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• Transcriptomic profiles studies CAREs group - IDIBGI

  The purpose of this DAC document is to outline the principles and procedures governing access to the transcriptomic data generated from endothelial progenitor cells, or any biological origin from patients. Data Access Policy: 1) Access to this dataset is restricted and subject to approval by the DAC to ensure ethical and legal compliance. 2) The DAC reserves the right to evaluate all applications for access based on: 2.1) The scientific validity and merit of the proposed research. 2.2) The ethical considerations and adherence to data protection regulations, including GDPR. 2.3) The qualifications and affiliations of the applicants. 3) Applicants must submit a detailed research proposal, including objectives, methods, and anticipated outcomes. 4) Data usage is limited to the specified research project approved by the DAC. Any secondary use of the data requires additional approval. Confidentiality: All applicants must agree to maintain the confidentiality of the dataset. Personal identifiers have been pseudonymized to protect patient privacy. Application Process: 1) Researchers must complete the application form provided by the DAC. 2) Submit proof of ethical approval and relevant certifications for their research project. 3) Provide a signed agreement affirming adherence to the DAC's terms and conditions.

  Dac EGAC50000000607

• Hypermutation of the inactive X chromosome is a frequent event in cancer

  Mutation is a fundamental process in tumorigenesis. However the degree to which the rate of somatic mutation varies across the human genome and the mechanistic basis underlying this variation remain to be fully elucidated. As part of the ICGC PedBrain and Malignant Lymphoma (MMML-Seq) consortium we performed a cross-cancer comparison of whole genomes comprising a diverse set of childhood and adult tumors including both solid and hematopoietic malignancies. In addition we performed whole genome sequencing of clonally expanded hematopoietic stem/progenitor cells (HSPCs) from healthy individuals to compare somatic mutation rates.

  Study EGAS00001000565

• Progression to AML is predictable and distinct from age related clonal hematopoiesis

  To examine the occurrence of somatic mutations prior to the development of acute myeloid leukemia, we undertook deep ECS (estimated limit of detection 1 mutation in 2500 cells) of 261 AML associated genes in 96 pre-AML cases and 420 age and gender-matched healthy controls of an average of 3853 unique DNA molecules covering each of the 1.19M bases spanning the target gene panel. The findings suggest that the development of clonal hematopoiesis and accumulation of somatic mutations is distinct and accelerated in pre-AML cases compared to healthy individuals

  Study EGAS00001002570

• The mutational landscape of normal human endometrial epithelium - Additional Samples

  All normal somatic cells are thought to acquire mutations but understanding of the rates, patterns, causes and consequences of somatic mutation in normal cells is limited. Uterine endometrium adopts multiple physiological states over a lifetime and is lined by a gland-forming epithelium. Whole genome sequencing of normal endometrial glands from women aged 19 to 81 years showed them to be clonal cell populations derived from recent common ancestors, with total mutation burdens that increase with age at ~29 base substitutions/year and which are many-fold lower than endometrial cancers. Normal endometrial glands frequently carry driver mutations in cancer genes. Driver mutation burdens increase with age and correlate negatively with parity. Phylogenetic trees of normal endometrial glands constructed using whole genome sequences indicated that clones with drivers often originate during the first decades and spread to colonise the endometrial epithelial lining. The results show that driver mutation landscapes differ between normal cell types, perhaps shaped by differences in normal tissue physiology, and suggest that the procession of neoplastic changes leading to endometrial cancer is initiated early in life.

  Dataset EGAD00001005214

• Somatic mutations in facial skin from countries of contrasting skin cancer risk

  The incidence of non-melanoma skin cancer is 17-fold lower in Singapore compared to the UK1, despite Singapore receiving 2-3 times more year-round ultraviolet radiation (UV)2,3. The ageing epidermis of the skin comprises competing somatic mutant clones4,5, from which such cancers develop. We question if differences in keratinocyte skin cancer incidence are reflected in the mutational landscape by comparing ageing facial epidermis from donors of Singapore and the UK. We find UK skin to be a highly competitive, densely mutated landscape with 4-fold greater mutation burden compared to Singaporean skin and differences in clonal selection by country. We disproportionately observe multiple features common to keratinocyte skin cancers6,7,8 in UK skin, such as UV mutagenesis, copy number aberration and hotspot mutations (in particular TP53 R248W). We conclude that keratinocyte skin cancer incidence is reflected in the somatic clones of non-cancerous epidermis. Finally, we re-analyse squamous cell carcinoma exomes from Korea9 to show, even in low incidence populations, carcinogenesis is driven by UV damage.

  Dataset EGAD00001009666

• Single-cell genome-wide concurrent haplotyping and copy-number profiling through genotyping-by-sequencing

  scGBS is a single-cell sequencing-based methodology to haplotype and copy-number profile single cells. Genomic size and complexity is reduced through restriction enzyme digestion and DNA is genotyped through sequencing of the restriction fragments. scGBS data serves as the input for haplarithmisis, an algorithm we previously developed for SNP array-based single-cell haplotyping (Zamani Esteki et al., 2015). We established technical parameters and developed an analysis pipeline enabling accurate concurrent haplotyping and copy-number profiling of single cells with the use of a HapMap cell line pedigree (7 single cells). A clinical validation of the methodology with a total of 14 single blastomeres and 3 trophectoderm samples biopsies from human preimplantation embryos for 6 PGT-M families were processed with scGBS and were previously haploptyped via SNP array.

  Dataset EGAD00001007794

• A spatiotemporal cancer cell trajectory underlies glioblastoma heterogeneity

  Abstract: Cancer cells display highly heterogeneous and plastic states in glioblastoma, an incurable brain tumour. However, how these malignant states arise and whether they follow a tractable cellular trajectory across tumours is poorly understood. Here, we generated a deep single cell and spatial multi-omic atlas of human glioblastoma that pairs transcriptomic, epigenomic and genomic profiling of 12 tumours across multiple regions. We identify that glioblastoma heterogeneity is driven by spatially-patterned transitions of cancer cells from developmental-like states towards those defined by a glial injury response and hypoxia. This cancer cell trajectory regionalizes tumours into distinct tissue niches and manifests in a conserved manner across tumours as well as genetically distinct tumour subclones. Moreover, using a new deep learning framework to jointly map cancer cell states and clones in situ, we show that tumour subclones are finely spatially intermixed through glioblastoma tissue niches. Finally, we show that this cancer cell trajectory is intimately linked to myeloid heterogeneity and unfolds across regionalised myeloid signalling environments. Our findings define a stereotyped trajectory of cancer cells in glioblastoma and unify glioblastoma tumour heterogeneity into a tractable cellular and tissue framework.

  Dataset EGAD00001015516

• Assessment of epigenetic variation in human iPS cells-Medip

  n order to progress human induced pluripotent stem cells (hiPSCs) towards the clinic, several outstanding questions must be addressed. It is possible to reprogram different somatic cell types into hiPSCs and from studies in the mouse, it appears that an epigenetic memory of the starting cell type is carried over to hiPSCs. However a comprehensive comparative study of the characteristics of these hiPSCs has been missing from the literature. Importantly studies which aimed to address these aspects of hiPSCs have used cells from different patients. In order to avoid this important confounding variable and to keep the genetic background constant, tissue samples were procured from the patients and reprogrammed to iPS cells. The methylation status of these iPS cells will be compared. Protocol: Primary cell cultures were generated and reprogrammed to iPS cells. DNA was extracted and immunoprecipitated using anti-methyl cytosine and anti-hydroxymethyl cytosine antibodies. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001000827

• Structural rearrangements generate cell-specific, gene-independent CRISPR-Cas9 loss of fitness effects.

  CRISPR-Cas9 genome editing is widely used to study gene function, from basic biology to biomedical research. Structural rearrangements are a ubiquitous feature of cancer cells and their impact on the functional consequences of CRISPR-Cas9 gene-editing has not yet been assessed. Utilizing CRISPR-Cas9 knockout screens for 250 cancer cell lines, we demonstrate that targeting structurally rearranged regions, in particular tandem or interspersed amplifications, is highly detrimental to cellular fitness in a gene independent manner. In contrast, amplifications caused by whole chromosomal duplications have little to no impact on fitness. This effect is cell line specific and dependent on the ploidy status. We devise a copy-number ratio metric that substantially improves the detection of gene-independent cell fitness effects in CRISPR-Cas9 screens. Furthermore, we develop a computational tool, called Crispy, to account for these effects on a single sample basis and provide corrected gene fitness effects. Our analysis demonstrates the importance of structural rearrangements in mediating the effect of CRISPR-Cas9-induced DNA damage, with implications for the use of CRISPR-Cas9 gene-editing in cancer cells.

  Dataset EGAD00001004124

• Sequencing component for the whole genome methylation analysis in PBMCs and cell subsets (pilot study)

  DNA methylation has been shown to play a major role in determining cellular phenotype by regulating gene expression. Moreover, dysregulation of differentially methylated genes has been implicated in disease pathogenesis of various conditions including cancer development as well as autoimmune diseases such as systemic Lupus erythematosus and rheumatoid arthritis. Evidence is rapidly accumulating for a role of DNA methylation in regulating immune responses in health and disease. However, the exact mechanisms remain unknown. The overall aim of the project is to investigate the role of epigenetic mechanisms in regulating immunity and their impact on autoimmune disease pathogenesis.The aim of this pilot study is to perform whole genome methylation analysis in peripheral blood mononuclear cells (PBMCs) and cell subsets (CD4, CD8, CD14, CD19, CD16 and whole PBMCs) obtained from 6 healthy volunteers. Whole genome methylation analysis will be performed using two methodological approaches, the Infinium Methylation Bead Array K450 (Illumina) and MeDIP-seq. mRNA expression arrays will also be performed in order to correlate DNA methylation with gene expression as well as genotyping on the Illumina OmniExpress chip

  Dataset EGAD00001000394