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 de methylating 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.