9337 results for "cancer rna-seq"

in 45.93 milliseconds.

• CTCF ChIP-seq of human acute leukemias

  CTCF ChIP-seq of 39 primary samples derived from human acute leukemias, namely AML, T-ALL and mixed myeloid/lymphoid leukemias with CpG Island Methylator Phenotype (CIMP).

  Dataset EGAD00001011059

• ATAC-Seq and CTCF ChIP-Seq on the OCIAML-2 cell line

  Study EGAS00001004741

• RNA sequencing data of 142 samples from 142 patients with HER2+ breast cancer treated with letrozole or tamoxifen (SOLTI PAMELA trial)

  PAMELA (NCT01973660) is a non-randomized, open-label, multicentric, prospective translational research study in stage I-IIIA HER2+ breast cancer designed to evaluate the ability of the PAM50 intrinsic subtypes to predict pCR in the breast (pCRB) following 18 weeks of neoadjuvant lapatinib and trastuzumab (+/- hormonal therapy if hormone receptor [HR] positive). Patients with HR+ disease received letrozole (if postmenopausal) or tamoxifen (if pre-menopausal). The primary objective was to compare the pCRB rates of the HER2-E versus the non-HER2-E subtypes in the intent-to-treat population.

  Study EGAS00001006410

• RNA sequencing of peripheral blood samples from 17 Greenlanders

  The data contain whole deep RNA sequencing of leukocytes from 17 Greenlanders. RNA was purified from peripheral blood with the PAXGene Blood miRNA Kit (Qiagen). The RNA sequencing library was prepared following the instructions of the TruSeq RNA Sample Prep Kit v2 (Illumina). For mRNA isolation and fragmentation 200 ng of total RNA was purified by oligo-dT beads. The qualified libraries were amplified on cBot to generate the cluster on the flowcell (TruSeq PE Cluster Kit V3–cBot–HS, Illumina). The amplified flow cell was sequenced paired-end on the HiSeq 4000 System (TruSeq SBS KIT-HS V3, Illumina).

  Dataset EGAD00001003814

• Comprehensive characterization of pre- and post-treatment samples of breast cancer reveal potential mechanisms of chemotherapy resistance

  When locally advanced breast cancer is treated with neoadjuvant chemotherapy, the recurrence risk is significantly higher if no complete pathologic response is achieved. Identification of the underlying resistance mechanisms is essential to select treatments with maximal efficacy and minimal toxicity. Here we employed gene expression profiles derived from 317 HER2-negative treatment-naïve breast cancer biopsies of patients who underwent neoadjuvant chemotherapy, deep whole exome and RNA-sequencing profiles of 22 matched pre- and post-treatment tumors, and treatment outcome data to identify biomarkers of response and resistance mechanisms. Molecular profiling of treatment-naïve breast cancer samples revealed that expression levels of proliferation, immune response and extracellular matrix (ECM) organization combined predict response to chemotherapy. Triple negative patients with high proliferation, high immune response and low ECM expression had a significantly better treatment response and survival benefit (HR 0.29, 95% CI 0.10-0.85; p=0.02), while in ER+ patients the opposite was seen (HR 4.73, 95% CI 1.51-14.8; 0=0.008). The characterization of paired pre-and post-treatment samples revealed that aberrations of known cancer genes were either only present in the pre-treatment sample (CDKN1B) or in the post-treatment sample(TP53, APC, CTNNB1). Proliferation-associated genes were frequently down-regulated in post-treatment ER+ tumors, but not in triple negative tumors. Genes involved in ECM were upregulated in the majority of post-chemotherapy samples. Genomic and transcriptomic differences between pre- and post-chemotherapy samples are common and may reveal potential mechanisms of therapy resistance. Our results show a wide range of distinct, but related mechanisms, with a prominent role for proliferation- and ECM-related genes.

  Study EGAS00001005876

• Germline mutations in the transcription factor IKZF5 cause thrombocytopenia.

  To identify novel causes of hereditary thrombocytopenia, we performed a genetic association analysis of whole-genome sequencing data from 13,037 individuals enrolled in the NIHR BioResource, including 233 cases with isolated thrombocytopenia. We found an association between rare variants in the transcription factor encoding gene IKZF5 and thrombocytopenia. We report five causal missense variants in or near IKZF5 zinc fingers (Znfs), of which two occurred de novo and three co-segregated in three pedigrees. A canonical DNA-Znf binding model predicts that three of the variants alter DNA recognition. Expression studies showed that chromatin binding was disrupted in mutant compared to wild-type (WT) IKZF5 and electron microscopy revealed a reduced quantity of alpha granules in normally sized platelets. Proplatelet formation (PPF) was reduced in megakaryocytes (MKs) from seven cases relative to six controls. Comparison of RNA-seq data from platelets, monocytes, neutrophils and CD4 T-cells from three cases and 14 healthy controls showed 1,194 differentially expressed genes in platelets but only four DEGs in each of the other blood cell types. In conclusion, IKZF5 is a novel transcriptional regulator of megakaryopoiesis and the eighth transcription factor associated with dominant thrombocytopenia in humans.

  Study EGAS00001003736

• Risk and modifying factors in Frontotemporal Dementia

  Understanding the molecular mechanisms underlying frontotemporal dementia (FTD) is essential for the development of successful therapies. Here, we present Phase 1 of a multi-omics, multi-model data resource for FTD research which will allows in-depth molecular research into these mechanisms. We have integrated and analysed data from the frontal lobe of FTD patients with mutations in MAPT, GRN and C9orf72 and detected common and distinct dysregulated cellular pathways. Our results highlight that excitatory neurons are the most vulnerable neuronal cell type and that vascular aberrations are a common hallmark in FTD. Via integration of multi-omics data, we detected several transcription factors and pathways which regulate the strong neuroinflammation observed in FTD-GRN. Finally, using small RNA-seq data and verification experiments in cellular models, we identified several up-regulated miRNAs that inhibit cellular trafficking pathways in FTD and lead to microglial activation. In this work we shed light on novel mechanistic and pathophysiological hallmarks of FTD. In addition, we believe that this comprehensive, multi-omics data resource will further mechanistic FTD research by the community.

  Study EGAS00001004895

• RNA-Seq of 584 DLBCL Cases of Non-China Cohort from Phoenix Clinical Trial

  Standard RNA-Seq datasets. Check the associated paper for more details.

  Dataset EGAD00001008131

• Region-Specific Neural Stem Cell Lineages Revealed by Single-Cell RNA-Sequences from Human Embryonic Stem Cells

  During development of the human brain, multiple cell types with diverse regional identities are generated. Here we report a system to generate early human brain forebrain and mid/hindbrain cell types from human embryonic stem cells (hESCs), and infer and experimentally confirm a lineage tree for the generation of these types based on single-cell RNA-Seq analysis. We engineered SOX2Cit/+ and DCXCit/Y hESC lines to target progenitors and neurons throughout neural differentiation for single-cell transcriptomic profiling, then identified discrete cell types consisting of both rostral (cortical) and caudal (mid/hindbrain) identities. Direct comparison of the cell types were made to primary tissues using gene expression atlases and fetal human brain single-cell gene expression data, and this established that the cell types resembled early human brain cell types, including preplate cells. From the single-cell transcriptomic data a Bayesian algorithm generated a unified lineage tree, and predicted novel regulatory transcription factors. The lineage tree highlighted a prominent bifurcation between cortical and mid/hindbrain cell types, confirmed by clonal analysis experiments. We demonstrated that cell types from either branch could preferentially be generated by manipulation of the canonical Wnt/beta-catenin pathway. In summary, we present an experimentally validated lineage tree that encompasses multiple brain regions, and our work sheds light on the molecular regulation of region-specific neural lineages during human brain development.

  Study phs001205

• Neuroblastoma Cell Line Circle-seq

  We generated Circle-seq data for 12 neuroblastoma cell lines to describe the landscape of extrachromosomal circular DNA in neuroblastoma.

  Study EGAS00001004796

• FASTQ Files for Human LV H3K27ac ChIP-seq

  This dataset contains 70 human LV H3K27ac ChIP-seq paired-end FASTQ files. The sequencing was performed using Illumina Hiseq 4000.

  Dataset EGAD00001004945

• ChIP-seq for GOF p53

  This dataset includes ChIP-seq data from two cell lines (HKCI-11 (GOFp53) and MIHA(WT p53)). All the experiments were performed on Illumina HiSeq 2000 platform with raw reads stored in fastq format.

  Dataset EGAD00001005449

• WGBS data of solid liver tumor DNA, and WGBS data of cell-free DNA derived from human blood, for CancerDetector study

  The blood samples of four liver cancer patients and four healthy people, and the solid liver tumor samples of two liver cancer patients are collected for this dataset. Blood samples were centrifuged first at 1,600 × g for 10 minutes, and then the plasma was transferred into new micro tubes and centrifuged at 16,000 × g for another 10 minutes. The plasma was collected and stored at -80⁰C. CfDNA was extracted from 5 ml plasma using the Qiagen QIAamp Circulating Nucleic Acids Kit and quantified by Qubit 3.0 Fluoromter (Thermo Fisher Scientific). Bisulfite conversion of cfDNA was performed by using EZ-DNA-Methylation-GOLD kit (Zymo Research). After that, Accel-NGS Methy-Seq DNA library kit (Swift Bioscience) was used to prepare the sequencing libraries. The DNA libraries were then sequenced with 150bp paired-end reads.

  Dataset EGAD00001004317

• RNA sequencing data of in vitro differentiated megakaryocyte cells transduced with E527K and WT SRC

  For RNA sequencing (RNAseq), CD34+ hematopoietic stem cells (HSC) were isolated from healthy controls before transduction with WT-SRC and E527K-SRC lentiviral vectors in triplicate and differentiation to MK. RNA was extracted from the complete cell population as the aim was to detect differences in genes regulating MK maturation and differentiation. A total of six WT-SRC and six E527K-SRC RNA samples were used for RNAseq to identify differentially expressed genes.

  Study EGAS00001005808

• Single cell RNA sequencing of human umbilical cord blood lymphoid progenitors

  We performed single cell RNA sequencing of human umbilical cord blood. To explore the differentiation pathway for human lymphoid lineage deeply, our target cells contain CD34+CD38+CD45RA+CD19-CD7-CD10+ cells (CD10SP). All these populations are evaluated by single cell RNA sequencing.

  Study JGAS000551

• Study of tumor RNA expression differences between treated and untreated PitNET patients

  The goal of the study is to evaluate response of PitNET to drug therapy before surgery. Patients with and without drug therapy are compared in RNA level. The RNA is extracted from surgery material, sequenced and deferentially expressed genes (DEG) determined.

  Study EGAS00001004736

• scATAC-seq and combined scRNA-seq of the human first trimester neurodevelopment

  Study EGAS00001007472

• Whole-Exome-Seq-Dataset

  Whole-Exome-Seq-Dataset

  Dataset EGAD00001000042

• whole genome seq

  20 whole genome seq

  Dataset EGAD00001004462

• dataset_CML_chipseq_pairend_fastq

  BMI1 ChIP-seq on human K562

  Dataset EGAD00001002061

• dataset_CML_chipseq_pairend_bam

  BMI1 ChIP-seq on human K562

  Dataset EGAD00001002062

• mFAST-SeqS

  Recent progress in the analysis of cell-free DNA fragments (cell-free circulating tumor DNA, ctDNA) now allows monitoring of tumor genomes by non-invasive means. However, previous studies with plasma DNA from patients with cancer demonstrated highly variable allele frequencies of ctDNA. The comprehensive analysis of tumor genomes is greatly facilitated when plasma DNA has increased amounts of ctDNA. Therefore, a fast and cost-effective pre-screening method to identify such plasma samples without previous knowledge about alterations in the respective tumor genome could assist in the selection of samples suitable for further extensive qualitative analysis. To address this, we adapted the recently described FAST-SeqS method, which was originally established as a simple and effective, non-invasive screening method for fetal aneuploidy from maternal blood. We show that our modified FAST-SeqS method (mFAST-SeqS) can be used as a pre-screening tool for an estimation of the ctDNA percentage. Using a combined evaluation of genome-wide and chromosome-arm specific z-scores from dilution series with cell line DNA and by comparisons of plasma-Seq profiles with data from mFAST-SeqS, we established a detection limit of 10% or more of mutant alleles. Plasma samples with an mFAST-SeqS z-score above 5 showed highly concordant results compared to copy number profiles obtained from our previously described plasma-Seq approach.

  Study EGAS00001001133

• HCA Female Reproductive Adult WSSS RNA

  HCA Endometrium_LM The endometrium regenerates monthly and its transformation is executed through dynamic changes in states and interactions of multiple cell types. Using transcriptomics methods we seek to profile changes of the endometrium across the menstrual cycle. Our map will have implications in women's health and cancer, by enabling the interpretation of GWAS analyses or the studying functional consequences of somatic mutations. 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 EGAD00001007909

• An MTOR mutation hitchhikes through renal embryogenesis, driving multifocal, multiphenotypic tumours - RNA

  Embryogenesis is a vulnerable time. Mutations in developmental cells can result in the seeding of cells predisposed to disease within mature organs, creating a field effect. We characterise an embryonic cancer mutation that drives multifocal, multiphenotypic renal tumours in a 14-year-old girl. Their shared MTOR mutation, absent from normal tissues, increases protein flexibility which enables a FAT domain hinge to dramatically increase mTORC1 activity. Developmental mutations, not usually detected in traditional genetic screening, have vital clinical importance in guiding prognosis, targeted treatment, and family screening decisions for paediatric tumours.

  Dataset EGAD00001011646

• ChIP-seq peaks of H3K27ac

  ChIP-seq peaks of H3K27ac. The dataset includes FASTQ files, BAM files, and analyses of the ChIP-seq peaks of H3K27ac determined using MACS2

  Dataset EGAD00001008964

• Simultaneous Trimodal Single Cell Measurement of Transcripts, Epitopes, and Chromatin Accessibility Using TEA-Seq

  Single-cell measurements of cellular characteristics have been instrumental in understanding the heterogeneous pathways that drive differentiation, cellular responses to signals, and human disease. Recent advances have allowed paired capture of protein abundance and transcriptomic state, but a lack of epigenetic information in these assays has left a missing link to gene regulation. Using the heterogeneous mixture of cells in human peripheral blood as a test case, we developed a novel scATAC-seq workflow that increases signal-to-noise and allows paired measurement of cell surface markers and chromatin accessibility: Integrated Cellular Indexing of Chromatin Landscape and Epitopes (ICICLE-seq). We extended this approach using a droplet-based multiomics platform to develop a trimodal assay that simultaneously measures Transcriptomics (scRNA-seq), Epitopes, and chromatin Accessibility (scATAC-seq) from thousands of single cells, which we term TEA-seq. Together, these multimodal single-cell assays provide a novel toolkit to identify type-specific gene regulation and expression grounded in phenotypically defined cell types.

  Study phs002316

• Genomic Analysis of Prostate Tumor Heterogeneity in Metastasis

  To investigate the molecular changes, mutations, and signaling pathways that characterize the initial steps of prostate cancer metastasis to the lymph nodes, we analyzed 19 discrete lymph node (LN) metastases, 97 primary tumor foci, 39 benign lymph nodes, and 10 normal adjacent prostate tissue samples from 43 patients enrolled in a clinical trial (NCT01808222) of extended lymphadenectomy and metastasis excision guided by [18F]-fluciclovine PET imaging for high risk, newly diagnosed prostate cancer conducted at Emory University. These patients fell within high or very high-risk groups (T3a, Gleason score 8-10, or PSA greater than 20 ng/ml). Of these patients, 16 had LN metastases at least 4 mm in diameter, and 20 patients had no metastases. For metastatic patients, we performed RNA and Whole Exome Sequencing (WES) on three primary tumor foci, one benign LN, and all LN metastases greater than 4mm in diameter. For non-metastatic patients, we sequenced two primary tumor foci and one benign LN. In total, RNAseq was performed on 165 tissue samples from 43 patients, and WES was performed on 137 samples from 35 patients.

  Study phs003404

• Oncogenic cooperation between the TCF7-SPI1 fusion and NRAS(G12D) requires β-catenin activity to drive T-cell acute lymphoblastic leukemia.

  In this study we investigate the role of TCF7-SPI1 fusions, more specifically in cooperation with RAS mutations. We make use of patients samples. This study contains paired-end RNA sequencing of the patients, Oxford Nanopore Technologies (ONT) sequencing, single cell RNA sequencing and RNA sequencing of treatment with inhibitors of these samples.

  Study EGAS00001005097

• A Multi-Omic Single-Cell Atlas of Human Gynecological Malignancies

  Matched single-cell transcriptomic sequencing (scRNA-seq) and single-cell chromatin accessibility sequencing (scATAC-seq) were performed for 11 fresh human tumors collected from the endometrium or ovary. More detailed information for each patient tumor will be provided in selected phenotype/attributes data. Both scRNA-seq and scATAC-seq assays revealed the underlying cellular heterogeneity in transcriptional output and in chromatin accessibility for each patient tumor specimen. In this work, we identified potential non-coding regulatory elements that mediate cell type-specific gene expression patterns. These data will serve as an important reference for the single-cell genomics and gynecologic oncology research communities.

  Study phs002340

• Medulloblastoma Cirlce-Seq

  Circle-Seq experiment.

  Dataset EGAD00001009483

• RNA sequencing of 12 NSCLC samples from 4 patients at MDACC

  Multi-region RNA sequencing of 12 NSCLC samples from 4 patients at MDACC

  Study EGAS00001005951

• RNA-seq dataset

  RNAseq FASTq files from 728 bulk pre-treatment tumors from IMvigor010.

  Dataset EGAD00001007575

• DNA Methylation Analysis of Prostate Cancer Cell Lines and Tissues Using Next Generation Sequencing

  Aberrant DNA methylation changes are known to occur during prostate cancer progression beginning with precursor lesions. Utilizing fifty nanograms of genomic DNA in Methylplex-Next Generation Sequencing (M-NGS) we mapped the global DNA methylation patterns in prostate tissues (n=17) and cells (n=2). Peaks were located from mapped reads obtained in each sequencing run using a Hidden Markov Model (HMM)-based algorithm previously used for Chip-Seq data analysis(http://www.sph.umich.edu/csg/qin/HPeak). The total methylation events in intergenic/intronic regions between benign adjacent and cancer tissues were comparable. Promoter CGI methylation gradually increased from -12.6% in benign samples to 19.3% and 21.8% in localized and metastatic cancer tissues and approximately 20% of all CpG islands (CGIs) (68,508) were methylated in tissues. We observed distinct patterns in promoter methylation around transcription start sites, where methylation occurred directly on the CGIs, flanking regions and on CGI sparse promoters. Among the 6,691 methylated promoters in prostate tissues, 2481 differentially methylated regions (DMRs) are cancer specific and several previously studied targets were among them. A novel cancer specific DMR in WFDC2 promoter showed 77% methylation in cancer (17/22), 100% methylation in transformed prostate cell lines (6/6), none in the benign tissues (0/10) and normal PrEC cells. Integration of LNCaP DNA methylation and H3K4me3 data suggested a role for DNA methylation in alternate transcription start site utilization. While methylated promoters containing CGIs had mutually exclusive H3K4me3 modification, the histone mark was absent in CGI sparse promoters. Finally, we observed difference in methylation of LINE-1 elements between transcription factor ERG positive and negative cancers. The comprehensive methylome map presented here will further our understanding of epigenetic regulation of the prostate cancer genome. Overall Design: We mapped the global DNA methylation patterns in prostate tissues (n=17) and cells (n=2) from fifty nanograms of genomic DNA using Methylplex-Next Generation Sequencing (M-NGS). For replicate analysis in cell lines, a total of 4 runs were completed for PrEC prostate normal cell line, and 5 runs were completed for LNCaP prostate cancer cell line. For tissue samples, 2 benign prostate samples were sequenced twice on Illumina next generation sequencing platform to access overall repeatability of M-NGS.

  Study phs000597

• Small RNA sequencing from CSF extracellular vesicles - PD/CTR

  The dataset contains FASTQ files referring to the study "Small RNA sequencing from CSF extracellular vesicles - PD/CTR". For this project, RNA was isolated from CSF extracellular vesicles obtained by ultracentrifugation. Libraries were prepared with the TruSeq Small RNA library prep Illumina, and sequencing conducted in the Illumina HiSeq4000.

  Dataset EGAD00001006629

• ChIP-seq and Hodgkin lymphoma

  ChIP-seq data (H3K4Me3, H3K27Ac histone modifications) of Hodgkin lymphoma cell line L-428. Samples were processed as previously described (Sud et al., 2018). The files are in bam format, aligned to build 37 of the human genome.

  Dataset EGAD00001004322

• Data upcycling, powered by EGA

  In 2012 a collaborative effort headed by the teams of Carlos Caldas in Cambridge, UK and Samuel Aparicio, Canada, produced a pivotal study aimed at defining the mutational landscape of breast cancer. They gathered a collection of over 2000 breast cancer samples (METABRIC) associated with long-term clinical follow-up. They delineated an array of inherited and somatically acquired genetic variants and associated them to gene expression. This led to the identification of putative cancer-driving events and improved stratification of breast cancer patients. The study elicited huge attention and was tackled as herculean effort by fellow researchers. Cristina Curtis and her colleagues deposited the data in the EGA archive (EGAS00000000083). What they probably could not foresee is that their data would be reused more than 100 times, becoming one of the most downloaded datasets at EGA. In 2015, Frederik S. Varn and colleagues accessed the above-mentioned data from the New Hampshire, USA, to correlate it to transcriptional programs of hematopoietic cells infiltrated in breast tumours and found that those can influence patients' prognosis. Their findings, published in Nature Communications, improved the understanding of the interplay between immune system and cancer. Again, in 2017 the dataset was downloaded by an Italian/Polish collaboration and used to corroborate their mechanistic study that demonstrate how a long non-coding RNA (lncRNA) is aberrantly localized into the chromatin, where it modulates oncogenic isoforms expression, thus contributing to breast cancer. To date, the METABRIC dataset has been reused to contribute to 147 publications. Its impact on breast cancer research is incalculable, and it even spread beyond that, with recent contributions to the understanding of pan-cancer mechanisms and features. Some of the publications are translating into improvements in diagnosis and treatment of different types of breast cancer. This is just an example of how data upcycling can amplify the potential of any dataset, well past the scope of its creation, the imagination of its owners and any geographical border. At EGA, we are proud to empower such fruitful worldwide cycles of knowledge, providing a platform that enables safe sharing of sensitive genetic data.

  Blog data-upcycling-powered-by-ega

• MTLE small RNA-sequencing and RNA-sequencing Data Access Committee

  Dac EGAC00001001427

• SEGA RNA-sequencing and small RNA-sequencing Data Access Commitee

  Dac EGAC00001001467

• Total RNA sequencing of RNA from testicular tissue

  Study EGAS00001006119

• Single cell RNA sequencing of human cord Blood CD34 Cells

  We performed single cell RNA sequencing and ATAC e valuation of human umbilical cord blood. To explore the differentiation pathway for human lymphoid lineage, our target cells contain CD34-positive cord blood. That population is evaluated by single cell RNA sequencing and single cell ATAC.

  Study JGAS000528

• Targeted_sequencing_of_genes_recurrently_mutated_in_AML

  Background Massively parallel sequencing technology has transformed cancer genomics. It is now feasible, in a clinically relevant time-frame, for a clinically manageable cost, to screen DNA from patient tumours for mutations essentially genome-wide. The challenge for personalised medicine will be to increase the sample size to thousands or tens of thousands of well-characterised cases in order to attain sufficient statistical power to stratify patients accurately across the complexity and genomic heterogeneity expected for most of the common tumour types. Currently, whole genome sequencing on this scale is not feasible, and targeted sequencing of relevant portions of the genome will be required. Pilot data We have developed protocols for large-scale, multiplexed sequencing of 100-200 genes in thousands of samples. Essentially, using robotic technology, genomic DNA from the cancer specimen is processed into sequencing libraries with unique DNA barcodes, thereby allowing sequencing reads to be attributed to the sample they derive from. Currently, these sequencing libraries can be generated in a 96-well format using fully automated protocols, and we are exploring methods to expand this to a 384-well format. The sequencing libraries are pooled and hybridized to custom sets of RNA baits representing the genomic regions of interest. Sequencing of the pulled-down libraries is done in pools of 48-96 samples per lane of an Illumina Hi-Seq. This protocol is already implemented at the Sanger Institute. We have published proof that somatic mutations in novel cancer genes can be identified from exome-wide sequencing. In unpublished pilot data, we have established the feasibility of robotic library production, custom pull-down, and multiplexed sequencing of barcoded libraries for 100 known myeloid cancer genes across 760 myelodysplasia samples. Highlights of the data thus far analysed reveal that the coverage is remarkably even between samples; when 96 samples are run, average coverage per lane of sequencing is ~250, with 90-95% of targeted exons covered by >25 reads; known mutations can be discovered in the data set; and the protocol is amenable to whole genome amplified DNA. The bioinformatic algorithms for identification of substitutions and indels in pull-down data are well-established; we have pilot data proving that copy number changes, LOH and genomic rearrangements in specific regions of interest can also be identified by tiling of baits across the relevant loci. Proposal We propose to apply this methodology to 10000 samples from patients with AML enrolled in clinical trials over the last 10-20 years. Oncogenic point mutations and potentially genomic rearrangements will be identified, and linked to clinical outcome data, with a view to undertaking the following sorts of analyses: • Identification of co-occurrence, mutual exclusivity and clusters of driver mutations. • Correlation of prognosis with driver mutations and potentially gene-gene interactions • Exploration of genomic markers of drug response Ultimately, we would like to be in a position to release the mutation data together with matched clinical outcome data to genuine medical researchers via a controlled access approach, possibly within the COSMIC framework (www.sanger.ac.uk/genetics/CGP/cosmic/). The vision here is to generate a portal whereby a clinician faced with an AML patient and his / her mutational profile can obtain a ‘personalised’ prediction of outcome, together with a fair assessment of the uncertainty of the estimate. With a sufficient sample size, there would also be the potential to develop decision support algorithms for therapeutic choices based on such data.

  Study EGAS00001000408

• Single cell RNA sequencing of normal endometrial derived organoids uncovers novel cell type markers for prognostication

  Endometrial carcinoma, the most common gynecologic cancer, develops from endometrial epithelium which is composed of secretory and ciliated cells. Pathologic classification is unreliable and there is a need for prognostic tools. We used single cell sequencing to study organoid model systems derived from normal endometrial endometrium to discover novel markers specific for endometrial ciliated or secretory cells. We performed single cell sequencing on endometrial and ovarian tumors and found both secretory-like and ciliated-like tumor cells.

  Study EGAS00001004466

• Combinatorial CRISPR screen identifies fitness effects of paralogues FAM50A and FAM50B

  Genetic redundancy has evolved as a way for human cells to survive the loss of genes that are single copy and essential in other organisms, but also allows tumours to survive despite having highly rearranged genomes. In this study we CRISPR screen 1,191 gene pairs, including paralogues and known and predicted synthetic lethal interactions to identify 105 gene combinations whose co-disruption results in a loss of cellular fitness. 27 pairs influence fitness across multiple cell lines including the paralogues FAM50A/FAM50B, two genes of unknown function. Silencing of FAM50B occurs across a range of tumour types and in this context disruption of FAM50A reduces cellular fitness whilst promoting micronucleus formation and extensive perturbation of transcriptional programmes. This dataset includes CRISPR screening of cancer cell lines, RNA sequencing studies of cancer cell lines and also data from the sequencing of tumour xenografts collected from mice.

  Dataset EGAD00001006649

• ATAC-Seq of human CD4 Treg cells

  This dataset maps gene expression regulation in human primary regulatory CD4+ T cells (Tregs). It includes whole genome sequence data for ATAC-seq (114 samples) The final quality filtered set included 73 individuals with ATAC-seq.

  Dataset EGAD00001005002

• SF11956 snATAC Seq GBM

  IDHR132H Wildtype GBM. Male, 63 Single Nuclei ATAC seq data from high grade human glioma samples. NovaSeq6000 was used for ATAC seq. The files uploaded are bam files created with grch38 reference.

  Dataset EGAD00001005406

• ATAC-seq

  ATAC-seq data. Dataset includes FASTQ files, BAM files, and analysis files with the ATAC-seq peaks determined using MACS2.

  Dataset EGAD00001008962

• RNA-sequencing

  RNA-sequencing for a cohort of B-ALL samples : 5 Down Syndrome (DS), 16 Hyperdiploid (HeH), 6 iAMP21, 9 other. RNA-sequencing for B-cell progenitors from 3 healthy. It also contains RNA-sequencing datasets of Patient-Derived Xenografts (X) developed from the B-ALL samples : 4 Down Syndrome (DS), 4 Hyperdiploid (HeH), 1 iAMP21, 3 other.

  Dataset EGAD00001005426

• Ewings Sarcoma RNA-Seq

  Sarcomas are cancers of the bone and soft tissue often defined by their gene fusions. However, the timing, context, and processes by which these pathogenic fusions arise are unknown. We explored this in Ewing sarcoma, a cancer driven by EWSR1-ETS fusions, with very few cooperating mutations. Combining whole-genome sequencing with enhanced informatics, we found that the EWSR1-ETS fusion arose from striking rearrangement clusters in 42% of cases (52/124). Notably, these were organized in loops that universally contained the fusion at their center, while also weaving up to 18 genes together with it. We found the same pattern of rearrangements in three additional types of sarcoma. From these data, we define a new signature for sarcoma fusions that precedes other somatic changes, in the earliest replicating DNA of the genome. This dramatic, sudden process impinges on many genes – generating multiple coding changes that profoundly affect the transcriptome, with the disease-defining gene fusion at its core. These rearrangement loops emerge in an early ES clone from which both the primary tumor and the lethal relapse emerged, and then evolved in parallel until clinically detected.

  Study EGAS00001003062

• MMP-seq cell lines (FASTQ)

  MMP-seq cell lines (FASTQ)

  Dataset EGAD00001001107

• MMP-seq tumor samples (FASTQ)

  MMP-seq tumor samples (FASTQ)

  Dataset EGAD00001001108