Flow cytometry: a new approach for the molecular profiling of breast cancer

The established method in prognosis of breast cancer includes detection of molecular markers, such as the estrogen receptor (ER), progesterone receptor (PR), and HER-2/neu. These markers are routinely checked via immunohistochemistry (IHC). HER-2/neu is also detected by fluorescent in situ hybridization (FISH). Flow cytometric analysis has not yet been used for detection of such markers. Flow cytometry was performed on four established breast cancer cell lines: MCF7, T47D, BT474, MDA-MB-231, and on one normal breast epithelial cell line: MCF10A. Flow cytometric analysis was used for the detection of ER, PR, HER-2/neu, epidermal growth factor receptor (EGFR), and E-cadherin. Currently, EGFR and E-cadherin are not standard predictive factors in determining survival of breast cancer patients, but both may be beneficial to prognosis. Cells undergoing flow cytometric analysis lost marker expression with increasing passage number. The highest expression was found at cells passaged 0-1 times. MCF7, T47D, and BT474 all had similar marker expression patterns. E-cadherin demonstrated a strongly positive pattern with marker expression of 85-92% among the three cell lines. ER, PR, and HER-2/neu demonstrated a weakly positive expression pattern when compared with E-cadherin. Marker expression ranged from 15 to 61%. These three cell lines were almost negative for expression of EGFR where expression ranged from 0 to 6%. MDA-MB-231 had almost no expression of all 5 markers, with positive values ranging from 0 to 5%. MCF10A had weak positive to almost negative expression values of ER, PR, HER-2/neu, and E-cadherin, which ranged from 3 to 13%. EGFR, both surface and cytoplasmic markers, again were not expressed in MCF10A cells with an expression value of <1%. We found that ER, PR, and HER-2/neu marker expressions in 5 out of 5 cell lines were consistent with established expression patterns. EGFR and E-cadherin expression in 4 out of 5 cell lines were also consistent with established expression patterns. We have shown that flow cytometry provides quantitative data on expression patterns of important prognostic markers in breast cancer.