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  • 1
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    The mutational landscape of lethal castration-resistant prostate cancer (2012)
    Nature Publishing Group (NPG)
    Details
    Publication Date: 2012-06-23
    Description: Characterization of the prostate cancer transcriptome and genome has identified chromosomal rearrangements and copy number gains and losses, including ETS gene family fusions, PTEN loss and androgen receptor (AR) amplification, which drive prostate cancer development and progression to lethal, metastatic castration-resistant prostate cancer (CRPC). However, less is known about the role of mutations. Here we sequenced the exomes of 50 lethal, heavily pre-treated metastatic CRPCs obtained at rapid autopsy (including three different foci from the same patient) and 11 treatment-naive, high-grade localized prostate cancers. We identified low overall mutation rates even in heavily treated CRPCs (2.00 per megabase) and confirmed the monoclonal origin of lethal CRPC. Integrating exome copy number analysis identified disruptions of CHD1 that define a subtype of ETS gene family fusion-negative prostate cancer. Similarly, we demonstrate that ETS2, which is deleted in approximately one-third of CRPCs (commonly through TMPRSS2:ERG fusions), is also deregulated through mutation. Furthermore, we identified recurrent mutations in multiple chromatin- and histone-modifying genes, including MLL2 (mutated in 8.6% of prostate cancers), and demonstrate interaction of the MLL complex with the AR, which is required for AR-mediated signalling. We also identified novel recurrent mutations in the AR collaborating factor FOXA1, which is mutated in 5 of 147 (3.4%) prostate cancers (both untreated localized prostate cancer and CRPC), and showed that mutated FOXA1 represses androgen signalling and increases tumour growth. Proteins that physically interact with the AR, such as the ERG gene fusion product, FOXA1, MLL2, UTX (also known as KDM6A) and ASXL1 were found to be mutated in CRPC. In summary, we describe the mutational landscape of a heavily treated metastatic cancer, identify novel mechanisms of AR signalling deregulated in prostate cancer, and prioritize candidates for future study.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3396711/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3396711/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Grasso, Catherine S -- Wu, Yi-Mi -- Robinson, Dan R -- Cao, Xuhong -- Dhanasekaran, Saravana M -- Khan, Amjad P -- Quist, Michael J -- Jing, Xiaojun -- Lonigro, Robert J -- Brenner, J Chad -- Asangani, Irfan A -- Ateeq, Bushra -- Chun, Sang Y -- Siddiqui, Javed -- Sam, Lee -- Anstett, Matt -- Mehra, Rohit -- Prensner, John R -- Palanisamy, Nallasivam -- Ryslik, Gregory A -- Vandin, Fabio -- Raphael, Benjamin J -- Kunju, Lakshmi P -- Rhodes, Daniel R -- Pienta, Kenneth J -- Chinnaiyan, Arul M -- Tomlins, Scott A -- P50 CA069568/CA/NCI NIH HHS/ -- P50 CA069568-14/CA/NCI NIH HHS/ -- P50 CA69568/CA/NCI NIH HHS/ -- R01 CA132874/CA/NCI NIH HHS/ -- R01 CA132874-05/CA/NCI NIH HHS/ -- R01CA13287/CA/NCI NIH HHS/ -- T32 CA009676/CA/NCI NIH HHS/ -- T32 CA140044/CA/NCI NIH HHS/ -- U01 CA111275/CA/NCI NIH HHS/ -- U01 CA111275-08/CA/NCI NIH HHS/ -- U01 CA113913/CA/NCI NIH HHS/ -- U01 CA113913-03/CA/NCI NIH HHS/ -- Howard Hughes Medical Institute/ -- England -- Nature. 2012 Jul 12;487(7406):239-43. doi: 10.1038/nature11125.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Michigan Center for Translational Pathology, University of Michigan Medical School, Ann Arbor, Michigan 48109, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/22722839" target="_blank"〉PubMed〈/a〉
    Keywords: Cell Proliferation ; Cells, Cultured ; Hepatocyte Nuclear Factor 3-alpha/genetics ; Humans ; Male ; Molecular Sequence Data ; Mutation ; Orchiectomy ; Prostatic Neoplasms/*genetics/pathology ; Receptors, Androgen/metabolism ; Sequence Alignment ; Signal Transduction
    Print ISSN: 0028-0836
    Electronic ISSN: 1476-4687
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
    Published by Nature Publishing Group (NPG)
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  • 2
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    Methods and challenges in timing chromosomal abnormalities within cancer samples (2013)
    Oxford University Press
    Details
    Publication Date: 2013-11-29
    Description: Motivation: Tumors acquire many chromosomal amplifications, and those acquired early in the lifespan of the tumor may be not only important for tumor growth but also can be used for diagnostic purposes. Many methods infer the order of the accumulation of abnormalities based on their occurrence in a large cohort of patients. Recently, Durinck et al. (2011) and Greenman et al. (2012) developed methods to order a single tumor’s chromosomal amplifications based on the patterns of mutations accumulated within those regions. This method offers an unprecedented opportunity to assess the etiology of a single tumor sample, but has not been widely evaluated. Results: We show that the model for timing chromosomal amplifications is limited in scope, particularly for regions with high levels of amplification. We also show that the estimation of the order of events can be sensitive for events that occur early in the progression of the tumor and that the partial maximum likelihood method of Greenman et al. (2012) can give biased estimates, particularly for moderate read coverage or normal contamination. We propose a maximum-likelihood estimation procedure that fully accounts for sequencing variability and show that it outperforms the partial maximum-likelihood estimation method. We also propose a Bayesian estimation procedure that stabilizes the estimates in certain settings. We implement these methods on a small number of ovarian tumors, and the results suggest possible differences in how the tumors acquired amplifications. Availability and implementation: We provide implementation of these methods in an R package cancerTiming , which is available from the Comprehensive R Archive Network (CRAN) at http://CRAN.R-project.org/ . Contact: epurdom@stat.Berkeley.edu Supplementary information: Supplementary data are available at Bioinformatics online.
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
    Published by Oxford University Press
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  • 3
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    FOXA1 alters ER and IL-8 in endocrine resistance [Cell Biology] (2016)
    National Academy of Sciences
    Details
    Publication Date: 2016-10-26
    Description: Forkhead box protein A1 (FOXA1) is a pioneer factor of estrogen receptor α (ER)–chromatin binding and function, yet its aberration in endocrine-resistant (Endo-R) breast cancer is unknown. Here, we report preclinical evidence for a role of FOXA1 in Endo-R breast cancer as well as evidence for its clinical significance. FOXA1...
    Print ISSN: 0027-8424
    Electronic ISSN: 1091-6490
    Topics: Biology , Medicine , Natural Sciences in General
    Published by National Academy of Sciences
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