title: The role of pyrosequencing in head and neck cancer epigenetics: correlation of quantitative methylation data with gene expression.
abstract: OBJECTIVE
  To evaluate promoter methylation quantitation using recently described pyrosequencing techniques by correlation with messenger RNA (mRNA) expression.
  
  
  METHODS
  DNA was extracted from tissue samples and was subjected to bisulphite conversion. Quantitative methylation data for multiple CpG sites in each of 9 gene promoters were obtained for tumors using pyrosequencing. RNA was extracted and converted to complementary DNA, and this formed the template for relative quantitation assays of the expression of each gene by real-time reverse transcription-polymerase chain reaction.
  
  
  METHODS
  Academic research.
  
  
  METHODS
  Thirty-seven patients with head and neck squamous cell carcinoma.
  
  
  METHODS
  The genes studied were P16 (OMIM 600160), cyclin A1 (OMIM 604036), RARB (OMIM 180220), E-cadherin (OMIM 192090), MGMT (OMIM 156569), STAT1 (OMIM 600555), ATM (OMIM 607585), hMLH1 (OMIM 120436), and TIMP3 (OMIM 188826). Immunohistochemistry was also performed for p16.
  
  
  RESULTS
  STAT1, TIMP3, ATM, and hMLH1 promoters were essentially unmethylated in all cases. The data for cyclin A1 (Spearman rank correlation, rho = -0.53; P < .001), MGMT (rho = -0.53, P < .001), and RARB (rho = -0.34, P =.02) showed the expected negative correlation between levels of methylation and mRNA expression. The data relating to E-cadherin were inconclusive. Surprisingly, P16 expression was statistically significantly greater in those cases with higher levels of methylation (rho = 0.57, P < .001), a finding at odds with assumptions usually made in the literature relating gene promoter methylation to reduced gene expression. The results from p16 immunohistochemistry were in keeping with the mRNA data, but the number of positive staining samples proved too few for statistical analysis.
  
  
  CONCLUSIONS
  These data present a novel perspective on head and neck cancer epigenetics and reveal new and some unexpected associations and findings. The advantages of pyrosequencing over nonquantitative techniques are discussed in analyses of this nature.
authors.affiliation: Molecular Genetics & Oncology Group, School of Dental Sciences, University of Liverpool, Liverpool, England. richard.shaw@liverpool.ac.uk
authors.forename: Richard J
authors.initials: RJ
authors.lastname: Shaw
authors.forename: Gillian L
authors.initials: GL
authors.lastname: Hall
authors.forename: Derek
authors.initials: D
authors.lastname: Lowe
authors.forename: Triantafillos
authors.initials: T
authors.lastname: Liloglou
authors.forename: John K
authors.initials: JK
authors.lastname: Field
authors.forename: Phillip
authors.initials: P
authors.lastname: Sloan
authors.forename: Janet M
authors.initials: JM
authors.lastname: Risk
mesh_terms: D001483:Base Sequence; D002294:Carcinoma, Squamous Cell / Q000235:genetics*; D019941:Cyclin-Dependent Kinase Inhibitor p16 / Q000235:genetics; D019175:DNA Methylation; D044127:Epigenesis, Genetic; D015972:Gene Expression Regulation, Neoplastic; D006258:Head and Neck Neoplasms / Q000235:genetics*; D006801:Humans; D007124:Immunoenzyme Techniques; D011401:Promoter Regions, Genetic; D012333:RNA, Messenger / Q000032:analysis; D020133:Reverse Transcriptase Polymerase Chain Reaction; D017422:Sequence Analysis, DNA
chemical_list: D019941:Cyclin-Dependent Kinase Inhibitor p16; D012333:RNA, Messenger