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      Androgen receptor profiling predicts prostate cancer outcome

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          Abstract

          Prostate cancer is the second most prevalent malignancy in men. Biomarkers for outcome prediction are urgently needed, so that high-risk patients could be monitored more closely postoperatively. To identify prognostic markers and to determine causal players in prostate cancer progression, we assessed changes in chromatin state during tumor development and progression. Based on this, we assessed genomewide androgen receptor/chromatin binding and identified a distinct androgen receptor/chromatin binding profile between primary prostate cancers and tumors with an acquired resistance to therapy. These differential androgen receptor/chromatin interactions dictated expression of a distinct gene signature with strong prognostic potential. Further refinement of the signature provided us with a concise list of nine genes that hallmark prostate cancer outcome in multiple independent validation series. In this report, we identified a novel gene expression signature for prostate cancer outcome through generation of multilevel genomic data on chromatin accessibility and transcriptional regulation and integration with publically available transcriptomic and clinical datastreams. By combining existing technologies, we propose a novel pipeline for biomarker discovery that is easily implementable in other fields of oncology.

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          Most cited references49

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          STEM: a tool for the analysis of short time series gene expression data

          Background Time series microarray experiments are widely used to study dynamical biological processes. Due to the cost of microarray experiments, and also in some cases the limited availability of biological material, about 80% of microarray time series experiments are short (3–8 time points). Previously short time series gene expression data has been mainly analyzed using more general gene expression analysis tools not designed for the unique challenges and opportunities inherent in short time series gene expression data. Results We introduce the Short Time-series Expression Miner (STEM) the first software program specifically designed for the analysis of short time series microarray gene expression data. STEM implements unique methods to cluster, compare, and visualize such data. STEM also supports efficient and statistically rigorous biological interpretations of short time series data through its integration with the Gene Ontology. Conclusion The unique algorithms STEM implements to cluster and compare short time series gene expression data combined with its visualization capabilities and integration with the Gene Ontology should make STEM useful in the analysis of data from a significant portion of all microarray studies. STEM is available for download for free to academic and non-profit users at .
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            Progesterone receptor modulates estrogen receptor-α action in breast cancer

            Summary Progesterone receptor (PR) expression is employed as a biomarker of estrogen receptor-α (ERα) function and breast cancer prognosis. We now show that PR is not merely an ERα-induced gene target, but is also an ERα-associated protein that modulates its behaviour. In the presence of agonist ligands, PR associates with ERα to direct ERα chromatin binding events within breast cancer cells, resulting in a unique gene expression programme that is associated with good clinical outcome. Progesterone inhibited estrogen-mediated growth of ERα+ cell line xenografts and primary ERα+ breast tumour explants and had increased anti-proliferative effects when coupled with an ERα antagonist. Copy number loss of PgR is a common feature in ERα+ breast cancers, explaining lower PR levels in a subset of cases. Our findings indicate that PR functions as a molecular rheostat to control ERα chromatin binding and transcriptional activity, which has important implications for prognosis and therapeutic interventions.
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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
                EMBO Mol Med
                EMBO Mol Med
                emmm
                EMBO Molecular Medicine
                John Wiley & Sons, Ltd (Chichester, UK )
                1757-4676
                1757-4684
                November 2015
                27 September 2015
                : 7
                : 11
                : 1450-1464
                Affiliations
                [1 ]Division of Molecular Pathology, The Netherlands Cancer Institute Amsterdam, The Netherlands
                [2 ]Division of Molecular Carcinogenesis, The Netherlands Cancer Institute Amsterdam, The Netherlands
                [3 ]Division of Urology, The Netherlands Cancer Institute Amsterdam, The Netherlands
                [4 ]Division of Pathology, The Netherlands Cancer Institute Amsterdam, The Netherlands
                [5 ]Department of Pathology, Josephine Nefkens Institute, Erasmus Medical Center Rotterdam, The Netherlands
                [6 ]Department of Urology, Josephine Nefkens Institute, Erasmus Medical Center Rotterdam, The Netherlands
                [7 ]Division of Medical Oncology, The Netherlands Cancer Institute Amsterdam, The Netherlands
                Author notes
                * Corresponding author. Tel: +31 20 512 2101; E-mail: a.bergman@ 123456nki.nl
                ** Corresponding author. Tel: +31 20 512 2101; E-mail: w.zwart@ 123456nki.nl

                Subject Categories Cancer; Systems Medicine; Urogenital System

                [†]

                These authors contributed equally to this study

                Article
                10.15252/emmm.201505424
                4644377
                26412853
                6cd930bf-568d-4df9-8ff0-474f51120b56
                © 2015 The Authors. Published under the terms of the CC BY 4.0 license

                This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 08 May 2015
                : 01 September 2015
                : 03 September 2015
                Categories
                Research Articles

                Molecular medicine
                androgen receptor profiling,chip-seq,companion diagnostics for prostate cancer,faire-seq,treatment prediction

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