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      The androgen receptor cistrome is extensively reprogrammed in human prostate tumorigenesis

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          Abstract

          Master transcription factors interact with DNA to establish cell-type identity and to regulate gene expression in mammalian cells 1, 2 . The genome-wide map of these transcription factor binding sites has been termed the cistrome 3 . Here we show that the androgen receptor (AR) cistrome undergoes extensive reprogramming during prostate epithelial transformation in man. Using human prostate tissue, we observed a core set of AR binding sites that are consistently reprogrammed in tumors. FOXA1 and HOXB13, co-localized with the reprogrammed AR sites in human tumor tissue. Introduction of FOXA1 and HOXB13 into an immortalized prostate cell line reprogrammed the AR cistrome to resemble that of a prostate tumor, functionally linking these specific factors to AR reprogramming. These findings offer mechanistic insights into a key set of events that drive normal prostate epithelium towards transformation and establish the centrality of epigenetic reprogramming in human prostate tumorigenesis.

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          Most cited references16

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          Identifying ChIP-seq enrichment using MACS.

          Model-based analysis of ChIP-seq (MACS) is a computational algorithm that identifies genome-wide locations of transcription/chromatin factor binding or histone modification from ChIP-seq data. MACS consists of four steps: removing redundant reads, adjusting read position, calculating peak enrichment and estimating the empirical false discovery rate (FDR). In this protocol, we provide a detailed demonstration of how to install MACS and how to use it to analyze three common types of ChIP-seq data sets with different characteristics: the sequence-specific transcription factor FoxA1, the histone modification mark H3K4me3 with sharp enrichment and the H3K36me3 mark with broad enrichment. We also explain how to interpret and visualize the results of MACS analyses. The algorithm requires ∼3 GB of RAM and 1.5 h of computing time to analyze a ChIP-seq data set containing 30 million reads, an estimate that increases with sequence coverage. MACS is open source and is available from http://liulab.dfci.harvard.edu/MACS/.
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            The influence of finasteride on the development of prostate cancer.

            Androgens are involved in the development of prostate cancer. Finasteride, an inhibitor of 5alpha-reductase, inhibits the conversion of testosterone to dihydrotestosterone, the primary androgen in the prostate, and may reduce the risk of prostate cancer. In the Prostate Cancer Prevention Trial, we randomly assigned 18,882 men 55 years of age or older with a normal digital rectal examination and a prostate-specific antigen (PSA) level of 3.0 ng per milliliter or lower to treatment with finasteride (5 mg per day) or placebo for seven years. Prostate biopsy was recommended if the annual PSA level, adjusted for the effect of finasteride, exceeded 4.0 ng per milliliter or if the digital rectal examination was abnormal. It was anticipated that 60 percent of participants would have prostate cancer diagnosed during the study or would undergo biopsy at the end of the study. The primary end point was the prevalence of prostate cancer during the seven years of the study. Prostate cancer was detected in 803 of the 4368 men in the finasteride group who had data for the final analysis (18.4 percent) and 1147 of the 4692 men in the placebo group who had such data (24.4 percent), for a 24.8 percent reduction in prevalence over the seven-year period (95 percent confidence interval, 18.6 to 30.6 percent; P<0.001). Tumors of Gleason grade 7, 8, 9, or 10 were more common in the finasteride group (280 of 757 tumors [37.0 percent], or 6.4 percent of the 4368 men included in the final analysis) than in the placebo group (237 of 1068 tumors [22.2 percent], P<0.001 for the comparison between groups; or 5.1 percent of the 4692 men included in the final analysis, P=0.005 for the comparison between groups). Sexual side effects were more common in finasteride-treated men, whereas urinary symptoms were more common in men receiving placebo. Finasteride prevents or delays the appearance of prostate cancer, but this possible benefit and a reduced risk of urinary problems must be weighed against sexual side effects and the increased risk of high-grade prostate cancer. Copyright 2003 Massachusetts Medical Society
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              The androgen receptor fuels prostate cancer by regulating central metabolism and biosynthesis.

              The androgen receptor (AR) is a key regulator of prostate growth and the principal drug target for the treatment of prostate cancer. Previous studies have mapped AR targets and identified some candidates which may contribute to cancer progression, but did not characterize AR biology in an integrated manner. In this study, we took an interdisciplinary approach, integrating detailed genomic studies with metabolomic profiling and identify an anabolic transcriptional network involving AR as the core regulator. Restricting flux through anabolic pathways is an attractive approach to deprive tumours of the building blocks needed to sustain tumour growth. Therefore, we searched for targets of the AR that may contribute to these anabolic processes and could be amenable to therapeutic intervention by virtue of differential expression in prostate tumours. This highlighted calcium/calmodulin-dependent protein kinase kinase 2, which we show is overexpressed in prostate cancer and regulates cancer cell growth via its unexpected role as a hormone-dependent modulator of anabolic metabolism. In conclusion, it is possible to progress from transcriptional studies to a promising therapeutic target by taking an unbiased interdisciplinary approach.
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                Author and article information

                Journal
                9216904
                2419
                Nat Genet
                Nat. Genet.
                Nature genetics
                1061-4036
                1546-1718
                23 September 2015
                12 October 2015
                November 2015
                01 May 2016
                : 47
                : 11
                : 1346-1351
                Affiliations
                [1 ]Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts, USA
                [2 ]Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
                [3 ]Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
                [4 ]The Eli and Edythe L. Broad Institute, Cambridge, Massachusetts, USA
                [5 ]Department of Pathology, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, USA
                Author notes

                M.M.P., F.L. and D.T. contributed equally to this work.

                Correspondence to: freedman@ 123456broadinstitute.org (M.L.F.)
                Article
                NIHMS724274
                10.1038/ng.3419
                4707683
                26457646
                8ab3cb77-998d-402d-b44b-96e65b50a13c

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                Genetics
                Genetics

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