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• MP2PRT: Evaluation of an Inflammation Polygenic Risk Score (iPRS) to Predict Cancer Related Cognitive Impairment and Fatigue in Patients Receiving Chemotherapy for Non-Metastatic Breast Cancer in URCC0701 and URCC10055

  This study is a secondary analysis of cancer related cognitive impairment (CRCI) and cancer related fatigue (CRF) among participants in URCC0701 and URCC10055 from the University of Rochester NCI Community Oncology Research Program (NCORP) Research Base. CRCI and CRF are common, troublesome, and dose-limiting toxicities reported by patients undergoing breast cancer chemotherapy that have an etiologic basis linked to low-grade systemic inflammation. Chronic, low-grade systemic inflammation is, in part, genetically determined with common single nucleotide polymorphisms (SNPs) capturing variation across individuals. This study aimed to 1) determine whether an inflammation polygenic risk score (iPRS) is associated with CRCI or CRF, 2) determine whether the relationship between the iPRS and CRCI or CRF is modified by exercise at the time of cancer treatment, 3) identify SNPs associated with serum cytokines measured at the time of cancer treatment, and 4) identify novel CRCI- and CRF-associated risk SNPs via genome-wide association analyses. We found that there was a significant inverse correlation between the iPRS and change in fatigue score from pre-chemotherapy to post-chemotherapy while there was no statistically significant association between the iPRS and cognitive impairment score. The inverse relationship between the iPRS and fatigue may be explained in part by the finding that the iPRS was also significantly associated with greater pre-chemotherapy fatigue, suggesting that women with a genetic predisposition to low-grade systemic inflammation (i.e., high iPRS) have more fatigue at the time of breast cancer diagnosis and, therefore, are less likely to worsen over the course of treatment. In contrast, women with a low iPRS had significantly less fatigue pre-chemotherapy and a significant worsening of fatigue from pre- to post-chemotherapy. The relationship between the iPRS and fatigue remained after adjustment for patient and cancer treatment covariates and was most pronounced in women who reported regularly exercising for at least 6 months prior to starting their cancer treatment. Exploratory genome-wide analysis identified a novel risk locus on chromosome chr6q27, tagged by rs9365961, associated with CRCI. This locus is upstream of TBXT, which encodes an embryonic nuclear transcription factor previously associated with susceptibility to neural tube defects. The genome-wide SNP data, patient-reported CRCI and CRF outcome measures, and covariate data used in this analysis are available through dbGaP.

  Study phs003688

• Implementation, Adoption, and Utility of Family History in Diverse Care Settings

  The purpose of this study is to address the key question of whether and how family health history (FHH) is adopted as a tool to more efficiently manage patients at risk for breast, colon, ovarian, and hereditary cancer syndromes as well as thrombophilia and coronary heart disease (CHD) and to provide evidence supporting clinical utility -- improved health behaviors in patients and physician screening recommendations. Five health care delivery organizations will participate in this demonstration project: Duke University, the Medical College of Wisconsin, the Air Force, Essentia Health, University of North Texas. Duke will serve as a coordinating center for this project (Pro00043372) as well as a site. Healthcare Effectiveness Data and Information Set (HEDIS) measures as intermediate clinical effectiveness measures for Coronary Heart Disease (CHD) and selected cancers as well as survey/formative data and electronic medical record (EMR) data will be used as outcomes measures. The research model is purposely designed to mimic clinical delivery as an important step toward widespread implementation and sustainability. In addition, a cost-effectiveness analysis comparing usual care to the FHH guided preventive health model will be used. The completion of this project will result in an optimal strategy for integration of FHH data collection and clinical decision support (CDS) tools into an EMR and demonstrate the utility of the FHH intervention among diverse primary care patients, their settings, their providers, and the health systems that deliver their care. Specific Aim 1: To optimize the collection of patient entered FHH in diverse clinical environments for coronary heart disease, thrombosis, and selected cancers Specific Aim 2: To export FHH data to an open clinical decision support (open CDS) platform and return CDS results to providers and patients (and to EMRs where relevant). To explore the integration of genetic risk and FHH data at selected sites. Specific Aim 3: To assess the clinical and personal utility of FHH using a pragmatic observational study design to assess reach, adoption, integrity, exposure, and sustainability, and to capture, analyze, and report effectiveness outcomes at each stakeholder level: patient, provider, and clinic/system. Specific Aim 4: To take a leadership role in the dissemination of guidelines for a FHH intervention across in diverse practice settings. AAA Hypertension Lupus Multiple sclerosis Obesity Osteoporosis Thyroid disease Rheumatoid arthritis Blood clotting (6): Blood Clot (high risk features) Factor V PT mutation AT III deficiency Protein S deficiency Protein C deficiency Brain Disorders (5): Dementia Hemorrhagic stroke Ischemic stroke Macrocephaly Seizure Cancer/Adenomas (32): Bone cancer Brain cancer Breast cancer Colon cancer Adrenal cortex tumor Neuroendocrine tumor Paraganglioma Pheochromoctyoma Pituitary adenoma Medullary thyroid cancer Non-medullary (follicular or papillary) thyroid cancer Don't know type of thyroid cancer Thyroid nodule Other type of endocrine cancer Esophageal cancer Kidney cancer Leukemia Lipoma Liver cancer Muscle cancer Ovarian cancer Pancreatic cancer Prostate cancer Rectal cancer Retinoblastoma Melanoma Non-melanoma skin cancer Do not know type of skin cancer Small bowel cancer Stomach cancer Uterine cancer Other type of cancer Cardiovascular/heart/artery disease (5): Atrial fibrillation Carotid stenosis Heart attack/coronary artery disease Peripheral arterial disease Other heart disease Diabetes (3): Gestational diabetes Diabetes type I Diabetes type 2 Digestive Disorders (5): Colon polyp Crohn's disease Irritable bowel syndrome Ulcerative colitis Other digestive disorder Eye Disorder (3): Blindness Glaucoma Macular degeneration Hereditary Cancer Syndromes (22): Birt-Hogg-Dube syndrome Cowden syndrome Familial adenomatous polyposis Hereditary breast and ovarian cancer syndrome Hereditary diffuse gastric cancer Hereditary leiomyomatosis and renal cell carcinoma syndrome Hereditary melenoma Hereditary papillary renal cancer syndrome Hereditary paraganglioma-pheochromocytoma syndrome Hereditary retinoblastoma Juvenile polyposis Li-Fraumeni syndrome Lynch syndrome Mutyh-associated polyposis Malignant hyperthermia susceptibility Multiple endocrine neoplasia type 1 Multiple endocrine neoplasia type 2 Nevoid basal cell carcinoma syndrome Peutz-Jeghers syndrome Tuberous Sclerosis complex Von-Hippel Lindau syndrome Other hereditary cancer Hereditary Cardiovascular syndromes (10): Long qt Brugada Catecholaminergic polymorphic ventricular tachycardia Hypertrophic cardiomyopathy Dilated cardiomyopathy Left ventricular non-compaction syndrome Arrhythmogenic right ventricular dysplasia Ehlers-Danlos syndrome Marfan syndrome Other hereditary cardiovascular syndrome High cholesterol (2): Hyperlipidemia Familial hypercholesterolemia Kidney Disease (6): Cystic kidney disease Diabetic kidney disease Kidney nephrosis Nephritis Nephrotic syndrome Other kidney disease Liver Disease (6): Alpha 1 antitrypsinase deficiency Auto-immune hepatitis Hereditary hemochromatosis Primary biliary cirrhosis Sclerosing cholangitis Wilson's disease Lung Disease (3): Asthma COPD/chronic bronchitis/emphysema Other lung disease Psychological disorder (14): Addiction ADHD Autism Bipolar Depression Eating disorder Intellectual disability Obsessive compulsive disorder Panic disorder Personality disorder PTSD Schizophrenia Social phobia Sickle cell/thalassemia (3): Sickle cell disease Sickle cell trait Thalassemia

  Study phs001641

• Lung Tissue Research Consortium (LTRC-BioLINCC)

  Data Access NOTE: Please refer to the "Authorized Access" section below for information about how access to the data from this accession differs from many other dbGaP accessions. Biospecimens: Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from LTRC include DNA, Plasma, Serum, Tissue - FFPE Cassettes, Tissue – RNALater Frozen, and Tissue - Snap Frozen. Please note that use of biospecimens in genetic research is subject to a tiered consent. Objectives: The LTRC was a biobank resource established by the NHLBI to collect and distribute lung tissue, blood samples, clinical data, and radiographic studies from participants with chronic obstructive pulmonary disease (COPD), idiopathic pulmonary fibrosis (IPF), other related idiopathic interstitial pneumonias (IIP) and interstitial pneumonias associated with connective tissue diseases who undergo medically-indicated lung resection. All tissue and blood specimens and clinical data were banked centrally and stored for distribution to external investigators who have approved study proposals to investigate the pathogenesis or management of lung diseases. The ultimate goal of this program was to enable research that illuminates the pathobiology of lung diseases and leads to novel interventional treatments for these conditions. Background: Chronic lung diseases are a main cause of death and disability in the United States. COPD affects over 14 million individuals in the United States and represents the third leading cause of mortality. Cigarette smoking is a major risk factor. However, only one of six individuals who smoke develops COPD. This could imply either an individual susceptibility or an additional immunologic or infectious injury to lung cells. Current treatments offer symptomatic relief, but do not prevent disease progression. Better understanding of disease pathogenesis, including the potential roles of lung parenchymal cell apoptosis, immunologic injury, and inflammation may lead to therapies that improve survival and quality of life. Interstitial pneumonias, including IPF and those associated with connective tissue disease, are less common than COPD, but for many of these diseases there are poor outcomes. For example, IPF has a 50% survival rate 2-3 years following diagnosis, and currently no treatment exists which prolongs survival. The prevalence of IPF is approximately 28 cases per 100,000. The underlying histology of IPF is usual interstitial pneumonia (UIP), which can also occur in connective tissue diseases. The incidences of other interstitial pneumonias such as non-specific interstitial pneumonia (NSIP) or acute interstitial pneumonia (AIP) are less frequent but also occur as an expression of interstitial lung disease in the connective tissue diseases. Moreover, there is significant crossover of these three interstitial pneumonias so that cases of IPF/UIP may also reveal fibrotic NSIP and be complicated by episodes of AIP. This implies common injuries but dissimilar histological responses. All of these processes are characterized by epithelial injury, uncontrolled fibroproliferation and the deposition of collagen, irrespective of the histology. It is clear that a better understanding of the genesis of the interstitial pneumonias is required before effective interventions can be developed. Participants: A total of 4,486 participants were enrolled, and lung tissue was obtained from 3,333 of these participants.Design: Written informed consent of each participant was required before any LTRC procedure was performed. Phenotypic data were then obtained that included recording of relevant medical information, a limited exposure history, radiological evaluation, and pulmonary physiological and lung function testing. Questionnaires were administered to determine the extent of symptoms, associated medical illnesses, smoking, environmental and occupational exposures, and quality of life. Laboratory testing included pulmonary function testing, a six-minute walk test, and chest x-ray CT. Blood specimens were collected both for defining the clinical phenotype of donors and to obtain serum, plasma, and DNA for later investigative purposes. At the time of surgery, lung tissues were collected and processed for long-term storage. The LTRC collected only the 'non-tumorous' portions of lung tissue from surgical procedures performed for primary or metastatic lung tumors and received those specimens only after the local pathologist had procured all tissue required for clinical care. Samples of appropriate size were cut and placed in formalin, RNAlater, glutaraldehyde, or liquid nitrogen within 30 minutes of excision (approximately 5% of cases exceeded this target time). Blood and tissue specimens were subsequently shipped to a central Tissue Repository for further processing and long-term storage. A Radiology Center provided quality control and quality assessment of CT data. A Data Coordinating Center managed study operations and maintained a repository of study data. Conclusions: LTRC established a biospecimen collection that is unique in its size, diseases included, standardization of methods, and extent of phenotypic data, serving as a valuable resource to facilitate research on the pathobiology of lung diseases.

  Study phs003913

• Myelodysplastic Syndrome Follow Up Series

  Agilent whole exome hybridisation capture was performed on genomic DNA derived from MDS and matched normal DNA from the same patients. Next Generation sequencing performed on the resulting exome libraries and mapped to build 37 of the human reference genome to facilitate the identification of novel cancer genes. Now we aim to discover the prevalence of our findings using bespoke pulldown methods and sequencing the products from a larger set of patient DNA.

  Dataset EGAD00001000283

• Cambridge_INTERVAL_SomaLogic_pQTLs

  This dataset contains four data files relating to the Cambridge Interval SomaLogic pQTL study to go with the corresponding genetic data: (1) Genome-wide pQTL summary associations for each analyte. (2) Mapping table for the genetic variants analysed - containing rsID, position and allele information. (3) Normalised quantitative readouts for each analyte, along with covariates used for the pQTL analysis. (4) Table of SOMAmer analytes mapped to their protein targets. Please see the readme file in the dataset for more information.

  Dataset EGAD00001004080

• Phase II Trial with Correlative Genomic Analysis of Durvalumab plus Pazopanib Combination in Patients with Advanced Soft Tissue Sarcomas

  This study includes an open-label, phase 2 study to determine the activity of the anti-VEGF receptor tyrosine-kinase inhibitor, pazopanib, combined with the anti-PD-L1 immune checkpoint inhibitor, durvalumab, in unselected advanced sarcomas. We conducted whole exome and transcriptomic sequencing with pre-treatment tissue biopsy to correlate clinical outcomes with molecular and genomic biomarkers to identify patients who would most likely benefit from the combination treatment.

  Dataset EGAD50000000114

• Bulk Iso-Seq from brain tissue and exosomes isolated from brain tissue using long-read PacBio sequencing of poly-adenylated transcripts

  Human brain sEVs were isolated from postmortem human brain tissue. RNA was extracted from both the source brain tissue and sEVs and prepared for long-read sequencing. cDNA was sequenced on the PacBio Sequel II. The data provided have undergone processing using the tool ccs (v6.0.0) to generate circula consensus reads. For further processing, it is recommended to follow the guidelines at https://isoseq.how/, starting with using lima to remove cDNA primers.

  Dataset EGAD50000000043

• National Heart, Lung, and Blood Institute (NHLBI) Bench to Bassinet Program: The Pediatric Cardiac Genetics Consortium (PCGC)

  Multi-center, prospective observational cohort study of individuals with congenital heart defects (CHD). Phenotypic data and source DNA derived from 10,000 probands, parents, and families of interest are being collected to investigate relationships between genetic factors and phenotypic and clinical outcomes in patients with CHD.

  Study phs000571

• Molecular Epidemiology of Colorectal Cancer (MECC) Metastasis Study: A Germline Variant on Chromosome 4q31.1 Associates with Susceptibility to Developing Colon Cancer Metastasis

  This study compared Ashkenazi Jewish individuals with Stage IV metastatic colon cancer to those with non-metastatic Stage I or II colon cancers. A genome-wide association study, using a 2-stage design, identified a significant association with rs60745952.

  Study phs001045

• WES data of pediatric cancer patients with P/LP variants in HBOC-related genes

  The current study aimed to identify (likely) pathogenic germline variants(LP/PVs) in 25 adult-onset HBOC-related genes within a cohort of 372 pediatric cancer patients. For this purpose we performed (paired-end) whole exome sequencing (WES) using Ilumina sequencing technology. The files uploaded here belong to the 27 individuals with such a LP/PV. The project provides insight into the prevalence and spectrum of such variants in childhood cancer, contributing to the understanding of genetic predisposition in pediatric oncology.

  Dataset EGAD50000001561

• Trial of Onco-Panel for Geneprofiling to Estimate both Adverse events and Response by cancer treatment (TOP-GEAR)

  Bam files and fastq files in a hospital-based prospective study (TOP-GEAR project, the 2nd stage) to investigate the feasibility and utility of NGS-based analysis of 114 cancer-associated genes (the NCC Oncopanel test). DOI: 10.1111/cas.13969

  Study JGAS000662

• Targeted panel sequencing of two patient-derived melanoma cell lines

  Targeted panel sequencing was conducted on patient-derived cell lines: Mel-DCC-11 (the parental line, sensitive to the BRAF inhibitor) and Mel-DCC-11-R (resistant to the BRAF inhibitor). The parental cell line was generated from disseminated cancer cells (DCCs) obtained from a lymph node sample of a melanoma patient. The resistant cell line was generated from the parental one through exposure to Vemurafenib. Normal peripheral blood lymphocytes from the same patient served as the control for comparison. Sequencing on NovaSeq6000. Fastq files.

  Dataset EGAD50000001745

• Enzymatic methylation sequencing of rectal mucus from patients suspected to have colorectal cancer

  This dataset contains comprises enzymatic methylation sequencing (EM-Seq) data generated from 208 rectal mucus samples from patients suspected to have colorectal cancer and healthy controls. Targeted CpG sites were enriched using a panel of genes implicated in colorectal cancer, and libraries were prepared with NEBNext EM-Seq prior to Illumina sequencing. Sequencing was performed on the Illumina NovaSeq6000 platform, producing paired-end FASTQ files. These data support analyses of DNA methylation patterns in CRC detection and progression

  Dataset EGAD50000001871

• We performed whole exome sequencing (WES) using Hiseq on 22 paired CMLs. We also performed whole exome sequencing (WES) using CG on 88 paired CMLs. All the data belongs to CML in China - ICGC project.

  We performed whole exome sequencing (WES) using Hiseq on 22 paired CMLs. We also performed whole exome sequencing (WES) using CG on 88 paired CMLs.All the data belongs to CML in China - ICGC project.

  Study EGAS00001001742

• ENU-LS-411N-TripleTherapy

  BRAF V600E colorectal cancers do not respond to the only currently FDA approved targeted therapy for CRC. There is currently a trial underway in the UK recruiting V600E CRC patients for treatment with a triple therapy combination of Cetuximab, Trametinib and Dabrafenib. We have mutagenized a pool of V600E CRC cell lines and treated with this triple therapy to select out drug resistant clones. We will now sequence these drug resistant clones with the aim of identifying common point mutations engendering resistance to this new therapy.

  Dataset EGAD00001002051

• FinHer Breast Cancer Study

  The purpose of this study is to sequence 500 known cancer genes in 960 newly diagnosed high risk breast cancer patients treated with current standard of care therapies and trastuzumab, for somatic alteration and copy number changes. We will be using next gen sequencing technology to determine the prognostic relevance of these somatic genetic alterations and of teh low frequency events to determine if they are associated with trastuzumab benefit or HER2 positive breast cancer, i.e. treatment interaction. The samples will be analysed adn correlated with clinical variables including outcome.

  Dataset EGAD00001000871

• Mutational Signatures of relapse in rectal cancer FFPE samples in the CR07 clinical trial

  The CRO7 clinical trial recruited patients with clinically operable rectal adenocarcinoma. Patients were randomized to either pre-operative short course surgery followed by chemo-radiotherapy only in those patients at high risk of local relapse. Patients in both arms the received standard %-FU based adjuvant chemotherapy as per local policy. We intend to use FFPE derived DNA from the primary tumours to identify patterns of mutations or copy number alterations that are predictive of local or distant relapse.

  Dataset EGAD00001000875

• Non-ADT METs ICGC Prostate UK

  To characterize the subclonal genomic architecture of non-androgen-deprived metastatic prostate cancer, we performed whole-genome sequencing (WGS) of pelvic lymph node metastases and matching noncancerous blood from 10 patients to an average sequencing depth of 55x. The patients are part of PELICAN (Project to ELIminate Lethal Cancer) study led by G. Steven Bova at Johns Hopkins University (USA) and Tampere University (Finland). As of September 2020, study using these data is: Wedge et al, Nature Genetics 2018 (PMID: 29662167)

  Dataset EGAD00001002002

• Indonesian Genome Diversity Project

  High-coverage whole genome sequences were collected to study patterns of genomic variation across the broad geography of Indonesia and New Guinea. This region has experienced an extremely complex demographic history, including repeated bouts of admixture with archaic and modern human groups. We have sequenced the genomes of 161 individuals from 14 populations spanning this geographical region, from communities close to mainland Asia through to New Guinea.

  Dataset EGAD00001004156

• Whole exome sequencing of young onset Primary Sclerosing Cholangitis

  Primary sclerosing chloangitis is a rare autoimmune disease of the liver (prevalence =10/100,000) with a mean age of onset of 40 years. We are currently undertaking GWASand immunochip experiments to identify loci underlying PSC susceptibility. Through ourcollaborators at the University of Calgary we have access to DNA from three parent-offspringtrios where the children required liver transplants due to PSC before the age of 9. These areextremely rare cases indeed and we believe that exome-sequencing represents a powerfulmeans of identifying the causal mutation underlying this severe phenotype.

  Dataset EGAD00001000671

• Translation of non-canonical open reading frames as a cancer cell survival mechanism in childhood medulloblastoma - RNA-Seq

  This study aims to investigate the dysregulation of RNA translation and identify functional non-canonical open reading frames (ORFs) as potential targets for medulloblastoma treatment. The study involves ribosome profiling and RNAseq of medulloblastoma tissues and cell lines to observe the translation of non-canonical ORFs. Multiple CRISPR-Cas9 screens will be used to identify functional non-canonical ORFs implicated in medulloblastoma cell survival.

  Dataset EGAD00001011192

• 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

• WGS of primary mesothelioma cell lines

  Mesothelioma is an aggressive cancer associated with previous exposure to asbestos and dismal prognosis. Since a pemetrexed/cisplatin combination was introduced for treatment of mesothelioma, no new first- or second-line therapies have been discovered. Thus, to better understand what drives mesothelioma carcinogenesis and to identify potential targets for therapy, in this project we aim at performing WGS analysis of a panel of mesothelioma cells lines.

  Dataset EGAD00001009641

• Genomic profiling of Follicular thyroid adenomas and carcinomas using exome-sequencing analyses

  This dataset was conceived to characterize the genomic differences among different types of follicular-like thyroid lesions. To do so, we performed whole exome sequencing experiments on human biopsies corresponding to nodular hyperplasias, follicular thyroid adenomas, follicular thyroid carcinomas and Follicular Variant Thyroid Gland Papillary Carcinomas.

  Dataset EGAD00001008022

• ESR1 mutations in tamoxifen-associated endometrial cancer versus spontaneous arisen endometrial tumors

  An increased incidence of endometrial cancer has been described for patients that have received tamoxifen to treat breast cancer. Using samples from endometrial tumors, isolated from surgivcal specimens of patients who previously received tamoxifen treatment for breast cancer, we aimed to identify whether there are specific somatic mutations enriched in this population, relative to endometrial tumors from the general population. For this, WES was performed on matched endometrial tumors and healthy tissue (n=21).

  Dataset EGAD00001009088