9338 results for "cancer rna-seq"

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• Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) - OncoArray Genotypes

  Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) was one of five projects funded in 2010 as part of the NCI's Genetic Associations and Mechanisms in Oncology (GAME-ON) initiative (http://epi.grants.cancer.gov/gameon/). GAME-ON's overall goal was to foster an intra-disciplinary and collaborative approach to the translation of promising research leads deriving from the initial wave of cancer GWAS. Specific goals included replication of previous GWAS findings and identification of new susceptibility loci through meta analyses of existing GWAS data and fine mapping of identified loci to better pinpoint causal variants; and identify germline variants that are associated with risk of multiple cancers. The other four funded GAME-ON projects were: the ColoRectal TransdisciplinaryStudy (CORECT), Elucidating Loci Involved in Prostate Cancer Susceptibility (ELLIPSE), Follow-up of Ovarian Cancer Genetic Association and Interaction Study (FOCI), and Transdisciplinary Research in Cancer of the Lung (TRICL). To identify additional cancer risk loci, improve the precision of fine-mapping, and facilitate cross-cancer analyses, the GAME-ON projects and other consortia formed the OncoArray network (http://epi.grants.cancer.gov/oncoarray/), which developed and genotyped a new custom genotyping array (the "OncoArray") in large numbers of cancer cases and controls (over 400,000 samples). The OncoArray is a custom array manufactured by Illumina. The array includes a backbone of approximately 260,000 SNPs that provide genome-wide coverage of most common variants, together with markers of interest for each of the five GAME-ON cancers identified through genome-wide association studies (GWAS), fine-mapping of known susceptibility regions, sequencing studies, and other approaches. The array also includes loci of interest identified through studies of other cancer types, and other loci of interest to multiple cancer types (including loci associated with cancer related phenotypes, drug metabolism and radiation response). Additionally, SNPs relating to quantitative phenotypes such as body mass index (BMI), height, and breast density that correlate with common cancer risks are also included. The DRIVE data included under this dbGAP submission include OncoArray data from 60,015 breast cancer cases and controls genotyped at the Center for Inherited Disease Research (CIDR), University of Cambridge, National Cancer Institute, University of Copenhagen, University of Southern California and Mayo Clinic. Details on an additional approx. 80,000 breast cancer cases and controls genotyped at other centers can be found at http://bcac.ccge.medschl.cam.ac.uk/bcacdata/oncoarray/.

  Study phs001265

• Genomic-Enabled Medicine for Recurrent Glioblastoma

  In this prospective study, we performed genome-wide tumor/normal exome sequencing and tumor RNA-sequencing for recurrent glioblastoma patients. A subset of patients had both enhancing tumor and non-enhancing tissue sequenced to investigate spatial heterogeneity of this disease. Together, this information builds our understanding of the genomic underpinnings of glioblastoma, and contributes toward the knowledge base for identifying and developing more effective treatments for patients with glioblastoma.

  Study phs001460

• Pilot Sequencing Study: DNA Hydroxymethylation and Gene Expression in Peripheral Blood Mononuclear Cells in Healthy Human Aging

  This study was a pilot analysis of samples of human peripheral blood mononuclear cell (PBMCs) from 10 young (23-30 years) and 10 older (68-76 years) healthy Caucasian female volunteers. Whole genome sequencing was performed to assess multiple epigenetic mechanisms and gene expression, including 5hmC-capture sequencing and RNA-sequencing, followed by integrative analyses to identify regions and genes associated with age.

  Study phs001916

• Cellular Origins and Genetic Landscape of Cutaneous GD T Cell Lymphoma

  Cutaneous gamma-delta T cell lymphomas are a rare and aggressive subtype of cutaneous lymphoma. In the present study, we analyzed these cancers by DNA and RNA sequencing in order to illuminate the genetic landscape for this rare disease. We obtained tumor samples from multiple institutions, including Northwestern University (Chicago, IL), University of Chicago (Chicago, IL), University of Virginia (Charlottesville, VA), and Massachusetts General Hospital (Boston, MA).

  Study phs001969

• MicroRNA Biomarkers for Prediction of Preeclampsia

  Maternal serum was collected between 17-28 weeks gestation. Samples were obtained from the high-risk Placental Study at the University of California, San Diego (n=48) and from the average-risk Proteomic Assessment of Preterm Risk (PAPR) Study at Sera Prognostics (n=164). RNA was extracted from 500 microliter of maternal serum using the miRNeasy Micro kit (Qiagen). NEBNext Small RNAseq Library Preparation Kit was used for library construction.

  Study phs002016

• HG Transcriptome sequencing in the INTERVAL cohort

  We performed bulk RNA-sequencing on peripheral blood collected from 4,732 blood donors recruited as part of the INTERVAL study. Using these data, we mapped gene expression and splicing quantitative trait loci (QTLs). Then, we integrated these data with protein, metabolite and lipid QTLs in the same individuals. The study aimed to identify the shared genetic etiology across transcriptional phenotypes, molecular traits and health outcomes in humans.

  Study EGAS00001003346

• Multiomics Characterization of Low-grade Serous Ovarian Carcinoma

  Low-grade serous ovarian carcinoma (LGSOC) is a rare tumor subtype with high case fatality rates. There is a pressing need to develop effective treatments using newly available preclinical models for therapeutic discovery and drug evaluation. In this study, we use multiomics integration of whole exome sequencing, RNA sequencing, and mass spectrometry-based proteomics on fourteen LGSOC patient derived cell lines to elucidate novel biomarkers and therapeutic vulnerabilities.

  Study EGAS00001004724

• SPECIAL: Dissecting the melanoma ecosystem one cell at the time during immunotherapy

  The aim of this study was to identify potential biomarkers of response to immunotherapy (anti-PD1-based) as well as gain understanding of the biological mechanism of therapy resistance (either intrinsic or acquired) in melanoma patients. Single cell RNA sequencing was performed from pre- and on-treatment (2-3 weeks after immunotherapy) metastatic biopsies from stage III and IV melanoma patients.

  Study EGAS00001006488

• RNA_expression_profiling_of_melanoma_patient_derived_xenograft

  Patient-derived xenografts (n=96) were derived from metastatic melanoma patients. RNA expression profiling will be preformed to study 1. HLA-typing and 2. the effect of the tumour microenvironment on tumour growthThis 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/

  Study EGAS00001001537

• RNAseq Iron-Treated iPSC-derived Microglia

  Iron accumulation in microglia has been observed in Alzheimer’s disease and other neurodegenerative disorders and is thought to contribute to disease progression through various mechanisms including neuroinflammation. To study the interaction between iron accumulation and inflammation, we treated human induced pluripotent stem cell-derived microglia (iPSC-MG) with an increasing concentration of iron, in combination with inflammatory stimuli such as interferon gamma and amyloid β, and performed RNA sequencing.

  Study EGAS00001006112

• Somatic L1 retrotranspositions in normal human cells

  Genomic mutations accumulate in normal cells during lifetime; however, somatic mosaicism generated by mobilization of transposable elements is not well understood. Here, we explored whole-genome sequences of single-cell expanded clones to illustrate the mutational landscape produced by L1. In addition, we analyzed promoter DNA methylation status of retrotransposition-competent L1 and read-through RNA expression profiles to investigate the epigenetic regulation of L1 activity.

  Study EGAS00001006213

• Gene expression by RNAseq in bronchial biopsies of asthmatics, asthma in remission and healthy subjects

  The study focus was differential expression in bronchial biopsies between persistent asthma, asthma in remission and healthy controls using RNAseq. There were 184 samples that passed QC. RNA samples were processed using the TruSeq Stranded Total RNA Sample Preparation Kit (Illumina, San Diego, CA), using an automated procedure in a Caliper Sciclone NGS Workstation (PerkinElmer, Waltham, MA). In this procedure, all cytoplasmic and mitochondria rRNA was removed (RiboZero Gold kit). The obtained cDNA fragment libraries were loaded in pools of multiple samples unto an Illumina HiSeq2500 sequencer using default parameters for paired-end sequencing (2 × 100 bp). Data are available as 221 pairs of FASTQ-files. Note that several samples are associated with multiple sequence runs.

  Dataset EGAD00001005112

• African American Breast Cancer GWAS

  The GWAS includes African American participants from 9 epidemiological studies of breast cancer, comprising a total of 3,153 cases and 2,831 controls (cases/controls: The Multiethnic Cohort Study (MEC), 734/1,003; The Los Angeles component of The Women's Contraceptive and Reproductive Experiences (CARE) Study, 380/224; The Women's Circle of Health Study (WCHS), 272/240; The San Francisco Bay Area Breast Cancer Study (SFBCS), 172/231; The Northern California Breast Cancer Family Registry (NC-BCFR), 440/53;The Carolina Breast Cancer Study (CBCS), 656/608; The Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO) Cohort, 64/133; The Nashville Breast Health Study (NBHS), 310/186; and, The Wake Forest University Breast Cancer Study (WFBC), 125/153). Quality control of the GWAS data and additional details can be found in Chen et al. Hum Genet. 2013 (PMID: 22923054)

  Study phs000851

• PanProstate Cancer Group UK data

  THE PAN PROSTATE CANCER PROJECT: Many groups around the world have generated Whole Genome DNA Sequence (WGS) data from prostate cancer patients. The pan prostate group have gathered with the idea that the accumulated data, should be collected and compared in a common format including common storage, re-analysis through a single pipeline, and investigation to achieve a variety of scientific goals. The combined collection would include the following categories: (i) cancers from different ethnic groups: eg Caucasian, Asian, Black Caribbean; (ii) cancer from different stages of progression from normal, to organ-confined disease, to metastases; (iii) early-onset prostate cancer; (iv) prostate cancer from aggressive and indolent disease; and (v) prostate cancer patients managed by different treatments with information linked to long-term clinical follow up data in many cases.This study contains the initial pilot samples (train 1) from the CRUK-ICGC prostate group.

  Study EGAS00001002876

• germline variants in children with hematological cancer

  Trio parent-child whole exome sequencing has been used to identify cancer predisposing syndrome (CPS) in our pediatric patients with hematological cancer, and it was identified in 3.8% of the total number of patients(131).

  Study EGAS00001006907

• SNP array datas of 'Matched' cancer/PNE

  SNP array data of 31 Matched cancer/PNE samples

  Study EGAS00001003331

• Metformin for Oral Cancer Prevention

  The M4OC-PREVENT clinical trial addressed whether metformin has utility in the prevention of oral cancer. It is a phase IIa clinical trial of metformin ER 2,000 mg per day given for 12-14 weeks to individuals with oral premalignant lesions, either oral leukoplakia or erythroplakia (which are precursors to oral cancer). The goal was to determine if metformin decreases the size of oral leukoplakia (clinical response). Additionally, effects on biomarkers of cancer risk and metformin effect were ascertained. The clinical trial was performed at the University of California San Diego Moores Cancer Center, the University of Minnesota, and the British Columbia Cancer Agency, with monitoring and oversight provided by the University of Arizona.

  Study phs002437

• Chugai_colorectal_organoid_sequencing

  Genomic and transcriptomic characterization of drug-resistant colon cancer stem cell lines.

  Study EGAS00001000872

• 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

• RNA Sequencing of human fetal brain (FBSeq)

  FastQ files with paired-end RNAseq data for human fetal brain homogenate from 120 samples (12-19 post-conception weeks).

  Dataset EGAD00001004363

• Lymphocyte RNA profiling

  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 EGAD00001002183

• Hypoxia acts as an environmental cue for the human TRM differentiation program

  Dataset consists of 19 bam files from RNA sequencing experiments batch1 and batch2.

  Dataset EGAD00001007692

• Presence of bacterial infection in brains of patients with Huntington's disease (HD)

  Bacterial isolation in infected brains in patients with Huntington's disease. Here we used next generation sequencing of 16S ribosomal RNA gene PCR amplicons (NGS 16S amplicon analysis)

  Dataset EGAD00001005996

• B15PON dataset

  Organoid cultures derived from normal colon and/or colorectal adenomas and/or colorectal carcinomas. RNA and DNA was isolated from these cultures for genome wide profiling.

  Dataset EGAD00001008411

• Etiological Investigation of Cancer Susceptibility in Inherited Bone Marrow Failure Syndromes: A Natural History Study

  Background: A prospective cohort of Inherited Bone Marrow Failure Syndrome (IBMFS) will provide new information regarding cancer rates and types in these disorders. Mutations in IBMFS genes are relevant to carcinogenesis in sporadic cancers. Patients with IBMFS who develop cancer differ in their genetic and/or environmental features from patients with IBMFS who do not develop cancer. These cancer-prone families are well suited for cancer screening and prevention trials targeting those at increased genetic risk of cancer. Carriers of IBMFS gene mutations are at increased risk of cancer. The prototype disorder is Fanconi Anemia (FA); other IBMFS will also be studied. Objectives: To determine the types and incidence of specific cancers in patients with an IBMFS. To investigate the relevance of IBMFS gene mutations in the carcinogenesis pathway of the sporadic counterparts of IBMFS-associated cancers. To identify risk factors for IBMFS-related cancers in addition to the primary germline mutations. To determine the risk of cancer in IBMFS carriers. Design: Natural history study, with questionnaires, clinical evaluations, clinical and research laboratory tests, review of medical records, cancer surveillance. Primary endpoints are all cancers, solid tumors, and cancers specific to each type of IBMFS. Secondary endpoints are markers of pre-malignant conditions, such as leukoplakia, serum or tissue evidence of carcinogenic viruses, and bone marrow morphologic myelodyplastic syndrome or cytogenetic clones.

  Study phs001481