Methylated genes in breast cancer: associations with clinical and histopathological features in a familial breast cancer cohort.

BACKGROUND

Hundreds of hypermethylated genes have been described in breast cancer, yet the nature and contribution of these genes in their methylated state to overall risk and prognosis is under-characterized in non-sporadic breast cancers. We therefore compared associations of DNA methylation with tumor stage, hormone/growth receptor status, and clinical outcomes in a familial breast cancer cohort. Because few previous methylation studies have considered the oncogenic or tumor suppressor properties of their gene sets, this functional status was included as part of our correlative analysis.

RESULTS

We found methylation of oncogenes was associated with better prognostic indicators, whereas tumor suppressor gene methylation was associated with a more severe phenotype in women that were either HER2+ or lymph node positive at diagnosis, and/or tended to recur or develop distant metastases. For example, the methylation of the tumor suppressor gene APC was strongly associated with a specific subset of tumors that were both ER+ and HER2+, while methylation of the TWIST oncogene was associated with breast cancers that did not metastasize.

METHODS

This was a retrospective, hospital-based study of n = 99 archival breast tumors derived from women with a germline genetic BRCA1 or BRCA2 mutation and/or familial breast cancer history. DNA methylation was quantified from formalin fixed, paraffin embedded tumors using the established protocol of quantitative multiplex-methylation specific PCR (QM-MSP). Non-parametric statistics were used to analyze candidate gene methylation in association with clinical outcomes.

CONCLUSION

We report several novel, positive associations between percent methylation of the APC, RASSF1A, TWIST, ERα, CDH1, and Cyclin D2 genes and key variables such as tumor stage, hormone and growth receptor status, and a history of recurrent or metastatic disease. Our data suggest the potential utility of parsing gene methylation by functional status and breast tumor subtype.