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• DNA methylation array analysis of pediatric T-cell acute lymphoblastic leukemia

  Pediatric T-cell acute lymphoblastic leukemia (T-ALL) is rare and its pathogenesis is poorly understood. To investigate epigenetic profiles of pediatric T-ALL, we performed DNA methylation array analysis in 79 cases of pediatric T-ALL.

  Study JGAS000138

• BGISEQ-500 Cancer Dataset - WGS tumour/normal pairs

  This study contains whole genome sequencing data for 3 matched tumour / normal pairs from Mesothelioma patients. The sequencing is 50bp paired-end generated using the BGISEQ-500 and is provided as 6 aligned and duplicate-marked BAM files.

  Study EGAS00001002298

• Subtype specific studies of breast cancer progression. Milan cohort.

  The aim of this study is to compare DCIS and IBC in a subtype stratified manner in several genomic levels (gene expression, copy number, methylation).The data in this archive is supplementary to previously published data.

  Study EGAS00001004390

• NCI Cancer Model Development for the Human Cancer Model Initiative (HCMI)

  The Cancer Model Development Center (CMDC) project is part of the Human Cancer Model Initiative (HCMI) and is managed by the Office of Cancer Genomics within the Center for Cancer Genomics at the National Cancer Institute (NCI). The goal of the HCMI is to generate approximately 1000 novel human "next generation" tumor-derived models as a community resource. The models aim to faithfully recapitulate the cellular complexity and heterogeneity of human tumors. The CMDCs are tasked by the NCI with producing a proportion of the cancer models. Wellcome Sanger Institute (WSI) is a contributing member of the HCMI. Models developed by HCMI are being derived from a number of tumor types and subtypes (see below), including rare adult, pediatric and understudied cancers. The number of models and the clinical sites from which patient samples are acquired is increasing. Normal tissue, originating tumor, and tumor-derived models are sequenced. The next generation cancer models are associated with rich clinical and genomic data through the NCI Genomic Data Commons for all researchers to advance cancer research. The CMDC and HCMI models will serve as excellent tools in research to provide insight into the pathways that influence tumor growth and progression, how tumors respond to therapy, etc. Ultimately, the data generated using these models will support the development of personalized oncology. There is a delay between registered IDs and model availability. The current model count is found in The HCMI Searchable Catalog which is updated when new models are available for distribution to the research community.

  Study phs001486

• Spatial and temporal evolution of distal 10q deletion, a prognostically unfavorable event in diffuse low-grade gliomas

  Background: The disease course of patients with diffuse low-grade glioma is notoriously unpredictable. Temporal and spatially distinct samples may provide insight into the evolution of clinically relevant copy number aberrations (CNAs). The purpose of this study is to identify CNAs that are indicative of aggressive tumor behaviour and can thereby complement the prognostically favorable 1p/19q co-deletion. Results: Genome-wide, 50 base pair single-end, sequencing was performed to detect CNAs in a clinically well-characterized cohort of 98 formalin-fixed paraffin-embedded low-grade gliomas. CNAs are correlated with overall survival as an endpoint. Seventy-five additional samples from spatially distinct regions and paired recurrent tumors of the discovery cohort were analysed to interrogate the intratumoral heterogeneity and spatial evolution. Loss of 10q25.2-qter is a frequent subclonal event and significantly correlates with an unfavorable prognosis. A significant correlation is furthermore observed in a validation set of 126 and confirmation set of 184 patients. Loss of 10q25.2-qter arises in a longitudinal manner in paired recurrent tumor specimens, whereas the prognostically favorable 1p/ 19q co-deletion is the only CNA that is stable across spatial regions and recurrent tumors. Conclusions: CNAs in low-grade gliomas display extensive intratumoral heterogeneity. Distal loss of 10q is a late onset event and a marker for reduced overall survival in low-grade glioma patients. Intratumoral heterogeneity and higher frequencies of distal 10q loss in recurrences suggest this event is involved in outgrowth to the recurrent tumor.

  Study EGAS00001000643

• PLCG1 R707Q mutation is counter selected under targeted therapy in a patient with a hepatic angiosarcoma

  PLCG1 R707Q mutation is counter selected under targeted therapy in a patient with a hepatic angiosarcoma

  Study EGAS00001001281

• Whole exome sequencing to discover genetic variation associated with aortopathy in Turner Syndrome

  Turner syndrome is a disorder affecting only girls and women, which is caused by a complete or partial loss of the second sex chromosome. Girls and women with Turner syndrome have a variety of phenotypes. Of interest to this study is aortopathy, including bicuspid aortic valve (BAV) and thoracic aortic dilation (TAD) in which we know that 25 - 50% of girls with Turner syndrome are born with. The aorta is the main artery that conducts the blood out of the heart. The aortic valve guards the entrance to the aorta. When the aortic valve has two leaflets instead of the usual three it is called a BAV. BAV is more common than all other congenital heart defects combined. BAV commonly causes obstructions to blood flow out of the heart or become leaky over time. BAV often occurs in combination with TAD. In Turner syndrome, TADs are increased 50-100 fold compared to the general population. Currently, there are no effective approaches or pre-surgical treatments for aortic disease. Therefore, progression of aortic disease in individuals with BAV/TAD can result in catastrophic aortic dissection, rupture, and death. Our goal is to leverage DNA sequencing and carefully curated patient samples to gain a better understanding of the molecular mechanisms that cause these inter-related aortic diseases.

  Study phs001531

• National Institute of Mental Health (NIMH) Amish Mennonite Bipolar Genetics Study (AmBiGen)

  Bipolar affective disorder is a severe, heritable condition affecting about one percent of the population. The mode of inheritance is poorly understood and probably involves multiple loci of small to moderate effect. In this project, we use genetic mapping and sequencing methods to identify genetic markers and variations that contribute to the risk of bipolar disorder. Individuals diagnosed with bipolar disorder are studied, along with their relatives. Phenotypic information obtained from clinical interviews and family history is correlated with genotypic information obtained from genetic marker and sequencing methods. The goal is to identify genes involved in bipolar disorder and related conditions so that better methods of diagnosis, treatment, and prevention can be developed.

  Study phs000899

• Identifying causative mutations for Thrombocytopenia with Absent Radii

  Thrombocytopenia with Absent Radii is an inherited disorder that manifests itself with major limb skeletal abnormalities and low platelet count (and therefore a bleeding diathesis). The syndrome is well-characterised and defined phenotypically and there is a well-established database of UK-based families affected with ths disorder. The causative mutation for the disorder is yet to be identified. If known, it would allow for pre-natal screening and counselling avoiding life-long care for patients who are affected and are therefore severely disabled. We postulate that exon sequencing of 4 unrelated affected individuals would give enough power to narrow down potential candidate mutations which would thereafter be confirmed using DNA from other affected families.

  Study EGAS00001000054

• CINECA synthetic data.Please note: This study contains synthetic data (with cohort “participants” / ”subjects” marked with FAKE) has no identifiable data and cannot be used to make any inference about cohort data or results.

  Please note: This study contains synthetic data (with cohort “participants” / ”subjects” marked with FAKE) has no identifiable data and cannot be used to make any inference about cohort data or results. The purpose of this dataset is to aid development of technical implementations for cohort data discovery, harmonization, access, and federated analysis. In support of FAIRness in data sharing, this dataset is made freely available under the Creative Commons Licence (CC-BY). Please ensure this preamble is included with this dataset and that the CINECA project (funding: EC H2020 grant 825775) is acknowledged. For any questions please contact isuru@ebi.ac.uk or cthomas@ebi.ac.uk

  Study EGAS00001002472