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• comprehensive genetic analysis and database construction for head and neck cancer

  The main purpose is to conduct comprehensive genetic analysis of head and neck malignant tumor tissue and patient-derived blood, and to construct a database for it. By analyzing these databases, we aim to clinically identify recurrence and metastasis prediction markers and establish new molecular target therapies.

  Study JGAS000214

• TTFields Glioblastoma Data Access Committee, Charité – Universitätsmedizin Berlin

  This Data Access Committee is responsible for reviewing and approving data access requests for genomic and associated clinical data from patients with glioblastoma, IDH wildtype, treated with surgery, standard chemoradiotherapy and Tumor Treating Fields at Charité – Universitätsmedizin Berlin. The DAC ensures that any data use is consistent with the patients’ informed consent, the study’s ethical approval and applicable data protection regulations. Approved applicants may use the data only for biomedical research on brain tumours and related methods, must not attempt re-identification of participants, and may not share the data with unauthorized third parties

  Dac EGAC50000000843

• Transcriptomics for LUNG-NSCLC2 cohort

  The goal of IMMUcan is to understand how the immune system interacts with tumors and how therapeutic interventions influence this interaction. This cohort includes patients with non-small cell lung cancer who had surgical resection. This is a subcohort of the EORTC SPECTAlung study. This dataset contains transcriptomics data processed with the STAR pipeline. Two sequencing kits were employed: Roche KAPA for high-quality RNA samples and Takara SMART-Seq Stranded for samples with limited RNA quantities.

  Dataset EGAD50000002236

• CEITEC DAC

  A CEITEC Data Access Committee (DAC) is a body of one or more named individuals who are responsible for data release to external requesters. The members of DAC are selected members of research groups and their respective leaders. Multiple datasets may be affiliated to a single DAC. DAC continues communication with requester to understand the purpose of use, i.e. research setting the dataset is envisioned for by requester, to identify if data sharing is possible directly under current conditions for the dataset, or actions such as re-consenting is needed and desirable to accommodate the proposed research setting/data use.

  Dac EGAC50000000049

• BLUEPRINT September 2016, ChIPmentation for CD38-negative naive B cell from cord blood, on Genome GRCh38

  ChIPmentation data for 1 sample(s) for CD38-negative naive B cell from cord blood, on Genome GRCh38. 5 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002929

• BLUEPRINT September 2016, ChIPmentation for class switched memory B cell from venous blood, on Genome GRCh38

  ChIPmentation data for 1 sample(s) for class switched memory B cell from venous blood, on Genome GRCh38. 2 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002933

• BLUEPRINT September 2016, ChIPmentation for effector memory CD4-positive, alpha-beta T cell from venous blood, on Genome GRCh38

  ChIPmentation data for 1 sample(s) for effector memory CD4-positive, alpha-beta T cell from venous blood, on Genome GRCh38. 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002926

• BLUEPRINT September 2016, ChIPmentation for central memory CD8-positive, alpha-beta T cell from venous blood, on Genome GRCh38

  ChIPmentation data for 2 sample(s) for central memory CD8-positive, alpha-beta T cell from venous blood, on Genome GRCh38. 11 run(s), 7 experiment(s), 7 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002924

• Hip OA Functional Genomics RNAseq (2017-06-09)

  From 9 patients undergoing hip joint replacement surgery for osteoarthritis, we collected 3 cartilage samples each: a low-grade sample (no obvious evidence of damage or fibrillation); a high-grade sample (damaged and fibrillated cartilage); an osteophytic sample (overlaid bony protrusions mainly around the margins of the articular surface). Multiplexed libraries were sequenced on Illumina HiSeq 2000 (75bp paired-end read length) and a cram file was produced for each sample. This dataset contains all the data available for this study on 2017-06-09.

  Dataset EGAD00001003354

• BLUEPRINT September 2016, ChIPmentation for immature conventional dendritic cell GM-CSF_IL4_T=6_days from venous blood, on Genome GRCh38

  ChIPmentation data for 1 sample(s) for immature conventional dendritic cell GM-CSF_IL4_T=6_days from venous blood, on Genome GRCh38. 2 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002925

• BLUEPRINT September 2016, ChIPmentation for central memory CD4-positive, alpha-beta T cell from venous blood, on Genome GRCh38

  ChIPmentation data for 1 sample(s) for central memory CD4-positive, alpha-beta T cell from venous blood, on Genome GRCh38. 5 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002927

• BLUEPRINT September 2016, ChIPmentation for cytotoxic CD56-dim natural killer cell from venous blood, on Genome GRCh38

  ChIPmentation data for 1 sample(s) for cytotoxic CD56-dim natural killer cell from venous blood, on Genome GRCh38. 2 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002934

• BLUEPRINT September 2016, ChIPmentation for mature conventional dendritic cell GM-CSF_IL4_T=6_days_R848_T=24hrs from venous blood, on Genome GRCh38

  ChIPmentation data for 1 sample(s) for mature conventional dendritic cell GM-CSF_IL4_T=6_days_R848_T=24hrs from venous blood, on Genome GRCh38. 2 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002941

• BLUEPRINT September 2016, ChIPmentation for effector memory CD8-positive, alpha-beta T cell from venous blood, on Genome GRCh38

  ChIPmentation data for 1 sample(s) for effector memory CD8-positive, alpha-beta T cell from venous blood, on Genome GRCh38. 2 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002945

• BLUEPRINT September 2016, ChIP-Seq for conventional dendritic cell from cord blood, on Genome GRCh38

  ChIP-Seq data for 1 sample(s) for conventional dendritic cell from cord blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001002948

• BLUEPRINT September 2016, ChIP-Seq Acute Lymphocytic Leukemia for precursor B cell from venous blood, on Genome GRCh38

  ChIP-Seq data for 1 sample(s) Acute Lymphocytic Leukemia for precursor B cell from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001002949

• BLUEPRINT September 2016, ChIP-Seq for memory B cell from venous blood, on Genome GRCh38

  ChIP-Seq data for 1 sample(s) for memory B cell from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001002950

• BLUEPRINT September 2016, RNA-Seq Acute Lymphocytic Leukemia for precursor B cell from bone marrow, on Genome GRCh38

  RNA-Seq data for 8 sample(s) Acute Lymphocytic Leukemia for precursor B cell from bone marrow, on Genome GRCh38. 8 run(s), 8 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002953

• BLUEPRINT September 2016, RNA-Seq for monocyte T=0day from venous blood, on Genome GRCh38

  RNA-Seq data for 1 sample(s) for monocyte T=0day from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002955

• BLUEPRINT September 2016, RNA-Seq T-cell lymphoma for helper T cell from venous blood, on Genome GRCh38

  RNA-Seq data for 2 sample(s) T-cell lymphoma for helper T cell from venous blood, on Genome GRCh38. 2 run(s), 2 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002956

• BLUEPRINT September 2016, RNA-Seq for monocyte T=2day_RANK_M-CSF from venous blood, on Genome GRCh38

  RNA-Seq data for 1 sample(s) for monocyte T=2day_RANK_M-CSF from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002957

• BLUEPRINT September 2016, RNA-Seq for monocyte T=1day_M-CSF_S100A9_4hr_RANL from venous blood, on Genome GRCh38

  RNA-Seq data for 1 sample(s) for monocyte T=1day_M-CSF_S100A9_4hr_RANL from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002959

• BLUEPRINT September 2016, RNA-Seq for monocyte T=6day_S100A9_RANKL_M-CSF from venous blood, on Genome GRCh38

  RNA-Seq data for 1 sample(s) for monocyte T=6day_S100A9_RANKL_M-CSF from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002960

• BLUEPRINT September 2016, RNA-Seq for monocyte T=10day_S100A9_RANKL_M-CSF from venous blood, on Genome GRCh38

  RNA-Seq data for 1 sample(s) for monocyte T=10day_S100A9_RANKL_M-CSF from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002961

• BLUEPRINT September 2016, RNA-Seq Acute Myeloid Leukemia for blast cell from bone marrow, on Genome GRCh38

  RNA-Seq data for 1 sample(s) Acute Myeloid Leukemia for blast cell from bone marrow, on Genome GRCh38. 1 run(s), 1 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002962

• BLUEPRINT September 2016, RNA-Seq Acute Lymphocytic Leukemia for precursor B cell from venous blood, on Genome GRCh38

  RNA-Seq data for 6 sample(s) Acute Lymphocytic Leukemia for precursor B cell from venous blood, on Genome GRCh38. 6 run(s), 6 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002963

• BLUEPRINT September 2016, RNA-Seq for monocyte T=1day_4hr_RANK from venous blood, on Genome GRCh38

  RNA-Seq data for 1 sample(s) for monocyte T=1day_4hr_RANK from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002964

• BLUEPRINT September 2016, RNA-Seq for monocyte T=2day_S100A9_RANKL_M-CSF from venous blood, on Genome GRCh38

  RNA-Seq data for 1 sample(s) for monocyte T=2day_S100A9_RANKL_M-CSF from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002965

• BLUEPRINT September 2016, RNA-Seq for monocyte T=10day_RANK_M-CSF from venous blood, on Genome GRCh38

  RNA-Seq data for 1 sample(s) for monocyte T=10day_RANK_M-CSF from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002966

• BLUEPRINT September 2016, RNA-Seq for monocyte T=6day_RANK_M-CSF from venous blood, on Genome GRCh38

  RNA-Seq data for 1 sample(s) for monocyte T=6day_RANK_M-CSF from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002967

• BLUEPRINT September 2016, RNA-Seq Acute Myeloid Leukemia for myeloid cell from venous blood, on Genome GRCh38

  RNA-Seq data for 2 sample(s) Acute Myeloid Leukemia for myeloid cell from venous blood, on Genome GRCh38. 2 run(s), 2 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002968

• Sequencing data for oesophageal and related samples - Noorani et al (WGS)

  Data supporting: "Genomic evidence supports a clonal diaspora model for metastases of esophageal adenocarcinoma." Noorani et al. WGS (BAM files) 134 samples for 18 cases Includes primary, lymph-node, distant metastatic, Barrett's and normal samples.

  Dataset EGAD00001005434

• WGS and WES of Advance Prostate Cancer

  The dataset consists of BAM files of 2 pairs of matched tumor/normal samples of a men with advanced prostate cancer. One pair is whole genome sequencing: WGS_T/WGS_N for tumor and normal samples, respectively; and the other pair is whole exome sequencing: WES_T/WES_N for tumor and normal specimens, respectively. Details can be found at the publication titled: "Molecular Medicine Tumor Board: Whole Genome Sequencing to Inform on Personalized Medicine for a Man with Advanced Prostate Cancer"

  Dataset EGAD00001006487

• To profile the landscape of sebaceous tumours_WES

  Sebaceous tumours are a rare cutaneous cancer with potential for aggressive behaviour. However, limited information is available on these cancers with few published cases. Here we wish to exome sequence these cancers to define the first genomic landscape for this malignancy. We will extract DNA from formalin-fixed, paraffin-embedded (FFPE) cores. Cores may be obtained from lesional and non-lesional tissues of primaries as well as matching metastases. The extracted DNA will be used for exome sequencing. Please note that the dataset was last revised on October 16, 2025.

  Dataset EGAD00001015367

• Identifying Novel Fusion Genes in Myeloma

  Identifying Novel Fusion Genes in Myeloma

  Dataset EGAD00001000112

• KIR imputation panel

  Construction of the KIR variant imputation panel in the Japanese population

  Study JGAS000314

• Analysis mechanism of CD19- relapse in CARPALL study

  Whole exome sequencing of CD19- relapses in CARPALL study

  Dataset EGAD00001005195

• Genotype of C3 SNPs in LOTx donors and recipients

  Genotype of C3 SNPs in 140 LOTx donors and recipients pairs.

  Dataset EGAD00001006889

• The Role of Myeloid Cells in Parkinson's Disease

  The Myeloid cells in Neurodegenerative Diseases (MyND) initiative is a collaborative effort with the goal of creating a multi-omic atlas of myeloid cells from the periphery and from autopsied brains of subjects with Parkinson’s disease (PD), Alzheimer’s disease (AD), and age-matched controls. We have generated large-scale transcriptomic profiles of CD14+ monocytes from 230 individuals with sporadic PD and age matched healthy subjects. We identified dysregulation of mitochondrial and proteasomal pathways, and single-cell analysis revealed that these pathways are enriched in the intermediate monocytes. We also generated transcriptomic profiles of primary microglia from autopsied brains of 55 PD and control subjects and observed discordant transcriptomic signatures of mitochondrial genes in PD monocytes and microglia/macrophages. ELISA NAVARRO*, EVAN UDINE*, et al. "Dysregulation of mitochondrial and proteolysosomal genes in Parkinson’s disease myeloid cells." Nature Aging, 2021. Link: https://www.biorxiv.org/content/10.1101/2020.07.20.212407v1PMID: 35005630

  Study phs002400

• Homopolymer switches mediate adaptive mutability in mismatch repair-deficient colorectal cancer

  Mismatch repair (MMR) deficient cancer evolves through the continuous erosion of coding homopolymers in target genes. Curiously, the MMR genes MSH6 and MSH3 also contain coding homopolymers and these are frequent mutational targets in MMR-deficient cancers. The impact of incremental MMR mutations on MMR-deficient colorectal cancer evolution is unknown. We show that microsatellite instability modulates DNA repair by toggling hypermutable mononucleotide homopolymer runs in MSH6 and MSH3 through stochastic frameshift switching. Spontaneous mutation and reversion modulates subclonal mutation rate, mutation bias, and clonal HLA and neoantigen diversity. Patient-derived organoids corroborate these observations and show that in the absence of immune selection MMR homopolymer sequences drift back into reading frame, suggesting a fitness cost of elevated mutation rates. Combined experimental and simulation studies demonstrate that subclonal immune selection favours incremental MMR mutations. Overall, our data demonstrate that MMR-deficient colorectal cancers fuel intratumour heterogeneity by adapting subclonal mutation rate and diversity to immune selection.

  Study EGAS50000000297

• Somatic Mosaicism in Amyotrophic Lateral Sclerosis and Frontotemporal Dementia

  The study was designed to investigate the role of somatic mosaic mutations in the pathogenesis of sporadic amyotrophic lateral sclerosis (sALS) and frontotemporal dementia (sFTD). A panel of molecular inversion probes (MIP) were used to target the exons and exon-intron junctions of 88 neurodegeneration-related genes. The panel included 34 ALS/FTD genes, 10 Alzheimer's disease genes, 28 Parkinson's disease genes, and 16 genes associated with other rare neurodegenerative disorders. The panel was used to perform ultra-deep sequencing on postmortem brain and spinal cord from 404 individuals with sALS or sFTD and 144 age-matched neurotypical controls. Known pathogenic germline mutations were found in 20.6% of ALS cases and 26.5% of FTD cases. Predicted pathogenic somatic mutations were observed in 2.7% of sALS and sFTD cases that did not have known germline mutations. The somatic variants had low variant allele fraction and region-specific enrichment, particularly in the primary motor cortex of sALS cases and prefrontal cortex of sFTD cases.

  Study phs003530

• Transcriptome alterations underlying metabolic dysfunction and liver disease in myotonic dystrophy type 1

  Myotonic dystrophy type 1 (DM1) is a multisystem disorder affecting various organs, including the skeletal muscles, eyes, heart, central nervous system, and endocrine system. Liver dysfunction and lipid metabolism abnormalities are frequently observed in DM1 but are not fully understood. To explore the molecular basis of these abnormalities, transcriptome analysis was performed on postmortem liver samples from DM1 patients DM1 patients (n = 11) and disease control patients (n = 9) using bulkRNA sequencing (RNA-seq) on the MGI DNBSEQ-G400RS. Differential gene expression and alternative splicing analyses revealed significant transcriptomic changes associated with lipid metabolism, liver fibrosis, and glucose homeostasis. Interestingly, transcriptome changes in DM1 livers also revealed partial resolution of sexual dimorphism in gene expression, along with unique sex-specific pathway alterations. A correlation between serum GGT levels and splicing abnormalities in DM1 patients was identified, suggesting a link between transcriptomic changes and clinical outcomes. This dataset provides valuable insights into the molecular mechanisms underlying DM1-related liver dysfunction and metabolic abnormalities.

  Study JGAS000814

• Heritable pulmonary arterial hypertension in a large Iberian family

  Data from a study of a large Iberian family (n=65 subjects, 5 generations) affected by pulmonary arterial hypertension (PAH) and segregating with the BMPR2 missense mutation p.Arg491Gln (rs137852749, c.1472G>A). PAH is a rare disease characterized by an abnormal rise in mean pulmonary arterial pressure (> or equal to 25 mmHg at rest), which, in turn, leads to a progressive increase in pulmonary vascular resistance and ultimately to death, due to right ventricular failure. Heritable PAH has an overall prevalence below 1 case per million adults and is defined by either the presence of a known genetic defect linked to the disease or a positive family history. Heritable PAH is inherited as an autosomal dominant disease. However, not all BMPR2 mutation carriers develop the disease, highlighting the presence of reduced penetrance. In this family, there are 22 mutation carriers from which 8 were diagnosed with heritable PAH and the other 14 were healthy at the time of examination.

  Study EGAS00001003123

• Super enhancers define regulatory subtypes and cell identity in neuroblastoma - RNA-seq

  Half of the children diagnosed with neuroblastoma have high-risk disease, disproportionately contributing to overall childhood cancer-related deaths. In addition to recurrent gene mutations, there is increasing evidence supporting the role of epigenetic deregulation in disease pathogenesis. Yet, comprehensive cis-regulatory network descriptions from neuroblastoma tissues are lacking. Here, using genome-wide H3K27ac profiles across 60 neuroblastomas, covering the different clinical and molecular subtypes, we identified four major super enhancer-driven epigenetic subtypes and their underlying master regulatory networks. Three of these subtypes recapitulated known clinical groups, namely MYCN amplified, MYCN non-amplified high-risk and MYCN non-amplified low-risk neuroblastomas. The fourth subtype, exhibiting mesenchymal characteristics, shared features with multipotent Schwann cell precursors, was induced by RAS activation and enriched in relapsed disease. Notably, CCND1, a disease essential gene, was regulated by both mesenchymal and adrenergic regulatory networks converging on distinct super-enhancer modules. Together, this reveals subtype-specific super-enhancer regulation in neuroblastoma.

  Study EGAS00001004552

• Super enhancers define regulatory subtypes and cell identity in neuroblastoma

  Half of the children diagnosed with neuroblastoma have high-risk disease, disproportionately contributing to overall childhood cancer-related deaths. In addition to recurrent gene mutations, there is increasing evidence supporting the role of epigenetic deregulation in disease pathogenesis. Yet, comprehensive cis-regulatory network descriptions from neuroblastoma tissues are lacking. Here, using genome-wide H3K27ac profiles across 60 neuroblastomas, covering the different clinical and molecular subtypes, we identified four major super enhancer-driven epigenetic subtypes and their underlying master regulatory networks. Three of these subtypes recapitulated known clinical groups, namely MYCN amplified, MYCN non-amplified high-risk and MYCN non-amplified low-risk neuroblastomas. The fourth subtype, exhibiting mesenchymal characteristics, shared features with multipotent Schwann cell precursors, was induced by RAS activation and enriched in relapsed disease. Notably, CCND1, a disease essential gene, was regulated by both mesenchymal and adrenergic regulatory networks converging on distinct super-enhancer modules. Together, this reveals subtype-specific super-enhancer regulation in neuroblastoma.

  Study EGAS00001004551

• Genome-wide quantification of rare somatic mutations in normal human tissues using massively parallel sequencing

  We present Bottleneck Sequencing System (BotSeqS), a nextgeneration sequencing method that simultaneously quantifies rare somatic point mutations across the mitochondrial and nuclear genomes. BotSeqS combines molecular barcoding with a simple dilution step immediately prior to library amplification. We use BotSeqS to show age and tissue-dependent accumulations of rare mutations and demonstrate that somatic mutational burden in normal tissues can vary by several orders of magnitude, depending on biologic and environmental factors. We further show major differences between the mutational patterns of the mitochondrial and nuclear genomes in normal tissues. Lastly, the mutation spectra of normal tissues were different from each other, but similar to those of the cancers that arose in them. This technology can provide insights into the number and nature of genetic alterations in normal tissues and can be used to address a variety of fundamental questions about the genomes of diseased tissues.

  Study EGAS00001001838

• Dissecting features of epigenetic variants underlying cardiometabolic risk using full-resolution epigenome profiling in regulatory elements

  Sparse profiling of CpG methylation in blood by microarrays have identified epigenetic links to common diseases. We apply methylC-capture sequencing (MCC-Seq) in a clinical population of ~200 adipose tissue and matched blood samples (Ntotal ~400), providing high-resolution methylation profiling (>1.3M CpGs) at regulatory elements. We link methylation to cardiometabolic risk through associations to circulating plasma lipid levels and identify lipid-associated CpGs with unique localization patterns in regulatory elements. We show distinct features of tissue-specific versus tissue-independent lipid-linked regulatory regions by contrasting with parallel assessments in ~800 independent adipose tissue and blood samples from the general population. We follow-up on adipose-specific regulatory regions under (1) genetic and (2) epigenetic (environmental) regulation via integrational studies. Overall, the comprehensive sequencing of regulatory element methylomes reveals a rich landscape of functional variants linked genetically as well as epigenetically to plasma lipid traits.

  Study EGAS00001003415

• A longitudinal single-cell atlas of treatment response in pediatric AML

  Pediatric acute myeloid leukemia (pAML) is a disease characterized by heterogeneous cellular composition, driver alterations and prognosis. Characterization of this heterogeneity and how it affects treatment response remains relatively understudied in pediatric patients. We therefore used single-cell RNA sequencing and single-cell ATAC sequencing to profile 684,031 diagnosis, remission and relapse cells from 28 patients representing different pAML subtypes. Analysis revealed that at diagnosis, cellular compositions differed between distinct subgroups. Upon relapse, cellular hierarchies transitioned towards a more primitive state regardless of subtype. These primitive cells were distinct compared to cells at diagnosis, having underrepresentation of transcriptional programs involved in myeloid differentiation while programs commonly found in other lineages were overrepresented. In a subset of patients, this appeared to accompany the appearance of a B-lymphoid-like hierarchy. Together, our data reveal the emergence of apparent subtype-specific plasticity upon treatment and inform on potential novel therapeutic angles to target these cell populations.

  Study EGAS00001007323

• Somatic mutation and selection at epidemiological scale - TwinsUK_ExomeNanoSeq_Buccal

  Exome NanoSeq in buccal swab samples obtained from patients with a wide range of clinical phenotypes. As we age, many tissues become colonised by microscopic clones carrying somatic driver mutations. Some of these clones represent a first step towards cancer whereas others may contribute to ageing and other diseases. However, our understanding of the clonal landscapes of human tissues, and their impact on cancer risk, ageing and disease, remains limited due to the challenge of detecting somatic mutations present in small numbers of cells. Here, we introduce a new version of nanorate sequencing (NanoSeq), a duplex sequencing method with error rates of less than 5 per billion base pairs, which is compatible with whole-exome and targeted gene sequencing. Deep sequencing of polyclonal samples with single-molecule sensitivity enables the simultaneous detection of mutations in large numbers of clones, yielding accurate somatic mutation rates, mutational signatures and driver mutation frequencies in any tissue. Applying targeted NanoSeq to 1,042 non-invasive samples of oral epithelium and 371 samples of blood from a twin cohort, we found an unprecedentedly rich landscape of selection, with 46 genes under positive selection driving clonal expansions in the oral epithelium, over 62,000 driver mutations, and evidence of negative selection in some genes. The high number of positively selected mutations in multiple genes provides high-resolution maps of selection across coding and non-coding sites, a form of in vivo saturation mutagenesis. Multivariate regression models enable mutational epidemiology studies on how carcinogenic exposures and cancer risk factors, such as age, tobacco or alcohol, alter the acquisition and selection of somatic mutations. Accurate single-molecule sequencing has the potential to unveil the polyclonal landscape of any tissue, providing a powerful tool to study early carcinogenesis, cancer prevention and the role of somatic mutations in ageing and disease.

  Dataset EGAD00001015620

• An IL-1β driven neutrophil-stromal cell axis fosters a BAFF-rich microenvironment in multiple myeloma

  The bone marrow is continuously occupied by high numbers of neutrophils, and a tumor-supportive bias of these cells could significantly impact bone marrow-confined malignancies. In multiple myeloma, the bone marrow is characterized by inflammatory stromal cells with the potential to influence neutrophils. Here, we investigated myeloma-associated alterations in marrow neutrophils and the impact of stromal inflammation on neutrophil function. Mature neutrophils in myeloma marrow are activated and tumor-supportive, transcribing increased levels of pro-inflammatory cytokines, including IL-1β, and myeloma cell survival factors, such as the BCMA-ligand BAFF. Neutrophils were re-activated after first-line treatment, while this regimen reduced, but did not normalize, stromal inflammation. Interactions with inflammatory stroma induced neutrophil activation, including BAFF secretion, in a STAT3-dependent manner and once activated, neutrophils gained the ability to reciprocally induce stromal activation. Combined, our data define the presence of a neutrophil-stromal cell feed-forward loop driving tumor-supportive inflammation that could impact disease recurrence.

  Study EGAS00001007038