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• 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

• 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

• Evaluation of commercial Guardant360 ctDNA test in metastatic prostate cancer

  Circulating tumor DNA (ctDNA) sequencing provides a minimally-invasive method for tumor molecular stratification. We compared the commercial Guardant360 ctDNA test to an academic sequencing approach for profiling of metastatic prostate cancer. Plasma cell-free DNA (cfDNA) from 24 patients was sequenced with a validated, prostate cancer specific targeted research panel, and sent for simultaneous Guardant360 analysis.

  Study EGAS00001003352

• 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

• RNASeq files for Roussel-MBPRG

  RNASeq files for Roussel-MPBRG paper titled "Combination of ribociclib and gemcitabine for the treatment of medulloblastoma"

  Dataset EGAD00001008824

• 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

• TPM for IMpower133 (GO30081)

  This dataset contains log2(TPM + 1) for 271 tumor samples profiled by RNA-seq for the entire transcriptome for samples originating from IMpower133 (GO30081).

  Dataset EGAD50000000196

• 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

• 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

• JAK Inhibitor Withdrawal Causes a Transient Proinflammatory Cascade: A Potential Mechanism for Major Adverse Cardiac Events

  This is a study of mesenchymal stromal cells (MSCs) from salivary glands. The salivary glands were derived from participants who had dry eye or dry mouth symptoms but did not have evidence of systemic autoimmune disease (sicca controls). The aim of the study was to determine the effects of Type I and Type II Janus kinase (JAK) inhibitors (JAKinibs) withdrawal on these cells in vitro. The MSCs were treated in vitro with a) IFN-gamma (10 ng/mL) for the entire duration, b) IFN-gamma (10 ng/mL) and withdrawal of ruxolitinib (1 µM), c) IFN-gamma (10 ng/mL) and withdrawal CHZ-868 (1 µM), and d) IFN-gamma (10 ng/mL) and ruxolitinib (1 µM) for the entire duration. For the drug (CHZ-868 and ruxolitinib) conditions, after IFN-gamma treatment for 48 hours, we washed the cells with PBS and treated them with standard growth media with 0.01% DMSO, 10 ng/mL IFN-gamma + 0.01% DMSO, or 10 ng/mL IFN-gamma + JAKinib for 48 hours. For withdrawal conditions, we washed the cells twice and then treated them with standard growth media with either 0.01% DMSO or with 10 ng/mL IFN-gamma + 0.01% DMSO for 24 hours before harvest.

  Study phs003915

• ChIP-seq for G3-MB

  ChIP-seq for H3K27ac and NeuroD1 in Group 3 Medulloblastoma cell models. Input DNA for each sample and target is also included.

  Dataset EGAD50000002303

• BLUEPRINT EpiVar RNA-seq for Naive naive CD4+ T-cells

  BLUEPRINT EpiVar RNA-seq for Naive naive CD4+ T-cells

  Study EGAS00001000752

• Fragment ends of circulating microbial DNA as signatures for infectious diseases

  Fragment ends of circulating microbial DNA as signatures for infectious diseases

  Study EGAS00001006321

• SNP data for Breast cancer PRS

  SNP data for 313 loci required for calculation of the Breast cancer PRS

  Dataset EGAD00001008144

• EXOME-WIDE ASSOCIATION ANALYSIS OF CORONARY ARTERY DISEASE IN THE KINGDOM OF SAUDI ARABIA POPULATION

  Coronary Artery Disease (CAD) remains the leading cause of mortality worldwide. Mortality rates associated with CAD have shown an exceptional increase particularly in fast developing economies like the Kingdom of Saudi Arabia (KSA). Over the past twenty years, CAD has become the leading cause of death in KSA and has reached epidemic proportions. This rise is undoubtedly caused by fast urbanization that is associated with a life-style that promotes CAD. However, the question remains whether genetics play a significant role and whether genetic susceptibility is increased in KSA compared to the well-studied Western European populations. Therefore, we performed an Exome-wide association study (EWAS) in 832 patients and 1,076 controls of Saudi Arabian origin to test whether population specific, strong genetic risk factors for CAD exist, or whether the polygenic risk score for known genetic risk factors for CAD, lipids, and Type 2 Diabetes show evidence for an enriched genetic burden. Our results do not show significant associations for a single genetic locus. However, the heritability estimate for CAD for this population was high (h2 = 0.53, S.E. = 0.1, p = 4e-12) and we observed a significant association of the polygenic risk score for CAD that demonstrates that the population of KSA, at least in part, shares the genetic risk associated to CAD in Western populations.

  Study EGAS00001001645

• Predictive value of chromosome 18q11.2-q12.1 loss for benefit from bevacizumab in metastatic colorectal cancer; a post-hoc analysis of the randomized controlled trial AGITG-MAX

  Patients and methods: We analyzed tumor samples of 256 patients enrolled in the AGITG-MAX 3-arm randomized controlled trial (RCT) who were randomly assigned to receive either capecitabine, or capecitabine and bevacizumab with- or without mitomycin. Chromosome 18q11.2-q12.1 copy number status was measured and correlated with PFS according to a predefined analysis plan with marker-treatment interaction as the primary end-point.Results: Chromosome 18q11.2-q12.1 losses were detected in 71% of patients (181/256) characteristic for mCRC. Consistent with the non-randomized study, significant PFS benefit of bevacizumab was observed in chromosome 18q11.2-q12.1 loss patients (P=0.009), and not in 18q no-loss patients (P=0.67). Although significance for marker-treatment interaction was not reached (Pinteraction = 0.28), hazard ratio and 95% confidence interval (HRinteraction 0.72, CI 0.39 - 1.32) show striking overlap with the non-randomized study cohorts (HRinteraction 0.41, CI 0.32 - 0.8) supported by a non-significant Cochrane chi-squared (P=0.11) for heterogeneity. Conclusions: PFS characteristics for marker positive- and negative patients randomized for treatment with- or without bevacizumab were consistent with those of the non-randomized discovery study, though the number of AGITG-MAX samples fell short to reach significance for marker-treatment interaction. Post-hoc analysis of the AGITG-MAX RCT provides supportive evidence for chromosome 18q11.2-q12.1 as a clinically relevant predictive marker for mCRC patients.

  Study EGAS00001005453

• Whole Genome Sequence and RNASeq Samples for Lung Cancer

  Short Read Whole Genome Sequence and RNASeq Samples for Lung Cancer

  Study EGAS00001007832

• 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

• 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

• 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

• 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

• Whole genome sequencing of matched patient sample sets of normal and tumor DNA

  Sixteen matched, male and female patient sample sets, each comprising normal DNA, tumor DNA, and RNA, were processed for storage comparison studies. Upon receipt, 10 μl quality control aliquots were prepared from each sample. DNA samples were characterized using Qubit dsDNA High Sensitivity assay for quantification, Genomic DNA TapeStation for integrity assessment (DIN scores), and NanoDrop for purity evaluation. RNA samples were analyzed using Qubit RNA High Sensitivity assay, RNA TapeStation (RIN scores), and NanoDrop. Each sample was divided equally by volume for parallel processing.

  Dataset EGAD50000002441