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• Orthotopic Patient-Derived Xenografts of Pediatric Solid Tumors

  Pediatric solid tumors arise from endodermal, ectodermal, or mesodermal lineages. Although the overall survival of children with solid tumors is 75%-80%, that of children with recurrent disease is below 30%. To capture the complexity and diversity of pediatric solid tumors and establish new models of recurrent disease, we developed a protocol to produce orthotopic patient-derived xenografts (O-PDXs) at diagnosis, recurrence, and autopsy. Tumor specimens were received from 168 patients, and 64 O-PDXs were established for 12 types of pediatric solid tumors. The origins of the O-PDX tumors were reflected in their gene-expression profiles and epigenomes. Genomic profiling of the tumors, including detailed clonal analysis, was performed to determine whether the clonal population in the xenograft recapitulated the patient’s tumor. We identified several drug vulnerabilities and showed that the combination of a WEE1 inhibitor (AZD1775), irinotecan, and vincristine can lead to complete response in multiple rhabdomyosarcoma O-PDX tumors in vivo.

  Study EGAS00001002528

• Gut metagenome associations with extensive digital health data in a volunteer-based EstMB cohort

  Microbiome research is starting to move beyond the exploratory phase towards interventional trials and therefore well-characterized cohorts will be instrumental for generating hypothesis and providing new knowledge. As part of the Estonian Biobank, we established the Estonian Microbiome Cohort which includes stool, oral and plasma samples from 2,509 participants and is supplemented with multi-omic measurements, questionnaires, and regular linkages to national electronic health records. In this study, we analyzed stool data from deep metagenomic sequencing together with rich phenotyping, including 71 diseases, 136 medications, 21 dietary questions, 5 procedures, and 19 other factors. The data revealed numerous relationships with different microbiome features. Additionally, the long-term antibiotic usage, independent from recent administration, has a significant impact on the microbiome composition, partly explaining the common associations between diseases. Overall, this study extends the understanding of microbiome–host interactions and facilitates the development of microbiome-related studies.

  Study EGAS00001005900

• Comparison of the performance of two commercial genome-wide association study genotyping platforms in Han Chinese Samples

  Affymetrix 6.0, Illumina OMNIExpress, and llumina Immunochip genotype data for Han Chinese population including rheumatoid arthritis cases and controls. Data is in PLINK binary format. Illumina genotype clustering was performed using Illumina’s BeadStudio software. SNPs were reclustered using the study samples, low quality subjects were removed, and a subset of clustering results were manually inspected and verified. All SNPs with GenCall scores less than 0.15 were excluded. For Affymetrix chips, clustering was performed using the program Birdseed version 2, as implemented using Affymetrix Genotyper Console v4.0, using the default quality control (QC) thresholds.

  Study EGAS00000000131

• (Epi)genetic Risk Architectures of Opioid-Dependent Brain

  With nearly 20,000 overdose deaths in 2014 alone, opioid addiction (OA) has emerged as one of the most pressing public health crises in recent US history. One-fifth of individuals who try heroin develop an addiction to opioids. Genetics is a major contributor to OA with an estimated 60% heritability, only somewhat less than schizophrenia (80%) which has recently seen substantial gains in identified underlying genetics. Yet, studies to date have failed to uncover most of the genes that predispose individuals to OA, leaving the overwhelming fraction of OA heritability unexplained. The proposed study takes a novel, integrated "omics-based" strategy to investigate the molecular basis of OA and uncover both genetic and epigenetic factors associated with opioid addiction. The premise for our approach is founded on studies from our labs, and others, implicating regulatory variation in common traits and diseases, including those associated with complex brain phenotypes like addiction. We have collected the largest known cohort of postmortem brains from addicts who overdosed on opioids, along with matched control brains from non-users. From both cases and control specimens, we will isolate cells from 2 regions of the brain closely implicated in the addiction phenotype: the Prefrontal Cortex (PFC) and the Nucleus Accumbens (NAc). In Aim 1, we propose ChIP-seq studies to identify regulatory elements that distinguish cases from controls and define the opioid addiction phenotype. The regulatory differences will be connected to their gene targets through high resolution in situ Hi-C. In Aim 2, we propose QTL-based approaches to identify genetic variants that underlie the regulatory differences (hmQTLs). We also propose eQTL analyses to identify genetic variants that underlie differences in transcript levels between cases and controls. Aim 3 leverages the largest heroin addiction GWAS meta-analysis to date to test the hypothesis that SNPs in regions associated with chromatin and expression differences between cases and controls define novel loci for predisposition to OA. Each Aim has the potential for discovery independent of the others (differential HM, RNAexp, QTLs, and variant-phenotype associations) but their synergy is the most powerful component of the proposed study: identifying regulatory pathways that generate, not only phenotype associations, but hypothesized mechanisms for those associations which can be the focus of new opioid addiction prevention and treatment development.

  Study phs002724

• 3D tissue engineered human skeletal muscle modelling Facioscapulohumeral Muscular Dystrophy

  acioscapulohumeral muscular dystrophy (FSHD) is caused by sporadic misexpression of the transcription factor double homeobox 4 (DUX4) in skeletal muscles. So far, monolayer cultures and animal models have been used to study the FSHD disease mechanism and for FSHD therapy development, but these models do not fully recapitulate the disease and there is a lack of knowledge on how DUX4 misexpression leads to skeletal muscle dysfunction. To overcome these barriers, we have developed a 3D tissue engineered skeletal muscle (3D-TESM) model by generating genetically matched myogenic progenitors (MPs) from human induced pluripotent stem cells of three mosaic FSHD patients. 3D-TESMs derived from genetically affected MPs recapitulate pathological features including DUX4 and DUX4 target gene expression, smaller myofiber diameters, and reduced absolute forces upon electrical stimulation. RNA sequencing data illustrates increased expression of DUX4 target genes in 3D-TESMs compared to 2D myotubes, and cellular differentiation was improved by 3D culture conditions. Treatment of 3D-TESMs with small molecules identified in drug development screens in 2D muscle culture showed no improvements in contractile force and sarcomere organization, highlighting the potential benefit of 3D-TESMs for preclinical drug potency screening by eliminating false-positive compounds for FSHD research and drug development.

  Study EGAS50000000502

• Transcriptomic and Epigenetic Profiling of SCLC Patient Samples

  Small cell lung cancer (SCLC) is an aggressive disease with poor outcomes and limited treatment options. Recent studies have identified transcriptionally defined subsets of SCLC that may allow for the personalization of treatment. Here we use transcriptomic sequencing and methylation profiling (RRBS) of biopsy and cfDNA to develop a highly accurate DNA methylation-based classifier to distinguish SCLC subtypes. These results demonstrate the clinical feasibility of molecular subtyping of SCLC.

  Study phs003416

• B Cell Lymphocytosis and Reprogramming due to a CARD11 Bi-Allelic Gain-of-Function Mutation

  This is a single-cell RNA sequencing (scRNA-seq) study using peripheral blood mononuclear cells (PBMC) from 2 healthy donors and 2 patients with B cell Expansion with NF-κB and T cell Anergy (BENTA). Samples were not hashed or multiplexed. The 10X Genomics Platform was used for sequencing. Principal findings include transcriptome changes due to mono- or bi-allelic mutations in the gene CARD11. FASTA files will be available through dbGaP.

  Study phs004115

• Epigenetic and transcriptional profile of memory B cells in Multiple sclerosis

  Methylome and transcriptome data of non-proliferating and autoproliferating memory B cells (CD27+) from Multiple sclerosis patients under natalizumab treatment, that have been generated and analyzed for the study "T-bet+ CXCR3+ B cells drive hyperreactive B-T cell interactions in multiple sclerosis". Aim is to understand epigentic and transcriptional differences in activated memory B cells in MS and how epigentic differences translated in transcriptional changes in the same patient.

  Study EGAS50000000872

• RRBS data from TRACERx non-small cell lung cancer (NSCLC) tumours and matched normal adjacent tissue.

  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 TRACERx cohort selected for quantity of material available and high tumour purity

  Study EGAS00001006523

• Female Infertility: Primary Ovarian Insufficiency

  Premature ovarian failure, or primary ovarian insufficiency (POI) is a phenotype of diminished or absent ovarian function occurring in 1-2% of reproductive aged women. Most cases occur spontaneously. Evaluation of the gametes in women with POI is difficult and invasive. Practitioners must often rely on indirect biomarkers of ovarian function and oocyte health, making it difficult to identify patients who may benefit from therapies allowing them to achieve pregnancy utilizing their own oocytes. This study will generate exome sequences from POI patients in an effort to elucidate the causes of unexplained POI and to better understand the normal processes of ovarian aging. A better understanding of the genetics of ovarian function may lead to new non-invasive tools for managing women's reproductive health, and direct better use of existing biomarkers in diagnosis, screening and predicting clinical outcomes.

  Study phs001174