With the advent of microarray technologies, it is now possible to classify tumors based on their global patterns of gene expression. This type of research provides an unprecedented opportunity to improve our understanding of the molecular mechanisms leading to the development of cancer. Motivated by this same concept, we have recently developed a novel microarray technique, called differential methylation hybridization (DMH), which allows for the first time a global analysis of another type of molecular alteration, i.e., DNA methylation, in cancer. DNA methylation is known to be a frequent epigenetic event in cancer cells and has profound effects on the silencing of tumor-suppressor genes and genes responsible for genomic stability. Using breast cancer as an experimental model, our preliminary observation has shown that aberrant DNA methylation occurs in multiple GC-rich CpG island sequences. In addition, this aberrant event is not random and differential susceptibility of critical CpG island loci to DNA hypermethylation likely influences the development of different breast tumor subtypes. Thus, this discovery-driven study has led us to formulate the hypotheses that 1) hypermethylation of CpG island loci in tumor cells can generate unique molecular signatures that are associated with clinicopathological subtypes of breast cancer and 2) dissecting these complex epigenetic profiles can lead to the identification of tumor-suppressors that are silenced via DNA hypermethylation in breast cancer. To test these hypotheses, we will first conduct large-scale screening of aberrant methylation in 100 primary breast tumors and 6 breast cancer cell lines using a microarray panel containing 7,776 CpG island tags. Second, an advanced computation system will be developed to decipher epigenetic profiles of different breast cancer subtypes and identify candidate tumor-suppressor genes. Third, the methylation-associated silencing of these candidate loci will be confirmed in breast cancer cells in vitro. Last, molecular analysis will be conducted to determine functional consequences of the methylation-silenced genes in relation to breast tumor growth. The proposed research is expected to provide new information on the governing mechanisms of DNA methylation in cancer. Furthermore, our approach offers an alternative to cDNA microarrays for tumor classification and diagnosis. It should be noted that cDNA microarrays require targets derived from mRNA, which is more labile and difficult to obtain from biopsies. In contrast, the CpG island microarray uses DNA targets, which is more stable and easier to isolate from patients' specimens.
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