64 research outputs found

    Big data in epilepsy: Clinical and research considerations. Report from the Epilepsy Big Data Task Force of the International League Against Epilepsy

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    Epilepsy is a heterogeneous condition with disparate etiologies and phenotypic and genotypic characteristics. Clinical and research aspects are accordingly varied, ranging from epidemiological to molecular, spanning clinical trials and outcomes, gene and drug discovery, imaging, electroencephalography, pathology, epilepsy surgery, digital technologies, and numerous others. Epilepsy data are collected in the terabytes and petabytes, pushing the limits of current capabilities. Modern computing firepower and advances in machine and deep learning, pioneered in other diseases, open up exciting possibilities for epilepsy too. However, without carefully designed approaches to acquiring, standardizing, curating, and making available such data, there is a risk of failure. Thus, careful construction of relevant ontologies, with intimate stakeholder inputs, provides the requisite scaffolding for more ambitious big data undertakings, such as an epilepsy data commons. In this review, we assess the clinical and research epilepsy landscapes in the big data arena, current challenges, and future directions, and make the case for a systematic approach to epilepsy big data

    Active medulloblastoma enhancers reveal subgroup-specific cellular origins

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    Medulloblastoma is a highly malignant paediatric brain tumour, often inflicting devastating consequences on the developing child. Genomic studies have revealed four distinct molecular subgroups with divergent biology and clinical behaviour. An understanding of the regulatory circuitry governing the transcriptional landscapes of medulloblastoma subgroups, and how this relates to their respective developmental origins, is lacking. Here, using H3K27ac and BRD4 chromatin immunoprecipitation followed by sequencing (ChIP-seq) coupled with tissue-matched DNA methylation and transcriptome data, we describe the active cis-regulatory landscape across 28 primary medulloblastoma specimens. Analysis of differentially regulated enhancers and super-enhancers reinforced inter-subgroup heterogeneity and revealed novel, clinically relevant insights into medulloblastoma biology. Computational reconstruction of core regulatory circuitry identified a master set of transcription factors, validated by ChIP-seq, that is responsible for subgroup divergence, and implicates candidate cells of origin for Group 4. Our integrated analysis of enhancer elements in a large series of primary tumour samples reveals insights into cis-regulatory architecture, unrecognized dependencies, and cellular origins

    TelomereHunter – in silico estimation of telomere content and composition from cancer genomes

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    Background: Establishment of telomere maintenance mechanisms is a universal step in tumor development to achieve replicative immortality. These processes leave molecular footprints in cancer genomes in the form of altered telomere content and aberrations in telomere composition. To retrieve these telomere characteristics from high-throughput sequencing data the available computational approaches need to be extended and optimized to fully exploit the information provided by large scale cancer genome data sets. Results: We here present TelomereHunter, a software for the detailed characterization of telomere maintenance mechanism footprints in the genome. The tool is implemented for the analysis of large cancer genome cohorts and provides a variety of diagnostic diagrams as well as machine-readable output for subsequent analysis. A novel key feature is the extraction of singleton telomere variant repeats, which improves the identification and subclassification of the alternative lengthening of telomeres phenotype. We find that whole genome sequencing-derived telomere content estimates strongly correlate with telomere qPCR measurements (r = 0.94). For the first time, we determine the correlation of in silico telomere content quantification from whole genome sequencing and whole genome bisulfite sequencing data derived from the same tumor sample (r = 0.78). An analogous comparison of whole exome sequencing data and whole genome sequencing data measured slightly lower correlation (r = 0.79). However, this is considerably improved by normalization with matched controls (r = 0.91). Conclusions: TelomereHunter provides new functionality for the analysis of the footprints of telomere maintenance mechanisms in cancer genomes. Besides whole genome sequencing, whole exome sequencing and whole genome bisulfite sequencing are suited for in silico telomere content quantification, especially if matched control samples are available. The software runs under a GPL license and is available at https://www.dkfz.de/en/applied-bioinformatics/telomerehunter/telomerehunter.html

    Human Disease-Drug Network Based on Genomic Expression Profiles

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    BACKGROUND: Drug repositioning offers the possibility of faster development times and reduced risks in drug discovery. With the rapid development of high-throughput technologies and ever-increasing accumulation of whole genome-level datasets, an increasing number of diseases and drugs can be comprehensively characterized by the changes they induce in gene expression, protein, metabolites and phenotypes. METHODOLOGY/PRINCIPAL FINDINGS: We performed a systematic, large-scale analysis of genomic expression profiles of human diseases and drugs to create a disease-drug network. A network of 170,027 significant interactions was extracted from the approximately 24.5 million comparisons between approximately 7,000 publicly available transcriptomic profiles. The network includes 645 disease-disease, 5,008 disease-drug, and 164,374 drug-drug relationships. At least 60% of the disease-disease pairs were in the same disease area as determined by the Medical Subject Headings (MeSH) disease classification tree. The remaining can drive a molecular level nosology by discovering relationships between seemingly unrelated diseases, such as a connection between bipolar disorder and hereditary spastic paraplegia, and a connection between actinic keratosis and cancer. Among the 5,008 disease-drug links, connections with negative scores suggest new indications for existing drugs, such as the use of some antimalaria drugs for Crohn's disease, and a variety of existing drugs for Huntington's disease; while the positive scoring connections can aid in drug side effect identification, such as tamoxifen's undesired carcinogenic property. From the approximately 37K drug-drug relationships, we discover relationships that aid in target and pathway deconvolution, such as 1) KCNMA1 as a potential molecular target of lobeline, and 2) both apoptotic DNA fragmentation and G2/M DNA damage checkpoint regulation as potential pathway targets of daunorubicin. CONCLUSIONS/SIGNIFICANCE: We have automatically generated thousands of disease and drug expression profiles using GEO datasets, and constructed a large scale disease-drug network for effective and efficient drug repositioning as well as drug target/pathway identification

    New Pharmacological Agents to Aid Smoking Cessation and Tobacco Harm Reduction: What has been Investigated and What is in the Pipeline?

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    A wide range of support is available to help smokers to quit and aid attempts at harm reduction, including three first-line smoking cessation medications: nicotine replacement therapy, varenicline and bupropion. Despite the efficacy of these, there is a continual need to diversify the range of medications so that the needs of tobacco users are met. This paper compares the first-line smoking cessation medications to: 1) two variants of these existing products: new galenic formulations of varenicline and novel nicotine delivery devices; and 2) twenty-four alternative products: cytisine (novel outside of central and eastern Europe), nortriptyline, other tricyclic antidepressants, electronic cigarettes, clonidine (an anxiolytic), other anxiolytics (e.g. buspirone), selective 5-hydroxytryptamine (5-HT) reuptake inhibitors, supplements (e.g. St John’s wort), silver acetate, nicobrevin, modafinil, venlafaxine, monoamine oxidase inhibitors (MAOI), opioid antagonist, nicotinic acetylcholine receptors (nAChR) antagonists, glucose tablets, selective cannabinoid type 1 receptor antagonists, nicotine vaccines, drugs that affect gamma-aminobutyric acid (GABA) transmission, drugs that affect N-methyl-D-aspartate receptors (NMDA), dopamine agonists (e.g. levodopa), pioglitazone (Actos; OMS405), noradrenaline reuptake inhibitors, and the weight management drug lorcaserin. Six criteria are used: relative efficacy, relative safety, relative cost, relative use (overall impact of effective medication use), relative scope (ability to serve new groups of patients), and relative ease of use (ESCUSE). Many of these products are in the early stages of clinical trials, however, cytisine looks most promising in having established efficacy and safety and being of low cost. Electronic cigarettes have become very popular, appear to be efficacious and are safer than smoking, but issues of continued dependence and possible harms need to be considered

    Pan-cancer analysis of whole genomes

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    Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

    Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

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    Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

    The mutational pattern of primary lymphoma of the central nervous system determined by whole-exome sequencing

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    To decipher the mutational pattern of primary CNS lymphoma (PCNSL), we performed whole-exome sequencing to a median coverage of 103 x followed by mutation verification in 9 PCNSL and validation using Sanger sequencing in 22 PCNSL. We identified a median of 202 (range: 139-251) potentially somatic single nucleotide variants (SNV) and 14 small indels (range: 7-22) with potentially protein-changing features per PCNSL. Mutations affected the B-cell receptor, toll-like receptor, and NF-kappa B and genes involved in chromatin structure and modifications, cell-cycle regulation, and immune recognition. A median of 22.2% (range: 20.0-24.7%) of somatic SNVs in 9 PCNSL overlaps with the RGYW motif targeted by somatic hypermutation (SHM); a median of 7.9% (range: 6.2-12.6%) affects its hotspot position suggesting a major impact of SHM on PCNSL pathogenesis. In addition to the well-known targets of aberrant SHM (aSHM) (PIM1), our data suggest new targets of aSHM (KLHL14, OSBPL10, and SUSD2). Among the four most frequently mutated genes was ODZ4 showing protein-changing mutations in 4/9 PCNSL. Together with mutations affecting CSMD2, CSMD3, and PTPRD, these findings may suggest that alterations in genes having a role in CNS development may facilitate diffuse large B-cell lymphoma manifestation in the CNS. This may point to intriguing mechanisms of CNS tropism in PCNSL
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