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• Determination_of_cell_specific_regulatory_enhancers_in_hematopoetic_models

  The BLUEPRINT project is a large-scale project investigating epigenetic mechanisms involved in blood formation, in health and disease. The human variation workpackage (WP10) of the project seeks to characterize the effect of common sequence variation on the epigenome status of a cell. To do this, the project will use highly purified blood cells to minimise “experimental noise” and therefore enhance the power to discover modest effects. Two peripheral blood cell types, the CD14+CD16- monocyte (an important central orchestrator of adaptive immunity and a bridge between innate and adaptive immunity) and the CD65+CD9- neutrophilic granulocyte (the frontline cell for innate immunity) have been selected for this purpose. The two types of cells will be obtained at high purity from adult blood (AB) of 200 healthy males and females, respectively. Cells will be purified by using already validated and fully operational protocols that are based on density gradient centrifugation of the buffy coat obtained from whole blood, followed by magnetic bead-based purification using monoclonal antibodies against Cluster of Differentiation (CD) lineage-specific cell surface markers. This data set contains functional genomics data for gene expression and chromatin state.

  Study EGAS00001000586

• Spatial Transcriptomics Uncovers Tumor Microenvironment-Based Subtypes in Invasive Lobular Carcinoma

  Invasive lobular carcinoma (ILC) is the second most common histological subtype of breast cancer (BC); however, little is known about its tumor microenvironment (TME). Here, we investigated the spatial architecture of 43 hormone-receptor-positive, HER2-negative (HR+/HER2-) primary ILC samples, using spatial transcriptomics and detailed morphological annotation. By integrating morphology, spatial, and single-cell data, we mapped TME-related cell types, exploring their proximity to tumor cells and their enrichment in specific compartments. Clustering of spatial transcriptomics spots revealed significant inter- and intra-tumor heterogeneity, identifying pathways and cell types linked with disease outcomes. Morphological and gene expression data were finally integrated with a multimodal approach, leading to the identification of 4 new ILC subtypes based on TME heterogeneity. By using derived, specific gene expression signatures, these subtypes were identified and validated in external bulk RNA-seq/microarray datasets (SCAN-B and METABRIC), where differences in prognosis emerged.

  Study EGAS50000001001

• Combined MEK and BCL-2/XL inhibition is effective in high-grade serous ovarian cancer patient-derived xenograft models and BIM levels are predictive of responsiveness

  Most patients with late stage high-grade serous ovarian cancer (HGSOC) initially respond to chemotherapy but inevitably relapse and develop resistance, highlighting the need for novel therapies to improve patient outcomes. The MEK/ERK pathway is activated in a large subset of HGSOC, thus making it an attractive therapeutic target. Here, we systematically evaluated the extent of MEK/ERK pathway activation and efficacy of pathway inhibition in a large panel of well-annotated HGSOC patient-derived xenograft (PDX) models. The vast majority of models were nonresponsive to the MEK inhibitor cobimetinib (GDC-0973) despite effective pathway inhibition. Proteomic analyses of adaptive responses to GDC-0973 revealed that GDC-0973 upregulated the pro-apoptotic protein BIM, thus priming the cells for apoptosis regulated by BCL2-family proteins. Indeed, combination of both MEK inhibitor and dual BCL-2/XL inhibitor (ABT-263) significantly reduced cell number, increased cell death and displayed synergy in vitro in most models. In vivo, the GDC-0973 and ABT-263 combination was well tolerated and resulted in greater tumor growth inhibition than single agents. Detailed proteomic and correlation analyses identified two subsets of responsive models – those with high BIM at baseline that was increased with MEK inhibition and those with low basal Bim and high pERK levels. Models with low BIM and low pERK were non-responsive. Our findings demonstrate that combined MEK and BCL-2/XL inhibition has therapeutic activity in HGSOC models and provide a mechanistic rationale for clinical evaluation of this drug combination as well as the assessment of the extent to which BIM and/or pERK levels predict drug combination effectiveness in chemoresistant HGSOC.

  Study EGAS00001003427

• Multi-omics analysis defines core genomic alterations in pheochromocytomas and paragangliomas

  Pheochromocytomas (PCC) and paragangliomas (PGL) are neural crest-derived tumors. We performed the integrated genomic analysis of a collection of PCC/PGL from the French COMETE network using SNP arrays, whole-exome sequencing, DNA methylation arrays, mRNA expression arrays and miRNA sequencing. We found that PCC/PGL are characterized by a low mutation rate, with few recurrent somatic mutations and focal copy number alterations (CNAs). In contrast, we detected recurrent broad CNAs strongly associated with known molecular groups, often leading to the biallelic inactivation of the known susceptibility genes of PCC/PGL. We also identified DNA methylation changes and miRNA expression clusters strongly associated with molecular groups. Of note, overexpression of the miRNA cluster 182/96/183 is specific of SDHB-mutated tumors and induces invasive traits, whereas silencing of the imprinted DLK1-MEG3 miRNA cluster due to a loss of heterozygosity of the 14q32.2 locus is a potential driver in a subset of sporadic tumors. This comprehensive analysis illustrates the functional interdependence between genomic and epigenomic dysregulations underlying PCC/PGL.

  Study EGAS00001000933

• SNPs and Extent of Atherosclerosis (SEA) Study

  The SEA study is a genome-wide association study to identify genetic variants associated with premature atherosclerosis in subjects included in the Pathobiological Determinants of Atherosclerosis in Youth (PDAY) repository - a unique NHLBI resource including data, DNA and arterial specimens from over 3000 multi-ethnic subjects 15-34 years of age who died of non-atherosclerotic causes (mostly trauma). All PDAY subjects had post-mortem quantitative assessment of raised atherosclerotic lesions in their aorta and coronary arteries - making this the largest and most carefully phenotyped cohort for premature atherosclerosis in the world. The goal of the current project was to use the quantitative measure of raised atherosclerotic lesions in the PDAY cohort as the target phenotype for a genome-wide association study and to use quantitative measures of subclinical atherosclerosis (coronary calcium and carotid IMT) in the Multi-Ethnic Study of Atherosclerosis (MESA) to confirm or refute candidate loci identified from the PDAY analysis. Identifying genetic factors that predispose individuals to premature atherosclerosis could lead to more effective screening and early treatment of high risk individuals and suggest novel molecular targets for treatment and prevention interventions.

  Study phs000349

• Pseudotime_ordering_of_cell_cycle_state

  We will be using G&T method to sequence single cell genome and transcriptome derived from FS13B iPSCs cell line. The cell cycle state of each of the single cells is known. Hence, we will be analysing the genome and transcriptome of single cells from each of the cell cycle state to generate a copy number profile and transcriptome profile per given cell cycle stage: G1, S, G2, S.

  Study EGAS00001003293

• 120 individuals from the TEENAGE study (Ntalla et al., 2013) have been genotyped on the Illumina HumanCoreExome-12v1-1_A array. This is a population-based study of adolescents from the Attica region in Greece

  120 individuals from the TEENAGE study (Ntalla et al., 2013) have been genotyped on the Illumina HumanCoreExome-12v1-1_A array. This is a population-based study of adolescents from the Attica region in Greece

  Study EGAS00001001733

• Reading about genomic analysis of pan-neuroblastoma

  There are virtually no research fields that do not benefit from the large-scale genomic analysis that are so popular nowadays. For research into diseases with highly diverse clinical behavior like pediatric neuroblastoma, nevertheless, this type of approach has been a game-changer. Samuel W. Brady and colleagues, from St. Jude Children’s Research Hospital in Memphis, have gathered data from 702 neuroblastomas which were profiled by whole genome sequencing (WGS, n = 205), whole exome sequencing (WES, n = 539), and/or RNA-Seq. Less than half of the samples were generated during this study, while the others were obtained from previous work. Part of the WES data was indeed deposited in EGA in 2012 (EGA study EGAS00001000213). A scratchy summary about the huge work from Samuel W. Brady and colleagues, published in Nature Communications this October 2020 “These findings suggest that the sympathetic nervous system, the tissue from which neuroblastoma arises, is susceptible to different oncogenic insults at different times during development, which could be explored in future investigations using animal models.” Conclude the authors, highlighting the importance of their findings. Pediatric neuroblastomas are classified according to clinical and molecular features into low, intermediate, and high risk. Age plays a critical role in the classification, with younger children having an overall better prognosis. The samples included in this study belonged to all ages and risk-groups: the aim of such set up is the identification of age-associated molecular aberrations. The authors defined a mutational landscape of pediatric neuroblastoma including rare driver events, impossible to pick with a smaller data set. Interestingly, most driver mutations' frequency was found to be age-related. Those include alterations on MYCN, TERT, PTPRD, and Ras pathway, in addition to the previously reported ATRX. In addition, the large data set allowed the authors to define co-existence relations between the mutations (mutual exclusion or co-occurrence) which is a crucial puzzle piece to unravel the mechanisms driving the pathogenesis. Enjoy this really interesting article, open source on Pubmed.

  Blog genomic-analysis-of-pan-neuroblastoma

• Single-cell RNA-Seq analysis of thymic ILC1 progenitors and NK cell differentiation This analysis involved a multiplexed sequencing run to study thymic innate lymphoid cells (ILCs) and NK progenitors. The generated data requires a demultiplexing file to separate and identify the individual sample tags for downstream analysis.

  This dataset contains multiplexed single-cell RNA sequencing (scRNA-seq) data from human thymic tissue, focusing on ILC1 progenitors and NK cell differentiation. The data were generated using the BD Rhapsody system and sequenced on the Illumina NovaSeq S4 platform. A demultiplexing file is required to assign sample identities.

  Dataset EGAD50000001157

• Access to shallow whole genome sequencing data from DETECT

  Access to this dataset is subject to aceptance of the terms and conditions. Please summarise your project and sign the following document:

  Dac EGAC50000000553