RESUMO
Background : Normal breast ducts contain at least 3 types of epithelial cells: luminal (glandular) cells, basal/myoepithelial cells and stem cells. Myoepithelial and luminal epithelia can be distinguished by their different cytokeratin expression patterns. The aim of this study is to evaluate the expression of some prognostic biomarkers (ER, PR and HER2), as well as histological grading and lymph node status in cytokeratin-based groups of breast cancer. Objective: To evaluate the correlation between expression of basal and luminal markers and hormonal receptors, HER2/neu, age, grade and lymph node status in breast-invasive ductal carcinoma. Materials and Methods : Sixty-seven formalin-fixed and paraffin-embedded breast cancer specimens (of invasive ductal carcinoma, 'NOS' type) which had already been studied for ER, PR and HER2/neu were selected. Data concerning age, tumor grade and lymph node status were also obtained from archives. Expression of basal (CK5/6) and luminal (CK7) cytokeratins was detected by immunohistochemistry. Stained sections were classified according to the intensity of staining and the percentage of stained cells. Results : We categorized the cases into 3 distinct phenotype groups: pure luminal, basal phenotype and null. Pure basal, mixed basal and luminal groups were classified as expressing a basal phenotype. There was a significant difference in the ER and/or PR expression between those 3 groups and a significant association between ER and/or PR negativity and basal phenotype expression. There was no significant difference in HER2/neu expression, age of the patients, tumor grade and lymph node status between the 3 cytokeratin-based groups and no significant association between lymph node status and basal phenotype expression. Conclusion : We found that to gain a real association between basal phenotype and prognostic markers, we should use a cocktail or a panel of different biomarkers to correctly determine basal-like phenotype of breast cancers. This approach guarantees more concordance with gene expression-based studies.