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Correlation of Quantitative Methylation Data With Gene Expression

Richard J. Shaw, MD, FDS, FRCS; Gillian L. Hall, MFDS; Derek Lowe, CStat; Triantafillos Liloglou, PhD; John K. Field, MA, PhD, BDS, FRCPath; Phillip Sloan, PhD, FRCPath; Janet M. Risk, PhD

Arch Otolaryngol Head Neck Surg. 2008;134(3):251-256.

Objective  To evaluate promoter methylation quantitation using recently described pyrosequencing techniques by correlation with messenger RNA (mRNA) expression.

Design  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.

Setting  Academic research.

Patients  Thirty-seven patients with head and neck squamous cell carcinoma.

Main Outcome Measures  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,  = –0.53; P < .001), MGMT ( = –0.53, P < .001), and RARB ( = –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 ( = 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.

Author Affiliations: Molecular Genetics & Oncology Group, School of Dental Sciences (Drs Shaw, Hall, Field, and Risk), and Cancer Research Centre, Roy Castle Lung Cancer Research Programme (Drs Liloglou and Field), University of Liverpool, and Regional Maxillofacial Unit, University Hospital Aintree (Dr Shaw and Mr Lowe), Liverpool, and Department of Oral Pathology, Turner Dental School, Manchester (Dr Sloan), England.

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