A Web-based database of genetic association studies in cutaneous melanoma enhanced with network-driven data exploration tools

The publicly available online database MelGene provides a comprehensive, regularly updated, collection of data from genetic association studies in cutaneous melanoma (CM), including random-effects meta-analysis results of all eligible polymorphisms. The updated database version includes data from 192 publications with information on 1114 significantly associated polymorphisms across 280 genes, along with new front-end and back-end capabilities. Various types of relationships between data are calculated and visualized as networks. We constructed 13 different networks containing the polymorphisms and the genes included in MelGene. We explored the derived network representations under the following questions: (i) are there nodes that deserve consideration regarding their network connectivity characteristics? (ii) What is the relation of either the genome-wide or nominally significant CM polymorphisms/genes with the ones highlighted by the network representation? We show that our network approach using the MelGene data reveals connections between statistically significant genes/ polymorphisms and other genes/polymorphisms acting as ‘hubs’ in the reconstructed networks. To the best of our knowledge, this is the first database containing data from a comprehensive field synopsis and systematic meta-analyses of genetic polymorphisms in CM that provides user-friendly tools for in-depth molecular network visualization and exploration. The proposed network connections highlight potentially new loci requiring further investigation of their relation to melanoma risk. Database URL: http://www.melgene.org.

[1]  John P A Ioannidis,et al.  Comprehensive field synopsis and systematic meta-analyses of genetic association studies in cutaneous melanoma. , 2011, Journal of the National Cancer Institute.

[2]  Siobhan M. Dolan,et al.  Genome-Wide Association Studies, Field Synopses, and the Development of the Knowledge Base on Genetic Variation and Human Diseases , 2009, American journal of epidemiology.

[3]  Nicholas G Martin,et al.  A population-based study of Australian twins with melanoma suggests a strong genetic contribution to liability. , 2009, The Journal of investigative dermatology.

[4]  A. Jemal,et al.  Cancer Statistics, 2009 , 2009, CA: a cancer journal for clinicians.

[5]  Gábor Csárdi,et al.  The igraph software package for complex network research , 2006 .

[6]  S A Forbes,et al.  The Catalogue of Somatic Mutations in Cancer (COSMIC) , 2008, Current protocols in human genetics.

[7]  N. Dubrawsky Cancer statistics , 1989, CA: a cancer journal for clinicians.

[8]  Andrew D. Johnson,et al.  SNAP: a web-based tool for identification and annotation of proxy SNPs using HapMap , 2008, Bioinform..

[9]  H. Chandler Database , 1985 .

[10]  P. Boyle,et al.  Meta-analysis of risk factors for cutaneous melanoma: III. Family history, actinic damage and phenotypic factors. , 2005, European journal of cancer.

[11]  I. Rennie,et al.  Invasive and noninvasive uveal melanomas have different adhesive properties , 2005, Eye.

[12]  J. Malvehy,et al.  Genome-wide association study identifies three loci associated with melanoma risk , 2009, Nature Genetics.

[13]  Doron Lancet,et al.  MalaCards: an integrated compendium for diseases and their annotation , 2013, Database J. Biol. Databases Curation.

[14]  A. Hauschild,et al.  Epidemiology of invasive cutaneous melanoma , 2009, Annals of oncology : official journal of the European Society for Medical Oncology.

[15]  Gary D. Bader,et al.  GeneMANIA Prediction Server 2013 Update , 2013, Nucleic Acids Res..

[16]  Damian Szklarczyk,et al.  STRING v9.1: protein-protein interaction networks, with increased coverage and integration , 2012, Nucleic Acids Res..

[17]  B. Safai,et al.  Diagnostic and prognostic biomarkers in melanoma. , 2014, The Journal of clinical and aesthetic dermatology.

[18]  Gary D Bader,et al.  A travel guide to Cytoscape plugins , 2012, Nature Methods.

[19]  Magali Olivier,et al.  TP53 mutations in human cancers: origins, consequences, and clinical use. , 2010, Cold Spring Harbor perspectives in biology.

[20]  References , 1971 .

[21]  Sharon R Grossman,et al.  Integrating common and rare genetic variation in diverse human populations , 2010, Nature.

[22]  Guozhen Liu,et al.  GNCPro: navigate human genes and relationships through net-walking. , 2010, Advances in experimental medicine and biology.

[23]  P. Pollock,et al.  p53 prevents progression of nevi to melanoma predominantly through cell cycle regulation , 2010, Pigment cell & melanoma research.

[24]  Wolfgang Viechtbauer,et al.  Conducting Meta-Analyses in R with the metafor Package , 2010 .