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Merck

Forkhead box A1 expression in breast cancer is associated with luminal subtype and good prognosis.

Journal of clinical pathology (2007-11-27)
M A Thorat, C Marchio, A Morimiya, K Savage, H Nakshatri, J S Reis-Filho, S Badve
ABSTRAKT

Forkhead box A1 (FOXA1) is a forkhead family transcription factor expressed in breast cancer cells. It is essential for optimal expression of approximately 50% of oestrogen receptor (ER)-related genes. This study explored the FOXA1 relationship with luminal and basal breast cancer subtypes, proliferation markers, and survival in breast cancer patients who had received similar treatment. A tissue microarray comprising tumours from 245 invasive breast cancer patients with 67 months of median follow-up was analysed for FOXA1 expression by immunohistochemistry. Interpretable FOXA1 expression, obtained in 184 patients, was analysed along with other variables such as tumour grade, size, nodal status, ER, progesterone receptor, HER2/neu, proliferation and basal markers. FOXA1 expression (score >3) was seen in 139 of 184 breast cancers. It correlated positively with ERalpha (p<0.0001), progesterone receptor (p<0.0001), and luminal subtype (p<0.0001); negatively with basal subtype (p<0.0001), proliferation markers and high histological grade (p = 0.0327). Univariate analysis showed nodal status, tumour grade, ER, progesterone receptor, FOXA1, basal markers and p53 as significant predictors of overall survival. Multivariate analysis showed that only nodal status (p = 0.0006) and ER (p = 0.0017) were significant predictors of OS. In luminal subtype patient subgroup, FOXA1 expression was associated with better survival (p = 0.0284) on univariate analysis. Based on this study in patients treated with surgery followed by adjuvant anthracycline-based chemotherapy, FOXA1 expression is associated with good prognosis. It correlates with luminal subtype breast cancer, and could possibly serve as a clinical marker for luminal subtype A. Prognostic ability of FOXA1 in these low-risk breast cancers may prove to be useful in treatment decision making.