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• Integrated Personal omics Processing (iPoP) Longitudinal multi-omics profiling of prediabetes

  Type 2 diabetes mellitus (T2D) is a significant health problem. Close to 20 million individuals in the United States have T2D, and 79 million aged 20 years or older are clinically pre-diabetic, with a 5-year conversion rate of 10% to 23% from prediabetes to T2D. In a collaborative effort to systematically understand diabetes and its etiology, the team is comprised of leading experts in research on both the human host as well as the microbiome, as properties of both are likely relevant in T2D development. For a better elucidation of mechanisms of onset and progression of T2D disease, the group is performing a detailed analysis of the biological processes that occur in the microbiome and human host by longitudinal profiling of patients at risk for T2D. Both microbiome and host profiles are being analyzed by state-of-the-art omics platforms, and these large-scale and diverse data sets will be integrated to determine the dynamic pathways that change during the onset and progression of T2D, especially during viral infections and other stresses. This longitudinal study is expected to reveal changes in the microbiome and host at an unprecedented level of detail, and identify molecules and pathways that play important roles in diabetes onset and progression.

  Study phs001719

• The malaria-protective human glycophorin structural variant DUP4 shows somatic mosaicism and association with hemoglobin levels

  Glycophorin A and glycophorin B are red blood cell surface proteins that are both receptors for the parasite Plasmodium falciparum, which is the principal cause of malaria in sub-Saharan Africa. DUP4 is a complex structural genomic variant that carries extra copies of a glycophorin A - glycophorin B fusion gene, and has a dramatic effect on malaria risk by reducing the risk of severe malaria by up to 40% Using fiber-FISH and Illumina sequencing, we validate the structural arrangement of the glycophorin locus in the DUP4 variant, and reveal somatic variation in copy number of the glycophorin A- glycophorin B fusion gene. By developing a simple, specific, PCR-based assay for DUP4 we show the DUP4 variant reaches a frequency of 13% in a malaria-endemic village in south-eastern Tanzania. We genotype a substantial proportion of that village and demonstrate an association of DUP4 genotype with hemoglobin levels, a phenotype related to malaria, using a family-based association test. Taken together, we show that DUP4 is a complex structural variant that may be susceptible to somatic variation, and show that it is associated with a malarial-related phenotype in a non-hospitalizedlongitudinally-followed population.

  Study EGAS00001003239

• The Vaginal Microbiome: Disease, Genetics and the Environment

  The vagina is an interactive interface with the environment, and as such is covered by a protective epithelial surface. This surface is colonized by a biofilm consisting of bacteria and other microorganisms, which through a variety of mechanisms serve to protect the host from invasion by pathogens. Alterations in the normal vaginal microflora; i.e., dysbioses, particularly those associated with bacterial vaginosis, the most common disorder of the female reproductive tract, contribute to risk of sexually transmitted infections, infection by HIV, and are associated with increased risk of adverse pregnancy outcomes including but not limited to spontaneous preterm birth. Physiologic alterations in the host (e.g., menopause and pregnancy), which are beginning to be investigated as potential selective conditions for change in the "normal" vaginal flora, and their impact on disease susceptibility and transmission, remain to be more definitively elucidated. The effects of chronically abnormal physiologic states (e.g., diabetes mellitus) on normal vaginal flora have not been well described or studied. Finally, an almost unexplored area of inquiry is the genetic contribution, including race/ethnicity, to the establishment and maintenance of a "normal" vaginal flora, under normal and physiologically altered circumstances. Our research will shed light on how the vaginal microbiome contributes to adverse obstetrical outcomes and sexually transmitted infections in diverse populations. This project addresses the following questions: First: Do the genes of the host contribute to the composition of the vaginal microbiome? We hypothesize that a woman's genetic composition significantly affects the ability of certain commensal, parasitic and pathogenic microbes to colonize and/or infect the genital tract. Thus, we will compare and quantify the microbial populations inhabiting the vaginas of monozygotic and dizygotic twins from the Mid Atlantic Twin Registry, and, in the process, address the question of whether there is a relationship between the microbiomes of the vagina, mouth and GI tract. Second: What changes in the vaginal microbiome are associated with common physiological perturbations or non-infectious pathological states of the host?We hypothesize that "altered" physiologic (pregnancy, menopause) and pathologic (chronic disease, hysterectomy) conditions, or environmental "exposures" (exogenous hormones, antibiotics, chronic immunosuppressant, smoking; douching) can predictably alter the vaginal microenvironment. These alterations will lead to changes in microbial populations within the vagina. Changes in the microbial populations may have impacts, positive or more likely negative, on the spontaneous and future well-being of the affected individual. We are characterizing the effects of these "altered" physiologic and pathologic conditions, and environmental exposures, on the composition of the vaginal microbiome. Finally, we are examining the impact of the important physiological changes incurred during pregnancy on the composition of the microbiome of the female reproductive tract. Third: What changes in the vaginal microbiome are associated with relevant infectious diseases and conditions? We are testing the hypothesis that infectious diseases predictably alter the vaginal microbiome, and that these changes have an impact on the disease susceptibility, process, and outcome. A predilection for bacterial vaginosis, vaginitis, HIV infection, or other sexually transmitted diseases, is likely associated with a women's vaginal microbial composition. Thus, we will characterize samples from women with a variety of these infectious conditions to determine the contribution of their microbiomes to the disease process and susceptibility. We are addressing these questions using a combination of high throughput 'nextgen' sequencing technologies. Early studies were performed using the Roche 454 FLX and the first generation Illumina Genome Analyzer II instruments and more recently employing Illumina MiSeq and HiSeq 2500 and 4000 platforms, installed in the Genomics Core of the Nucleic Acids Research Facilities at VCU. Thus, segments of the 16S rRNA genes are amplified from the complex samples taken from various target sites in and around the vagina of each study participant. These segments are sequenced and subjected to taxonomic classification protocols to identify and quantify the bacterial taxa present in each sample. Additionally, total DNA isolated from these samples are subjected to shotgun sequence analysis to empirically reconstruct the metabolic potential of these microbiomes. Finally, specific bacterial clones are completely sequenced and analyzed to associate the unavoidable strain and isolate diversity with the clinical phenotypes presented.

  Study phs000256

• National Cancer Institute (NCI) Head and Neck Cancer Study

  Head and neck cancers have well-documented associations with tobacco and alcohol exposure, but the disease develops in only a small fraction of users, which implies an important role for genetic susceptibility. Therefore, head and neck cancers are an excellent model for studying genetic susceptibility to environmental carcinogens. The primary goal of this study is to perform a comprehensive two-stage, high-density, genome-wide single-nucleotide polymorphism (SNP) analysis of head and neck cancer cases and corresponding frequency matched controls to identify novel genetic risk factors for head and neck cancer. In the study, we genotyped 2242 head and neck cancer cases and 1198 controls using Illumina HumanOmniExpress-12v1 BeadChip.

  Study phs001173

• PGRN-Leducq: Identification of the KCNE1 D85N Polymorphism as a Possible Modulator of Drug-Induced Torsades de Pointes

  The goal of this study was to search for genetic variants that could be responsible for modifying the risk of drug-induced long QT syndrome (diLQTS). diLQTS is a relatively common adverse drug event and has been a leading cause for drug relabeling and withdrawal from the market. Our hypothesis, that variants in genes which regulate electrical properties in the heart modify the risk of diLQTS, was tested by genotyping patients of European descent at 1424 single nucleotide polymorphisms (SNPs) in 18 candidate genes. We found that the SNP KCNE1 D85N was highly predictive of diLQTS with an odds ratio of 9.0 (95% confidence interval: 3.5-22.9).

  Study phs000617

• Genetics of Lymphatic Anomalies from Center of Applied Genomics (CAG) at CHOP

  Lymphatic anomaly, a rare and devastating disease spectrum of mostly unknown etiologies, is characterized by diffuse or multicentric proliferation of dilated lymphatic vessels, and includes a variety of diagnoses: lymphangiectasia, central conducting lymphatic anomaly, generalized lymphatic anomaly, kaposiform lymphangiomatosis, and Gorham Stout disease. Currently, most treatments are considered palliative; lymphatic anomalies are often chronic debilitating conditions that require multiple yearly outpatient visits and hospital admissions for procedures that ameliorate symptoms, but do not correct the underlying cause. Identifying the causal genes will be hugely informative for our understanding of diseases. This will also allow for the development of affordable and successful diagnostic tests and therapies in keeping with "precision medicine" implementation.

  Study phs001802

• Longitudinal Study of the Porphyrias

  This is an observational, longitudinal study of approximately 800 individuals with various types of porphyria. Those participants will be evaluated annually for 5 years, or longer if they agree. Participation in this project will include: Participating in annual visits or contacts. Providing samples, including blood, buccal cells (cells from inside of the mouth), saliva, and urine. The type of samples and amounts may vary from person to person, depending on the type of porphyria. Giving permission for samples to be stored and used for porphyrias research. Granting permission to obtain your medical records. Providing information about your medical history and family history. Completing a questionnaire about your porphyria symptoms and quality of life.

  Study phs001278

• The Diabetes Heart Study (DHS)

  The Diabetes Heart Study is a family based study enriched for type 2 diabetes (T2D). The cohort included 1220 self-reported European Americans from 475 families (Bowden et al 2010 Review of Diabetic Studies 7:188-201: PMID: 21409311; Bowden et al 2008 Annals of Human Genetics 72:598-601 PMID: 18460048) and included siblings concordant for T2D; where possible unaffected siblings were also recruited. The cohort was recruited between 1998 and 2006. Participants were extensively phenotyped for measures of subclinical CVD and other known CVD risk factors. Primary outcomes were quantified burden of vascular calcified plaque in the coronary artery, carotid artery and abdominal aorta all determined from non-contrast computed tomography scans.

  Study phs001012

• Comparison of WGBS, EPIC array, EM-seq, and Nanopore sequencing in assessing DNA methylation marks

  Bisulfite sequencing has long been the default method for analyzing methylation marks due to its single base resolution. However, the associated DNA degradation poses a concern for fragmented samples. Although several methods have been proposed to circumvent this issue, there has yet to be a clear consensus on which method is best suited for detecting methylation. We present an overview of the two mostly used and two alternative approaches: whole-genome bisulfite sequencing (WGBS), Illumina methylation microarray (EPIC), Enzymatic Methyl-sequencing (EM-seq) and third-generation sequencing by Oxford Nanopore Technologies (ONT). We evaluated DNA methylation levels in three human genomes derived from tissue, cell line, and whole blood.

  Study EGAS00001008014

• bulk RNAseq analysis of tumor from 3 non-muscle-invasive bladder cancer patients

  We performed screenings of patient-specific neo-epitopes by tumor-infiltrating CD8+ T lymphocytes of 4 non-muscle invasive bladder cancer patients. After the tumor resection, these patients went on to receive BCG treatment as they had high-risk disease. In order to select the neo-epitopes, we performed bulk RNAseq of the bladder tumor to select the mutated genes that were expressed in the tumor (TPM >1). For patient UC2, 3 different tumors were resected at the same time and RNA from these 3 tumors were sent separately for RNAseq. For patient UC4, no RNA was available, so this patient is not included in this study.

  Study EGAS50000001383

• TRACERx 100: RRBS data from a subset of the first 100 TRACERx tumours

  TRACERx (TRAcking Cancer Evolution through therapy (Rx)) is a prospective cohort study designed to investigate intratumor heterogeneity (ITH) in relation to clinical outcome, and to determine the clonal nature of driver events and evolutionary processes in early stage non-small cell lung cancer (NSCLC). This study looks at multi-region RRBS data from the TRACERx100 cohort selected for quantity of material available and high tumour purity. RRBS data was collected for 122 tumour regions across 36 patients each with matched normal. A subset of this cohort was used in a sister study looking at tumour neo-antigen promoter methylation status in NSCLC (71 tumour regions across 28 patients for a total of 99 samples).

  Study EGAS00001003484

• Dataset Rdata segmentations

  This data set contains an .Rdata file for all the processed segmentation profiles from 81 lpWGS samples included used in downstream analyses from Github repository Evo_history_CACRC. Lastly, there is an .Rdata object with 50 segmentations for 50 total samples from 25 sporadic SNP adenomas used in the comparison with colitis samples.

  Dataset EGAD00010001586

• DAC for EGA study: Multi-omic analyses from a randomized phase II study of epigenetic priming followed by nivolumab in previously treated metastatic non-small cell lung cancer

  This is the Data Access Committee for the EGA study: Multi-omic analyses from a randomized phase II study of epigenetic priming followed by nivolumab in previously treated metastatic non-small cell lung cancer (temp ID 800).

  Dac EGAC50000000563

• Characterization of iPSC derived macrophages - cardiovascular pilot (2017-05-24)

  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/ This dataset contains all the data available for this study on 2017-05-24.

  Dataset EGAD00001003347

• Genome-Wide Association Studies of Prematurity and Its Complications

  Preterm labor resulting in the delivery of a premature child is a complex problem with an enormous impact on individuals, families and society. An estimated 500,000 children are born prematurely in the U.S. each year, and 5 million worldwide die annually of prematurity and its complications. Prematurity is also the single largest contributor to disability-adjusted life years, a measure of the lifetime impact of a disease. Despite the importance of the problem and its disproportionate occurrence in poor and minority populations, its underlying etiology (or etiologies) remains unknown; the single best predictor for preterm delivery is a previous preterm birth. The largest single cause of prematurity is spontaneous preterm labor, and suspected triggers for this include infection, stress, poor nutrition and genetic factors. Family and twin studies provide strong evidence that genetic factors underlie about 40% of the risk for prematurity. A major challenge in studying genetic factors in prematurity is maternal/uterine factors, fetal/placental factors, or both may influence risk. Thus, any approach to studying preterm birth should account for both infant and maternal risk, environmental covariates and interactions. The Danish National Birth Cohort (DNBC) is a well-established, prospective cohort that enrolled women early in pregnancy, prior to any adverse pregnancy outcomes, to minimize bias in data collection and sampling. See details at: http://www.ssi.dk/English. The DNBC followed over 100,000 pregnancies beginning in the first trimester and has extensive biological material and epidemiologic data on health outcomes in both mother and child. The current study posted on dbGaP contains data from a genome-wide case/control study using approximately 1,000 preterm mother-child pairs from the DNBC most with spontaneous onset of labor or preterm premature rupture of membranes (PPROM), along with 1,000 control pairs where the child was born at ~40 weeks' gestation. After data cleaning some small changes in case/control status and other variables resulted in minor changes in numbers of cases or controls in certain categories. Environmental variables are being used as covariates in the analysis. To replicate positive findings, we are using additional mother-child pairs from the DNBC and from the general Danish population, as well as 2200 samples coming primarily from an African-American population known to have high rates of preterm labor and delivery. This group includes over 1000 mostly very low birthweight infants, over 500 infant term controls, 326 term mother/baby pairs and 180 preterm mother/baby pairs. The data from these additional cohorts will be available in separate dbGaP postings. The study is expected to yield a better understanding of the biology of parturition, identify common genetic factors that play a role in preterm birth and its complications and suggest environmental modifications that can prolong gestation, with the goal of improving both neonatal and adult outcomes. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to prematurity and its complications through large-scale genome-wide association studies of a well-characterized cohort of Danish mothers and babies. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.

  Study phs000103

• Catalogue Statistics

  EGA Statistics Bibliography Growth Community Archive Distribution Catalogue What is in the EGA? The European Genome-phenome Archive (EGA) overview The EGA archives and distributes the results of several types of studies. Such studies include genome-wide association studies (GWAS), different purpose sequencing and molecular diagnosis assays among others. Moreover, these studies target many different kind of diseases from cancer to neurodegenerative alterations. We summarised all this data in the charts below. The statistics are computed daily based on an updated list of studies. Each pie chart depicts a different aspect of the studies: which disease type was studied, which type of sampling method was used and what was the scope of the genomic analysis. Number of studies per disease type Studies in the EGA by disease barHorizontalChart('disease-graph', 'https://stats.ega-archive.org/catalog/by_disease') Number of studies per technology type Studies in the EGA by technology barHorizontalChart('technology-graph', '/stats/studies/technology', 'Include dbGaP') Number of studies per sample type Studies in the EGA by samples barChart('samples-graph', '/stats/studies/sample-types', 'Include dbGaP')

  Documentation about/statistics/catalogue

• Exploring the Microbiome-Gut-Brain Axis with Respect to Psychoneurological Symptoms for Children with Solid Tumors

  The human body hosts tens of trillions of microbes, a number 10 times greater than the number of human body cells. The collection of these human-associated microbes and their genomes is called the “human microbiome”. More than 90% of these microbes live in the gastrointestinal (GI) tract, representing 500 species on average. With the development of high-throughput sequencing technology and bioinformatics tools (e.g., 16S ribosomal RNA or 16S rRNA sequencing and shotgun metagenomics analysis), recent progress has been made to elaborate the critical role that the gut microbiome plays in human health and disease. A significant disruption (dysbiosis) of the composition and function of the gut microbiome is associated with carcinogenesis, chemotherapeutic metabolism, and treatment-related symptom toxicities. The current state of science on the gut microbiome in cancer has only recently started in animal models and adults, and has not been well investigated in children diagnosed and treated for cancer, nor with respect to associations with cancer treatment-related toxicities. This proposed study will explore the hypothesis that dysbiosis of the gut microbiome is associated with cancer treatment-related GI and psychoneurological symptoms. We will collect both stool samples (for the gut microbiome) and patient-reported outcomes across chemotherapy.

  Study phs002960

• RNA-Seq in Patients with Primordial Dwarfism

  Transcriptome studies in patients with rare genetic diseases can potentially aid in the interpretation of likely causal genetic variation through identification of altered transcript abundance and/or structure. RNA-Seq is the most sensitive assay for both investigating transcript structure and abundance The primary aim of this pilot project is to investigate to what degree integrating exome-Seq and RNA-Seq data on the same individual can accelerate the identification of causal alleles for rare genetic diseases. There are two main strands to this: (i) identifying which variants discovered in exome-seq appear to be having a functional impact on transcripts, and (ii) identifying transcript outliers, especially among known causal genes, that may not necessarily have a causal variant identified from exome sequencing. The latter may identify the presence of causal variants that lie far from coding regions (e.g. the formation of cryptic splice sites deep within introns, or loss of long range regulatory elements), which can be confirmed with further targeted genetic assays. Just over 50% of all disease-causing variants recorded in the Human Gene Mutation Database (HGMD) affect transcript structure and abundance (e.g. nonsense SNVs, essential splice site SNVs, frameshifting indels, CNVs). This pilot project will study RNA from lymphoblastoid cell-lines from 12 patients with primordial dwarfism syndromes, for 10 of these samples we have previously generate exome data as part of our collaboration with the group of Prof Andrew Jackson. The two remaining samples are positive controls where the causal mutation is known, and is known to affect transcript structure and/or abundance. Primordial dwarfism is a prime candidate for these RNA-seq studies because all known causal mutations to date have key roles in DNA replication and thus, unsurprisingly, the products of the causal genes are typically ubiquitously expressed. Each RNA will be sequenced, with two technical replicates (independent RT-PCR and libraries) per sample, and each replicate run in 1/2 of a HiSeq lane using 100bp paired reads. Samples preparation was as follows :The cells were grown to confluency, then pellets frozen at -80. RNA samples were prepared using the Qiagen RNeasy kit, then nanodropped and analyzed using the bioanalyzer to determine concentration and purity. 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 EGAD00001000640

• A Phase I/II Study of Revlimid (lenalidomide) in Combination with Vidaza (azacitidine) in Patients with Advanced Myelodysplastic Syndrome (MDS)

  This single-arm study design has been selected to investigate the safety of combination therapy with Vidaza® (azacitidine) and Revlimid® (lenalidomide) in a population of 18 participants with advanced MDS for the Phase I portion, and 18 participants for the Phase II portion. The multi-center nature of the study should enhance the general applicability of the results. Participants with advanced MDS were chosen because it is expected that the combination of the two drugs will by myelosuppressive, which can be considered a necessary toxicity to effect improvements in PR and CR rates in this advanced population, akin to participants with AML. Finally, the combination was chosen to be studied because currently available therapies in this population, and their effectiveness, are limited, and single-agent Vidaza® (azacitidine), while effective at delaying transformation to AML or death, is not curative. The doses of Revlimid® (lenalidomide) in this study are similar to those that were demonstrated to have an effect and to be well-tolerated in participants with MDS. Doses for Vidaza® (azacitidine) are similar to those used in the pivotal trial, though for a 5-day treatment period instead of 7 to minimize toxicity for the first 3 blocks of participants, and then at a lower dose over a protracted period of time to explore the safety of a 10-day treatment course.

  Study phs001318

• University of Texas PDX Development and Trial Center Grant

  The goal for the University Texas PDX Development and Trial Center (UTPDTC) is to optimize personalized biomarker-based cancer therapy and identify effective targeted drugs based on the molecular characteristics of each tumor. Our short-term goals are to establish a biobank of clinically, and molecularly-annotated Patient-Derived Xenografts (PDXs) and to use PDXs as a platform for preclinical drug development and biomarker discovery. The primary goal for UTPDTC investigators will be to develop PDX trial strategies for preclinical testing of single agents and drug combinations. These models will allow the determination of the optimal treatments (single drugs or combinations) that should be tested in clinical trials in increasingly individualized, molecularly defined subsets of tumors. The goal of the Patient-Derived Xenograft Core is to provide high-quality clinically relevant and molecularly annotated PDX models for the research projects proposed in the University of Texas PDX Development and Trial Center (UTPDTC) grant application and to the research activity of the NCI PDX Development and Trial Centers Research Network (PDXNet) by leveraging PDX resources at our institutions and developing new PDX models from human cancer specimens using rigorous quality standards so that the models can be used to guide clinical trial development. The PDX models developed and/or characterized by the PDX Core will be available to other cancer researchers through the PDXNet and NCI Patient-Derived Models Repository (PDMR).

  Study phs001980

• Genome-wide analysis of genetic risk factors for rheumatic heart disease in Aboriginal Australians provides support for pathogenic molecular mimicry

  Background. Rheumatic heart disease (RHD) following Group A Streptococcus (GAS) infections is heritable and prevalent in Indigenous populations. Molecular mimicry between human and GAS proteins triggers pro-inflammatory cardiac valve-reactive T-cells. Methods. Genome-wide genetic analysis was undertaken in 1263 Aboriginal Australians (398 RHD cases; 865 controls). Single nucleotide polymorphisms (SNPs) were genotyped using Illumina HumanCoreExome BeadChips. Direct typing and imputation was used to fine-map the human leukocyte antigen (HLA) region. Epitope binding affinities were mapped for human cross-reactive GAS proteins, including M5 and M6. Results. The strongest genetic association was intronic to HLA-DQA1 (rs9272622; P=1.86x10-7). Conditional analyses showed rs9272622 and/or DQA1*AA16 account for the HLA signal. HLA-DQA1*0101_DQB1*0503 (OR 1.44, 95%CI 1.09-1.90, P=9.56x10-3) and HLA-DQA1*0103_DQB1*0601 (OR 1.27, 95%CI 1.07-1.52, P=7.15x10-3) were risk haplotypes; HLA_DQA1*0301-DQB1*0402 (OR 0.30, 95%CI 0.14-0.65, P=2.36x10-3) was protective. Human myosin cross-reactive N-terminal and B repeat epitopes of GAS M5/M6 bind with higher affinity to DQA1/DQB1 alpha/beta dimers for the two risk haplotypes than the protective haplotype. Conclusions. Variation at HLA_DQA1-DQB1 is the major genetic risk factor for RHD in Aboriginal Australians studied here. Cross-reactive epitopes bind with higher affinity to alpha/beta dimers formed by risk haplotypes, supporting molecular mimicry as the key mechanism of RHD pathogenesis.

  Study EGAS00001002678

• Foundation Medicine Adult Cancer Clinical Dataset (FM-AD)

  The Foundation Medicine adult cancer clinical dataset consists of 18,004 unique solid tumor samples that underwent genomic profiling on a single uniform platform as part of standard clinical care. The dataset is derived from the FoundationOne® genomic profiling assay version 2 that interrogates exonic regions of 287 cancer-related genes and selected introns from 19 genes known to undergo rearrangements in human cancer. Genomic DNA samples were sequenced to over 500x median coverage, and custom computational analyses identified all classes of genomic alterations (base substitutions, insertions and deletions, copy number alterations, and rearrangements). Since matched normal tissue was unavailable for analysis, these data underwent additional filtering to enrich for cancer-related events. The reported data includes genomic alterations that are known and suspected tumor drivers, as well as variants of unknown significance. To preserve patient anonymity, all known or suspected germline variants were removed from the data unless known to be associated with cancer development. The dataset contains genomic alteration profiles generated by FoundationOne version 2 testing for adult cancer patients (over 18 y.o.), and represents a vast diversity of tumor subtypes, including many rare diseases not profiled as part of large-scale profiling efforts. Cases are grouped into 16 broad disease categories containing tumors from 162 unique disease subtypes. Since specimens were profiled as part of clinical care, limited clinical parameters were available, including age, gender, tissue of origin, % of tumor nuclei, and diagnosis. Publication of this dataset is intended to allow the broad scientific community access to this unique cohort for use in scientific research projects of common and rare types of cancer, both for generating leads regarding causal mechanisms as well as cross-testing and confirming existing hypotheses. A pediatric cancer clinical dataset consisting of data from 1,215 patients under 18 y.o. is available separately at: FOUNDATION MEDICINE

  Study phs001179

• In this study, blood-brain barrier (BBB)-forming brain endothelial-like cells were generated from apolipoprotein E gene allele E4 (APOE4, high AD risk) and allele E3 (APOE3, lower AD risk) carrying patient-derived induced pluripotent stem cells (iPSCs). Cells were subsequently exposed to focused ultrasound and microbubbles (FUS+MB) to induce BBB opening and their transcriptome analysed. RNA sequencing (RNA-seq) results demonstrated minimal changes in the gene expression following FUS+MB suggesting safety of FUS+MB application in the clinical setting.

  The blood-brain barrier (BBB) is a major impediment to therapeutic intracranial drug delivery for the treatment of neurodegenerative diseases, including Alzheimer’s disease (AD). Focused ultrasound applied together with microbubbles (FUS+MB) is a novel technique to transiently open the BBB and increase drug delivery. Evidence suggests that FUS+MB is safe, however the effects of FUS+MB on human BBB cells, especially in relation to AD, remain sparsely investigated. Here we developed a human sporadic AD BBB cell platform to investigate the effects of FUS+MB on BBB cells and screen for the delivery of two potentially therapeutic AD antibodies. We generated BBB cells from apolipoprotein E gene allele E4 (APOE4, high AD risk) and allele E3 (APOE3, lower AD risk) carrying patient-derived induced pluripotent stem cells (iPSCs). We utilized this robust and reproducible platform to demonstrate increased delivery of potentially therapeutic antibodies across the BBB, including an analogue of Aducanumab (AduhelmTM) following FUS+MB treatment. Our results also demonstrate the safety of FUS+MB indicated by minimal changes in the cell transcriptome as well as little or no changes in cell viability and inflammatory responses within first 24 h post FUS+MB, with potentially important implications in a clinical setting. Finally, we report a more physiologically relevant hydrogel-based 2.5D BBB model as a key development for FUS+MB-mediated drug delivery screening, with potentially higher translational utility. Our results provide an important advancement for identifying FUS+MB-deliverable drugs and screening for cell- and patient-specific effects of FUS+MB, accelerating its use as a therapy in AD.

  Study EGAS00001005944

• Copy number profiling of primary samples and cell lines of retinoblastoma

  While RB1 loss initiates retinoblastoma development, additional somatic copy number alterations (SCNAs) can drive tumor progression. Although SCNAs have been identified with good concordance between studies at a cytoband resolution, accurate identification of single genes for all recurrent SCNAs is still challenging. This study presents a comprehensive meta-analysis of genome-wide SCNAs integrated with gene expression profiling data, narrowing down the list of plausible retinoblastoma driver genes. We performed SCNA profiling of 45 primary retinoblastoma samples and 8 retinoblastoma cell lines by high-resolution microarrays. We combined our data with genomic, clinical and histopathological data of ten published genome-wide SCNA studies, which strongly enhanced the power of our analyses (N=310). Comprehensive recurrence analysis of SCNAs in all studies integrated with gene expression data allowed us to reduce candidate gene lists for 1q, 2p, 6p, 7q and 13q to a limited gene set. Besides the well-established driver genes RB1 (13q-loss) and MYCN (2p-gain) we identified CRB1 and NEK7 (1q-gain), SOX4 (6p-gain) and NUP205 (7q-gain) as novel retinoblastoma driver candidates. Depending on the sample subset and algorithms used, alternative candidates were identified including MIR181 (1q-gain) and DEK (6p gain). Remarkably, our study showed that copy number gains rarely exceeded change of one copy, even in pure tumor samples with 100% homozygosity at the RB1 locus (N=34), which is indicative for intra-tumor heterogeneity. In addition, profound between-tumor variability was observed that was associated with age at diagnosis and differentiation grades. Since focal alterations at commonly altered chromosome regions were rare except for 2p24.3 (MYCN), further functional validation of the oncogenic potential of the described candidate genes is now required. For further investigations, our study provides a refined and revised set of candidate retinoblastoma driver genes.

  Study EGAS00001001715

• Data Use Ontology (DUO) at EGA

  For those of you that follow the updates of GA4GH you will have seen the unanimous approval of the steering committee for DUO to be included in its suite of technical standards for the sharing of genomic and health related data. DUO has three main features: Each term has been generated by the community and includes a human readable definition that can be expanded where necessary. It is a machine-readable file that encodes how that data can be used and how a researcher intends to use the data. Can be implemented alongside an advanced search algorithm which would allow authenticated users to query and gain access to datasets pertaining to their research. e.g., an industry researcher working on cancer could potentially be matched to any dataset that is allowed for commercial use and for cancer research and offered the opportunity to fetch them automatically. So, what does this mean for EGA? EGA as a driver project has adopted this standard and will be utilizing it for two main purposes in the first instance. i) It will allow EGA users to instantly identify what terms they will need to agree to as part of any Data Access Agreements. This will save valuable time for both applicants and Data Access Committees alike - as you will be able to see if you are likely to be able to access the data based on your research intentions and working background. ii) In the future it will allow users to be able to search for data based on Data Use Ontology terms e.g., you could search for all data that can be used for General Research Use (GRU). As EGA moves forwards submitters will be asked to align their data access policies with DUO so that their dataset(s) can be tagged appropriately on our web pages. If you would like to add DUO to any of your existing datasets, or to any future datasets, do please just let us know.

  Blog data-use-ontology