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830 results for “Tumor microenvironment”
Dataset of 'HIV infection is associated with compromised tumor microenvironment adaptive immune reactivity in Hodgkin Lymphoma'
<p><span><span>§<span> </span></span></span><strong><span>:</span></strong><span>The data were generated using the i) GeoMx Digital Spatial Profiler (DSP) platform developed by Nanostring Technologies. GeoMx analysis utilizes <em>in situ </em>RNA hybridization with Whole Atlas Transcriptome probe (Nanostring) and ii) HTG platform (Immune Response kit) Our dataset comprises samples from donors categorized as HLposHIVnegEBVneg, HLposHIVposEBVpos, or HLposHIVnegEBVpos (HL: Hodgkin Lymphoma). Regions of interest (ROI) were spatially profiled to capture distinct molecular signatures associated with these donor categories.</span></p>
Datasets: Natural killer cells associate with malignant epithelial cells in the pancreatic ductal adenocarcinoma tumor microenvironment
<p>The following are necessary data files for the manuscript "Natural killer cells associate with malignant epithelial cells in the pancreatic ductal adenocarcinoma tumor microenvironment":</p> <ul> <li>.zip files for TMA_1, TMA_2, TMA_3, and TMA_4 are .mcd files acquired from imaging mass cytometry (IMC) for each slide of the pancreas TMA slide series</li> <li>pancreas_TMA_sample_info.xlxs includes info on all samples of the TMA slide series that were imaged by IMC</li> <li>custom_gates_0.zip includes histoCAT-derived single cell data files from all IMC samples in the pancreas TMA to be used for single cell analyses in R</li> <li>PDAC_IMC.RDS is a Seurat object of the IMC-derived PDAC single cell data to use for single cell and spatial analyses</li> <li>PDAC_sce is a SingleCellExperiment object of IMC-derived PDAC single cell data to use for spatial analyses</li> <li>mat.RDS is a distance matrix of PDAC cell types to use in R to generate network graph (Figure 2)</li> </ul> <p> </p> <p> </p>
Spatial immunophenotyping of the tumor microenvironment in non-small cell lung cancer
<p>A dataset with spatial immune cell information on a lung cancer cohort from Uppsala University Hospital, Sweden, with anonymized clinical data. For more information please refer to the 'readme' file and the original study (https://doi.org/10.1016/j.ejca.2023.02.012).</p>
Additional data: Longitudinal single-cell multiomic atlas of high-risk neuroblastoma reveals chemotherapy-induced tumor microenvironment rewiring
<p>This repository provides additional data for the manuscript titled "Longitudinal single-cell multiomic atlas of high-risk neuroblastoma reveals chemotherapy-induced tumor microenvironment rewiring", currently under revision at Nature Genetics. The primary data cohort has been deposited in the HTAN data portal. This repository includes processed 10x Xenium spatial transcriptomic data for six TH-MYCN mice (three chemotherapy-treated and three treatment-naive) as well as processed scRNA-seq data for CHLA15 and CHLA20 neuroblastoma (NBL) cells. The scRNA-seq data includes mono-cultured, co-cultured cells with THP-1 macrophages, and co-culture cells treated with Afatinib/CRM197. </p>
Dataset supporting the paper: Deciphering Oxygen Distribution and Hypoxia Profiles in the Tumor Microenvironment: A Data-Driven Mechanistic Modeling Approach
<p>The necessary image files for the paper titled "Deciphering Oxygen Distribution and Hypoxia Profiles in the Tumor Microenvironment: A Data-Driven Mechanistic Modeling Approach"</p>
Uncovering the spatial landscape of molecular interactions within the tumor microenvironment through latent spaces (Figures)
<p>High resolution figures related to the below manuscript:</p> <p>Atul Deshpande, Melanie Loth, et al., <a href="https://doi.org/10.1101/2022.06.02.490672">Uncovering the spatial landscape of molecular interactions within the tumor microenvironment through latent spaces</a>. <em>bioRxiv</em> 2022. doi:10.1101/2022.06.02.490672</p>
Tumor-Immune Microenvironment Revealed by Imaging Mass Cytometry in a Metastatic Sarcomatoid Urothelial Carcinoma with a Prolonged Response to Pembrolizumab - IMC data
<blockquote> <p>Sarcomatoid urothelial carcinoma (SUC) is a rare subtype of urothelial carcinoma (UC), that typically presents at an advanced stage compared to more common variants of UC. Locally advanced and metastatic UC have a poor long-term survival following progression on first-line platinum-based chemotherapy. Antibodies directed against the programmed cell death 1 protein (PD-1) or its ligand (PD-L1) are now approved to be used in these scenarios. The need for reliable biomarkers for treatment stratification is still under research. Here we present a novel case report of the first Image Mass Cytometry (IMC) analysis done in SUC to investigate the immune cell repertoire and PD-L1 expression in a patient who presented with metastatic SUC and experienced a prolonged response to the anti-PD1 immune checkpoint inhibitor pembrolizumab after progression on first line chemotherapy. This case report provides an important platform for translating these findings to a larger cohort of UC and UC variants.</p> </blockquote> <p>We make available TIFF files containing imaging mass cytometry data for 4 regions of interest of a sample of metastatic sarcomatoid urothelial carcinoma. The order of the axis in the image stacks is "CYX". The CSV files indicate the identity of the channels.</p>
Multiplexed imaging mass cytometry reveals distinct tumor-immune microenvironments linked to immunotherapy responses in melanoma
<p><strong>- melanoma_IMC_data.zip</strong></p> <p>The zip file contains the raw IMC images (in the raw_tiff folder) and corresponding single cell masks (in the mask folder) associated with the paper "Multiplexed imaging mass cytometry reveals distinct tumor-immune microenvironments linked to immunotherapy responses in melanoma". The MCD files by CyTOF IMC were exported to a multi-channel TIFF file including 41 channels, and the order of the channel was provided in the <strong>Melanoma_panel.csv</strong>. </p> <p><strong>- Melanoma_code_data.zip</strong></p> <p>The zip file contains the 4 folders described as follows: </p> <ul> <li>Folder ”data“: the processed data for the result shown in paper<br> - Folder "input": <br> - sc_data.csv: the single cell protein expression data;<br> - Folder "abundance": the cell type abundance files;<br> - Folder "clidata": the response and survival data for 4 melanoma datasets used in the paper; <br> - Folder "hc_result": TME archetypes annotation for each sample/ROI from hierarchical clustering;<br> - Folder "ICB": data for ICB analysis (presented in FigS3);<br> - Folder "meta": panel file for clustering;<br> - Folder "RNAseq_data": the RNAseq data for 4 melanoma datasets used in the paper;<br> - Folder "RNAseq_deconv": the result of cell type deconvolution from bulk RNAseq; <br> - Folder "spatial": data for neighbourhood analysis (presented in Fig3, FigS4).<br> - Folder "output": intermediate result for analysis.</li> <li>Folder "Rscript": R scripts for reproducing results in the paper.<br> - generate_Figs.Rmd: ploting figures presented in the paper;<br> - functions.R: functions used for analysis;<br> - Clustering.Rmd: determining cell types based on marker intensities;<br> - Spatial_analysis.Rmd: neighbourhood analysis to get significant interction/avoidance cell relationships.</li> <li>Folder "Figs": figures presented in paper.</li> <li>Folder "HE_figs": the H&E image and the ROIs distribution for each sample.</li> </ul>
INSPIRE-seq simultaneously selects nanobodies for immune epitopes in the complex tumor microenvironment
<p>scRNAseq of CD45 magnetic microbeads enriched cells were isolated form Py8119 bearing mice (three mice per pool/group) two hours after injection of either PBS, insertless phage display, CD45, DCs, or CD8 specific VHHs phage display libraries. </p>
Characterization of the tumor-immune microenvironment in hepatocellular carcinoma by highly multiplexed imaging mass cytometry
<p>Imaging mass cytometry data of 54 HCC patients. </p> <ul> <li>DC_img_normalized: Preprocessed and normalized multistack .tiff images. Each stack represents one channel. Channel annotations are stored in the ICICohort_panel.csv file. ROIs are located in the tumor, interface and adjacent liver as indicated in the file name.</li> <li>DC_cellmasks: Masks identifying individual cells on the images.</li> <li>DC_stromamasks: Masks identifying stromal and parenchymal regions on the image.</li> <li>DCCohort_panel.csv: table containing channel information (metal tag and marker).</li> </ul> <p>Patient metadata may be found as supplementary table 2 of DOI <a href="https://doi.org/10.1136/gutjnl-2024-332837" target="_blank" rel="noopener noreferrer"> 10.1136/gutjnl-2024-332837 </a>.</p>
Respiratory Complex I Regulates Dendritic Cell Maturation in Explant Model of Human Tumor Immune Microenvironment
<p>Source data for the paper, "Respiratory Complex I Regulates Dendritic Cell Maturation in Explant Model of Human Tumor Immune Microenvironment."<br><br>This includes nanostring gene expression profiling of primary human tumor material ("fresh" in the data, these samples are taken directly after enzymatic digestion) and the corresponding 3D Patient-Derived Explant Culture (PDEC). <br><br>transfer_257851_files_0a119f4d.zip refers to the mouse spatial transcriptomics data.<br><br>DE_results_Metformin/LPS files refer to differentially expressed genes of human monocyte-derived dendritic cells of 6 individual donors to control untreated dendritic cells after 24hr treatment. <br><br> Also includes the original Seurat.rds file for the scSEQ of primary tumor material (fresh) vs. PDEC<br><br><br><br><br> </p>
QPCTL regulates macrophage and monocyte abundance and inflammatory signatures in the tumor microenvironment
<p><strong>The enzyme glutaminyl-peptide cyclotransferase-like protein (QPCTL) catalyzes the formation of pyroglutamate residues at the NH<sub>2</sub>-terminus of proteins, thereby influencing their biological properties. A number of studies have implicated QPCTL in the regulation of chemokine stability. Furthermore, QPCTL activity has recently been shown to be critical for the formation of the high affinity SIRPa binding site of the CD47 “don’t-eat-me” protein. Based on the latter data, interference with QPCTL activity—and hence CD47 maturation—may be proposed as a means to promote anti-tumor immunity. However, the pleiotropic activity of QPCTL makes it difficult to predict the effects of QPCTL inhibition on the tumor microenvironment (TME). Using a syngeneic mouse melanoma model, we demonstrate that QPCTL deficiency alters the intra-tumoral monocyte-to-macrophage ratio, results in a profound increase in the presence of pro-inflammatory cancer-associated fibroblasts (CAFs) relative to immunosuppressive TGF-b1-driven CAFs, and leads to an increased IFN and decreased TGF-b transcriptional response signature in tumor cells. Importantly, the functional relevance of the observed TME remodeling is demonstrated by the synergy between QPCTL deletion and anti PD-L1 therapy, sensitizing an otherwise refractory melanoma model to anti-checkpoint therapy. Collectively, these data provide support for the development of strategies to interfere with QPCTL activity as a means to promote tumor-specific immunity.</strong></p>
Heterogeneity of RNA editing in mesothelioma and how RNA editing enzyme ADAR2 affects mesothelioma cell growth, response to chemotherapy and tumor microenvironment
<p>Raw data supporting the manuscript</p>
Increased spatial coupling of integrin and collagen IV in the immunoresistant clear-cell renal-cell carcinoma tumor microenvironment - Nanostring CosMx SMI Data
<p>Data export from Nanostring CosMx SMI, directly from Nanostring, in Seurat Object format for use in R. Clear cell renal cell carcinoma and papillary renal cell carcinoma were profiled before and after exposure to immunotherapy, with and without sarcomatoid features in clear cell tumors. Each tumor had a field of view in the stromal compartment and field of view in the tumor compartment.</p> <p>For appropriate clinical information associated with this study, please contact Dr. Brandon Manley.</p>
Hepatocellular carcinoma (HCC) Tumor microenvironment is more suppressive than colorectal cancer liver metastasis (CRLM) Tumor microenvironment.
<p><strong>Background and purpose:</strong> While HCC is an inflammation-associated cancer, CRLM develop on permissive healthy liver microenvironment. To evaluate the immune aspects of these two different environments, peripheral blood-(PB), peritumoral-(PT) and tumoral tissues-(TT) from HCC and CRLM patients were evaluated.</p> <p><strong>Methods:</strong> 40 HCC and 34 CRLM were enrolled and freshly TT, PT and PB were collected at the surgery. PB-, PT- and TT-derived CD4<sup>+</sup>CD25<sup>+ </sup>Tregs, M/PMN-MDSC and PB-derived CD4<sup>+</sup>CD25<sup>− </sup>Teffector cells (Teffs) were isolated and characterized. Tregs function was also evaluated in the presence of the CXCR4 inhibitor, Peptide-R29, AMD3100 or anti-PD1. RNA was extracted from PB/PT/TT-tissues and tested for FOXP3, CXCL12, CXCR4, CCL5, IL-15, CXCL5, Arg-1, N-cad, Vim, CXCL8, TGFβ and VEGF-A expression.</p> <p><strong>Results:</strong> In HCC/CRLM-PB higher number of functional Tregs, CD4<sup>+</sup>CD25<sup>hi</sup>FOXP3<sup>+</sup> were detected, although PB-HCC Tregs exert a more suppressive function as compared to CRLM-Tregs. In HCC/CRLM-TT Tregs were highly represented with Activated/ENTPD-1<sup>+</sup>Tregs prevalent in HCC. As compared to CRLM, HCC overexpressed CXCR4 and N-cadherin/Vimentin in a contest rich of arginase and CCL5. Monocytic-MDSCs were highly represented in HCC/CRLM while high Polymorphonuclear-MDSCs were detected only in HCC. Interestingly, CXCR4-PB-Tregs function was impaired in HCC/CRLM by the CXCR4 inhibitor R29.</p> <p><strong>Conclusion:</strong> In HCC and CRLM, peripheral blood, peritumoral and tumoral tissues-Tregs are highly represented and functional. Nevertheless, HCC display a more immunosuppressive TME due to Tregs, MDSCs, intrinsic tumor features (CXCR4, CCL5, arginase) and the contest in which it develops. As CXCR4 is overexpressed in HCC/CRLM tumor/TME cells, CXCR4 inhibitors may be considered for double hits therapy in liver cancer patients.</p>
Deep Learning-based 3D single-cell imaging analysis pipeline for quantifying cell-cell interaction dynamics in the tumor microenvironment
<p>These are 3D live-cell imaging datasets of gastric tumor organoids in co-culture with primary human Natural Killer (NK) cells. The datasets were analyzed by a new, deep learning-based 3D image analysis software tool, SiQ-3D, which we developed and presented in the paper titled "Deep Learning-based 3D single-cell imaging analysis pipeline for quantifying cell-cell interaction dynamics in the tumor microenvironment". Interested users can download the SiQ-3D software code from GitHub (https://github.com/simonlbd1/SiQ-3D) or Code Ocean (https://codeocean.com/capsule/6676007/tree/v2), analyze the 3D image datasets locally, and cross-check the results with the SiQ-3D quantified results that we provided here.</p>
Patient-Derived Tumor Organoid and Fibroblast Assembloid Models for interrogation of the tumor microenvironment in Esophageal Adenocarcinoma
<p>This repository contains original microscopy data from the Sharpe et al. paper, "Patient-Derived Tumor Organoid and Fibroblast Assembloid Models for interrogation of the tumor microenvironment in Esophageal Adenocarcinoma" in Cell Reports Methods 2024.</p> <p>All whole slide images were obtained using an LM dotSlide slide scanning microscope in Olympus .vsi format and can be opened using the BioFormats library (for example, in QuPath). Wholemount immunofluorescent stains were imaged on a Leica SP8 laser-scanning confocal microscope and are presented as .IMS files, which allows for visualization and further analysis of the 3D data in Imaris (Oxford Instruments).</p> <p>Data are arranged in subfolders based on the figure they came from (Figures 1-4).</p>
Single-cell multi-modal analysis of tumor microenvironment in human non-small cell lung cancer tissues
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Data from: Development of an adrenocortical cancer humanized mouse model to characterize anti-PD1 effects on tumor microenvironment
Context: While the development of immune checkpoint inhibitors has transformed treatment strategies of several human malignancies, research models to study immunotherapy in ACC are lacking. Objective: To explore the effect of anti-PD1 immunotherapy on the alteration of the immune milieu in ACC in a newly generated preclinical model and correlate with the response of the matched patient. Design, Setting and Intervention: To characterize the CU-ACC2-M2B patient-derived xenograft in a humanized mouse model, evaluate the effect of a PD-1 inhibitor therapy and compare to the CU-ACC2 patient with metastatic disease. Results: Characterization of the CU-ACC2-hu-CB-BRGS model confirmed ACC origin and match with the original human tumor. Treatment of the mice with pembrolizumab demonstrated significant tumor growth inhibition (TGI = 60%) compared to controls, which correlated with increased tumor infiltrating lymphocyte activity, with an increase of human CD8+ T cells (p<0.05), HLA-DR+ T cells (p<0.05) as well as Granzyme B+ CD8+ T cells (<0.001). In parallel, treatment of the CU-ACC2 patient, who had progressive disease, demonstrated a partial response with 79%-100% reduction in the size of target lesions, and no new sites of metastasis. Pre-treatment analysis of the patient's metastatic liver lesion demonstrated abundant intra-tumoral CD8+ T cells by immunohistochemistry. Conclusions: Our study reports the first humanized ACC PDX mouse model which may be useful to define mechanisms and biomarkers of response and resistance to immune-based therapies, to ultimately provide more personalized care for patients with ACC.
Roles of m5C RNA modification patterns in biochemical recurrence and tumor microenvironment characterization of prostate cancer
<p>The datasets included in the manuscript 'Roles of m5C RNA modification patterns in biochemical recurrence and tumor microenvironment characterization of prostate cancer'</p>
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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.