Forkhead box protein A1 (FOXA1) is a "pioneer factor" that plays a role in controlling nearly 50% of estrogen receptor target genes. FOXA1 expression correlates with estrogen receptor (ER)-positivity especially in luminal subtype A breast cancers. The aim of this study was to investigate the precise role of FOXA1 in breast cancer using a large population-based cohort. Nuclear expression of FOXA1 was analyzed in a tissue microarray of 4,444 invasive breast cancer cases using immunohistochemistry and correlated with clinicopathologic variables using previously described methods and cutoff points. The entire cohort was equally divided into a training and validation set. All survival analyses were performed using a previously defined cutoff (3) for validation. Additional X-tile analysis performed to analyze prognostic effects of low and high FOXA1 levels identified 24 as a cutoff. Bonferroni-Holmes test was used as appropriate. FOXA1 expression significantly correlated positively with markers of good prognosis or ER-positivity, and negatively with tumor size, tumor grade, nodal status, Ki67, HER2 expression, and basal subtype (each P value <0.0001). In both survival analyses, FOXA1 was a significant predictor of breast cancer-specific survival (P < 0.0001) and relapse-free survival (P < 0.0001). FOXA1 was also an independent predictor of breast cancer-specific survival at 10 years using both cutoffs. Among the ER-positive subgroup treated with tamoxifen, FOXA1 was an independent prognostic marker using the 24 cutoff (P = 0.030). FOXA1 is a significant marker of good prognosis in breast cancer; it also identifies a subset of ER-positive tamoxifen treated patients at low risk of recurrence.

Initially recognized through microarray-based gene expression profiling, basal-like breast cancer, for which we lack effective targeted therapies, is an aggressive form of carcinoma with a predilection for younger women. With some success, immunohistochemical studies have attempted to reproduce the expression profile classification of breast cancer through identification of subtype-specific biomarkers. This review aims to present an in depth summary and analysis of the current status of basal-like breast cancer biomarker research. While a number of biomarkers show promise for future clinical application, the next logical step is a comprehensive investigation of all biomarkers against a gene expression profile gold standard for breast cancer subtype assignment.