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• Mutational signatures of environmental carcinogens in human tissue organoids – WGS Bulk Normals

  Whole genome sequencing of human tumours has revealed distinct patterns (signatures) of mutations that provide clues to the causative origins of cancer. Some signatures have been attributed to endogenous processes, some to exogenous agents, while a substantial proportion are of unknown origin. Generation of mutational signatures induced in experimental systems can verify the signature assignments and shed light on their origins and mechanisms. We have investigated mutational signatures of environmental carcinogens in human tissue organoid cultures. These 3-dimensional systems retain some of the architecture and functions of the organs from which they are derived, affording the opportunity to observe the effects of carcinogens in both target and non-target organs. There was a lesser requirement for an exogenous metabolizing system, as the cultures were, in most cases, capable of activating test agents. Duplex sequencing eliminated PCR amplification errors from mutational profiles and removed the need to clone carcinogen-treated cultures. Gastric, colon, liver, pancreas and kidney organoids were exposed to benzo[a]pyrene (BaP), aflatoxin B1 (AFB1), aristolochic acid (AAI) and 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP). All four agents induced single-base substitution (SBS) signatures, BaP and AAI induced double-base substitution (DBS) signatures and indel (ID) signatures, and PhIP also induced an ID signature. These signatures were the same in all five organoid types, although there were quantitative differences. A further 13 environmental carcinogens were investigated in human gastric organoids, and signatures were obtained for seven of them: ethylnitrosourea (ENU), methylazoxymethanol acetate (MAM), N-methyl-N′-nitro-N-nitrosoguanidine (MMNG), potassium bromate, glycidamide, styrene oxide and propylene oxide, providing additional insights into processes underlying the causes of human cancer.

  Dataset EGAD00001015630

• Investigating low frequency variants in CAD/MI cases, controls and pedigrees using whole exome sequencing and custom pulldowns

  The Cardiogenics re-sequencing study will consist of three parts: Eight pools of 25 individuals will be sequenced using a Nimblegen hybrid-capture solution specific to miRNA sequences, 80 pools of 25 individuals will be sequenced using a custom Agilent SureSelect array covering genes associated with coronary artery disease (CAD) and myocardial infarction (MI), 10 individuals from families with a history of CAD/MI will be exome sequenced using the Sanger exome array. The experiment will use the early onset patients from the German MI cohort and the UK BHF CAD/MI cohort both of which have strong family history. For controls we will consider individuals from the UKBS and KORA cohorts.

  Dataset EGAD00001000400

• GSA reference

  reference whole exome sequence serving as a reference of individuals. Includes the raw GSa files and the called variants in vcf format merge for all individuals (S1-S5).

  Dataset EGAD50000000481

• Annotated germline variant calls from the lungNENomics project

  Annotated germline variant calls derived from WGS data for 72 individuals from the lungNENomics cohort. Variant calling was performed with Strelka2 and annotation with InterVar.

  Dataset EGAD00001015672

• Human Origins array data for 1510 individuals

  Genotype data typed on the Human Origins array for 1510 individuals published in "Dense sampling of ethnic groups within African countries reveals fine-scale genetic structure and extensive historical admixture."

  Dataset EGAD00001010015

• Hospital for Sick Children Infant Glioma RNA Sequencing

  Whole transcriptome (n=4) and targetted RNA sequencing (n=15) .bam files of infantile glioma samples reported on at the Hospital for Sick Children

  Dataset EGAD00001005092

• Probabilistic modeling of personalized drug combinations from integrated chemical screen and molecular data in sarcoma

  Background: Cancer patients with advanced disease exhaust available clinical regimens and lack actionable genomic medicine results, leaving a large patient population without effective treatments options when their disease inevitably progresses. To address the unmet clinical need for evidence-based therapy assignment when standard clinical approaches have failed, we have developed a probabilistic computational modeling approach which integrates sequencing data with functional assay data to develop patient-specific combination cancer treatments. Methods: Tissue taken from a murine model of alveolar rhabdomyosarcoma was used to perform single agent drug screening and DNA/RNA sequencing experiments; results integrated via our computational modeling approach identified a synergistic personalized two-drug combination. Cells derived from the tumor were allografted into mouse models and used to validate the personalized two-drug combination. Computational modeling of single agent drug screening and RNA sequencing of multiple heterogenous sites from a single patient’s epithelioid sarcoma identified a personalized two-drug combination effective across all tumor regions. The heterogeneity-consensus combination was validated in a xenograft model derived from the patient’s primary tumor. Cell cultures derived from human and canine undifferentiated pleomorphic sarcoma were assayed by drug screen; computational modeling identified a resistance-abrogating two-drug combination common to both cell cultures. This combination was validated in vitro via a cell regrowth assay. Results Our computational modeling approach addresses three major challenges in personalized cancer therapy: synergistic drug combination predictions (validated in vitro and in vivo in a genetically engineered murine cancer model), identification of unifying therapeutic targets to overcome intra-tumor heterogeneity (validated in vivo in a human cancer xenograft), and mitigation of cancer cell resistance and rewiring mechanisms (validated in vitro in a human and canine cancer model). Conclusions These proof-of-concept studies support the use of an integrative functional approach to personalized combination therapy prediction for the population of high-risk cancer patients lacking viable clinical options and without actionable DNA sequencing-based therapy.

  Study EGAS00001003564

• DAC for Genomic landscapes of endometrioid and mucinous ovarian cancers and morphologically similar tumor types

  While endometrioid and mucinous ovarian cancers represent nearly a quarter of ovarian cancers, their molecular characteristics and pathologic origins are poorly understood. To characterize the genomic and epigenomic alterations of these ovarian cancer subtypes and evaluate links to morphologically similar tumors from other sites, we performed sequence, copy number, mutation signature, rearrangement, and methylation analyses from tumor samples and matched normal tissues of 133 patients. These analyses included patients with ovarian endometrioid (n=44), ovarian mucinous (n=43), uterine endometrial (n=15), and gastrointestinal mucinous cancers (n=31). In addition to identifying genes previously known to be involved in these tumors, we identified alterations in RAD51C, NOTCH4, SMARCA1/4 and JAK1 in ovarian endometrioid, ESR1 in uterine endometrioid, and SMARCA4 in ovarian mucinous cancers. Whole genome sequencing revealed rearrangements involving PTEN, NF1, and NF2 in ovarian endometrioid tumors, and NF1 and MED1 in ovarian mucinous cancers. The number of alterations and affected genes in ovarian and uterine endometrioid cancers were similar as were genome-wide methylation profiles, suggesting that these tumors may have a similar tissue of origin. By contrast, methylation patterns in ovarian mucinous cancers were more similar to other gastrointestinal mucinous cancers, including mucinous cancers of the stomach, colon, and pancreas. These analyses provide insights into the genomic landscapes and origins of mucinous and endometrioid ovarian carcinomas, providing new avenues for early clinical intervention and management of patients with these cancers.

  Dac EGAC50000000341

• Dataset of scRNAseq from 56 CRC, treatment-naive and post-chemotherapy

  The dataset includes FASTQ source files of scRNA-seq for 56 CRC patients, sequenced with Illumina 10x platform. All patients were diagnosed with colorectal cancer between 2014 and 2022 at the Gustave Roussy Institute. Cohort includes 32 samples from untreated patients and 24 samples from patients who received chemotherapy. Chemotherapy included FOLFOX or FOLFIRI as first line, in some cases in combination with anti-VEGF or anti-EGRF drugs (avastin, bevacizumab or cetuximab) as the second and third lines. The post-treatment cohort included 18 responders (partial response, stable disease and complete response) and 6 progressors (progressive disease).

  Dataset EGAD50000001218

• Exome sequencing data, phenotypic information, and somatic mutation analysis results for 44 diagnosis-relapse DLBCL pairs

  This dataset contains exome sequencing data, phenotypic information, and somatic mutation analysis results for 44 diagnosis-relapse DLBCL pairs. Exon sequencing data were captured using the Agilent HaloPlex exon kit. bam files were obtained from illumina sequencing followed by BWA alignment.

  Dataset EGAD50000000049

• Common clonal origin of chronic myelomonocytic leukemia and B cell acute lymphoblastic leukemia in a patient with a germline CHEK2 variant

  Whole exome sequencing data obtained from sorted leukemic clones and a buccal swab as germline reference. The dataset contains raw sequencing data (paired-end reads) for 3 samples (2 leukemic, 1 buccal swab), for a total of 6 fastq files.

  Dataset EGAD00001007644

• Whole exome sequencing data for paired non-serous endometrial and ovarian carcinomas from 27 patients with concurrent tumours.

  Introduction: Concurrent non-serous endometrial and ovarian tumours are often managed clinically as two separate primary tumours, but almost all exhibit evidence of a genomic relationship. Methodology: This study investigates the extent of relatedness using whole exome sequencing, which was performed on paired non-serous endometrial and ovarian carcinomas from 27 patients with concurrent tumours in a cohort with detailed clinicopathological annotation. Four whole exome sequencing-derived parameters (mutation, mutational burden, mutational signatures and mutant allele tumour heterogeneity scores) were used to develop a novel unsupervised model for the assessment of genomic similarity to infer genomic relatedness of paired tumours. Results: This novel model demonstrated genomic relatedness across all four parameters in all tumour pairs. Mutations in PTEN, ARID1A, CTNNB1, KMT2D and PIK3CA occurred most frequently and 24 of 27 (89 %) tumour pairs shared identical mutations in at least one of these genes, with all pairs sharing mutations in a number of other genes. Ovarian endometriosis, CTNNB1 exon 3 mutation, and progression and death from disease were present across the similarity ranking. Mismatch repair deficiency was associated with less genomically similar pairs. Discussion: Although there was diversity across the cohort, the presence of genomic similarity in all paired tumours supports the hypothesis that concurrent non-serous endometrial and ovarian carcinomas are genomically related and may have arisen from a common origin. Keywords: Co-existing; Concurrent; Endometrial carcinoma; Genomics; Mutation; Ovarian carcinoma; Paired tumours; Tumour mutational burden.

  Study EGAS00001008259

• Profiling of gene expression and epigenomics in the fetal brain

  scRNA-seq and Cut&Tag from a sample of the human fetal brain. To compare neurogenesis in the primary human brain with that in organoids, we profiled transcriptome and chromatin accessibility (10X multiome) as well as bulk Cut&Tag of histone modifications H3K27me3, H3K27ac and H3K4me3. We used a human brain sample from GW 19 for all experiments.

  Dataset EGAD50000000225

• Whole exome data from PMID27216186

  This dataset comprises complete exome data from from the study PMID27216186 (Harbst & Lauss et al, Cancer Research 2016). These data are from 49 samples (tumor and matched normal) from 8 patients representing multi-region sequencing of human melanoma. Files are in the BAM format and contain aligned and processed data used for e.g. somatic variant calling. The sequencing libraries were constructed using SureSelect target enrichment with Clinical Research Exome Panel (Agilent) and sequenced on a HiSeq2500 (Illumina).

  Dataset EGAD00001008149

• Oncotrack_450K_tumor

  Oncotrack primary tumor samples using 450K. The dataset includes shared AF analysis files oncotrackDNAmAnalysis.R and oncotrackDNAmBetaScores.txt which were applied for both Oncotrack_450K_tumor (EGAD00010001162) and Oncotrack_450K_metastatic (EGAD00010001161) datasets.

  Dataset EGAD00010001162

• Sputum metagenome for COPD patients and healthy controls

  This dataset contains the sputum metagenome from 99 COPD patients and 36 healthy individuals in China.

  Dataset EGAD00001009063

• Extensive and differential platinum chemotherapy mutagenesis in livers of children - WGS cell lines

  Whole genome sequencing of HepG2 and THP-1 cell lines. They are untreated vehicle controls for the platinum experiment

  Dataset EGAD00001016141

• scRNA/TCR-seq of CD8+ T cells from a melanoma patient

  Specific in vitro stimulation of patient-derived PBMC with the neoantigens SYTL4-S363F and KIF2C-P13L was followed by enriching for CD137+ activated T cells. Restimulated T cells as well as an unstimulated patient PBMC sample from the same time point were used for scRNA-Seq/scTCR-Seq.

  Dataset EGAD50000000854

• CHROMATIN ACTIVATION PROFILING OF STEREOTYPED CHRONIC LYMPHOCYTIC LEUKEMIAS

  We used chromatin-immunoprecipitation followed by sequencing (ChIP-Seq) with an antibody for the H3K27ac (a bona fide histone mark for regulatory element activation) in sorted CLL cells from 15 CLL, including cases from stereotyped subsets #1, #2, #4, and #8. The samples were sequenced by Illumina HiSeq 2500.

  Dataset EGAD00001009082

• Whole exome sequencing for HELIC

  The HELIC study has been whole genome sequencing individuals from 2 Greek isolatedpopulations at 1x depth. The genotype calling process crucially involves a VQSR stepfollowed by imputation-based refinement. We have been investigating optimal ways toincrease calling accuracy. To aid us in setting appropriate parameters for VQSR and otherQC steps, we have carried out whole exome sequencing of a small number ofHELIC samples.

  Dataset EGAD00001001638

• Precise reconstruction of the tumor microenvironment using bulk RNA-seq and a unique machine learning-based algorithm trained on artificial transcriptomes

  Cellular deconvolution algorithms virtually reconstruct tissue composition by analyzing the gene expression of complex tissues. Here, we present the decision tree machine learning algorithm, Kassandra, trained on a broad collection of > 9,400 tissue and blood sorted cell RNA profiles to accurately reconstruct the tumor microenvironment (TME). Bioinformatic correction for technical and biological variability, aberrant cancer cell expression inclusion, and the accurate quantification and normalization of transcript expression increased the stability and robustness of Kassandra. Performance was validated on over 4,000 H&E tissue slides and more than 1,000 normal and tumor tissues by comparison with cytometric, immunohistochemical or single-cell RNA-seq measurements. Kassandra accurately deconvolved stromal and immune elements of blood and tumors, revealing the role of the TME in tumor pathogenesis. Digital TME reconstruction revealed that the presence of PD1-positive CD8+ T cells strongly correlated with immunotherapy response and increased the predictive potential of established biomarkers, indicating that Kassandra could potentially be utilized in future clinical applications.

  Dataset EGAD00001008776

• Germline variant analysis in childhood AML

  Analysis of rare germline variants in childhood AML in a large panel of cancer predisposition genes (n=216) compiled from literature review, and including genes involved in familial hematological malignancies (HM) and bone marrow failure (BMF) syndromes. The prevalence of extremely rare variants in the combined childhood AML cohort (n=72) was compared to that in the Medical Genome Reference Bank (MGRB; n=2570) comprising individuals aged at least 70 years with no history of cardiovascular disease, dementia or cancer. This showed a significant increase of rare alleles in childhood AML for 100% of subset comparisons. Next additional stringent filtering was applied to determine predicted damaging germline predisposition variants. Overall, 21% of the Australian cohort and 25% of the TARGET cohort presented germline variants predicted to be damaging predisposition variants.

  Study EGAS00001006276

• The PRIME-AIR Study: Positive End-Expiratory Pressure, Recruitment, Incentive Spirometry, Muscle Relaxant Optimization, Preoperative Education, Postoperative Early Ambulation, Individualized, and Reinforced

  Data Access NOTE: Please refer to the "Authorized Access" section below for information about how access to the data from this accession differs from many other dbGaP accessions.The PRIME-AIR study ("Positive end-expiratory pressure, Recruitment, Incentive spirometry, Muscle relaxant optimization, preoperative Education, postoperative early Ambulation, Individualized, and Reinforced") was a prospective multi-center randomized controlled pragmatic trial, with a blinded assessor, to compare post-operative pulmonary complications (PPCs) in patients with an individualized anesthetic-centered intervention (including individualized mechanical ventilation positive end-expiratory pressure (PEEP) management to maximize respiratory system compliance and minimize driving pressures, a neuromuscular agent and subsequent reversal, and post-operative lung expansion and early mobilization) versus usual care.

  Study phs003926

• Functional Mapping of AKT Signaling and Biomarkers of Response From the FAIRLANE Trial of Neoadjuvant Ipatasertib Plus Paclitaxel for Triple-Negative Breast Cancer

  Purpose: Despite extensive genomic and transcriptomic profiling, it remains unknown how signaling pathways are differentially activated and how tumors are differentially sensitized to certain perturbations. Here, we aim to characterize AKT signaling activity and its association with other genomic or immunohistochemistry-based PI3K/AKT pathway biomarkers as well as the clinical activity of ipatasertib (AKT inhibitor) in the FAIRLANE trial. Experimental Design: In FAIRLANE, 151 patients with early triple-negative breast cancer were randomized 1:1 to receive paclitaxel with ipatasertib or placebo for 12 weeks prior to surgery. Adding ipatasertib did not increase pathologic complete response rate and numerically improved overall response rate by magnetic resonance imaging (MRI). We used reverse-phase protein microarrays (RPPA) to examine the total level and/or phosphorylation states of over 100 proteins in various signaling or cell processes including PI3K/AKT and mTOR signaling. 125 baseline and 127 on-treatment samples were evaluable by RPPA, with 110 paired samples at both time points. Results: Tumors with genomic/protein alterations in PIK3CA/AKT1/PTEN were associated with higher levels of AKT phosphorylation. In addition, phosphorylated(p)AKT levels exhibited a significant association with enriched clinical benefit of ipatasertib, and identified patients who received benefit in the absence of PIK3CA/AKT1/PTEN alterations. Ipatasertib treatment led to a down-regulation of AKT/mTORC1 signaling, which was more pronounced among the tumors with PIK3CA/AKT1/PTEN alterations or among the responders to the treatment. Conclusions: We showed that the high baseline pAKT levels are associated with the alterations of PI3K/AKT pathway components and enriched benefit of ipatasertib in TNBC.

  Study EGAS00001005892

• Multi-institutional collaboration to characterize 5hmC in prostate cancer, both tumor biopsies and cfDNA.

  This study used pull-down sequencing to measure 5-hydroxymethylcytosine (5hmC) levels in tissue biopsy specimens from patients with localized and metastatic castration-resistant (mCRPC) prostate cancer. For a subset of the cohort, the same technique was used to sequence cell-free DNA (cfDNA) isolated from patient plasma. To assess 5hmC levels in cfDNA from a larger number of specimens, plasma samples from another mCRPC cohort were also assayed with this method. The larger cohort of cfDNA samples was further anlayzed with a targeted sequencing gene panel.

  Study EGAS00001004942

• The tissue origin of highly elevated cell-free DNA in patients with and without cancer

  Forty years ago, the first measurements of cell free DNA (cfDNA) from cancer patients revealed that its total concentration was often elevated compared to healthy controls. The basis for this increase, and in particular the source of the extra cfDNA in such patients, has never been determined. To address this issue, we assessed methylation patterns of cfDNA from 57 individuals, 34 of whom had unequivocally elevated cfDNA concentrations (i.e., >15 ng/mL of plasma). We found that the excess cfDNA in cancer patients did not come from either neoplastic cells or surrounding cells from the tumor's tissue of origin. Instead, 80% of the cfDNA was derived from neutrophils, B cells or T cells, with neutrophils accounting for ~2/3. B cells contributed more than T cells despite the great excess of T cells over B cells in the blood. To see if this result was generalizable to other clinical situations in which elevated cfDNA concentrations have been described, we evaluated nine patients before and one day following surgery. After surgical resection, cfDNA concentration increased by an average of 16.1-fold, as expected. The majority of this increase (55%) was contributed by leukocytes, though damaged hepatocytes contributed a substantial minority (31% of increase). These data suggest that the elevated concentrations of cfDNA in cancer patients, as with patients after surgery, arises largely from dying leukocytes—not from the neoplastic cells or the tissue of origin of the cancer.

  Study EGAS00001005400

• Sudden Cardiac Death in Heart Failure Trial (SCD-HeFT-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives The Sudden Cardiac Death in Heart Failure Trial (SCD-HeFT) was designed to evaluate the hypothesis that amiodarone or a conservatively programmed shock-only, single-lead implantable cardioverter defibrillator (ICD) would decrease the risk of death from any cause in a broad population of patients with mild-to-moderate heart failure. Background Patients with congestive heart failure (CHF) can die suddenly and unpredictably from arrhythmia despite the use of proven medical therapies, such as beta-blockade. Two approaches have been developed to prevent sudden death among patients with CHF: therapy with amiodarone and therapy with an ICD. However, most of the mortality data on amiodarone and ICD therapy at the time of the study had been obtained in clinical trials performed after myocardial infarction in patients without CHF or those with ventricular arrhythmias. Thus, more data was needed to guide these therapies in patients who did not meet these criteria. Participants There were a total of 2521 participants. 847 were randomly assigned to placebo, 845 to amiodarone, and 829 to ICD therapy. Design Before randomization, participants underwent electrocardiography, a 6-minute walk test, 24-hour ambulatory electrocardiography, liver and thyroid function studies, and chest radiography. Participants were required, if clinically reasonable, to receive treatment with a beta-blocker and an angiotensin-converting-enzyme inhibitor, as well as an aldosterone antagonist, aspirin, and statins, when appropriate. Participants were randomly assigned in equal proportions to receive placebo, amiodarone, or a single-chamber ICD programmed to shock-only mode. Participants assigned to amiodarone or matching placebo began therapy as outpatients immediately after randomization. Placebo and amiodarone were administered as a loading dose of 800 mg/day for one week, 400 mg/day for three weeks, and then as a daily maintenance dosage according to weight and bradycardia status. Participants assigned to ICD therapy received their device a median of three days after randomization. The goal of ICD therapy was to treat only rapid, sustained ventricular tachycardia or ventricular fibrillation. Dual-chamber or biventricular devices, or antitachycardia or rate-response pacing therapies were not permitted. The ICD was uniformly programmed to have a detection rate of 187 beats per minute or more. Antibradycardia pacing was initiated only if the intrinsic rate decreased to less than 34 beats per minute. Median follow-up was 45.5 months. The primary end point was death from any cause. Secondary outcome measures included cardiac mortality, arrhythmic mortality, morbidity, quality of life, and incremental cost-effectiveness of the interventions. Each active treatment arm was compared to the placebo drug arm. Conclusions In participants with NYHA class II or III CHF and LVEF of 35% or less, amiodarone had no favorable effect on survival, whereas single-lead, shock-only ICD therapy reduced overall mortality by 23%.

  Study phs003654

• G&T-seq: Parallel sequencing of single-cell genomes and transcriptomes

  Development of a method for separation and parallel sequencing of the genomes and transcriptomes of single cells.

  Dataset EGAD00001001332

• Tumor microenvironment study of ovarian granulosa cell tumors

  Adult-type granulosa cell tumors (aGCT) are rare ovarian sex cord tumors with few 41 effective treatments for recurrent disease. The objective of this study was to compare global gene expression profiles and characterize the tumor microenvironment (TME) of primary and recurrent aGCTs in order to identify correlates of disease recurrence. Total RNA sequencing was performed on 24 pathologically confirmed, cryopreserved aGCT samples, including 8 primary and 16 recurrent tumors. A total of 31 differentially expressed genes were identified between primary and recurrent aGCT. TME analysis demonstrated significantly higher fractions of neutrophils and macrophages in recurrent tumors in conjunction with significantly lower fractions of cancer-associated fibroblasts and endothelial cells.

  Study EGAS00001006478

• 10x Multiome from Human Fetal Heart

  We hope to uncover the genetic basis of congenital heart disease by examining how genetic variants, especially those in non-coding regions, influence heart development. To achieve this goal, our research team created a single-cell atlas of human fetal heart development. The study population consists of 41 structurally normal fetal hearts spanning 6 to 22 weeks post-conception. We profiled close to 750,000 using single-cell RNA sequencing and ATAC sequencing technologies via the 10x Genomics Multiome platform.The molecular technologies employed allowed for simultaneous analysis of gene expression and chromatin accessibility at the single-cell level. This approach identified numerous distinct cell types and states within the developing heart, offering detailed insights into gene activity and enhancer usage during critical stages of heart development.Principal findings include the characterization of diverse cell populations and the identification of specific gene expression patterns and regulatory elements active during heart formation. This high-resolution atlas provides valuable insights into how genetic variants may disrupt normal heart development, particularly those in non-coding regions that affect gene regulation.

  Study phs003778

• Isala Cross sectional Flow Meta Data

  This meta data contains extensive meta data from the cross sectional flow of the Isala Citizen Science project. The meta data file contains ENA Accession numbers for 16S Microbiome data, and cleaned responses to questionnaires.

  Dataset EGAD00001009890

• Analysis of resistance to PLX4032 (2019-08-21)

  We have collected material from a patient who had BrafV600E mutant melanoma that was treated with PLX4032. We have germline DNA from the patient and DNA and RNA from distinct lesions before and after treatment with PLX4032. We would like to exome sequence these samples to gain a snap shot of the mechanisms of resistance that are operative. . This dataset contains all the data available for this study on 2019-08-21.

  Dataset EGAD00001005278

• Exome reads

  This dataset contains WES data (.bam files) and associated phenotype information from 10 patients included in our microbiome study who went on to anti PD-1 immunotherapy for the treatment of metastatic melanoma at the University of Texas MD Anderson Cancer Center. Both tumor and matching germ line normal were sequenced on each patient using Illumina HiSeq 2500. The average coverage was 283X in tumors and 135X in germline (tumor+germline overall:209, Range: 0-1552).

  Dataset EGAD00001003797

• DAC for study involving the spatial transcriptomics analysis of HPV-dependent and HPV-independent vulval squamous cell carcinoma at Imperial College London.

  Dac EGAC00001003515

• Structural and Non-Coding Variants Increase the Diagnostic Yield of Clinical Whole Genome Sequencing for Rare Diseases

  Study EGAS00001007575

• Primary breast tumor heterogeneity through therapy

  We performed whole-exome sequencing on multiple regions (n=2-3) from four primary untreated breast tumors (n=1 HER2+, n=2 ER+/HER2-, n=1 triple-negative), as well as matched normal. We also performed whole-exome sequencing on one region from the pre-treatment diagnostic core biopsy and multiple regions (n=2-6) from the post-treatment surgical specimen for five HER2+ primary breast tumors, as well as matched normal; all were treated with combination chemotherapy and trastuzumab. Analysis of these specimens allows characterization of breast tumor heterogeneity and clonal evolution.

  Study EGAS00001003168

• Single-cell expression of Hodgkin and Reed-Sternberg (HRS) cell

  Hybrid capture sequencing was performed to 3 purified Hodgkin and Reed-Sternberg (HRS) cell samples. In brief, Probes for 177 genes were designed and synthesized by Twist Bioscience. Hybridization capture of DNA libraries was performed using Twist Hybridization and Wash Kit (Twist Bioscience). The captured library was measured using Agilent Bioanalyzer High Sensitivity chip and Qubit dsDNA HS Assay Kit and run on Illumina Nextseq550. The BAM files were generated from the raw sequencing data using Cell Ranger (v6.0.2) mkfastq and count commands

  Dataset EGAD00001010892

• Single-cell ATAC-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell ATAC sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015715

• Single-cell RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015710

• Single-cell ATAC-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell ATAC sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015711

• Single-cell RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015717

• Single-cell ATAC-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell ATAC sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015719

• Somatic mutation in edited cholangiocyte organoids

  Primary human cells cultured in organoid format have great promise as potential regenerative cellular therapies. However, their immunogenicity and mutagenic profile remain unresolved, impeding effective long-term translation to the clinic. In this study we report, for the first time, the generation of human leukocyte antigen (HLA)-I and HLA-II knock-out human expandable primary cholangiocyte organoids (PCOs) using CRISPR-Cas9 as a potential ‘universal’ low-immunogenic therapy for bile duct disorders. HLA-edited PCOs (ePCOs) displayed the same phenotypic and functional characteristics as parental unedited PCOs. Despite minimal off-target edits, duplex sequencing approaches demonstrated that ePCOs and PCOs acquire mutations in culture at similar rates, but without evident selection for cancer-driver mutations. ePCOs induced reduced T cell-mediated immunity and donor-dependent NK cell cytotoxicity in vitro and evaded cytotoxic responses with increased graft survival in humanized mice in vivo. Our findings have important implications for assessment of safety and immunogenicity of primary cell-derived organoid cellular therapies.

  Dataset EGAD00001015457

• Somatic mutation in edited cholangiocyte organoids

  Primary human cells cultured in organoid format have great promise as potential regenerative cellular therapies. However, their immunogenicity and mutagenic profile remain unresolved, impeding effective long-term translation to the clinic. In this study we report, for the first time, the generation of human leukocyte antigen (HLA)-I and HLA-II knock-out human expandable primary cholangiocyte organoids (PCOs) using CRISPR-Cas9 as a potential ‘universal’ low-immunogenic therapy for bile duct disorders. HLA-edited PCOs (ePCOs) displayed the same phenotypic and functional characteristics as parental unedited PCOs. Despite minimal off-target edits, duplex sequencing approaches demonstrated that ePCOs and PCOs acquire mutations in culture at similar rates, but without evident selection for cancer-driver mutations. ePCOs induced reduced T cell-mediated immunity and donor-dependent NK cell cytotoxicity in vitro and evaded cytotoxic responses with increased graft survival in humanized mice in vivo. Our findings have important implications for assessment of safety and immunogenicity of primary cell-derived organoid cellular therapies.

  Dataset EGAD00001015455

• Somatic mutation in edited cholangiocyte organoids

  Primary human cells cultured in organoid format have great promise as potential regenerative cellular therapies. However, their immunogenicity and mutagenic profile remain unresolved, impeding effective long-term translation to the clinic. In this study we report, for the first time, the generation of human leukocyte antigen (HLA)-I and HLA-II knock-out human expandable primary cholangiocyte organoids (PCOs) using CRISPR-Cas9 as a potential ‘universal’ low-immunogenic therapy for bile duct disorders. HLA-edited PCOs (ePCOs) displayed the same phenotypic and functional characteristics as parental unedited PCOs. Despite minimal off-target edits, duplex sequencing approaches demonstrated that ePCOs and PCOs acquire mutations in culture at similar rates, but without evident selection for cancer-driver mutations. ePCOs induced reduced T cell-mediated immunity and donor-dependent NK cell cytotoxicity in vitro and evaded cytotoxic responses with increased graft survival in humanized mice in vivo. Our findings have important implications for assessment of safety and immunogenicity of primary cell-derived organoid cellular therapies.

  Dataset EGAD00001015456

• human CMV-specific CD8+ T cells

  In this study we established a comprehensive workflow to collect multi-omics single-cell data using a commercially available micro-well based platform. This included whole transcriptome, cell surface markers (targeted sequencing-based cell surface proteomics), T cell specificities, adaptive immune receptor repertoire (AIRR) profiles and sample multiplexing. With this technique we identified novel paired T cell receptor sequences for three prominent human CMV epitopes. In addition, we review the ability of dCODE dextramers to detect antigenspecific T cells at low frequencies by estimating sensitivities and specificities when used as reagents for single-cell multi-omics.

  Study EGAS50000000633

• Cell-free MeDIP-seq of plasma samples from lymphoma patients and healthy controls

  This dataset contains cell-free methylated DNA immunoprecipitation sequencing (cfMeDIP-seq) data generated from plasma samples of lymphoma patients and healthy controls. The study aims to characterize genome-wide methylation patterns of circulating cell-free DNA and identify hypermethylated regions associated with lymphoma. Sequencing libraries were prepared using cfMeDIP with anti-5-methylcytidine antibody enrichment and sequenced on an Illumina platform. The dataset supports differential methylation analyses and the development of classification models for lymphoma detection.

  Dataset EGAD50000002108

• High-coverage whole-genome sequencing reveals structural variations in triple-negative breast cancer

  Triple-negative breast cancer (TNBC) cells do not express estrogen receptors, progesterone receptors or human epidermal growth factor receptor 2 (HER2). Currently, apart from poly ADP-ribose polymerase (PARP) inhibitors, there are few effective therapeutic options for this cancer type. Here, we present a comprehensive characterization of genetic alterations in TNBC via high-coverage whole-genome sequencing along with transcriptomic and whole-exome sequencing. Silencing of BRCA1 gene impaired the homologous recombination (HR) pathway in a subset of TNBC, which exhibited similar phenotypes with tumors with BRCA1 mutations; they harbored many structural variations (SVs) with relative enrichment for tandem duplication. Clonal analysis suggested that TP53 mutations and methylation of CpG dinucleotides in the BRCA1 promoter were the early events of carcinogenesis. SVs were associated with driver oncogenic events such as amplification of MYC, NOTCH2 or NOTCH3 and impacted tumor suppressor genes including RB1, PTEN and KMT2C. We also identified a variety of oncogenes that could transform 3T3 mouse fibroblast cells, suggesting that individual TNBC tumors may undergo a unique driver event that can be targetable. Thus, we revealed several features of TNBC that had important clinical implications.

  Study JGAS000095

• The Genetic Basis of Progression in Multiple Sclerosis

  This study examined the genetic determinants of multiple sclerosis (MS) severity in an international cohort of people with MS assembled by the International Multiple Sclerosis Genetics Consortium (IMSGC) and the MultipleMS Consortium. A total of 12,584 people with MS of European ancestry were included in the main genome-wide association study (GWAS). Participants were enriched for older individuals with longer disease duration (mean age 51.7 years and mean disease duration 18.2 years). All individuals were whole-genome genotyped on the Illumina Global Screen Array (GSAMD-24v2-0). Imputation was performed using the Haplotype Reference Consortium reference panel. The primary outcome was the age-related MS severity score. All individuals had at least 1 expanded disability status scale (EDSS) measure. When multiple EDSS scores were available, the last one was selected to calculate the age-related MS severity score.Of those 12,584 people with MS, this data release includes 4,623 participants recruited from non-European sites in the US, Canada and Australia. This release includes individual-level genotype and phenotype files necessary to replicate our GWAS of MS severity, including covariates.

  Study phs002929

• Whole genome characterisation of lung cancer organoids and tissue

  Organoids are self-organizing 3D structures grown from stem cells that recapitulate essential aspects of organ structure and function. Here we describe a method to establish long-term expanding human airway organoids from broncho-alveolar biopsies or lavage material. The pseudostratified airway organoid epithelium consists of basal cells, functional multi-ciliated cells, mucus-producing goblet cells, and CC10-secreting club cells. Airway organoids derived from cystic fibrosis (CF) patients allow assessment of CFTR function in an organoid swelling assay. Organoid culture conditions also allow gene editing as well as the derivation of various types of lung cancer organoids. Respiratory syncytial virus (RSV) infection recapitulated central disease features and dramatically increases organoid cell motility, found to be driven by the non-structural viral NS2 protein. We conclude that human airway organoids represent versatile models for the in vitro study of hereditary, malignant, and infectious pulmonary disease.

  Study EGAS00001002899