Predicitive DNA Methylation Markers in Breast Cancer

The treatment of breast cancer is complex and involves surgery, radiation, chemotherapy, and hormonal therapy, used singly or in combination, depending on the stage and estrogen-receptor status of the disease in the individual patient. Tamoxifen, a selective estrogen-receptor modulator (SERM) is a mainstay of the hormonal treatment of all phases of estrogen receptor positive breast cancer. Many estrogen receptor-positive breast cancer patients initially respond to the treatment, but remissions are often followed by acquisition of resistance and ultimately disease relapse. Aberrant CpG island methylation of multiple genes occurring in a nonrandom manner during tumour development and during the acquisition of drug resistance provides a mechanism whereby expression of multiple genes could be affected simultaneously resulting in antihormonal resistance. The development of a rationale for the effective treatment of tamoxifen-resistant breast cancer requires an understanding of the complex signal transduction mechanisms that contribute towards loss of antiestrogen response. The finding of predictive biomarkers for the identification of tamoxifen-resistant patients could have important implications for the individualization of therapy. The aim of this study is to carry out a genome-wide screening study for identification of hypermethylated genes in tamoxifen-resistant breast cancer cell-lines. Hypermethylated and silenced genes should be reactivated in the tamoxifen resistant cell lines by treatment with 5-aza-2`-deoxycytidine, a DNA methyltransferase inhibitor, and identified on expression microarrays by comparison of untreated, drug-treated and the tamoxifen-sensitive parental cell-lines. Candidate genes proven to be significantly differentially expressed and hypermethylated from these studies will then be analyzed in DNA from paraffin embedded tissues obtained from patients with antihormonal- resistant and responsive breast cancer, to evaluate their potential as biomarkers for individualization of treatment.