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• A conserved enhancer in ecDNA-containing Medulloblastoma

  Extrachromosomal DNA (ecDNA) fundamentally reshapes the regulatory landscape of cancer cells by providing a platform for massive oncogene amplification and heightened chromatin accessibility. This research investigates how ecDNA-resident enhancers operate within large-scale molecular hubs to drive potent, long-range transcriptional activation that transcends standard chromosomal boundaries. By analyzing the unique structural configurations of these elements, the work identifies key mechanisms that contribute to rapid tumor evolution and significant phenotypic plasticity. These findings highlight the critical role of non-chromosomal regulatory elements in maintaining oncogenic signaling and suggest new avenues for therapeutic intervention in aggressive, ecDNA-driven malignancies.

  Study EGAS50000001610

• A conserved enhancer in ecDNA-containing Medulloblastoma

  Extrachromosomal DNA (ecDNA) fundamentally reshapes the regulatory landscape of cancer cells by providing a platform for massive oncogene amplification and heightened chromatin accessibility. This research investigates how ecDNA-resident enhancers operate within large-scale molecular hubs to drive potent, long-range transcriptional activation that transcends standard chromosomal boundaries. By analyzing the unique structural configurations of these elements, the work identifies key mechanisms that contribute to rapid tumor evolution and significant phenotypic plasticity. These findings highlight the critical role of non-chromosomal regulatory elements in maintaining oncogenic signaling and suggest new avenues for therapeutic intervention in aggressive, ecDNA-driven malignancies.

  Study EGAS50000001608

• An Integrated Approach to Patient Stratification and Therapy Selection in Acute Myeloid Leukemia

  As more clinically-relevant genomic features of myeloid malignancies are revealed, it has become clear that targeted clinical genetic testing is inadequate for risk stratification. Here, we developed and validated a clinical transcriptome-based assay for stratification of acute myeloid leukemia (AML). Comparison of RNA-Seq to whole genome and exome sequencing revealed that as a standalone assay, RNA-Seq offered the greatest diagnostic return, enabling identification of expressed gene fusions, single nucleotide and short insertion/deletion variants, and whole-transcriptome expression information. Expression data were used to develop a novel risk score which, when combined with molecular risk guidelines, allowed for the re-stratification of 22.1 to 25.3% of AML patients from three independent cohorts into correct risk groups. Within the adverse-risk subgroup, we identified a subset of patients characterized by dysregulated integrin signaling and RUNX1 or TP53 mutation. We show that these patients may benefit from therapy with inhibitors of focal adhesion kinase (PTK2), demonstrating additional utility of transcriptome-based testing for therapy selection in myeloid malignancy.

  Dataset EGAD00001006701

• Glioblastoma stem cell lines RNA-seq (Guilhamon et al.)

  RNA was extracted from GSCs using the Qiagen RNeasy Plus kit. RNA sample quality was measured by Qubit (Life Technologies) for concentration and by Agilent Bioanalyzer for RNA integrity. All samples had RIN above 9. Libraries were prepared using the TruSeq Stranded mRNA kit (Illumina). Two hundred nanograms from each sample were purified for polyA tail containing mRNA molecules using poly-T oligo attached magnetic beads, then fragmented post-purification. The cleaved RNA fragments were copied into first strand cDNA using reverse transcriptase and random primers. This is followed by second strand cDNA synthesis using RNase H and DNA Polymerase I. A single “A” base was added and adapter ligated followed by purification and enrichment with PCR to create cDNA libraries. Final cDNA libraries were verified by the Agilent Bioanalyzer for size and concentration quantified by qPCR. All libraries were pooled to a final concentration of 1.8nM, clustered and sequenced on the Illumina NextSeq500 as a pair-end 75 cycle sequencing run using v2 reagents to achieve a minimum of ~40 million reads per sample.

  Dataset EGAD00001006813

• GWAS for IgA Nephropathy

  IgA nephropathy (IgAN) is a common form of immune-mediated glomerulonephritis characterized by glomerular deposition of IgA-containing immune complexes and manifesting with hematuria, proteinuria, and often kidney failure. This dataset is from a genome-wide association study (GWAS) designed to identify novel genetic risk loci for IgAN. In this dataset, seven cohorts were genotyped by Illumina Multi-Ethnic Global Array, consisting of 3,337 IgAN cases and 2,177 healthy controls of European and East Asian ancestries. Three of the provided cohorts were genotyped by Illumina HumanImmuno Chip, which are composed of 2007 cases of IgAN of European ancestry. These cohorts were used in the GWAS meta-analysis, as described in the manuscript entitled "GWAS defines pathogenic signaling pathways and prioritizes drug targets for IgA nephropathy" (Nature Genetics 2022, in press).

  Study phs000431

• Comprehensive Molecular Analysis of Colon Cancer for the Identification and Validation of New Biomarkers

  This study aims to identify diagnostic and prognostic biomarkers in colon cancer and to study understand the complex genomic, genetic and epigenetic relationships with a multiomic approach. The study includes tumor and paired normal mucosa of 100 colon cancer patients diagnosed at stage II, untreated and with microsatellite stable tumours. Also 50 normal mucosa samples from healthy donors are included as reference. The samples have been analysed for gene expression with Affymetrix U219 array (available at GEO GSE44076), SNP/CNV with the Affymetrix 6.0 Human SNP array, for DNA methylation with the Illumina 450K array. Small RNAs were sequenced with the Solid technology and 42 of the tumours and paired normal mucosa DNA were whole exome sequenced with Illumina Genome Analyzer.

  Study EGAS00001002453

• Open Targets 020 Epigenomes of Cell Lines (2018-10-23)

  There is currently a drive to establish cell based assay systems of greater human biological and disease relevance through the use of well characterised transformed cell lines, primary cells and complex cellular models (e.g. co-culture, 3D models). However, although the field is gaining valuable experience in running more non-standard & complex cell assays for target validation and compound pharmacology studies, there is the lack of a systematic approach to determine if this expansion in cell assay models is reflected in increased human biological and disease relevance. The increasing wealth of publically available transcriptomic, and epigenome (ENCODE and Epigenome Roadmap) data represents an ideal reference mechanism for determining the relationship between cell types used for target & compound studies to primary human cells and tissues from both healthy volunteers & patients. The CTTV020 epigenomes of cell line project aims to generate epigenetic and transcriptomic profiles of cell lines and compare these with existing and newly generated reference data sets from human tissue and cell types. The aim is to identify assay systems which will provide greater confidence in translating target biology and compound pharmacology to patients. Multiple cell types commonly used within research have been grouped according to biology. Examples include erythroid, lung epithelial, hepatocyte cell types and immortalised models of monocyte / macrophage biology. 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 please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2018-10-23.

  Dataset EGAD00001004415

• Transcriptional and DNA binding profiling of CEBPE in REH acute lymphoblastic leukaemia cells using shRNA RNA-Seq and ChIP-Seq

  ChIP-Seq - CEBPE - REH. The ETV6/RUNX1 translocated acute lymphoblastic leukaemia cell line. REH was used to perform ChIP-Seq using a CEBPE antibody. Cells were fixed in 1% formaldehyde for 10mins, prior to preparation of chromatin using Active Motif Express ChIP-IT. 2ug of antibody (anti CEBPE Atlas Antibodies HPA002928)was added to 25ug of chromatin O/N at 4C with rotation. Duplicate reactions were pooled and purified. 10ng of ChIP’d and input DNA used for Illumina NGS preparation (NEBNext ChIP-Seq Library kit; New England Biolabs), CEBPE and Input DNA ChIP samples were sequenced on a MiSeq using 150bp Kit v3 paired end and a HiSeq 2500 using 2x101 version 4 paired end (Illumina) respectively. Reactions performed in duplicate. shCEBPE RNA-Seq - REH. REH cells were lentivirally transduced with a pTRIPZ shRNA vector for transcriptional profiling of CEBPE. Two controls (empty and non-targeting) and two CEBPE shRNAs (V3THS_150517(A13), V3THS_404312(G3) Dharmacon, GE) were transduced into REH cells. Cells were treated with 1ug/ml doxycyclin for 144hrs and total RNA purified using Qiagen RNeasy. Knock down of CEBPE was validated by qRT. RNA integrity >7.7 for all samples. Libraries were prepared using NEBNext Ultra II Directional RNA Library Prep Kit and sequenced on an Illuimna HiSeq 2500 using 2x101 version 4 paired end chemistry. 3 biological replicates of each samples were prepared.

  Dataset EGAD00001004084

• DAC for CancerLocator study

  Dac EGAC00001000602

• Point of contact for Data

  Dac EGAC00001000977