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      A sequence-based survey of the complex structural organization of tumor genomes

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          Abstract

          Tumors and cancer cell lines were surveyed with end-sequencing profiling, yielding the largest available collection of sequence-ready tumor genome breakpoints and providing evidence that some rearrangements may be recurrent.

          Abstract

          Background

          The genomes of many epithelial tumors exhibit extensive chromosomal rearrangements. All classes of genome rearrangements can be identified using end sequencing profiling, which relies on paired-end sequencing of cloned tumor genomes.

          Results

          In the present study brain, breast, ovary, and prostate tumors, along with three breast cancer cell lines, were surveyed using end sequencing profiling, yielding the largest available collection of sequence-ready tumor genome breakpoints and providing evidence that some rearrangements may be recurrent. Sequencing and fluorescence in situ hybridization confirmed translocations and complex tumor genome structures that include co-amplification and packaging of disparate genomic loci with associated molecular heterogeneity. Comparison of the tumor genomes suggests recurrent rearrangements. Some are likely to be novel structural polymorphisms, whereas others may be bona fide somatic rearrangements. A recurrent fusion transcript in breast tumors and a constitutional fusion transcript resulting from a segmental duplication were identified. Analysis of end sequences for single nucleotide polymorphisms revealed candidate somatic mutations and an elevated rate of novel single nucleotide polymorphisms in an ovarian tumor.

          Conclusion

          These results suggest that the genomes of many epithelial tumors may be far more dynamic and complex than was previously appreciated and that genomic fusions, including fusion transcripts and proteins, may be common, possibly yielding tumor-specific biomarkers and therapeutic targets.

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          Most cited references49

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          DAVID: Database for Annotation, Visualization, and Integrated Discovery.

          Functional annotation of differentially expressed genes is a necessary and critical step in the analysis of microarray data. The distributed nature of biological knowledge frequently requires researchers to navigate through numerous web-accessible databases gathering information one gene at a time. A more judicious approach is to provide query-based access to an integrated database that disseminates biologically rich information across large datasets and displays graphic summaries of functional information. Database for Annotation, Visualization, and Integrated Discovery (DAVID; http://www.david.niaid.nih.gov) addresses this need via four web-based analysis modules: 1) Annotation Tool - rapidly appends descriptive data from several public databases to lists of genes; 2) GoCharts - assigns genes to Gene Ontology functional categories based on user selected classifications and term specificity level; 3) KeggCharts - assigns genes to KEGG metabolic processes and enables users to view genes in the context of biochemical pathway maps; and 4) DomainCharts - groups genes according to PFAM conserved protein domains. Analysis results and graphical displays remain dynamically linked to primary data and external data repositories, thereby furnishing in-depth as well as broad-based data coverage. The functionality provided by DAVID accelerates the analysis of genome-scale datasets by facilitating the transition from data collection to biological meaning.
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            Patterns of somatic mutation in human cancer genomes.

            Cancers arise owing to mutations in a subset of genes that confer growth advantage. The availability of the human genome sequence led us to propose that systematic resequencing of cancer genomes for mutations would lead to the discovery of many additional cancer genes. Here we report more than 1,000 somatic mutations found in 274 megabases (Mb) of DNA corresponding to the coding exons of 518 protein kinase genes in 210 diverse human cancers. There was substantial variation in the number and pattern of mutations in individual cancers reflecting different exposures, DNA repair defects and cellular origins. Most somatic mutations are likely to be 'passengers' that do not contribute to oncogenesis. However, there was evidence for 'driver' mutations contributing to the development of the cancers studied in approximately 120 genes. Systematic sequencing of cancer genomes therefore reveals the evolutionary diversity of cancers and implicates a larger repertoire of cancer genes than previously anticipated.
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              Structural variation in the human genome.

              The first wave of information from the analysis of the human genome revealed SNPs to be the main source of genetic and phenotypic human variation. However, the advent of genome-scanning technologies has now uncovered an unexpectedly large extent of what we term 'structural variation' in the human genome. This comprises microscopic and, more commonly, submicroscopic variants, which include deletions, duplications and large-scale copy-number variants - collectively termed copy-number variants or copy-number polymorphisms - as well as insertions, inversions and translocations. Rapidly accumulating evidence indicates that structural variants can comprise millions of nucleotides of heterogeneity within every genome, and are likely to make an important contribution to human diversity and disease susceptibility.
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                Author and article information

                Journal
                Genome Biol
                Genome Biology
                BioMed Central
                1465-6906
                1465-6914
                2008
                25 March 2008
                : 9
                : 3
                : R59
                Affiliations
                [1 ]Department of Computer Science & Center for Computational Molecular Biology, Brown University, Waterman Street, Providence, RI 02912-1910, USA
                [2 ]Cancer Research Institute, UCSF Comprehensive Cancer Center, Sutter Street, San Francisco, CA 94115, USA
                [3 ]Chinese National Human Genome Center, North Yongchang Road, BDA, Beijing, P.R.C. 100016
                [4 ]Shandong Provincial Hospital, JingWuWeiQi Road, Jinan, P.R.C. 250021
                [5 ]Division of Human Biology, Fred Hutchinson Cancer Research Center, Fairview Avenue N, Seattle, WA 98109, USA
                [6 ]The University of Michigan, Departments of Internal Medicine and Urology, E Medical Center Drive, Ann Arbor, MI 48109-0330, USA
                [7 ]MD Anderson Cancer Center, University of Texas, Holcombe Blvd, Houston, TX 77030, USA
                [8 ]Amplicon Express, NE Eastgate Blvd, Pullman, WA 99163, USA
                [9 ]BioMedical Informatics Program, Stanford University, Stanford, CA 94305, USA
                [10 ]Bioinformatics Program, University of California, San Diego, Gilman Drive, La Jolla, CA 92093, USA
                [11 ]Lawrence Berkeley National Laboratory, Life Sciences Division, Cyclotron Road, Berkeley, CA 94720-8268, USA
                [12 ]Lawrence Berkeley National Laboratory, Genomics Division and Joint Genome Institute, Cyclotron Road, Berkeley, CA 94720, USA
                [13 ]BACPAC Resources Children's Hospital Oakland, 52nd Street, Oakland, CA 94609, USA
                [14 ]Section of Cancer Genomics, Genetics Branch, Center for Cancer Research, South Drive, Bldg. 50, MSC-8010, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
                Article
                gb-2008-9-3-r59
                10.1186/gb-2008-9-3-r59
                2397511
                18364049
                3cd71a21-b8d7-42eb-8f00-31c405b9a14e
                Copyright © 2008 Raphael et al.; licensee BioMed Central Ltd.

                This is an open access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 9 October 2007
                : 20 February 2008
                : 25 March 2008
                Categories
                Research

                Genetics
                Genetics

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