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      A new 12-gene diagnostic biomarker signature of melanoma revealed by integrated microarray analysis

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          Abstract

          Genome-wide microarray technology has facilitated the systematic discovery of diagnostic biomarkers of cancers and other pathologies. However, meta-analyses of published arrays often uncover significant inconsistencies that hinder advances in clinical practice. Here we present an integrated microarray analysis framework, based on a genome-wide relative significance (GWRS) and genome-wide global significance (GWGS) model. When applied to five microarray datasets on melanoma published between 2000 and 2011, this method revealed a new signature of 200 genes. When these were linked to so-called ‘melanoma driver’ genes involved in MAPK, Ca 2+ , and WNT signaling pathways we were able to produce a new 12-gene diagnostic biomarker signature for melanoma (i.e.,  EGFR, FGFR2, FGFR3, IL8, PTPRF, TNC, CXCL13, COL11A1, CHP2, SHC4, PPP2R2C, and WNT4). We have begun to experimentally validate a subset of these genes involved in MAPK signaling at the protein level, including CXCL13, COL11A1, PTPRF and SHC4 and found these to be over-expressed in metastatic and primary melanoma cells in vitro and in situ compared to melanocytes cultured from healthy skin epidermis and normal healthy human skin. While SHC4 has been reported previously to be associated to melanoma, this is the first time CXCL13, COL11A1, and PTPRF have been associated with melanoma on experimental validation. Our computational evaluation indicates that this 12-gene biomarker signature achieves excellent diagnostic power in distinguishing metastatic melanoma from normal skin and benign nevus. Further experimental validation of the role of these 12 genes in a new signaling network may provide new insights into the underlying biological mechanisms driving the progression of melanoma.

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          Integrative genomic analyses identify MITF as a lineage survival oncogene amplified in malignant melanoma.

          Systematic analyses of cancer genomes promise to unveil patterns of genetic alterations linked to the genesis and spread of human cancers. High-density single-nucleotide polymorphism (SNP) arrays enable detailed and genome-wide identification of both loss-of-heterozygosity events and copy-number alterations in cancer. Here, by integrating SNP array-based genetic maps with gene expression signatures derived from NCI60 cell lines, we identified the melanocyte master regulator MITF (microphthalmia-associated transcription factor) as the target of a novel melanoma amplification. We found that MITF amplification was more prevalent in metastatic disease and correlated with decreased overall patient survival. BRAF mutation and p16 inactivation accompanied MITF amplification in melanoma cell lines. Ectopic MITF expression in conjunction with the BRAF(V600E) mutant transformed primary human melanocytes, and thus MITF can function as a melanoma oncogene. Reduction of MITF activity sensitizes melanoma cells to chemotherapeutic agents. Targeting MITF in combination with BRAF or cyclin-dependent kinase inhibitors may offer a rational therapeutic avenue into melanoma, a highly chemotherapy-resistant neoplasm. Together, these data suggest that MITF represents a distinct class of 'lineage survival' or 'lineage addiction' oncogenes required for both tissue-specific cancer development and tumour progression.
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            Melanoma.

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              Identifying biological themes within lists of genes with EASE.

              EASE is a customizable software application for rapid biological interpretation of gene lists that result from the analysis of microarray, proteomics, SAGE and other high-throughput genomic data. The biological themes returned by EASE recapitulate manually determined themes in previously published gene lists and are robust to varying methods of normalization, intensity calculation and statistical selection of genes. EASE is a powerful tool for rapidly converting the results of functional genomics studies from 'genes' to 'themes'.
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                Author and article information

                Contributors
                Journal
                Peerj
                Peerj
                PeerJ
                PeerJ
                PeerJ
                PeerJ Inc. (San Francisco, USA )
                2167-8359
                5 March 2013
                2013
                : 1
                : e49
                Affiliations
                [1 ]Department of Computing, University of Bradford , Great Britain
                [2 ]Centre of Skin Sciences, University of Bradford , Great Britain
                Article
                49
                10.7717/peerj.49
                3628745
                23638386
                ff9226a2-5c9c-4945-b845-ff2fa2ec3a6c
                © 2013 Liu et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 3 December 2012
                : 20 February 2013
                Funding
                Funded by: University of Bradford’s Department of Computing
                Funded by: University of Bradford’s Centre for Skin Sciences
                The funding for this study was provided by the University of Bradford’s Department of Computing and Centre for Skin Sciences. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Bioinformatics
                Cell Biology
                Computational Biology
                Genomics
                Dermatology

                gene biomarker,microarray,bioinformatics,genome,nevi,skin,melanocytes,melanoma,metastasis,immunochemistry

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