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• Whole exome sequencing of endometriod ovarian cancer tumours

  Whole Exome sequencing data of tumour samples for 112 patients with endometrioid ovarian carcinoma in FASTQ format. Data was derived as summarized below: Library Preparation: Libraries were prepared from each DNA sample using the Illumina TruSeq Exome Library Prep kit (#FC-150-1002) according to the provided protocol using modifications for working with FFPE sourced material. Libraries were quantified using the Qubit 2.0 Fluorometer and the Qubit DNA HS assay (#Q32854) and the size distribution of fragments was assessed using the Agilent Bioanalyser with the DNA HS Kit (#5067-4626). Library QC: Exome-captured sequencing library pools were quantified using the Qubit 2.0 Fluorometer and the Qubit DNA HS assay (#Q32854) and the size distribution of fragments was assessed using the Agilent Bioanalyser with the DNA HS Kit (#5067-4626). Fragment size and quantity measurements were used to calculate molarity for each library pool. Sequencing: Sequencing was performed using the NextSeq 500/550 High-Output v2 (150 cycle) Kit (# FC-404-2002) on the NextSeq 550 platform (Illumina Inc, #SY-415-1002).

  Dataset EGAD00001006389

• ISCAPE V(D)J libraries from HA-specific single memory B cells of four Influenza A exposed individuals

  Peripheral blood mononuclear cells were used to produce paired, full-length IGM, IGK and IGL V(D)J libraries from HA-binding single memory B cells using the ISCAPE (Individualized Single Cell Analysis of Paired Expressed antigen receptors) technique. Locus-specific multiplexed nested PCR with primer sets targeting the 5’ UTR/leader and 3’ constant region was performed before well and plate indexing and paired chain sequencing with an Illumina MiSeq instrument. Expressed total IGM, IGK and IGL V(D)J libraries from each donor were acquired and analyzed to define personalized IG allele content. The fastq file names include the donor and a numerical plate index for the HA-specific ISCAPE BCR HC and LC V(D)J libraries.

  Dataset EGAD50000002019

• RRBS of 25 pleural mesothelioma samples (Single-end)

  The dataset contains RRBS data (bam files) for 25 pleural mesothelioma samples.The samples were sequenced on NovaSeq6000 (Illumina, San Diego, CA) in single-end 150bp mode. RRBS raw reads were trimmed for adaptor sequences using trim galore (v. 0.6.5) (http://www.bioinformatics.babraham.ac.uk/projects/trim_galore/) and filtered for low-quality sequences using fastQC (v. 0.11.8) (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/). High quality trimmed reads were mapped to the Human reference genome (UCSC genome assembly GRCh38/hg38) using Bismark (v. 0.22.3) with default parameters.

  Dataset EGAD50000002130

• RRBS of 58 pleural mesothelioma samples (Paired-end)

  The dataset contains RRBS data (bam files) for 58 pleural mesothelioma samples. The samples were sequenced on NovaSeq6000 (Illumina, San Diego, CA) in paired-end 150bp mode. RRBS raw reads were trimmed for adaptor sequences using trim galore (v. 0.6.5) (http://www.bioinformatics.babraham.ac.uk/projects/trim_galore/) and filtered for low-quality sequences using fastQC (v. 0.11.8) (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/). High quality trimmed reads were mapped to the Human reference genome (UCSC genome assembly GRCh38/hg38) using Bismark (v. 0.22.3) with default parameters.

  Dataset EGAD50000002129

• Characterizing the cell-free transcriptome in a humanized DLBCL patient-derived tumor xenograft model for RNA-based liquid biopsy in a preclinical setting

  This study explores the cell-free transcriptome in a humanized DLBCL patient-derived tumor xenograft (PDTX) model. Blood plasma samples (n=171) derived from a DLBCL PDTX model including 27 humanized (HIS) PDTX, 8 HIS non-PDTX and 21 non-HIS PDTX NOD-scid IL2Rgnull mice were collected during humanization, xenografting, treatment, and sacrifice. The mice were treated with either R-CHOP, huCD20-Fc-AFN-CHOP, or phosphate-buffered saline (PBS). RNA was extracted using the miRNeasy serum/plasma kit and sequenced on the NovaSeq 6000 platform using the SMARTer Stranded Total RNA-seq pico v3 kit.

  Study EGAS50000000566

• High titers and low fucosylation of early phase anti-SARS-CoV-2 IgG promote hyper-inflammation by alveolar macrophages

  We show that early phase anti-Spike IgG in serum of critically ill COVID-19 patients induces hyper-inflammatory responses by human alveolar macrophages. We identified that this excessive inflammatory response is dependent on two antibody features that are specific for severe COVID-19. First, inflammation is driven by high titers of anti-Spike IgG, a hallmark of severe disease. Second, we found that anti-Spike IgG from severely ill patients is intrinsically more pro-inflammatory because of different glycosylation of the Fc tail, particularly by low fucosylation. This dataset is linked with the following ArrayExpress Experiment: E-MTAB-10431 - 2020_COVID19_FCGR_MIL10_IgGfucosylation

  Study EGAS00001005206

• Recurrent mTORC1-activating RRAGC mutations in follicular lymphoma

  Follicular lymphoma (FL) is an incurable B-cell malignancy characterized by the t(14;18) and mutations in one or more components of the epigenome. Whilst frequent gene mutations in signaling pathways, including JAK-STAT, NOTCH and NF-κB, have also been defined, the spectrum of these mutations typically overlap with the closely-related diffuse large B cell lymphoma (DLBCL). A combination of discovery exome and extended targeted sequencing revealed recurrent somatic mutations in RRAGC uniquely enriched in FL patients (17%). More than half of the mutations preferentially co-occurred with ATP6V1B2 and ATP6AP1 mutations, components of the vacuolar H+-adenosine triphosphate ATPase (v-ATPase) known to be necessary for amino acid-dependent mTORC1 activation. RagC mutants increased raptor binding whilst rendering mTORC1 signaling resistant to amino acid deprivation through nucleotide-independent mechanisms. Collectively, the activating nature of the RRAGC mutations, their existence within the dominant clone and stability during disease progression supports their potential as an excellent candidate to be therapeutically exploited.

  Study EGAS00001001190

• Variables of diversity, clonality, V and J usage and main COVID-19-reactive GLIPH2 frequencies.

  Main results of the T cell repertorie analysis of a cohort of 61 patients. For each patient, repertorie diversity and clonality metrics, V an J alelle frequency and COVID-19-reactive sequencies have been calculated using open.source code. For more information about the study, please visit DOI: 10.1186/s40246-024-00654-0

  Study EGAS50000000587

• Identifying genetic variants that alter TCR usage in the peripheral repertoire

  The relationship between genetic variation and CD8+ T-cell receptor (TCR) repertoire usage in patients receiving Immune Checkpoint Blockade (ICB) therapy for cancer is unexplored. We have conducted a genome-wide and human leukocyte antigen (HLA)-focused analysis of CD8+ T-cell TCR repertoire to identify genetic determinants of variable gene (V-gene) and CDR3 K-mer usage from samples taken prior to and after ICB (n=250). We identify 11 cis and 10 trans V-gene associations, primarily to the MHC, that meet genome-wide significance. TCR clones containing HLA associated V-genes were less stable across treatment, whilst at the single-cell level, genetically associated clones demonstrate subset enrichment and increased tumor reactivity expression profiles. Notably, patients with HLA-matched TCR clones demonstrate improved overall survival. Our work indicates a complex relationship between genotype and TCR repertoire in the context of ICB treatment, with novel implications for understanding factors relating to therapeutic response and patient outcomes.

  Study EGAS00001008189

• Single-cell transcriptome analysis of B-cell development in the ABO platform

  The dataset includes samples from four individual donors, pooled at each cell-harvesting time point (days 21, 28, and 35). Single-cell RNA sequencing was performed on the 10x Genomics Chromium platform using GEM-X Single Cell 5′ v3 and GEM-X Single Cell V(D)J v3 for BCR profiling. For each timepoint, paired libraries were constructed: a 5′ GEX library and a V(D)J-B library. Per reaction 350,000-400,000 cells were loaded, aiming for 60,000 cells per reaction. Pooled libraries were sequenced on an Illumina NovaSeq X sequencer. 50,000 read pairs per cell for GEX and 5,000 read pairs per cell for V(D)J were targeted.

  Dataset EGAD50000002433