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• 2015 AML-ETO WGS analysis result

  This data is belong to 2015 AML-ETO patients' genome data which is aligned to human reference(human_g1k_v37.fasta). There are 10 paired tumor/normal samples from SNUH. All samples has passed QC and recalibration steps while aligning to reference.

  Dataset EGAD00001004011

• Lung Multi-site Targeted Sequence Capture

  DNA extracted from multiple biopsies taken from different areas of primary lung tumours will be subjected to targeted re-sequencing and analysed in order to assess intra-tumour heterogeneity with respect to mutations in a selection of cancer related genes.

  Dataset EGAD00001001017

• Whole Exome Sequencing of a Melanoma Patient with Acquired Resistance to MEK plus CDK4/6 Inhibition

  Longitudinal biopsies from a melanoma patient who initially responded to MEK plus CDK4/6 inhibitor therapy were whole exome sequenced to identify potential resistance mutations. The biopsies included normal tissue, pre-treatment, on-treatment, and several post-resistance timepoints.

  Dataset EGAD00001003989

• 2015_AML Whole exome sequencing analysis result

  This data is belong to 2015 whole exome sequenced AML data which is aligned to human reference(human_g1k_v37.fasta). There are 40 paired NR samples from Chunnam University. All samples has passed QC and recalibration steps while aligning to reference.

  Dataset EGAD00001003587

• 2018 AML-ETO WGS analysis result

  This data is belong to 2018 AML-ETO patients' genome data which is aligned to human reference(human_g1k_v37.fasta). There are 12 paired tumor/normal samples from SNUH. All samples has passed QC and recalibration steps while aligning to reference.

  Dataset EGAD00001003912

• 2014 sequenced AML-WGS analysis result

  This data is belong to 2014 AML-WGS patients' genome data which is aligned to human reference(human_g1k_v37.fasta). There are 10 paired tumor/normal samples from SNUH. All samples has passed QC and recalibration steps while aligning to reference.

  Dataset EGAD00001003925

• After the completion of CINECA, EUCANCan, and euCanSHare. What's next?

  CINECA, EUCANCan, and euCanSHare were part of the EUCAN Cluster, made up of six projects that received funding under the same Horizon 2020 call. All EUCAN projects (CINECA, EUCANCan, EUCAN-Connect, euCanSHare, Receptor Plus, and ReCoDID) were aimed at facilitating data reuse and knowledge discovery by enhancing data exchange and long-term collaboration in the health field. Here are some highlights about EGA’s contribution to these projects. CINECA: advances in Federated discovery and infrastructure for cohorts CINECA (Common Infrastructure for National Cohorts in Europe, Canada, and Africa) developed a federated cloud-based infrastructure for making genomic and biomolecular data accessible. The project has assembled a virtual cohort of 1.4 million individuals from sources such as the EGA, CanDIG and H3Africa. The EGA–CRG co-leaded a work package Work Package 1 on Federated Data Discovery and Querying. Beacon v2, championed by Jordi Rambla and Lauren Fromont, has been one of the central elements for the discovery of human genetic and phenotypic data. The EGA-CRG contributed to the development of a model for cohort discovery inside the Beacon v2 model. The team also delivered a Discovery Portal was implemented to explore cohorts and individuals of synthetic data. It is a UI that gathers a network of Beacons, a service for query expansion, and a visualisation tool. Have a look at the Discovery Portal UI, gathering a network of Beacons. You will find entities such as the Barcelona Supercomputing Center (BSC), BioData.pt and the European Genomic Data Infrastructure (GDI), among others. euCanSHare: facilitation of data access management This joint EU-Canada project aimed to build a European and Canadian FAIR platform for cardiovascular data sharing and analysis. The EGA’s tasks contributed to the development of the data management plan and data flows, main web-portal and interoperability protocols. An important part of the EuCanShare platform is the data access manager, a tool for the data owners to control the access to their sensitive datasets. We built a user-friendly interface for data access committees (data owners) to easily manage their data requests and access credentials. The data access portal facilitates the creation and internal organization of the data access committees as well as the linkage of data usage conditions to specific datasets. The interface includes filters for browsing requests and page to visualize the request history helping with the handling of data access requests. EUCANCan: toward a federation of clinical institutions in oncology The EUropean-CAnadian CANcer Network worked towards building a federated network to advance personalized medicine in oncology, by promoting the standard analysis, management and sharing of harmonized genomic and phenotypic data. The EGA led tasks on defining data flows and preparing an adapted infrastructure for long-term data storage and sharing. One of the key contributions was the conception of the EGA communities, offering standard and interoperable solutions for data discovery, processing, and sharing to projects and institutions that would like to manage and share data in the context of the EGA ecosystem. What's Next? The participation in projects such as CINECA, EUCANCan, and euCanSHare provide us with experience for future projects. We are happy to enhance data sharing and reuse, vital for advancing clinical and genomic research. The Discovery Portal is a wonderful proof of concept for the Beacon network. Next, we will finalise both the network and the user interface, and make sure it can be applied to more clinically-centred settings like hospitals. Most data hosted at the EGA are about cancer research. Currently, we contribute to building tools and infrastructure to empower oncology research in several European projects such as EUCAIM, EUCANIMAGE and EOSC4Cancer. We also do not lose sight of initiatives in the field such as the International Cancer Genome Consortium (ICGC) with the project ARGO, whose data model was adopted in EUCanCan.

  Blog cineca-eucancan-and-eucanshare-were-concluded-in-june

• Successful Clinical Response in Pneumonia Therapy (SCRIPT)

  The goal of this study is to iteratively identify, validate and refine biomarkers to predict clinical failure, and identify novel targets for therapy, beyond traditional antibiotics, for patients with severe pneumonia requiring intubation, including severe community-acquired pneumonia (CAP), hospital-acquired pneumonia, and ventilator-associated pneumonia (HAP/VAP). We hypothesize that factors within the alveolar microenvironment in many patients with pneumonia prevent the active process of pneumonia resolution.The major emphasis will be on HAP. Mechanically ventilated CAP patients are a very high-risk group for subsequent VAP, and therefore CAP samples will be included to determine baseline bacteria, microbiome, and host defense patterns for those that do or do not develop HAP/VAP. Hospital-acquired pneumonia is the leading cause of death from nosocomial infections. Even in patients receiving pathogen-appropriate therapy, reported clinical failure rates are increasing, approaching 50% in recent clinical trials. Current approaches to improve outcomes in patients with pneumonia almost exclusively focus on the development of antibiotics to address the problem of resistance. However, the prevalence of antibiotic-resistant pathogens is insufficient to explain the high rates of clinical failure. Instead, we hypothesize that factors within the alveolar microenvironment in many patients with pneumonia prevent the active process of pneumonia resolution. These factors include pathogen-specific adaptations to the injured lung that modulate the innate and adaptive immune response, as well as changes to the alveolar microbiome, driven by selective pressure within our modern intensive care units. Understanding this complex adaptive system requires the integration of clinical information with unbiased measures of the host, pathogen, and microbiome changes within the alveolar microenvironment. These measures must be repeated over time to identify factors that distinguish successful from failed therapy for pneumonia sufficiently early during the clinical course to allow for effective interventions. To address this challenge, we have assembled a talented group of investigators in the Successful Clinical Response In Pneumonia Therapy (SCRIPT) Systems Biology Center. We will leverage our routine clinical practice of safe alveolar sampling in mechanically ventilated patients with pneumonia with repeated non-bronchoscopic bronchoalveolar lavage (NBBAL) sampling over the course of pneumonia. From this fluid, we will combine flow cytometry with multi-omic technologies (cell population-specific transcriptomics, epigenomics, shotgun microbiome sequencing, and pathogen-specific sequencing). Our systems scientists will integrate these genomic data with robust clinical -omics with the goal of identifying biomarkers that can be prospectively tested in patients and causally evaluated in humanized mouse models.The addition of a pooled sample artificially increases the number of automatically computed subjects by one.

  Study phs002300

• Mucociliary Clearance Consortium (MCC) Rare Genetic Disorders of the Airways: Cross-section Comparison of Clinical Features, and Development of Novel Screening and Genetic Test

  We have established a consortium of 7 geographically-dispersed clinical research sites that are designed to study rare diseases of the airways, which involve defects in clearance of mucus secretions from the airways (defective "mucociliary clearance"). These sites will collaborate in diagnostic, genetic, and other studies in patients with impairments of mucociliary clearance, including primary ciliary dyskinesia (PCD), variant cystic fibrosis (CF), and pseudohypoaldosteronism (PHA). These disorders reflect genetic defects in airway host-defense, and typically result in chronic infection of the airways. Patients with these disorders of the conducting airways and sinuses have delayed (or incorrect) diagnoses, because diagnostic tests are not readily available. These patients may also have sub-optimal management of their clinical disease, because the cause of these disorders is not well-defined, and treatment regimens are usually not driven by evidence-based medicine. This current protocol is designed to employ a systematic approach to the diagnostic evaluation of these patients with chronic airways disease, which will yield precise diagnoses in individual patients, and will be associated with development of better diagnostic techniques, including genetic testing. In addition, we will compare/contrast clinical features (phenotype) across these disorders. A rigorous cross-sectional comparison of the clinical features will provide better understanding of the clinical disease of these disorders; in turn, this will lead not only to a better standard of clinical care, but will also assist in the identification of novel therapeutic approaches. The patient population for these studies includes individuals carrying a tentative diagnosis of the three disorders (PCD, variant CF or PHA), plus individuals suspected to have one of these disorders, but with inadequate or inconclusive diagnostic tests. Individuals in this latter category must have a preliminary clinical evaluation to evaluate for other more common disorders that may have similar manifestations including classical CF, immunodeficiency, asthma, and severe gastroesophageal reflux. We have an informal agreement with a network of pulmonologists across the United States to perform clinically-indicated (not research) preliminary clinical testing, if not directly available to patients who inquire about these studies. Blood will be collected for DNA to test for genetic mutations. The blood samples will be processed to establish a cell line (lymphocyte transformation) for a source of DNA for future genetic studies, in participants with disease. For participants unable to provide a blood sample, a buccal sample will be obtained for DNA.

  Study phs000595

• Genomics of Kidney Transplantation

  We have an established consortium consisting of 5 clinical centers which do a total of >800 kidney transplants/year. We have developed a quality-controlled multicenter database with high quality data, and obtained DNA samples and clinical data on 962 recipients and 442 donors. Using our developed infrastructure, we propose to study whether genetic variants are, in part, responsible for the differing outcomes of transplant recipients treated with contemporary immunosuppressive protocols. Our central hypotheses are that the genetic variation is associated with a) kidney transplant outcome, and b) immunosuppressive drug disposition and toxicity. Our long-term goals are to determine whether it is possible to individualize immunosuppressive therapy, based on genetics. At the same time, our studies may elicit new information on pathways important in the immune response or in immunosuppressive drug efficacy, disposition, and toxicity.Our application consists of 3 cores (Genetics Core, Clinical Core, and Administrative Core). We will do a genome wide association study (GWAS). Significant single nucleotide polymorphisms (SNPs) will be identified using the GWAS.Project 1 has 2 specific aims.Aim 1: To identify recipient SNPs that are associated with kidney allograft outcomes, including acute rejection, chronic graft dysfunction, and graft failure. Aim 2: To identify living donor SNPs that are associated with kidney allograft outcomes. Project 2 has 4 specific aims. Aim 1: To identify SNPs that are associated with tacrolimus blood levels.Aim 2: To identify SNPs that are associated with early tacrolimus-related nephrotoxicity and immune suppressant-related new onset diabetes.Aim 3: To identify SNPs that are associated with mycophenolate-related toxicity. Aim 4: To establish the relationships between candidate recipient SNPs, enzyme activity and mRNA expression of the pharmacologic targets of mycophenolate and calcineurin inhibitors. The projects use the genotyping data, which were provided by the Genetics Core, and clinical information, which were collected and entered into the multicenter database by the Clinical Core. Further, biostatistical support (Clinical Core) and administrative oversight and support (Administrative Core) will facilitate data collection, data entry, and data analyses for both projects. The Administrative Core will also facilitate interaction between Sites, Cores, and Projects.Technical note: Regarding to the study design, all transplant recipients should be unrelated. Given the nature of transplantation, some donors may be related to recipients. The donor-recipient relationships are reported in the demographic file under the "related" column. As we did not collect full pedigree information for the related donor-recipient pairs, we have included a IBD file (calculated using PLINK) with the genotype data.

  Study phs001667