Search Results - EGA European Genome-Phenome Archive

ELLIPSE Prostate Cancer Meta-Analysis and Genotyping

The ELLIPSE Consortium is an international effort to discover risk loci for prostate cancer. It includes the meta-analysis of existing GWAS data as well as novel GWAS, exome, and iCOGS genotyping. The GWAS meta-analysis includes the following cases and controls from studies of European ancestry: UK GWAS stage 1 (Illumina Infinium HumanHap 550 Array: 1854 cases and 1894 controls), UK GWAS stage 2 (Illumina iSELECT: 3706 cases and 3884 controls), CAPS1 (Affymetrix GeneChip 500K: 474 cases and 482 controls), CAPS2 (Affymetrix GeneChip 5.0K: 1458 cases and 512 controls), BPC3 (Illumina Human610 Illumina: 2068 cases and 3011 controls), PEGASUS (HumanOmni2.5: 4600 cases and 2941 controls). The OMNI 2.5M genotyping was conducted for 977 prostate cancer cases from UKGPCS. The Exome SNP array genotyping was conducted for 4741 subjects from UKGPCS. The iCOGs genotyping was conducted for 10366 subjects which includes the Multiethnic Cohort (n=1648) and UKGPCS (n=8718). Below is a description of each study that contributed to the meta-analysis of men of European ancestry. Information about the studies that contributed to the multiethnic meta-analysis can be found on the associated study page and also in Conti et al (Nature Genetics, PMID:33398198).   UK GWAS Stage 1 (UK1) and Stage 2 (UK2): The UK Genetic Prostate Cancer Study (UKGPCS) was first established in 1993 and is the largest prostate cancer study of its kind in the UK, involving nearly 189 hospitals. We are based at The Institute of Cancer Research in Sutton, Surrey, and collaborate with the Royal Marsden NHS Foundation Trust. Our aim is to find genetic changes which are associated with prostate cancer risk. Our target is to recruit 26,000 gentlemen into the UKGPCS by 2017. Men are eligible to take part if they fit into at least one of the following groups: They have been diagnosed with prostate cancer at 60 years of age or under (up to their 61st birthday). They have been diagnosed with prostate cancer and a first, second or third degree relative where at least one of these men were diagnosed with prostate cancer at 65 years of age or under. They are affected and have 3 or more cases of prostate cancer on one side of their family. They are a prostate cancer patient at the Royal Marsden NHS Foundation Trust. We have to date recruited around 16,000 men on whom we have germline DNA and clinical data at diagnosis. The UK GWAS is based on genotyping of 541,129 SNPs in 1,854 individuals with clinically detected (non-PSA-screened) prostate cancer (cases) and 1,894 controls. 43,671 SNPs showing strong evidence of association in stage 1 were followed up by genotyping a further 3,268 cases and 3,366 controls from UK and Melbourne in stage2. CAPS1 and CAPS2: The CAPS (Cancer of the Prostate in Sweden) study represents a large Swedish population-based cancer study, comprising 3,161 cases and 2,149 controls, recruited between 2001 and 2003. Biopsy confirmed prostate cancer cases were identified and recruited from four out of six regional cancer registries in Sweden, diagnosed between July 2001 and October 2003. Clinical data including TNM stage, Gleason grade and PSA levels at time for diagnosis were retrieved through record linkage to the National Prostate Cancer Registry. Control subjects, who were recruited concurrently with case subjects, were randomly selected from the Swedish Population Registry and matched according to the expected age distribution of cases (groups of 5-year intervals) and geographic region. Whole blood was collected from all individuals for extraction of genomic DNA. A GWAS was conducted in two parts. In the first phase (CAPS1) 498 cases and 502 controls were genotyped, in the second phase 1,483 cases and 519 controls were genotyped. Genotyping was performed using the GeneChip Human Mapping 500K (CAPS1) and 5.0K (CAPS2) Array Set from Affymetrix (Santa Clara, CA). The National Cancer Institute Breast and Prostate Cancer Cohort Consortium, BPC3: BPC3 was a consortium of prospective cohort studies investigating genetic and gene-environmental risk factors for breast and prostate cancer. Each study selected cases and controls for this study as described below. The clinical criteria defining advanced prostate cancer (Gleason = 8 or stage C/D) were either obtained from medical records or cancer registries. The Gleason score source was either surgical specimens (radical prostatectomy or autopsy) or the diagnostic biopsy (needle biopsy or TURP). When multiple Gleason scores were available the surgical value was used. PLCO was removed from the analysis as the samples were included in the Pegasus GWAS described below. In total 2,473 advanced prostate cancer cases and 3,534 controls were included in the analysis following QC. ATBC, Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study: ATBC was a randomized, placebo-controlled primary prevention trial to investigate whether α-tocopherol or ß-carotene supplementation reduced the incidence of lung or other cancers in male smokers. Between 1985 and 1988, 29,133 men ages 50 to 69 years were enrolled in the trial from Finland and randomized to supplementation (50 mg α-tocopherol, 20mg ß-carotene, or both) or placebo. Men with a prior history of cancer, other than non-melanoma skin cancer or carcinoma in situ, were excluded from participating. Incident cancer cases are identified through linkage with the Finnish Cancer Registry, which has ~100% ascertainment of cancer cases nationwide. Cases included 249 men diagnosed with advanced prostate cancer (Gleason = 8 or stage C/D) from 1985 to 2003 with DNA available. Controls were 1,271 men selected previously for a GWAS of lung cancer in ATBC without a diagnosis of prostate cancer. CPSII, Cancer Prevention Study II: CPSII is a cohort study started in 1982 to investigate the relationship between dietary, lifestyle and other etiologic factors and cancer mortality. Approximately 1.2 million men and women enrolled in the study from 50 states in the U.S. In 1992, a subset of these participants (n= ~184,000) were enrolled in the CPSII Nutrition Cohort to examine the relationship between dietary and other exposures and cancer incidence. Blood samples were drawn from approximately 39,376 members of the Nutritional Cohort from 1998 to 2001, and buccal cells were collected from 69,467 members from 2001 to 2002. Cancer cases are identified by self-report through follow-up questionnaires followed by verification through medical records and/or linkage to state cancer registries as well as death certificates. A total of 660 advanced prostate cancer cases (Gleason = 8 or stage III/IV) with a source of DNA were identified for this study. Controls were 660 men matched on ethnicity, date of birth, sample collection date and DNA type. EPIC, European Prospective Investigation into Cancer and Nutrition: EPIC is a prospective study designed to investigate both genetic and non-genetic risk factors for different forms of cancer. Study participants were almost all white Europeans. Approximately 500,000 individuals (150,000 men) in EPIC were recruited between 1992 and 2000, from 23 centers in 10 European countries. Overall approximately 400,000 subjects also provided a blood sample at recruitment. The methods of recruitment and details of the study design are described in detail elsewhere. In brief, study participants completed an extensive questionnaire on both dietary and nondietary data at recruitment. The present study includes subjects from advanced prostate cancer cases (Gleason = 8 or stage III/IV) matched to controls based on study center, length of follow-up, age at enrollment (± 6 months), fasting and time of day of blood collection (± 1 hour). The advanced prostate cancer subjects were from 8 of the 10 participating countries: Denmark, Germany, Greece, Italy, the Netherlands, Spain, Sweden and the United Kingdom (UK). France and Norway were not included in the current study because these cohorts only included female subjects. All participants gave written consent for the research and approval for the study was obtained from the ethical review board from all local institutions in the regions where participants had been recruited for the EPIC study. HPFS, Health Professionals Follow-up Study: HPFS began in 1986 and is an ongoing prospective cohort study of 51,529 United States male dentists, optometrists, osteopaths, podiatrists, pharmacists, and veterinarians 40 to 75 years of age. The baseline questionnaire provided information on age, marital status, height and weight, ancestry, medications, smoking history, disease history, physical activity, and diet. At baseline the cohort was 97% white, 2% Asian American, and 1% African American. The median follow-up through 2005 was 10.5 years (range 2-19 years). Self-reported prostate cancer diagnoses were confirmed by obtaining medical and/or pathology records. Prostate cancer deaths are either reported by family members in response to follow-up questionnaires, discovered by the postal system, or the National Death Index. Questionnaires are sent every two years to surviving men to update exposure and medical history. In 1993 and 1994, a blood specimen was collected from 18,018 men without a prior diagnosis of cancer. Prostate cancer cases are matched to controls on birth year (+/-1) and ethnicity. Controls are selected from those who are cancer-free at the time of the case’s diagnosis, and had a prostate-specific antigen test after the date of blood draw.   MEC, Multiethnic Cohort: The Multiethnic Cohort Study is a population-based prospective cohort study that was initiated between 1993 and 1996 and includes subjects from various ethnic groups - African Americans and Latinos primarily from Californian (great Los Angeles area) and Native Hawaiians, Japanese-Americans, and European Americans primarily from Hawaii. State drivers’ license files were the primary sources used to identify study subjects in Hawaii and California. Additionally, in Hawaii, state voter’s registration files were used, and, in California, Health Care Financing Administration (HCFA) files were used to identify additional African American men. All participants (n=215,251) returned a 26-page self-administered baseline questionnaire that obtained general demographic, medical and risk factor information. In the cohort, incident cancer cases are identified annually through cohort linkage to population-based cancer Surveillance, Epidemiology, and End Results (SEER) registries in Hawaii and Los Angeles County as well as to the California State cancer registry. Information on stage and grade of disease are also obtained through the SEER registries. Blood sample collection in the MEC began in 1994 and targeted incident prostate cancer cases and a random sample of study participants to serve as controls for genetic analyses. PHS, Physicians Health Study:PHS was a randomized trial of aspirin and ß carotene for cardiovascular disease and cancer among 22,071 U.S. male physicians ages 40-84 years at randomization; none had a cancer diagnosis at baseline. The original trial ended, but the men are followed. From 1982 to 1984, blood samples were collected from 14,916 physicians before randomization. Participants are sent yearly questionnaires to ascertain endpoints. Whenever a physician reports cancer, we request permission to obtain the medical records, and cancers are confirmed by pathology report. We obtain death certificates and pertinent medical records for all deaths. Follow-up for nonfatal outcomes in PHS is over 97% complete, and for mortality, over 99%. PLCO, Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial:PLCO is a multicenter, randomized trial to evaluate screening methods for the early detection of prostate, lung, colorectal and ovarian cancer. Between 1993 and 2001, over 150,000 men and women ages 55-74 years were recruited from ten centers in the United States (Birmingham, AL; Denver, CO; Detroit, MI; Honolulu, HI; Marshfield, WI; Minneapolis, MN; Pittsburgh, PA; Salt Lake City, UT; St. Louis, MO; and Washington, D.C.). Men randomized to the screening arm underwent prostate cancer screening with prostate-specific antigen (PSA) annually for six years and digital rectal exam annually for four years. Blood specimens were collected from participants randomized to the screening arm of the trial, and buccal cell specimens were obtained from participants randomized to the control arm. Cases included 754 men diagnosed with advanced prostate cancer (Gleason = 8 or stage III/IV) from either arm of the trial. Of these cases, 317 were genotyped previously as part of Cancer Genetic Markers of Susceptibility (CGEMS), a GWAS for prostate cancer. Controls included 1,491 men without a diagnosis of prostate cancer from the screening arm of the PLCO trial. All subjects provided informed consent to participate in genetic etiology studies of cancer and other traits. This study was approved by the institutional review boards at the ten centers and the National Cancer Institute. PLCO was removed from the meta-analysis of the BPC3 studies as a consequence of PEGASUS below. PEGASUS, Prostate cancer Genome-wide Association Study of Uncommon Susceptibility loci: Pegasus is a genome-wide association nested within the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial. PLCO is a multicenter, randomized trial to evaluate screening methods for the early detection of prostate, lung, colorectal and ovarian cancer. Between 1993 and 2001, over 150,000 men and women ages 55-74 years were recruited from ten centers in the United States (Birmingham, AL; Denver, CO; Detroit, MI; Honolulu, HI; Marshfield, WI; Minneapolis, MN; Pittsburgh, PA; Salt Lake City, UT; St. Louis, MO; and Washington, D.C.). Men randomized to the screening arm underwent prostate cancer screening with prostate-specific antigen annually for six years and digital rectal exam annually for four years. Blood specimens were collected from participants randomized to the screening arm of the trial, and buccal cell specimens were obtained from participants randomized to the control arm. Cases included 4,598 men of European ancestry diagnosed with prostate cancer from either arm of the trial and controls included 2,941 men of European ancestry without a diagnosis of cancer from the screening arm, matched on age and year of randomization. All subjects provided informed consent, and the study approved by the institutional review board at the National Cancer Institute. Funding:This work was supported by the GAME-ON U19 initiative for prostate cancer (ELLIPSE): U19 CA148537. The BPC3 was supported by the U.S. National Institutes of Health, National Cancer Institute (cooperative agreements U01-CA98233, U01-CA98710, U01-CA98216, and U01-CA98758, and Intramural Research Program of NIH/National Cancer Institute, Division of Cancer Epidemiology and Genetics). The ATBC study and PEGASUS was supported in part by the Intramural Research Program of the NIH and the National Cancer Institute. Additionally, this research was supported by U.S. Public Health Service contracts N01-CN-45165, N01-RC-45035, N01-RC-37004 and HHSN261201000006C from the National Cancer Institute, Department of Health and Human Services. CAPS: The Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden was supported by the Cancer Risk Prediction Center (CRisP; www.crispcenter.org), a Linneus Centre (Contract ID 70867902) financed by the Swedish Research Council, Swedish Research Council (grant: K2010-70X-20430-04-3), the Swedish Cancer Foundation (grant: 09-0677), the Hedlund Foundation, the Söderberg Foundation, the Enqvist Foundation, ALF funds from the Stockholm County Council. Stiftelsen Johanna Hagstrand och Sigfrid Linnér’s Minne, Karlsson’s Fund for urological and surgical research. We thank and acknowledge all of the participants in the Stockholm-1 study. We thank Carin Cavalli-Björkman and Ami Rönnberg Karlsson for their dedicated work in the collection of data. Michael Broms is acknowledged for his skillful work with the databases. KI Biobank is acknowledged for handling the samples and for DNA extraction. Hans Wallinder at Aleris Medilab and Sven Gustafsson at Karolinska University Laboratory are thanked for their good cooperation in providing historical laboratory results. UKGPCS would like to acknowledge the NCRN nurses and Consultants for their work in the UKGPCS study. We thank all the patients who took part in this study. This work was supported by Cancer Research UK (grants: C5047/A7357, C1287/A10118, C1287/A5260, C5047/A3354, C5047/A10692, C16913/A6135 and C16913/A6835). We would also like to thank the following for funding support: Prostate Research Campaign UK (now Prostate Cancer UK), The Institute of Cancer Research and The Everyman Campaign, The National Cancer Research Network UK, The National Cancer Research Institute (NCRI) UK. We are grateful for support of NIHR funding to the NIHR Biomedical Research Centre at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust. The MEC was supported by NIH grants CA63464, CA54281 and CA098758. 

Study phs001120

Circulating cell-free and extracellular vesicles-derived microRNA as prognostic biomarkers in patients with early-stage NSCLC: results from RESTING study

Lung cancer, especially non-small cell lung cancer (NSCLC), has high mortality rates. Early-stage NSCLC shows a 50% relapse rate post-surgery, with most recurrences occurring within two years and a 5-year survival of only 30%. This study focuses on the prognostic value of circulating miRNAs in surgically treated ES-NSCLC patients, aiming to assess their predictive accuracy and compare them to standard prognostic factors.

Study EGAS50000001032

Cell-free DNA methylome and fragmentome analysis for disease relapse monitoring in patients with Ewing Sarcoma

We conducted whole-genome and methylome sequencing of cfDNA from 87 serial samples of 23 patients with EwS and 3 patients with CIC-rearranged sarcoma (CIC). With EwingSign, a new machine learning model, we identified EwS or CIC in a test set for 11 out of 16 patients at diagnosis and 15 out of 18 clinically confirmed relapse events. 0 out of 24 non-cancer controls were detected positive with EwingSign.

Study EGAS50000001415

Nuclease deficiencies alter plasma cell-free DNA methylationprofiles (mouse)

The effects of DNASE1L3 or DNASE1 deficiency on cfDNA methylation was explored in plasma of mice deficient in these nucleases and in DNASE1L3-deficient humans. Compared to wildtype cfDNA, cfDNA in Dnase1l3-deficient mice was significantly hypomethylated, while cfDNA in Dnase1-deficient mice was hypermethylated. The cfDNA hypomethylation in Dnase1l3-deficient mice was due to increased fragmentation and representation from open chromatin regions (OCRs) and CpG islands (CGIs). These findings were absent in Dnase1-deficient mice.

Study EGAS00001004696

Nuclease deficiencies alter plasma cell-free DNA methylationprofiles (Human)

The effects of DNASE1L3 or DNASE1 deficiency on cfDNA methylation was explored in plasma of mice deficient in these nucleases and in DNASE1L3-deficient humans. Compared to wildtype cfDNA, cfDNA in Dnase1l3-deficient mice was significantly hypomethylated, while cfDNA in Dnase1-deficient mice was hypermethylated. The cfDNA hypomethylation in Dnase1l3-deficient mice was due to increased fragmentation and representation from open chromatin regions (OCRs) and CpG islands (CGIs). These findings were absent in Dnase1-deficient mice.

Study EGAS00001004897

Circulating Tumor DNA Analysis Profiles of Repotrectinib in NTRK fusion–positive advanced solid tumors: a phase 1/2 trial

The dataset contains circulating tumor DNA (ctDNA) profiles from frozen plasma samples of 593 patients from the TRIDENT-1 clinical trial. Plasma was processed with centrifugation and automated liquid handling systems, and cell-free DNA was extracted using the Qiagen QIAsymphony platform. ctDNA libraries were constructed with the Guardant360 2.11 assay, which used targeted, hybridization-based capture and barcoding of cfDNA fragments for digital analysis, followed by high-throughput sequencing on the Illumina NextSeq 550 instrument. Sequencing data were processed and interpreted using the Bioinformatics Pipeline (BIP v3.5.2 or later) for variant calling and quantification and managed within LabVantage LIMS (v3.7 or later) to support sample tracking and workflow integration. Aligned read files are provided in bam and bai formats.

Dataset EGAD50000002249

Indonesian Microbiome Ecology and Evolution v1 (raw data)

This dataset comprises 124 human faecal samples collected across Indonesia between 2015 and 2021, together with 6 controls. It was collected to study patterns of human microbiome variation across Indonesia’s diverse geography and lifestyles, and to generate the Indonesian Microbiome Ecology and Evolution (IndoMEE) metagenome-assembled genome (MAG) reference database. The dataset consists of 250 bp paired-end metagenomic reads from 124 faecal samples acquired from 116 individuals, at ca. 10.6 Gb / sample, together with 2 positive controls (ZymoBIOMICS Microbial Community DNA Standard by Zymo Research Cat# D6305), and 4 negative controls (for sampling: Blank, for extraction: Buffer EB by Qiagen Cat# 19086, for library prep: Nuclease Free Water by Ambion-Invitrogen Cat# AM9937). Library preparation was carried out using Illumina's TruSeq DNA Nano DNA kit, and sequencing was performed on the Illumina NovaSeq 6000 platform.

Dataset EGAD50000001399

Whole genome and transcriptome sequencing of cancer of unknown primary tumours

Whole genome and transcriptome sequencing of cancer of unknown primary tumours was used to determine yield of clinical biomarkers for a molecular guided trial or for resolving cancer type of origin. This study includes profiling of germline DNA and tumour DNA and RNA by whole genome and transcriptome sequencing. All samples are in BAM format aligned with GRCh38 reference genome. This dataset includes: 1. Whole genome sequencing (WGS) of 78 cancer of unknown primary tumour samples and 73 matched germline DNA. 2. Whole transcriptome sequencing (WTS) of 69 cancer of unknown primary tumour samples (matched to WGS cases) 3. Whole genome sequencing of 22 cell-free DNA samples from cancer of unknown primary patients and matched Germaine DNA(8 samples matched to tumour WGS)

Dataset EGAD50000000656

The G2 gene expression signature and MYC overexpression are independent poor prognostic factors in childhood high-grade osteosarcoma

Key objective Are the prognostic transcriptomic G1/G2 gene expression signature, MYC overexpression, and MYC amplification replicable stratifying biomarkers for future clinical trials in high-grade osteosarcoma? Knowledge gathered In an unselected cohort, the G2 gene expression signature and MYC overexpression, but not MYC amplification, were independently associated with poor event-free and overall survival. Relevance Transcriptomic biomarkers may serve as stratifying factors that guide the management of patients with high-grade osteosarcoma. Current data underlines the importance of prospective validation of the G1/G2 signature and MYC overexpression in an international, multicenter, study.

Dataset EGAD00001015503

IYDP Indonesian Y chromosome Diversity Project

The IYDP dataset includes BAM files of 126 Y chromosomes extracted from whole genome sequences. These are from individuals from a broad range of Indonesian islands - communities close to mainland Asia through to New Guinea. The original whole genome sequencing libraries were prepared using TruSeq DNA PCR-Free and TruSeq Nano DNA HT kits depending on DNA quantity. 150 bp paired-end sequencing was performed on the Illumina HiSeq X sequencer. Individuals were sequenced to expected mean depth of 30x, with an achieved median depth of raw reads across samples of 43x.

Dataset EGAD00001008573

WGBS data (CancerLocator study) of cell-free DNA derived from human blood

The blood samples of eight lung cancer patients and one benign lung tumor patient are collected for this dataset. Blood samples were centrifuged first at 1,600 × g for 10 minutes, and then the plasma was transferred into new micro tubes and centrifuged at 16,000 × g for another 10 minutes. The plasma was collected and stored at -80⁰C. CfDNA was extracted from 5 ml plasma using the Qiagen QIAamp Circulating Nucleic Acids Kit and quantified by Qubit 3.0 Fluoromter (Thermo Fisher Scientific). Bisulfite conversion of cfDNA was performed by using EZ-DNA-Methylation-GOLD kit (Zymo Research). After that, Accel-NGS Methy-Seq DNA library kit (Swift Bioscience) was used to prepare the sequencing libraries. The DNA libraries were then sequenced with 150bp paired-end reads.

Dataset EGAD00001003168

Unrelated Donor Reduced Intensity Bone Marrow Transplant for Children with Severe Sickle Cell Disease (BMT CTN-0601-BioLINCC)

ObjectivesThe primary objective is to determine event-free survival (EFS) at 1 year after unrelated donor (URD) hematopoietic stem cell transplantation (HCT) using bone marrow (BM) in patients with sickle cell disease (SCD).BackgroundSickle cell disease (SCD), also known as sickle cell anemia, is an inherited blood disease that can cause organ damage, stroke, and intense pain episodes. Children with sickle cell disease experience organ damage, impaired quality of life, and premature mortality. A blood stem cell transplant is a treatment option for someone with a severe form of the disease. Prior to undergoing a transplant, people typically receive a conditioning regimen of high doses of chemotherapy and other medications to prepare the body to accept the transplant. This type of conditioning regimen is known as a myeloablative conditioning regimen, but it can result in toxicities and sterility. A conditioning regimen that uses lower doses of chemotherapy and medications may be safer for transplant recipients. This type of regimen is known as reduced intensity conditioning (RIC) regimen. RIC has a more favorable toxicity profile but is associated with higher rates of graft rejection (GR), especially with graft sources such as umbilical cord blood This study evaluated the safety and effectiveness of blood stem cell transplants, using bone marrow from unrelated donors, in children with severe SCD who receive a RIC regimen prior to the transplant.SubjectsPatients 3.0-19.75 years old with symptomatic SCD AND one or more of the following complications: (1)-(i) a clinically significant neurologic event (stroke) or any neurologic defect lasting > 24 hours and accompanied by an infarct on cerebral magnetic resonance imaging (MRI); OR, (ii) patients who have a Transcranial Doppler (TCD) velocity that exceeds 200 cm/sec by the non-imaging technique (or TCD measurement of >185 cm/sec by the imaging technique) measured at a minimum of 2 separate occasions one month or more apart; OR, (2) Minimum of two episodes of acute chest syndrome within the preceding 2-year period defined as new pulmonary alveolar consolidation involving at least one complete lung segment (associated with acute symptoms including fever, chest pain, tachypnea, wheezing, rales, or cough that is not attributed to asthma or bronchiolitis) despite adequate supportive care measures; OR, (3) History of 3 or more severe pain events (defined as new onset of pain that lasts for at least 2 hours for which there is no other explanation) per year in the 2 years prior to enrollment despite adequate supportive care measures (if patients are receiving hydroxyurea and compliant with therapy, being symptomatic is an indication for transplantation; however, if patients decline hydroxyurea or non-compliant with this therapy, they would still remain eligible for study if pain criteria as described above are met). Lansky/Karnofsky performance score must be ≥ 40. Hemoglobin S must be ≤ 45%. Patients must have an unrelated adult bone marrow donor who is HLA-matched at 8 of 8 HLA-A, -B, -C and -DRB1 at high resolution using DNA-based typing. Patients with bridging fibrosis or cirrhosis of the liver, with uncontrolled bacterial, viral, or fungal infection in the past month, or seropositivity for HIV are excluded. Patients with HLA-matched family donors, or who have received prior HCT, and females who are pregnant or breast feeding are excluded. Thirty patients were enrolled on this study and of these, 29 patients met the criteria and proceeded to the study transplant.DesignParticipants attended a study visit prior to the transplant to undergo a blood collection, neurocognitive testing to measure learning and brain function, magnetic resonance angiogram (MRA) and magnetic resonance imaging (MRI) scans. Questionnaires to assess quality of life were also completed. All patients received erythrocyte transfusions before transplant. Twenty-two days (-22) before the transplant, participants began receiving a reduced intensity conditioning regimen of chemotherapy and medications. On days -21, -20, and -19 participants weighing 10 kg or more received 10 mg, 15 mg, and then 20 mg of Alemtuzumab intravenously (IV) followed by 30 mg/m2/day IV on days -8 through -4 of Fludarabine. Eight days (-8) before the transplant, participants were admitted to the hospital to continue the conditioning regimen which included 140 mg/m2 IV of Melphalan on day -3. Participants received the bone marrow transplant on day 0. Prophylaxis for GVHD consisted of a calcineurin inhibitor (tacrolimus or cyclosporine) administered from day -3 through day 100 after graft infusion, with subsequent taper through day 180; methotrexate 7.5 mg/m2 on days 1, 3, and 6; and methylprednisolone 1 mg/kg per day from days 7 through 28, with subsequent taper by 20% per week. One week after the transplant continuing until the WBC is normal, participants received granulocyte-colony-stimulating factor (G-CSF). After leaving the hospital, participants attended study visits weekly during weeks 1 to 8, at day 60, weekly during weeks 9 to 14, at Day 100, at month 6, and at years 1 and 2. At all study visits, a blood collection, medical history review, and physical exam occurred. In addition, at day 100, month 6, and years 1 and 2, questionnaires to assess quality of life were completed. At select visits the following procedures were conducted: lung function testing, heart function testing, MRA and MRI scans, and neurocognitive testing.The primary outcome was 1-year EFS. Death, disease recurrence or graft rejection by 1 year were considered events for this endpoint.ConclusionsThe trial met its prespecified 1-year EFS, and significantly improved HRQL was reported posttransplant. However, although the Reduced-intensity conditioning (RIC) provided successful engraftment in most patients, the regimen cannot be considered safe for widespread adoption without modification due to the regimen-related toxicity (RRT) and high rate of chronic GVHD, which was the predominant cause of mortality.

Study phs003470

Submitter Portal

Submitter Portal The Submitter Portal does not support array submissions! Please refer to the array documentationAny new objects registered in the Submitter Portal will not be available for use in an array submission For further information please check our Submission FAQs, submission quickguide as well as submission terms! The metadata submission process can be difficult and time-consuming. For this reason, the EGA has developed the Submitter Portal, a tool that was created to offer a simplified and user-friendly method of registering metadata. Our portal provides features that are intended to make the input of metadata easier, ensuring that your data is registered correctly and effectively. Our page is divided into logical sections and includes a helpful video instruction to further assist you as you complete the submission process. With the Submitter Portal, you can rest assured that the submission of your data is in good hands. Submitter Portal Index Previous steps Access to Submitter Portal Start a Submission Take The Tour Tutorial Previous steps Create your EGA account To submit data, you first need to create your EGA user. Then, once your account has been verified by the Help Desk team, you will be able to request a submitter role and send the EGA Data Processing Agreement (DPA). In the case you already have an EGA account, or an ega-box (submission account), you can skip this step. Upload your files Please note that all your files must be encrypted using the Crypt4GH tool before upload them.As soon as you are assigned with a submitter role and added your public key to your profile, you will be able to connect to the EGA inbox and upload your files. Understand the EGA metadata schema It's crucial to comprehend the EGA metadata schema, a set of rules that specify how data is organised, described, and shared inside the EGA, in order to get the most out of this resource. Learn all about EGA metadata schema! Register your DAC and policy There are two objects in the EGA metadata schema that are registered in a separate portal. All DACs and policy objects are registered using the DAC Portal, a tool developed by EGA to help data controllers manage their data stored at the EGA. You can find relevant information in the DAC Portal Guide. Access to Submitter Portal 1. Request Submitter Role Once you have created your EGA user, request a Submitter Role and complete relevant information such as submission type and size. 2. Signature of the Data Processing Agreement The Data Processing Agreement (DPA) signed by CRG and EMBL-EBI (Joint Data Processors for the EGA) can be downloaded to the submitter for its signature. Further information related to the DPA can be in the Privacy Notice section. The DPA should be signed by a legal representative of the submitter with power of attorney/appointment duly authorised to sign contracts on behalf of the institution. The submitter will return a fully-executed copy of the DPA to us. Please note that due to the high volume of submissions to EGA the DPA is non-negotiable. Once you have completed all the information and attached the DPA signed, send your Submitter request and the EGA Helpdesk Team will validate it and send a confirmation to start submitting your metadata. Start a Submission The steps below will show you how to start a submission and are accompanied with a tutorial and the Take the tour of Submitter Portal. 1. Login Go to the Submitter Portal interface and log in using your EGA account credentials. 2. Create a submission The Submitter Portal interface will show you any already existing open submission. To start a new submission click on “Create a Submission”.In this phase you have the option to add any collaborator(s) as well as their permissions (“Read only” or “Read & Write”). If you want to invite all the collaborators from a previous submission, you can add them by selecting said submission.In the event that the submission has been closed, you will need to reopen it. To do this, you will need to modify one of the objects in the submission, for example, copy and paste the title. Once the submission is open, you can add a collaborator. Further information can be found in the Submission Tour 3. Create Study Click on add Study and complete the form with the relevant information. The fields with an asterisk (*) are mandatory. Further information can be found in the Submission Tour4. Create Sample Sample registration can be done either individually or in batch by using a template. Batch upload: download the template and complete it with information about the sequencing samples. Upload the samples.csv and the sample will be created.Add single sample: complete the mandatory fields with the metadata information of your sample. Further information can be found in the Submission Tour5. Create Experiment Register an experiment with information about the sequencing methods, protocols and machines. Experiments generate the connection between samples and study. Further information can be found in the Submission Tour6. Create Run Samples, experiments and files are linked through runs. To register a run, you will be asked to select the appropriate experiment and the file format. Run registration can be done either individually or in batch by using a template. Batch upload: download the template and complete it with the sample - file linkage. Upload the run.csv and the runs will register.As the INBOX is a directory, bear in mind to include the file path (/). Example: /filename.c4gh. Add single run: select the file format, sample and experiment from the drop box. For re-using submitted samples, please use the EGA accession ID (EGANXXX). Please note that files must be uploaded in your inbox before linking your files and samples. Further information can be found in the Submission Tour7. Create Analysis Analysis should be only used for BAM/BAI or CRAM/CRAI pair, VCF and phenotype linkage to samples. The analysis is an EGA specific metadata object that links samples to files. This object also stores some metadata about your experiments, such as the experiment type, genome reference, or the platform used. **If only BAM or CRAM alignment files are submitted but not the original unaligned FASTQ files, then please make sure that the BAM or CRAM files also contain the unaligned reads. This is critical to enable primary re-analysis and re-alignment of the dataset using new tools or future genome assemblies.** Start by selecting the samples to be linked to the file, and then populate the required attribute fields. Please be aware of the existence of mandatory fields that must be populated.When populating the chromosome field (mandatory), please select the chromosomes from the checkbox. Please take in consideration that EGA allows for the re-use of any registered metadata. Therefore, a previously registered study or samples can be referenced for the analysis in the current data submission.Further information can be found in the Submission Tour 8. Create Dataset Dataset contains the collection of runs/analysis data files subjected to controlled access by being associated with a Policy. Complete the mandatory fields such as title, description, type and policy. Please, take in consideration that DAC and Policy must be registered in advance in the DAC Portal. Similar to other metadata objects, you can re-use previous runs or analyses, using their EGA accessions IDs (runs - EGAR, analyses - EGAZ). Further information can be found in the Submission Tour 9. Finalise submission Once the files are ingested please delete them from your SFTP INBOX before finalising your submission. This will prevent the files from reappearing in your Submitter Portal Inbox. Once you have completed your submission, click on the Finalise button, and schedule an estimated release date. Afterwards, your submission will be sent to Helpdesk for approval. Please note that once the Helpdesk has approved your submission, you will receive the identifiers for your data. See the Frequently Asked Questions (FAQ) for more information. 10. Update closed submission If you want to append more file to a closed submission, you will need to re-open the submission where the dataset was registered. Find the Submission: go to the Submitter Portal Menu -> Datasets section and find the submission id (EGA0XXX). Reopen the submission where the dataset is located: to reopen a submission, you must edit any object within the submission. For example, you can copy and paste the title. Take The Tour The Submitter Portal Take The Tour is a visual guidance of all the steps described previously about how to start a submission. Tutorial In this tutorial we will show you how to use the Submitter Portal to register your metadata. Please note the video focuses on the run-based submission (for raw files - fastq - and aligned data - BAM/CRAM) and analysis-based submission (for your BAM/BAI pairs, variation -VCF - and phenotype files).

Documentation submission/metadata/submission/sequencing-phenotype/submitter-portal

Circulating RNA profiles of healthy and preeclamptic pregnancies

This prospective study investigated whether circulating RNA (C-RNA; cell free RNA present in the bloodstream) measurements could non-invasively monitor pregnancy status, with emphasis on detecting molecular markers associated with preterm preeclampsia. Whole blood samples were collected from pregnant women at the time of diagnosis with early-onset preeclampsia with severe features. Blood samples were also obtained normotypical control pregnancies and from patients diagnosed with late-onset preeclampsia for comparison. For all samples, C-RNA was extracted from 4 mL blood and whole transcriptome enrichment performed on cDNA libraries prior to sequencing to a target depth of 50M reads on an Illumina HiSeq 2000 platform. Throughout the course of this work, whole transcriptome RNA sequencing data was obtained from 289 C-RNA samples collected from 178 subjects. The complete dataset consists of samples from the following cohorts: Illumina Preeclampsia Cohort (iPEC): 40 pregnancies at the time of early-onset preeclampsia diagnosis and 73 gestational age-matched controls PEARL preeclampsia cohort: 12 early-onset and 12 late-onset preeclampsia patients PEARL healthy control cohort: 152 longitundinal samples collected from 41 healthy pregnancies

Study phs002017

Cohort-Based Genome-Wide Association Study of Glioma (GliomaScan)

We conducted a new independent GWAS of adult glioma using 1,856 cases and 4,955 controls from 14 cohort studies belonging to the Cohort Consortium, 3 case-control studies, and 1 population-based case only study. Cases were newly diagnosed glioma [ICDO-3 codes 9380-9480 or equivalent], and controls were cancer-free at the time of glioma diagnosis. We found evidence of strong replication for three of the seven previously reported associations at 20q13.33 (RTEL), 5p15.33 (TERT), and 9p21.3 (CDKN2BAS), and consistent association signals for the remaining four at 7p11.2 (EGFR both loci), 8q24.21 (CCDC26) and 11q23.3 (PHLDB1). The direction and magnitude of the signal were consistent for samples from cohort and case-control studies, but the strength of the association was more pronounced for loci rs6010620 (20q,13.33; RTEL) and rs2736100 (5p15.33, TERT) in cohort studies despite the smaller number of cases in this group, likely due to higher grade tumors being captured in the cohort studies. Our findings suggest that larger studies focusing on novel approaches as well as specific tumor subtypes or subgroups will be required to identify additional common susceptibility loci for glioma risk.

Study phs000652

Non-small cell lung cancer molecular subtypes and vulnerability to immunotherapy treatment combinations

The phase 3 IMpower150 trial in treatment-naïve patients with metastatic non-small-cell lung cancer (NSCLC) demonstrated significantly longer progression-free (PFS) and overall survival (OS) with first-line atezolizumab (anti-PD-L1)-bevacizumab (anti-VEGF)-carboplatin-paclitaxel (ABCP) than with bevacizumab-carboplatin-paclitaxel (BCP). We characterised four molecular NSCLC subtypes identified by unsupervised clustering of transcriptomes of 564 pre-treatment primary tumour samples from IMpower150 using non-negative matrix factorization (NMF1-4). Each subtype had distinct tumour PD-L1 expression levels, epithelial characteristics, immune composition, and treatment outcomes. Both NMF2 (enriched in tumour proliferation signal, macrophages, and monocytes) and NMF4 (enriched in B-cells and T cells) had elevated tumour PD-L1 expression. Of these two, only NMF4 demonstrated PFS and OS benefits with ABCP versus either BCP or atezolizumab-carboplatin-paclitaxel (ACP). Patients with NMF1 (enriched in basal and squamous-like cells) had improved outcomes on ABCP compared with ACP or BCP; those with NMF3 (enriched in adenocarcinoma signatures) showed similar outcomes among treatments. These insights could help inform individualised first-line treatment for metastatic NSCLC.

Study EGAS50000001272

Atezolizumab Plus Chemotherapy With or Without Bevacizumab in Advanced Biliary Tract Cancer: Clinical and Biomarker Data From the Randomized Phase II IMbrave151 Trial

PURPOSE Biliary tract cancers (BTCs) harbor an immunosuppressed tumor microenvironment (TME) and respond poorly to PD-1/PD-L1 inhibitors. Bevacizumab (anti-VEGF) plus chemotherapy can promote anticancer immunity, augmenting response to PD-L1 inhibition. PATIENTS AND METHODS This randomized, double-blind, proof-of-concept Phase II study enrolled patients (n=162) with previously untreated advanced BTC (IMbrave151; NCT04677504). Patients were randomized 1:1 to receive 3-weekly cycles of atezolizumab (1200 mg) plus bevacizumab (15 mg/kg) or atezolizumab plus placebo until disease progression or unacceptable toxicity. All patients received cisplatin (25 mg/m2) plus gemcitabine (1000 mg/m2; CisGem) on Days 1 and 8 every 3 weeks for up to 8 cycles. Stratification of patients was by disease status, geographic region, and primary tumor location. The primary endpoint was progression-free survival (PFS). No formal hypothesis testing was performed. Exploratory correlative biomarker analysis was undertaken using transcriptome analysis (n=95) and mutation profiling (n=102) on baseline tumor samples. RESULTS Between February and September 2021, 162 patients were enrolled. Median PFS was 8.3 months in the bevacizumab arm and 7.9 months in the placebo

Study EGAS50000000387

Rapid brain tumor classification from sparse epigenomic data

Although the intraoperative, molecular differential diagnosis of the approximately one hundred different brain tumor entities described to date has been a goal of neuropathology in the last decade, this has not yet been achieved in a clinically relevant time frame of less than one hour after biopsy collection. Recent advances in third-generation sequencing technologies have brought this once-elusive goal within reach. However, established machine learning techniques rely on concepts and methods, impractical for live diagnostic workflows in clinical applications. Here, we present MethyLYZR, a Naïve Bayesian framework enabling fully tractable live classification of cancer epigenomes. MethyLYZR can be run in parallel with an ongoing Nanopore experiment with negligible computational cost and provides clinically relevant and accurate cancer classification results within 15 minutes of sequencing. Therefore, only the time required for DNA extraction and the Nanopore sequencer's maximum parallel throughput remain limiting factors for even faster time-to-results. We demonstrate the potential utility of the MethyLYZR framework not only for the neurosurgical intraoperative use case but also for other oncologic indications and cell-free DNA from liquid biopsies.

Study EGAS50000000559

Clinical significance of novel subtypes of acute lymphoblastic leukemia in the context of minimal residual disease-directed therapy

We evaluate clinical significance of recently identified subtypes of acute lymphoblastic leukemia (ALL) in 598 children treated with minimal residual disease (MRD)-directed therapy. Among the 16 B-ALL and 8 T-ALL subtypes identified by next generation sequencing, ETV6-RUNX1, high-hyperdiploid and DUX4-rearranged B-ALL had the best five-year event-free survival rates (95% to 98.4%); TCF3-PBX1, PAX5alt, T-cell, ETP, iAMP21, and hypodiploid ALL intermediate rates (80.0% to 88.2%); and BCR-ABL1, BCR-ABL1-like and ETV6-RUNX1-like and KMT2A-rearranged ALL the worst rates (64.1% to 76.2%). All but three of the 142 patients with day-8 blood MRD <0.01% remained in remission. Among new subtypes, intensified therapy based on day-15 MRD≥1% improved outcome of DUX4-rearranged, BCR-ABL1-like, and ZNF384-rearranged ALL, and achievement of day-42 MRD<0.01% did not preclude relapse of PAX5alt, MEF2D-rearranged and ETV6-RUNX1-like ALL. Thus, new subtypes including DUX4-rearranged, PAX5alt, BCR-ABL1-like, ETV6-RUNX1-like, MEF2D-rearranged and ZNF384-rearranged ALL have important prognostic and therapeutic implications.

Study EGAS00001005084

The Egyptian Collaborative Cardiac Genomics (ECCO-GEN) Project: Defining a Healthy Volunteer Cohort

The integration of comprehensive genomic and phenotypic data from diverse ethnic populations offers unprecedented opportunities towards advancements in precision medicine and novel diagnostic technologies. Current reference genomic databases are not representative of the global human population, making variant interpretation challenging, especially in underrepresented populations such as the North African population. To address this, the Egyptian Collaborative Cardiac Genomics (ECCO-GEN) Project launched a study comprising 1000 individuals free of cardiovascular disease (CVD). Here, we present the first 391 Egyptian healthy volunteers (EHVols) recruited to establish a pilot phenotyped control cohort. All individuals underwent detailed clinical investigation, including cardiac MRI, and were sequenced using a targeted panel of 174 genes with reported roles in inherited cardiac conditions (ICC). We identified 1,262 variants in 27 cardiomyopathy genes of which 15.1% were not captured in current global and regional genetic reference databases (here: gnomAD and Great Middle Eastern (GME) Variome). The ECCO-GEN project aims at defining the genetic landscape of an understudied population and providing individual-level genetic and phenotypic data to support future studies in CVD and population genetics.

Study EGAS00001004434

FASTQ files of total RNA-Seq data of POPS control samples

Placental biopsies (n = 64 female placentas, n = 67 male placentas) were selected from healthy pregnancies from the POPs cohort. These patients had no evidence of hypertension at booking and during pregnancy, did not experience pre-eclampsia, Hemolysis, Elevated Liver enzymes, and Low Platelets (HELLP) syndrome, gestational diabetes, or diabetes mellitus type I or type II and other obstetric complications. They delivered live babies with a birth weight percentile in the normal range (20-80th percentile), with no evidence of slowing in fetal growth trajectory. Chorionic villi from the corresponding placentas (free from decidua, visible infarction, calcification, hematoma, or damage) were collected and processed within 30 minutes of separation from the uterus. After repeated washes in chilled phosphate buffered saline, the samples were placed in RNA later (Applied Biosystems) and stored at -80°C. Total placental RNA was extracted using mirVana Isolation Kit (Ambion). For each placenta, approximately 5 mg of tissue were homogenized in the Lysis/Binding solution for 20 sec at 6 m/s using a bead beater (FastPrep24) and Lysing Matrix D Tubes (MP Biomedicals). The samples were then spun at 13,000 rpm for 5 min at 4°C and the supernatants recovered. Afterwards, the manufacturer's instructions were followed. Immediately after the RNA extraction, placental RNA samples were DNase-treated using DNA-free DNA Removal Kit (Ambion), aliquoted, and stored in -80°C. Quantity and quality of the RNA samples were assessed using the Agilent 2100 Bioanalyzer, the Agilent RNA 6000 Nano Kit (Agilent Technologies), and Qubit fluorometer. Libraries were prepared starting with 300-500 ng of good quality total RNA (RIN ≥7.5) using the TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero Human/Mouse/Rat (Illumina), according to the manufacturer's instructions. The kit contains 96 uniquely indexed adapter combinations in order to allow pooling of multiple samples prior to sequencing. After determining their size (with the Agilent 2100 Bioanalyzer and the Agilent High Sensitivity DNA Kit by Agilent Technologies) and concentration (by qPCR with the KAPA Illumina ABI Prism Library Quantification Kit, Kapa Biosystems), libraries have been pooled and sequenced (single-end, 125 bp) using a Single End V4 Cluster Kit and an Illumina HiSeq2500 or HiSeq4000 instrument.

Dataset EGAD00001003457

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

Immune-Related Adverse Events after Immune Checkpoint Blockade-Based Therapy are Associated with Improved Survival in Advanced Sarcoma

Immune activation after immune checkpoint blockade (ICB) can lead to a unique group of adverse events (AEs), which have been associated with improved outcome in many carcinomas. The association between immune-related AEs (irAEs) and outcome in patients with sarcoma is not well studied. This study has two components: (1) a retrospective clinical study of irAEs among 131 patients treated with ICB at Memorial Sloan Kettering Cancer Center and (2) an analysis of a subset of these patients who have whole transcriptome sequencing available for analysis. In the clinical study portion, we reviewed a cohort of patients with advanced sarcoma treated on prospective clinical trials utilizing ICB-based therapy between April 2017 and January 2020. The objectives were to pool the safety data from each trial, identify irAEs, and correlate them with best overall response by RECIST 1.1, progression-free survival (PFS) and overall survival (OS). Association of irAEs with response and survival was assessed using a Cox regression model. A total of 131 patients were included. Forty-two (32%) had at least one irAE of any grade and 16 (12%) had at least one Grade ≥ 3 irAE. On Cox analysis adjusting for clinical covariates that were significant in the univariate setting, the hazard ratio (HR) for an irAE (HR 0.662, 95% CI 0.421 - 1.041) approached, but did not reach statistical significance for PFS (P = 0.074), while patients had a significantly lower HR for OS (HR 0.443, 95% CI 0.246 – 0.798; P = 0.007) compared to those without or before an irAE. Tumor samples with available RNA sequencing data were stratified by presence of an irAE to identify patterns of differential gene expression. In total, 71 unique patients had RNA sequencing available for analysis. The transcriptomes of 31 of these patients have been previously uploaded to dbGaP (phs002852), leaving 36 unique transcriptomes that have not been previously publicly shared. Three patients did not agree for their sequencing to be publicly shared. Therefore, 33 unique patient samples will be uploaded to this dbGaP study. Overall, this study found that gene expression profiling on baseline tumor samples from patients who had an irAE had higher numbers of tumor-infiltrating dendritic cells, CD8+ T cells, and regulatory T cells as well as upregulation of immune and inflammatory pathways.

Study phs003284

Comparison of the treated celiac disease microbiome to that of controls

Coeliac disease (CeD) is an immune-mediated disorder primarily affecting the small intestine, characterised by an inflammatory immune reaction to dietary gluten. CeD onset results from a multifaceted interplay of genetic and environmental factors. While recent data show that alterations in gut microbiome composition could play an important role, many current studies are constrained by small sample sizes and limited resolution. To address these limitations, we analysed faecal gut microbiota from two Dutch cohorts, CeDNN (128 treated CeD patients (tCeD), 106 controls) and the Lifelines Dutch Microbiome Project (24 self-reported tCeD, 654 controls), using shotgun metagenomic sequencing. Self-reported IBS (570 cases, 1710 controls) and IBD (93 cases, 465 controls) were used as comparative conditions of the gastrointestinal tract. Interindividual variation within the case and control groups was calculated at whole microbiome and strain level. Finally, species-specific gene repertoires were analysed in tCeD patients and controls. Within-individual microbiome diversity was decreased in patients with self-reported IBS and IBD but not in tCeD patients. Each condition displayed a unique microbial pattern and, in addition to confirming previously reported microbiome associations, we identify an increase in the levels of Clostridium sp. CAG:253, Roseburia hominis, and Eggerthella lenta, amongst others. We further show that the observed changes can partially be explained by gluten-free diet adherence. We also observe increased interindividual variation of gut microbiome composition among tCeD patients and a higher bacterial mutation frequency in tCeD that contributes to higher interindividual variation at strain level. In addition, the immotile European subspecies of Eubacterium rectale, which has a distinct carbohydrate metabolism potential, was nearly absent in tCeD patients. Our study sheds light on the complex interplay between the gut microbiome and CeD, revealing increased interindividual variation and strain-level variation in tCeD patients. These findings expand our understanding of the microbiome’s role in intestinal health and disease. Note that some of the data in this study belong to the Lifelines cohort. Access to this dataset can be requested via the page of the EGA data access committee EGAC00001001996. The phenotype data can be requested, for a fee, by filling the application form at https://www.lifelines.nl/researcher/how-to-apply/apply-here.

Study EGAS50000000959

GDAP - Genome Diversity in Africa Project (2021-02-12)

The Genomic Diversity in Africa Project (GDAP) started with the plan to develop a genomic resource from African populations, characterise genomic diversity and population history, and facilitate clinical studies in Africa. Currently, 25 individuals from 24 ethnolinguistic groups have been whole-genome sequenced at high depth totalling 585 individuals. An additional 41 individuals have been sequenced with 10X Genomics libraries. At this stage, the initial curation of this dataset has been finished and we are performing the analysis in coordination with our collaborators. The current state of the GDAP represents a very diverse panel of African populations that maximizes geographical and ethnic variation and represents a great starting point to achieve the aforementioned goals. However, southern sub-Saharan countries, Bantu speakers and hunter gatherer groups are currently underrepresented, despite being crucial to understand the evolutionary history of the continent. After extensive effort to collate studies documentation, we finally have the opportunity to sequence 600 new individuals from these groups, including countries as Gabon, Rwanda and Zambia, and address these deficiencies. We aim to proceed with the same strategy: to sequence at high depth 25 individuals with standard PCR free libraries, with 2 additional individuals with 10X Genomics Chromium libraries per ethnolinguistic group. The former allows a good representation of variants down to low frequency in any given population, and the latter allows accurate phasing and the analysis of structural variation. By including these new populations, we want to investigate three crucial questions in African history in addition to the initial objectives: the Bantu expansion, the evolutionary history of hunter gatherers and the transatlantic slave trade. Additionally, the expanded dataset will help us better discover the genetic variation present in Africa and characterize the African pangenome. 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/ . This dataset contains all the data available for this study on 2021-02-12.

Dataset EGAD00001006965

Cell-free DNA and bone marrow samples from myelodysplastic syndromes

We have assessed the molecular profile of a cohort of 70 patients with MDS by next-generation sequencing (NGS) using cfDNA and compared the results to paired bone marrow (BM) DNA. Sequencing of BM DNA and cfDNA showed a comparable mutational profile and variant allele frequencies (VAF) strongly correlated between both sample types. Our results support the analysis of cfDNA as a promising strategy for performing molecular characterization, detection of chromosomal aberrations and monitoring of MDS patients.

Study EGAS00001005992

Poland Lesser Voivodeship - WGS

This project used NGS (next generation sequencing), using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner. The dataset includes BAM and BAM.BAI files from Whole Genome Sequencing of 32 samples (14 female, 18 male of Lesser Voivodeship, Poland from POPULOUS collection). Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

Dataset EGAD50000000166

Poland Lodz Voivodeship - WGS

This project used NGS (next generation sequencing), using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner. The dataset includes BAM and BAM.BAI files from Whole Genome Sequencing of 41 samples (20 female, 21 male of Lodz Voivodeship, Poland from POPULOUS collection). Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

Dataset EGAD50000000165

Poland Mazovia Voivodeship - WGS

This project used NGS (next generation sequencing), using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner. The dataset includes BAM and BAM.BAI files from Whole Genome Sequencing of 43 samples (16 female, 27 male of Mazovia Voivodeship, Poland from POPULOUS collection). Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

Dataset EGAD50000000164

Poland Silesian Voivodeship - WGS

This project used NGS (next generation sequencing), using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner. The dataset includes BAM and BAM.BAI files from Whole Genome Sequencing of 47 samples (23 female, 24 male of Silesian Voivodeship, Poland from POPULOUS collection). Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

Dataset EGAD50000000163

Poland Holy Cross Voivodeship - WGS

This project used NGS (next generation sequencing), using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner. The dataset includes BAM and BAM.BAI files from Whole Genome Sequencing of 6 samples (6 female of Holy Cross Voivodeship, Poland from POPULOUS collection). Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

Dataset EGAD50000000162

Poland Greater Poland Voivodeship - WGS

This project used NGS (next generation sequencing), using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner. The dataset includes BAM and BAM.BAI files from Whole Genome Sequencing of 37 samples (19 female, 18 male of Greater Voivodeship, Poland from POPULOUS collection). Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

Dataset EGAD50000000161

Poland Pomeranian Voivodeship - WGS

This project used NGS (next generation sequencing), using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner. The dataset includes BAM and BAM.BAI files from Whole Genome Sequencing of 25 samples (14 female, 11 male of Pomeranian Voivodeship, Poland from POPULOUS collection). Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

Dataset EGAD50000000160

Poland Kuyavian-Pomeranian Voivodeship - WGS

This project used NGS (next generation sequencing), using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner. The dataset includes BAM and BAM.BAI files from Whole Genome Sequencing of 22 samples (11 female, 11 male of Kuyavian-Pomeranian Voivodeship, Poland from POPULOUS collection). Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

Dataset EGAD50000000158

Poland Lublin Voivodeship - WGS

This project used NGS (next generation sequencing), using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner. The dataset includes BAM and BAM.BAI files from Whole Genome Sequencing of 24 samples (14 female, 10 male of Lublin Voivodeship, Poland from POPULOUS collection). Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

Dataset EGAD50000000155

Poland Subcarpathian Voivodeship - WGS

This project used NGS (next generation sequencing), using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner. The dataset includes BAM and BAM.BAI files from Whole Genome Sequencing of 22 samples (11 female, 11 male of Subcarpathian Voivodeship, Poland from POPULOUS collection). Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

Dataset EGAD50000000157

Poland Lower Silesian Voivodeship - WGS

This project used NGS (next generation sequencing), using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner. The dataset includes BAM and BAM.BAI files from Whole Genome Sequencing of 30 samples (15 female, 15 male of Lower Silesian Voivodeship, Poland from POPULOUS collection). Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

Dataset EGAD50000000156

The G2 gene expression signature and MYC overexpression are independent poor prognostic factors in childhood high-grade osteosarcoma

Key objective Are the prognostic transcriptomic G1/G2 gene expression signature, MYC overexpression, and MYC amplification replicable stratifying biomarkers for future clinical trials in high-grade osteosarcoma? Knowledge gathered In an unselected cohort, the G2 gene expression signature and MYC overexpression, but not MYC amplification, were independently associated with poor event-free and overall survival. Relevance Transcriptomic biomarkers may serve as stratifying factors that guide the management of patients with high-grade osteosarcoma. Current data underlines the importance of prospective validation of the G1/G2 signature and MYC overexpression in an international, multicenter, study.

Dataset EGAD00001015502

WGBS data of solid liver tumor DNA, and WGBS data of cell-free DNA derived from human blood, for CancerDetector study

The blood samples of four liver cancer patients and four healthy people, and the solid liver tumor samples of two liver cancer patients are collected for this dataset. Blood samples were centrifuged first at 1,600 × g for 10 minutes, and then the plasma was transferred into new micro tubes and centrifuged at 16,000 × g for another 10 minutes. The plasma was collected and stored at -80⁰C. CfDNA was extracted from 5 ml plasma using the Qiagen QIAamp Circulating Nucleic Acids Kit and quantified by Qubit 3.0 Fluoromter (Thermo Fisher Scientific). Bisulfite conversion of cfDNA was performed by using EZ-DNA-Methylation-GOLD kit (Zymo Research). After that, Accel-NGS Methy-Seq DNA library kit (Swift Bioscience) was used to prepare the sequencing libraries. The DNA libraries were then sequenced with 150bp paired-end reads.

Dataset EGAD00001004317

NextGen Consortium: Globin Gene Expression in Sickle Cell Genotype-Specific iPS Cells

Implement an efficient, highly reproducible and 'scalable' system for the production of large numbers of sickle cell anemia-specific iPS cells (iPSC). Derive and characterize a novel, in vitro system for the production of an unlimited supply of erythroid lineage cells from the directed differentiation of 'clinical grade' transgene-free iPS cells; use this system to recapitulate erythroid-lineage ontogeny in vitro with the sequential development of primitive and definitive erythropoiesis, accompanied by the appropriate expression of stage-specific globin genes. Identify developmental gene expression profile differences between erythroid precursors that produce primarily HbF and those that produce primarily HbA or HbS. Determine the effects of the three known HbF major quantitative trait loci (QTL) on globin gene expression in disease-specific iPS cells during in vitro erythropoiesis. Search for novel HbF genetic modifiers associated with markedly elevated HbF levels found in sickle cell anemia patients naturally, or in response to hydroxyurea treatment, by examining gene expression profiles and mRNA sequence of their iPSC-derived erythroid cells. Develop and use a CRISPR-based gene editing platform to study the effect of novel HbF genetic modifiers, explore globin switching, and correct the HbS mutation in sickle iPSC lines.

Study phs001212

Single-Cell Genomic and Transcriptomic Analysis of the Aging Human Brain

We studied human brain aging using single-cell whole genome sequencing and single-nucleus RNA sequencing of the pre-frontal cortex from 19 donors ranging in age from 0.4 years to 104 years. All donors were free of neuropathology and none received a clinical neurological diagnosis prior to death. snRNA-seq libraries were prepared in batches that always included old and young donors to mitigate batch effects in the preparations. Neurons for single-cell WGS were collected from the same tissue region as the snRNA-seq for each donor but represent independent cells. Multiplexed error-robust fluorescent in-situ hybridization (MERFISH) data was also collected from pre-frontal cortex samples of a subset of the 19 donors. Transcriptomic results identified infant-specific cell clusters, and common-down regulation of cell-essential genes involved in ribosomes, transport, homeostasis and metabolism during aging, across all cell types. scWGS identified two-age associated mutational signatures, as well as gene-length and expression-level dependent somatic mutation rates in neurons. Raw sequencing data in fastq format for single-nucleus RNA-seq and single-cell DNA-seq, as well as cell and gene count matrix, transcript metadata, and cell metadata for MERFISH will be available in dbGaP.

Study phs003445

APOBEC3 mutagenesis drives therapy resistance in breast cancer

Acquired genetic alterations commonly drive resistance to endocrine and targeted therapies in metastatic breast cancer, however the underlying processes engendering these diverse alterations are largely uncharacterized. To identify the mutational processes operant in breast cancer and their impact on clinical outcomes, we utilized a well-annotated cohort of 3,880 patient samples with paired tumor-normal sequencing data. The mutational signatures associated with apolipoprotein B mRNA-editing enzyme catalytic polypeptide-like 3 (APOBEC3) enzymes were highly prevalent and enriched in post-treatment compared to treatment-naïve hormone receptor-positive (HR+) cancers. APOBEC3 mutational signatures were independently associated with shorter progression-free survival on antiestrogen plus CDK4/6 inhibitor combination therapy in patients with HR+ metastatic breast cancer. Whole genome sequencing (WGS) of breast cancer models and selected paired primary-metastatic samples demonstrated that active APOBEC3 mutagenesis promoted resistance to both endocrine and targeted therapies through characteristic alterations such as RB1 loss-of-function mutations. Evidence of APOBEC3 activity in pre-treatment samples illustrated a pervasive role for this mutational process in breast cancer evolution. The study reveals APOBEC3 mutagenesis to be a frequent mediator of therapy resistance in breast cancer and highlights its potential as a biomarker and target for overcoming resistance.

Study EGAS50000000875

Direct Detection of Early-stage Cancers Using Circulating Tumor DNA

Early detection and intervention are likely to be the most effective means for reducing morbidity and mortality of human cancer. However, development of methods for noninvasive detection of early-stage tumors has remained a challenge. We have developed an approach called targeted error correction sequencing (TEC-Seq) that allows ultrasensitive direct evaluation of sequence changes in circulating cell-free DNA using massively parallel sequencing. We have used this approach to examine 58 cancer-related genes encompassing 81 kb. Analysis of plasma from 44 healthy individuals identified genomic changes related to clonal hematopoiesis in 16% of asymptomatic individuals but no alterations in driver genes related to solid cancers. Evaluation of 200 patients with colorectal, breast, lung, or ovarian cancer detected somatic mutations in the plasma of 71, 59, 59, and 68%, respectively, of patients with stage I or II disease. Analyses of mutations in the circulation revealed high concordance with alterations in the tumors of these patients. In patients with resectable colorectal cancers, higher amounts of preoperative circulating tumor DNA were associated with disease recurrence and decreased overall survival. These analyses provide a broadly applicable approach for noninvasive detection of early-stage tumors that may be useful for screening and management of patients with cancer.

Study EGAS00001002577

A neoadjuvant, phase II trial demonstrates efficacy and tolerability of Talimogene laherparepvec in cutaneous basal cell carcinoma (NeoBCC trial)

We present a single arm, phase II neoadjuvant trial with the oncolytic virus Talimogene laherparepvec (T-VEC) in 18 patients with difficult-to-resect basal cell carcinomas. Six cycles of T-VEC were applied intralesionally. The primary endpoint of the study, defined as the proportion of the patients, who after six cycles of T-VEC (13 weeks) at the time point of surgery, become resectable with primary wound closure without the need for plastic reconstructive surgery like skin flaps or skin grafts, was achieved (9/18 patients; 50.0%). Secondary endpoints also included the relapse free survival rate (100%), overall survival (100%) and biological read outs in the tumor samples. T-VEC led to a significant increase of cytotoxic T cells, B cells and myeloid cells, and a decrease of Tregs within the tumor microenvironment. We observed a potent induction of antitumoral and antiviral T cell clones, as well as a strong humoral immune response. The objective response rate was 55.6% and the complete pathological response rate was 33.3%. Only mild adverse events occurred. Together, neoadjuvant T-VEC represents a viable treatment option for patients with difficult-to-resect BCCs (EudraCT Number 2018-002165-19).

Study EGAS50000000252

Identifying New Genetic Subtypes in Follicular Lymphoma

Follicular lymphoma (FL) exhibits considerable variability in biological features and clinical trajectories across patients. To dissect the diversity of FL, we utilized a Bernoulli mixture model to identify genetic subtypes in 713 pre-treatment tumor tissue samples. Our analysis revealed the existence of five subtypes with unique genetic profiles that correlated with clinicopathological characteristics. The clusters were enriched in specific mutations as follows: CS (CREBBP and STAT6), TT (TNFAIP3 and TP53), GM (GNA13 and MEF2B), Q (quiescent, for low mutation burden), and AR (mutations of mTOR pathway-related genes). The subtype Q was enriched for patients with stage I disease and was associated with a lower proliferative history compared to the other subtypes. The AR subtype was unique in its enrichment for IgM-expressing FL cases and was associated with advanced-stage and more than 4 nodal sites. The existence of subtypes was validated in an independent cohort of 418 samples from the GALLIUM trial. Notably, patients assigned to the TT subtype consistently experienced inferior progression-free survival when treated with immunochemotherapy. Collectively, our findings offer insight into core pathways distinctly linked with each FL cluster and are expected to be informative in the era of targeted therapies.

Study EGAS50000000435

FASTQ files of total RNA-Seq data from the POPS SGA (Small for Gestational Age) samples

All the samples were obtained from the Pregnancy Outcome Prediction–a prospective cohort study of nulliparous women attending the Rosie Hospital, Cambridge (UK) for their dating ultrasound scan between January 14, 2008, and July 31, 2012. Ethical approval for the study was given by the Cambridgeshire 2 Research Ethics Committee (reference number 07/H0308/163) and all participants provided written informed consent. Cases of preeclampsia (PET) were defined on the basis of the 2013 ACOG criteria and cases of small for gestational age (SGA)infants were confined to severe SGA, i.e. a customized birth weight <5th percentile. Chorionic villi from the corresponding placentas (free from decidua, visible infarction, calcification, hematoma, or damage) were collected and processed within 30 minutes of separation from the uterus. After repeated washes in chilled phosphate buffered saline, the samples were placed in RNA later (Applied Biosystems) and stored at -80°C. Total placental RNA was extracted using mirVana Isolation Kit (Ambion). For each placenta, approximately 5 mg of tissue were homogenized in the Lysis/Binding solution for 20 sec at 6 m/s using a bead beater (FastPrep24) and Lysing Matrix D Tubes (MP Biomedicals). The samples were then spun at 13,000 rpm for 5 min at 4°C and the supernatants recovered. Afterwards, the manufacturer's instructions were followed. Immediately after the RNA extraction, placental RNA samples were DNase-treated using DNA-free DNA Removal Kit (Ambion), aliquoted, and stored in -80°C. Quantity and quality of the RNA samples were assessed using the Agilent 2100 Bioanalyzer, the Agilent RNA 6000 Nano Kit (Agilent Technologies), and Qubit fluorometer. Libraries were prepared starting with 300-500 ng of good quality total RNA (RIN ≥7.5) using the TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero Human/Mouse/Rat (Illumina), according to the manufacturer's instructions. The kit contains 96 uniquely indexed adapter combinations in order to allow pooling of multiple samples prior to sequencing. After determining their size (with the Agilent 2100 Bioanalyzer and the Agilent High Sensitivity DNA Kit by Agilent Technologies) and concentration (by qPCR with the KAPA Illumina ABI Prism Library Quantification Kit, Kapa Biosystems), libraries have been pooled and sequenced (single-end, 125 bp) using a Single End V4 Cluster Kit and an Illumina HiSeq2500 or HiSeq4000 instrument.

Dataset EGAD00001003507

FASTQ files of total RNA-Seq data from the POPS PET (pre-eclamptic) samples

All the samples were obtained from the Pregnancy Outcome Prediction–a prospective cohort study of nulliparous women attending the Rosie Hospital, Cambridge (UK) for their dating ultrasound scan between January 14, 2008, and July 31, 2012. Ethical approval for the study was given by the Cambridgeshire 2 Research Ethics Committee (reference number 07/H0308/163) and all participants provided written informed consent. Cases of preeclampsia (PET) were defined on the basis of the 2013 ACOG criteria and cases of small for gestational age (SGA)infants were confined to severe SGA, i.e. a customized birth weight <5th percentile. Chorionic villi from the corresponding placentas (free from decidua, visible infarction, calcification, hematoma, or damage) were collected and processed within 30 minutes of separation from the uterus. After repeated washes in chilled phosphate buffered saline, the samples were placed in RNA later (Applied Biosystems) and stored at -80°C. Total placental RNA was extracted using mirVana Isolation Kit (Ambion). For each placenta, approximately 5 mg of tissue were homogenized in the Lysis/Binding solution for 20 sec at 6 m/s using a bead beater (FastPrep24) and Lysing Matrix D Tubes (MP Biomedicals). The samples were then spun at 13,000 rpm for 5 min at 4°C and the supernatants recovered. Afterwards, the manufacturer's instructions were followed. Immediately after the RNA extraction, placental RNA samples were DNase-treated using DNA-free DNA Removal Kit (Ambion), aliquoted, and stored in -80°C. Quantity and quality of the RNA samples were assessed using the Agilent 2100 Bioanalyzer, the Agilent RNA 6000 Nano Kit (Agilent Technologies), and Qubit fluorometer. Libraries were prepared starting with 300-500 ng of good quality total RNA (RIN ≥7.5) using the TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero Human/Mouse/Rat (Illumina), according to the manufacturer's instructions. The kit contains 96 uniquely indexed adapter combinations in order to allow pooling of multiple samples prior to sequencing. After determining their size (with the Agilent 2100 Bioanalyzer and the Agilent High Sensitivity DNA Kit by Agilent Technologies) and concentration (by qPCR with the KAPA Illumina ABI Prism Library Quantification Kit, Kapa Biosystems), libraries have been pooled and sequenced (single-end, 125 bp) using a Single End V4 Cluster Kit and an Illumina HiSeq2500 or HiSeq4000 instrument.

Dataset EGAD00001003508

Osteoporotic Fractures in Men (MrOS)

The Osteoporotic Fractures in Men Study (MrOS) is a multi-center prospective, longitudinal, observational study of risk factors for vertebral and all non-vertebral fractures in older men, and of the sequelae of fractures in men. The original specific aims of the study include: (1) to define the skeletal determinants of fracture risk in older men, (2) to define lifestyle and medical factors related to fracture risk, (3) to establish the contribution of fall frequency to fracture risk in older men, (4) to determine to what extent androgen and estrogen concentrations influence fracture risk, (5) to examine the effects of fractures on quality of life, (6) to identify sex differences in the predictors and outcomes of fracture, (7) to collect and store serum, urine and DNA for future analyses as directed by emerging evidence in the fields of aging and skeletal health, and (8) define the extent to which bone mass/fracture risk and prostate diseases are linked. The MrOS study population consists of 5,994 community dwelling, ambulatory men aged 65 years or older from six communities in the United States (Birmingham, AL; Minneapolis, MN; Palo Alto, CA; Monongahela Valley near Pittsburgh, PA; Portland, OR; and San Diego, CA). Inclusion criteria were designed to provide a study cohort that is representative of the broad population of older men. The inclusion criteria were: (1) ability to walk without the assistance of another, (2) absence of bilateral hip replacements, (3) ability to provide self-reported data, (4) residence near a clinical site for the duration of the study, (5) absence of a medical condition that (in the judgment of the investigator) would result in imminent death, and (6) ability to understand and sign an informed consent. To qualify as an enrollee, the participant had to provide written informed consent, complete the self-administered questionnaire (SAQ), attend the clinic visit, and complete at least the anthropometric, DEXA, and vertebral X-ray procedures. There were no other exclusion criteria. The baseline examination was completed over a 25-month period from March 2000 to April 2002. Participants completed questionnaires regarding medical history, medications, physical activity, diet, alcohol intake, and cigarette smoking. Objective measures of anthropometric, neuromuscular, vision, strength, and cognitive variables were obtained at a clinic visit. Skeletal assessments included DEXA, calcaneal ultrasound, and vertebral radiographs. Vertebral and proximal femoral QCT was performed on a subset (65%) of participants. Serum, urine, and whole blood specimens were collected. During the study period, participants complete a tri-annual questionnaire every four months that obtains information concerning the occurrence of incident falls and fractures. Follow-up is over 99% complete. All reported fractures are confirmed using physician review of radiology reports or study radiologist review of x-rays. All deaths are also centrally adjudicated using death certificates and recent hospitalization records. In additional to the baseline study visit and tri-annual questionnaires, all surviving active participants were invited to follow-up visits and questionnaires. A second comprehensive clinic visit was completed between March 2005 and May 2006 or about 4.5 years after baseline. Most baseline measures, including vertebral radiographs, were repeated at the second visit. A third comprehensive clinic visit was completed between March 2007 and March 2009 or about 7.0 years after baseline. Many baseline measures were repeated at the third visit. A measure of energy expenditure was also obtained utilizing an accelerometer based armband device. Surviving participants have also completed two extensive mailed questionnaires designed to updated information obtained at clinic visits. The first questionnaire was mailed between baseline and visit 2 between July 2002 and March 2004. The second questionnaire was mailed after the third questionnaire between March 2009 and February 2011. The MrOS Sleep Study, an ancillary study of the parent MrOS cohort, was conducted between December 2003 and March 2005 and recruited 3,135 MrOS participants for a comprehensive sleep assessment. Men were screened for nightly use of mechanical devices during sleep including pressure mask for sleep apnea (CPAP or BiPAP), mouthpiece for snoring or sleep apnea, or oxygen therapy and were generally excluded. The sleep visit included objective measures of sleep using actigraphy and polysomnography. Other measures at the sleep visit include neuropsychiatric measures, performance measures, health related questionnaires, routine exam measures previously completed at MrOS clinic visits and a urine and serum specimen collection. During the sleep study period, participants complete a tri-annual questionnaire every four months that contains information about incident cardiovascular events. All reported events are centrally adjudicated utilizing hospital records, study ECGs and other supporting documentation. The Hip Osteoarthritis study, another ancillary study of the parent MrOS cohort, was completed at the second clinic visit between March 2005 and May 2006. Participants were asked for consent for a hip x-ray and osteoarthritis measurements were obtained from these x-rays. DNA was extracted from baseline whole blood samples for use in genetic research. Consent for use of DNA was obtained through written consent. Raw GWAS data is housed at the study's coordinating center and not released as part of the dbGAP release. The raw data can be requested from the study's coordinating center. Only QC cleaned Plink files are available on dbGAP.

Study phs000373

DNA Methylation Analysis of Prostate Cancer Cell Lines and Tissues Using Next Generation Sequencing

Aberrant DNA methylation changes are known to occur during prostate cancer progression beginning with precursor lesions. Utilizing fifty nanograms of genomic DNA in Methylplex-Next Generation Sequencing (M-NGS) we mapped the global DNA methylation patterns in prostate tissues (n=17) and cells (n=2). Peaks were located from mapped reads obtained in each sequencing run using a Hidden Markov Model (HMM)-based algorithm previously used for Chip-Seq data analysis(http://www.sph.umich.edu/csg/qin/HPeak). The total methylation events in intergenic/intronic regions between benign adjacent and cancer tissues were comparable. Promoter CGI methylation gradually increased from -12.6% in benign samples to 19.3% and 21.8% in localized and metastatic cancer tissues and approximately 20% of all CpG islands (CGIs) (68,508) were methylated in tissues. We observed distinct patterns in promoter methylation around transcription start sites, where methylation occurred directly on the CGIs, flanking regions and on CGI sparse promoters. Among the 6,691 methylated promoters in prostate tissues, 2481 differentially methylated regions (DMRs) are cancer specific and several previously studied targets were among them. A novel cancer specific DMR in WFDC2 promoter showed 77% methylation in cancer (17/22), 100% methylation in transformed prostate cell lines (6/6), none in the benign tissues (0/10) and normal PrEC cells. Integration of LNCaP DNA methylation and H3K4me3 data suggested a role for DNA methylation in alternate transcription start site utilization. While methylated promoters containing CGIs had mutually exclusive H3K4me3 modification, the histone mark was absent in CGI sparse promoters. Finally, we observed difference in methylation of LINE-1 elements between transcription factor ERG positive and negative cancers. The comprehensive methylome map presented here will further our understanding of epigenetic regulation of the prostate cancer genome. Overall Design: We mapped the global DNA methylation patterns in prostate tissues (n=17) and cells (n=2) from fifty nanograms of genomic DNA using Methylplex-Next Generation Sequencing (M-NGS). For replicate analysis in cell lines, a total of 4 runs were completed for PrEC prostate normal cell line, and 5 runs were completed for LNCaP prostate cancer cell line. For tissue samples, 2 benign prostate samples were sequenced twice on Illumina next generation sequencing platform to access overall repeatability of M-NGS.

Study phs000597

Whole genome sequencing of neuroendocrine tumors of the small intestine

This dataset contains whole genome sequences for 13 patients with neuroendocrine (unique/multiple) tumor(s) of the small intestine. There are in total 25 tumor and 12 matched normal genomes. Libraries were prepared using a Illumina DNA PCR Free kit following the manufacturer’s recommendations and sequencing was performed on Illumina Novaseq6000 machine with a 2x151bp paired-end fashion. It contains data for : - 1 patient with 4 tumors and 1 matched normal - 1 patient with 3 tumors and 1 matched normal - 1 patient with 2 tumors, 1 liver metastasis and 1 matched normal - 2 patients with 1 tumor, 1 mesenteric nodule and 1 matched normal - 7 patients with 1 tumor and 1 matched normal - 1 patient with 3 tumors and 1 mesenteric nodule

Dataset EGAD50000000907

6806 results for "get free fc 26 coins Buyfc26coins.com is FC 26 coins official site..P1Ah"

in 27.88 milliseconds.

ELLIPSE Prostate Cancer Meta-Analysis and Genotyping

Circulating cell-free and extracellular vesicles-derived microRNA as prognostic biomarkers in patients with early-stage NSCLC: results from RESTING study

Cell-free DNA methylome and fragmentome analysis for disease relapse monitoring in patients with Ewing Sarcoma

Nuclease deficiencies alter plasma cell-free DNA methylationprofiles (mouse)

Nuclease deficiencies alter plasma cell-free DNA methylationprofiles (Human)

Circulating Tumor DNA Analysis Profiles of Repotrectinib in NTRK fusion–positive advanced solid tumors: a phase 1/2 trial

Indonesian Microbiome Ecology and Evolution v1 (raw data)

Whole genome and transcriptome sequencing of cancer of unknown primary tumours

The G2 gene expression signature and MYC overexpression are independent poor prognostic factors in childhood high-grade osteosarcoma

IYDP Indonesian Y chromosome Diversity Project

WGBS data (CancerLocator study) of cell-free DNA derived from human blood

Unrelated Donor Reduced Intensity Bone Marrow Transplant for Children with Severe Sickle Cell Disease (BMT CTN-0601-BioLINCC)

Submitter Portal

Circulating RNA profiles of healthy and preeclamptic pregnancies

Cohort-Based Genome-Wide Association Study of Glioma (GliomaScan)

Non-small cell lung cancer molecular subtypes and vulnerability to immunotherapy treatment combinations

Atezolizumab Plus Chemotherapy With or Without Bevacizumab in Advanced Biliary Tract Cancer: Clinical and Biomarker Data From the Randomized Phase II IMbrave151 Trial

Rapid brain tumor classification from sparse epigenomic data

Clinical significance of novel subtypes of acute lymphoblastic leukemia in the context of minimal residual disease-directed therapy

The Egyptian Collaborative Cardiac Genomics (ECCO-GEN) Project: Defining a Healthy Volunteer Cohort

FASTQ files of total RNA-Seq data of POPS control samples

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

Immune-Related Adverse Events after Immune Checkpoint Blockade-Based Therapy are Associated with Improved Survival in Advanced Sarcoma

Comparison of the treated celiac disease microbiome to that of controls

GDAP - Genome Diversity in Africa Project (2021-02-12)

Cell-free DNA and bone marrow samples from myelodysplastic syndromes

Poland Lesser Voivodeship - WGS

Poland Lodz Voivodeship - WGS

Poland Mazovia Voivodeship - WGS

Poland Silesian Voivodeship - WGS

Poland Holy Cross Voivodeship - WGS

Poland Greater Poland Voivodeship - WGS

Poland Pomeranian Voivodeship - WGS

Poland Kuyavian-Pomeranian Voivodeship - WGS

Poland Lublin Voivodeship - WGS

Poland Subcarpathian Voivodeship - WGS

Poland Lower Silesian Voivodeship - WGS

The G2 gene expression signature and MYC overexpression are independent poor prognostic factors in childhood high-grade osteosarcoma

WGBS data of solid liver tumor DNA, and WGBS data of cell-free DNA derived from human blood, for CancerDetector study

NextGen Consortium: Globin Gene Expression in Sickle Cell Genotype-Specific iPS Cells

Single-Cell Genomic and Transcriptomic Analysis of the Aging Human Brain

APOBEC3 mutagenesis drives therapy resistance in breast cancer

Direct Detection of Early-stage Cancers Using Circulating Tumor DNA

A neoadjuvant, phase II trial demonstrates efficacy and tolerability of Talimogene laherparepvec in cutaneous basal cell carcinoma (NeoBCC trial)

Identifying New Genetic Subtypes in Follicular Lymphoma

FASTQ files of total RNA-Seq data from the POPS SGA (Small for Gestational Age) samples

FASTQ files of total RNA-Seq data from the POPS PET (pre-eclamptic) samples

Osteoporotic Fractures in Men (MrOS)

DNA Methylation Analysis of Prostate Cancer Cell Lines and Tissues Using Next Generation Sequencing

Whole genome sequencing of neuroendocrine tumors of the small intestine