Search Results - EGA European Genome-Phenome Archive

Genome-Wide Characterization of Pancreatic Adenocarcinoma Patients Using Next Generation Sequencing

In this study, we whole genome sequenced tumor/normal pairs from three pancreatic adenocarcinoma patients to separately characterize each patient with respect to somatic alterations. For 2 patients for whom tumor RNA was available, we also performed RNA sequencing to evaluate gene expression changes. While additional sequencing is needed to improve our understanding of the disease, the information acquired from this study contributes to our knowledge base on pancreatic cancer and helps to establish a foundation for identifying and developing more efficacious treatments for patients.

Study phs000550

Single cell transcriptome sequencing of the developing human embryonic meninges

There are no effective medical therapies for meningiomas, partly due to our limited understanding of their cellular origin and composition For this purpose, we generated data to make a comprehensive reference single cell and spatial transcriptomic atlas of human fetal meninges. Samples of meninges from human embryos of post-conceptional week (PCW) 5.0-13.0 were dissected and subject to 10Xgenomics chromium single cell RNA sequencing with the purpose of identifying cell types and gene expression programs for normal meninges development, Furthermore, this dataset should help discover cells of origin for meningiomas.

Study EGAS50000000980

ATAC-Seq on OCIAML-22 Fractions

The donor AML patient (unsorted) that was used to generate OCI-AML22 was expanded for 3-4 months, then sorted for the indicated fraction (CD34p: CD34+; CD34m: CD34-)

Study EGAS00001006511

The dataset for "Validation of cfDNA fragmentome analyses for early detection of liver cancer"

The dataset for “Validation of cfDNA fragmentome analyses for early detection of liver cancer” includes 380 cram files from whole genome next-generation sequencing on the Illumina NovaSeq 6000 with 10x coverage. The samples analyzed include plasma samples from patients with cancer and liver disease.

Dataset EGAD00001015538

WES dataset for cfDNA cohort

Whole exome sequencing data for 457 samples, including diagnosis and germline sample, across multiple cancer types for cfDNA cohort

Dataset EGAD50000000103

WGS data for cfDNA cohort

Whole genome sequencing data for 423 samples, including diagnosis and germline, across multiple cancer types for cfDNA cohort

Dataset EGAD50000000102

Dataset for COPD human sputum 16S rRNA gene sequencing data

Dataset for 16S rRNA gene sequencing data for sputum samples 61 COPD patients, generated using PacBio sequencing technology.

Dataset EGAD00001009103

WGS data for MMML for Study EGAS00001002198

Whole genome sequencing data for MMML (12 tumor/control pairs)

Dataset EGAD00001003208

BAP1 study

Background: Mutations in BAP1 have been identified in many aggressive cancers. Current therapeutic strategies for BAP1-deficient tumors are not effective. Goal: Discover novel strategies for BAP1-deficient tumors. Details: In our study, we identified a potential therapeutic strategy for BAP1-deficient cancers. We used multi-omics approaches to understand the underlying mechanisms behind why the discovered potential therapeutic strategy is effective.

Study EGAS50000000235

Multi-omic dataset of neuroendocrine neoplasm organoids

This dataset corresponds to one of the first biobanks for the understudied neuroendocrine neoplasms from multiple grades and body sites (lung, pancreas, small intestine). It contains whole-genome sequencing data for original tumors, patient-derived tumor organoids at multiple passages, and matched normal tissue, and RNA-seq data for the original tumor and patient-derived tumor organoids.

Study EGAS00001005752

WTCCC case-control study for Multiple Sclerosis - Combined controls

WTCCC genome-wide accosication study for Multiple Sclerosis (MS) - Combined controls

Study EGAS00000000023

Container Study for ICGC Malignant Lymphoma Master Study (MMML)

Master Container Study for Malignant Lymphoma data (ICGC - Germany)

Study EGAS00001001600

Exome sequencing for LySeqST

Exome sequencing of 120 lymphoma samples and 13 normal samples for LySeqST: A targeted sequencing assay for robust genomic classification of diffuse large B-cell lymphoma.

Dataset EGAD50000002289

Exome Sequencing of Schizophrenia Cases and Controls in the South African Xhosa Population

The goal of this international collaborative project is to identify genes responsible for Schizophrenia in the Xhosa population of South Africa. The vast majority of the genetic basis for Schizophrenia has yet to be explained. We hypothesize that genes and pathways important to Schizophrenia will harbor different, severe disease-causing mutations in different affected individuals. Given the genetic diversity of African populations, we expect to find genes for Schizophrenia that have not yet emerged from studies of other populations. This project will also foster the development of gene discovery research for neuropsychiatric disorders in Africa. Our approach will identify genes important for the disorder in populations worldwide. These genes will stimulate future efforts to develop more effective treatment and prevention strategies.

Study phs000959

HCI-PDX Trial Center for Breast Cancer Therapy

The HCI-PDX Trial Center for Breast Cancer Therapy study is a collection of patient-tumor samples that are serially established as patient-derived tumor xenografts (human tumor in mouse) and matching organoids. For this study, we describe valuable methods and resources to generate organoids and use them as cost-effective models for precision drug screens. This study leveraged whole-exome sequencing, RNAseq, and SNP-array data to illustrate how the heterogeneity of tumors is preserved in xenograft and organoid models. Sequencing files are provided for whole-exome and RNAseq data. Processed copy number variant calls from the SNP arrays are also available. A full description of the study can be found in the article entitled, "A human breast cancer-derived xenograft and organoid platform for drug discovery and precision oncology," written by Guillen et al., 2022 in Nature Cancer (PMID: 35221336).

Study phs002479

Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Genetic Epidemiology of COPD Study (COPDGene)

Cohort Description The Genetic Epidemiology of COPD (COPDGene) study is a non-interventional, multicenter, longitudinal, case-control study at 21 US sites of smokers with a ≥10 pack-year history of smoking, with and without COPD, and healthy never smokers. The initial goal was to characterize disease-related phenotypes and explore associations with susceptibility genes. Data Being Submitted Wave 1 questionnaire data includes 397 variables for up to 3683 COPDGene participants in C4R. Wave 2 questionnaire data includes 447 variables for up to 2191 COPDGene participants in C4R. Dried Blood Spot/Serosurvey data includes 7 variables for up to 1692 COPDGene participants in C4R. Derived data includes 43 variables for up to 4082 COPDGene participants in C4R. Phenotype data includes 113 variables for up to 4082 COPDGene participants in C4R.

Study phs002910

Early on-treatment changes in circulating tumor DNA fraction and response to enzalutamide or abiraterone in metastatic castration-resistant prostate cancer

On-treatment circulating tumor DNA (ctDNA) quantification is touted as a surrogate biomarker for understanding metastatic cancer response to systemic therapy, but there is relatively little supporting data from standardized patient cohorts. Here, in a prospective observational cohort, we demonstrate that 4-week on-treatment changes in plasma ctDNA levels can accurately identify metastatic castration-resistant prostate cancer that will progress within 6 months of initiating first-line abiraterone or enzalutamide treatment. On-treatment ctDNA measurements outperformed existing clinical variables for predicting disease response and were also closely associated with differential overall survival. Although optimal timing of blood collections and thresholds for ctDNA detection will require further testing, our data highlights the potential for sequential ctDNA measurements to provide an early and reliable read-out for therapy response. The high accuracy of this information suggests that ctDNA could be useful for guiding clinical trials of therapy changes in initially non-responsive metastatic cancers.

Study EGAS00001006856

Pharmacogenetics of Efavirenz Discontinuation for Reported Central Nervous System Symptoms Appears to Differ by Race

This is an evaluation of genetic associations with efavirenz (EFV) discontinuation for central nervous system (CNS) symptoms within 12 months of treatment. Patients were treated at an HIV primary care clinic in Nashville TN from 1998 to 2012. Previously known SNPs in CYP2B6 and CYP2A6 were used to define metabolizer genotypes (extensive, intermediate, slow metabolizer). Over 500,000 SNPs from genome-wide genotyping were used to define MDS (Multidimensional Scaling) coordinates to account for population stratification. Patients were defined as cases if they discontinued EFV for CNS symptoms within 12 months, otherwise they were defined as controls if they did not stop treatment. Among 563 evaluable participants, the hazard ratio for EFV discontinuation for CNS symptoms was 4.9 (95% C.I. 1.9 TO 12.4, p=0.001) in slow metabolizers compared to extensive metabolizers. This association was very significant in Whites 6.5 (95% CI: 2.3 to 18.8; p = 0.001), but not in Blacks 2.6 (95% C.I. 0.5 to 14.1; p = 0.27). The reason for this difference by race is not clear and warrants further investigation.

Study phs001253

HIV-phyloTSI: Subtype-independent estimation of time since HIV-1 infection for cross-sectional measures of population incidence using deep sequence data

Estimating the time since HIV infection (TSI) at population level is essential for tracking changes in the global HIV epidemic. Most methods for determining TSI give a binary classification of infections as recent or non-recent within a window of several months, and cannot assess the cumulative impact of an intervention. We developed a Random Forest Regression model, HIV-phyloTSI, which combines measures of within-host diversity and divergence to generate continuous TSI estimates directly from viral deep-sequencing data, with no need for additional variables. HIV-phyloTSI provides a continuous measure of TSI up to 9 years, with a mean absolute error of less than 12 months overall and less than 5 months for infections with a TSI of up to a year. It performs equally well for all major HIV subtypes based on data from African and European cohorts. We demonstrate how HIV-phyloTSI can be used for incidence estimates on a population level.

Study EGAS50000000895

Comparison between phenotypic-defined stage of blasts and transcriptional profile

Established a proof-of-concept methodology with potential integration into flow cytometry software for objective AML subtype classification based on blast differentiation, offering valuable prognostic insights for elderly patients.

Study EGAS50000000336

Data Access Committee for Maurice Lab - UMC Utrecht

The Data Access Committee of the Maurice lab at the Center for Molecular Medicine, University Medical Center Utrecht, is responsible for reviewing and approving requests for access to controlled human transcriptomics and genomics data generated by the lab. The DAC ensures that data access requests are consistent with informed consent, ethical approvals, and applicable legal and institutional regulations, including GDPR.

Dac EGAC50000000876

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