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      Aberrant MicroRNA Expression and Its Implications for Uveal Melanoma Metastasis

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          Abstract

          Uveal melanoma (UM) is the most frequently found primary intra-ocular tumor in adults. It is a highly aggressive cancer that causes metastasis-related mortality in up to half of the patients. Many independent studies have reported somatic genetic changes associated with high metastatic risk, such as monosomy of chromosome 3 and mutations in BAP1. Still, the mechanisms that drive metastatic spread are largely unknown. This study aimed to elucidate the potential role of microRNAs in the metastasis of UM. Using a next-generation sequencing approach in 26 UM samples we identified thirteen differentially expressed microRNAs between high-risk UM and low/intermediate-risk UM, including the known oncomirs microRNA-17-5p, microRNA-21-5p, and miR-151a-3p. Integration of the differentially expressed microRNAs with expression data of predicted target genes revealed 106 genes likely to be affected by aberrant microRNA expression. These genes were involved in pathways such as cell cycle regulation, EGF signaling and EIF2 signaling. Our findings demonstrate that aberrant microRNA expression in UM may affect the expression of genes in a variety of cancer-related pathways. This implies that some microRNAs can be responsible for UM metastasis and are promising potential targets for future treatment.

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          Most cited references44

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          miRDB: an online resource for microRNA target prediction and functional annotations

          MicroRNAs (miRNAs) are small non-coding RNAs that are extensively involved in many physiological and disease processes. One major challenge in miRNA studies is the identification of genes regulated by miRNAs. To this end, we have developed an online resource, miRDB (http://mirdb.org), for miRNA target prediction and functional annotations. Here, we describe recently updated features of miRDB, including 2.1 million predicted gene targets regulated by 6709 miRNAs. In addition to presenting precompiled prediction data, a new feature is the web server interface that allows submission of user-provided sequences for miRNA target prediction. In this way, users have the flexibility to study any custom miRNAs or target genes of interest. Another major update of miRDB is related to functional miRNA annotations. Although thousands of miRNAs have been identified, many of the reported miRNAs are not likely to play active functional roles or may even have been falsely identified as miRNAs from high-throughput studies. To address this issue, we have performed combined computational analyses and literature mining, and identified 568 and 452 functional miRNAs in humans and mice, respectively. These miRNAs, as well as associated functional annotations, are presented in the FuncMir Collection in miRDB.
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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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              miRWalk: An online resource for prediction of microRNA binding sites

              miRWalk is an open-source platform providing an intuitive interface that generates predicted and validated miRNA-binding sites of known genes of human, mouse, rat, dog and cow. The core of miRWalk is the miRNA target site prediction with the random-forest-based approach software TarPmiR searching the complete transcript sequence including the 5’-UTR, CDS and 3’-UTR. Moreover, it integrates results other databases with predicted and validated miRNA-target interactions. The focus is set on a modular design and extensibility as well as a fast update cycle. The database is available using Python, MySQL and HTML/Javascript Database URL: http://mirwalk.umm.uni-heidelberg.de.
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                Author and article information

                Journal
                Cancers (Basel)
                Cancers (Basel)
                cancers
                Cancers
                MDPI
                2072-6694
                12 June 2019
                June 2019
                : 11
                : 6
                : 815
                Affiliations
                [1 ]Department of Ophthalmology, Erasmus University MC, 3015 GD Rotterdam, The Netherlands; k.n.smit@ 123456erasmusmc.nl (K.N.S.); j.vaarwater@ 123456erasmusmc.nl (J.V.)
                [2 ]Department of Clinical Genetics, Erasmus University MC, 3015 GD Rotterdam, The Netherlands; t.brands@ 123456erasmusmc.nl (T.B.); a.deklein@ 123456erasmusmc.nl (A.d.K.)
                [3 ]Department of Molecular Genetics, Erasmus University MC, 3015 GD Rotterdam, The Netherlands; j.chang@ 123456erasmusmc.nl (J.C.); kasper.derks@ 123456mumc.nl (K.D.); j.pothof@ 123456erasmusmc.nl (J.P.)
                [4 ]Department of Pathology, Section Ophthalmic Pathology, Erasmus University MC, 3015 GD Rotterdam, The Netherlands; r.verdijk@ 123456erasmusmc.nl
                [5 ]The Rotterdam Eye Hospital, 3011 BH Rotterdam, The Netherlands; h.mensink@ 123456oogziekenhuis.nl
                [6 ]Department of Medical Oncology, Erasmus University MC, 3015 GD Rotterdam, The Netherlands; e.wiemer@ 123456erasmusmc.nl
                Author notes
                [* ]Correspondence: e.kilic@ 123456erasmusmc.nl ; Tel.: +31-107-044-157
                Author information
                https://orcid.org/0000-0003-0865-8934
                https://orcid.org/0000-0003-1437-214X
                https://orcid.org/0000-0002-0673-7236
                Article
                cancers-11-00815
                10.3390/cancers11060815
                6628189
                31212861
                f09bedfc-b3e0-44ac-bfe2-8bd861b26c04
                © 2019 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 14 May 2019
                : 10 June 2019
                Categories
                Article

                uveal melanoma,metastasis,micrornas,mrna expression,ipa pathway analysis

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