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BMC Cancer. 2007 Jun 14;7:99.

Polymorphisms cMyc-N11S and p27-V109G and breast cancer risk and prognosis.

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Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada.



cMyc and p27 are key genes implicated in carcinogenesis. Whether polymorphisms in these genes affect breast cancer risk or prognosis is still unclear. In this study, we focus on a rare non-synonymous polymorphism in cMyc (N11S) and a common polymorphism in p27 (V109G) and determine their role in risk and prognosis using data collected from the Ontario Breast Cancer Family Registry.


Risk factor data was collected at baseline on a large group of women (cases = 1,115 and population-based controls = 710) and clinical data (including treatment and follow-up) were collected prospectively by periodic review of medical records for a subset of cases (N = 967) for nearly a decade. A centralized pathology review was conducted. Unconditional logistic regression was used to determine the association of polymorphisms with breast cancer risk and the Cox proportional hazards model was used to determine their association with survival.


Our results suggest that while cMyc-N11S can be considered a putatively functional polymorphism located in the N-terminal domain, it is not associated with risk, tumor characteristics or survival. The p27-G109 allele was associated with a modest protective effect in adjusted analyses and higher T stage. We found no evidence to suggest that p27-V109G alone or in combination with cMyc-N11S was associated with survival. Age at onset and first-degree family history of breast or ovarian cancer did not significantly modify the association of these polymorphisms with breast cancer risk.


Further work is recommended to understand the potential functional role of these specific non-synonymous amino acid changes and a larger, more comprehensive investigation of genetic variation in these genes (e.g., using a tagSNP approach) in combination with other relevant genes is needed as well as consideration for treatment effects when assessing their potential role in prognosis.

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