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• National Cancer Institute Clinical and Laboratory Analysis of Familial Cancer

  The purpose of this study is to continue the analysis begun on 09C0079 which was focused on identification of the genetic mutation associated with a new gastric polyposis syndrome, Gastric Adenocarcinoma and Proximal Polyposis of the Stomach (GAPPS). GAPPS, first described in 2012, is an autosomal dominant gastric polyposis syndrome that confers a substantial risk for gastric adenocarcinoma. The GAPPS phenotype consists of a carpeting of greater than 100 fundic gland polyps (FGPs) in the oxyntic mucosa of the gastric body and fundus, with antral sparing with some FGPs displaying high-grade dysplasia. This is in contrast to sporadic FGPs that are benign, most often are not associated with high-grade dysplasia though low-grade dysplasia has been reported, and are fewer in number. Gastric FGPs have been found to be associated with Familial Adenomatous Polyposis (FAP) and attenuated FAP, which is an autosomal dominant condition associated with germ line mutations in APC which confers a phenotype consisting of multiple (>100) adenomatous polyps in the colon and rectum developing after the first decade of life. FGPs are reported to occur in 12-84% of patients with FAP, whereas sporadic FGPs are identified in ~5% of patients undergoing upper gastrointestinal endoscopy. Gastric adenocarcinoma arising from FGPs in individuals with FAP have been reported. Other manifestations of FAP and AFAP include polyps in the upper gastrointestinal tract, congenital hypertrophy of retinal pigment epithelium, osteomas and epidermoid cysts, supernumerary teeth, desmoid formation, and other malignancies such as thyroid, small bowel cancer, hepatoblastoma, and medulloblastoma. Thus far there are no reports in GAPPS of polyposis arising in the esophagus, gastric antrum, pylorus, small intestine, or colon.

  Study phs001935

• Host Response to Respiratory Infections

  In this study, we describe a strategy to identify undiagnosed respiratory viral infections through screening nasopharyngeal (NP) swabs for the chemokine CXCL10, which is highly induced in the nasopharynx as part of the host antiviral response. Using this strategy, we conducted two screens: first, we screened NP swabs collected at Yale New Haven Hospital (YNHH) in January 2017 from patients with undiagnosed respiratory viral infections and identified patients infected with seasonal coronaviruses and the relatively uncommon influenza C virus. Second, we screened samples from the beginning of March 2020 in the weeks before YNHH tested for SARS-CoV-2 and identified four patients that had undiagnosed SARS-CoV-2 infections. Sequences uploaded as part of this study include samples with rhinovirus, human coronavirus NL63, and 8 samples as part of the January 2017 screen for undiagnosed respiratory viral infections.

  Study phs002442

• OncoArray: Oral and Pharynx Cancer

  Genetic factors play an important role in susceptibility to head and neck cancer and could also explain differences in response to treatment and outcome. The goal of this project is to investigate genetic variation involved in oral and oropharyngeal cancer susceptibility by performing the largest GWAS on these diseases, using a novel genotyping tool specifically designed for cancer studies by the OncoArray Network. This project encompasses data from approximately 6000 oral and pharynx cancer cases and 4000 controls derived from 12 epidemiological studies most of case-control design. The genotyping was centralized at the Center for Inherited Disease Research (CIDR), and the epidemiological data harmonization and analysis were completed at the International Agency for Research on Cancer (IARC). This study was supported by National Institute of Dental and Craniofacial Research (NIDCR) with direct funding to CIDR.

  Study phs001202

• Cystic Fibrosis Nasal Epithelium Gene Expression by RNAseq

  Cystic fibrosis (CF) is a monogenic disorder leading to multi-organ system dysfunction, with the primary cause of morbidity and mortality being lung disease. Mutations in CFTR result in defective ion channel transport leading to hyperviscous mucus, airway infection, inflammation and lung function decline. While the Phe508del mutation is the most common CFTR mutation in North American people with CF, it is well known that there is a broad range of lung disease severity even amongst Phe508del homozygotes, including twins/siblings. Heritability analyses showing the relative contribution of non-CFTR modifier genes in such differences in phenotype, have led to our genomic and transcriptomic studies of gene modifiers in CF. Complementary to two international CF GWAS studies, this study was performed to a) determine differential expression of genes relative to a quantitative lung disease severity phenotype score (KNoRMA; as used in CF GWAS studies) and b) to assess expression quantitative trait loci. To better understand genetic modification of CF lung disease severity, we analyzed gene expression (transcriptomic) profiles by mRNA sequencing from nasal mucosal biopsy specimens of 134 people with CF. Each study participants was characterized for CF lung disease severity phenotype by averaging three years of lung function data (forced expiratory volume in 1 second; FEV1), normalized to a CF-specific reference population matching for age, sex, and height. Participants completed nasal lavage and nasal curettage mucosal sampling, with directed sampling to the inferior nasal turbinate, a well validated surrogate for cellular characteristics and CFTR function of the lower CF airways. Participants were further invited to complete a second set of these sampling procedures for validation analysis. Specimen and concurrent clinical data collection occurred across four North American study sites and nasal mucosal specimens were subjected to RNASeq analysis. These data were to be made available in the dbGaP. Our association analyses of gene expression relative to quantitative CF lung disease phenotype, taken together with previously identified GWAS signals, identified biological pathways correlated with CF lung disease pathogenesis. Our further association analyses of gene expression relative to single nucleotide polymorphism variation at significant CF GWAS loci further identified potential mechanisms of genetic variants associated with CF lung disease. This resource is intended to aid researchers in characterizing airway mucosal gene expression from the CF airways for the purpose of gene expression profiling in CF and in muco-obstructive airways disease.

  Study phs002254

• The Gene Partnership (TGP) - eMERGE Data

  The Gene Partnership (TGP) is a prospective longitudinal registry at Boston Children's Hospital (BCH) to study the genetic and environmental contributions to childhood health and disease, collect genetic information on a large number of children who have been phenotyped, and implement the Informed Cohort and the Informed Cohort Oversight Board (ICOB). The term "The Gene Partnership" reflects a partnership between researchers and participants. Children seen at BCH are offered enrollment, as are their parents and siblings. DNA is collected on all enrollees. BCH has a comprehensive EMR system, and virtually all inpatient and outpatient data are captured electronically. Clinical data in the BCH EMR is loaded in the i2b2 data warehouse which is available to investigators. Cases, phenotypes, and covariates are ascertained using the i2b2 database. Participants at BCH in TGP have consented to receive any research result and/or incidental finding that arises from studies using TGP that is approved by the Informed Cohort Oversight Board (ICOB) and is in accordance with the participants' preferences; results are returned through the Personally Controlled Health Record (PCHR). BCH and Cincinnati Children's Hospital Medical Center (CCHMC) have partnered as the Pediatric Alliance for Genomic and Electronic Medical Record (EMR) Research (PAGER) site for the eMERGE Phase II network for pediatric institutions, and the cohort for eMERGE at BCH is TGP.

  Study phs000495

• Identification of drug resistance genes in melanoma by mRNA gene expression

  We aim to sequence the mRNA transcriptome of 22 human melanoma cell lines in biological triplicate in order to define the gene expression profile of each cell line. The data will be correlated to the mutation status and the sensitivity to a panel of drugs in order to identify genes whose deregulation is associated to drug resistance 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 EGAD00001003244

• Identification of drug resistance genes in melanoma by small RNAs expression analysis

  We aim to sequence the small RNAs of 22 human melanoma cell lines in biological triplicate in order to define the microRNAs expression profile of each cell line. The data will be correlated to the mutation status and the sensitivity to a panel of drugs in order to identify genes whose deregulation is associated to drug resistance 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 EGAD00001003245

• HCA Female Reproductive Adult WSSS RNA

  HCA Endometrium_LM The endometrium regenerates monthly and its transformation is executed through dynamic changes in states and interactions of multiple cell types. Using transcriptomics methods we seek to profile changes of the endometrium across the menstrual cycle. Our map will have implications in women's health and cancer, by enabling the interpretation of GWAS analyses or the studying functional consequences of somatic mutations. 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 EGAD00001007909

• Combination_therapies_for_personalized_cancer_medicine

  It is the ambition of the team formed by members of the Netherlands Cancer Institute (NKI) and the Cancer Genome Project at the Wellcome Trust Sanger Institute (WTSI) to unravel the genomic and phenotypic complexity of human cancers in order to identify optimal drug combinations for personalized cancer therapy. Our integrated approach will entail (i) deep sequencing of human tumours and cognate mouse tumours; (ii) drug screens in a 1000+ fully characterized tumour cell line panel; (iii) high-throughput in vitro and in vivo shRNA and cDNA drug resistance and enhancement screens; (iv) computational analysis of the acquired data, leading to significant response predictions; (v) rigorous validation of these predictions in genetically engineered mouse models and patient-derived xenografts. This integrated effort is expected to yield a number of combination therapies and companion-diagnostics biomarkers that will be further explored in our existing clinical trial networks.

  Study EGAS00001000655

• EDi018-A / SAMEA4771918 WGS data

  The iPSC line EDi018-A / SAMEA4771918 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi018-A is available for research use at www.EBiSC.org.

  Dataset EGAD50000001027