Predicting Aberrant CpG Island Methylation

• Published in: Proceedings of the National Academy of Sciences - PNAS 2003-10, Vol.100 (21), p.12253-12258
• Main Authors: Feltus, F. A., Lee, E. K., Costello, J. F., Plass, C., Vertino, P. M.
• Format: Article
• Language: English
• Subjects: Base Sequence; Biological Sciences; Cancer; Cell Line; CpG Islands - genetics; Deoxyribonucleic acid; Discriminant analysis; DNA; DNA (Cytosine-5-)-Methyltransferase 1; DNA (Cytosine-5-)-Methyltransferases - genetics; DNA (Cytosine-5-)-Methyltransferases - metabolism; DNA Methylation; DNA, Neoplasm - genetics; DNA, Neoplasm - metabolism; Epigenetics; Gene Expression; Gene Silencing; Genes; Genes, Tumor Suppressor; Genetic loci; Genome, Human; Genomes; Genomics; Humans; Methane; Methylation; Neoplasms - genetics; Neoplasms - metabolism; Promoter Regions, Genetic; Tumors
• ISSN: 0027-8424; 1091-6490
• DOI: 10.1073/pnas.2037852100

Epigenetic silencing associated with aberrant methylation of promoter region CpG islands is one mechanism leading to loss of tumor suppressor function in human cancer. Profiling of CpG island methylation indicates that some genes are more frequently methylated than others, and that each tumor type is associated with a unique set of methylated genes. However, little is known about why certain genes succumb to this aberrant event. To address this question, we used Restriction Landmark Genome Scanning to analyze the susceptibility of 1,749 unselected CpG islands to de novo methylation driven by overexpression of DNA cytosine-5-methyltransferase 1 (DNMT1). We found that although the overall incidence of CpG island methylation was increased in cells overexpressing DNMT1, not all loci were equally affected. The majority of CpG islands (69.9%) were resistant to de novo methylation, regardless of DNMT1 overexpression. In contrast, we identified a subset of methylation-prone CpG islands (3.8%) that were consistently hypermethylated in multiple DNMT1 overexpressing clones. Methylation-prone and methylation-resistant CpG islands were not significantly different with respect to size, C+G content, CpG frequency, chromosomal location, or promoter association. We used DNA pattern recognition and supervised learning techniques to derive a classification function based on the frequency of seven novel sequence patterns that was capable of discriminating methylation-prone from methylation-resistant CpG islands with 82% accuracy. The data indicate that CpG islands differ in their intrinsic susceptibility to de novo methylation, and suggest that the propensity for a CpG island to become aberrantly methylated can be predicted based on its sequence context.