Search Results - EGA European Genome-Phenome Archive

neoALTTO

RNAseq fastq files for 254 samples for the neoALTTO study of lapatinib, trastuzumab or combination in HER2+ breast cancer patients. Those are pre-treatment baseline samples.

Dataset EGAD00001011354

Targeted sequencing using SPET for Mesothelioma.

Dataset EGAD00001001916

Mucoepidermoid carcinoma- normals

Whole exome sequencing data for 18 mucoepidermoid carcinoma samples. The samples were used for Illumina TruSeq library construction and captured using Agilent V4 exome panel. The PE fastq files are provided.

Dataset EGAD00001004946

MT amplicon sequencing reads of 217 Egyptian individuals

This data set contains for 217 Egyptian individuals the amplicon sequencing reads mapping to chrM. These were subsequently used for haplogroup assignment.

Dataset EGAD00001006040

Genomic Data Archive From the Network for Pancreatic Organ Donors With Diabetes

The Network for Pancreatic Organ Donors with Diabetes (nPOD) is the largest biorepository of human pancreata from organ donors with type 1 diabetes (T1D), maturity-onset diabetes of the young (MODY), cystic fibrosis-related diabetes (CFRD), type 2 diabetes (T2D), gestational diabetes, and islet autoantibody positive (AAb+)/pre-T1D. The mission of the nPOD is to distribute biospecimens and associated de-identified data/metadata to an international researcher network, and to promote the development of new treatments for these diabetes conditions. Here, we describe the release of high-parameter genotyping data for the nPOD cohort. Specifically, 372 subjects were genotyped using a customized precision medicine single nucleotide polymorphism (SNP) microarray (UFDIchip). These data were technically validated using published algorithms to evaluate donor relatedness, ancestry, imputed HLA, and T1D genetic risk score. Additionally, 207 subjects were queried for rare known and novel coding region variants via whole exome sequencing (WES). These data are now publicly available, enabling genotype-selected sample requests and the study of novel genotype : phenotype associations, ultimately to explain diabetes heterogeneity and inform precision medicine strategies to interrupt diabetes pathogenesis.

Study phs002861

HTAN Pilot Project: Single-Cell Transcriptomics Toolbox for Fresh and Frozen Human Tumors (Lung, Breast, Ovarian, Melanoma, Neuroblastoma, Sarcoma, Glioblastoma, Glioma, and Leukemia)

Single cell transcriptomics is a powerful tool to map the complex tumor microenvironment, providing unprecedented resolution into cell types, cell states, cell interactions, and tumor heterogeneity. Depending on their tissue site and whether processing begins from a fresh or frozen sample, different tumors require different optimizations in order to obtain high quality single cell transcriptomic data. In this study, we profiled a range of tumor types, varying in cell-of-origin, solid and non-solid forms, patient ages, and transitions. The tumors also further varied in their tissue site and in their sample collection method. To enable profiling of such diverse samples, we developed a systematic toolbox for single cell RNA-Seq and single nucleus RNA-Seq of fresh and frozen clinical tumor samples. We validated this toolbox for 216,490 cells and nuclei extracted from 39 samples across 23 tumors (some tumors were split into multiple samples). The 23 tumors represented eight unique tumor types. This toolbox comprises both experimental and computational protocols as well as guidelines for comparing and selecting protocols for the biological problem of interest.

Study phs001983

Ultra-Low-Pass Whole Genome Sequencing of Cell-Free DNA for Large B-Cell Lymphoma

While deep targeted DNA sequencing of liquid biopsies has shown prognostic utility in large B-cell lymphoma (LBCL), the routine clinical adoption of these assays remains limited due to their high costs. Here, leveraging a well-annotated cohort of encompassing both frontline and relapsed/refractory (R/R) LBCL, we profiled patient plasma samples with two complementary modalities – ultra-low-pass whole genome sequencing (ulpWGS) and deep targeted DNA sequencing, the former being a cost-effective method to profile large scale chromosomal abnormalities and estimate tumor burden. Our findings revealed a strong association of high cell-free tumor burden by both genomic profiling modalities with established measures of tumor burden and patient survival. Notably, the associations with survival remained statistically significant after accounting for international prognostic index scoring. Furthermore, we showed that del(17p) in circulating tumor DNA as detected by ulpWGS was strongly associated with TP53 mutation status and predicted for significantly inferior patient outcome in frontline but not R/R LBCL patients. Our study demonstrates that ulpWGS can provide robust prognostic biomarkers for both frontline and R/R LBCL, highlighting its broad applicability for risk stratification.

Study EGAS50000001027

Discovery of immunotherapy targets for pediatric solid and brain tumors by exon-level expression

Immunotherapy with chimeric antigen receptor T cells for pediatric solid and brain tumors is constrained by available targetable antigens. Cancer-specific exons present a promising reservoir of targets; however, these have not been explored and validated systematically in a pan-cancer fashion. To identify cancer specific exon targets, we analyze 1,532 RNA-seq datasets from 16 types of pediatric solid and brain tumors for comparison with normal tissues using a newly developed workflow. We find 2,933 exons in 157 genes encoding proteins of the surfaceome or matrisome with high cancer specificity either at the gene (n=148) or the alternatively spliced isoform (n=9) level. Expression of selected alternatively spliced targets, including the EDB domain of fibronectin 1, and gene targets, such as COL11A1, are validated in pediatric patient derived xenograft tumors. We generate T cells expressing chimeric antigen receptors specific for the EDB domain or COL11A1 and demonstrate that these have antitumor activity. The full target list, explorable via an interactive web portal (https://cseminer.stjude.org/), provides a rich resource for developing immunotherapy of pediatric solid and brain tumors using gene or AS targets with high expression specificity in cancer.

Study EGAS00001007766

Rapid Whole Genome Sequencing for Genetic Disease Diagnosis in Neonatal Intensive Care Units

Monogenic diseases are frequent causes of neonatal morbidity and mortality, and disease presentations are often undifferentiated at birth. More than 3,500 monogenic diseases have been characterized, but clinical testing is available for only some of them and many feature clinical and genetic heterogeneity. As such, an immense unmet need exists for improved molecular diagnosis in infants. Because disease progression is extremely rapid, albeit heterogeneous, in newborns, molecular diagnoses must occur quickly to be relevant for clinical decision-making. We describe 50-hour differential diagnosis of genetic disorders by whole-genome sequencing (WGS) that features automated bioinformatic analysis and is intended to be a prototype for use in neonatal intensive care units. Retrospective 50-hour WGS identified known molecular diagnoses in two children. Prospective WGS disclosed potential molecular diagnosis of a severe GJB2-related skin disease in one neonate; BRAT1-related lethal neonatal rigidity and multifocal seizure syndrome in another infant, identified BCL9L as a novel, recessive visceral heterotaxy gene (HTX6) in a pedigree, and ruled out known candidate genes in one infants. Sequencing of parents or affected siblings expedited the identification of disease gene in prospective cases. Thus, rapid WGS can potentially broaden and foreshorten differential diagnosis, resulting in fewer empirical treatments and faster progression to genetic and prognostic counseling. Reprinted from Saunders et. al, Rapid Whole-Genome Sequencing for Genetic Disease Diagnosis in Neonatal Intensive Care Units. Sci. Transl. Med. 4, 154ra135 (2012; PMID: 23035047) with permission from AAAS.

Study phs000564

Reference Standards for Mosaic Variant Detection

After conception, postzygotic mutations continuously occur throughout life in humans, causing somatic mosaicism in an individual. The variant type, time of origination, and locations of the mosaic mutations result in unique mosaic patterns in a combinatorial manner and further affect phenotypes, including various noncancerous diseases. Several efforts have, thus, been made to identify the mutational landscape and mechanisms underlying the mosaic mutations. From a technical aspect, the accurate detection of mutations is at the core of the mosaicism research, and the construction of a standard reference is a critical first step to serve as the basis for analytical validation and benchmarks for germline and somatic mutation detection. Furthermore, a reference standard for mosaic mutations is urgently needed to enable more advanced research.Herein, we generated robust, large-scale, and cell line mixture-based reference standards that contain abundant mosaic SNVs and INDELs along with wild-type sites and germ line variants. Moreover, the whole reference standard set mimics the cumulative aspect of mosaic variant acquisition in the early developmental stage through a progressive cell line mixing with confirmed genotypes. It can be used for optimizing the current use of mosaic variant detection strategies, as well as developing algorithms for future improvements.We previously generated an NCBI BioProject (PRJNA758606) to release much of these data. Only the data that are subject to authorized access constraints have been included in this submission to dbGaP. The two data sources are thus, complementary to each other.

Study phs003399

Preclinical Pediatric Molecular Analysis for Therapy Choice (MATCH)

Purpose: Pediatric solid tumors arise from diverse tissues during development and exhibit a wide range of molecular, cellular and genetic features. This diversity, combined with the low incidence of pediatric cancer makes it increasingly difficult to personalize therapy for individual patients based on the unique features of their tumors. Therefore, well-credentialed preclinical models that capture the diversity and heterogeneity of pediatric solid tumors are essential for identifying molecular targeted therapeutics for precision medicine. Experimental Design: Here, we report 281 orthotopic patient derived xenografts (O-PDXs) from 224 patients representing 24 different types of pediatric solid tumors. We have performed genomic characterization of the O-PDXs and compared them to their corresponding patient tumors. To demonstrate the feasibility and utility of using such a diverse collection of O-PDXs in preclinical studies, we performed a preclinical pediatric precision medicine trial based on the NCI-COG Pediatric MATCH trial enrollment criteria. We also tested molecular targeted therapy for a novel oncogenic fusion recently reported in pediatric melanoma and precision drug delivery using nano-liposomal irinotecan. Results: In the preclinical match study, we identified one specific single agent response to LY3023414 in an osteosarcoma model with a TSC2 variant of unknown significance. Combinations of nano-liposomal irinotecan were effective in treating both Ewing sarcoma and rhabdomyosarcoma xenografts. Conclusion: Our studies demonstrate the value of large, well-credentialed preclinical models for future precision medicine in pediatric oncology using single agents, drug combinations and novel drug formulations.

Study EGAS00001008011

Platelet RNAseq data for SLFN14 K219N patients

Pathogenic missense variants in SLFN14, which encodes an RNA endoribonuclease protein that regulates rRNA degradation, are known to cause inherited thrombocytopenia with impaired platelet aggregation and ATP secretion. Despite rather mild laboratory defects, these patients display an obvious bleeding phenotype. The function of SLFN14 in megakaryocyte (MK) and platelet biology is unknown. This study aims to characterize the platelet transcriptome in patients with a SLFN14 K219N variant and model the disease in the immortalized megakaryocyte cell line imMKCL. Total platelet RNA was sequenced for two patients and 19 healthy controls. Differential gene expression analysis yielded a total of 2999 and 2888 significantly (|log2FC|>1, FDR<0.05) up- and downregulated genes, respectively. Remarkably, these downregulated genes were not enriched for any biological pathway while upregulated genes were enriched for pathways involved in (mitochondrial) translation and transcription with a significant upregulation of 134 ribosomal protein genes (RPG). Heterozygous and homozygous SLFN14 K219N imMKCL showed a defect in MK differentiation that aggravated during cell passaging of undifferentiated cells and in proplatelet formation. SLFN14 defective platelets and MK showed signs of rRNA degradation while this was absent in undifferentiated imMKCL cells. Upregulation of RPG through increased mTOR signaling in SLFN14 K219N MK seems to be a compensatory response for rRNA degradation. Indeed, mTOR inhibition with rapamycin resulted in further enhanced rRNA degradation in SLFN14 K219N MK. Taken together, our study indicates dysregulation of mTOR-regulated ribosomal biogenesis as the disease mechanism for SLFN14-related thrombocytopenia.

Study EGAS00001006339

Bioinformatic Methods and Bridging of Assay Results for Reliable Tumor Mutational Burden Assessment in Non-Small Cell Lung Cancer

Tumor mutational burden (TMB) has emerged as a predictive biomarker of response to immune checkpoint inhibitors. Standardization of TMB measurement is essential for implementing diagnostic tools to guide treatment. Here we evaluate bioinformatic TMB analysis by whole exome sequencing (WES) in formalin-fixed, paraffin-embedded samples. In CheckMate 026, TMB was retrospectively assessed in 312 patients with non-small cell lung cancer (58% of the intent-to-treat population) who received first-line nivolumab treatment or chemotherapy. We examined the sensitivity of TMB assessment to bioinformatic filtering methods and assessed concordance between TMB data derived by WES and the FoundationOne CDx™ assay. TMB scores comprising synonymous, indel, frameshift, and nonsense mutations (all mutations) were 3.1-fold higher than data including missense mutations only, but values were highly correlated (Spearman’s r = 0.99). Scores from CheckMate 026 samples including missense mutations only were similar to those generated from data in The Cancer Genome Atlas, but those including all mutations were generally higher. Using databases for germline subtraction (instead of matched controls) showed a trend for race-dependent increases in TMB scores. Parameter variation can therefore impact TMB calculations, highlighting the need for standardization. Encouragingly, WES and FoundationOne CDx outputs were highly correlated (Spearman’s r = 0.90) and differences could be accounted for by empirical calibration, suggesting that reliable TMB assessment across assays, platforms and centers is achievable.

Study EGAS00001003661

Low-coverage whole genome sequencing for a highly selective cohort of severe COVID-19 patients

Background Despite advances in identification of genetic markers associated to severe COVID-19, the full genetic characterisation of the disease remains elusive. Imputation of low-coverage whole genome sequencing (lcWGS) has emerged as a competitive method to study such disease-related genetic markers as they enable genotyping of most common genetic variants used for genome wide association studies. This study aims at exploring the potential use of imputation in lcWGS for a highly selected severe COVID-19 patient cohort. Findings We generated an imputed dataset of 79 variant call format (VCF) patient files using the GLIMPSE1 tool, each containing, on average, 9.5 million single nucleotide variants. The validation assessment of imputation accuracy yielded a squared Pearson correlation of approximately 0.97 across sequencing platforms, showing that GLIMPSE1 can be used to confidently impute variants with minor allele frequency up to approximately 2% in Spanish ancestry individuals. We conducted a comprehensive analysis on the patient cohort, examining hospitalisation and intensive care utilisation, sex and age-based differences, and clinical phenotypes using a standardised set of medical terms specifically developed to characterise severe COVID-19 symptoms for this cohort. Conclusion This dataset highlights the utility and accuracy of lcWGS imputation in the study of COVID-19 severity, setting a precedent for other applications in resource-constrained environments. The methods and findings presented here may be leveraged in future genomic projects, providing vital insights for health challenges like COVID-19.

Study EGAS00001007573

Centers for Common Disease Genomics (CCDG) - Whole Genome Sequencing in Type 1 Diabetes (T1DGC)

The Type 1 Diabetes Genetics Consortium (T1DGC) was established to collect resources (biological samples and data) and conduct research to better understand the genetic basis of type 1 diabetes (T1D). Collection was initiated by ascertaining affected sib-pair families (both parents, two affected siblings and, when available, an unaffected sibling), collected from five geographic regions through four recruitment networks (Asia-Pacific, Europe, North America, United Kingdom). In addition, the T1DGC collected trio families (both parents and affected child) and cases and controls from low-prevalence populations (African-American, with four grandparents self-reporting as African ancestry; Mexican-American, with four grandparents self-reporting as ancestry from Mexico). The T1DGC also served as a repository for contributed collections from other studies, all meeting the broad data-sharing policy of the T1DGC, for inclusion in the genetic studies. These collections include T1D case samples ascertained from the UK Genetic Resource Investigating Diabetes (UK GRID) cohort, SEARCH for Diabetes in Youth (SEARCH), The Genetics of Kidneys in Diabetes (GoKinD), and control samples obtained from the British 1958 Birth Cohort, the UK National Blood Services collection, CLEAR (Consortium for the Longitudinal Evaluation of African-Americans with Early Rheumatoid Arthritis), the New York Cancer Project (NYCP), and other cohorts. For the NHGRI-funded Centers for Common Disease Genomics (CCDG) project, participants with T1D and ancestry-matched controls were identified through the T1DGC, either through direct ascertainment or by contribution from other sources to the T1DGC. As the CCDG has focused initially on non-Caucasian populations for whole genome sequencing, T1DGC participants of African, Mexican and Asian ancestry (targeting ~1200 cases and ~1200 controls in each ancestral group) and a small group of participants of Northern European ancestry (~100 cases, ~100 controls) were to be contributed to the study. Whole genome sequencing of T1DGC samples would be conducted at Washington University McDonnell Genome Institute and based upon matching case-control status within an ancestry group and prioritization by the CCDG.

Study phs001222

Privacy Notice for the Account User

Privacy Notice for EGA User Account This Privacy Notice explains what personal data is collected by the specific service you are requesting, for what purposes, how it is processed, and how we keep it secure. Note that this service collects personal data directly provided by the user, and also collects personal data from users that is provided by other organisations. 1. Who controls your personal data and how to contact us? European Genome- Phenome Archive - EGA offers a service for permanent archiving and sharing of all types of personally identifiable genetic and phenotypic data resulting from biomedical research projects, jointly managed by European Molecular Biology Laboratory – European Bioinformatics Institute (EMBL-EBI) and Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG). EMBL-EBI and CRG represent joint Data Controllers’ of processing of your personal data. They and their Data protection officers may be contacted for data protection queries and for exercising your rights under Section 8. You may contact EMBL-EBI, represented by dr. Thomas Keane, by: email at: tk2@ebi.ac.uk or post at EMBL-EBI, Wellcome Genome Campus, CB10 1SD Hinxton, Cambridgeshire, UK. EMBL’s Data Protection Officer may be contacted by: telephone at +49 6221 387-8590, email at dpo@embl.org, or post at EMBL Heidelberg, Data protection officer, Meyerhofstraße 1, 69117 Heidelberg, Germany. You may contact CRG, whose EGA team is represented by dr. Jordi Rambla de Argila, by: email at jordi.rambla@crg.eu, or post at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), Dr.Aiguader 88, PRBB Building, 08003 Barcelona, Spain. CRG Data protection officer may be contacted by: email at dpo@crg.eu post at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), C/ Dr. Aiguader, 88, PRBB Building, 08003 Barcelona, Spain. 2. 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The joint Data Controllers provide these rights regarding your personal data You have the right to: Not be subject to decisions based solely on an automated processing of data (i.e. without human intervention) without you having your views taken into consideration. Request at reasonable intervals and without excessive delay or expense, information about the personal data processed about you. Under your request we will inform you in writing about, for example, the origin of the personal data or the preservation period. Request information to understand data processing activities when the results of these activities are applied to you. It must be clarified that rights under points 4 and 5 are only available whenever you need support whilst using our website. For other processing based on the grounds of important public interest you cannot exercise your rights to object, rectify or erase your personal data according to the Article 13(2)(a)(b) of IP 68 (equivalent to Article 17(3)(b)(d) and Article 21(6) of the GDPR). 8. Supervisory authority If you wish to complain against the processing of your personal data, you may do so by post at: EMBL Heidelberg, Data Protection Committee, Meyerhofstraße 1, 69117 Heidelberg, Germany, or Autoritat Catalana de Protecció de Dades (Catalan Data Protection Authority), C/Rosselló 214, Esc A, 1r 1a, Barcelona 08008, Spain. Published at: February 6, 2019

Documentation data-protection/privacy-notice/ega-user-account

Driver mutations in histone H3.3 and chromatin remodelling genes in paediatric glioblastoma

Sequence reads for pediatric GBM samples for manuscript: Driver mutations in histone H3.3 and chromatin remodelling genes in paediatric glioblastoma

Dataset EGAD00001000134

Single-cell Full Transcriptome RNA sequencing

Single cell full transcriptome sequencing of CD19 CAR T-cell infusion products used for standard of care treatment for relapsed/refractory large B-cell lymphoma.

Dataset EGAD50000000201

Cancer Registry of Norway - NIPH Data Access Committee for CRCbiome datasets

The Cancer Registry of Norway - NIPH appointed Data Access Committee for the CRCbiome datasets - The microbiome as a colorectal cancer screening biomarker. https://www.mn.uio.no/sbi/english/groups/rounge-group/crcbiome/.

Dac EGAC50000000121

WGS dataset for gamma delta (γδ) T-ALL patients

Whole genome sequencing data for 61 samples with acute lymphoblastic leukemia expressing the gamma delta T cell receptor (γδ T-ALL) and 29 germline samples

Dataset EGAD50000000028

RNA-seq data for genomic determinants of response and resistance to inotuzumab in B-ALL

RNA-seq data for 101 samples with B-cell acute lymphoblastic leukemia

Dataset EGAD50000000095

WTCCC2 Schizophrenia study

A WTCCC2 project genome-wide case-control association study for schizophrenia (SP) in individuals from Ireland.

Study EGAS00000000118

DAC for "HIPSD&R-seq enables scalable genomic copy number and transcriptome profiling"

This is the DAC for the study "HIPSD&R-seq enables scalable genomic copy number and transcriptome profiling" of PD Dr. Aurélie Ernst (a.ernst@dkfz.de) B420, DKFZ.

Dac EGAC50000000452

Massachusetts General Hospital Cancer Center DAC for high-throughput microfluidic enrichment from whole leukopak for CTC-based liquid biopsy

Whole genome sequencing and whole exome sequencing data of circulating tumor cells isolated from patients with metastatic prostate cancer and liver cancer.

Dac EGAC50000000423

Akershus University Hospital Data Access Committee for Immunoglobulin Heavy-Chain locus in Multiple Sclerosis datasets in FEGA Norway

This is the Data Access Committee appointed by Akershus University Hospital (AHUS) for datasets from Immunoglobulin Heavy-Chain locus in Multiple Sclerosis studies.

Dac EGAC50000000659

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