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• Conserved features of TERT promoter duplications reveal an activation mechanism that mimics hotspot mutations in cancer

  Mutations in the TERT promoter are the single most common non-coding mutation in cancer and represent the genetic underpinnings of tumor cell immortality. Beyond the two most common point mutations, G228A and G250A, which selectively recruit the ETS factor GABP to activate TERT, the significance of other variants in the TERT promoter are unknown. We identified duplications of wildtype sequence within the core promoter region of TERT in 7 different cancer types that have strikingly similar features including size, insertion position, and inclusion of one of the native ETS motifs. Each duplication activates the TERT promoter to a similar level as G228A and G250A and is critically dependent on the insertion site. The GABP tetramer binds to the TERT duplicated promoter sequence by virtue of the native ETS motif and its duplicated version with precise spacing, and it is necessary for the transcriptional activation by all duplications tested. Spatiotemporal analysis in a multifocal glioblastoma shows the duplication is clonal and its activation of TERT is readily detectable at the single cell level and in bulk tumor tissue. We conclude that recurrent TERT promoter duplications of the native ETS sequence are functionally and mechanistically equivalent to the hotspot mutations that confer tumor cell immortality. The shared mechanism of these divergent somatic genetic alterations suggests a strong selective pressure for recruitment of the GABP tetramer to activate TERT.

  Study EGAS00001006118

• Whole-genome sequencing of normal Singaporean volunteers

  Sleep is associated with various health outcomes. Despite their growing adoption, the potential for consumer wearables to contribute sleep metrics to sleep-related biomedical research remains largely uncharacterized. Here we analyzed sleep tracking data, along with questionnaire responses and multi-modal phenotypic data generated from 482 normal volunteers. First, we compared wearable-derived and self-reported sleep metrics, particularly total sleep time (TST) and sleep efficiency (SE). We then identified demographic, socioeconomic and lifestyle factors associated with wearable-derived TST. Among others, male gender (β = -15.539, 95% confidence interval [CI] = -26.245 - -4.832, p = 0.005), older age (β = -0.493, CI = -0.941 - -0.044, p = 0.032) and manual labor (β = -26.856, CI = -49.715 - -3.997, p = 0.022) were associated with reduced TST, whereas alcohol consumption (β = 19.247, CI = 8.008 - 30.486, p = 8.54x10-04) was associated with increased TST. Multi-modal phenotypic data analysis showed that wearable-derived TST and SE were associated with various cardiovascular disease risk markers such as body mass index (β = -0.006, CI = -0.00 - -0.000, p = 0.040) and waist circumference (β = 0.001, CI = -0.015-0.017, p = 0.893), whereas self-reported measures were not. We then showed that insufficient sleep was associated with premature telomere attrition, using telomere length estimated using whole-genome sequencing (β = 1.275, CI = 0.187 - 2.363, p = 0.023) and quantitative PCR (β = 0.001, CI = 8.318x10-05 - 0.001, p = 0.028). Our study highlights the potential for sleep metrics from consumer wearables to provide novel insights into data generated from population cohort studies.

  Study EGAS00001004007

• Bibliography Statistics

  EGA Statistics Bibliography Growth Community Archive Distribution Catalogue Here we expose in a yearly and cumulative manner, the publications, citations, publishers journals and impact factor of EGA related studies. Publications citing data stored at the EGA The studies that use EGA datasets are requested to cite the EGA into their bibliography. This fact allows for a faster spreading of the role and purpose of the EGA, being the availability of their studies for testability and reusability purposes. In order to track the studies we use the unique study accession, provided by the EGA when submitting a new study, and comprised of the keyword EGAS followed by 11 digits such as EGAS00000000001. We use the Europe PMC RESTful Web Service in order to query, and index studies where the EGAS accession was used. Below, you can find a chart showing the journal publishers of the studies citing data stored in the EGA being cited: Publications Citing Data Stored in the EGA pieChart('publishers-citations', 'https://stats.ega-archive.org/publishers/citations', 'Publishers') Number of publications citing data stored in the EGA by year Here, you can find a chart showing the number of publications citing data stored in the EGA by year. These publications could have deposit, or re-used the data. The study acession can be found in the publication. The default values are non-cumulative. You can see cumulative values by clicking "Cumulative". Number of Publications Citing Data Stored in the EGA by Year barChart('publications-by-year', 'https://stats.ega-archive.org/publications/year', ['Number of Publications by Year', 'Publications by Year']) Journal Impact Factor of Publications Citing Data Stored in the EGA Here, you can find a chart showing the journal impact factor of publications citing data stored in the EGA. We have used Scimago Journal Rank for this purpose. Low impact treshold was defined between 0.0 and 5.0 excluding; Medium impact treshold was defined between 5.0 and 10.0 excluding; High impact range was established from values equal to or higher than 10.0; Journal Impact Factor of Publications Citing Data Stored in the EGA pieChart('citations-publication-impact-factor', 'https://stats.ega-archive.org/citations/publication/impact/factor', 'Publication Impact Factor') Publications citing a publication containing a EGA study accession The publications, stating a EGA study accession in the bibliography, can be cited for testibility or reusability purposes. Below, you can find a chart showing the publishers of the publications being cited: Publications Citing a Publication Containing a EGA Study Accession pieChart('publications-citations', 'https://stats.ega-archive.org/publications/citations', 'Publishers') Number of publications citing a publication containing a EGA study accession by year Here, you can find a chart showing the number of publications citing a publication containing a EGA study accession by year by year. The values are non-cumulative: Number of published citations by year barChart('citations-year', 'https://stats.ega-archive.org/citations/year', ['Number of Publications', 'Citations by Year'])

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• WTCCC3 case-control study for Primary Biliary Cirrhosis

  Genome-wide association scan was performed in 1,840 cases of primary biliary cirrhosis and 5,163 controls. Replication of new associations was tested in an independent set of 620 cases and 2,514 controls.

  Study EGAS00000000039

• Mutational processes moulding the genomes of 21 breast cancers

  The expression data for this study can be found here: http://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-1088/and its SNP6 data can be found here:http://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-1087/

  Dataset EGAD00001000138

• UK10K_COHORT_ALSPAC REL-2011-12-01

  For information about this sample set, please contact the sample custodian Nic Timpson: N.J.Timpson@bristol.ac.uk

  Dataset EGAD00001000195

• AML_controls

  Blastic plasmacytoid dendritic cell neoplasm (BPDCN) is a rare hematologic malignancy that is most similar in expression profiles to plasmacytoid dendritic cells. However, patients often exhibit features of AML and can progress to AML. In this project, we will determine the differentially and commonly expressed genes between BPDCN and AML specimens. Available BPDCN and TET2-mutated AML specimens were taken for transcriptome microarray analysis.

  Dataset EGAD00010001726

• genotyped_bacterial_meningitis

  This study includes 1146 samples of host genotyping data (genotyped) from Illumina Omni arrays. Samples were collected from adults (>16 yrs) patients with CSF confirmed bacterial meningitis in the Netherlands between 2006 and 2015. Metadata includes patient outcome, species of bacteria, and for 467 samples a link to an ENA run with the associated bacterial genome (S. pneumoniae only).

  Dataset EGAD00010002328

• Liquid biopsy for molecular characterization of diffuse large B-cell lymphoma and early assessment of minimal residual disease

  Genomic data from Diffuse-large B-cell lymphomas at diagnosis and during the treatment. The processed samples were : -Circulating tumor DNA: at diagnosis and after2-cycles of treatment. -Tumour lymph node at diagnosis -Genomic DNA

  Dataset EGAD50000000310

• A model for predicting response to PD-1 inhibitors in NSCLC

  Whole exome sequencing was used to examine the impact of human leukocyte antigen B44 in a non-small cell lung cancer cohort treated with single agent pembrolizumab with over five years of follow-up.

  Study phs002244