Find research datasets worth reusing

opencc-by-4.0Mar 2024View details →

Enhancing comparative T-cell receptor repertoire analysis in small biological samples through pooling homologous cell samples from multiple mice

All data files used to generate the figures in the paper are shared in this project. Scripts are available on <a href="https://github.com/i3-unit/CRM_24" target="_blank" rel="noopener">GitHub</a>.

dryad36/100

Data from: Gastrointestinal gd T cells reveal upregulated T-cell transcripts and signaling pathways during peanut oral immunotherapy

Oral immunotherapy (OIT) has been successful in desensitizing patients to offending food allergens, although identification of tissue-resident T cell subsets and cognate pathways leading to desensitization has been challenging. The T cells are a major T-cell subset of mucosal intraepithelial lymphocytes (IELs) and play a significant role in tissue homeostasis and repair. Studies in mouse models suggested a regulatory role of gd T cells in food allergy (FA). Also, peripheral gd T cells from patients analyzed over 24 weeks of peanut OIT were shown to undergo dynamic changes in expression profiles, implicating pathways involved in immune homeostasis. To our knowledge, the role of gd T cells in the intestinal mucosa of FA patients during immunotherapy has not been examined. To this end, we investigated whether gd T cells in the gastrointestinal (GI) tract are modulated during peanut OIT. We hypothesized that GI-resident gd T cells in FA patients would increase during the course of peanut OIT and reveal transcripts and pathways relevant to the mechanisms of peanut desensitization.

opencc-zeroMar 2024View details →

opencc-by-4.0Apr 2022View details →

Metabolic data: Inhibition of mitochondrial complex I reverses NOTCH1-driven metabolic reprogramming in T-cell acute lymphoblastic leukemia

T-cell acute lymphoblastic leukemia (T-ALL) is commonly driven by activating mutations in NOTCH1 that facilitate glutamine oxidation. Here we identify oxidative phosphorylation (OxPhos) as a critical pathway for leukemia cell survival and demonstrate a direct relationship between NOTCH1, elevated OxPhos gene expression, and acquired chemoresistance in pre-leukemic and leukemic models. Disrupting OxPhos with IACS-010759, an inhibitor of mitochondrial complex I, causes potent growth inhibition through induction of metabolic shut-down and redox imbalance in NOTCH1-mutated and less so in NOTCH1-wt T-ALL cells. Mechanistically, inhibition of OxPhos induces metabolic reprogramming into glutaminolysis. We show that pharmacological blockade of OxPhos combined with inducible knock-down of glutaminase, the key glutamine enzyme, confers synthetic lethality in mice harboring NOTCH1-mutated T-ALL. We leverage this synthetic lethal interaction to demonstrate that IACS-010759 in combination with chemotherapy containing L-asparaginase, an enzyme that uncovers the glutamine dependency of leukemic cells, causes reduced glutaminolysis and profound tumor reduction in pre-clinical models of human T-ALL. In summary, this metabolic dependency of T-ALL on OxPhos provides a rational therapeutic target.

opencc-by-4.0Feb 2023View details →

T-cell receptor Vβ (TCRVB) deep sequencing on human T cells isolated from humanized mice engrafted with human PBMC and treated or not with PTCy post-transplantation

Nucleotide sequence data of  TCRVB sequencing performed on T cells isolated from the pre-transplantation hPBMC (donor T cells) or from mice organs at day 21 post-transplantation (injected or not with PTCy at day 3) to determine the impact of PTCy on the T cell V beta (TCRVB) receptor repertoire diversity. NSG mice were engrafted with human PBMC to develop xeno-GVHD and treated or not with 100 mg/kg PTCy. Spleens and lungs from 10 NSG mice per group were pooled and stained to sorted  human CD4+ and CD8+ . DNA of human CD4+ and CD8+ T cells sorted from each organ and  from the PBMC donor was extracted. One hundred fifty µg from each sample were used for T-cell receptor Vβ (TCRVB) deep sequencing performed by Adaptive Biotechnologies.

opencc-by-4.0May 2024View details →

MR1-restricted T-cell clonotypes are associated with 'resistance' to Mycobacterium Tuberculosis infection - TRA/D immunoSEQ

Summary <ul> <li>Number of files: 39</li> <li>Data format: tsv</li> <li>Data type: TCRA/D immunoSEQ (Adaptive Biotechnologies)</li> <li>immunoSEQ version: v2</li> <li>Sample type: peripheral blood mononuclear cells (PBMCs)</li> <li>Genomic DNA extraction protocol: QIAGEN DNeasy Blood and Tissue kit</li> </ul> Sample description Peripheral blood samples were collected from participants enrolled in a longitudinal cohort study based in Uganda. Donors were classified as either "resistors" (RSTRs, n = 19, defined as concordantly negative for tuberculin skin test and IFNg release assay despite high environmental exposure) or latently infected with M. Tuberculosis (LTBI, n = 20, concordantly as longitudinally positive for tuberculin skin test and IFNg release assay). Genomic DNA (gDNA) was extracted from cryopreserved PBMCs without stimulation or enrichment of T-cells using the Quiagen DNeasy Blood and Tissue kit. Protocol can be found at: https://www.qiagen.com/us/products/discovery-and-translational-research/dna-rna-purification/dna-purification/genomic-dna/dneasy-blood-and-tissue-kit

opencc-by-4.0Jul 2024View details →

HER2/neu-specific T-cells

Single-cell RNA-seq data of HER2/neu-specific T-cells genereated with the BD Rhapsody™ system. Donor information: 3 healthy subjects, 2 male (SampleTag04, SampleTag05), 1 female (SampleTag06). Cell preparation: HER2/neu-specific T-cells were obtained via a Tetramer-based sorting of the naturally-occuring anti-CD3 and anti-CD28-activated T-cells co-cultured with the Dendritic cells that were maturated by a KIFGSLAFL peptide.  Single-cell analysis system: BD Rhapsody™ Library strategy: 5' mRNA sequencing Library preparation protocol: BD Rhapsody™ TCR/BCR Full Length, Targeted mRNA, and Sample Tag Library Preparation mRNA panel: BD Rhapsody™ Immune Response Panel HS BD Pipeline version: 1.11.1L

opencc-by-4.0Sep 2019View details →

NGS data produced in 'Rapid selection and identification of functional CD8+ T-cell epitopes from large peptide-coding libraries'; Nature Communications (2019)

Sharma, G et al. Rapid selection and identification of functional CD8+ T-cell epitopes from large peptide-coding libraries. Nature Communications. Accepted (August 2019) Abstract: Cytotoxic CD8+ T-cells recognize and eliminate infected or malignant cells that present, at their cell surfaces, short peptide epitopes derived from intracellularly processed antigens. However, broadly searching for specific major histocompatibility complex (MHC)-bound peptide epitopes that are naturally processed and capable of eliciting a functional T-cell response has been challenging. Here, we report a method for deep and unbiased T-cell epitope profiling, which is done by using in vitro co-culture of CD8+ T-cells and target cells transduced with high-complexity epitope-encoding minigene libraries. Target cells that are subject to cytotoxic attack from T-cells in co-culture are isolated, before they are lost to apoptosis, by fluorescence-activated cell sorting and characterized by sequencing the minigenes encoded within. In the present study, we validate this highly parallelized method using known murine T-cell receptor/peptide-MHC pairs and diverse minigene-encoded epitope libraries to identify naturally processed and MHC-presented peptide epitopes unambiguously and with high sensitivity.

opencc-by-4.0Oct 2024View details →

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

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)     *experimental design  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.   *extract protocol  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.   *library construction protocol  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.   *library strategy  scRNA-seq and scTCR-seq   *data processing step  Pre-processing of sequencing results to generate count matrices (gene expression and HTO barcode counts) was performed using the 10x genomics Cell Ranger pipeline.  Further processing was done with Seurat (cell and gene filtering, hashtag identification, clustering, differential gene expression analysis based on gene expression).    *genome build/assembly  Alignment was performed using prebuilt Cell Ranger human reference GRCh38.   *processed data files format and content  RNA counts and HTO counts are in sparse matrix format and TCR clonotypes are in csv format. Datasets were merged and analyzed by Seurat and the analyzed objects are in rds format.   <table> <tbody> <tr> <td> file name </td> <td> file checksum </td> </tr> <tr> <td> PD1CD8_160421_filtered_feature_bc_matrix.zip </td> <td> da2e006d2b39485fd8cf8701742c6d77 </td> </tr> <tr> <td> PD1CD8_190421_filtered_feature_bc_matrix.zip </td> <td> e125fc5031899bba71e1171888d78205 </td> </tr> <tr> <td> PD1CD8_160421_filtered_contig_annotations.csv </td> <td> 927241805d507204fbe9ef7045d0ccf4 </td> </tr> <tr> <td> PD1CD8_190421_filtered_contig_annotations.csv </td> <td> 8ca544d27f06e66592b567d3ab86551e </td> </tr> </tbody> </table>    <table> <tbody> <tr> <td> *processed data file </td> <td> antibodies/tags </td> </tr> <tr> <td> PD1CD8_160421_filtered_feature_bc_matrix.zip </td> <td> none </td> </tr> <tr> <td> PD1CD8_160421_filtered_feature_bc_matrix.zip </td> <td> TotalSeq™-C0251 anti-human Hashtag 1 Antibody - (HASH_1) - M1_base_monotherapy TotalSeq™-C0252 anti-human Hashtag 2 Antibody - (HASH_2) - M1_post_monotherapy TotalSeq™-C0253 anti-human Hashtag 3 Antibody - (HASH_3) - C1_base_combined_therapy TotalSeq™-C0254 anti-human Hashtag 4 Antibody - (HASH_4) - C1_post_combined_therapy TotalSeq™-C0255 anti-human Hashtag 5 Antibody - (HASH_5) - C2_base_combined_therapy TotalSeq™-C0256 anti-human Hashtag 6 Antibody - (HASH_6) - C2_post_combined_therapy </td> </tr> <tr> <td> PD1CD8_160421_filtered_contig_annotations.csv </td> <td> none </td> </tr> <tr> <td> PD1CD8_190421_filtered_feature_bc_matrix.zip </td> <td> none </td> </tr> <tr> <td> PD1CD8_190421_filtered_feature_bc_matrix.zip </td> <td> TotalSeq™-C0251 anti-human Hashtag 1 Antibody - (HASH_1) - M2_base_monotherapy TotalSeq™-C0252 anti-human Hashtag 2 Antibody - (HASH_2) - M2_post_monotherapy TotalSeq™-C0253 anti-human Hashtag 3 Antibody - (HASH_3) - M3_base_monotherapy TotalSeq™-C0254 anti-human Hashtag 4 Antibody - (HASH_4) - M3_post_monotherapy TotalSeq™-C0255 anti-human Hashtag 5 Antibody - (HASH_5) - C3_base_combined_therapy TotalSeq™-C0256 anti-human Hashtag 6 Antibody - (HASH_6) - C3_post_combined_therapy </td> </tr> <tr> <td> PD1CD8_190421_filtered_contig_annotations.csv </td> <td> none </td> </tr> </tbody> </table>

opencc-by-4.0Mar 2023View details →

T-cell activity - Imaging flow cytometry experiment data

Raw image data from the imaging flow cytometry experiments for correlating receptor localization and cytokine production.

opencc-by-4.0Oct 2023View details →

Functional anaysis of miR-143-3p/KSR2 interaction and oncogenic function in JURKAT and ALL-SIL T-cell acute lymphoblastic leukemia cell lines

1. FCS files from GFP competition assay performed in ALL-SIL and JURKAT cell lines upon transduction with hsa-mir-143 expression vector (pCDH miR-143-3p) or empty vector (pCDH EV) as control.2. Uncropped chemiluminescent immunoblot in JURKAT and ALL-SIL cell lines transduced with hsa-mir-143 expression vector (pCDH miR-143-3p) or empty vector (pCDH EV) as control. Upper band is KSR2 protein (~100 kDa) and lower band is loading control GAPDH protein (~37 kDa). Order of samples on the membrane: JURKAT pCDH miR-143-3p replicate 1, pCDH EV replicate 1, pCDH EV replicate 2, pCDH miR-143-3p replicate 2, pCDH EV replicate 3, pCDH miR-143-3p replicate 3, ALL-SIL pCDH miR-143-3p replicate 1, pCDH miR-143-3p replicate 2, pCDH EV replicate 1, pCDH miR-143-3p replicate 3, pCDH EV replicate 2, pCDH EV replicate 3.3. RT-qPCR amplification data for relative quantification of KSR2 expression in reference to ACTB and GAPDH in JURKAT and ALL-SIL cell lines expressing deadCas9-KRAB system for transcriptional repression, upon transduction with sgRNA targeting KSR2 transcription start site vector (KSR2 sgRNA1 and KSR2 sgRNA2) or non-targeting sgRNA vector (NT) as control.4. FCS files from GFP competition assay performed in ALL-SIL and JURKAT cell lines expressing deadCas9-KRAB system for transcriptional repression, upon transduction with sgRNA targeting KSR2 transcription start site vector (KSR2 sgRNA1 and KSR2 sgRNA2) or non-targeting sgRNA vector (NT) as control.

restrictedIPD-UNDECIDEDFeb 2026View details →

Dose-Escalation Trial of Carfilzomib With and Without Romidepsin in Cutaneous T-Cell Lymphoma

ClinicalTrials.gov study NCT01738594. IPD Sharing: Not stated. Countries: 1. Publications: 1.

Phase I/II Study of Autologous T Cells to Express T-Cell Receptors (TCRs) in Subjects With Solid Tumors

ClinicalTrials.gov study NCT05194735. IPD Sharing: NO. Countries: 1. Publications: 1.

Genetically Engineered Cells (MAGE-A1-specific T Cell Receptor-transduced Autologous T-cells) and Atezolizumab for the Treatment of Metastatic Triple Negative Breast Cancer, Urothelial Cancer, or Non-

ClinicalTrials.gov study NCT04639245. IPD Sharing: NO. Countries: 1. Publications: 1.

Safety and Tolerability of a Modified Vaccinia Ankara (MVA)-Based Vaccine Modified to Express Brachyury and T-cell Costimulatory Molecules (MVA-Brachyury-TRICOM)

ClinicalTrials.gov study NCT02179515. IPD Sharing: NO. Countries: 1. Publications: 4.

controlledIPD-YESFeb 2026View details →

Ruxolitinib for Adult T-Cell Leukemia

ClinicalTrials.gov study NCT01712659. IPD Sharing: YES. Countries: 1. Publications: 4.

T-cell Receptor α/β Depleted Donor Lymphocyte Infusion

ClinicalTrials.gov study NCT05350163. IPD Sharing: NO. Countries: 1. Publications: 31.

restrictedIPD-UNDECIDEDFeb 2026View details →

Busulfan, Melphalan, Fludarabine and T-Cell Depleted Allogeneic Hematopoietic Stem Cell Transplantation Followed by Post Transplantation Donor Lymphocyte Infusions

ClinicalTrials.gov study NCT01131169. IPD Sharing: Not stated. Countries: 1. Publications: 1.

Efficacy and Safety of Oral HBI-8000 in Patients With Relapsed or Refractory Peripheral T-cell Lymphoma (PTCL)

ClinicalTrials.gov study NCT02953652. IPD Sharing: NO. Countries: 2. Publications: 1.

CC486-CHOP in Patients With Previously Untreated Peripheral T-cell Lymphoma

ClinicalTrials.gov study NCT03542266. IPD Sharing: NO. Countries: 1. Publications: 2.