19375 results for "Cheap fc 26 coins Buyfc26coins.com is official EA Sports partner for FC 26 coins That was the fastest delivery ever..fxB4"

in 50.51 milliseconds.

• Pediatric Non-Down Syndrome Acute Megakaryoblastic Leukemia is Characterized by Distinct Genomic Subsets with Varying Outcomes

  Acute Megakaryoblastic Leukemia (AMKL) is a subtype of acute myeloid leukemia (AML) in which cells morphologically resemble abnormal megakaryoblasts.  While extremely rare in adults, AMKL accounts for 4-15% of newly diagnosed childhood AML1-3.  A significant proportion of pediatric AMKL cases occur in children with Down syndrome (DS).  These patients have excellent outcomes and are characterized at the genomic level by a founding GATA1 mutation4-6.  In contrast, AMKL in patients without DS (non-DS-AMKL) is frequently associated with poor outcomes.  Previous efforts have identified chimeric oncogenes in a significant number of cases, including RBM15-MKL1, CBFA2T3-GLIS2, KMT2A gene rearrangements and NUP98-KDM5A7-9.  The etiology of 30-40% of cases, however, remains unknown.  To better understand the genomic landscape of non-DS-AMKL, we performed RNA and exome sequencing on specimens from 99 patients (75 pediatric and 24 adult).  We demonstrate that pediatric non-DS-AMKL is a heterogeneous malignancy that can be divided into seven subgroups with varying outcomes.  These subgroups are characterized by chimeric oncogenes with cooperating mutations in epigenetic and kinase signaling genes.  Overall, these data shed light on the etiology of AMKL and provide useful information for treatment tailoring. 

  Study EGAS00001002183

• Epigenome-wide methylation analysis of colorectal carcinoma, adenoma and normal tissue reveals novel biomarkers addressing unmet clinical needs

  Studies about CRC biomarker discovery have focused on methylation patterns in normal and colorectal tumor tissue, leading to a lack of knowledge of methylation in adenomas. Therefore, we performed the first epigenome-wide study to compare the epigenomes of all three tissue types combined, and to identify discriminatory biomarkers. Public Illumina MethylEPIC® data was collected from 552 normal, 118 carcinoma and 116 adenoma samples. Pairwise analyses were performed for discovery of differentially methylated probes (DMPs). We identified 693 813, 620 643 and 558 897 DMPs when comparing normal vs carcinoma, normal vs adenoma and adenoma vs carcinoma respectively. To double evidence (DE) these DMPs, analysis of Illumina 450K data from public datasets was performed. Through this analysis, 13 DE DMPs with │Δβ│≥0.3 were identified for adenoma vs carcinoma. A binary logistic regression model was generated to evaluate the discriminatory potential of these DE DMPS. The model was validated in an in-house experimental methylation dataset of 13 adenoma and 9 carcinoma samples. Our classifier reached a cross-validated AUC of 0.996 and 0.855 in the discovery and validation datasets respectively. A sensitivity and specificity of 96% and 95% were reached, with an overall accuracy of 96%. Our analysis show that methylation biomarkers have the potential to discriminate between normal, precursor and carcinoma tissues of the colorectum. More importantly, we highlight the power of the methylome, showing that DMPs can be used as biomarkers in the clinic to identify colorectal adenoma and carcinoma. 

  Study EGAS00001007017

• How to use EGA Webin?

  EGA Webin EGA Webin serves as a platform for registering metadata for array based submissions, large scale sequence submission as well as for legacy EGA submission accounts (ega-box-XXXX). For large scale submitters of sequence data you have also the option to submit metadata via XMLS programmatic submission, while new submitters are advised to utilise the Submitter Portal for their submissions. You can request a legacy EGA submission account (ega-box-XXXX) by populating this form. Please, allow two business days for our Helpdesk team to contact you after populating this form. WEBIN actions: Register metadata for a sequence submission Register study, samples, experiments, runs, DAC, policy and dataset/s after file upload. Register components for your array-based metadata submission Register study, samples, DAC or policy before uploading files. Edit existing submission metadata Change or update previously submitted metadata. Register metadata for a sequence submission Ensure that all sequence files have been encrypted before uploading them to your submission account using the EgaCryptor. Go to the EGA Webin and log in using your submission account name (ega-box-XXX) and password. Register components of your metadata submission Study Samples Data Access Committee (DAC) Data access policy Dataset For array-base submissions: Study, Samples, Data Access Committee (DAC) and Data access policy may all be registered BEFORE file upload and dataset registration through the array-base template. Register your Study Go to the “Studies (Projects)” box Click on “Register Study” and fill in the information related to your study. Click on “Submit”, this will save the information and generate an EGA study ID. To use the study accession number in a publication, the study has to be previously released on the EGA website, we suggest the following format: "Sequence data has been deposited at the European Genome-phenome Archive (EGA), which is hosted by the EBI and the CRG, under accession number EGASXXXXXXXXXXX.Further information about EGA can be found on https://ega-archive.org and “The European Genome-phenome Archive in 202 "(10.1093/nar/gkab1059)" Register your Samples Go to the “Samples” box Click on “Register Samples” Select “Download spreadsheet to register samples” and customise your template, there is a default EGA template (EGA default checklist) but more attributes can be added if required. For the EGA default checklist, there are mandatory,recommended and optional attributes. As well custom fields which can be added if required. Mandatory attributes Field Name Description tax_id Taxonomy ID of the organism as in the NCBI Taxonomy database. Entries in the NCBI Taxonomy database have integer taxon IDs. See our tips for sample taxonomy here scientific_name Scientific name of the organism as in the NCBI Taxonomy database. Scientific names typically follow the binomial nomenclature. For example, the scientific name for humans is Homo sapiens. sample_alias Unique name of the sample. If not selected system will auto generate an unique alias sample_title Title of the sample sample_description Description of the sample phenotype *** Where possible, please use the Experimental Factor Ontology (EFO) to describe your phenotypes. Recommended attributes Field Name Description subject_id Identifier for the subject where the sample has been derived from gender * Sex Optional attributes Field Name Description sex sex of the organism from which the sample was obtained disease_site Affected organ sample type Affected organ donor_id ** Identifier of the donor where the sample has been derived from *Gender should be described as 'male', 'female' or 'unknown'. If 'unknown' due to a known sex chromosome aneuploidy, please create a user defined attribute called 'Sex chromosome karyotype' and add the appropriate value, for example, 'XXY'. **Donor id (Subject id) should be a de-identified subject handle. If unknown, please add 'unknown' to the field. ***Phenotypes should, where possible, be an Experimental Factor Ontology accession. If a term cannot be found to describe your phenotype please use free text. All sample phenotypes considered important for further analysis of the data should be provided (for example, tumour type), additional phenotype attributes can be created by defining your own attributes; use the notion 'phenotype2', 'phenotype3', etc. After you have customised the fields for the sample submission, download the template and fill in the information. Example of the sample template: Finally upload the sample template to get the EGA accession IDs for the samples. Register your Data Access Committee (DAC) Further information on the role of your DAC Go to the “Data Access” box Click on “Register Dacs” Input the information about the DAC and register at least one main DAC contact. Register your Data Access Policy Your Data Access Policy provides the terms and conditions of data use, this is also referred to as the Data Access Agreement (DAA). Completion of a DAA by the applicant/s should form part of the application process to the Data Access Committee (DAC). Go to the “Data Access” box Click on “Register Policies” Select the DAC to which this policy will be linked to and fill in the policy information. Submitting your Runs and Analyses This section is only for sequence data submission, for array-based submission it can be skipped. Please refer to our Submitting array based metadata Runs Registration Go to the “Raw Reads (Experiments and Runs)” box Click on “Submit Reads” Select “Download spreadsheet template for Read submission” Select the template corresponding to your submission type For the templates you have the option to customise the optional fields. To check their description click on “Show Description “ Download the template and fill in the required information. Example of the runs template: We recommend that Fastq, BAM, and CRAM read files are submitted using Webin-CLI When using this interface instead of Webin-CLI, raw sequences must be uploaded in one of the supported data formats before they can be submitted. The files can be uploaded using FTP or Aspera. The study and the sequenced samples must be pre-registered before the raw reads are submitted. Please note that each individual study and sample should be registered only once. You will be asked to provide information about the sequencing libraries and instruments. Submitting your Dataset This section is only for sequence data submissions, for array based submissions it can be skipped. Please refer to our Submitting array based metadata The dataset describes the data files, defined by the run (EGARXXXXXXXXXXX) and analysis (EGAZXXXXXXXXXXX) accessions that make up the dataset and links the collection of data files to a specified Data Access Committee and Data Access Policy. As a result, you must have registered your Reads and experiments, Data Access Committee (DAC) and Data access policy before submitting your Dataset. Please consider the number of datasets that your submission consists of, for example, a case control study is likely to consist of at least two datasets. In addition, we suggest that multiple datasets should be described for studies using the same samples but different sequence technologies. Please contact EGA Helpdesk for further assistance. Go to the “Data Access” box Click on “Register Dataset” Select the Data Access Committee (DAC) and Data access policy Register your dataset After submitting your dataset you should contact the EGA Helpdesk to provide a release date for your dataset. Datasets are automatically held (i.e. not released) unless they are affiliated to a study that has already been released. Edit/update existing submission metadata Go to the “Report” section of the object you would like to edit. Locate the object and click on the arrow under action. An option menu will be displayed. Objects can be edited through their XML or with the WEBIN menu. After an object has been edited, changes would be available on the website until the submission is released again. Please contact the EGA Helpdesk if you require further assistance.

  Documentation submission/metadata/submission/EGA_webin

• Jeju Genome Project DAC

  This Data Access Committee (DAC) evaluates and manages access requests for large-scale genomic and phenotypic datasets generated as part of the Jeju Genome Project (JGP). The committee's mission is to facilitate responsible data sharing to advance precision medicine and population genetics. The DAC ensures that data access is granted only to bona fide researchers who agree to the terms of the Data Access Agreement (DAA) and whose proposed research is strictly consistent with the informed consent provided by the participants and the ethical guidelines of the project.

  Dac EGAC50000000938

• ScRNA-seq of human kidney immune cells of patients with ANCA-associated glomerulonephritis, Lupus Nephritis against a "healthy" nephrectomy control

  ANCA-associated glomerulonephritis (AGN) associates with a high risk of end-stage kidney disease. The role of kidney immune cells in local inflammation remains unclear. Here, we investigate kidney immune cell diversity and function. Kidney tissue from AGN patients (n=5) and a lupus nephritis (LN) patient (n=1) were aquired during a biopsy procedure for a clinical indication. Needle-core biopsies were obtained for histopathological examination, and an additional pass was performed to retrieve kidney tissue for scRNA-seq. Healthy kidney tissue (n=1) was obtained from a kidney that was surgically removed do tue due to a (non-invasive) papillary urothelial carcinoma. Immediately after collection, kidney tissue was processed into a single-cell suspension and sorted using a 4-color flow cytometry panel to isolate living, CD45+ immune cells. To aid in the multi-omic characterization, surface markers and T and B cell repertoires were sequenced in 2 samples (1 AGN patient and the nephrectomy control). These samples were incubated with an oligo-antibody TotalSeq-C cocktail containing 130 unique cell surface antigens.

  Study EGAS50000000159

• Identification_of_the_underlying_causal_variant_in_a_multi_generational_family_with_autosomal_dominant_common_variable_immunodeficiency

  Common variable immunodeficiency (CVID) is the most common form of primary immunodeficiency with an estimated incidence of 1:10,000. It has been apparent for many years that CVID has a genetic component, occurs frequently in families and can have both a recessive or dominant mode of inheritance. In recent years, 4 genes underlying CVID have been identified; however, mutations within in them are estimated to account for no more than 10% of all cases of CVID.We have identified a multi-generational family with autosomal dominant CVID. Genome-wide linkage analysis has mapped the locus underlying CVID in this family to an approximately 9.2 Mb interval on chromosome 3q27.3-q29, between the markers D3S3570 and D3S1265. This locus is distinct from any of the previously mapped susceptibility loci suggesting a novel genetic variant is responsible for disease in this family. The aim of this study is to use exome sequencing of affected (n = 4) and unaffected (n = 4) individuals, in tandem with the available genetic mapping data, to identify the causal variant underlying CVID in this family.

  Study EGAS00001000269

• Novel Factors for Unexplained Phenotypes of Subclinical Carotid Atherosclerosis

  The overall goal for this study was to determine the genetic factors associated with extreme phenotypes of subclinical atherosclerosis (protective and deleterious). Study participants were selected from the Northern Manhattan Study (NOMAS), a population based cohort study investigating stroke and stroke risk factors in Northern Manhattan. Cases and controls were individuals at the extreme ends of the distribution for carotid intima-media thickness and carotid plaque, with cases defined as individuals with subclinical atherosclerosis that could not be explained by traditional vascular risk factors (USAth) and controls defined as individuals with unexplained protection against atherosclerosis (UPAth).

  Study phs001560

• NEI CIDR Methylation Profiling of Primary Open Angle Glaucoma in GLAUGEN Samples

  This is a case-control study of Primary Open Angle Glaucoma (POAG). POAG is a progressive optic neuropathy that eventually leads to blindness. More than 30 million people worldwide have Primary Open Angle Glaucoma (POAG), of which greater than 3 million are blind. Gene expression changes in the retina have been observed for POAG. Several recent studies, including the GLAUGEN (Glaucoma Gene Environment) initiative have used GWAS to identify correlative regions of the genome. Despite this, the genetic basis of Glaucoma is not well understood. Epigenetic variation may account for low heritability and environmental effects on human disease. Despite the significant advances being made in understanding the role of epigenetics in gene regulation in other fields, little is known about the relationship between DNA methylation patterns, retinal gene expression, and retinal disease. The goal of this study is to identify differentially methylated regions in the peripheral blood of patients with POAG. The case identification is as per the GLAUGEN description: Cases and controls were recruited from ophthalmology clinics and were examined by ophthalmologists. For cases the clinical exam included intraocular pressure measurements, optic nerve assessment and visual field evaluation. Controls had no family history of glaucoma, normal intraocular pressure and normal optic nerves. POAG and control samples come from Massachusetts Eye and Ear Infirmary (MEEI). These samples were collected and genotyped as part of the GLAUGEN study. From the MEEI, 50 patients were selected from POAG pedigrees, to include all the probands genotyped by CIDR and are currently undergoing exome sequencing, and to include additional genotyped probands who belong to pedigrees of sufficient size and structure that parent of origin effects could be evaluated. Additional individual-level phenotype and genotype data may be obtained through the authorized access portal of phs000308 (Geneva - Glaugen GWAS Study).

  Study phs000461

• Data Access Committee for Maurice Lab - UMC Utrecht

  The Data Access Committee of the Maurice lab at the Center for Molecular Medicine, University Medical Center Utrecht, is responsible for reviewing and approving requests for access to controlled human transcriptomics and genomics data generated by the lab. The DAC ensures that data access requests are consistent with informed consent, ethical approvals, and applicable legal and institutional regulations, including GDPR.

  Dac EGAC50000000876

• National Eye Institute Glaucoma Human Genetics Collaboration (NEIGHBOR) Consortium Glaucoma Genome-Wide Association Study

  This is a case-control study of primary open angle glaucoma (POAG). POAG is an intraocular pressure (IOP) related progressive optic neuropathy that ultimately leads to blindness. For this study we have formed a collaborative consortium contributing 2170 POAG cases and 2347 controls with a unified definition of POAG (the NEIGHBOR consortium: NEI Glaucoma Human genetic collaBORation). The case definition has also been harmonized with an additional 976 cases and 1140 controls from the NHGRI supported GENEVA (gene-environment) study of glaucoma (GLAUGEN) (NIH/NHGRI U01HG004728, Pasquale PI). Cases and controls were recruited from ophthalmology clinics and were examined by ophthalmologists. For cases, the clinical exam included intraocular pressure measurements, optic nerve assessment and visual field evaluation. Controls had no family history of glaucoma, normal intraocular pressure and normal optic nerves. Cases and controls were also drawn from two clinical trial populations: Advanced Glaucoma Intervention Study (AGIS, NEI U10EY006827, D. Gaasterland PI) and Collaborative Initial Glaucoma Treatment Study (CIGTS, NEI U10 EY009149, P. Lichter PI). The NEIGHBOR consortium has two Co-Principal Investigators: J. Wiggs (Harvard, MEEI), and M. Hauser (Duke). The consortium includes eleven different centers where data collection and analysis take place. The eleven sites and investigators are: Harvard Medical School (Massachusetts Eye and Ear Infirmary) (J. Wiggs, L. Pasquale); Duke University Medical Center (M. Hauser, E. Hauser, R. Allingham, S. Schmidt); University of Michigan (J. Richards, S. Moroi, P. Lichter); University of Miami (M. Pericak-Vance, R. Lee, D. Budenz); Vanderbilt University (J. Haines); University of California San Diego (K. Zhang, R. Weinreb; T. Gaasterland); University of Pittsburgh (J. Schuman, G. Wollstein); University of West Virginia (A. Realini, J. Charlton, S. Zareparsi); Johns Hopkins University (D. Friedman, D. Zack); Stanford University (D. Vollrath, K. Singh), Eye Doctors of Washington (D. Gaasterland). Hemin Chin serves as the NEI Staff Collaborator. This national collaborative study is supported by multiple NIH grants: NEI R01 EY015543 (Allingham); NEI U10 EY006827 (D. Gaasterland); NHLBI R01 HL073389 (E. Hauser); NEI R01 EY13315 (M. Hauser); NEI U10 EY009149 (Lichter); NEI R01 EY015473 (Pasquale); NEI U10 EY012118 (Pericak-Vance); NEI R03 EY015682 (Realini); NEI R01 EY011671 (Richards); NEI R01 EY09580 (Richards); NEI R01 EY013178 (Schuman); NEI R01 EY015872 (Wiggs); NEI R01 EY009847 (Wiggs); NEI R01 EY010886 (Wiggs); NEI R01 EY144428 (Zhang); NEI R01 EY144448 (Zhang); NEI R01 EY18660 (Zhang). Funding support for genotyping, which was performed at the Johns Hopkins University Center for Inherited Disease Research, was provided by the National Eye Institute (X01HG005259).

  Study phs000238

• The aim of this study was to identify underlying hub genes and dysregulated pathways associated with the development of HCC using bioinformatics analysis.

  In the present study, we identified differentially expressed protein-coding genes from RNA transcriptional profiling performed on 11 paired cancer tissues and adjacent non-cancerous tissues. Then, we conducted GO, KEGG, PPI network and centralities analyses to study and identify changes in pathways and hub genes. The aim of this study was to improve understanding of HCC carcinogenesis by providing information concerning the genetic changes that occur during disease progression and to uncover the expression of biomarkers with potential use for clinical diagnosis, treatment, and monitoring of disease progression.

  Study EGAS00001002526

• A PROSTATE TUMORGRAFT PANEL TO ACCELERATE PRECISION MEDICINE

  The management of advanced prostate cancer (PCa) has strongly evolved in the last decade with the introduction of the next generation of androgen receptor pathway inhibitors which have considerably improved patient outcomes. Most recently, the investigation of genomic landscape has provided targetable molecular alterations such as homologous gene DNA repair defects correlated with response to PARP inhibitors. Despite these significant advances, while localized PCa is generally associated with favorable outcome, metastatic PCa is currently considered incurable. For further investigations in precision treatment, the development of preclinical models representing the complex prostate tumor heterogeneity are mandatory. Accordingly, we aimed to establish a resource of patient-derived xenograft (PDX) models that exemplify each phase of this multistage disease for accurate and rapid evaluation of candidate therapies.

  Study EGAS00001007033

• Chromosomal copy number heterogeneity predicts survival rates across cancers

  Survival rates of cancer patients vary widely within and between malignancies. While genetic aberrations are at the root of all cancers, individual genomic features cannot explain these distinct disease outcomes. In contrast, intra-tumour heterogeneity (ITH) has the potential to elucidate pan-cancer survival rates and the biology that drives cancer prognosis1,2. Unfortunately, a comprehensive and effective framework to measure ITH across cancers is missing3. Here, we introduce a scalable measure of chromosomal copy number heterogeneity that predicts patient survival across cancers. We show that the level of ITH can be derived from a single-sample copy number profile. Using gene-expression data we demonstrate that ongoing chromosomal instability underlies the observed heterogeneity. Analysing 11,534 primary cancer samples from 35 different malignancies, we find that copy number heterogeneity can be accurately deduced and predicts cancer survival across tissues of origin and stages of disease. Our results provide a unifying molecular explanation for the different survival rates observed between cancer types.

  Study EGAS00001004702

• Single-cell targeted DNA-sequencing and protein sequencing

  We performed single-cell targeted DNA sequencing (MissionBio) on 13 high hyperdiploid B-ALL patients at diagnosis to study the genetic heterogeneity. For a number of patients single-cell surface protein antibody sequencing was added (DAB-seq) to better characterize the different cell types. Furthermore, additional samples during treatment were collected and analysed for some patients. In this way we want to study the clonal heterogeneity of these B-ALL samples, based both on mutations and CNVs, and identify resistant clones that could be targeted after relapse.

  Study EGAS50000000580

• WGS of liver cancer in the Japanese population

  Hepatocellular carcinoma (HCC) is the third leading cancer-related cause of death and the seventh most common form of cancer worldwide, with an estimate of more than 700,000 new cases each year. The most established risk factors of HCC are chronic HBV and HCV infection. HBV infection is responsible for over 50% of the worldwide attributable risk of HCC, especially in East Asia and Africa, while in Japan and several Western countries HCV infection is the most common risk factor for HCC. To gain insights into the molecular alterations of virus-associated HCC, we performed whole genome sequencing (WGS) of 321 HCC tumors from 159 patients. This work was performed as a part of the ICGC (International Cancer Genome Consortium) project.

  Study EGAS00001000678

• Tetralogy of fallot whole-exome sequencing

  829 adult and child probands of Northern European ancestry presenting with TOF were recruited from nine centres: seven in the UK, Leuven (Belgium), and Sydney (Australia). Patients sequenced exhibited no clinical features of recognised syndromes, extra-cardiac abnormalities or learning difficulties. All samples were screened for the 22q11.2 deletion associated with TOF prior to sequencing to ensure that this was not present. Samples were sequenced on HiSeq2000 and reads aligned using BWA.

  Study EGAS00001003302

• Ensemble learning for classifying single-cell data and projection across reference atlases

  Single-cell data are being generated at an accelerating pace.How best to project data across single-cell atlases is an open problem. We developed a boosted learner that overcomes the greatest challenge with status quo classifiers: low sensitivity, especially when dealing with rare cell types.

  Study EGAS00001004283

• Esophageal Squamous Cell Carcinoma Precursor Study

  Esophageal cancer is the sixth most common cause of cancer death in the world. High-risk areas occur across central Asia and from eastern to southern Africa, and in these populations, nearly all of the cases are esophageal squamous cell carcinoma (ESCC). ESCC has a dismal prognosis, largely because symptoms usually appear late in the course of the disease, when the tumors are incurable. Early detection and treatment of curable precursor lesions and early invasive ESCC in asymptomatic high-risk adults offers the potential for long-term survival and reduced mortality from this disease. Previous studies have shown that routine cytology of non-endoscopically collected esophageal cell samples is not sensitive and specific enough to be clinically useful, so we are now looking for molecular markers of high-grade esophageal squamous dysplasia (HGD), the proven clinically important precursor lesion of ESCC, that can be used to increase the accuracy and utility of this initial screening exam. National Cancer Institute (NCI) and Cancer Institute and Hospital, Chinese Academy of Medical Sciences (CAMS) began collaborative studies of ESCC since the mid-1980s in China. The present proposal is designed to characterize the type and prevalence of DNA mutations in tissue samples of HGD and to establish biologic and questionnaire resources for further study. The proposed study has two components, a field study to obtain questionnaire data and biological samples, and a genomic analysis to perform sequencing of the biological samples and bioinformatics analysis of the sequencing. 

  Study phs002814

• GEenetic landscape of hypodiploid acute lymphoblastic leukemia

  Hypodiploid acute lymphoblastic leukemia (ALL) is an aggressive leukemia characterized by aneuploidy and poor outcome. The genetic basis of hypodiploid ALL is unknown. Here, using complementary genome-wide profiling approaches, we show that hypodiploid ALL comprises two subtypes that differ in the severity of aneuploidy, transcriptional profile and submicroscopic genetic alterations. Near haploid cases with 24-31 chromosomes frequently harbor alterations targeting receptor tyrosine kinase- and Ras signaling (71%) and IKZF3 (AIOLOS; 13%). In contrast, low hypodiploid ALL cases with 32-39 chromosomes are characterized by TP53 alterations, almost half of which are present in non-tumor cells, and have alterations of IKZF2 (HELIOS; 53%) and RB1 (41%). Both near haploid and low hypodiploid tumors exhibit activation of Ras and PI3K signaling pathways, and are sensitive to PI3K inhibition, indicating that these drugs should be explored as a new therapeutic strategy for this frequently lethal form of leukemia.

  Study EGAS00001000380

• DONSON encodes a novel replication fork protection factor mutated in microcephalic dwarfism.

  To ensure efficient genome duplication, cells have evolved a multitude of factors that promote unperturbed DNA replication, and protect, repair and restart damaged forks. Here we identify DONSON as a novel fork protection factor, and report biallelic DONSON mutations in 29 individuals with microcephalic dwarfism. We demonstrate that DONSON is a component of the replisome that stabilises forks during normal genome replication. Loss of DONSON leads to severe replication-associated DNA damage arising from nucleolytic cleavage of stalled replication forks. Furthermore, ATR-dependent signalling in response to replication stress is impaired in DONSON-deficient cells, resulting in decreased checkpoint activity, and potentiating chromosomal instability. Hypomorphic mutations substantially reduce DONSON protein levels and impair fork stability in patient cells, consistent with defective DNA replication underlying the disease phenotype. In summary, we identify mutations in DONSON as a common cause of microcephalic dwarfism, and establish DONSON as a critical replication fork protein required for mammalian DNA replication and genome stability.

  Study EGAS00001002224

• Human PMS1-dependent non-canonical mismatch repair converges with MBD4 to repair 5-methylcytosine deamination

  CpG dinucleotides are mutational hotspots due to spontaneous deamination of 5-methylcytosine (5mC), resulting in T:G mismatches that can lead to CpG>TpG transitions. These mutations are a hallmark of aging and cancer and play a central role in the evolution of vertebrate genomes. We have previously uncovered MBD4 as the primary Base Excision Repair (BER) glycosylase responsible for 5mC deamination repair. Here, we employ an APOBEC1 deaminase fused to a catalytically dead Cas9 to induce targeted 5mC deamination independently of DNA replication, and track its repair in human cells. This approach reveals that MBD4 elicits a coordinated repair response with a non-canonical branch of Mismatch Repair (MMR) involving complexes MutLβ (MLH1-PMS1) and MutSα (MSH2-MSH6). We demonstrate that human PMS1 loss phenocopies the CpG>TpG hypermutation associated with MBD4 deficiency, revealing 5mC deamination repair as one of its main functions. Structural predictions with functional validation reveal that MBD4 activity is dependent on its physical interaction with MutLβ. In alignment with our experimental data, we show that the CpG>TpG mutational burden of MMR-deficient tumors is partly explained by replication-independent processes. Altogether, we uncover a novel function of non-canonical MMR that underscores its interplay with BER in safeguarding genomic integrity against damage to methylated DNA.

  Study EGAS50000001662

• Comparison of the performance of two commercial genome-wide association study genotyping platforms in Han Chinese Samples

  Affymetrix 6.0, Illumina OMNIExpress, and llumina Immunochip genotype data for Han Chinese population including rheumatoid arthritis cases and controls. Data is in PLINK binary format. Illumina genotype clustering was performed using Illumina’s BeadStudio software. SNPs were reclustered using the study samples, low quality subjects were removed, and a subset of clustering results were manually inspected and verified. All SNPs with GenCall scores less than 0.15 were excluded. For Affymetrix chips, clustering was performed using the program Birdseed version 2, as implemented using Affymetrix Genotyper Console v4.0, using the default quality control (QC) thresholds.

  Study EGAS00000000131

• Carboxylesterase 1 mediates a distinctive metabolic profile of dendritic cells to attain an inflammatory phenotype

  The metabolic profile of dendritic cells (DCs) shapes their phenotype and functions. Carboxylestrase 1 (CES1) enzyme is highly expressed in mononuclear myeloid cells however its exact role in DCs is elusive. We used a CES1 inhibitor (WWL113) and genetic overexpression to explore the role of CES1 in DCs differentiation in inflammatory models. CES1 expression was analyzed during CD14+ monocytes differentiation to DCs (MoDCs) using quantitative PCR. CES1 Inhibitor (WWL113) was applied during MoDCs differentiation. Surface markers, secreted cytokines, lactic acid production, phagocytic and T cell polarization capacity were analyzed. Transcriptomic and metabolic profile were assessed with RNA-sequencing and mass spectrometry. Cellular respiration was assessed with seahorse respirometry. Transgenic mice were used to assess CES1 overexpression in DCs in inflammatory models. CES1 expression peaks early during MoDCs differentiation. Pharmacological inhibition of CES1 led to higher expression of CD209, CD86 and MHCII. WWL113 treated MoDCs secreted higher quantities of IL6, IL8, TNF and IL10 and demonstrated stronger phagocytic ability and higher capacity to polarize Th17 differentiation in autologous DCs-T cells co-culture model. Transcriptomic profiling revealed enrichment of multiple inflammatory and metabolic pathways. Functional metabolic analysis shows impaired maximal mitochondrial respiration capacity, increased lactate production and decreased intracellular amino acids and TCA intermediates. Transgenic human CES1 overexpression in murine DCs generated less inflammatory phenotype and increased resistance to T cell mediated colitis. In conclusion, CES1 inhibition directs DCs differentiation towards more inflammatory phenotype, that shows stronger phagocytic capacity and supports Th17 skewing. This is associated with disrupted mitochondrial respiration and amino acids depletion.

  Study EGAS50000000230

• 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

• Diet, Genetic Factors, and the Gut Microbiome in Crohn's Disease

  We investigate the hypothesis that consistent changes in the human gut microbiome are associated with Crohn's disease, a form of inflammatory bowel disease, and that altered microbiota contributes to pathogenesis. Analysis of this problem is greatly complicated by the fact that multiple factors influence the composition of the gut microbiota, including diet, host genotype, and disease state. For example, data from us and others document a drastic impact of diet on the composition of the gut microbiome. No amount of sequencing will yield a useful picture of the role of the microbiota in disease if samples are confounded with uncontrolled variables. We aim to characterize the composition of the gut microbiome while controlling for diet, host genotype, and disease state. Diet is controlled by analyzing children treated for Crohn's disease by placing them on a standardized elemental diet, and by testing effects of different diets on the gut microbiome composition in adult volunteers. Genotype is analyzed by large scale SNP genotyping, which is already underway and separately funded--team member Hakon Hakonarson is currently genotyping 50 children a week at ~half a million loci each and investigating connections with inflammatory bowel disease. Clinical status is ascertained in the very large IBD practice in the UPenn/CHOP hospital system. Effects of diet, host genotype, and disease state on the gut microbiome are summarized in a multivariate model, allowing connections between microbiome and disease to be assessed free of confounding factors. This project is divided into four sub-studies. In the Fecal Storage Methods (FSM) study, methods of stool storage and DNA extraction are compared to examine their impact on DNA sequence analysis results. The Controlled Feeding Experiment (CaFE) addresses the effects of controlled diets on the gut microbiome. In the Cross-sectional Study of Diet and Stool Microbiome Composition (COMBO), the effects of diet analyzed using surveys and deep sequencing of stool specimens. The fourth study, Pediatric Longitudinal Study of Elemental Diet and Stool Microbiome Composition (PLEASE), examines the effects of an elemental diet treatment on pediatric patients diagnosed with inflammatory bowel disease (IBD), particularly Crohn's disease. Fecal Storage Methods (FSM): Cross-sectional study Controlled Feeding Experiment (CaFE): Controlled trial Cross-sectional Study of Diet and Stool Microbiome Composition (COMBO): Cross-sectional study Pediatric Longitudinal Study of Elemental Diet and Stool Microbiome Composition (PLEASE): Longitudinal cohort study

  Study phs000252

• GENOMIC MUTATION LANDSCAPE OF SKIN CANCERS FROM DNA REPAIR-DEFICIENT XERODERMA PIGMENTOSUM PATIENTS

  Xeroderma pigmentosum (XP) is a genetic disorder caused by mutations in genes of the Nucleotide Excision Repair (NER) pathway (groups A-G) or in Translesion Synthesis (TLS) DNA polymerase η (group V). XP is associated with an increased skin cancer risk, reaching, for some groups, several thousand-fold compared to the general population. Here, we analyzed 38 skin cancer genomes from five XP groups. We found that the activity of NER determines heterogeneity of the mutation rates across skin cancer genomes and that transcription-coupled NER extends beyond the gene boundaries reducing the intergenic mutation rate. Mutational profile in XP-V tumors revealed the role of polymerase η in the error-free bypass of (i) rare TpG and TpA DNA lesions, (ii) 3’ nucleotides in pyrimidine dimers, and (iii) TpT photodimers. Our study unravels the genetic basis of skin cancer risk in XP and provides insights into the mechanisms reducing UV-induced mutagenesis in the general population.

  Study EGAS00001006732

• PSCP_bisulphite analysis in hESCs (2018-08-13)

  Many studies over the past 10 years, culminating in the recent report of the International Stem Cell Initiative (ISCI, 2011) have shown that hPSC acquire genetic and epigenetic changes during their time in culture. Many of the genetic changes are non-random and recurrent, probably because they provide a selective growth advantage to the undifferentiated cells. Some are shared by embryonal carcinoma cells, the malignant counterparts of ES cells. The origins of these growth advantages are poorly understood, but may come from altered cell cycle dynamics, resistance to apoptosis or altered patterns of differentiation. Less is known about the nature and consequences of epigenetic changes, but it is likely that these similarly affect hPSC behaviour; e.g., enhanced expression of DLK1, an imprinted gene, is associated with altered hPSC growth (Enver et al 2005). Inevitably, these genetic and epigenetic changes will impact on our ability to use hPSC for regenerative medicine, either because malignant transformation of the undifferentiated cells or their differentiated derivatives to be used for transplantation compromises safety, or because they impede the function of those differentiated derivatives, or because they affect the efficiency with which the undifferentiated cells can be expanded and differentiated into desired cell types. Focusing initially upon the existing clinical grade hESC lines, later moving to iPSC, we will Consolidate and extend knowledge of the rate, type and functional impact of the genetic variations that occur during hPSC culture. We will use whole genome and exome sequencing as well as SNP arrays, together with clonal analysis and other cytogenetics techniques. Common changes will be compared with those found in the normal human population, at low frequency in the original cell population or observed during iPSC generation in the HIPSCI project currently based at the WTSI. These studies will provide a better understanding of the range of genetic changes that occur in hPSC beyond the CNVs already identified. In conjunction with cancer genome resources and expertise at WTSI, bioinformatic analyses of these hPSC data will allow us to assess potential impact on hPSC behaviour pertinent to applications in regenerative medicine, notably the likelihood that specific changes arising in undifferentiated PSC cultures may be associated with potential malignant transformation of differentiated progeny. 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 2018-08-13.

  Dataset EGAD00001004295

• Spatiotemporal immune atlas of the first clinical-grade gene-edited pig-to-human kidney xenotransplant

  Pig-to-human xenotransplantation is rapidly approaching the clinical arena; however, it is unclear which immunomodulatory regimens will effectively control human immune responses to pig xenografts. We transplanted a gene-edited pig kidney into a brain-dead human recipient on pharmacologic immunosuppression and studied the human immune response to the xenograft using spatial transcriptomics and single-cell RNA sequencing. Human immune cells were uncommon in the porcine kidney cortex early after xenotransplantation and consisted of primarily myeloid cells. Both the porcine resident macrophages and human infiltrating macrophages expressed genes consistent with an alternatively activated, anti-inflammatory phenotype. No significant infiltration of human B or T cells into the porcine kidney xenograft was detected. Altogether, these findings provide proof of concept that conventional pharmacologic immunosuppression is sufficient to restrict infiltration of human immune cells into the xenograft early after compatible pig-to-human kidney xenotransplantation.

  Dataset EGAD50000000359

• L1 Retrotransposon Sequencing in Schizophrenia - Study 1

  Schizophrenia (SZ) is a devastating psychiatric disorder with substantial global clinical and economic implications. While SZ is marked by high heritability, discovery of common variants associated with even moderate risk for SZ has proven difficult. We used Restriction Enzyme Based Enriched L1 sequencing (REBELseq) to amplify L1 retrotransposons in gDNA isolated from dorsolateral prefrontal cortex NeuN+ neuronal nuclei from 63 SZ cases and 63 controls. Amplified libraries were sequenced on the Illumina HiSeq 4000 platform, and sequencing data was analyzed with the REBELseq bioinformatics pipeline.

  Study phs001968

• The Chromatin Landscape of Pathogenic Transcriptional Cell States in Rheumatoid Arthritis

  In this study, we characterized 24 rheumatoid arthritis (RA) synovial tissue chromatin classes (i.e., cell states defined by chromatin accessibility) across 5 cell types (T, B/plasma, myeloid, stromal, and endothelial). We also investigated the transcription factors that may regulate these chromatin classes, their connections to transcriptional cell states in a proposed superstate model, and their interplay with RA pathology through associations with histological parameters and risk variants.As part of the Accelerating Medicines Partnership (AMP) network, we obtained 18 synovial tissue samples from 14 RA and 4 osteoarthritis (OA) patients for this study. Samples were collected from 7 clinical sites. We performed a 10x single cell ATAC-seq experiment on each sample.We further collected synovial tissue samples from 11 RA patients and 1 OA patient from 2 clinical sites; each sample was used for a 10x single cell multimodal ATAC and Gene Expression experiment.For additional support of the proposed superstate model, we also collected peripheral blood mononuclear cells (PBMCs) from 4 RA patients, sorted for 4 populations (CD4+CD127-CD25hi Tregs, CD4+CD127-CD25int Tregs, CD4+CD25-PD1+CXCR5- TPH, CD4+CD25-PD1+CXCR5+ TFH), tagged each population with a hashing antibody, and pooled populations for one multimodal sequencing run.The FASTQ files are available for controlled access via dbGaP. Additional data can be found on Synapse.The presence of pooled subjects inflates the automatically-generated subject count; the actual consented subject count for this data is 34.

  Study phs003417

• Network-based systems pharmacology identifies heterogeneity in LCK and BCL2 signaling and differential vulnerability of T-cell acute lymphoblastic leukemia to targeted therapy

  T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematological malignancy, and novel therapeutics are much needed. Profiling patient leukemia’ drug sensitivities ex vivo, we discovered striking inter-patient variability in T-ALL response to a panel of targeted agents. Applying network-based systems pharmacology analyses, by integrating ex vivo pharmacotyping, bulk and single-cell RNA-seq, genomics, phospho-proteomics, and genome-wide CRISPR screening data, to examine signal circuitry, we identified the pharmacogenomic basis of T-ALL drug response and revealed a therapeutic vulnerability that is directly related to the developmental stage of leukemia cells. In conclusion, our results indicate that heterogeneity in the differentiation of T-ALL drives activation of key signaling pathways in this leukemia, providing unique opportunities for targeted therapy.

  Study EGAS00001004700

• Pathogenic Neurofibromatosis type 1 (NF1) RNA splicing resolved by targeted RNAseq

  Neurofibromatosis type 1 (NF1) is caused by loss-of-function variants in the NF1 gene. Approximately 10% of these variants affect RNA splicing and are either missed by conventional DNA diagnostics or are misinterpreted by in silico splicing predictions. Therefore, a targeted RNAseq-based approach was designed to detect pathogenic RNA splicing and associated pathogenic DNA variants. an in-house developed tool (QURNAS) was used to calculate the enrichment score (ERS) for each splicing event. RNA enrichment of NF1 and SPRED1 was done using SPET (NUGEN - NF1 only) and using SureSelect (Agilent - NF1 and SPRED1).

  Study EGAS00001005530

• CCR8-targeted specific depletion of clonally expanded Treg cells in tumor tissues evokes potent tumor immunity with long-lasting memory

  Foxp3-expressing CD25+CD4+ regulatory T cells (Tregs) are abundantly infiltrating into tumor tissues, hindering effective anti-tumor immunity. Here, assuming that such tumor Tregs were clonally expanding by recognizing tumor-associated antigens, we attempted to characterize them by their gene expression profiling and T-cell receptor (TCR) clonotyping at the single-cell level. We found that they predominantly expressed the chemokine receptor CCR8: ~40% of tumor Tregs, less than 10% of Tregs in other tissues, and few tumor-infiltrating conventional T cells expressed CCR8 in mice and humans. CCR8+ tumor Tregs were phenotypically highly differentiated and functionally stable. One injection of anti-CCR8 mAb with high antibody-dependent cellular cytotoxic activity was indeed able to specifically deplete clonally expanded tumor Tregs and thereby eradicate established tumors in mice. The depletion predominantly expanded tumor-infiltrating CD8+ effector T cells, which were different in activated or exhausted patterns from those seen after immune checkpoint blockade by anti-PD-1 mAb. The treatment also evoked potent secondary immune responses against the same tumor cell line inoculated several months after tumor eradication, indicating that the anti-CCR8-induced memory-type tumor-reactive effector T cells were, once induced, resistant to recovered Treg suppression. In contrast to such evocation of potent tumor immunity, anti-CCR8 treatment scarcely elicited discernable autoimmunity in mice, contrasting with a similar treatment for systemic whole Treg depletion, which induced histologically and serologically evident autoimmunity. Thus, temporary and specific depletion of clonally expanded Tregs in tumor tissues by cell-depleting anti-CCR8 mAb is sufficient to evoke potent tumor immunity with long-lasting memory and without serious autoimmunity.

  Study JGAS000312

• TTFields Glioblastoma Data Access Committee, Charité – Universitätsmedizin Berlin

  This Data Access Committee is responsible for reviewing and approving data access requests for genomic and associated clinical data from patients with glioblastoma, IDH wildtype, treated with surgery, standard chemoradiotherapy and Tumor Treating Fields at Charité – Universitätsmedizin Berlin. The DAC ensures that any data use is consistent with the patients’ informed consent, the study’s ethical approval and applicable data protection regulations. Approved applicants may use the data only for biomedical research on brain tumours and related methods, must not attempt re-identification of participants, and may not share the data with unauthorized third parties

  Dac EGAC50000000843

• Hereditary_Cerebellar_Ataxias___Whole_Genome_Sequencing___2021

  Looking to identify mutations in order to validate that lines we have classified as from Ataxia patients contain the disease relevant mutations. This will allow us to publish on the existance of these lines which are now commercially avalable. 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 EGAS00001006234

• Mucosal Melanoma Targeted Exome Sequencing Study (UCSF)

  Mucosal melanoma is a deadly disease that carries the worst prognosis amongst subtypes of melanoma. Like all melanomas, mucosal melanomas are frequently driven by activating mutations in the MAPK and/or PI3K pathways; however, unlike melanomas that arise on sun-exposed skin, mucosal melanomas harbor few point mutations. Instead, most somatic alterations involve structural alterations, which appear early during tumor progression. Molecular studies in mucosal melanoma generally only profile point mutations without interrogating copy number alterations, and pathogenic mutations are only found in 30% of cases. We sequenced 38 mucosal melanomas, and in addition to profiling point mutations, we looked for copy number alterations that amplify oncogenes or delete tumor suppressors.

  Study phs001594

• MINCR is a MYC-induced lncRNA able to modulate MYC’s transcriptional network in Burkitt lymphoma cells

  Despite the established role of the transcription factor MYC in cancer, little is known about the impact of a new class of transcriptional regulators, the long non-coding RNAs (lncRNAs), on the way MYC is able to influence cellular transcriptome. To this aim we have intersected RNA-sequencing data from two MYC-inducible cell lines and from a cohort of 91 mature B-cell lymphomas carrying, or not carrying, genetic variants resulting in MYC over-expression. By this approach, we identified 13 lncRNAs differentially expressed in IG-MYC-positive Burkitt lymphoma and regulated in the same direction by MYC in the model cell lines. Among them we focused on a lncRNA that we named MINCR, for MYC-Induced long Non-Coding RNA, showing a strong correlation with MYC expression in MYC-positive lymphomas and also in pancreatic ductal adenocarcinomas. To understand its cellular role we performed RNA interference (RNAi) experiments and found that MINCR knock-down is associated with a reduction in cellular viability, due to an impairment in cell cycle progression. Differential gene expression analysis following RNAi showed a strongly significant enrichment of cell cycle genes among the genes down-regulate following MINCR knock-down. Interestingly these genes are enriched in MYC binding sites in their promoters, suggesting that MINCR acts as a modulator of MYC transcriptional program. Accordingly, following MINCR knock-down, we observed a reduction in the binding of MYC to the promoters of selected cell cycle genes. Finally we provide evidences that down-regulation of AURKA, AURKB and CTD1 may explain the reduction in cellular proliferation observed upon MINCR knock-down. We therefore suggest that MINCR is a newly identified player in the MYC transcriptional network able to control the expression of cell cycle genes.

  Dataset EGAD00001001441

• Next Generation Sequencing to Predict Risk of Events from Coronary Artery Disease

  Coronary artery disease (CAD) and myocardial infarction (MI) remain the leading cause of death worldwide and in the US. In recent years, clinical studies that considered intermediate phenotypes (phenotypic or genomic data isolated between DNA and the main disease phenotype) have greatly enhanced our understanding of complex traits like CAD by enabling inference of biological networks from the combination of genetic and genomic datasets isolated from disease-relevant tissue(s). The NGS-PREDICT study used whole transcriptome sequence data generated from primary macrophages derived in vitro from venous blood that was obtained from CAD cases and non-CAD controls. This study provided a valuable resource for the validation of biomarkers identified in STARNET NGS data from macrophages obtained from patients with and without CAD. It also can be used as a reference dataset for the study of metabolic syndrome as well as other systemic inflammatory diseases.

  Study phs003883

• Revealing active mutational processes in tumours using DigiPico/MutLX at unprecedented accuracy

  Active mutational processes in a tumor result in genetic micro-heterogeneity that can determine the tumor’s evolutionary trajectory. Identification of these processes by studying micro-heterogeneity can unveil novel aspects of tumor evolution with potential therapeutic implications. Such studies, however, are inherently problematic because of the discovery of excessive false positive mutations. Here we report the optimization and validation of a robust whole genome sequencing and analysis pipeline (DigiPico/MutLX) that virtually eliminates false positive results. Using our method, we identified, for the first time, a sub-clonal local hyper-mutation (kataegis) event in a recurrent ovarian carcinoma, which was unidentifiable from the bulk WGS data of the same tumor. Overall, we propose DigiPico/MutLX method as a powerful framework for the reliable study of genetic micro-heterogeneity in tumor and normal tissues.

  Study EGAS00001003555

• Transcriptome (RNA-seq) data for the validation of the glioblastoma progression study (GBMatch).

  37 transcriptomes derived from fresh-frozen glioblastoma tumor samples. These transcriptomes have been produced for validation purposes and match the corresponding RRBS and WGS profiles in that DNA and RNA was extracted from the same tumor samples.

  Dataset EGAD00001004076

• Genomic (WGS) data for the validation of the glioblastoma progression study (GBMatch).

  43 low-coverage genomes derived from fresh-frozen glioblastoma tumor samples. These genomes have been produced for validation purposes and match the corresponding RRBS and RNA-seq profiles in that DNA and RNA was extracted from the same tumor samples.

  Dataset EGAD00001004077

• Molecular Biomarkers Predicting Lung Cancer Response Phenotypes

  We have used a "chemistry first" approach to discover druggable acquired vulnerabilities that arised in the pathogenesis of non-small cell lung cancer (NSCLC). We screened chemical libraries (~200,000 compounds) for chemical toxins that killed subsets of NSCLC but not normal human lung epithelial cells (HBECs). We first screened a panel of 12 NSCLC lines that represented a variety of known oncogenotypes and identified chemicals with large Z scores and appropriate properties including re-supply, chemistry, and reproducible drug response phenotypes. This was then narrowed down to a list of 202 chemicals and 18 drugs with known targeting (henceforth called "Precision Oncology Probe Set", or POPS). These, and a panel of 30 clinically available drugs, targeted therapies, and drug combinations, already in use or in trials for NSCLC treatment, were then tested on a panel of 96 NSCLC lines for their drug response phenotypes in 12-point dose response curves. This information was analyzed using scanning ranked KS (Kolmogorov-Smirnov) and elastic net biostatistics approaches to identify molecular biomarkers (mutations, mRNA expression, copy number variation, protein expression, and metabolomics) which could predict for sensitivity or resistance to a particular chemical toxin or treatment regimen. From this we have discovered that: our approach identifies already known molecular biomarker of drug sensitivities (e.g. EGFR mutations and EGFR TK inhibitors); many clinically available chemotherapy agents have molecular biomarkers predicting preclinical model drug responses; the POP set of chemical toxins provides novel drug response phenotype patterns in the large NSCLC panel different from those found with clinically available agents including a therapeutic window; many of the POP toxins only hit a small percentage (~5%) of the NSCLC panel but the POP set as a whole provides "coverage" of the entire NSCLC panel; there are simple, one or 2 component molecular biomarkers (mutations, mRNA expression) that predict responses to the different chemical toxins in the NSCLC panel; and that the molecular biomarkers provide some information on the targets and pathways involved in response to the chemical toxins. Thus, we have identified a group of chemical toxins with selectivity for subsets of NSCLC and associated tumor molecular biomarkers to facilitate their development for precision medicine, and also, in some cases, information on the targets and pathways interdicted by these chemical compounds. In addition, we have discovered NSCLC predictive biomarkers for clinically available agents.

  Study phs001823

• Identification of RNA biomarkers in Parkinson's disease iPSC-derived neuronal cells

  Parkinson?s disease (PD) is an age-related, chronic and progressive neurodegenerative disorder characterized by a loss of multifocal neurons and subsequent motor symptoms. These overt motor symptoms are often preceded by prodromal non-motor symptoms. Though a number of genetic and environmental factors have been identified to play a role in PD, more exact methods for both diagnosing and assessing prognosis are yet to be discovered. Probing the transcriptomes of control and PD cells can give some interesting insight into changes caused by the disease (in both coding and non-coding gene expression), highlighting potential RNA biomarkers that may be used for PD diagnosis and as new drug targets. The study consists of two main sources of data: matched neural stem cell (NSC) and fully differentiated dopaminergic neurons derived from iPS cells. Both sets of data are made up of three samples from a control cell line, and five samples carrying a mutation in one of several genes known to be linked to heritable PD: PARK2, PARK22 or PARK9. All transcriptome libraries were synthesized and sequenced using no-amplification non-tagging cap analysis of gene expression (nAnT-iCAGE) on the Illumina HiSeq 2500 platform. Resulting data was mapped to the human genome annotation (hg38) and processed CAGE tags were clustered ready for differential expression analyses. The 16 samples here described were sequenced across two lanes.

  Study JGAS000142

• Identification of RNA biomarkers in Parkinson's disease iPSC-derived neuronal cells

  Parkinson���s disease (PD) is an age-related, chronic and progressive neurodegenerative disorder characterized by a loss of multifocal neurons and subsequent motor symptoms. These overt motor symptoms are often preceded by prodromal non-motor symptoms. Though a number of genetic and environmental factors have been identified to play a role in PD, more exact methods for both diagnosing and assessing prognosis are yet to be discovered. Probing the transcriptomes of control and PD cells can give some interesting insight into changes caused by the disease (in both coding and non-coding gene expression), highlighting potential RNA biomarkers that may be used for PD diagnosis and as new drug targets. The study consists of two main sources of data: matched neural stem cell (NSC) and fully differentiated dopaminergic neurons derived from iPS cells. Both sets of data are made up of three samples from a control cell line, and five samples carrying a mutation in one of several genes known to be linked to heritable PD: PARK2, PARK22 or PARK9. All transcriptome libraries were synthesized and sequenced using no-amplification non-tagging cap analysis of gene expression (nAnT-iCAGE) on the Illumina HiSeq 2500 platform. Resulting data was mapped to the human genome annotation (hg38) and processed CAGE tags were clustered ready for differential expression analyses. The 16 samples here described were sequenced across two lanes.

  Study JGAS000318

• 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

• Healthy_ageing_thymus

  Single cell RNA sequencing of immune and non-immune cells from healthy ageing thymus Thymus is a primary lymphoid organ that creates an environment for the T lymphocyte precursors differentiation into the naive T cells, which involves TCR gene rearrangement, negative and positive selection. Despite thymus critical function for the recognition of the pathogens it starts to atrophy very early in life. Thymic Epithelial Space (TES), where thymocyte education occurs, starts to decline rapidly just after birth, while with the onset of puberty thymus is also progressively replaced with adipose tissue. This leads to a reduced naive T cell output,which decreases an organism's ability to recognize pathogens. In our lab, we have already collected and characterized cell type composition and gene regulatory networks of the fetal tand adult human thymus (Park et al, Science 2020). In the current project we plan to expand the number of paediatric and adult samples in the study with the aim to understand how the process of thymic involution happens. We will use single-cell transcriptomics to zoom on changes that occur in immune and non-immune cell types in different phases of thymic involution with the hope to understand which gene expression changes are causal for the thymic involution process and how naïve T cell production can be increased in elderly. 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 EGAS00001004311

• Deletion of FUNDC2 and CMC4 on chromosome Xq28 is sufficient to cause hypergonadotropic hypogonadism in men

  Hypergonadotropic hypogonadism (HH) is characterized by low sex steroid levels and secondarily elevated gonadotropin levels with either congenital or acquired etiology. Genetic factors leading to HH have yet to be fully elucidated. We submit genome and transcriptome data analyses from a male patient with HH and history of growth delay who has an inherited deletion of chromosome Xq28. Expression analyses were done for this patient and his unaffected family members, and compared to normal controls to identify dysregulated genes due to this deletion. Our patient's Xq28 deletion is 44,806 bp and contains only two genes, FUNDC2 and CMC4. Expressions of both FUNDC2 and CMC4 are completely abolished in the patient. Gene ontology analyses of differentially expressed genes in the patient in comparison to controls show that significantly up-regulated genes in the patient are enriched in Sertoli cell barrier regulation, apoptosis, inflammatory response and gonadotropin-releasing regulation. Indeed, our patient has an elevated FSH level, which regulates Sertoli cell proliferation and spermatogenesis. In his mother and sister, who are heterozygous for this deletion, X-chromosome inactivation is skewed towards the deleted X, suggesting a mechanism to avoid FSH dysregulation. Compared to the previously reported men with variable sized Xq28 deletions, our study suggests that the loss of function of FUNDC2 and/or CMC4 results in dysregulation of apoptosis, inflammation and FSH, and is sufficient to cause Xq28-associated HH.

  Study phs002234

• Variation in the Glucose Transporter gene SLC2A2 is associated with glycaemic response to metformin

  Metformin is the first-line antidiabetic drug with over 100 million users worldwide, yet its mechanism of action remains unclear1. Here the Metformin Genetics (MetGen) Consortium reports a three-stage genome wide association study (GWAS), consisting of 13,123 participants of different ancestries. The C-allele of rs8192675 in the intron of SLC2A2, which encodes the facilitated glucose transporter GLUT2, was associated with a 0.17% (p=6.6x10-14) greater metformin induced HbA1c reduction in 10,577 participants of European ancestry. rs8192675 is the top cis-eQTL for SLC2A2 in 1,226 human liver samples, suggesting a key role for hepatic GLUT2 in regulation of metformin action. In obese individuals C-allele homozygotes at rs8192675 had a 0.33% (3.6mmol/mol) greater absolute HbA1c reduction than T-allele homozygotes.This is about half the effect seen with the addition of a DPP-4 inhibitor, and equates to a dose difference of 550mg of metformin, suggesting rs8192675 as a potential biomarker for stratified medicine.

  Study EGAS00001001875

• L1-Seq and Genome-Wide SNP Genotyping in a Multiethnic Asian Population

  Insertions of the human-specific subfamily of LINE-1 (L1) retrotransposon are highly polymorphic across individuals and can critically influence the human transcriptome. We hypothesized that L1 insertions could represent genetic variants determining important human phenotypic traits, and performed an integrated analysis of L1 elements and single nucleotide polymorphisms (SNPs) in several human populations. We found that a large fraction of L1s were in high linkage disequilibrium (LD) with their surrounding genomic regions and that they were well-tagged by SNPs. However, L1 variants were only partially captured by SNPs on standard SNP arrays, so that their potential phenotypic impact would be frequently missed by SNP array-based genome-wide association studies. We next identified potential phenotypic effects of L1s by looking for signatures of natural selection linked to L1 insertions; significant extended haplotype homozygosity (EHH) was detected around several L1 insertions. This suggests that some of these L1 insertions may have been the target of recent positive selection.

  Study phs000732

• 'Targeted High Throughput Sequencing in Clinical Cancer Settings: Formaldehyde fixed-paraffin embedded (FFPE) tumor tissues, input amount and tumor heterogeneity'

  "Background: Massively parallel sequencing technologies have brought an enormous increase in sequencing throughput. However, these technologies need to be further improved with regard to reproducibility and applicability to clinical samples and settings. Methods: Using identification of genetic variations in prostate cancer as an example we address three crucial challenges in the field of targeted re-sequencing: Small nucleotide variation (SNV) detection in samples of formalin-fixed paraffin embedded (FFPE) tissue material, minimal amount of input sample and sampling in view of tissue heterogeneity.Results: We show that FFPE tissue material can supplement for fresh frozen tissues for the detection of SNVs and that solution-based enrichment experiments can be accomplished with small amounts of DNA with only minimal effects on enrichment uniformity and data variance. Finally, we address the question whether the heterogeneity of a tumor is reflected by different genetic alterations, e.g. different foci of a tumor display different genomic patterns. We show that the tumor heterogeneity plays an important role for the detection of copy number variations, but is of minor importance for the detection of somatic variations.Conclusions: The application of high throughput sequencing technologies in cancer genomics opens up a new dimension for the identification of disease mechanisms. In particular the ability to use small amounts of FFPE samples available from surgical tumor resections and histopathological examinations facilitates the collection of precious tissue materials. However, care needs to be taken in regard to the locations of the biopsies taken, which can have an influence on the prediction of copy number variations. Bearing these technological challenges in mind will significantly improve many large-scale sequencing studies and will - on a long-range - result in a more reliable prediction of individual cancer therapies."

  Study EGAS00001000136