title: Pan-cancer analysis of frequent DNA co-methylation patterns reveals consistent epigenetic landscape changes in multiple cancers.
abstract: DNA methylation is the major form of epigenetic modifications through which the cell regulates the gene expression and silencing. There have been extensive studies on the roles of DNA methylation in cancers, and several cancer drugs were developed targeting this process. However, DNA co-methylation cluster has not been examined in depth, and co-methylation in multiple cancer types has never been studied previously.
  
  
  
  In this study, we applied newly developed lmQCM algorithm to mine co-methylation clusters using methylome data from 11 cancer types in TCGA database, and found frequent co-methylated gene clusters exist in these cancer types. Among the four identified frequent clusters, two of them separate the tumor sample from normal sample in 10 out of 11 cancer types, which indicates that consistent epigenetic landscape changes exist in multiple cancer types.
  
  
  
  This discovery provides new insight on the epigenetic regulation in cancers and leads to potential new direction for epigenetic biomarker and cancer drug discovery. We also found that genes commonly believed to be silenced via hypermethylation in cancers may still display highly variable methylation levels among cancer cells, and should be considered while using them as epigenetic biomarkers.
authors.affiliation: Department of Biomedical Informatics, The Ohio State University, Columbus, OH, 43210, USA.
authors.forename: Jie
authors.initials: J
authors.lastname: Zhang
authors.affiliation: Department of Biomedical Informatics, The Ohio State University, Columbus, OH, 43210, USA. kun.huang@osumc.edu.
authors.forename: Kun
authors.initials: K
authors.lastname: Huang
mesh_terms: D000375:Aging / Q000235:genetics; D016000:Cluster Analysis; D019175:DNA Methylation; D044127:Epigenesis, Genetic; D057890:Epigenomics / Q000379:methods*; D015972:Gene Expression Regulation, Neoplastic; D053263:Gene Regulatory Networks; D006801:Humans; D009369:Neoplasms / Q000235:genetics* / Q000378:metabolism; D015398:Signal Transduction
keywords: DNA co-methylation; Epigenetics; Frequent network mining; Pan-cancer methylation