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• Spatial heterogeneity of follicular lymphoma

  Follicular lymphoma (FL) is an incurable B cell malignancy characterized by advanced stage disease and a heterogeneous clinical course. Recent genomic studies have focused on profiling “single” FL biopsies over several time-points, however, multi-site sampling in solid cancers has demonstrated profound spatial intra-tumor heterogeneity (ITH) with implications for precision medicine based initiatives. This study examined the extent of spatial heterogeneity in FL by whole exome sequencing 22 synchronously removed spatially separated biopsies from 9 patients. We observed significant differences in the extent of ITH across cases, with two distinct patterns of high and low spatial heterogeneity emerging. Site-specific alterations in genes with biological, prognostic or therapeutic relevance included, TNFRSF14, PIK3CD, TNFAIP3, PTEN, EP300 and XBP1. In depth characterization of these variants using deep-sequencing techniques confirmed their discordant nature, suggesting on-going genetic diversification driving evolution after widespread tumor dissemination. There was evidence of tumors comprising multiple competing subclones, with distinct clusters of mutations demonstrating differential expansions within spatially-separated sites. For cases where spatial tumors were examined at two time-points (FL and transformation to diffuse large B cell lymphoma (DLBCL)), the degree of heterogeneity increased with transformation. Collectively, our results demonstrate that spatial ITH is prevalent in FL. The existence of site-specific aberrations suggests that a single biopsy may not be sufficient in all patients to capture the full genomic complexity present and these spatial variations need to be considered in biomarker-led clinical studies.

  Dataset EGAD00001003553

• Test dataset: Sequence and variant data from public 1000 Genomes Project

  This is a test dataset derived from public data of the 1000 Genomes Project. Its purpose is not to allow for any inference about cohort data or results, but to aid bioinformaticians in the technical development and testing of tools, as well as data consumers in learning how to access information. This dataset consists of 2508 samples from the 1000 Genomes Project (https://www.nature.com/articles/nature15393). Samples' (e.g. NA18534) data can be accessed through the IGSR portal (e.g. https://www.internationalgenome.org/data-portal/sample/NA18534) or their corresponding folder at the 1000 Genomes' FTP site (e.g. http://ftp.1000genomes.ebi.ac.uk/vol1/ftp/data_collections/1000_genomes_project/data/CHB/NA18534/exome_alignment/). There are several different types of data this dataset encompasses: Variant Calling Format (VCF, or its binary counterparts BCF) files, both joint (e.g. ALL_chr22_20130502_2504Individuals.vcf.gz) and split (HG01775.chrY.vcf.gz); exome sequencing CRAM files (e.g. NA18534.GRCh38DH.exome.cram); whole genome sequencing CRAM/BAM files (e.g. NA19239.cram). Additionally, there are multiple files that were sliced to create shorter files, which allows for a quick download, formated as "{FILE-INFO}__{NUMBER-OF-READS}r__{CHR}.{START-COORDINATE}-{END-COORDINATE}.{FILETYPE}" (e.g. "HG01500.GRCh38DH__90r__3.10000-10500__4.10000-10500.cram"). These files can be downloaded directly through the EGA-download-client PyEGA3 (https://github.com/EGA-archive/ega-download-client).

  Dataset EGAD00001003338

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: pancreas (2019-04-03)

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute (Illumina HiSeqX, 40X and 20X depth respectively). Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development. . This dataset contains all the data available for this study on 2019-04-03.

  Dataset EGAD00001004893

• Somatic mutations and single cell transcriptomes reveal the root of malignant rhabdoid tumours

  Like many childhood cancers, malignant rhabdoid tumours (MRT) are thought to arise from aberrant foetal development. Although MRT predominantly exhibit a mesenchymal phenotype, it has been suggested that the foetal root of MRT lies in neural crest development. Here, we combine phylogenetic analyses of MRT, single cell mRNA assays, and functional experiments in patient-derived MRT organoids, to define the embryological origin of MRT and explore therapeutic avenues that may drive MRT differentiation. Phylogenetic analyses from the distribution of somatic mutations revealed that MRT were related to neural crest-derived, but not to mesodermal tissues, providing direct evidence of the neural crest origin of MRT in humans. In MRT organoids, reversal of the principal driver event underpinning MRT, SMARCB1 loss, induced differentiation along mesenchymal pathways. Together, these findings placed MRT cells on a developmental trajectory of neural crest to mesenchyme conversion, and defined the transcriptional changes underpinning MRT differentiation. Searching perturbation databases for agents that mimic these mRNA changes, we identified HDAC and mTOR inhibition as potential differentiation agents. Treatment of MRT organoids with this drug combination induced proliferation arrest with transcriptional changes akin to SMARCB1 re-expression. Our study defines the embryological root of MRT and proposes a differentiation treatment for this often fatal childhood cancer.

  Dataset EGAD00001006296

• Exome trios in patients with gastroschisis (2019-04-08)

  Gastroschisis (MIM 230750) is a herniation of the intestines through a defect of the abdominal wall lateral to the umbilicus (usually on the right side), and it is not covered by a membrane [Ledbetter, 2012]. Gastroschisis is a congenital anomaly with increasing incidence, easy prenatal diagnosis and extremely variable postnatal outcomes. On the basis of clinical manifestations, epidemiologic charateristics, and the presence and type of additional malformations, gastroschisis could be considered a heterogeneous condition with no gene/s discovered yet. This congenital anomaly affects approximately 1-3 infancts per 10,000 live births [Calzolari et al.1995;Parker et al.,2010] Current knowledge about causative mutations/variants. To date, no single gene has been linked to gastroschisis. Some publications have tried to link this malformation to variants in genes (such as AEBP1 (adipocyte enhancer binding protein) gene [Feldkamp et al,. 2012] or the VEGF-NOS3 pathway [Lammer et al., 2008]. Previously, a Scribble mutant mouse model (circletail) was reported to exhibit gastroschisis, however recent studies demonstrated that the Scribble knockout fetus exhibits exomphalos phenotype of gastroschisis [Carnagham et al., 2013]. 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/ . This dataset contains all the data available for this study on 2019-04-08.

  Dataset EGAD00001004942

• Integrated genomic analysis identifies recurrent mutations and evolution patterns driving the initiation and progression of follicular lymphoma.

  follicular lymphoma (FL), the most common indolent non-Hodgkin’s lymphoma, remains incurable. A well-recognized complication of FL is its transformation to a diffuse large B-cell lymphoma (DLBCL)-morphology in a subset of patients, for which the clinical outcomes are poor. Recent genetic profiling and single case studies of donor-derived FL following stem cell transplantation had alluded to the putative existence of a ‘long lived’ tumor-initiating progenitor cell compartment from which successive disease events occurred. To chronicle the genetic changes associated with progression to transformation, we conducted whole-genome sequencing (WGS) of FL-tFL pairs and matched germline (GL) samples from six patients, a total of 20 genomes.

  Study EGAS00001000399

• The 3D evolution of glioma cell populations

  Study description: A detailed understanding of heterogeneity in solid tumors has been limited due to insufficient sampling and a lack of knowledge from where within the tumor the sample was taken from. We present here a novel resource - the 3D Glioma Atlas - in which we record the precise, three-dimensional (3D) coordinate for each of 8-20 spatially-distinct samples obtained from each patient tumor.By revealing how genetic alterations and tumor cell states are patterned in glioma in 3D space, our Atlas shows that genetic diversity is more regionally confined in indolent as compared to aggressive tumors, that recurrent tumors have a greater density of genetic diversity, and that more aggressive tumors have greater tumor-wide transcriptomic heterogeneity.

  Study EGAS00001003710

• DPY30_ChIP_seq

  H9 human embryonic stem cells (hESCs) were cultured in feeder-free chemically-defined conditions in medium containing 10ng/ml Activin A and 12ng/ml FGF2 (Vallier L. 2011, Methods in Molecular Biology, 690: 57–66). Chromatin immunoprecipitation was performed as described in Brown S. et al. 2011. Stem Cells 29: 1176–85 by using 5ug of anti-DPY30 antibody (Sigma, cat. number HPA043761). This protocol was performed in control hESCs (expressing a scrambled shRNA) and in hESCs stably expressing an shRNA against DPY30 (Sigma, clone n. TRCN0000131112).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/

  Study EGAS00001001132

• RNA-seq study of longitudinal blood cell samples from children at risk of type 1 diabetes

  The appearance of type 1 diabetes (T1D)-associated autoantibodies is the first and only measurable parameter to predict progression toward T1D in genetically susceptible individuals. However, autoantibodies indicate an active autoimmune reaction, wherein the immune tolerance is already broken. Therefore, there is a clear and urgent need for new biomarkers that predict the onset of the autoimmune reaction preceding auto-antibody positivity or reflect progressive b-cell destruction. Here we report the mRNA sequencing–based analysis of 306 samples including fractionated samples of CD4+ and CD8+ T cells as well as CD4, CD8 cell fractions and unfractionated PBMC samples longitudinally collected from seven children who developed beta-cell autoimmunity (Case subjects) at a young age and matched control subjects.

  Study EGAS00001004071

• 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