Patterns of DNA methylation in human cells are crucial in regulating tumor growth and can be indicative of breast cancer susceptibility. In our research, we have pinpointed genes with significant methylation variation in the breast cancer epigenome to be used as potential novel biomarkers for breast cancer susceptibility.
Using the statistical software package R, we compare DNA methylation sequencing data from seven normal individuals with eight breast cancer cell lines. This is done by selecting CG sites, or cytosine-guanine pairings, at which normal cell and cancer cell variation patterns fall in different ranges, and by performing upper one-tailed chi-square tests. These selected CG sites are mapped to their corresponding genes. Using the Consensus Path Database software, we generate genetic pathways with our data to study biological relations between our selected genes and tumorigenic cellular mechanisms.
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