome Atlas (TCGA) datasets. The HPA data is found in `data/hpa` and contains gene ranks used to compute the thymus-likeness score (TLS) and files where the TLS has been calculated for the HPA tissues. The TCGA data can be found in `data/proc`, where individual RDS files have been given for each analyzed cohort. These RDS files contain the results of the cutoff scanning procedure mentioned in the manuscript and account for the bulk of the data generated for this study. RDS files can be loaded using the `readRDS` function in an R session. Other information used to create plots is in the `data` folder.</p> <p>The `plots` folder contain the result of plotting the entireity of the cutoff scanning procedure. The manuscript only contains plots for the 28 cohorts where a significant difference in terms of immune difference is observed, and that too, only the final heuristic plots. The `plots/tcga/immuneres` folder has plots at different levels: (i) single cell category/single deconvolution method with permutation tests (ii) single cell category/multiple deconvolution methods and (iii) significant cell categories/representative deconvolution method. Only (iii) is present in the manuscript. Overall, this folder should contain ~2000 plots.</p> <p>The code used to generate this study is deposited at: https://gitlab.com/narencs179/thymus-like-score</p>
ARID1A suppresses R-loop mediated STING-Type I Interferon pathway activation of anti-tumor immunity
<p>Clinical trials have identified ARID1A mutations as enriched among patients who respond favorably to Immune Checkpoint Blockade (ICB) in several solid tumor types independent of microsatellite instability. We show that ARID1A loss in murine models is sufficient to induce anti-tumor immune phenotypes observed in ARID1A mutant human cancers, including increased CD8+ T cell infiltration and cytolytic activity. ARID1A deficient cancers upregulated an interferon (IFN) gene expression signature, the ARID1A-IFN signature, associated with increased R-loops and cytosolic single stranded DNA (ssDNA). Overexpression of the R-loop resolving enzyme, RNASEH2B, or cytosolic DNase, TREX1, in ARID1A deficient cells prevented cytosolic ssDNA accumulation and ARID1A-IFN gene upregulation. Further, the ARID1A-IFN signature and anti-tumor immunity were driven by STING dependent Type I IFN signaling, which was required for improved responsiveness of ARID1A mutant tumors to ICB treatment. These findings define a molecular mechanism underlying anti-tumor immunity in ARID1A mutant cancers.</p>
Distant metastases of breast cancer resemble primary tumors in tumor cell composition but differ in immune cell phenotypes
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Immune single-cell RNA-seq data from PyMT-M tumor and its peripheral blood samples
<p><em>Immune single-cell RNA-seq data collection and preprocessing</em></p> <p>Blood and tumor samples were harvested from PyMT-M tumor-bearing mice. Blood samples (n=3) are collected retro-orbitally using caliper tubes and processed with red blood cell lysis buffer (Tonbo Biosciences) before library preparation. A tumor sample are dissociated with Tumor Dissociation Kit following the manufacturer’s instructions (Miltenyi Biotec). After isolation and filtering through a 70µm filter, CD45+DAPI- cells were sorted using FACSAria cell sorter (BD Biosciences) at the Cytometry and Cell Sorting Core. The single-cell libraries were prepared using Chromium Controller (10X Genomics) at the Single Cell Genomics Core and sequenced using NovaSeq 6000 at the Genomics and RNA Profiling Core of Baylor College of Medicine. The FASTQ files were processed using Cell Ranger pipelines (10X Genomics) to generate feature-barcode matrices.</p> <p><em>Integrating immune single-cell RNA-seq data from the blood and tumor of PyMT-M mouse</em></p> <p>We followed the Seurat tutorial on single-cell RNA integration from <a href="https://satijalab.org/seurat/articles/integration_introduction.html">https://satijalab.org/seurat/articles/integration_introduction.html</a>. Specifically, both datasets were library-size normalized and log-scaled. Then, variable genes from both datasets were extracted, and overlapped variable genes were used as anchors to integrate the two datasets to generate a combined immune single-cell RNA-seq dataset.</p> <p> </p> <p><em>Immune cell type annotation using SingleR</em></p> <p>After having the integrated immune single-cell RNA-sequencing data, we performed the standard pipeline for clustering, including scaling the expression data, performing dimension reduction using PCA and UMAP, and finding clusters by a shared nearest neighbor (SNN) modularity optimization (<a href="https://satijalab.org/seurat/articles/integration_introduction.html">https://satijalab.org/seurat/articles/integration_introduction.html</a>). Then, we used the R package <em>SingleR </em>to assign cell-type labels to each identified cluster using the <em>ImmGen</em> reference data from the Immunological Genome Project.</p> <p> </p>
Data from: The CD73 immune checkpoint promotes tumor cell metabolic fitness
<p>CD73 is an ectonucleotidase overexpressed on tumor cells that suppresses anti-tumor immunity. Accordingly, several CD73 inhibitors are currently being evaluated in the clinic, including in large randomized clinical trials. Yet, the tumor cell-intrinsic impact of CD73 remains largely uncharacterized. Using metabolomics, we discovered that CD73 significantly enhances tumor cell mitochondrial respiration and aspartate biosynthesis. Importantly, rescuing aspartate biosynthesis was sufficient to restore proliferation of CD73-deficient tumors in immune-deficient mice. Seahorse analysis of a large panel of mouse and human tumor cells demonstrated that CD73 enhanced oxidative phosphorylation (OXPHOS) and glycolytic reserve. Targeting CD73 decreased tumor cell metabolic fitness, increased genomic instability and suppressed poly ADP ribose polymerase (PARP) activity. Our study thus uncovered an important immune-independent function for CD73 in promoting tumor cell metabolism and provides the rationale for previously unforeseen combination therapies incorporating CD73 inhibition.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.