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• 10x Genomics Single Cell Gene Expression for SA1035X7XB03502

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA1035 passage 7

  Dataset EGAD00001009151

• 10x Genomics Single Cell Gene Expression for SA535X4XB02498

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 4

  Dataset EGAD00001009152

• 10x Genomics Single Cell Gene Expression for SA1035X5XB03021

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA1035 passage 5

  Dataset EGAD00001009153

• 10x Genomics Single Cell Gene Expression for SA1035X6XB03216

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA1035 passage 6

  Dataset EGAD00001009154

• 10x Genomics Single Cell Gene Expression for SA535X5XB02891

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 5

  Dataset EGAD00001009155

• 10x Genomics Single Cell Gene Expression for SA535X5XB02895

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 5

  Dataset EGAD00001009156

• 10x Genomics Single Cell Gene Expression for SA535X9XB03617

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 9

  Dataset EGAD00001009157

• 10x Genomics Single Cell Gene Expression for TOV2295(R)

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma cell line TOV2295(R)

  Dataset EGAD00001009158

• 10x Genomics Single Cell Gene Expression for SA604X9XB02425

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA604 passage 9

  Dataset EGAD00001009159

• 10x Genomics Single Cell Gene Expression for SA610X3XB03802

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA610 passage 3

  Dataset EGAD00001009160

• RNA-sequencing of ex vivo exhausted human antigen-specific T cells

  Tumor-specific T cells are frequently exhausted by chronic antigenic stimulation. To explore new pathways for reinvigoration of anti-tumor immune functions, we developed a human ex vivo exhaustion model by repetitive antigenic stimulation of primary CD8 T cells. This results in T cells that resemble patient-derived T cells in tumors on a phenotypic and transcriptional level. Four human healhy donor CD8+ T cells were isolated, transduced with an NY-ESO-1 TCR lentivirus construct, stimulated in four different conditions (Trested, Ttumor, Tex, Teff) with T2 tumor cells and specific peptides over 12 days. Cells were then sorted for TCR Vbeta 13.1+ (NY-ESO-1 TCR) CD8+ CD3+ CD56- CD4- DAPI- cells. RNA-seq TruSeq libraries were generated from polyA-enriched mRNA isolated from the samples, and sequenced in paired-end mode (2x51bp) on 2 lanes of an Illumina NovaSeq 6000 flow-cell. FASTQ sequence files were generated with the Illumina RTA version 3.4.4 and Base-calling Version bcl2fastq-2.20.0.422.

  Dataset EGAD00001009754

• Oesophageal adenocarcinoma RNAseq from LUD2015-005 study (NCT02735239, EudraCT 2015-005298-19)

  This dataset contains bulk transcriptomes from the inoperable cohorts of the LUD2015-005 study (NCT02735239, EudraCT 2015-005298-19). Transcriptomes were prepared from pre-treatment oesophageal tumour biopsies using a ribodepletion approach in order to assess both previously reported (e.g. PD-L1 expression) and novel predictive expression-based biomarkers for immunochemotherapy treatment in this setting. On-treatment and post-treatment biopsies were generated as well to characterize response to therapy, and samples were also prepared from paired normal GI tissues for a subset of patients. scRNA-seq based deconvolution was also applied to bulk transcriptomes in this study to estimate the cell composition of tumour biopsies and assess the link between the presence of specific cell types with immunochemotherapy outcomes.

  Dataset EGAD00001009399

• The scRNA dataset for TIGIT in MCL with CART

  We collected longitudinal samples from 15 patients with MCL at various clinical time points before and after CAT-T therapy brexucabtagene autoleucel (BA) infusion. The patients were grouped into three categories based on their clinical responses after BA treatment: 1) responsive (n = 9), 2) relapsed (n = 5), and 3) refractory (n = 1). All patients in category #1 and #2 had initially attained a complete response (CR) after BA therapy. The responsive group maintained CR with no relapse at the time of last follow up, while the relapsed group achieved initial CR but eventually relapsed. The 10x Chromium™ Single-Cell 5′ Reagent Kit v2 (PN-1000190, 10x GENOMICS) and Chromium Single-Cell Human TCR amplification Kit (PN-1000252, 10x GENOMICS) were used to perform single-cell separation, cDNA amplification, and library construction for gene expression and TCR repertoire following the manufacturer’s guidelines. Thirty-nine samples passed quality control and underwent single-cell transcriptome profiling with simultaneous single-cell T-cell receptor (TCR) repertoire analysis.

  Dataset EGAD00001010180

• Heart Failure Network: Functional Impact of GLP-1 for Heart Failure Treatment (HFN FIGHT-BioLINCC)

  Objectives To test whether therapy with a GLP-1 agonist improves clinical stability following hospitalization for acute heart failure. Background Heart failure was the leading cause of hospitalization in the United States with more than 4 million admissions per year from 2003–2009. Abnormal cardiac metabolism contributes to the pathophysiology of advanced heart failure with reduced left ventricular ejection fraction (LVEF). As heart failure progresses, these abnormalities become more pronounced and are observed in both patients with and without type 2 diabetes. At this time of this study, there was no heart failure therapy that targeted these metabolic abnormalities; however, in earlier clinical studies, glucagon-like peptide 1 (GLP-1) agonists showed cardioprotective effects in patients with advanced heart failure, irrespective of type 2 diabetes status. Glucagon-like peptide 1 is an endogenous incretin hormone that improves insulin sensitivity with minimal risk of hypoglycemia. This study was created to determine if use of GLP-1 agonists improved clinical stability in recently hospitalized patients with acute heart failure and reduced LVEF. Participants There were 300 participants. Design Participants were identified by hospital admission records and were enrolled during either the last 24 hours of his or her hospitalization for heart failure or the 2-week interval after the hospitalization. Baseline evaluations were conducted, which included echocardiographic measures, the 6-minute walk test, the Kansas City Cardiomyopathy Questionnaire (KCCQ), and blood tests. After the baseline evaluation, patients were randomized in a 1:1 ratio to receive either the GLP-1 agonist liraglutide or placebo as a daily subcutaneous injection. The protocol involved titration of study drug dosage as tolerated every 14 days from 0.6 mg/d to 1.2 mg/d to 1.8 mg/d during the first 30 days of the trial (as tolerated). Follow-up testing was performed at 30-, 90-, and 180-day study visits. The primary end point was a global rank score in which all participants, regardless of treatment assignment, were ranked across 3 hierarchical tiers: time to death, time to rehospitalization for heart failure, and time-averaged proportional change in N-terminal pro-B-type natriuretic peptide (NT-proBNP) level from baseline to 180 days. Conclusions The GLP-1 agonist liraglutide did not improve post-hospitalization clinical stability in patients with advanced heart failure and reduced LVEF. There was no significant between-group difference in the global rank scores and furthermore, there were no significant differences detected in any of the secondary endpoints.

  Study phs003542

• McQuillin_Global_London_SCZ_Bipolar_WES

  "McQuillin_Global_London_SCZ_Bipolar_WES. This research project was a collaboration between University College London, UK and the Stanley Center at the Broad Institute. In this project we sequenced and analyzed the whole exomes of 1,623 Schizophrenia and Bipolar case/control samples from collaborators in UK. Genomic DNA from each sample was sequenced to a mean depth of 20x. For EGA Study ID: 1128"

  Dac EGAC50000000311

• Flexible and rapid validation of structural variants using adaptive sampling

  This is the DAC that oversees the application and approval process for access to the Oxford Nanopore fastq files associated with the study, "Flexible and rapid validation of structural variants using adaptive sampling". The DAC members include Dr. Stephen W. Scherer (swscherer@sickkids.ca) and Dr. Lars Feuk (lars.feuk@igp.uu.se).

  Dac EGAC50000000748

• SNP array data for 140 individuals from 5 populations in Pakistan

  We have genotyped 140 individuals from 5 populations in Pakistan, using the OmniExpressExome-8 array, which includes approximately one million autosomal SNP markers.

  Study EGAS00001002965

• Sequencing data for CLL patients

  Single-cell RNA-sequencing and other genome-wide approaches were applied to a cohort of CLL patients receiving Venetoclax treatment to study mechanisms of resistance.

  Study EGAS00001005815

• Dataset of Recurrent resistance mutations to lirafugratinib delineate treatment sequences for FGFR2-driven tumors

  This dataset is made of 23 pairs of RNAseq and 36 pairs of Exome-seq, both sequenced from Illumina Novaseq. This includes 47 samples, composed of 25 tumors, 13 healthy and 9 xenograft

  Dataset EGAD50000001981

• cfDNA sWGS BAM — NSCLC stage I–III

  Plasma cfDNA sWGS for NSCLC patients (stage I–III), blood drawn pre-operatively, CHU Montpellier/LUNGDOC study. Libraries: DSP as recorded. Sequencing provider IntegraGen (2022–2024). Alignment to GRCh38 (hg38 canonical), BWA-MEM; BAMs sorted/indexed; only primary mapped reads retained (analysis pages list -F/MAPQ). Controlled access.

  Dataset EGAD50000001878

• 10X snMultiome (ATAC+GEX) sequencing of 5 human reactive tonsil samples

  10X snMultiome (ATAC+GEX) sequencing of 5 human reactive tonsil samples for the study of Non-canonical NF-κB signaling skews B cells away from germinal center to low-affinity effector fate.

  Dataset EGAD50000002366

• WGS from 9 MPNSTs from 2 individuals, including relapses and metastasis. Data from Ortega-Bertran et. al.

  WGS from 2 individuals with MPNSTs. Multiple MPNSTs (independent tumor, relapses and metastasis) from each individual. Data from "Personalized Medicine Strategy for MPNSTs: Using Precision Oncology on PDOX Models to Inform Tumor Boards" by Ortega-Bertran et.al.

  Dataset EGAD50000002171

• RNA-Seq dataset for malignant pleural and peritoneal mesothelioma

  This dataset contains RNA sequencing data of pleural and peritoneal mesothelioma. The number of samples is 18. Sequencing was performed on Illumina NovaSeq 6000 and Illumina NovaSeqXPlus. The sequencing was always paired.

  Dataset EGAD50000001342

• circulating cell-free RNAs, CF-miRNAs, Sequencing with Qiaseq and NextSeq 550

  This dataset includes small RNA sequencing data from circulating cell-free RNAs (CF-miRNAs). miRNA libraries were prepared using the Qiaseq miRNA Library Kit with adaptations for low RNA input and sequenced on the Illumina NextSeq 550 platform

  Dataset EGAD50000001503

• HIV-phyloTSI: BEEHIVE

  This dataset includes sample numbers TSI_0203 to TSI_0315 for the BEEHIVE cohort of the study. Samples were sequenced using the Illumina NovaSeq system and the veSEQ-HIV method (see Bonsall, Golubchik et al 2020, DOI: 10.1128/JCM.00382-20). Each sample has a BAM file, and its associated reference file.

  Dataset EGAD50000001310