19 research outputs found

    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

    Primary immunodeficiencies associated with eosinophilia

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    Electrostatic interactions govern extreme nascent protein ejection times from ribosomes and can delay ribosome recycling

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    The ejection of nascent proteins out of the ribosome exit tunnel, after their covalent bond to transfer-RNA has been broken, has not been experimentally studied due to challenges in sample preparation. Here, we investigate this process using a combination of multiscale modeling, ribosome profiling, and gene ontology analyses. Simulating the ejection of a representative set of 122 E. coli proteins we find a greater than 1000-fold variation in ejection times. Nascent proteins enriched in negatively charged residues near their C-terminus eject the fastest, while nascent chains enriched in positively charged residues tend to eject much more slowly. More work is required to pull slowly ejecting proteins out of the exit tunnel than quickly ejecting proteins, according to all-atom simulations. An energetic decomposition reveals, for slowly ejecting proteins, that this is due to the strong attractive electrostatic interactions between the nascent chain and the negatively charged ribosomal-RNA lining the exit tunnel, and for quickly ejecting proteins, it is due to their repulsive electrostatic interactions with the exit tunnel. Ribosome profiling data from E. coli reveals that the presence of slowly ejecting sequences correlates with ribosomes spending more time at stop codons, indicating that the ejection process might delay ribosome recycling. Proteins that have the highest positive charge density at their C-terminus are overwhelmingly ribosomal proteins, suggesting the possibility that this sequence feature may aid in the cotranslational assembly of ribosomes by delaying the release of nascent ribosomal proteins into the cytosol. Thus, nascent chain ejection times from the ribosome can vary greatly between proteins due to differential electrostatic interactions, can influence ribosome recycling, and could be particularly relevant to the synthesis and cotranslational behavior of some proteins

    Vulnerabilities in Fog/Edge Computing from Architectural Perspectives

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    Recently, the emerging IoTization paradigm generates a tremendous amount of heterogeneous data offloaded from digital devices to networks. The heterogeneity of these big IoT data requires the networks to expand their computational capability from the cloud to the edge, realizing a new fog/edge computing (FEC) system. The FEC system provides multiple satisfactory levels in terms of performance, latency, security, etc. to user devices according to service demands. Because the FEC system is in between the cloud and user devices, this supplemental part introduces several vulnerabilities on both north and south interfaces as well as among internal FEC components. This chapter analyzes open security and privacy issues in FEC from architectural perspectives. First, a comprehensive overview of computational cloudization is presented, which leads to a hierarchical computing architecture in the network. From that, vulnerabilities within each architectural model, such as intrinsic FEC, the standard reference FEC architecture, FEC virtualization, and FEC integration into the 5G network, are discussed in detail. Finally, we summarize the chapter in the last section
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