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• Clonal_selection_after_gene_therapy_in_SCD___Duplex_sequencing

  This study includes the targeted duplex sequencing data relating to this study. A custom targeted panel was used including 29 AML-associated genes, and a set of mutations from driver-containing clones that were sequenced during the WGS tree-building phase of the study. Targeted sequencing is performed on each of 6 individuals included at the study at at least 3 time points per individual: one prior to gene therapy, and two post-therapy time points.

  Study EGAS00001007253

• RNA sequencing in primary human macrophages overexpressing ETS2

  We investigated an intergenic haplotype on chr21q22, linked to five different inflammatory diseases, and discovered a mechanism that orchestrates macrophage responses during chronic inflammation. We delineated how the risk haplotype increases expression of the causal gene, ETS2, and demonstrated that ETS2 is necessary for inflammatory macrophage effector functions. To establish whether ETS2 is sufficient to drive inflammatory responses, we overexpressed ETS2 in a dose-dependent manner and performed RNA-sequencing to characterise the transcriptional effects.

  Study EGAS00001007554

• Acquisition of additional mutations drives accelerated progression of NPM1 positive CMML to AML

  This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ We performed exome sequencing on serial samples from a patient with CMML who progressed to AML. The exome sequencing suggests that NPM1, TET2 and DNMT3a mutations were present in the dominant clone in the CMML sample and that NRAS is a new subclonal mutation in the AML sample. Diagnostic data shows the presence of a FLT3-ITD mutation in the AML sample, which is likely to have driven progression. Here we are performing re-sequencing of the putative driver and some passenger mutations which appear to be in the same clone to validate these mutations and to verify the relative quantification of these abnormalities .

  Dataset EGAD00001002194

• Evaluating gene expression in aggressive B-cell lymphoma using a quantitative nuclease protection assay

  Diffuse large B-cell lymphoma (DLBCL) is the most common non-Hodgkin lymphoma (NHL), comprising 25-30% of all NHL in developed countries with an annual incidence in the USA of 7 cases/100000 persons/year. Collectively, DLBCL is classified based on a common morphological appearance of diffuse growth of large transformed B-cells, immunophenotype, high proliferation rate and aggressive behaviour. Despite these similarities, DLBCLs are a heterogeneous collection of malignancies with distinct clinical and molecular characteristics that do not always correlate with immunohistological features. This gene expression dataset includes transcriptomes of ABC-DLBCLs and of GCB-DLBCLs where cell of origin is determined by the HTG-EdgeSeq quantitative nuclease protection assay. Also included are clonality results from BCR profiling from high-grade B-cell lymphomas sequenced using a NOVA sequencer

  Dataset EGAD00001011309

• Somatic mutation and clonal evolution in premalignant lung disease - WGS (2020-01-15)

  Cancer is a genetic disease caused by an accumulations of mutations, however many of these mutations have been identified in pathologically normal tissue. We aim to use laser-capture microscopy (LCM) to sample individual clones from the lung tissue of individuals with a variety of lung diseases (COPD, UIP, IPF, Emphysema, pulmonary hypertension). This will allow us to identify whether cancer-associated mutations appear in this normal tissue, assess the mutational burden present, and identify the mutational processes causing these mutations. Smoking is a large risk factor for developing many of these lung diseases so we are particularly keen to determining whether there is evidence of a smoking signature in these patients. . This dataset contains all the data available for this study on 2020-01-15.

  Dataset EGAD00001005786

• Clonal origin of lineage switch leukemia following CAR-T cell and blinatumomab therapy

  Children with ALL treated with anti-CD19 therapy occasionally develop a phenotypically distinct AML. However, the precise clonal origin of such class switch leukemias remains unresolved. Here, we reconstructed the evolution of leukemia in a child with primary ALL, two ALL relapses and AML after treatment with anti-CD19 CAR-T and blinatumomab through whole-genome sequencing. The phylogeny revealed that the AML was a monoclonal outgrowth descending from the initial ALL and harbored biallelic loss of CDKN2A, PAX5 and TP53. However, none of the ALL or AML relapses directly descended from one another, suggesting the presence of a reservoir of persistent clones. Our findings suggest anti-CD19 treatment selects pre-existing clones, with many key genetic alterations underpinning the lineage switch detectable prior to treatment.

  Dataset EGAD00001009161

• Organ maturation in preparation for birth (Peds RFA) to develop a tissue resource and a single-cell atlas of organ development and maturation for dissemination among the scientific and clinical community: RNA (2025-10-14)

  Knowledge about abnormal organ development is important to understand pathology and to develop novel treatment approaches for individuals with congenital and acquired disease. Most of our current understanding is based on examination of tissues from the embryo and early foetus, collected from women undergoing termination of pregnancy in the first trimester (third) of pregnancy. There is very little known about normal and abnormal organ development from a developmental perspective during the crucial last two-thirds of pregnancy when much remodelling of foetal tissues occurs. This study will generate a single-cell atlas of late-foetal lungs, blood, heart, bone and immune organs. . This dataset contains all the data available for this study on 2025-10-14.

  Dataset EGAD00001015737

• Variant calling analysis of cfDNA whole exome sequencing in neuroblastoma

  This dataset contains VCF files from a variant calling analysis of 19 neuroblastoma patients. WES or WGS data of the primary tumor were compared to WES cfDNA analysis at the time of diagnosis and at a 2nd timepoint (complete remission, partial remission, disease progression or relapse). For 4 patients, WGS of germline, tumor at diagnosis and tumor at relapse DNA was performed on Illumina HiSeq2500, with 100-bp paired-end reads. For the other patients, WES was performed using either an AgilentSureSelect Human All Exon v5 or a Roche Nimblegen SeqCap EZ Exome V3 kit on Illumina HiSeq2000, with 100-bp paired-end reads. SNVs observed in any of the primary tumors or cfDNA samples studied by WES were targeted using a capture sequencing panel at all intermediate time points.

  Dataset EGAD00001003803

• Identification of genes involved in congenital disorders of glycosylation and 3-methylglutaconic aciduria (2018-03-14)

  Identification of genes involved in congenital disorders of glycosylation and 3-methylglutaconic aciduria. There are more than 100 genes known for congenital disorders of glycosylation and new disorders are discovered each year. WE included patients with a so far unsolved glycosylation disease. The diagnostic group 3-methyglutaconic aciduria is a heterogenous group of disorders mostly caused by abnormal phospholipid synthesis or in association with mitochondrial dysfunction. We included patients with a so far unsolved disease and 3-methylglutaconic aciduria. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2018-03-14.

  Dataset EGAD00001004038

• Cell-free DNA methylome and fragmentome analysis for disease relapse monitoring in patients with Ewing Sarcoma

  We conducted whole-genome and methylome sequencing of cfDNA from 87 serial samples of 23 patients with EwS and 3 patients with CIC-rearranged sarcoma (CIC). With EwingSign, a new machine learning model, we identified EwS or CIC in a test set for 11 out of 16 patients at diagnosis and 15 out of 18 clinically confirmed relapse events. 0 out of 24 non-cancer controls were detected positive with EwingSign.

  Study EGAS50000001415