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      Integrative network-based analysis of mRNA and microRNA expression in 1,25-dihydroxyvitamin D 3-treated cancer cells

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          Abstract

          Nutritional systems biology is an evolving research field aimed at understanding nutritional processes at a systems level. It is known that the development of cancer can be influenced by the nutritional status, and the link between vitamin D status and different cancer types is widely investigated. In this study, we performed an integrative network-based analysis using a publicly available data set studying the role of 1,25-dihydroxyvitamin D 3 (1,25(OH) 2D 3) in prostate cancer cells on mRNA and microRNA level. Pathway analysis revealed 15 significantly altered pathways: eight more general mostly cell cycle-related pathways and seven cancer-specific pathways. The changes in the G1-to-S cell cycle pathway showed that 1,25(OH) 2D 3 down-regulates the genes influencing the G1-to-S phase transition. Moreover, after 1,25(OH) 2D 3 treatment the gene expression in several cancer-related processes was down-regulated. The more general pathways were merged into one network and then extended with known protein–protein and transcription factor–gene interactions. Network algorithms were used to (1) identify active network modules and (2) integrate microRNA regulation in the network. Adding microRNA regulation to the network enabled the identification of gene targets of significantly expressed microRNAs after 1,25(OH) 2D 3 treatment. Six of the nine differentially expressed microRNAs target genes in the extended network, including CLSPN, an important checkpoint regulator in the cell cycle that was down-regulated, and FZD5, a receptor for Wnt proteins that was up-regulated. The extendable network-based tools PathVisio and Cytoscape enable straightforward, in-depth and integrative analysis of mRNA and microRNA expression data in 1,25(OH) 2D 3-treated cancer cells.

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          The online version of this article (doi:10.1007/s12263-015-0484-0) contains supplementary material, which is available to authorized users.

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          Most cited references22

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          miRTarBase update 2014: an information resource for experimentally validated miRNA-target interactions

          MicroRNAs (miRNAs) are small non-coding RNA molecules capable of negatively regulating gene expression to control many cellular mechanisms. The miRTarBase database (http://mirtarbase.mbc.nctu.edu.tw/) provides the most current and comprehensive information of experimentally validated miRNA-target interactions. The database was launched in 2010 with data sources for >100 published studies in the identification of miRNA targets, molecular networks of miRNA targets and systems biology, and the current release (2013, version 4) includes significant expansions and enhancements over the initial release (2010, version 1). This article reports the current status of and recent improvements to the database, including (i) a 14-fold increase to miRNA-target interaction entries, (ii) a miRNA-target network, (iii) expression profile of miRNA and its target gene, (iv) miRNA target-associated diseases and (v) additional utilities including an upgrade reminder and an error reporting/user feedback system.
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            Discovering regulatory and signalling circuits in molecular interaction networks.

            In model organisms such as yeast, large databases of protein-protein and protein-DNA interactions have become an extremely important resource for the study of protein function, evolution, and gene regulatory dynamics. In this paper we demonstrate that by integrating these interactions with widely-available mRNA expression data, it is possible to generate concrete hypotheses for the underlying mechanisms governing the observed changes in gene expression. To perform this integration systematically and at large scale, we introduce an approach for screening a molecular interaction network to identify active subnetworks, i.e., connected regions of the network that show significant changes in expression over particular subsets of conditions. The method we present here combines a rigorous statistical measure for scoring subnetworks with a search algorithm for identifying subnetworks with high score. We evaluated our procedure on a small network of 332 genes and 362 interactions and a large network of 4160 genes containing all 7462 protein-protein and protein-DNA interactions in the yeast public databases. In the case of the small network, we identified five significant subnetworks that covered 41 out of 77 (53%) of all significant changes in expression. Both network analyses returned several top-scoring subnetworks with good correspondence to known regulatory mechanisms in the literature. These results demonstrate how large-scale genomic approaches may be used to uncover signalling and regulatory pathways in a systematic, integrative fashion.
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              WikiPathways: building research communities on biological pathways

              Here, we describe the development of WikiPathways (http://www.wikipathways.org), a public wiki for pathway curation, since it was first published in 2008. New features are discussed, as well as developments in the community of contributors. New features include a zoomable pathway viewer, support for pathway ontology annotations, the ability to mark pathways as private for a limited time and the availability of stable hyperlinks to pathways and the elements therein. WikiPathways content is freely available in a variety of formats such as the BioPAX standard, and the content is increasingly adopted by external databases and tools, including Wikipedia. A recent development is the use of WikiPathways as a staging ground for centrally curated databases such as Reactome. WikiPathways is seeing steady growth in the number of users, page views and edits for each pathway. To assess whether the community curation experiment can be considered successful, here we analyze the relation between use and contribution, which gives results in line with other wiki projects. The novel use of pathway pages as supplementary material to publications, as well as the addition of tailored content for research domains, is expected to stimulate growth further.
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                Author and article information

                Contributors
                +31 43 38 82913 , martina.kutmon@maastrichtuniversity.nl
                susan.coort@maastrichtuniversity.nl
                k.denooijer@student.maastrichtuniversity.nl
                claire.lemmens@student.maastrichtuniversity.nl
                chris.evelo@maastrichtuniversity.nl
                Journal
                Genes Nutr
                Genes Nutr
                Genes & Nutrition
                Springer Berlin Heidelberg (Berlin/Heidelberg )
                1555-8932
                1865-3499
                15 August 2015
                15 August 2015
                September 2015
                : 10
                : 5
                : 35
                Affiliations
                [ ]Department of Bioinformatics - BiGCaT, NUTRIM School for Nutrition, Toxicology and Metabolism, Maastricht University, Maastricht, The Netherlands
                [ ]Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, The Netherlands
                Article
                484
                10.1007/s12263-015-0484-0
                4537452
                26276506
                1d43d343-b755-4d18-82f5-0d722794423d
                © The Author(s) 2015

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

                History
                : 23 February 2015
                : 1 August 2015
                Categories
                Research Paper
                Custom metadata
                © Springer-Verlag Berlin Heidelberg 2015

                Nutrition & Dietetics
                pathway analysis,network analysis,vitamin d,prostate cancer,systems nutrition

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