title: Extracting coordinated patterns of DNA methylation and gene expression in ovarian cancer.
abstract: OBJECTIVE
  DNA methylation, a regulator of gene expression, plays an important role in diverse biological processes including developmental process, carcinogenesis and aging. In particular, aberrant DNA methylation has been largely observed in several types of cancers. Currently, it is important to extract disease-specific gene sets associated with the regulation of DNA methylation.
  
  
  METHODS
  Here we propose a novel approach to find the minimum regulatory units of genes, co-methylated and co-expressed gene pairs (MEGP) that are highly correlated gene pairs between DNA methylation and gene expression showing the co-regulatory relationship. To evaluate whether our method is applicable to extract disease-associated genes, we applied our method to a large-scale dataset from the Cancer Genome Atlas extracting significantly associated MEGP and analyzed their functional correlation.
  
  
  RESULTS
  We observed that many MEGP physically interacted with each other and showed high semantic similarity with gene ontology terms. Furthermore, we performed gene set enrichment tests to identify how they are correlated in a complex biological process. Our MEGP were highly enriched in the biological pathway associated with ovarian cancers.
  
  
  CONCLUSIONS
  Our approach is useful for discovering coordinated epigenetic markers associated with specific diseases.
authors.affiliation: Division of Biomedical Informatics, Seoul National University Biomedical Informatics (SNUBI), Seoul, Republic of Korea.
authors.forename: Je-Gun
authors.initials: JG
authors.lastname: Joung
authors.forename: Dokyoon
authors.initials: D
authors.lastname: Kim
authors.forename: Kyung Hwa
authors.initials: KH
authors.lastname: Kim
authors.forename: Ju Han
authors.initials: JH
authors.lastname: Kim
mesh_terms: D019295:Computational Biology / Q000379:methods; D019175:DNA Methylation; D005260:Female; D015870:Gene Expression; D020869:Gene Expression Profiling / Q000379:methods; D005796:Genes / Q000502:physiology*; D006801:Humans; D055641:Mathematical Concepts; D010051:Ovarian Neoplasms / Q000235:genetics*
keywords: Cancer Gene; DNA Methylation; Gene Expression Profile; Ovarian Cancer; Protein Interaction Maps