Abstract:
The Canadian Cancer Society estimates that 13 Canadian women will die from breast cancer every day. Epigenetic modifications, like aberrant DNA methylation contribute to breast cancer progression and must be addressed to improve patient outcomes. DNA hypermethylation can inhibit the expression of tumor suppressor genes (TSGs), which contributes to the development and progression of cancer. Using a de-methylating agent such as decitabine (5-aza-2'-deoxycytidine), results in the re-expression or induction of TSGs. Although this effect has been well documented in cancer, it may not be the main contributor to decitabine sensitivity. Other aspects of decitabine treatment, such as the induction of an interferon response have also been suggested as contributors to decitabine sensitivity. Using a representative panel of breast cancer cell lines with varying sensitivities to decitabine, these possible effects of decitabine will be evaluated to reveal their value in predicting decitabine response. Using quantitative polymerase chain reaction (qPCR), expression of genes associated with TSG induction and the interferon response were analyzed to reveal the predominate class of genes that are induced upon treatment. It was found that neither class of gene was indicative of decitabine sensitivity. Alternative factors that might predict decitabine sensitivity were evaluated; these factors all have well-established roles in decitabine’s mode-of-action. Decitabine must be imported, processed and incorporated into the DNA. It was found that incorporation into the DNA is also not predictive of decitabine sensitivity. Next, genes associated with import/export, processing and de-methylating effects of decitabine were evaluated for any association with decitabine sensitivity. Relatively strong correlations with the import gene SLC28A1, the processing gene DCK as well as the DNMT1A and DNMT3B demethylating genes were found. This suggests that these four genes may be important mediators of decitabine sensitivity in breast cancer, and could be useful in predicting patient response to this new therapy.