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47 results for “Tumour Microenvironment”
Molecular Signatures of Tumour and its Microenvironment for Precise Quantitative Diagnosis of Oral Squamous Cell Carcinoma: An Interna-tional Multi-cohort Diagnostic Validation Study
<p><strong>Supplementary Materials: </strong>The following supporting information can be downloaded at: www.mdpi.com/xxx/s1, <strong>Table ST1</strong> – qMIDS<sup>V2 </sup>Gene panel primer sequences; <strong>Figure S1</strong> – qMIDS<sup>V1</sup> vs qMIDS<sup>V2</sup> 384-well assay format and protocols; <strong>Figure S2.</strong> Individual target gene expression pattern in 1761 samples; <strong>Figure S3.</strong> Various statistical methods used for gene selection analysis on 1761 clinical samples; <strong>Figure S4. </strong>Diagnostic performance comparison between qMIDS<sup>V2</sup> vs qMIDS<sup>V2* </sup>(with 4 less effective genes removed from the panel of 14 target genes of qMIDS<sup>V2</sup>); <strong>Figure S5</strong>. Effect of removing individual genes from the 14-target gene panel qMIDS<sup>V2</sup> (qV2) on diagnostic test performance based on the UK patient cohort data.</p>
Processed CODEX Datasets from - Graph deep learning for the characterization of tumour microenvironments from spatial protein profiles in tissue specimens
<p>This entry provides access to processed CODEX data files of three studies analyzed in the article "Graph deep learning for the characterization of tumour microenvironments from spatial protein profiles in tissue specimens". Details of datasets can be found in the Methods section of the article.</p> <p>For each dataset:</p> <ul> <li>A comma-separated values (CSV) file containing metadata of regions is included</li> <li>A zip file containing multiple CSV files is included: <ul> <li>`{region_id}.cell_data.csv`, a table containing three columns: "CELL_ID", "X", and "Y". This table provides centroid locations for all cells segmented in this region.</li> <li>`{region_id}.expression.csv`, a table containing multiple columns: "CELL_ID", "DAPI", "CD45", etc. This table provides detailed protein biomarker expression quantified and normalized for all cells in this region.</li> <li>`{region_id}.cell_types.csv`, a table containing two columns: "CELL_ID" and "CELL_TYPE". This table provides cell type annotations for all cells in this region.</li> <li>`{region_id}.cell_features.csv`, a table containing two columns: "CELL_ID" and "SIZE". This table provides morphology descriptors (only containing cell size for these studies) for all cells in this region.</li> </ul> </li> </ul> <p>These data files are also available through the Enable Medicine Public Study page: <a href="https://app.enablemedicine.com/portal/atlas-library/studies/92394a9f-6b48-4897-87de-999614952d94?sid=1168">https://app.enablemedicine.com/portal/atlas-library/studies/92394a9f-6b48-4897-87de-999614952d94?sid=1168</a>. Raw multiplexed immunofluorescence images will be accessible through the visualizer app of Enable Medicine Portal.</p> <p>Codes for this study are stored in <a href="https://gitlab.com/enable-medicine-public/space-gm">https://gitlab.com/enable-medicine-public/space-gm</a>. Please direct all further questions and/or issues to the gitlab repository or lead contact (A.E.T.).</p>
Spatial Transcriptomics in Breast Cancer Reveals Tumour Microenvironment-Driven Drug Responses and Clonal Therapeutic Heterogeneity
<p>We acquired 10x Visium spatial transcriptomics (ST) data from 9 patients with invasive adenocarcinomas [1–5] to explore the role of the tumour microenvironment (TME) on intratumor heterogeneity (ITH) and drug response in breast cancer. By leveraging a new version of Beyondcell [6] (<a href="https://github.com/cnio-bu/beyondcell" target="_blank" rel="noopener">cnio-bu/beyondcell</a>), a tool for identifying tumour cell subpopulations with distinct drug response patterns, we predicted sensitivity to over 1,200 drugs while accounting for the spatial context and interaction between the tumour and TME compartments. Moreover, we also used Beyondcell to compute spot-wise functional enrichment scores and identify niche-specific biological functions.</p> <p>Here, you can find:</p> <p>In signatures folder:</p> <ul> <li><strong>SSc breast:</strong> Collection of gene signatures used to predict sensitivity to > 1,200 drugs derived from breast cancer cell lines.</li> <li><strong>Functional signatures:</strong> Collection of gene signatures used to compute enrichment in different biological pathways.</li> </ul> <p>In visium folder:</p> <ul> <li><strong>Visium objects:</strong> Processed ST Seurat objects with deconvoluted spots, SCTransform-normalised counts, and clonal composition predicted with SCEVAN [7]. These objects, together with the signatures, were used to compute the Beyondcell objects.</li> </ul> <p>In single-cell folder:</p> <ul> <li><strong>Single-cell objects:</strong> Raw and filtered merged single-cell RNA-seq (scRNA-seq) Seurat objects with unnormalised counts used as a reference for spot deconvolution.</li> </ul> <p>In beyondcell folder:</p> <ul> <li><strong>Beyondcell </strong><strong>sensitivity </strong><strong>objects</strong> with prediction scores for all drug response signatures in SSc breast.</li> <li><strong>Beyondcell functional objects </strong>with enrichment scores for all functional signatures.</li> </ul>
Engineering Micro Oxygen Factories to Slow Tumour Progression via Hyperoxic Microenvironments
<p>Imaging data of the paper</p>
Transcriptome profiling associated with CARD11 overexpres-sion in Colorectal Cancer implicates a potential role for Tumour Immune Microenvironment and Cancer pathways modulation via NF-κB
<p>tables for CARD11</p>
Transcriptome profiling associated with CARD11 overexpres-sion in Colorectal Cancer implicates a potential role for Tumour Immune Microenvironment and Cancer pathways modulation via NF-κB
<p>Images for CARD11 study in IJMS</p>
Morphological, Genetic and Tumour Microenvironment Characterisation in Uveal Melanoma
ClinicalTrials.gov study NCT05889481. IPD Sharing: NO. Countries: 1. Publications: 14.
Virus-associated Tumour Microenvironment
ClinicalTrials.gov study NCT06471296. IPD Sharing: YES. Countries: 0. Publications: 0.
Combinatorial treatment rescues tumour-microenvironment-mediated attenuation of MALT1 inhibitors in B-cell lymphomas
GEO Series GSE209551. Homo sapiens. 18 samples. Type: Expression profiling by high throughput sequencing.
Single-cell RNA-sequencing of γδ-T cells from peripheral blood and breast tumour microenvironment.
GEO Series GSE141665. Homo sapiens. 4 samples. Type: Expression profiling by high throughput sequencing.
Distinct metabolic programs control the effector fate of γδ T cell subsets and their activities in the tumour microenvironment
GEO Series GSE150585. Mus musculus. 2 samples. Type: Expression profiling by high throughput sequencing.
TERT activates endogenous retroviruses to promote an immunosuppressive tumour microenvironment
GEO Series GSE169715. Homo sapiens; Mus musculus. 23 samples. Type: Expression profiling by high throughput sequencing.
Spatially resolving the tumour microenvironment of head and neck cancer to discover novel predictive biomarkers of immunotherapy response
GEO Series GSE255939. Homo sapiens. 38 samples. Type: Other.
Ionic immune suppression within the tumour microenvironment limits T cell effector function
GEO Series GSE84996. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing.
Mesothelioma location influences the tumour microenvironment and immune checkpoint therapy response in preclinical models
GEO Series GSE310501. Mus musculus. 31 samples. Type: Expression profiling by high throughput sequencing.
CD103+CD56+ ILCs are associated with an immunosuppressed tumour microenvironment
GEO Series GSE276563. Homo sapiens. 3 samples. Type: Expression profiling by high throughput sequencing.
Transcriptomic analysis identifies novel cancer associated fibroblast marker in the breast tumour microenvironment
GEO Series GSE296349. Homo sapiens. 24 samples. Type: Expression profiling by high throughput sequencing.
CD103+CD56+ ILCs are associated with an immunosuppressed tumour microenvironment (bulk RNA-Seq)
GEO Series GSE276966. Homo sapiens. 8 samples. Type: Expression profiling by high throughput sequencing.
LSD1 activation promotes inducible EMT programs and modulates the tumour microenvironment in breast cancer
GEO Series GSE104754. Homo sapiens. 3 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Tumour-intrinsic endomembrane trafficking by ARF6 shapes an immunosuppressive microenvironment that drives melanomagenesis and response to checkpoint blockade therapy [bulk RNA-seq]
GEO Series GSE253092. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing.
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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.