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      A DNA methylation‐based definition of biologically distinct breast cancer subtypes

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          Abstract

          In cancer, epigenetic states are deregulated and thought to be of significance in cancer development and progression. We explored DNA methylation‐based signatures in association with breast cancer subtypes to assess their impact on clinical presentation and patient prognosis. DNA methylation was analyzed using Infinium 450K arrays in 40 tumors and 17 normal breast samples, together with DNA copy number changes and subtype‐specific markers by tissue microarrays. The identified methylation signatures were validated against a cohort of 212 tumors annotated for breast cancer subtypes by the PAM50 method (The Cancer Genome Atlas). Selected markers were pyrosequenced in an independent validation cohort of 310 tumors and analyzed with respect to survival, clinical stage and grade. The results demonstrate that DNA methylation patterns linked to the luminal‐B subtype are characterized by CpG island promoter methylation events. In contrast, a large fraction of basal‐like tumors are characterized by hypomethylation events occurring within the gene body. Based on these hallmark signatures, we defined two DNA methylation‐based subtypes, Epi‐LumB and Epi‐Basal, and show that they are associated with unfavorable clinical parameters and reduced survival. Our data show that distinct mechanisms leading to changes in CpG methylation states are operative in different breast cancer subtypes. Importantly, we show that a few selected proxy markers can be used to detect the distinct DNA methylation‐based subtypes thereby providing valuable information on disease prognosis.

          Highlights

          • We describe distinct signatures associated with luminal‐B and basal‐like subtypes.

          • The signatures identified show differences in genes, but also in the CpG context.

          • A selected set of proxy markers for each signature revealed their clinical relevance.

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          Most cited references16

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          Gene body methylation can alter gene expression and is a therapeutic target in cancer.

          DNA methylation in promoters is well known to silence genes and is the presumed therapeutic target of methylation inhibitors. Gene body methylation is positively correlated with expression, yet its function is unknown. We show that 5-aza-2'-deoxycytidine treatment not only reactivates genes but decreases the overexpression of genes, many of which are involved in metabolic processes regulated by c-MYC. Downregulation is caused by DNA demethylation of the gene bodies and restoration of high levels of expression requires remethylation by DNMT3B. Gene body methylation may, therefore, be an unexpected therapeutic target for DNA methylation inhibitors, resulting in the normalization of gene overexpression induced during carcinogenesis. Our results provide direct evidence for a causal relationship between gene body methylation and transcription. Copyright © 2014 Elsevier Inc. All rights reserved.
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            The shaping and functional consequences of the microRNA landscape in breast cancer.

            MicroRNAs (miRNAs) show differential expression across breast cancer subtypes, and have both oncogenic and tumour-suppressive roles. Here we report the miRNA expression profiles of 1,302 breast tumours with matching detailed clinical annotation, long-term follow-up and genomic and messenger RNA expression data. This provides a comprehensive overview of the quantity, distribution and variation of the miRNA population and provides information on the extent to which genomic, transcriptional and post-transcriptional events contribute to miRNA expression architecture, suggesting an important role for post-transcriptional regulation. The key clinical parameters and cellular pathways related to the miRNA landscape are characterized, revealing context-dependent interactions, for example with regards to cell adhesion and Wnt signalling. Notably, only prognostic miRNA signatures derived from breast tumours devoid of somatic copy-number aberrations (CNA-devoid) are consistently prognostic across several other subtypes and can be validated in external cohorts. We then use a data-driven approach to seek the effects of miRNAs associated with differential co-expression of mRNAs, and find that miRNAs act as modulators of mRNA-mRNA interactions rather than as on-off molecular switches. We demonstrate such an important modulatory role for miRNAs in the biology of CNA-devoid breast cancers, a common subtype in which the immune response is prominent. These findings represent a new framework for studying the biology of miRNAs in human breast cancer.
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              TSGene: a web resource for tumor suppressor genes

              Tumor suppressor genes (TSGs) are guardian genes that play important roles in controlling cell proliferation processes such as cell-cycle checkpoints and inducing apoptosis. Identification of these genes and understanding their functions are critical for further investigation of tumorigenesis. So far, many studies have identified numerous TSGs and illustrated their functions in various types of tumors or normal samples. Furthermore, accumulating evidence has shown that non-coding RNAs can act as TSGs to prevent the tumorigenesis processes. Therefore, there is a growing demand to integrate TSGs with large-scale experimental evidence (e.g. gene expression and epigenetic signatures) to provide a comprehensive resource for further investigation of TSGs and their molecular mechanisms in cancer. To achieve this goal, we first developed a comprehensive literature-based database called TSGene (tumor suppressor gene database), freely available at http://bioinfo.mc.vanderbilt.edu/TSGene/. In the current release, TSGene contains 716 human (637 protein-coding and 79 non-coding genes), 628 mouse and 567 rat TSGs curated from UniProtKB, the Tumor Associated Gene database and 5795 PubMed abstracts. Additionally, the TSGene provides detailed annotations for each TSG, such as cancer mutations, gene expressions, methylation sites, TF regulations and protein–protein interactions.
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                Author and article information

                Contributors
                mesteller@idibell.cat
                Journal
                Mol Oncol
                Mol Oncol
                10.1002/(ISSN)1878-0261
                MOL2
                Molecular Oncology
                John Wiley and Sons Inc. (Hoboken )
                1574-7891
                1878-0261
                05 November 2014
                March 2015
                : 9
                : 3 ( doiID: 10.1002/mol2.2015.9.issue-3 )
                : 555-568
                Affiliations
                [ 1 ]Cancer Epigenetics and Biology Program (PEBC), Bellvitge Biomedical Research Institute, L'Hospitalet, Barcelona, Catalonia 08908, Spain
                [ 2 ]The Cancer Research Laboratory, Medical Faculty, University of Iceland, Reykjavik, Iceland
                [ 3 ]The Icelandic Cancer Registry, Reykjavik, Iceland
                [ 4 ]Department of Pathology, Landspitali University Hospital, Reykjavik, Iceland
                [ 5 ]Department of Physiological Sciences II, School of Medicine, University of Barcelona, Barcelona, Catalonia, Spain
                [ 6 ]Institucio Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Catalonia, Spain
                Author notes
                [*] [* ]Corresponding author. IDIBELL – Bellvitge Biomedical Research Institute, Cancer Epigenetics and Biology Program (PEBC), Hospital Duran i Reynals, Gran Via de l'Hospitalet, 199, L'Hospitalet de Llobregat, Barcelona, Catalonia 08907, Spain. Tel.: +34 93 260 71 40; fax: +34 93 260 72 19.
                Article
                MOL2201593555
                10.1016/j.molonc.2014.10.012
                5528700
                25468711
                c7b299fc-7e6c-4754-89dd-0e575766d6d1
                © 2015 The Authors. Published by FEBS Press and John Wiley & Sons Ltd.

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

                History
                : 27 December 2013
                : 06 October 2014
                : 29 October 2014
                Page count
                Figures: 6, Tables: 3, Equations: 0, References: 33, Pages: 14, Words: 11054
                Categories
                Research Article
                Research Articles
                Custom metadata
                2.0
                mol2201593555
                March 2015
                Converter:WILEY_ML3GV2_TO_NLMPMC version:5.1.4 mode:remove_FC converted:25.07.2017

                Oncology & Radiotherapy
                breast cancer,dna methylation,microarrays,biological subtypes,prognosis
                Oncology & Radiotherapy
                breast cancer, dna methylation, microarrays, biological subtypes, prognosis

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