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      Identification of novel chemotherapeutic strategies for metastatic uveal melanoma

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          Abstract

          Melanoma of the uveal tract accounts for approximately 5% of all melanomas and represents the most common primary intraocular malignancy. Despite improvements in diagnosis and more effective local therapies for primary cancer, the rate of metastatic death has not changed in the past forty years. In the present study, we made use of bioinformatics to analyze the data obtained from three public available microarray datasets on uveal melanoma in an attempt to identify novel putative chemotherapeutic options for the liver metastatic disease. We have first carried out a meta-analysis of publicly available whole-genome datasets, that included data from 132 patients, comparing metastatic vs. non metastatic uveal melanomas, in order to identify the most relevant genes characterizing the spreading of tumor to the liver. Subsequently, the L1000CDS 2 web-based utility was used to predict small molecules and drugs targeting the metastatic uveal melanoma gene signature. The most promising drugs were found to be Cinnarizine, an anti-histaminic drug used for motion sickness, Digitoxigenin, a precursor of cardiac glycosides, and Clofazimine, a fat-soluble iminophenazine used in leprosy. In vitro and in vivo validation studies will be needed to confirm the efficacy of these molecules for the prevention and treatment of metastatic uveal melanoma.

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          Most cited references34

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          Rational design and simple chemistry yield a superior, neuroprotective HDAC6 inhibitor, tubastatin A.

          Structure-based drug design combined with homology modeling techniques were used to develop potent inhibitors of HDAC6 that display superior selectivity for the HDAC6 isozyme compared to other inhibitors. These inhibitors can be assembled in a few synthetic steps, and thus are readily scaled up for in vivo studies. An optimized compound from this series, designated Tubastatin A, was tested in primary cortical neuron cultures in which it was found to induce elevated levels of acetylated alpha-tubulin, but not histone, consistent with its HDAC6 selectivity. Tubastatin A also conferred dose-dependent protection in primary cortical neuron cultures against glutathione depletion-induced oxidative stress. Importantly, when given alone at all concentrations tested, this hydroxamate-containing HDAC6-selective compound displayed no neuronal toxicity, thus, forecasting the potential application of this agent and its analogues to neurodegenerative conditions.
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            Uveal melanoma: From diagnosis to treatment and the science in between.

            Melanomas of the choroid, ciliary body, and iris of the eye are collectively known as uveal melanomas. These cancers represent 5% of all melanoma diagnoses in the United States, and their age-adjusted risk is 5 per 1 million population. These less frequent melanomas are dissimilar to their more common cutaneous melanoma relative, with differing risk factors, primary treatment, anatomic spread, molecular changes, and responses to systemic therapy. Once uveal melanoma becomes metastatic, therapy options are limited and are often extrapolated from cutaneous melanoma therapies despite the routine exclusion of patients with uveal melanoma from clinical trials. Clinical trials directed at uveal melanoma have been completed or are in progress, and data from these well designed investigations will help guide future directions in this orphan disease. Cancer 2016;122:2299-2312. © 2016 American Cancer Society.
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              LINCS Canvas Browser: interactive web app to query, browse and interrogate LINCS L1000 gene expression signatures

              For the Library of Integrated Network-based Cellular Signatures (LINCS) project many gene expression signatures using the L1000 technology have been produced. The L1000 technology is a cost-effective method to profile gene expression in large scale. LINCS Canvas Browser (LCB) is an interactive HTML5 web-based software application that facilitates querying, browsing and interrogating many of the currently available LINCS L1000 data. LCB implements two compacted layered canvases, one to visualize clustered L1000 expression data, and the other to display enrichment analysis results using 30 different gene set libraries. Clicking on an experimental condition highlights gene-sets enriched for the differentially expressed genes from the selected experiment. A search interface allows users to input gene lists and query them against over 100 000 conditions to find the top matching experiments. The tool integrates many resources for an unprecedented potential for new discoveries in systems biology and systems pharmacology. The LCB application is available at http://www.maayanlab.net/LINCS/LCB. Customized versions will be made part of the http://lincscloud.org and http://lincs.hms.harvard.edu websites.
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                Author and article information

                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                2045-2322
                17 March 2017
                2017
                : 7
                : 44564
                Affiliations
                [1 ]Department of Biomedical and Biotechnological Sciences, University of Catania , Catania, Italy
                [2 ]Department of Medical and Surgical Sciences and Advanced Technologies, G.F. Ingrassia, University of Catania , Catania, Italy
                [3 ]Department of Ophthalmology, University of Catania , Catania, Italy
                [4 ]Department of Dermatology, AOU Policlinico Vittorio Emanuele Hospital Catania , Catania, Italy
                Author notes
                Article
                srep44564
                10.1038/srep44564
                5355998
                28303962
                9b7856a6-0f6b-4efe-b08e-f9c535838ae7
                Copyright © 2017, The Author(s)

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                History
                : 17 November 2016
                : 09 February 2017
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