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      Whole-genome sequencing of human malignant mesothelioma tumours and cell lines

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          Abstract

          Pleural mesothelioma is a cancer of serosal surfaces caused by environmental exposure to asbestos. Clinical outcome remains poor and while trials of new treatments are ongoing it remains an understudied cancer. Mesothelioma cell lines can readily be grown from primary tumour and from tumour cells shed into pleural effusion with the latter representing a particularly valuable source of DNA in clinical settings, procurable without the need for additional invasive procedures. However, it is not well understood how accurately patient-derived cultured tumour cells represent the molecular characteristics of their primary tumour. We used whole-genome sequencing of primary tumour and matched cultured cells to comprehensively characterize mutations and structural alterations. Most cases had complex rearranged genomes with evidence of chromoanagenesis and rearrangements reminiscent of chromoplexy. Many of the identified driver mutations were structural, indicating that mesothelioma is often caused by structural alterations and catastrophic genomic events, rather than point mutations. Because the majority of genomic changes detected in tumours were also displayed by the genomes of cultured tumour cells, we conclude that low-passage cultured tumour cells are generally suitable for molecular characterization of mesothelioma and may be particularly useful where tissue samples with high tumour cell content are not available. However, the subclonal compositions of the cell lines did not fully recapitulate the subclonal diversity of the primary tumours. Furthermore, longitudinal acquisition of major alterations in subclonal cell populations was observed after long-term passaging. These two factors define limitations of tumour-derived cell lines as genomic substrate for clinical purposes.

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          Most cited references47

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          The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface combined with customized data storage enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes. The portal provides graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and software programmatic access. The intuitive Web interface of the portal makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries. Here, we provide a practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics.
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            The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data.

            Next-generation DNA sequencing (NGS) projects, such as the 1000 Genomes Project, are already revolutionizing our understanding of genetic variation among individuals. However, the massive data sets generated by NGS--the 1000 Genome pilot alone includes nearly five terabases--make writing feature-rich, efficient, and robust analysis tools difficult for even computationally sophisticated individuals. Indeed, many professionals are limited in the scope and the ease with which they can answer scientific questions by the complexity of accessing and manipulating the data produced by these machines. Here, we discuss our Genome Analysis Toolkit (GATK), a structured programming framework designed to ease the development of efficient and robust analysis tools for next-generation DNA sequencers using the functional programming philosophy of MapReduce. The GATK provides a small but rich set of data access patterns that encompass the majority of analysis tool needs. Separating specific analysis calculations from common data management infrastructure enables us to optimize the GATK framework for correctness, stability, and CPU and memory efficiency and to enable distributed and shared memory parallelization. We highlight the capabilities of the GATK by describing the implementation and application of robust, scale-tolerant tools like coverage calculators and single nucleotide polymorphism (SNP) calling. We conclude that the GATK programming framework enables developers and analysts to quickly and easily write efficient and robust NGS tools, many of which have already been incorporated into large-scale sequencing projects like the 1000 Genomes Project and The Cancer Genome Atlas.
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              The cBio Cancer Genomics Portal (http://cbioportal.org) is an open-access resource for interactive exploration of multidimensional cancer genomics data sets, currently providing access to data from more than 5,000 tumor samples from 20 cancer studies. The cBio Cancer Genomics Portal significantly lowers the barriers between complex genomic data and cancer researchers who want rapid, intuitive, and high-quality access to molecular profiles and clinical attributes from large-scale cancer genomics projects and empowers researchers to translate these rich data sets into biologic insights and clinical applications. © 2012 AACR.
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                Author and article information

                Contributors
                Journal
                Carcinogenesis
                Oxford University Press (OUP)
                0143-3334
                1460-2180
                June 2019
                July 06 2019
                April 25 2019
                June 2019
                July 06 2019
                April 25 2019
                : 40
                : 6
                : 724-734
                Affiliations
                [1 ]Diamantina Institute, Faculty of Medicine, Translational Research Institute, The University of Queensland, Brisbane, Australia
                [2 ]Thoracic Research Centre, Faculty of Medicine, The University of Queensland, Queensland, Australia
                [3 ]Department of Anatomical Pathology, The Prince Charles Hospital, Queensland, Australia
                [4 ]Department of Thoracic Medicine, The Prince Charles Hospital, Queensland, Australia
                [5 ]Institute of Health and Biomedical Innovation, School of Biomedical Sciences, Queensland University of Technology (QUT) at Translational Research Institute, Brisbane, Australia
                Article
                10.1093/carcin/bgz066
                31038674
                e93b07f4-58e5-45b6-9944-a5f32645a59c
                © 2019

                https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model

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