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• Tumor Profiler Project - MEL bulk transcriptomics data

  The dataset contains bulk transcriptomics data from 80 samples from 77 different patients with melanoma. Samples were collected from the tumor. Sequencing was performed in paired-end mode and sequencing data is provided in fastq format.

  Dataset EGAD50000000851

• Tumor Profiler Project - MEL scDNA data

  The dataset contains 10x Chromium single-cell DNA sequencing data from 63 samples from 60 different patients with melanoma. Samples were collected from the tumor. Sequencing was performed in paired-end mode and sequencing data is provided in fastq format.

  Dataset EGAD50000000852

• Tumor Profiler Project - OV cell-free DNA data

  The dataset contains amplicon sequencing data from 48 samples from 35 different patients with ovarian cancers. Cell free DNA was collected from plasma. Sequencing was performed on an Ion Torrent platform and the sequencing data is provided in bam format.

  Dataset EGAD50000001410

• miRNA

  The purpose is to perform miRNA analysis on FACS sorted target immune cell populations to uncover novel potential miRNA diagnostic markers biomarkers predictive of therapy response but also possibly identify perturbed signaling pathways or miRNA targets of intervention with the use of agomirs/antagomirs.

  Dataset EGAD50000002025

• Bulk RNASeq of metastatic colorectal cancer organoids with ATOH1 knockout

  Bulk RNA sequencing was performed on mCRC organoids subjected to cetuximab treatment, comparing ATOH1 knockout and control conditions. The dataset is intended to elucidate the contribution of ATOH1-regulated secretory cell population to cetuximab persistence mechanisms.

  Dataset EGAD50000002060

• Single-cell RNA sequencing of anti-LAG3+anti-PD1 treated melanoma patients

  Single-cell RNA sequencing of 18 peripheral blood samples from six melanoma patients. The raw data is available as fastq files.

  Dataset EGAD00001009807

• Human placenta microRNA sequencing dataset

  Human placenta samples from 52: 5 first trimester , 7 second trimester, and 40 term placenta. Data is uploaded as BAM files.

  Dataset EGAD00001007766

• ExHiBITT – Exploring Host microBIome inTeractions in Twins – a colon multiomic cohort study

  The objective of the colonoscopy study is to carry out the 16s sequencing of colon biopsies and faecal samples provided in ExHiBITT study to compare potential fluctuations in the microbiota of different sites.

  Dataset EGAD00001010936

• MESA colorectal cancer cfDNA EM-seq dataset

  This dataset contains the methylation sequencing data of 60 nonCancer and 70 colorectal cancer cfDNA samples. The methylation library is constructed by using NEBNext Enzymatic-seq Kit.

  Dataset EGAD00001009165

• Genetic factors underlying premature MI in Greek families without vessel disease

  The study will analyse by exome sequencing 8 Greek family members with an excess of potentially damaging mutations relating to premature MI and no vessel disease, to identify genetic factors underlying this condition. This is a follow on from project GPMI-NVD

  Dataset EGAD00001002178

• RNA-seq of BCR-ABL1 lymphoblastic leukemia

  This dataset is derived from whole-transcriptome sequencing (RNA-seq) of RNA from 57 BCR-ABL1 lymphoblastic leukemias (53 diagnostic, 4 relapse).

  Dataset EGAD00001010307

• COVID-19 Postmortem Lung snRNA-seq

  A deeper understanding of the pathological mechanisms of SARS-CoV-2 infection is required to combat COVID-19. Through this dataset, we analyze postmortem lung cells from patients that are infected/uninfected with SARS-CoV-2 with snRNA-seq.

  Dataset EGAD00001006584

• TCRab sequencing of T-LGLL patients

  TCRab sequencing was performed on viably frozen cells from 11 T-LGLL samples from 9 T-LGLL patients and 6 age-matched healthy samples. The raw data is available as fastq files.

  Dataset EGAD00001008691

• HERBY trial RNASeq

  RNA sequencing of non-brainstem paediatric high grade glioma from the HERBY phase II randomised trial. RNA from fresh frozen surgical tissue in 20 cases was subjected to Illumina whole transcriptome paired end sequencing. Data is provided as paired-end FASTQ files

  Dataset EGAD00001004070

• Shwachman-Diamond syndrome (SDS) Exome sequencing

  Shwachman-Diamond syndrome (SDS) is a rare autosomal recessive disorder characterized by exocrine pancreatic insufficiency, bone marrow dysfunction, leukemia predisposition, and skeletal abnormalities. We aim to characterise the structural effects of SDS in patients with this disorder by exome sequencing.

  Dataset EGAD00001000847

• Genetics of Microcephalic Osteodysplatics Primordial Dwarfism

  This project aims to find causal variants in 50 patients diagnosed with Microcephalic Osteodysplastic Primordial Dwarfism (MOPD), of presumed recessive inheritance performing whole exome sequencing to ~50x mean depth.This is a collaboration with Prof A. Jackson, MRC Human Genetics Unit, Edinburgh

  Dataset EGAD00001000342

• IBDCA_Edinburgh

  In this experiment we have sequenced tumour normal pairs from patients presenting with CRC who have a prior history of inflammatory bowel disease. The idea is to identify driver mutations, new genes and novel pathways associated with the development of these malignancies.

  Dataset EGAD00001001330

• Identifying and Reducing Disparities in Patient-Reported Outcomes Among African American Prostate Cancer Survivors

  This research study aimed to identify disparities in prostate cancer symptom burden and their contributors among African American, Hispanic, and non-Hispanic White prostate cancer survivors. We collected patient-reported outcomes data, focusing on various aspects of the survivors' health and well-being, clinical data, demographics data, and germline genomic data.

  Study phs003745

• Spatial tumor microenvironment characterization and outcome of relapsed/refractory classic Hodgkin lymphoma

  About half of relapsed or refractory classic Hodgkin lymphoma (r/r CHL) patients succumb to their disease after high dose chemotherapy followed by autologous stem cell transplantation (HDT/ASCT). Here, we aimed at describing spatially resolved tumor microenvironment (TME) ecosystems to establish novel biomarkers associated with treatment failure in r/r CHL.

  Study EGAS00001007261

• Gene Expression and Regulatory Networks in Human Leukocytes - Immunological Variation Consortium

  Profiling of gene expression with microarrays holds great potential for human health, for illuminating disease pathways or providing biomarkers to monitor disease or its resolution. Using high-throughput approaches for genotyping, immunophenotyping and gene expression analysis, the project will examine the basis for the control of gene expression in human immune cells, and how it is influenced by natural genetic variation or aging. In practice, the project will combine several cross-informative approaches: 1) Building on the established sample/data pipelines and robust protocols of the Immunological Genome (ImmGen) project, and on established cohorts of ethnically diverse healthy volunteers at hand, microarray techniques will be used to generate whole-genome expression profiles from purified naive CD4+ lymphocytes and monocytes from 600 healthy volunteers. A dense genetic map will be established for all donors. The results will elucidate how variation in the human genome affects the expression of immune genes, of key importance in understanding gene variants that bring susceptibility to immune or inflammatory disease. Computational analysis of these rich data will allow the reconstruction of regulatory connections between genes, helping to establish general modules and those specific of a given immune cell type. These data will be complemented by an orthogonal data group, generated from a restricted subset of 10 individuals, in which we will profile a larger set of 28 carefully delineated cell populations that exist in human blood. This work will also benefit from powerful interspecies comparison with similar experiments being performed in mice by ImmGen. 2) In addition, RNA from the same set of 28 defined cell populations will be probed with microarrays that explore other aspects of the transcriptome: i) microRNAs and other non-coding RNAs; ii) exon or splice junction arrays that will establish a map of differential splicing in human blood leukocyte. 3) The composition and reactivity of blood cells from the same donors will be established at the time of sample collection using high-throughput flow cytometry, correlating immune phenotypes with gene expression and genetic variation. 4) Genetic variability conditions the baseline levels of gene expression, but also the responsiveness to activating challenges. With samples from the same donors, NanoString technology for transcript counting will be used to analyze the transcriptional response of defined gene sets, representing response signatures of T or dendritic cells, for a fine-grained dissection of responses to different triggers (different bacterial ligands for dendritic cells, different cytokine environment for T cells). In keeping with the resource aspect of this project, all data and interpretations will be made publicly available rapidly upon curation, allowing public querying and browsing of the data, by using and evolving the existing web architectures of the ImmGen project, of the Broad Institute, and of international repositories. RELEVANCE: Exploration with DNA chips of the genome's expression microarrays holds great potential for human health, to better understand disease and to serve as diagnostic tools. Using a combination of high-throughput genomic techniques and computational biology, we will perform a broad exploration of gene expression in human blood cells across groups of African-American, Asian and European ancestry, asking how these profiles are affected by genetic variation or by age. These results will provide an invaluable reference benchmark for the interpretation of genetic and immunological studies. Additionally, over 90% of genetic variants associated with complex human traits map to non-coding regions, but little is understood about how they modulate gene regulation in health and disease. One possible mechanism is that genetic variants affect the activity of one or more cis-regulatory elements leading to gene expression variation in specific cell types. To identify such cases, in a second study we analyzed ATAC-seq and RNA-seq profiles from stimulated primary CD4+ T cells in up to 105 healthy donors. We found regions of accessible chromatin (ATAC-peaks) are co-accessible at kilobase and megabase resolution. 15% of genetic variants located within ATAC-peaks affected the accessibility of the corresponding peak (ATAC-QTLs). ATAC-QTLs have the largest effects on co-accessible peaks, are associated with gene expression, and are enriched for autoimmune disease variants. Our results provide insights into how natural genetic variants modulate cis-regulatory elements, in isolation or in concert, to influence gene expression. In another study we analyzed RNA-seq profiles from primary CD4+ T cells of two healthy donors at six time points from 0 to 72 hours after stimulation with bead-bound antibodies against CD3 and CD28.

  Study phs000815

• Molecular Biomarkers Predicting Lung Cancer Response Phenotypes

  We have used a "chemistry first" approach to discover druggable acquired vulnerabilities that arised in the pathogenesis of non-small cell lung cancer (NSCLC). We screened chemical libraries (~200,000 compounds) for chemical toxins that killed subsets of NSCLC but not normal human lung epithelial cells (HBECs). We first screened a panel of 12 NSCLC lines that represented a variety of known oncogenotypes and identified chemicals with large Z scores and appropriate properties including re-supply, chemistry, and reproducible drug response phenotypes. This was then narrowed down to a list of 202 chemicals and 18 drugs with known targeting (henceforth called "Precision Oncology Probe Set", or POPS). These, and a panel of 30 clinically available drugs, targeted therapies, and drug combinations, already in use or in trials for NSCLC treatment, were then tested on a panel of 96 NSCLC lines for their drug response phenotypes in 12-point dose response curves. This information was analyzed using scanning ranked KS (Kolmogorov-Smirnov) and elastic net biostatistics approaches to identify molecular biomarkers (mutations, mRNA expression, copy number variation, protein expression, and metabolomics) which could predict for sensitivity or resistance to a particular chemical toxin or treatment regimen. From this we have discovered that: our approach identifies already known molecular biomarker of drug sensitivities (e.g. EGFR mutations and EGFR TK inhibitors); many clinically available chemotherapy agents have molecular biomarkers predicting preclinical model drug responses; the POP set of chemical toxins provides novel drug response phenotype patterns in the large NSCLC panel different from those found with clinically available agents including a therapeutic window; many of the POP toxins only hit a small percentage (~5%) of the NSCLC panel but the POP set as a whole provides "coverage" of the entire NSCLC panel; there are simple, one or 2 component molecular biomarkers (mutations, mRNA expression) that predict responses to the different chemical toxins in the NSCLC panel; and that the molecular biomarkers provide some information on the targets and pathways involved in response to the chemical toxins. Thus, we have identified a group of chemical toxins with selectivity for subsets of NSCLC and associated tumor molecular biomarkers to facilitate their development for precision medicine, and also, in some cases, information on the targets and pathways interdicted by these chemical compounds. In addition, we have discovered NSCLC predictive biomarkers for clinically available agents.

  Study phs001823

• Platelet RNAseq data for SLFN14 K219N patients

  Pathogenic missense variants in SLFN14, which encodes an RNA endoribonuclease protein that regulates rRNA degradation, are known to cause inherited thrombocytopenia with impaired platelet aggregation and ATP secretion. Despite rather mild laboratory defects, these patients display an obvious bleeding phenotype. The function of SLFN14 in megakaryocyte (MK) and platelet biology is unknown. This study aims to characterize the platelet transcriptome in patients with a SLFN14 K219N variant and model the disease in the immortalized megakaryocyte cell line imMKCL. Total platelet RNA was sequenced for two patients and 19 healthy controls. Differential gene expression analysis yielded a total of 2999 and 2888 significantly (|log2FC|>1, FDR<0.05) up- and downregulated genes, respectively. Remarkably, these downregulated genes were not enriched for any biological pathway while upregulated genes were enriched for pathways involved in (mitochondrial) translation and transcription with a significant upregulation of 134 ribosomal protein genes (RPG). Heterozygous and homozygous SLFN14 K219N imMKCL showed a defect in MK differentiation that aggravated during cell passaging of undifferentiated cells and in proplatelet formation. SLFN14 defective platelets and MK showed signs of rRNA degradation while this was absent in undifferentiated imMKCL cells. Upregulation of RPG through increased mTOR signaling in SLFN14 K219N MK seems to be a compensatory response for rRNA degradation. Indeed, mTOR inhibition with rapamycin resulted in further enhanced rRNA degradation in SLFN14 K219N MK. Taken together, our study indicates dysregulation of mTOR-regulated ribosomal biogenesis as the disease mechanism for SLFN14-related thrombocytopenia.

  Study EGAS00001006339

• BPH Tissues for Cell Culture and Analysis - Spatial Transcriptomics Identifies Candidate Stromal Drivers of Benign Prostatic Hyperplasia

  The study goal was to apply spatial transcriptomics to identify candidate stromal drivers of benign prostatic hyperplasia (BPH). Laser microdissection (LCM) with RNA-seq of the stroma adjacent to hyperplastic and budding BPH ducts identified secreted factors including IGF1 and CXCL13. Single‐cell RNA sequencing (scRNA‐seq) revealed their co-expression from BPH fibroblasts. Additional studies sought to define similarities to embryonic prostate development, as well as therapeutic applications. Subjects were those who underwent prostatectomy for prostate or bladder cancer, with concurrent BPH, and who consented to use of surplus tissue for research studies. LCM/RNA-seq studies included 5 patients, and scRNA-seq studies included 1 patient. Phenotypic data submitted to this study include patient age, sex, prostate size, and international prostate symptom score (IPSS). Sequencing was done on an Illumina NovaSeq 6000 (LCM/RNAseq) and Illumina HiSeq X-Ten (scRNA-seq). The data processing pipeline utilized Kallisto (LCM/RNA-seq) and Cell Ranger (scRNA-seq). Data submitted are raw sequencing (Fastq) files.

  Study phs003477

• NIH RECOVER-Pediatric: Understanding the Long-Term Impact of COVID on Children and Families

  The NIH Researching COVID to Enhance Recovery (RECOVER) initiative comprises a set of three combined retrospective and prospective, longitudinal and observational meta-cohort studies with nested case-control studies designed to define and characterize the epidemiology, natural history, clinical spectrum, and underlying mechanisms of post-acute effects of SARS-CoV-2 infection (PASC or Post-COVID syndrome) in a diverse study population representative of the general COVID-19 population in the US. Enrolled patients, with and without known SARS-CoV-2 infection, will be observed for clinical signs and symptoms of PASC and will be assessed for risk and resiliency factors and potential mediating factors associated with the severity and progression of PASC. The objective of the RECOVER initiative is to enhance knowledge of recovery from SARS-CoV-2 infections in order to support development of novel diagnostic and therapeutic interventions. Overarching scientific objectives are as follows:Characterize the incidence and prevalence of sequelae of SARS-CoV-2 infection.Characterize the spectrum of clinical symptoms, subclinical organ dysfunction, natural history, and distinct phenotypes identified as sequelae of SARS-CoV-2 infection. Define the biological mechanisms underlying pathogenesis of the sequelae of SARS-CoV-2 infection. The RECOVER observational studies comprise three cohorts across the lifespan (adult, pediatric, and tissue pathology (autopsy)). The data collection and data analysis plans for each cohort have been harmonized to use common data elements where feasible. Brief descriptions of each cohort are provided in the following paragraphs: 1) NIH RECOVER: A Multi-site Observational Study of Post-Acute Sequelae of SARS-CoV-2 Infection in Adults (see phs003463)The RECOVER adult cohort study is a combined retrospective and prospective, longitudinal, observational meta-cohort of individuals who will enter the cohort with and without SARS-CoV-2 infection and at varying stages before and after infection. Individuals with and without SARS-CoV-2 infection, and with or without PASC symptoms, will be followed to identify risk factors and occurrence of PASC. This study will be conducted in the United States and subjects will be recruited through inpatient, outpatient, and community-based settings. Study data including age, demographics, social determinants of health, medical history, vaccination history, details of acute SARS-CoV-2 infection, overall health and physical function, and PASC symptom screen will be reported by subjects or collected from the electronic health record using a case report form at specified intervals. Biologic specimens will be collected at specified intervals, with some tests performed in local clinical laboratories and others performed by centralized research centers or banked in the Biospecimen Repository. Advanced clinical examinations and radiologic examinations will be performed at local study sites with cross-site standardization. 2) A Multi-Center Observational Study: The RECOVER Post Acute Sequelae of SARS-CoV-2 (PASC) Pediatric Cohort Study (this study)The RECOVER pediatric study is a combined retrospective and prospective, longitudinal, observational meta-cohort of individuals ages newborn-25 years who will enter the cohort with and without SARS-CoV-2 infection at varying stages before and after infection. Individuals with and without SARS-CoV-2 infection and with or without PASC symptoms will be followed to identify risk factors and occurrence of PASC. This study recruit participants inpatient, outpatient, and community-based settings in the United States. Study data including age, demographics, social determinants of health, medical history, vaccination history, details of acute SARS-CoV-2 infection, overall health and physical function, and PASC symptoms will be reported by participants or collected from the electronic health record using a case report form at specified intervals. Biologic specimens will be collected at specified intervals, with some tests performed in local clinical laboratories and others performed by centralized research centers or banked in the Biospecimen Repository. Advanced clinical and radiologic examinations will be performed at local study sites with cross-site standardization. 3) NIH RECOVER: A Multi-site Pathology Study of Post-Acute Sequelae of SARS-CoV-2 Infection The RECOVER tissue pathology study is a cross-sectional study designed to define and characterize the epidemiology, natural history, clinical spectrum, and underlying mechanisms of post-acute effects of SARS-CoV-2 infection in a diverse population representative of the general COVID-19 population in the US. The autopsy study will characterize the pathology of PASC in (i) non-hospitalized patients who die 30 days or later from symptom onset of COVID-19, and (ii) hospitalized patients who die 30 days or later after discharge from a hospitalization for COVID-19. The study will include decedents who had previously fully recovered from SARS-CoV-2 infection (i.e., >30 days from onset in non-hospitalized, or >30 days from discharge in hospitalized patients), and decedents who meet clinical criteria of PASC as defined by the recent World Health Organization publication (see Section 5.4 below). The autopsy study will also explore the pathology of acute SARS-CoV-2 infection in a smaller subset of patients who died 15-30 days from symptom onset. This protocol defines the common set of clinical data elements, autopsy procedures for tissue collection, core measures, pathology protocols, shared pathology tissues, data elements, and methodology. Each investigator site is expected to perform autopsies on the decedents to address the pathophysiology of the potential long-term effects of SARS-CoV-2 infection on human health. The Consortium analysis plan aims to address research questions by incorporating: 1) tissue obtained from autopsies performed at each Phase II participant's site; and 2) tissue available from other pathology investigators/autopsy sites within the Consortium.

  Study phs003461

• RNA-Seq of human longitudinal whole blood samples from PCR-positive and PCR-negative adults following controlled inoculation with Influenza A H3N2 virus.

  Understanding of the transcriptomic profile of individuals in early influenza infection is limited. To investigate this, longitudinal whole-blood samples (n=178) were taken from adult participants following controlled inoculation with Influenza A H3N2 virus (sampling at baseline (0) and days 1, 2, 3, 7, 10 and 14 post-challenge). Most participants became influenza PCR-positive; a minority remained PCR-negative. Total RNA was extracted from PAXgene tubes before undergoing globin and rRNA depletion. DNA libraries were constructed using the NEBNext® Ultra™ II Directional RNA Library Prep Kit for Illumina. All samples were then sequenced using Illumina NovaSeq 6000.

  Dataset EGAD50000000956