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483
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ShareScore release 0.9.0
Dataset results
483 results for “anti-PD-1”
Single-cell RNA-seq profiles of tumor-bearing mice treated with PAGln with or without anti-PD-1
<p>single-cell RNA sequencing (scRNA-seq) profiles of tumor-bearing mice treated using Phenylacetylglutamine (PAGln) with or without anti-PD-1 were performed to compare the alterations of immune microenvironment affected by PAGln under the condition of anti-PD-1 treatment.</p>
Platinum-Based Chemotherapy With/Without INCMGA00012, an Anti-PD-1 Antibody, in Non-Small Cell Lung Cancer
ClinicalTrials.gov study NCT04205812. IPD Sharing: YES. Countries: 17. Publications: 1.
Safety and Immunotherapeutic Activity of an Anti-PD-1 Antibody (Cemiplimab) in Participants With HIV-1 on Suppressive cART
ClinicalTrials.gov study NCT03787095. IPD Sharing: YES. Countries: 1. Publications: 2.
Imaging mass cytometry analysis of brain tissues with CNS immune-related adverse events during anti-PD-1 cancer immunotherapy
<p><span>Dataset accompanying the manuscript "Anti-PD-1 cancer immunotherapy induces CNS immune-related adverse events by Spleen tyrosine kinase activation in microglia".</span></p> <p><span>The Metadata.xls file includes the metadata, the raw image data is saved as .txt file, the segmented cellular expression data is available as csv files. </span></p>
Single-cell RNA-Seq and TCR-Seq analysis of PD-1+ CD8+ T-cells responding to anti-PD-1 and anti-PD-1/CTLA-4 immunotherapy in melanoma
<p><strong>This dataset details the scRNASeq and TCR-Seq analysis of sorted PD-1+ CD8+ T cells from patients with melanoma treated with checkpoint therapy (anti-PD-1 monotherapy and anti-PD-1 & anti-CTLA-4 combination therapy) at baseline and after the first cycle of therapy. A major publication using this dataset is accessible here: (reference) </strong></p> <p> </p> <p><strong>*experimental design</strong></p> <p> Single-cell RNA sequencing was performed using 10x Genomics with feature barcoding technology to multiplex cell samples from different patients undergoing mono or dual therapy so that they can be loaded on one well to reduce costs and minimize technical variability. Hashtag oligomers (oligos) were obtained as purified and already oligo-conjugated in TotalSeq-C format from BioLegend. Cells were thawed, counted and 20 million cells per patient and time point were used for staining. Cells were stained with barcoded antibodies together with a staining solution containing antibodies against CD3, CD4, CD8, PD-1/IgG4 and fixable viability dye (eBioscience) prior to FACS sorting. Barcoded antibody concentrations used were 0.5 µg per million cells, as recommended by the manufacturer (BioLegend) for flow cytometry applications. After staining, cells were washed twice in PBS containing 2% BSA and 0.01% Tween 20, followed by centrifugation (300 xg 5 min at 4 °C) and supernatant exchange. After the final wash, cells were resuspended in PBS and filtered through 40 µm cell strainers and proceeded for sorting. Sorted cells were counted and approximately 75,000 cells were processed through 10x Genomics single-cell V(D)J workflow according to the manufacturer’s instructions. Gene expression, hashing and TCR libraries were pooled to desired quantities to obtain the sequencing depths of 15,000 reads per cell for gene expression libraries and 5,000 reads per cell for hashing and TCR libraries. Libraries were sequenced on a NovaSeq 6000 flow cell in a 2X100 paired-end format.</p> <p> </p> <p><strong>*extract protocol</strong></p> <p> PBMCs were thawed, counted and 20 million cells per patient and time point were used for staining. Cells were stained with barcoded antibodies together with a staining solution containing antibodies against CD3, CD4, CD8, PD-1/IgG4 and fixable viability dye (eBioscience) prior to FACS sorting. Barcoded antibody concentrations used were 0.5 µg per million cells, as recommended by the manufacturer (BioLegend) for flow cytometry applications. After staining, cells were washed twice in PBS containing 2% BSA and 0.01% Tween 20, followed by centrifugation (300 xg 5 min at 4 °C) and supernatant exchange. After the final wash, cells were resuspended in PBS and filtered through 40 µm cell strainers and proceeded for sorting. Sorted cells were counted and approximately 75,000 cells were processed through 10x Genomics single-cell V(D)J workflow according to the manufacturer’s instructions.</p> <p> </p> <p><strong>*library construction protocol</strong></p> <p> Sorted cells were counted and approximately 75,000 cells were processed through 10x Genomics single-cell V(D)J workflow according to the manufacturer’s instructions. Gene expression, hashing and TCR libraries were pooled to desired quantities to obtain the sequencing depths of 15,000 reads per cell for gene expression libraries and 5,000 reads per cell for hashing and TCR libraries. Libraries were sequenced on a NovaSeq 6000 flow cell in a 2X100 paired-end format.</p> <p> </p> <p><strong>*library strategy</strong></p> <p> scRNA-seq and scTCR-seq</p> <p> </p> <p><strong>*data processing step</strong></p> <p> Pre-processing of sequencing results to generate count matrices (gene expression and HTO barcode counts) was performed using the 10x genomics Cell Ranger pipeline.</p> <p> Further processing was done with Seurat (cell and gene filtering, hashtag identification, clustering, differential gene expression analysis based on gene expression).</p> <p> </p> <p> <strong>*genome build/assembly</strong></p> <p> Alignment was performed using prebuilt Cell Ranger human reference GRCh38.</p> <p> </p> <p><strong>*processed data files format and content</strong></p> <p> RNA counts and HTO counts are in sparse matrix format and TCR clonotypes are in csv format.</p> <p>Datasets were merged and analyzed by Seurat and the analyzed objects are in rds format.</p> <p> </p> <table> <tbody> <tr> <td> <p><strong>file name</strong></p> </td> <td> <p><strong>file checksum</strong></p> </td> </tr> <tr> <td> <p>PD1CD8_160421_filtered_feature_bc_matrix.zip</p> </td> <td> <p>da2e006d2b39485fd8cf8701742c6d77</p> </td> </tr> <tr> <td> <p>PD1CD8_190421_filtered_feature_bc_matrix.zip</p> </td> <td> <p>e125fc5031899bba71e1171888d78205</p> </td> </tr> <tr> <td> <p>PD1CD8_160421_filtered_contig_annotations.csv</p> </td> <td> <p>927241805d507204fbe9ef7045d0ccf4</p> </td> </tr> <tr> <td> <p>PD1CD8_190421_filtered_contig_annotations.csv</p> </td> <td> <p>8ca544d27f06e66592b567d3ab86551e</p> </td> </tr> </tbody> </table> <p> </p> <table> <tbody> <tr> <td> <p><strong>*processed data file </strong></p> </td> <td> <p><strong>antibodies/tags</strong></p> </td> </tr> <tr> <td> <p>PD1CD8_160421_filtered_feature_bc_matrix.zip</p> </td> <td> <p>none</p> </td> </tr> <tr> <td> <p>PD1CD8_160421_filtered_feature_bc_matrix.zip</p> </td> <td> <p>TotalSeq™-C0251 anti-human Hashtag 1 Antibody - (HASH_1) - M1_base_monotherapy<br>TotalSeq™-C0252 anti-human Hashtag 2 Antibody - (HASH_2) - M1_post_monotherapy<br>TotalSeq™-C0253 anti-human Hashtag 3 Antibody - (HASH_3) - C1_base_combined_therapy<br>TotalSeq™-C0254 anti-human Hashtag 4 Antibody - (HASH_4) - C1_post_combined_therapy<br>TotalSeq™-C0255 anti-human Hashtag 5 Antibody - (HASH_5) - C2_base_combined_therapy<br>TotalSeq™-C0256 anti-human Hashtag 6 Antibody - (HASH_6) - C2_post_combined_therapy</p> </td> </tr> <tr> <td> <p>PD1CD8_160421_filtered_contig_annotations.csv</p> </td> <td> <p>none</p> </td> </tr> <tr> <td> <p>PD1CD8_190421_filtered_feature_bc_matrix.zip</p> </td> <td> <p>none</p> </td> </tr> <tr> <td> <p>PD1CD8_190421_filtered_feature_bc_matrix.zip</p> </td> <td> <p>TotalSeq™-C0251 anti-human Hashtag 1 Antibody - (HASH_1) - M2_base_monotherapy<br>TotalSeq™-C0252 anti-human Hashtag 2 Antibody - (HASH_2) - M2_post_monotherapy<br>TotalSeq™-C0253 anti-human Hashtag 3 Antibody - (HASH_3) - M3_base_monotherapy<br>TotalSeq™-C0254 anti-human Hashtag 4 Antibody - (HASH_4) - M3_post_monotherapy<br>TotalSeq™-C0255 anti-human Hashtag 5 Antibody - (HASH_5) - C3_base_combined_therapy<br>TotalSeq™-C0256 anti-human Hashtag 6 Antibody - (HASH_6) - C3_post_combined_therapy</p> </td> </tr> <tr> <td> <p>PD1CD8_190421_filtered_contig_annotations.csv</p> </td> <td> <p>none</p> </td> </tr> </tbody> </table> <p> </p>
1454GCC: Anti-PD-1 (MK-3475) and IMiD (Pomalidomide) Combination Immunotherapy in Relapsed/Refractory Multiple Myeloma
ClinicalTrials.gov study NCT02289222. IPD Sharing: Not stated. Countries: 1. Publications: 1.
A Study of Tilsotolimod in Combo With Ipilimumab vs Ipilimumab Alone in Subjects With Anti-PD-1 Refractory Melanoma
ClinicalTrials.gov study NCT03445533. IPD Sharing: NO. Countries: 11. Publications: 1.
AdvanTIG-202: Anti-PD-1 Monoclonal Antibody Tislelizumab (BGB-A317) Combined With or Without Anti-TIGIT Monoclonal Antibody Ociperlimab (BGB-A1217) in Participants With Previously Treated Recurrent or
ClinicalTrials.gov study NCT04693234. IPD Sharing: YES. Countries: 8. Publications: 1.
An Investigational Immuno-therapy Study to Assess the Safety, Tolerability and Effectiveness of Anti-LAG-3 With and Without Anti-PD-1 in the Treatment of Solid Tumors
ClinicalTrials.gov study NCT01968109. IPD Sharing: Not stated. Countries: 15. Publications: 4.
Platinum-Based Chemotherapy Plus Ramucirumab in Patients With Advanced NSCLC Who Have Progressed on First Line Anti-PD-1 Immunotherapy
ClinicalTrials.gov study NCT03904108. IPD Sharing: NO. Countries: 1. Publications: 24.
Tyrosine Kinase Inhibitor (TKI) + Anti-PD-1 Antibody in TKI-responded Microsatellite Stability/Proficient Mismatch Repair (MSS/pMMR) Metastatic Colorectal Adenocarcinoma.
ClinicalTrials.gov study NCT04483219. IPD Sharing: YES. Countries: 1. Publications: 1.
Preoperative Anti-PD-1 Antibody Combined With Chemoradiotherapy for Locally Advanced Squamous Cell Carcinoma of Esophagus
ClinicalTrials.gov study NCT03792347. IPD Sharing: NO. Countries: 1. Publications: 1.
Phase 2 Multi-center Study of Anti-PD-1 During Lymphopenic State After HDT/ASCT for Multiple Myeloma
ClinicalTrials.gov study NCT02331368. IPD Sharing: Not stated. Countries: 1. Publications: 1.
A Trial of SHR-1210 (an Anti-PD-1 Inhibitor) in Combination With Apatinib in Patients With Advanced HCC(RESCUE)
ClinicalTrials.gov study NCT03463876. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Study Investigating Safety, Tolerability, Pharmacokinetics (PK) and Antitumor Activities of Anti-PD-1 (Programmed Death-1) Monoclonal Antibody
ClinicalTrials.gov study NCT04068519. IPD Sharing: YES. Countries: 1. Publications: 2.
Anti-PD-1 Monoclonal Antibody in Advanced, Trastuzumab-resistant, HER2-positive Breast Cancer
ClinicalTrials.gov study NCT02129556. IPD Sharing: Not stated. Countries: 5. Publications: 5.
Safety, Tolerability and Pharmacokinetics of an Anti-PD-1 Monoclonal Antibody in Subjects With Advanced Malignancies
ClinicalTrials.gov study NCT03474640. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Combinations of Cemiplimab (Anti-PD-1 Antibody) and Platinum-based Doublet Chemotherapy in Patients With Lung Cancer
ClinicalTrials.gov study NCT03409614. IPD Sharing: Not stated. Countries: 18. Publications: 3.
Talimogene Laherparepvec With Pembrolizumab in Melanoma Following Progression on Prior Anti-PD-1 Based Therapy (MASTERKEY-115) (Mk-3475-A07/KEYNOTE-A07).
ClinicalTrials.gov study NCT04068181. IPD Sharing: YES. Countries: 11. Publications: 1.
Lymphodepletion and Anti-PD-1 Blockade to Reduce Relapse in AML Patient Not Eligible for Transplant
ClinicalTrials.gov study NCT02771197. IPD Sharing: NO. Countries: 1. Publications: 24.
ScienceDex guides
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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)
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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.