Biologic profiling of lymph node negative breast cancers by means of microRNA expression.

Breast cancer is a heterogeneous disease. Different subgroups can be recognized on the basis of the steroid receptors, HER-2, cytokeratin expression and proliferation patterns. As a result of mRNA-profiling studies, five major groups can be recognized, of which the triple-negative and basal-like tumors have the worst prognosis. Many of these tumors have a high proliferation that has the strongest prognostic value in node negative breast cancer. In the current study we analyzed the microRNA pattern in 103 lymph node negative breast cancers and compared these profiles with different biological characteristics and clinicopathological features. Unsupervised hierarchical cluster analysis divides the patients into four main groups, of which the basal-like/triple-negative group is the most prominent (11 % of all cases), the luminal A cancers containing the Her2 negative and estrogen receptor/progesterone receptor-positive tumors is the largest group (57%), and the group of luminal B (32%) is more heterogeneous and contains the Her2 positive/estrogen receptor-negative patients as well. The highest overall classification values by analysis of variance followed by cross validation (leave one sample out and reselect genes) were found for cytokeratin 5 and 6, triple-negative and estrogen receptor, with 97, 90 and 90% accuracy, respectively. MiR-106b gene is prominent in all of these signatures and correlates strongest with high proliferation. Other interesting observations are the presence of several microRNAs (miR532-5p, miR-500, miR362-5p, and miR502-3p) located at Xp11.23 in cancers with a triple-negative signature, and the upregulation of several miR-17 cluster members in estrogen receptor-negative tumors. The current study shows that estrogen receptor negativity and cytokeratin 5 and 6 expression are important, and specific biological processes in lymph node negative breast cancer, as microRNA signatures are strongest in these subgroups.