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• Circulating cell-free DNA methylation profiles as noninvasive multiple sclerosis biomarkers: A proof-of-concept study

  In chronic neurodegenerative diseases such as multiple sclerosis (MS), there is a critical unmet need for cost-effective non-invasive blood biomarkers to concurrently classify disease subtypes, monitor disability severity, and predict long-term progression. In this proof-of-concept study, we performed low-coverage whole-genome bisulfite sequencing (WGBS) on 75 plasma cell-free DNA (cfDNA) samples collected from a well-characterized real-world prospective clinic cohort with longitudinal disability outcome measurements. We assessed the clinical utility of cfDNA methylation profile for differentiating MS patients from non-MS controls, classifying MS subtypes, estimating disability severity, and predicting disease trajectories.

  Study EGAS50000001277

• CLUSTER RNAseq Study of Juvenile Idiopathic Arthritis patients in methotrexate cohort

  CLUSTER aims to discover novel disease mechanisms and biomarkers in children suffering from Juvenile idiopathic arthritis (JIA). Currently, little is known about the pathological disease mechanisms of JIA and there are no validated tools capable of predicting response or non-response to treatment. The study aims to identify biomarkers for treatment response using RNAseq technology. The samples used in this study comes from blood samples that were collected prior to patients receiving methotrexate treatment (naive). These samples were then processed for PBMC isolation followed by sorting cells into 4 different immune cell types. All of these samples were then sequenced by NovaSeq6000.

  Study EGAS50000000995

• CLUSTER Read-counts matrix of RNAseq Datasets of JIA in methotrexate cohort

  CLUSTER aims to discover novel disease mechanisms and biomarkers in children suffering from Juvenile idiopathic arthritis (JIA). Currently, little is known about the pathological disease mechanisms of JIA and there are no validated tools capable of predicting response or non-response to treatment. The study aims to identify biomarkers for treatment response using RNAseq technology. The samples used in this study comes from blood samples that were collected prior to patients receiving methotrexate treatment (naive). These samples were then processed for PBMC isolation followed by sorting cells into 4 different immune cell types. All of these samples were then sequenced by NovaSeq6000.

  Study EGAS50000001501

• RNA seq of intestinal biopsies and blood cells from patients with celiac disease and controls

  This study presents RNA sequenced from several intestinal phenotypes such as from patients with damaged intestinal mucosa as well as from those without a damaged intestine but still an autoantibody response to tissue transglutaminase (“potential celiac disease”) or those with treated celiac disease. By combining phenotypes in a much larger number of tissue samples from both peripheral blood and mucosal biopsies, we found highly differentially expressed genes, but also identify genes involved in controlling and triggering celiac disease associated changes. This study identifies molecular mechanisms involved in celiac disease and new possible targets for treatment and for identification of individuals at risk.

  Study EGAS50000001104

• The EGA joins EUCAIM, the European project powering AI and imaging in cancer research

  EUCAIM (EUropean Federation for CAncer IMages) is the cornerstone of the European Cancer Imaging Initiative, one of the flagships of the Europe’s Beating Cancer Plan (EBCP). The European Genome-Phenome Archive (EGA), as member of the EUCAIM consortium, attended the kick-off meeting organized this week in Brussels for the launch of the Initiative. The EGA will contribute to the project with the experience gained in the deployment of our federated network, the Federated EGA (FEGA), and the experience gained as partners of EuCanImage (AI4HI initiative) contributing to the definition of common data models, ontologies and data standards. The ultimate goal of the project is to unlock the power of imaging and Artificial Intelligence for the benefit of cancer patients, clinicians and researchers. The consortium will deploy a pan-European digital federated infrastructure hosting cancer-related images, and associated pathology, molecular and laboratory data from Real-World. This endeavour will provide a comprehensive dashboard for imaging data discovery, federated search, metadata harvesting, annotation and distributed data processing. EUCAIM joins 76 partners, gathering the experience and previous effort made by the different repositories of the AI4HI initiative, European Research Infrastructures and national/regional repositories. Find out more information about the EUCAIM launch here

  Blog the-ega-joins-eucaim

• GCAT | Genomes for life

  The GCAT project is a prospective cohort study that was designed to recruit the general population of Catalonia, the north-east region of Spain. This study is a long-term genomic, environmental and lifestyle cohort project that aims to evaluate and track multiple pathologies as well as biologically related traits. By the end of 2017, the GCAT Study had recruited a total of 20 000 participants aged 40–65 years. Participants who agreed to take part in the study completed a self-administered computer-driven questionnaire, and underwent blood pressure, cardiac frequency and anthropometry measurements. For each participant, blood plasma, blood serum and white blood cells are collected at baseline. The GCAT Study has access to the electronic health records of the Catalan Public Healthcare System. Participants are followed biannually for/during, at least, 20 years after recruitment. Therefore, the GCAT Study offers a unique opportunity to integrate diverse data to allow the identification of novel relations among different biomarkers and conditions. Results may lead to the development of new genetic, genomic, epigenomic and proteomic diagnoses and screening tests, as well as new public health recommendations. The only currently available population-based prospective cohort study in Spain to the date, including more than 4899 genotyped participants and 800 whole genome sequences is now stored in the EGA archive under accession id EGAS00001003018.

  Blog gcat-genomes-for-life

• Chracterising_cellur_pathways_underlying_CD3_CD28_activation_of_human_CD4__cells

  We devised an approach to disentangle the TCR and CD28 pathways upon stimulation in naive and memory primary human CD4+ T cells (Tcons) in response to defined stimulatory signals. Sorted Tcons were activated using a titration of anti-CD3 and anti-CD28 in combination as well as individually. As a control we cultured cells in the same conditions but without the stimuli. In total, we defined seven conditions from four individuals for sequencing. 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/

  Study EGAS00001004147

• 2014_Lung_sq_WES

  Purpose Lung squamous cell carcinoma (SqCC) is the second most prevalent type of lung cancer. Currently, no targeted-therapeutics are approved for treatment of this cancer, largely due to lack of systematic understanding of the molecular parthenogenesis of the disease. To identify therapeutic targets and comparatively analyze them in lung SqCC, we probed somatic alterations of Korean lung SqCC. Patients and Methods We performed massively parallel whole-exome sequencing of 104 Korean lung SqCC patients’ samples with matched normal samples. In addition, copy number analysis and transcriptome analysis were conducted for a subset of these samples. Clinical association with cancer-specific somatic alterations was investigated.

  Study EGAS00001002844

• RNA sequencing of a glioblastoma PDX cohort

  Patient-derived xenograft (PDX) models represent an essential tool for the preclinical evaluation of novel targeted therapies and their combinations. In this project, we molecularly characterized a comprehensive panel of glioma PDX models with well conserved molecular and pathological features over multiple passages. PDX samples were subjected to next generation sequencing (NGS). Characterization of cancer-relevant features including driver mutations or cellular processes was performed using mutational and gene expression data in order to identify potential biomarker or treatment targets in glioblastoma. In summary, we reported a newly established and molecularly characterized panel of glioma PDX models with high relevance for translational preclinical research.

  Study EGAS00001007119

• Deciphering Intratumoral Molecular Heterogeneity in Clear Cell Renal Cell Carcinoma with a Radiogenomics Platform

  Intratumoral heterogeneity (ITH) challenges the molecular characterization of clear cell renal cell Carcinoma (ccRCC) with percutaneous biopsies and is a confounding factor in selection of molecular-targeted versus immune-based therapy. Magnetic Resonance (MR) Imaging can noninvasively assess the spatial landscape of the entire tumor. To validate MRI for ITH assessment, we implemented a radiogenomic platform through a systematic imaging based co-localization approach for multi region tissue acquisition from single tumors. We investigated if the spatial changes in imaging can predict the molecular changes using transcriptome and histopathological correlatives. Our study confirmed imaging heterogeneity as a predictor of molecular heterogeneity in ccRCC.

  Study EGAS00001003846