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      Whole-genome sequencing of bladder cancers reveals somatic CDKN1A mutations and clinicopathological associations with mutation burden

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          Abstract

          Bladder cancers are a leading cause of death from malignancy. Molecular markers might predict disease progression and behaviour more accurately than the available prognostic factors. Here we use whole-genome sequencing to identify somatic mutations and chromosomal changes in 14 bladder cancers of different grades and stages. As well as detecting the known bladder cancer driver mutations, we report the identification of recurrent protein-inactivating mutations in CDKN1A and FAT1. The former are not mutually exclusive with TP53 mutations or MDM2 amplification, showing that CDKN1A dysfunction is not simply an alternative mechanism for p53 pathway inactivation. We find strong positive associations between higher tumour stage/grade and greater clonal diversity, the number of somatic mutations and the burden of copy number changes. In principle, the identification of sub-clones with greater diversity and/or mutation burden within early-stage or low-grade tumours could identify lesions with a high risk of invasive progression.

          Abstract

          Bladder cancer is a complex genetic disease and a common cause of death due to malignancy. Here, the authors carry out whole-genome sequencing of 14 bladder cancers to characterize the genomic landscape of the disease and show that mutational burden is associated with tumour progression in these samples.

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          Most cited references17

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          Stampy: a statistical algorithm for sensitive and fast mapping of Illumina sequence reads.

          High-volume sequencing of DNA and RNA is now within reach of any research laboratory and is quickly becoming established as a key research tool. In many workflows, each of the short sequences ("reads") resulting from a sequencing run are first "mapped" (aligned) to a reference sequence to infer the read from which the genomic location derived, a challenging task because of the high data volumes and often large genomes. Existing read mapping software excel in either speed (e.g., BWA, Bowtie, ELAND) or sensitivity (e.g., Novoalign), but not in both. In addition, performance often deteriorates in the presence of sequence variation, particularly so for short insertions and deletions (indels). Here, we present a read mapper, Stampy, which uses a hybrid mapping algorithm and a detailed statistical model to achieve both speed and sensitivity, particularly when reads include sequence variation. This results in a higher useable sequence yield and improved accuracy compared to that of existing software.
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            Lost in transcription: p21 repression, mechanisms, and consequences.

            The cyclin-dependent kinase inhibitor p21WAF1/CIP1 is a major player in cell cycle control and it is mainly regulated at the transcriptional level. Whereas induction of p21 predominantly leads to cell cycle arrest, repression of p21 may have a variety of outcomes depending on the context. In this review, we concentrate on transcriptional repression of p21 by cellular and viral factors, and delve in detail into its possible biological implications and its role in cancer. It seems that the major mode of p21 transcriptional repression by negative regulators is the interference with positive transcription factors without direct binding to the p21 promoter. Specifically, the negative factors may either inhibit binding of positive regulators to the promoter or hinder their transcriptional activity. The ability of p21 to inhibit proliferation may contribute to its tumor suppressor function. Because of this, it is not surprising that a number of oncogenes repress p21 to promote cell growth and tumorigenesis. However, p21 is also an inhibitor of apoptosis and p21 repression may also have an anticancer effect. For example, c-Myc and chemical p21 inhibitors, which repress p21, sensitize tumor cells to apoptosis by anticancer drugs. Further identification of factors that repress p21 is likely to contribute to the better understanding of its role in cancer.
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              Whole-genome and whole-exome sequencing of bladder cancer identifies frequent alterations in genes involved in sister chromatid cohesion and segregation.

              Bladder cancer is one of the most common cancers worldwide, with transitional cell carcinoma (TCC) being the predominant form. Here we report a genomic analysis of TCC by both whole-genome and whole-exome sequencing of 99 individuals with TCC. Beyond confirming recurrent mutations in genes previously identified as being mutated in TCC, we identified additional altered genes and pathways that were implicated in TCC. Notably, we discovered frequent alterations in STAG2 and ESPL1, two genes involved in the sister chromatid cohesion and segregation (SCCS) process. Furthermore, we also detected a recurrent fusion involving FGFR3 and TACC3, another component of SCCS, by transcriptome sequencing of 42 DNA-sequenced tumors. Overall, 32 of the 99 tumors (32%) harbored genetic alterations in the SCCS process. Our analysis provides evidence that genetic alterations affecting the SCCS process may be involved in bladder tumorigenesis and identifies a new therapeutic possibility for bladder cancer.
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                Author and article information

                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Pub. Group
                2041-1723
                29 April 2014
                : 5
                : 3756
                Affiliations
                [1 ]Bioinformatics Group, University of Oxford , Old Road Campus Research Building, Oxford OX3 7DQ, UK
                [2 ]Cancer Research UK, Oxford Cancer Research Centre, University of Oxford , Old Road Campus Research Building, Oxford OX3 7DQ, UK
                [3 ]Botnar Research Centre, University of Oxford , Oxford OX3 7LD, UK
                [4 ]Nuffield Department of Surgical Sciences, University of Oxford , Old Road Campus Research Building, Oxford OX3 7DQ, UK
                [5 ]Gray Institute for Radiobiology and Oncology, Department of Oncology, University of Oxford , Old Road Campus Research Building, Oxford OX3 7DQ, UK
                [6 ]Bioinformatics and Statistical Genetics Core, Wellcome Trust Centre for Human Genetics , Oxford OX3 7BN, UK
                [7 ]Molecular and Population Genetics Laboratory, Wellcome Trust Centre for Human Genetics , Oxford OX3 7BN, UK
                [8 ]Yau Group, Wellcome Trust Centre for Human Genetics , Oxford OX3 7BN, UK
                [9 ]NIHR Comprehensive Biomedical Research Centre, Wellcome Trust Centre for Human Genetics , Oxford OX3 7BN, UK
                [10 ]Academic Urology Unit, University of Sheffield , Sheffield S10 2JF, UK
                [11 ]These authors contributed equally to this work
                [12 ]The Wellcome Trust Centre for Human Genetics , Roosevelt Drive, Oxford OX3 7BN, UK
                [13 ]Office of the Regius Professor of Medicine, Richard Doll Building , Roosevelt Drive, Oxford OX3 7LF, UK
                [14 ]Illumina Cambridge Ltd., Chesterford Research Park , Little Chesterford, Essex CB10 1XL, UK
                [15 ]NIHR Oxford Biomedical Research Centre , Oxford OX3 9DU, UK.
                [16 ]Weatherall Institute of Molecular Medicine, University of Oxford; John Radcliffe Hospital Headington , Oxford OX3 9DS, UK
                [17 ]Imperial College London, South Kensington Campus , London SW7 2AZ, UK
                Author notes
                [*]

                Lists of participants and their affiliations appear at the end of the paper.

                Article
                ncomms4756
                10.1038/ncomms4756
                4010643
                24777035
                57379445-58e7-484b-8bbf-7373fa72fbb5
                Copyright © 2014, Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.

                This work is licensed under a Creative Commons Attribution 3.0 Unported License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/

                History
                : 30 November 2013
                : 28 March 2014
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