Search Results - EGA European Genome-Phenome Archive

Molecular risk stratification in patients with T1 colorectal cancer_WES

The introduction of bowel cancer screening has led to a significant increase in the proportion of patients being diagnosed with asymptomatic, early-stage colorectal cancer (CRC). Although the majority of these patients are successfully treated with surgery alone, a small proportion of patients have 'born-to-be-bad' aggressive lesions with early dissemination leading to distant metastases. Current standard of care histological assessment is unable to distinguish between these aggressive versus non-aggressive early lesions which is essential to provide appropriate clinical management decisions. This study aims to carry out molecular and histological profiling of approximately 300 T1 CRCs in order to develop a molecular stratifier based on the risk of relapse in early-invasive CRC. This novel T1 cohort will represent the world's largest molecularly characterised T1 cohort of samples, with digital pathology assessment alongside whole exome sequencing, copy number variation analysis and 3' RNA-seq. This data will be used to generate a robust panel of molecular and/or histological markers applicable to formalin-fixed paraffin embedded (FFPE) archival tissue which discriminates between T1 lesions based on risk of relapse, which will ultimately be used to inform clinical management of CRC at the earliest stages of the disease.

Dataset EGAD00001010890

dbGaP Collection: NHLBI Heart Failure Related dbGaP Data (No IRB requirement)

The National Heart, Lung, and Blood Institute (NHLBI) Big Data Analysis Challenge: Creating New Paradigms for Heart Failure Research has concluded. The NHLBI will continue to make this collection of data available to the research community.Past information regarding the Data Collection for the NHLBI Big Data Analysis Challenge: Creating New Paradigms for Heart Failure Research is below.The National Heart, Lung, and Blood Institute (NHLBI), part of the National Institutes of Health (NIH), is inviting novel Solutions for the NHLBI Big Data Analysis Challenge: Creating New Paradigms for Heart Failure Research. The goal of the challenge is to foster innovation in computational analysis and machine learning approaches utilizing large-scale NHLBI-funded datasets to identify new paradigms in heart failure research. The challenge aims to address the need for new open source disease models that can define sub-categorizations of adult heart failure to serve as a springboard for new research hypotheses and tool development in areas of heart failure research from basic to clinical settings. NHLBI has a history of making considerable investments in the creation of deep data resources including: long-standing, deeply-phenotyped epidemiological cohorts, innovative clinical trials, and large-scale precision medicine efforts that have generated whole genome sequencing and "other omics" data for more than one-hundred thousand individuals. To provide challenge participants with streamlined access to data across NHLBI's numerous studies containing heart failure data, the NHLBI has created this dbGaP study collection. Data access for this collection is controlled by NHLBI's Data Access Committee. Challenge participants are required to follow the use restrictions and acknowledgement instructions from the original dataset(s). Please note that the data in this collection are not harmonized across studies or otherwise altered from the original study. The NHLBI Big Data Analysis Challenge: Heart Failure Data Collection contains all NHLBI studies currently in dbGaP that contain data that may be relevant to research on heart failure. The studies in this collection are approved for General Research Use (GRU), Health/Medical/Biomedical Use (HMB), or Disease-Specific Use (DS) that permits research on heart failure. These studies span a variety of study designs, inclusion and exclusion criteria, sample sizes, and provide a wide breadth and depth of phenotype data on study participants. The available genomic data in these studies also varies, including genotyping arrays, sequencing (targeted, exome, whole genome), and additional -omic data (e.g., RNA or metabolite profiles). Please refer to each study's individual accession page to learn more about how study data were collected. Challenge participants are reminded that in addition to dbGaP, NHLBI's Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC) contains other studies that have collected data relevant to heart failure and may wish to utilize BioLINCC data in the development of their Solution. Please refer to the individual accession page for each study in this collection to learn more about the history of each study.

Study phs001991

GA4GH

Standards The EGA is a long-standing supporter of the Global Alliance for Genomics & Health (GA4GH) to enhance responsible sharing of human genetic data through the development of interoperable global standards for human data access. The EGA is one of the founding GA4GH Driver Projects and has contributed to the development and implementation of several GA4GH standards and APIs. Below is a list of the GA4GH standards and APIs that are currently available or planned for implementation at EGA. TechnicalStandards Purpose SpecificationVersion SupportedVersion Implementation Large Scale Genomics htsget A protocol for secure, efficient, and reliable access to sequencing read and variation data. V1.3.0 V1.0.0 Specification Documentation Endpoint Read File Formats (SAM/BAM/CRAM) Specifications for storing next-generation sequencing read data. V3.0.0 V3.0.0 Implementation Example of Usage Variation File Formats (VCF/BCF) The specifications for Variant Call Format Files (VCF) and its binary counterpart BCF. V4.0.0 V2.0.0 V4.0.0 V2.0.0 Implementation Example of Usage Crypt4GH v1.0 Enables direct byte-level compatible random access to encrypted genetic data stored in community standards (e.g. CRAM, VCF) V1.0 V1.0 Specification Documentation Endpoint refget API Enables access to reference sequences using an identifier derived from the sequence itself. V1.2.6 NA Specification RNAget API v1 Provides a means of retrieving data from several types of RNA experiments including (i) feature-level expression data from RNA-seq type measurements and (ii) coordinate-based signal/intensity data similar to a bigwig representation via a client/server model. V1.0.0 NA Documentation Discovery Beacon v2 Supports discovery of genomic variants, phenotypes, and individuals V1.0.1 V0.3 Web UI API Source Code Service Info API v1 The Service Info API is an endpoint for describing GA4GH service metadata, designed for extension and inclusion in other APIs. Service info is used to describe a single service, while Service Registry is used to describe multiple services. V1.0.0 NA Documentation Service Registry API v1 provides information about other GA4GH services, primarily for the purpose of organizing services into networks or groups and service discovery across organizational boundaries. V1.0.0 NA Documentation Data Use Researcher Identities Data Use Ontology (DUO) Allow users to semantically tag genomic datasets with usage restrictions, allowing them to become automatically discoverable based on a health, clinical, or biomedical researcher’s authorisation level or intended use. 2021-02-23 2021-02-23 Specification Documentation Endpoint Authentication & Authorization Infrastructure (AAI) The GA4GH AAI specification leverages OpenID Connect (OIDC) Servers for use in authenticating the identity of researchers desiring to access clinical and genomic resources from data holders adhering to GA4GH standards, and to enable data holders to obtain security-related attributes of those researchers. V1.2.0 V1.2.0 API URI: ega.ebi.ac.uk:8443 Documentation Repository Researcher IDs (passport, visa) Specify the collection of researchers that may access a dataset at any given time, and the credentials they must supply. V1.0.1 V1.0.1 Specification Documentation Endpoint Cloud Tool Registry Service API TRS is a standard API for exchanging tools and workflows to analyze, read, and manipulate genomic data. V2.0.1 NA Documentation Repostiory Data Repository Service API DRS API is a standard for building data repositories and adapting access tools to work with those repositories, works with other approved APIs from the GA4GH Cloud Work Stream to allow researchers to discover algorithms across different cloud environments and send them to datasets they wish to analyse. V1.0.3 NA Documentation Repostiory Workflow Execution Service API This API lets users run a single workflow (defined using CWL or WDL) on multiple different platforms, clouds, and environments, and be confident that it will work the same way. The API provides methods to request that a workflow be run, pass parameters to that workflow, get information about running workflows, and cancel a running workflow. V1.0.1 NA Documentation Repostiory Genomic Knowledge Standards Variation Representation v1 Provides a flexible framework of computational models, schemas, and algorithms to precisely and consistently exchange genetic variation data across communities. V1.3.0 EGA team is contributing to including it in in Beacon v2 Specification and Elixir Reference Implementation Documentation Repostiory Clin/ Pheno Data Capture Phenopackets Provides information models with different levels of complexity to enable high level clinical phenotype information as well as deep clinical phenotype information to be exchanged. V2.0.0 Included in Ongoing Submissions EGA team is contributing to including it in in Beacon v2 Specification and Elixir Reference Implementation Documentation Repostiory Driver Project The EGA, jointly coordinated by the EBI and the CRG, was announced, in 2017, to be one of the 15 Driver Projects for GA4GH. Driver Projects are international genomic data initiatives, focussed on real projects and challenges that will guide the development efforts in order to accelerate and enable completely responsible and standarised data sharing by 2022. All chosen Driver Projects make a cross-sectional effort by playing an important role across the different workstreams. Thomas Keane, Jordi Rambla, Mallory Freeberg, and Aina Jené have been named Driver Project Champions for the EGA. All Driver Project Champions will be leading this ambitious initiative for the following years.

Documentation about/projects-and-funders/ga4gh

RNA-sequencing of tumors from 45 patients with recurrent or metastatic gastric cancer treated with immune checkpoint inhibitors

Genomic profiling can provide prognostic and predictive information to guide clinical care. Biomarkers that reliably predict patient response to chemotherapy and immune checkpoint inhibition in gastric cancer are lacking. In this work, we used our machine learning algorithm NTriPath to identify a gastric-cancer specific 32-gene signature. Using unsupervised clustering on expression levels of these 32 genes in tumors from 567 patients, we identified four molecular subtypes that were prognostic for survival. We then built a support vector machine with linear kernel and the binary classifier to generate a risk score that is prognostic for 5-year overall survival and validated the risk score using three independent datasets. We also found that the molecular subtypes predicted response to adjuvant 5-fluorouracil and platinum after gastrectomy and immune checkpoint inhibitors in patients with metastatic or recurrent disease. The 32-gene signature is a promising prognostic and predictive biomarker to guide the clinical care of gastric cancer patients and should be validated in a prospective manner. This EGA archive includes both St.Mary hospital cohort samples (n=28) and Yonsei immunotherapy patient samples (n=17).

Study EGAS00001005588

Cryptococcosis in Previously Healthy Adults

Cryptococcus is a fungus that causes infections most commonly in immunocompromised patients, such as those with AIDS and solid organ transplant recipients and is currently responsible for an estimated 15% of all AIDS-related deaths globally. However, in developed countries, approximately one-third of cases fall outside these groups such that cryptococcal meningoencephalitis (CM) has become the most common cause of non-viral meningitis in the U.S. Within the U.S., approximately 15-20% have no readily identifiable immune defect and cryptococcal infection in these hosts has a mortality rate of 30-50% despite optimal antifungal therapy. NIH Clinical Study Protocol 93-I-0106 (NCT00001352). The objectives of this protocol can be broadly categorized as: 1) Characterize the immunologic and genetic mechanisms predisposing to disease acquisition; 2) Understand the post-infectious inflammatory response and distinguish its consequences from those directly due to fungal growth; and 3) Management of post-infectious neuro-inflammatory syndromes associated with cryptococcal meningitis (CM). This protocol recruits patients who have microbiological evidence of cryptococcal neurologic or non-CNS disease (typically pulmonary or bone). Cerebrospinal fluid (CSF) and blood samples collected during clinical care are used to measure serum and CNS cellular and soluble cytokines as well as to perform in-situ immunohistochemistry. CSF and blood samples are also collected to measure transcriptional (gene expression), proteomic (protein), and lipidomic (lipids) changes that occur throughout disease and treatment. Observational data detailing audiological, ophthalmological and neurocognitive deficits in these patients is also recorded. We have recently described a post-infectious inflammatory syndrome (PIIRS) associated with cryptococcal meningoencephalitis (CM) which can be best described as a neuro-inflammatory state during which CM patients present with altered mental status (Montreal Cognitive Assessment Score As part of the protocol, we treat patients for either microbiological failure or neuroinflammatory sequelae by conventional therapies utilizing FDA-approved pharmaceuticals at FDA-approved doses. To understand and identify the predominant biological pathways responsible for PIIRS neuroinflammation, we examined patient CSF at baseline (at time of PIIRS diagnosis) and post-treatment with different FDA-approved pharmaceuticals at FDA-approved doses compared to CSF from non-PIIRS donors. Upstream pathway analysis of differentially expressed genes in the CSF of PIIRS patients revealed a prominent role for the JAK/STAT pathway in the pathogenesis of PIIRS and support the use of the JAK inhibitor, ruxolinib, as a pathway-instructed therapy to treat PIIRS patients. Data available through dbGaP: single cell RNA sequencing (scRNA-seq) data from CSF cells of a patient with PIIRS at the time of diagnosis and following treatment with steroids (1g solumedrol/day) and NanoString transcriptional data from CSF cells of patients with PIIRS at the time of diagnosis compared to CSF cells from non-PIIRS donors.

Study phs003871

Single-cell RNA sequencing reveals the mesangial identity and species diversity of glomerular cell transcriptomes

Molecular characterization of the individual cell types in human kidney as well as model organisms are critical in defining organ function and understanding translational aspects of biomedical research. Previous studies have uncovered gene expression profiles of several kidney glomerular cell types, however, important cells, including mesangial (MCs) and glomerular parietal epithelial cells (PECs), were missing or incompletely described, and a systematic comparison between mouse and human kidney is lacking. To this end, we used Smart-seq2 to profile 4332 individual glomerulus-associated cells isolated from human living donor renal biopsies and mouse kidney. The analysis revealed genetic programs for all four glomerular cell types (podocytes, glomerular endothelial cells, MCs and PECs) as well as rare glomerulus-associated macula densa cells (MDCs). Importantly, we detected heterogeneity in glomerulus-associated Pdgfrb-expressing cells, including bona fide intraglomerular MCs with the functionally active phagocytic molecular machinery, as well as a unique mural cell type located in the central stalk region of the glomerulus tuft. Furthermore, we observed remarkable species differences in the individual gene expression profiles of defined glomerular cell types that highlight translational challenges in the field and provide a guide to design translational studies.

Study EGAS00001004943

Re-Evaluation of Systemic Early Neuromuscular Blockade

This study of the ROSE trial data explored two distinct molecular subtypes of ARDS (Acute Respiratory Distress Syndrome) to better understand the disease's complexity and potential for personalized treatment. Previous studies had identified different inflammatory profiles in ARDS patients, with this research addressing three key questions: Can these molecular subtypes be consistently identified in a more severe group of ARDS patients? Do these subtypes respond differently to neuromuscular blockade treatment? What specific biological processes differentiate these inflammatory profiles? Advanced transcriptomic and protein analyses examined blood samples from ARDS patients. Analysis of these data revealed two main molecular phenotypes: Hypoinflammatory phenotype (60.4% of patients) Hyperinflammatory phenotype (39.6% of patients) Key findings demonstrated that the hyperinflammatory subtype was associated with:Significantly higher mortality rates relative to hypoinflammatory (61.6% vs. 30.3%)Significantly higher mortality rates relative to hypoinflammatory (61.6% vs. 30.3%)Distinct gene expression patterns related to immune responseUnique changes in genes associated with tissue remodeling and cellular processes Notably, the neuromuscular blockade treatment showed no difference in effects across these subtypes. Complex relationships emerged between gene expression and protein levels, with some genes closely matching their protein counterparts and others displaying more variable connections. The study concludes that these molecular phenotypes possess distinct clinical, protein, and genetic characteristics, suggesting potential for more precise, personalized approaches to ARDS treatment in the future.

Study phs003929

Exome and RNA sequencing of relapsed TCF3-PBX1 t(1;19) acute lymphoblastic leukemia

TCF3-PBX1 (E2A-PBX1) is a recurrent gene fusion in B-cell precursor lymphoblastic leukemia (BCP-ALL), which is caused by the translocation t(1;19)(q23;p13). TCF3-PBX1 BCP-ALL patients typically benefit from chemotherapy; however, many relapse and subsequently develop resistant disease with few effective treatment options. Mechanisms driving disease progression and therapy resistance have not been studied in TCF3-PBX1 BCP-ALL. Here, we aimed to identify novel treatment options for TCF3-PBX1 BCP-ALL by profiling leukemia cells from a relapsed patient, and determine molecular mechanisms underlying disease pathogenesis and progression. By drug sensitivity testing of leukemic blasts from the index patient, control samples and TCF3-PBX1 positive and negative BCP-ALL cell lines, we identified the phosphatidylinositide 3-kinase delta (p110δ) inhibitor idelalisib as an effective treatment for TCF3-PBX1 BCP-ALL. This was further supported by evidence showing TCF3-PBX1 directly regulates expression of PIK3CD, the gene encoding p110δ. Other somatic mutations to TP53 and MTOR, as well as aberrant expression of CXCR4, may influence additional drug sensitivities specific to the index patient and accompanied progression of the disease. Our results suggest that idelalisib is a promising treatment option for patients with TCF3-PBX1 BCP-ALL while other drugs could be useful depending on the genetic context of individual patients.

Study EGAS00001001876

Raw sequencing files from WGS and RNA-Seq

Acute leukemias are the most common malignancies in children with an onset of the disease among 0-6 years-old. The early development of theses malignancies has been proposed as an indicator of their prenatal origin, hypothesis that has been confirmed especially in the case of acute lymphoblastic leukemia. For acute myeloid leukemia (AML), comprising an heterogenous group of different cytogenetics subtypes, this prenatal origin has also been confirmed specially for MLL-rearranged and t(8;21) subgroups. AMLs carrying t(7;12) constitute up to 30% of cases under 2-years-old, frequently being associated with a trisomy of chromosome 19 and an overexpression of MNX1 gene. An in utero origin of this specific subgroup has been suggested but not clearly confirmed. Here, we present the case of a 5-months-old AML patient with t(7;12) in which we have fully characterized a novel breakpoint occurring among ETV6 and NOM1 genes. We demonstrate the presence of this specific ETV6-NOM1 fusion in CD34+ hematopoietic stem and progenitor cells isolated from the cord blood unit from the same patient and stored at birth. Moreover, trisomy +19 present at diagnosis was not detected at birth. Together, our results demonstrate the prenatal origin of the t(7;12) in infant AML, and establish trisomy +19 as a secondary event in this leukemia.

Study EGAS50000000186

A Platform Study of Combination Immunotherapy for the Neoadjuvant and Adjuvant Treatment of Patients with Surgically Resectable Adenocarcinoma of the Pancreas

This is a single-institutional, randomized, open label platform clinical trial testing various immunotherapy combinations. Patients with newly diagnosed and surgically resectable pancreatic ductal adenocarcinoma (PDA) and scheduled to undergo the Whipple procedure at Johns Hopkins Hospital were eligible to participate in this study. Criteria for determining resectability strictly followed National Comprehensive Cancer Network (NCCN) guidelines. The study consisted of 6 parts: parts 1-5 constituted the Prime Phase (see below), and part 6 was the Extended Treatment Phase. Part 1: Participants received one cycle of immunotherapy two weeks prior to undergoing the Whipple procedure. Part 2: Subjects underwent the Whipple procedure. Part 3: Subjects received a second cycle of immunotherapy 4-10 weeks following the Whipple procedure (2-4 weeks prior to adjuvant chemoradiation). Part 4: Subjects underwent chemoradiation. Part 5: Subjects received 4 additional 28-day cycles of immunotherapy beginning 1-2 months after completing chemoradiation for a total of six cycles (two before chemoradiation and 4 following chemoradiation). Eligible subjects were randomized to Arms A and B in a 1:1 ratio, stratified up-front by age (≤65, >65). Arm A participants received Cy/GVAX. Arm B participants received the combination of Cy/GVAX and nivolumab. GVAX Vaccine consists of equal numbers (2.5 x 108 each) of Panc 6.03 pcDNA1GM-CSF and Panc 10.05 pcDNA1GM-CSF combined into a single vaccination. Each vaccination consisted of six total intradermal injections. A single intravenous (IV) dose of 200 mg/m2 Cy (CytoxanR) was given one day prior to GVAX. Anti-PD-1 Therapeutic Antibody Nivolumab 480 mg every 4 weeks was administered as an intravenous infusion. The primary objective for Arms A and B was to compare IL17 expression (Th17) in vaccine-induced lymphoid aggregates between resected PDAs from patients treated with the combination of Cy/GVAX and anti-PD-1 blockade antibody vs. the treatment of Cy/GVAX alone. Secondary objectives were to assess the safety, overall survival (OS), and disease free survival (DFS) of patients treated with each of the study drug combinations, and to assess the effects of each of the immunotherapy study drug combinations on PD-L1/PD-1 associated pathways, vaccine-induced immune regulatory signatures, and peripheral and intratumoral antigen specific T cell responses. The exploratory objective was to explore the effects of therapy on tumor and peripheral blood and tumor infiltrating immune cells, and to explore potential molecular determinants of response, progression and disease stability. To these ends, tumor infiltrating immune cells (TIICs) were obtained from surgically resected tumors following the neoadjuvant treatment of the study immunotherapy. TIICs were sorted into CD3+CD4+ T cells, CD3+CD8+ T cells, CD3-CD19+ B cells, and CD3-CD19-CD11b+ myeloid cells by flow cytometry. The sorted immune cell subtype pellets were sent to the commercial vendor (Eurofins) for RNA extraction and sequencing. SMART-seq v4 Ultra Low Input mRNA Sample Prep Kit was used for library preparation with 100bp paired end reads. FASTQ files, that were returned from the vendor, are deposited here.

Study phs003002

3883 results for "RNA AND sequencing OR transcriptome"

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