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• ERDERA WES reanalysis - DPF1 Batch 2

  This dataset comprises processed genomic data from 733 samples, corresponding to 733 whole-exome sequencing experiments. Data files include CRAM, gVCF (containing short variants, copy number variants, and structural variants), RoH (BED), B-allele frequencies (BW), and variant IGV visualizations (XML). Associated phenotypic and pedigree information for all samples is also included.

  Dataset EGAD50000002331

• The life-saving benefit of dexamethasone in severe COVID-19 is linked to a reversal of monocyte dysregulation

  Assessment of dexamethasone response in human lung through scRNA-seq analysis of bronchoalveolar lavage (BAL) samples from patients with severe COVID-19.

  Study EGAS50000000203

• miRNA-sequencing of PBMCs from COVID-19 patients experiencing different degrees of the disease (mild and critical), and control patients

  micro RNA-sequencing of peripheral blood mononuclear cells collected from mild COVID-19 (n = 6), critical COVID-19 (n = 13) and control (n = 8) patients. Sequencing data is provided as FASTQ files.

  Dataset EGAD50000001406

• Genomic characterization of CNA-quiet oral cancer

  Low-coverage whole genome sequencing and targeted (30 gene panel) deep sequencing of oral cancer. Note that the targeted deep sequencing is not actually amplicon sequencing but hybrid capture sequencing, which was not available as on option.

  Dataset EGAD50000000790

• Pregnancy-associated melanoma

  The aim of this project is to assess differences in intratumoral immune composition in pregnant melanoma patients versus non pregnant melanoma controls. Samples (N=25) were obtained from a local patient database. From archived FFPE we isolated RNA and performed NGS and bio-informatica data-analysis.

  Dataset EGAD50000000706

• Whole exome sequencing of sequential samples from a CLL patient over the course of venetoclax treatment, BCR inhibitor treatment, and venetoclax re-treatment

  The dataset contains whole exome sequencing data (libraries prepared using the Agilent SureSelect Human All Exon V6 kit, and paired-end sequenced on Illumina HiSeq4000 (2 x 150bp)) of 6 samples taken from peripheral blood mononuclear cells (PBMCs) (Samples 1-5) and bone marrow (BM). Data are provided as fastq files. Sample 1 was taken prior to initial venetoclax treatment. Sample 2 was taken as disease progression on venetoclax. Sample 3 was taken during response to BTK and PI3K inhibitor therapy. Sample 4 and the BM sample were taken at disease progression/prior to venetoclax re-treatment. And Sample 5 was taken during venetoclax re-treatment response.

  Dataset EGAD00001008685

• Genomic characterisation of SDH deficient renal cell carcinoma - WGS

  SDH deficient renal cell carcinomas are a rare and recently defined subtype of kidney cancer, often associated with an inherited mutation in one of the SDH gene subunits. This dataset sought to understand the genomic events that underpin tumour formation, from putative cell of origin, characterisation of the tumour microenvironment, to the genomic evolution of these rare tumours. We performed whole genome and RNA sequencing of 4 patients with SDH deficient renal cell carcinomas, including one patient who had an additional paraganglioma. An addition patient in this cohort had the initial diagnosis revised to a clear cell renal cell carcinoma.

  Dataset EGAD00001008469

• scRNAseq of distal colon biopsies from patients with ulcerative colitis and healthy controls

  scRNAseq dataset of colonic epithelium from distal colon biopsies from 4 patients with ulcerative colitis and 4 healthy individuals. Includes 11 samples split into three conditions: healthy, healthy margin and ulcerated. Dataset includes raw Fastq files and processed csv count matrices. Fastq files are divided into 4 lanes and into index (I1) and read (R1, R2) files. Count matrices contain comma-separated values with cell barcodes as column names and gene names as row names. Cell Ranger (v3.0.1) software from 10x Genomics was used to process the output and align the reads. The refdata-cellranger-GRCh38-3.0.0 reference was downloaded from the 10x Genomics website. First, cellranger mkfastq function was used to demultiplex raw base call files into FASTQ files. Then, the FASTQ files were aligned and filtered with cellranger count function.

  Dataset EGAD00001010167

• Blood Transcriptome Profiling Links Immunity to Disease Severity in Myotonic Dystrophy Type 1 (DM1)

  Here, we explore the molecular signatures in RNA sequencing data from blood associated with disease severity as measured in Myotonic dystrophy type 1 (DM1) patients with less than 400 CTG-repeat length size in the DMPK gene in blood. These DM1 patients participated in the OPTIMISTIC study. This approach involved stratifying those within the OPTIMISTIC study into different patient groups with different degrees of disease severity (as measured by the muscle-impairment rating scale (MIRS)) and assessed at baseline. Patients were divided into groups with mild (MIRS 1–2) and severe (MIRS 3–5) neuromuscular symptoms with different DMPK repeat length characteristics. Therefore these .Bam files are baseline samples from this study.

  Dataset EGAD00001010010

• Combination therapies to inhibit LCK tyrosine kinase and mTOR signaling in T-cell Acute Lymphoblastic Leukemia

  Relapse and refractory T cell acute lymphoblastic leukemia (T-ALL) has a poor prognosis and new combination therapies are sorely needed. This work uncovered potent drug synergies between AKT/mTORC1 inhibitors and the general tyrosine kinase-inhibitor, dasatinib. The combination effectively curbed T-ALL growth in human cell lines and primary human T-ALL samples, and was well tolerated and effective in suppressing leukemia growth in patient-derived xenografts grown in mice. Mechanistically, dasatinib inhibited phosphorylation and activation of the lymphocyte-specific protein tyrosine kinase (LCK) to blunt the T-cell receptor (TCR) signaling pathway and when complexed with mTORC1 inhibition, induced potent T-ALL cell killing through reducing MCL-1 protein expression. Analysis of responses across T-ALL subtypes and association with specific genetic mutations or expression patterns failed to identify any obvious biomarkers or correlations in predicting therapy responses, although there appeared to be a trend toward higher TCR/LCK pathway activity in samples that exhibited synergistic therapy responses.

  Study EGAS00001005945