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• Young Boost Trial for Breast Cancer patients

  The Young Boost Trial (YBT, YOUNG BOOST / BOOG 2004-01 (Borstkanker) | Kanker.nl investigated the optimal radiation dose for breast cancer patients aged 50 years or younger, treated with breast-conserving therapy (BCT). In this randomized study, participants were assigned to receive either a 26 Gy or a 16 Gy radiation boost, with the primary endpoint being local recurrence. To explore potential predictive biomarkers of treatment response in this patient group, whole exome sequencing (WES) was performed on tumor samples to identify genetic factors that could guide personalized treatment strategies and improve clinical outcomes for these young breast cancer patients.

  Study EGAS50000000797

• Expression data from the Neo-CheckRay trial

  ER+/HER2- early breast cancer were treated with neoadjuvant immune-modulating SBRT and anti-CD73. The RNAseq dataset contains fastq files for 234 samples corresponding to 134 patients. There are 208 breast cancer samples, taken at screening (N=136) or week 6 (N=76). In addition, there are 26 lymph node samples taken at screening.

  Dataset EGAD50000002552

• H3Africa H3AChipDesign Phenotype

  Basic phenotypic data (country, ethnicity and sex) for 348 samples of the H3Africa Chip Design Study. Divided into 8 datasets of 41 samples from Zambia, 24 samples from Cameroon, 50 samples from Mali, 26 samples from Cameroon, 49 samples from Nigeria, 48 samples from Botswana, 50 samples from Benin, 60 samples from Burkina Faso and Ghana.

  Dataset EGAD00001005310

• Whole-exome/genome sequencing of childhood acute leukemia in Iraq

  This dataset contains 26 whole-genome sequencing (13 paired tumor and normal), 106 whole-exome sequencing (53 paired tumor and normal), and 43 targeted sequencing data. Sequencing was performed using an Illumina platform. The data are BAM files aligned to the hg19 reference genome.

  Dataset EGAD00001007873

• RNA-seq samples

  Raw FASTQ files obtained by RNA sequencing of tumor samples from patients (age 12-29) with newly diagnosed, recurrent intermediate or high-grade sarcoma.

  Dataset EGAD00001008393

• Oral Immunotherapy for Induction of Tolerance and Desensitization in Peanut-Allergic Children (IMPACT)

  Brief Summary:This is a randomized, double-blind, placebo-controlled, multi-center study comparing peanut oral immunotherapy (OIT) to placebo in the induction of tolerance and desensitization in peanut-allergic children. Eligible participants with peanut allergy will be randomly assigned to receive either peanut OIT or placebo for 134 weeks followed by peanut avoidance for 26 weeks.Detailed Description:An initial oral food challenge (OFC) to 1 g of peanut flour (500 mg peanut protein) will be conducted. Participants must have a clinical reaction during this OFC to initiate study dosing. After the initial OFC, the study design includes four phases:Initial dose escalation (1 day): Peanut or placebo dosing will be given incrementally and increase every 20 minutes until a dose of 12 mg peanut flour (6 mg peanut protein) or placebo flour is given. Build-up (30 weeks): Initial observed dose administration of highest tolerated dose, followed by daily OIT at home with return visit every 2 weeks for dose escalation. Maintenance (104 weeks):The participant will continue on daily OIT with return visits every 13 weeks. At the end of this phase the participant will undergo a blinded OFC to 10 g peanut flour (5 g peanut protein). Avoidance (26 weeks): In this final phase participants will be seen every 13 weeks. At the completion of this phase participants will have a final blinded OFC to 10g peanut flour (5 g peanut protein)

  Study phs003109

• Exome Sequencing of Esophageal Adenocarcinoma

  The incidence of esophageal adenocarcinoma (EAC) has risen 600% over the last 30 years. When coupled to the five-year survival rate of only 15% for this disease, identification of new therapeutic targets for EAC is of great importance. Here, we analyze the mutational spectra identified from the whole genome sequencing of 16 EACs and complete exome sequencing of 149 EAC tumors and matched germline samples. We identify a novel mutation signature marked by high prevalence of A to C transversions at AA*(N) trinucleotides. Notably, the development of EAC is preceded by pathologic intestinal metaplasia of the lower esophagus, Barrett's esophagus, itself a response to injury from gastric-esophageal reflux disease (GERD). Thus, we hypothesize to represent these AA*(N) mutations to a novel signature of GERD-induced mutagenesis. Analysis of the exome data identified 26 genes subject to statistically significant recurrent mutation. Of these 26 genes, only TP53, CDKN2A, SMAD4, and PIK3CA had been previously implicated in EAC. Novel mutations include those targeting chromatin modifying factors and novel candidate contributors to EAC: SPG20, TLR4, ELMO1 and DOCK2. Of these, ELMO1 and DOCK2 are notably direct dimerization partners that act to activate Rac1 to enhance cellular invasiveness, thus generating new hypotheses about the potential for the Rac1 pathway to be a novel target for therapy of EAC. "Reprinted from 'Unraveling the mutational complexity of esophageal adenocarcinoma', with permission from Nature Genetics."

  Study phs000598

• Download Metadata

  Metadata Distribution Welcome to the realm of Metadata Distribution within the EGA ecosystem! Our Metadata REST API empowers you to effortlessly retrieve metadata from the expansive landscape of EGA. By utilising this API, you gain access to publicly available insights across various EGA domains, including studies, samples, experiments, runs, analyses, policies, DACs, and datasets. Furthermore, this API facilitates cross-referencing of objects, enabling you to gather, for example, all the datasets associated with a specific DAC, seamlessly. In addition, we have added the ability to query private data using the metadata API. If you possess the necessary permissions, you can access behind-the-login private data for a specified list of datasets. Metadata Distribution Index Identifiers Dataset Mappings Website Download Metadata API - Private Identifiers At the core of EGA's organisational structure are unique accessions that serve as essential tags for our diverse objects. Here's a quick overview of the accessions and their corresponding object types: EGA Accession ID EGA Object description EGAS EGA Study Accession ID EGAC EGA DAC Accession ID EGAP EGA Policy Accession ID EGAN EGA Sample Accession ID EGAR EGA Run Accession ID EGAX EGA Experiment ID EGAZ EGA Analysis Accession ID EGAD EGA Dataset Accession ID EGAB EGA Submission ID EGAF EGA File Unique Accession ID For further information check our metadata schema documentation. Dataset Mappings For authorised datasets, comprehensive mappings reveal meaningful connections: Sample_file: This file presents information about the linkage between samples and files available in the dataset. Study_experiment_run_sample: This file presents information about the linkage between studies, experiments, runs, and samples within the dataset. Study_analysis_sample: This file presents information about the linkage between studies, analyses, and samples contained within the dataset. Run_sample: This file presents information about the linkage between runs and samples within the dataset. Analysis_sample: This file presents information about the linkage between analyses and samples within the dataset. An empty file indicates the absence of corresponding information. Website Download Our website serves as your gateway to downloading metadata. Simply navigate to the dataset page, and you'll find a blue Metadata button. Once authenticated, you can click this button for authorised datasets. If you lack permissions for a particular dataset, request access by clicking the 'Request Access' button. For authorised datasets, choose your preferred metadata format: CSV, TSV, or JSON. Metadata API - Private Leverage the power of programmatic metadata downloads! Start by authenticating yourself with your credentials to obtain an access token. With this token, programmatically query private information. Queries mirror the structure of the Public Metadata API. However, behind the login, you can delve into specific mapping information (as mentioned above in dataset mappings) alongside object-level exploration. Authentication An active session is required to work with the API. Each time you log in with your credentials a new session is started, which is identified by an access_token. Below an example on how to obtain one using curl: curl https://idp.ega-archive.org/realms/EGA/protocol/openid-connect/token \ -d 'client_id=metadata-api' \ -d 'username=...' \ --data-urlencode 'password=...' \ -d 'grant_type=password' All responses from the API are in JSON format. A successful response should include a new token to be used for the session: {"access_token":"eyJhbGciOiJSUzI1NiIsInR5cCIgOiA...TNw", "expires_in":300, "refresh_expires_in":1800, "refresh_token":"eyJhbGciOiJIUzI1NiIsInR5cCIgOiA...pTX10", "token_type":"Bearer", ... } Save the access_token value and include it in the API call headers. Example query usage Below you can find some example of queries available behing authentication and authorisation. Querying study-experiment-run-sample mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/study_experiment_run_sample \ -H 'Authorization: Bearer access_token' Querying run-sample mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/run_sample \ -H 'Authorization: Bearer access_token' Querying study-analysis-sample mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/study_analysis_sample \ -H 'Authorization: Bearer access_token' Querying analysis-sample mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/analysis_sample \ -H 'Authorization: Bearer access_token' Querying sample-file mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/sample_file \ -H 'Authorization: Bearer access_token' You can get a different output format by adding one of these options to the curl command: -H 'Accept: text/tsv' -H 'Accept: application/json' -H 'Accept: text/csv' For more detailed information, refer to the Metadata API Specification.

  Documentation access/download/metadata

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 17)

  The dataset contains whole genome sequencing data of 26 high-grade serous carcinoma (HGSC) patients sequenced with Novoseq 6000. The 86 samples are either fresh frozen tumour samples or blood samples. The files provided are paired fastq files.

  Dataset EGAD50000002409

• WES of der(1;7)(q10;p10)

  This dataset contains the BAM files of WES of 26 myeloid neoplasm patients with der(1;7)(q10;p10)(+) cases. The dataset was used to identify key driver genes in patients with der(1;7)(q10;p10). Already known drivers along with novel driver genes were identified through the use of this WES.

  Dataset EGAD50000000986

• Contribution of systemic and somatic factors to clinical response and resistance in urothelial cancer: an exploratory multi-omic analysis

  Patients with metastatic urothelial cancer (n=29) were treated with atezolizumab (anti-PD-L1). All 29 patients had T-cell receptor sequencing (TCR-seq) of the pre-treatment blood; 24 also had TCR-seq on at least one post-treatment blood sample. 24 patients had TCR-seq of their pre-treatment tumors. TCR-seq data can be found at http://doi.org/10.5281/zenodo.546110. 26 patients also had RNAseq of their tumors and whole exome sequencing (WES) of their tumors and matched normal blood. WES results for one sample were excluded from our analysis after failing to meet coverage requirements.

  Study phs001743

• Radiation-Related Genomic Profile of Papillary Thyroid Cancer after the Chernobyl Accident

  The April 26, 1986 accident at the Chernobyl nuclear power plant in northern Ukraine resulted in the release of radioactive contaminants, which were deposited in the surrounding areas in Ukraine, Belarus, and Russia. The main radiation-related health effect resulting from these exposures is the increased occurrence of thyroid cancer among individuals who were children at the time of the accident or born shortly thereafter. The purpose of this study was to conduct a comprehensive genomic landscape analysis of papillary thyroid tumors arising in individuals who were exposed as children to radioactive iodine (I-131) from the Chernobyl nuclear power plant accident.

  Study phs001134

• COVID-19-Induced Immune Alterations in Infants

  Although previous studies have described some overlap between COVID-19-induced immune alterations in adults and children, no systematic immune profiling studies have been reported in infants. We applied a multidimensional approach to decipher the immune responses to SARS-CoV-2 infected infants (n=26; 10 mild, 11 moderate and 5 severe) and healthy matched controls (n=14). Single-cell RNA-seq profiling (scRNA-seq) of PBMCs revealed alterations in cell composition upon infection, with most cell types demonstrating an interferon-stimulated gene (ISGhi) state. Our findings shed insight into the immune responses to SARS-CoV-2 in the first year of life.

  Study phs002655

• Evolution of Structural Rearrangements in Prostate Cancer Intracranial Metastases

  Intracranial metastases in prostate cancer are uncommon but clinically aggressive. We sought to characterize prostate cancer intracranial metastases in order to improve our understanding of their pathogenesis and to promote the search for new treatment strategies. We evaluated the clinical and molecular characteristics of 36 patients with metastatic prostate cancer to either the dura or brain parenchyma. We performed whole genome sequencing (WGS) on samples from 21 patients. The WGS samples include 10 intracranial prostate cancer metastases, as well as WGS of primary prostate tumors from men who later developed metastatic disease (n=6) and non-brain prostate cancer metastases (n=26).

  Study phs003357

• Pre-existing immunity drives the response to neoadjuvant chemotherapy in esophageal adenocarcinoma

  Esophageal adenocarcinoma (EAC) is a highly aggressive tumor. Patients with locally advanced disease undergo neoadjuvant chemotherapy (nCT) before surgery, however fewer than 30% of treated patients achieve a pathological complete response associated with increased 5-year overall survival. We set out to elucidate the mechanisms the response to nCT by multi-dimensional profiling of pre-treatment tumor biopsies and blood samples from EAC patients. In particular we performed whole exome sequencing (WES) and RNAseq on n=26 baseline EAC tumor; two additional EAC samples underwent only WES. WES on matched peripheral blood mononuclear cells (PBMCs) were used as germline control.

  Study EGAS00001007245

• Peripheral blood DNA transcriptomics of ustekinumab treatment response in patients with Crohn's disease

  Data pertains longitudinal transcriptomic data measured from blood obtained from patients with Crohn's disease that were starting treatment with ustekinumab. Samples were obtained prior to treatment and approximately 26 weeks into treatment during response assessment. At response assessment, patients were classified as responders (R) or non-responders (NR) based on a strict combination of endoscopic, biochemical and clinical criteria: ≥50% reduction in the endoscopic SES-CD score, corticosteroid-free clinical remission (≥3 point drop98 in HBI or HBI ≤4 and no systemic steroids) and/or biochemical response (C-reactive protein (CRP) and fecal calprotectin reduction ≥50% or ≤5 mg/L and fecal calprotectin ≤250 µg/g). Modified response was defined as a combination of corticosteroid-free clinical- (HBI ≤4) and biochemical (CRP ≤5 mg/L and/or fecal calprotectin ≤250 µg/g) remission between week 26-52 without treatment change through week 52. Transcriptomic analyses was conducted through RNA sequencing, wherein mRNA was extracted utilizing the QIAsymphony system, converted into cDNA and sequenced in a paired-end format on the Illumina NovaSeq6000 at the Amsterdam UMC Core Facility Genomics, generating a dataset comprising 40 million 150 bp-reads.

  Dataset EGAD50000000386

• Peripheral blood DNA transcriptomics of vedolizumab treatment response in patients with Crohn's disease

  Data pertains longitudinal transcriptomic data measured from blood obtained from patients with Crohn's disease that were starting treatment with vedolizumab. Samples were obtained prior to treatment and approximately 26 weeks into treatment during response assessment. At response assessment, patients were classified as responders (R) or non-responders (NR) based on a strict combination of endoscopic, biochemical and clinical criteria: ≥50% reduction in the endoscopic SES-CD score, corticosteroid-free clinical remission (≥3 point drop98 in HBI or HBI ≤4 and no systemic steroids) and/or biochemical response (C-reactive protein (CRP) and fecal calprotectin reduction ≥50% or ≤5 mg/L and fecal calprotectin ≤250 µg/g). Modified response was defined as a combination of corticosteroid-free clinical- (HBI ≤4) and biochemical (CRP ≤5 mg/L and/or fecal calprotectin ≤250 µg/g) remission between week 26-52 without treatment change through week 52. Transcriptomic analyses was conducted through RNA sequencing, wherein mRNA was extracted utilizing the QIAsymphony system, converted into cDNA and sequenced in a paired-end format on the Illumina NovaSeq6000 at the Amsterdam UMC Core Facility Genomics, generating a dataset comprising 40 million 150 bp-reads.

  Dataset EGAD50000000385

• Longitudinal sampling in relapsed and refractory Hodgkin lymphoma

  Ultra-deep next-generation panel-sequencing on 59 FFPE-samples (20 LTR, 26 relapsed (rHL: 11 initial-diagnosis, 15 relapse) and 13 primary-refractory (prHL: 8 initial-diagnosis, 5 progression) from 44 cHL-patients applying a hybrid-capture approach. Data was processed as described in the publication and mark duplicated bam files were uploaded.

  Dataset EGAD50000000210

• WGS Fastq files from the CPC-Gene project in support of PRAD-CA, DCC Release 26

  This dataset contains fastq files with Whole genome sequencing data for the CPC-Gene Project. Data from each sample was generated using multiple whole genome libraries and sequenced across multiple runs

  Dataset EGAD00001003761

• ICGC PCAWG Dataset: ORCA-IN_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: ORCA-IN.

  Dataset EGAD00001002120

• GEnetics of Nephropathy - an International Effort (GENIE) GWAS of Diabetic Nephropathy in the UK GoKinD and All-Ireland Cohorts

  Diabetic kidney disease, or diabetic nephropathy (DN), is one of the leading causes of end-stage renal disease in the United States and worldwide. DN is a common complication of long-standing type 1 and type 2 diabetes. The clinical course is characterized by development of proteinuria and gradual loss of kidney function. Although existing treatments that decrease proteinuria have been shown to moderately abate progression of diabetic kidney disease, many affected patients, who do not die from cardiovascular disease, go on to develop terminal renal failure, necessitating costly renal replacement therapies, such as dialysis and renal transplantation. Type 1 diabetes (T1D) can have its onset in childhood and affected individuals often develop end-stage renal disease in early adulthood, leading to further loss of quality of life. The genetic basis of the disease is not well understood. The GENIE (GEnetics of Nephropathy an International Effort) consortium was initiated to perform the most comprehensive and well powered DN susceptibility genome wide association study (GWAS) analysis to date, using the largest collection of type 1 diabetics with and without kidney disease across four study cohorts. The UK-ROI samples were genotyped as part of this project. UK-ROI Sample Description The UK-ROI collection consists of samples derived from the Republic of Ireland (Dr. Catherine Godson, PI, at University College, Dublin, Ireland) and the United Kingdom (Warren 3 and Genetics of Kidneys in Diabetes UK, UK GoKinD, Dr. Alexander P. Maxwell, PI, at Queen's University of Belfast, UK). All study subjects met the inclusion criteria: white individuals with T1D, diagnosed before 31 years of age, whose parents and grandparents were born in the British Isles.

  Study phs000389

• Whole Exome Sequencing of Human Gastro-esophageal Cancer PDXs

  The dataset includes 51 whole exome sequencing datasets generated using Illumina paired-end sequencing technology. These data derive from 26 patient-derived xenograft (PDX) tumors and their matched normal tissues, which consist of either normal gastric mucosa or blood samples. In one case (GTR0607), the matched normal tissue data are unavailable. As a result, the dataset comprises 102 FASTQ files, providing raw sequencing reads for comprehensive genomic analysis.

  Dataset EGAD50000001407

• Whole Exome Sequencing of paired gDNAs and PPGL tumor DNA from patients with cyanotic congenital heart disease

  Fastq files from Whole Exome Sequencing of 12 paired germline DNA (from blood/saliva) and 14 PPGL tumor DNA (from formalin-fixed paraffin-embedded (FFPE) blocks from surgery) from patients with cyanotic congenital heart disease (CCHD) and pheochromocytoma and paraganglioma (PPGL). Sequencing was performed using the Illumina HiSeq4000.

  Dataset EGAD50000001201

• WGS data of patient derived organoids (PDO) generated from dMMR colorectal tumor subclones

  The dataset includes bam files from WGS of 26 monoclonal patient derived organoid (PDO) lines isolated from 6 independent tumor subclones of a dMMR colorectal tumor. These organoids were grown as part of an in vitro timecourse experiment for the duration of 9 weeks; bam files represent the mutational load at the start of the timecourse (t0) and the end of the timecourse (t1).

  Dataset EGAD50000000427

• RNA-seq of atypical 3q26 samples

  RNA was isolated using phenol-chloroform extraction followed by DNase digestion or using the Qiagen Allprep DNA/RNA kit and protocol (Qiagen, #80204). cDNA synthesis was done using the SuperScript II Reverse Transcriptase kit (Invitrogen). Quantitative real-time PCR was performed by using primers as described previously13,21 on the 7500 Fast Real-time PCR System (Applied Biosystems). Relative levels of gene expression were calculated using the ΔΔCt method

  Dataset EGAD00001006106