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• Starting Treatment with Agonist Replacement Therapies (START): A Randomized Trial of Methadone vs Buprenorphine/Naloxone for the Treatment of Opioid Dependence

  The Starting Treatment with Agonist Replacement Therapy (START) study was a 24-week, open-label, randomized trial of methadone versus Suboxone (buprenorphine/naloxone) for the treatment of opioid dependence. Patients were over the age of 18 and met DSM-IV qualifications for opioid dependence. The primary goal of the study was to determine if either medicine was associated with liver toxicity issues in this vulnerable patient population. Liver enzymes were measured at four time points. Urinalysis for opioids, cocaine, cannabis, benzodiazepines, and methamphetamine were performed on a weekly basis. A flexible dosing scheme was used during which physicians could alter medication dose based on withdrawal symptoms and urinalysis results. Neither medication was found to be associated with liver enzyme levels. In version 2 of this study, a text file containing 7704 SNPs with large allele frequency discrepancy as compared to 1000 Genomes is included. Users have the option to exlude these 7704 SNPs.

  Study phs001135

• Epigenetic landscape reorganization and reactivation of embryonic development genes are associated with malignancy in IDH-mutant astrocytoma

  Accurate grading of IDH-mutant gliomas is crucial for determining patient prognosis and guiding treatment decisions. However, histological grading can be challenging, so we aimed to identify objective molecular markers. To this end, we conducted bulk RNA sequencing on primary IDH-mutant astrocytomas (n=138) from the prospective CATNON trial, which evaluated the prognostic impact of adjuvant and concurrent temozolomide. Using this data, we sought to identify molecular markers linked to increased malignancy in IDH-mutant astrocytomas to establish objective grading criteria.

  Study EGAS50000000381

• Whole Genome Sequencing of HCC

  The present series corresponds to 24 whole genome sequencing (12 Tumoral/Non-tumoral pairs). Hepatocellular carcinoma (HCC) accounts for more than 90% of liver cancers, and is a major health problem. It is the 3rd cause of cancer-related mortality. Advances in genomic analyses have formed a comprehensive understanding of different underlying pathobiological layers resulting in hepatocarcinogenesis. Thus, the development of next-generation sequencing technologies has made it possible to generate more comprehensive catalogues of somatic alteration events (single nucleotide substitutions, structural variations, and epigenetic changes) in liver cancer genome than ever before.

  Dataset EGAD00001003994

• ICU transcriptomics: Assessing the role of the host immune response in patients with ventilator-associated pneumonia

  This is a study of 100 patients with the aim to provide transcriptomic sequencing data analysis of cells isolated from bronchioalveolar lavage and blood samples from critically ill patients with pneumonia on an intensive care unit in order to investigate the host contribution to disease. 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/

  Dataset EGAD00001015407

• Omic Studies in Children's Respiratory and Environmental Workgroup (CREW) Cohorts

  Children's Respiratory Research Workgroup (CREW) is an NIH-funded project consisting of multiple individual U.S. cohorts and three scientific centers working together to identify phenotypes and causes of childhood asthma. CREW will include data from a large number of children and their families, with broad diversity in terms of ethnicity, family characteristics, neighborhoods and geographic locations. One of the primary goals of CREW is to put together sets of data and samples of participating cohorts to identify phenotypes of childhood asthma (i.e. specific subtypes of asthma that can be distinguished by clinical features such as natural history, triggers, exacerbation frequency, concurrent allergies, lung function, sex, etc). Omics studies will include genotyping, methylation, and RNA sequencing. By integrating the DNA genotyping with the expression, immunologic and clinical data, we will identify eQTL, inflammation QTL, and lung function QTL, as well as QTL associated with other biomarkers. Analyses will identify genetic, epigenetic, transcriptional and protein/metabolite profiles that are associated with specific exposures or phenotypes. As we obtain mechanistic insights about personal and early life risk factors, we will connect asthma phenotypes with underlying causes and pathogenic mechanisms to define endotypes of childhood asthma.

  Study phs004036

• Genotyping_data_total

  Genotyping data for ACE2 (rs2285666), MX1 (rs469390) and TMPRSS2 (rs2070788) variants. Patients are classified as mild (n=34) and severe (n=32). DNA genotyping was performed using the TaqMan® Genotyping Master Mix (Applied Biosystems). Allelic discrimination assays were performed on a 7900HT Fast Real-Time PCR System (Applied Biosystems).

  Dataset EGAD00010002445

• Sorted WGS for three samples

  This dataset contains Whole Genome Sequencing (WGS) data from two cell populations (myeloid and lymphoid) and the germline population sorted from a primary sample of the novel FOXF1/FENDRR ALL subtype. All the three samples are in bam file type.

  Dataset EGAD50000001792

• Cancer Single Cell Sequencing

  This study is to ascertain whether it is feasible to extract a single cell form a Cancer cell line, amplify it and sequence it.

  Study EGAS00001000003

• University of Michigan Clinical Sequencing Exploratory Research (CSER)

  Overview. The personalization of therapy for cancer will require molecular characterization of unique and shared genetic aberrations. In particular, patients who have a sarcoma or other rare cancers and are candidates for clinical trials could potentially benefit by identifying eligibility for "targeted" drugs based on the "actionable" genes in their specific tumor. Growing technological advances in genomic sequencing has now made it possible to consider the use of sequence data in a clinical setting. For instance, comprehensive testing that includes whole exome and transcriptome sequencing may identify biomarkers for predictive or prognostic purposes and thereby inform treatment choices and prevention strategies. Thus, the translation of high throughput next generation sequencing would support a "personalized" strategy for cancer. However, the translation of clinical sequencing bears unique challenges including identifying patients who could benefit, developing informed consent and human subjects protections, outlining measurable outcomes, interpreting what results should be reported and validated, and how results should be reported. In addition, we know very little about how patients and clinicians will respond to the potentially confusing and overwhelming amount of information generated by genomic sequencing, and we lack model processes for clinically evaluating and presenting these data. For the promise of our innovative biotechnologies to be realized, "translational genomics" research that evaluates genomic applications within real-world clinical settings will be required. This proposal brings together expertise at the University of Michigan including clinical oncology, cancer genetics, genomic science/bioinformatics, clinical pathology, social and behavioral sciences, and bioethics in order to implement this clinical cancer sequencing project. Three integrated Projects have the following themes: Project 1) "Clinical Genomic Study" will identify patients with a rare cancer (i.e., 15 out of 100,000 individuals per year) who are eligible for clinical trials, consent them to the study, obtain biospecimens (tumor tissue, germline tissue), store clinical data, and assemble a multi-disciplinary Sequencing Tumor Board to deliberate on return of actionable or incidental genomic results; Project 2) "Sequencing & Analysis" will process biospecimens and perform comprehensive sequencing and analysis of tumors to identify point mutations, copy number changes, rearrangements/gene fusions, and aberrant gene expression; Project 3) "Ethics & Psychosocial Analysis" will observe the expert review process for evaluating sequence results and will examine the clinician and patient response to the informed consent process, delivery of genomic sequence results, and use of genomic results.

  Study phs000673

• Base modification analysis using single molecule real-time sequencing

  This dataset was generated using single-molecule real-time sequencing for both training and testing purposes. The DNA samples isolated from human buffy coats or placenta of healthy individuals (n=4,) were prepared in a way that four types of base modifications were incorporated, including unmodified controls, 5mC, 5hmC, and 6mA. The sequence data for each sample consists of subreads produced by single-molecule real-time sequencing and stored in a bam format. Details of the specific experiments conducted in this study are outlined in our manuscript.

  Dataset EGAD50000000541

• fibroblast RNAseq from a GINS3 patient and two parents

  RNA-seq was performed from 3 separate GINS3 patient fibroblast cultures and 1 replicate of fibroblasts derived from each of the two parents. RNA-seq libraries were generated with NEBNext Ultra II Directional RNA library prep for Illumina with NEBNext Poly(A) mRNA Magnetic Isolation Module (New England Biolabs) and sequenced on Illumina NextSeq500 with paired-end 150 bp read length. SIRV Set 3 (Lexogen) spike-ins were added. Two fastq files are provided for each RNAseq sample.

  Dataset EGAD00001008571

• Pharmacogenomics of Mercaptopurine Intolerance in Children with Acute Lymphoblastic Leukemia (AALL03N1)

  Mercaptopurine (MP) is the mainstay of curative therapy for acute lymphoblastic leukemia (ALL). We performed a genome-wide association study (GWAS) to comprehensively identify the genetic basis of MP intolerance in children with ALL in AALL03N1. MP dose intensity was defined as prescribed dose divided by the planned protocol dose during maintenance therapy.  Germline variants in NUDT15 and TPMT were found to be strongly associated with MP intolerance in childhood ALL, which may have implications for treatment individualization in this disease.

  Study phs002846

• Solve-RD Solving the Unsolved Rare Dieseases

  Solve-RD – solving the unsolved rare diseases is a research project funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 779257 from 1 January 2018 to 31 March 2024. Six European Reference Networks (ERNs; ERN-RND, -ITHACA, -EuroNMD, -GENTURIS, -RITA and -EpiCare) contributed data and samples to one or more of the four cohorts for data re-analysis and novel omics. For more information see https://solve-rd.eu/results/solve-rd-data/.

  Study EGAS00001003851

• A first-in-human clinical study of an allogenic iPSC-derived corneal endothelial cell substitute transplantation for bullous keratopathy

  iPSC-derived corneal endothelial cell substitutes recover pathological corneal edema. No adverse reactions are observed after one year follow-up. Gene mutations may appear despite whole genome sequencing of the master cell bank. This study contains the RNA-seq data.

  Study EGAS50000000673

• Discover Cancer Image Europe, the first release of the EUCAIM platform to fuel cancer research and data sharing

  The EUCAIM consortium and the European Commission have announced the release of Cancer Image Europe, a platform to fuel collaborative innovation and data sharing across Europe. This constitutes a major milestone in EUCAIM's development and an exciting step towards achieving the project's vision and goals. The platform aims to accelerate the pace of AI development and other data-intensive cancer research activities, constituting the basis for a fully-fledged infrastructure for sharing, reusing, and exploiting cancer imaging data, especially using AI techniques. A platform paving the way for the future of cancer diagnosis and treatment Cancer Image Europe brings benefits to researchers, clinicians, and AI innovators across Europe as it addresses the fragmentation of existing cancer image repositories. The platform gathers a public catalogue of cancer imaging datasets from the repositories of the EU-funded AI for Health Imaging projects. A distributed Atlas of Cancer Imaging with over 60 million anonymised cancer image data from over 100,000 patients will be established as part of future updates. The first version of Cancer Image Europe also includes a public catalogue of cancer imaging datasets, a federated searching tool to understand the information available in the federated providers, and full integration with Life Science Login. Moreover, it reuses and adds value to key components of EU-funded research projects and infrastructure in the field of cancer. The Public Catalogue When we talk about data re-use, data discovery is key. The EUCAIM public catalogue is the result of a systematic and collaborative process to which the EGA-CRG has actively contributed. This browsing interface gathers the metadata of the available cancer imaging datasets. This descriptive information will help researchers in their data retrieval. Our contribution to the Public Catalogue comes from our experience gained in the deployment of our federated network, the Federated EGA (FEGA), and as partners in projects such as EuCanImage (AI4HI initiative), in which we worked on the definition of common data models, ontologies and data standards. The EUCAIM Project EUCAIM is a cornerstone of the European Commission-initiated European Cancer Imaging Initiative, a flagship of the Europe's Beating Cancer Plan, which aims to foster innovation and deployment of digital technologies in cancer treatment and care, to achieve more precise and faster clinical decision-making, diagnostics, treatments, and predictive medicine for cancer patients. For more information about the first release of the Cancer Image Europe platform and the EUCAIM project, please visit cancerimage.eu.

  Blog discover-cancer-image-europe

• Collagen Proteostasis in Health and Disease

  This study uses human iPSC-derived cartilage to investigate the effects of the p.Arg719Cys mutation in the COL2A1 gene, which is linked to precocious osteoarthritis. Using a CRISPR-edited isogenic cell line pair, we compared wild-type and mutant cartilage for matrix defects and cellular stress responses. We performed RNA-sequencing and quantitative proteomics to characterize changes in gene expression, protein interactions, and collagen folding.

  Study phs004112

• Analysis of Loose Ends in Cancer Genome Structure

  Short-read sequencing (SRS) forms the basis of our understanding of cancer genome evolution, yet it is widely thought to be inadequate for detecting structural variants (SVs). To understand the nature of cancer SVs missed by SRS, we introduce the concept of "loose ends" - sites of missing rearrangements revealed by balancing copy number (CN) across the genomic intervals and adjacencies of a genome graph.

  Study EGAS00001007324

• Brain transcriptome of hereditary cerebral haemorrhage with amyloidosis–Dutch type (HCHWA-D)

  HCHWA-D is an early onset hereditary form of Cerebral Amyloid Angiopathy (CAA) caused by a point mutation resulting in an amino acid change (NP_000475.1:p.Glu693Gln) in the Amyloid Precursor Protein (APP). Post-mortem brain tissue (9 patients and 9 age-related controls; frontal and occipital cortex) was used for next generation sequencing of RNA (RNA-Seq with ribosomal RNA depletion).

  Study EGAS00001002730

• Intratumoural heterogeneity and immune modulation in lung adenocarcinoma of female smokers and never smokers

  Lung cancer is still the leading cause of cancer death worldwide despite declining smoking prevalence in industrialised countries. Although lung cancer is highly associated with smoking status, a significant proportion of lung cancer cases develop in patients who never smoked, with an observable bias towards female never smokers. A better understanding of lung cancer heterogeneity and immune system involvement during tumour evolution and progression in never smokers is therefore highly warranted. We employed single nucleus transcriptomics of surgical lung adenocarcinoma (LADC) and normal lung tissue samples from patients with or without smoking history. Immune cells as well as fibroblasts and endothelial cells respond to tobacco smoke exposure by inducing a highly inflammatory state in normal lung tissue. In the presence of LADC, we identified differentially expressed transcriptional programmes in macrophages and cancer-associated fibroblasts, providing insight into how the niche favours tumour progression. Within tumours, we distinguished eight subpopulations of neoplastic cells in female smokers and never smokers. Through pseudotemporal ordering, we inferred a trajectory towards two differentiated tumour cell states implicated in cancer progression and invasiveness. A proliferating cell population sustaining tumour growth exhibits differential immune modulating signatures in both patient groups. Our results resolve cellular heterogeneity and immune interactions in LADC, with a special emphasis on female never smokers and implications for the design of therapeutic approaches.

  Study EGAS00001006331

• 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

• Spatial and temporal transcriptome analysis on human skeletal muscle regeneration

  Skeletal muscle carries a unique ability for adaptation as well as regeneration that highly depends on a supportive cellular microenvironment. Here we show that spatial and single-cell transcriptomic analysis in human skeletal muscle is a unique approach to illuminate cellular interactions in the microenvironment.

  Dataset EGAD50000000263

• Paroxysmal_Neurological_Disorders___rare_epilepsies

  We are sequencing the exomes of patients with paroxysmal neurological disorders mainly focusing on migraine and epilepsy. Cases are collected from performance sites of members of EuroEPINOMICS. Most cases have a strong family history. The study sample will include both cases and controls.

  Study EGAS00001000421

• Biomarker Research for Anti EGFR Monoclonal Antibodies by Comprehensive Cancer Genomics

  The purpose of this study is to explore new biomarkers for predicting the effectiveness of an anti-epidermal growth factor receptor (anti-EGFR) antibody in patients with advanced colorectal cancer. The investigation involves analyzing the entire exome, conducting a genome-wide association study (GWAS), and analyzing copy number variations (CNVs) using single nucleotide polymorphism (SNP) arrays. Genetic material from both cancerous and non-cancerous tissues, as well as blood samples from patients who received the antibody treatment, will be used. The goal is to identify genetic mutations and SNPs associated with treatment efficacy and adverse events, and to assess the correlation between their presence and treatment effectiveness using statistical methods.

  Study JGAS000779

• WES of probands in KLB project

  These are the vcf files of exome sequencing of the two probands who were found to harbor mutations in KLB. Sample: EGAN00001564799 is the proband 1; Sample: EGAN00001564800 is the proband 11 in the KLB paper. Exome capture was performed using the SureSelect All Exon capture (Agilent Technologies, Santa Clara, CA USA) and sequenced on the HiSeq2500 (Illumina, San Diego CA USA).

  Dataset EGAD00001003463

• A clinically applicable connectivity signature for glioblastoma includes the tumor network driver CHI3L1

  Tumor microtubes (TMs) connect glioma cells to a network with considerable relevance for tumor progression and therapy resistance. The determination of TM-interconnectivity in individual tumors has been challenging and the impact on patient survival unresolved. Here, a connectivity signature from single-cell RNA-sequenced (scRNA-Seq) xenografted primary glioblastoma (GB) cells has been established using a dye uptake methodology, confirmed with recording of cellular calcium epochs and validated with clinical correlations. Astrocyte-like and mesenchymal-like GB cells have the highest connectivity signature scores in scRNA-sequenced patient-derived xenografts and patient samples. In large GB cohorts, network connectivity correlated with the mesenchymal subtype and dismal patient survival. CHI3L1 has been identified and validated as a robust molecular marker of connectivity with functional relevance. The connectivity signature allows novel insights into brain tumor biology, provides a proof-of-principle that tumor cell TM-connectivity is relevant for patients’ prognosis, and serves as a robust prognostic biomarker.

  Study EGAS00001007611