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• WGS data from NEN patient derived tumor organoids (PDTOs) and matched parental tumors - UMCU/NKI

  The dataset includes cram files from WGS of 6 NEN tumors or metastases and matched PDTOs. For all tumors, cram files from WGS of either matched normal tissue or matched blood from the corresponding patients are included. Analysis VCF files are also included in the dataset. The sequencing was done with a NovaSeq 6000 instrument.

  Dataset EGAD00001009989

• Transgenerational transmission of reproductive and metabolic dysfunction in the male progeny of polycystic ovary syndrome

  The transgenerational maternal effects of PCOS in female progeny have been revealed. As there are evidence that a male equivalent of PCOS may exist, we asked whether sons born to mother with PCOS (PCOS-sons) transmit reproductive and metabolic phenotypes to their male progeny. Here, in a Swedish nationwide register-based cohort and a clinical case-control study from Chile we found that PCOS-sons are more often obese and dyslipidemic. Their serum miRNAs are found to potentially regulate PCOS-risk genes. Our prenatal androgenized PCOS-like mouse model with or without diet-induced obesity confirmed that reproductive and metabolic dysfunctions in F1 male offspring are passed down to F3. Small non-coding RNAs (sncRNAs) sequencing of F1-F3 sperm revealed distinct differentially expressed (DE) sncRNAs across generations in the androgenized, obese, and obese and androgenized lineages, respectively. Notably, common targets between transgenerational DEsncRNAs in mouse sperm and in PCOS-sons serum indicate similar effects of maternal hyperandrogenism. These findings strengthen the translational relevance highlighting a previously underappreciated risk of reproductive and metabolic dysfunction via the male germline transmission and potential molecular markers to study in future generations.

  Study EGAS00001007079

• Single molecule genome-wide mutation profiles of cell-free DNA for non-invasive detection of cancer

  Somatic mutations are a hallmark of tumorigenesis and may be useful for non-invasive diagnosis of cancer. We analyzed whole-genome sequencing (WGS) data from 2,511 individuals in the Pan-Cancer Analysis of Whole Genomes (PCAWG) study as well as 489 individuals from four prospective cohorts and found distinct regional and mutation type specific frequencies in tissue and cell-free DNA (cfDNA) of cancer patients that were associated with replication timing and other chromatin features. A machine learning model using genome-wide mutational profiles combined with other features and followed by CT imaging detected >90% of lung cancer patients, including those with stage I and II disease. The fixed model was validated in an independent cohort, detected patients with cancer earlier than standard approaches, and could be used to monitor response to therapy. This approach lays the groundwork for non-invasive cancer detection using genome-wide mutation features that may facilitate cancer screening and monitoring.

  Study EGAS00001007248

• RNA-seq profiling of NKX6.1 reporter iPSC lines for isolation and analysis of functionally relevant neuronal and pancreas populations

  We generated human induced pluripotent stem cell (iPSC) lines with a GFP reporter inserted in the endogenous NKX6.1 locus. Characterisation of the reporter lines demonstrated faithful GFP labelling of NKX6.1 expression during pancreas and motor neuron differentiation. We performed three independent in vitro differentiations towards the pancreatic endocrine lineage. We FACS-purified GFP positive and negative cells from stage 7 cultures, and generated Smart-Seq2 RNA-sequencing libraries for the pre-sorted cells, as well as the two GFP-sorted cell populations. Gene expression profiling by RNA-sequencing reveals that the NKX6.1-positive population closely resembles mature human beta cells and the functional evaluation of purified populations shows that the glucose-responsive beta-like cells are enriched within the NKX6.1-positive population. These reporter lines provide a valuable resource to the scientific community for the derivation of functional relevant pancreas and neuronal cell subtypes.

  Study EGAS00001002802

• Pediatric UBA1-mutated MDS Single-Cell Sequencing DAC

  This DAC oversees controlled access to single-cell DNA and protein sequencing data generated from a pediatric MDS patient with somatic UBA1 mutation. Access is restricted to researchers who have appropriate ethical approvals and intend to use the data for studies related to pediatric blood disorders, immunology, or VEXAS pathogenesis. The DAC evaluates requests for compliance with these conditions.

  Dac EGAC50000000947

• RNA-seq data of 370 high grade ovarian tumors from the ICON7 trial

  Collection of RNA-seq, Illumina, paired-end fastq files for 370 archival tissues from a subset of patients with high grade serous ovarian carcinoma enrolled in the phase 3 ICON7 trial. Clinical data and digital pathology information for CD8 is also available.

  Dataset EGAD00001004988

• ChIP sequencing for β-catenin and histone modifications in HCC cell lines and organoids with CTNNB1 mutations

  CTNNB1 mutation is a major driver of HCC, particularly in metabolic-associated subtype. This study utilized patient-derived tumour organoids and cell lines harbouring various endogenous CTNNB1 mutations to comprehensively map the transcriptional repertoire regulated by mutant β-catenin through ChIP-seq under normal and fatty conditions. Genome-wide binding patterns of β-catenin were integrated with ChIP-seq data for histone modifications H3K27ac and H3K27me3 to assess active and repressive chromatin states. Oleic acid treatment was used to model fatty conditions.

  Study EGAS50000001274

• The Cancer Dependency Map (DepMap)

  The Cancer Dependency Map (DepMap) aims to accelerate precision cancer medicine by creating a comprehensive map of tumor vulnerabilities. The DepMap project genomically profiles a wide range of cancer models and characterizes them for their sensitivity to genetic and compound perturbations. The data is computationally analyzed to create a systematic overview of the genetic dependencies and compound sensitivities of cancer types and the predictive biomarkers that point to patient populations most likely to benefit from targeting of these vulnerabilities. The DepMap public portal has become a comprehensive resource to identify cancer vulnerabilities by providing datasets at scale, cutting-edge computational tools, and sophisticated visualization tools that together have accelerated the discovery of novel targets and biomarkers. Please visit Depmap.org to access the public portal.

  Study phs003444

• Assessment of de novo copy number variations in Italian patients with schizophrenia.

  We investigated de novo CNVs in the whole genomic DNA of schizophrenia patients and their parents and, specifically, in putative enhancer motifs.Study participants were part of a wider multicenter study, involving an Italian cohort of schizophrenia patients recruited by members of INRP - Italian Network for Research on Psychoses.Whole genomic DNA obtained from 46 family trios of schizophrenia probands was analyzed using the Enhancer Chip, a customized array CGH developed using the Agilent SurePrint G3 8X60K format, which is able to investigate the whole genome with a 300Kb resolution, specific disease loci at a tenfold higher resolution, and that was highly enriched in probes in more than 1.250 enhancer elements selected from the Vista Enhancer Browser (PLoS One. 2012;7(12):e52264).

  Study EGAS00001002159

• Fragmentomic features of individuals with different cfDNA concentrations

  The goal of this study is to explore fragmentomic patterns that vary between individuals of different concentrations of total cell-free DNA in plasma. We have selected a large cohort of individuals (ethnically Chinese men with a median age of 54 years, IQR 49-57) who were part of a screening of a large-scale clinical study to screen for nasopharyngeal carcinoma. Differences in fragmentomic features provided insights into the modulation of cfDNA levels in blood circulation. Fragmentomic and machine learning systems adopted in this study have also been applied to assess the quantity of cfDNA species of clinical interest, including the fraction of circulating fetal and tumor DNA, from pregnancy cases and individuals with hepatocellular carcinoma, respectively.

  Study EGAS50000000692