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• Bulk and single-cell RNA-sequencing data from five lines of human iPSC-derived (hiPSC-derived) astrocytes (3 in-house and 2 commercial lines), both alone and in co-culture with neurons, to define the molecular response of astrocytes to misfolded alpha-synuclein

  RNA editing is a post transcriptional mechanism that targets changes in RNA transcripts to modulate innate immune responses. We report the role of astrocyte specific, ADAR1 mediated RNA editing in neuroinflammation in Parkinson’s disease. We generated hiPSC-derived astrocytes, neurons and co-cultures and exposed them to small soluble alpha-synuclein aggregates. Oligomeric alpha-synuclein triggered an inflammatory glial state associated with TLR activation, viral responses, and cytokine secretion. This reactive state resulted in loss of neurosupportive functions, and the induction of neuronal toxicity. Notably, interferon response pathways were activated leading to upregulation, and isoform switching of the RNA deaminase enzyme, ADAR1. ADAR1 mediates A-to-I RNA editing, and increases in RNA editing were observed in inflammatory pathways in cells, as well as in post-mortem human PD brain. Aberrant, or dysregulated, ADAR1 responses and RNA editing may lead to sustained inflammatory reactive states in astrocytes triggered by alpha-synuclein aggregation, and this may drive the neuroinflammatory cascade in Parkinson’s.

  Study EGAS50000000751

• Prevalence and Clinical Characteristics of hearing loss caused by MYH14 mutation

  Mutations in MYH14 are reported to cause autosomal dominant nonsyndromic hereditary hearing loss (ADNSHL), and 35 variants have been reported to cause hearing loss in various ethnic groups, but the information on prevalence as well as clinical features are fragmented. In this study, genetic screening for MYH14 variants was carried out using a large series of Japanese hearing loss patients to reveal the information. Massively parallel DNA sequencing of 68 target candidate genes was utilized in 8074 (including 1336 ADNSHL) unrelated Japanese hearing loss patients (probands) to identify genomic variations responsible for hearing loss. We identified 20 patients with 14 mutations from 15 pedigrees. The prevalence was proved to be 0.19% (15/8074) among hearing loss patients, and 1.12% (15/1336) among ADNSHL patients. The 12 mutations out of 14 mutations identified were novel. The patients typically showed late onset, slowly progressive modelate flat-type hearing loss. The clinical information revealed by the present study would contribute to further diagnosis and management of MYH14-associated hearing loss.

  Study JGAS000323

• Immuno-genomic Profiling of Biopsy Specimens Predicts Neoadjuvant Chemotherapy Response in Esophageal Squamous Cell Carcinoma

  Esophageal squamous cell carcinoma (ESCC) is one of the most aggressive cancers and is primarily treated with platinum-based neoadjuvant chemotherapy (NAC). Some ESCCs respond well to NAC. However, biomarkers to predict NAC sensitivity and their response mechanism in ESCC remain unclear. We introduce a model by machine learning and validated its potential to predict the NAC response in ESCC. To create this model, we performed whole genome sequencing and RNA-seq analysis on totally 141 ESCC biopsy specimens before NAC treatment and analyzed their immuno-genomic features and association with NAC response. Neutrophils infiltration could play an important role in ESCC response to NAC. We also demonstrated that specific copy number alterations and copy number signatures in the ESCC genome were significantly associated with NAC response. The interactions between the tumor genome and immune features of ESCC are likely to be a new indicator of therapeutic capability and a new therapeutic target for ESCC, and machine learning prediction for NAC response is useful.

  Study JGAS000535

• DCIS fresh frozen fragmentomics dataset

  Ductal carcinoma in situ (DCIS) is a non-obligate precursor lesion of breast cancer (BC). Often detected by mammography, most cases are managed through surgical and/or radiotherapy approaches. Today, it is not possible to predict which patients will progress to invasive disease. Here, we evaluated high-depth whole-genome sequenced (WGS) DCIS, enriched for highgrade clinical lesions, to understand whether deep WGS could reveal biological insights and/or personalized therapeutic vulnerabilities that may be targetable. We find genomic locations that are likely susceptible to producing the initiating lesion for structural variations (SVs) prone to subsequent evolution, termed SHOREs (Susceptibility HOtspots for Rearrangements and ongoing Evolution). We additionally highlight individualized therapeutic potential that would otherwise not be appreciable without WGS. We posit that holistic WGS profiling could offer a more precise stratification approach, discerning higher-risk cases for prospective clinical studies on personalized therapies, from truly low-risk cases suitable for active monitoring. To substantiate our WGS findings, we also performed RNAseq on the same samples, this EGA study contains the RNAseq data.

  Study EGAS50000001475

• Comprehensive analyses of somatic TP53 mutation in tumors with variable mutant allele frequency

  Somatic mutation of the tumor suppressor gene TP53 is reported in at least 50% of human malignancies. Most high-grade serous ovarian cancers (HGSC) have a mutant TP53 allele. Accurate detection of these mutants in heterogeneous tumor tissue is paramount as therapies emerge to target mutant p53. We used a Fluidigm Access Array™ System with Massively Parallel Sequencing (MPS) to analyze DNA extracted from 76 serous ovarian tumors. This dataset has been made available to researchers through the European Genome-phenome Archive (EGA). Herein, we present detailed analyses of this dataset using HaplotypeCaller and MuTect2 through the Broad Institute’s Genome Analysis Toolkit (GATK). We also present comparisons of the ability to detect TP53 mutation by MPS and Sanger sequencing in these tumors. We anticipate that this TP53 mutation dataset will be useful to researchers developing and testing new software to accurately determine high and low frequency variant alleles in heterogeneous aneuploid tumor tissue. Further, the analysis pipeline we present provides a valuable framework for determining somatic variants more broadly in tumor tissue.

  Study EGAS00001002200

• Targeted sequencing of Burkitt lymphoma tumour samples from the UK's Haematological Malignancy Research Network

  The UK’s Haematological Malignancy Research Network (www.HMRN.org) was established in 2004 to provide robust generalizable data to inform clinical practice and research. HMRN is a collaboration between researchers in the Epidemiology & Statistics Group (ECSG) at the University of York, a unified Clinical Network operating across 14 hospitals, and an integrated Haematological Malignancy Diagnostic Service (HMDS) in Leeds. Covering a population of around 4 million, HMRN collects detailed information about all patients diagnosed with a haematological malignancy within the HMRN region, accruing around 2,400 new diagnoses each year. The population has a similar socio-demographic profile to the country as a whole, and HMRN’s maturing data present an increasingly valuable resource to address real questions of concern to haematologists, commissioners and health service researchers – locally, nationally and internationally. This study forms part of a larger project employing targeted exome sequencing on tumour samples from patients diagnosed with a variety of both lymphoid and myeloid malignancies. The results for samples collected from 39 Burkitt lymphoma patients, diagnosed within HMRN from 2005 to 2012, are provided.

  Study EGAS00001004649

• Mechanisms_of_patient_response_to_Dabrafenib_in_Melanoma

  Samples will be from the BRF113683 (BREAK-3) study which is a Phase III Randomized, Open-label Study Comparing GSK2118436 to Dacarbazine (DTIC) in Previously Untreated Subjects With BRAF Mutation Positive Advanced (Stage III) or Metastatic (Stage IV) Melanoma (n=250 enrolled)•NGS [Agilent capture (Sanger V2 panel): 360 genes and 20 gene fusions; Illumina HiSEQ Sequencing]•CNV: [via NGS or Affy SNP 6.0 or Illumina Omni (TBD)]Bioinformatics: Analysis will be performed using core Sanger informatics pipelines similar to those previously described (Papaemmanuil E et al. (2013) Blood. 22:3616 -3627). Briefly, copy number analysis will be performed using the ASCAT algorithm, and base substitutions, small insertions and deletions using the CAVEMAN and Pindel algorithms, respectively. Statistical approaches including generalized linear models will be used to predict clinical variables such as maximum clinical response and duration of response using genetic data. Sanger and EBI to conduct analysis; Raw data and correlation with clinical endpoints to be analyzed by both EBI/Sanger and GSK (unique pipeline analyses to increase call confidence)

  Study EGAS00001000946

• HCA_Placental_Infection_Atlas

  HCA Placental Infection Atlas Self-renewing human trophoblast stem cells (hTSC) can give rise to major trophoblast lineages, including syncytiotrophoblast (SCT) and extravillous trophoblast (EVT). hTSC has facilitated the study of placental development and function in vitro. Here, we aim to utilise the hTSC line (HMDMC 20/0005) to study human placental infection and inflammation. This study will provide the opportunity to better understand the pathogenesis of human placenta in the event of infection and inflammation. In brief, differentiated hTSC will be infected with relevant pathogens and stimulated with a panel of inflammatory cytokines. We will use single-cell genomic and spatial approaches to characterise cellular heterogeneity in response to infection or cytokines stimulus. In parallel, we will investigate the interaction between iPSC-derived macrophages with different trophoblast lineages during the course of infection using single-cell genomic and spatial methods. 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 EGAS00001004722

• Primary prostate Hi-C

  Prostate cancer is a heterogeneous disease whose progression is linked to genome instability. Despite large-scale tumour sequencing efforts, the impact of mutations on the genetic architecture in cancer remains ill-defined due to limited integration of genomics data across dimensions. We addressed this limitation by assessing the impact of structural variants on the chromatin states and the three-dimensional organization across benign and malignant primary prostate genomes. We find high concordance in the three-dimensional genome organization between malignant and benign prostate tissues, arguing for constraints to the three-dimensional genome of prostate tumours. Moreover, we identify structural variants as effectors of changes to focal chromatin interactions, guiding cis-regulatory element hijacking that imposes opposing expression changes on genes found at antipodes of a rearrangement. This leads to the repression of tumour suppressor gene expression and up-regulation of oncogenes, such as at the TMPRSS2-ERG and PMEPA1-ZNF156 loci. Collectively, our results argue that cis-regulatory element hijacking by structural variants overshadows large-scale topological changes to alter gene regulation and promote oncogenesis.

  Study EGAS00001005014

• A combined circulating tumor DNA and protein biomarker-based liquid biopsy for the earlier detection of pancreatic cancer

  The earlier diagnosis of cancer is one of the keys to reducing future cancer deaths. Here we describe our efforts to develop a non-invasive, blood test for the detection of pancreatic ductal adenocarcinoma. We combined blood tests for KRAS gene mutations with carefully thresholded protein biomarkers to determine whether the combination of these markers was superior to any single marker. The cohort tested included 221 patients with resectable pancreatic ductal adenocarcinoma and 185 control patients without known cancers. KRAS mutations were detected in the plasma of 66 patients (30%) and every mutation found in the plasma was identical to that subsequently found in the patients' primary tumor (100% concordance). The use of KRAS in conjunction with two thresholded protein biomarkers (CA19-9 and prolactin) increased the sensitivity to 67%. Only one of the 185 plasma samples from the control cohort were positive for any of the three markers (99.5% specificity). This combinatorial approach may prove useful for the earlier detection of many cancer types.

  Study EGAS00001002444