There is substantial variability in women's risk of breast cancer due to differences in exogenous factors and enormous variation in underlying familial, including genetic/epigenetic susceptibility. Recent advances in tools for genetic and epigenetic studies of complex diseases are facilitating work to uncover components that together determine where a woman might be placed on the wide population breast cancer risk spectrum.
We have conducted a case-control study of breast cancer nested within the Melbourne Collaborative Cohort Study involving the measurement of methylation across the genome using the HM450K Beadchip assay on DNA extracted from blood (collected at baseline) from women subsequently diagnosed with breast cancer and women unaffected by breast cancer during follow-up. The odds ratio for breast cancer (OR) associated with the fourth versus first quartile of global DNA methylation was 0·45 (95% CI 0·22-0·93). Higher global DNA methylation of CpGs within functional gene promoters was associated with an increased risk whereas higher global DNA methylation at genomic regions outside promoters was associated with decreased risk. Tests for association between specific methylation marks and breast cancer risk have been explored using conditional logistic regression adjusting for age and principal components and have identified a number of putative (biologically feasible) marks associated with breast cancer risk.
We have also (via modest protocol modifications) applied the HM450K Breadchip assay to the corresponding breast cancers (FFPE) from the affected women in the case-control study. The data reflect the anticipated relationship between breast cancer subtypes (defined by expression profiles) and methylation profiles. They also illustrate the heterogeneity of such breast cancer subtypes and identify marks that are differentially methylated between subtypes.
These datasets provide exciting opportunities for improving our risk prediction modeling via integration with other corresponding datasets such a genetic, lifestyle and mammographic density measures and moves towards a further realization of increasing precision in public health practice.