title: Identification of endometrial cancer methylation features using combined methylation analysis methods.
abstract: BACKGROUND
  DNA methylation is a stable epigenetic mark that is frequently altered in tumors. DNA methylation features are attractive biomarkers for disease states given the stability of DNA methylation in living cells and in biologic specimens typically available for analysis. Widespread accumulation of methylation in regulatory elements in some cancers (specifically the CpG island methylator phenotype, CIMP) can play an important role in tumorigenesis. High resolution assessment of CIMP for the entire genome, however, remains cost prohibitive and requires quantities of DNA not available for many tissue samples of interest. Genome-wide scans of methylation have been undertaken for large numbers of tumors, and higher resolution analyses for a limited number of cancer specimens. Methods for analyzing such large datasets and integrating findings from different studies continue to evolve. An approach for comparison of findings from a genome-wide assessment of the methylated component of tumor DNA and more widely applied methylation scans was developed.
  
  
  METHODS
  Methylomes for 76 primary endometrial cancer and 12 normal endometrial samples were generated using methylated fragment capture and second generation sequencing, MethylCap-seq. Publically available Infinium HumanMethylation 450 data from The Cancer Genome Atlas (TCGA) were compared to MethylCap-seq data.
  
  
  RESULTS
  Analysis of methylation in promoter CpG islands (CGIs) identified a subset of tumors with a methylator phenotype. We used a two-stage approach to develop a 13-region methylation signature associated with a "hypermethylator state." High level methylation for the 13-region methylation signatures was associated with mismatch repair deficiency, high mutation rate, and low somatic copy number alteration in the TCGA test set. In addition, the signature devised showed good agreement with previously described methylation clusters devised by TCGA.
  
  
  CONCLUSIONS
  We identified a methylation signature for a "hypermethylator phenotype" in endometrial cancer and developed methods that may prove useful for identifying extreme methylation phenotypes in other cancers.
authors.affiliation: Department of Cancer Biology & Genetics, The Ohio State University, Columbus, Ohio, United States of America.
authors.forename: Michael P
authors.initials: MP
authors.lastname: Trimarchi
authors.affiliation: Department of Internal Medicine, College of Medicine, The Ohio State University, Columbus, Ohio, United States of America.
authors.forename: Pearlly
authors.initials: P
authors.lastname: Yan
authors.affiliation: Department of Cancer Biology & Genetics, The Ohio State University, Columbus, Ohio, United States of America.
authors.forename: Joanna
authors.initials: J
authors.lastname: Groden
authors.affiliation: Center for RNA Biology, Department of Physics, Department of Chemistry & Biochemistry, and Department of Internal Medicine, and Center for RNA Biology, The Ohio State University, Columbus, OH, United States of America.
authors.forename: Ralf
authors.initials: R
authors.lastname: Bundschuh
authors.affiliation: Department of Obstetrics and Gynecology, College of Medicine, The Ohio State University, Columbus, Ohio, United States of America.
authors.forename: Paul J
authors.initials: PJ
authors.lastname: Goodfellow
mesh_terms: D016022:Case-Control Studies; D018899:CpG Islands; D019175:DNA Methylation; D016889:Endometrial Neoplasms / Q000235:genetics*; D004717:Endometrium / Q000378:metabolism*; D005260:Female; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D010641:Phenotype; D011401:Promoter Regions, Genetic / Q000235:genetics; D017422:Sequence Analysis, DNA / Q000379:methods*