Molecular subtyping of breast cancer from traditional tumor marker profiles using parallel clustering methods

PURPOSE: Recent small-sized genomic studies on the identification of breast cancer bioprofiles have led to profoundly dishomogeneous results. Thus, we sought to identify distinct tumor profiles with possible clin. relevance based on clusters of immunohistochem. mol. markers measured on a large, single institution, case series. Exptl. Design: Tumor biol. profiles were explored on 633 archival tissue samples analyzed by immunohistochem. Five validated markers were considered, i.e., estrogen receptors (ER), progesterone receptors (PR), Ki-67/MIB1 as a proliferation marker, HER2/NEU, and p53 in their original scale of measurement. The results obtained were analyzed by three different clustering algorithms. Four different indexes were then used to select the different profiles (no. of clusters). RESULTS: The best classification was obtained creating four clusters. Notably, three clusters were identified according to low, intermediate, and high ER/PR levels. A further subdivision in two biol. distinct subtypes was detd. by the presence/absence of HER2/NEU and of p53. As expected, the cluster with high ER/PR levels was characterized by a much better prognosis and response to hormone therapy compared to that with the lowest ER/PR values. Notably, the cluster characterized by high HER2/NEU levels showed intermediate prognosis, but a rather poor response to hormone therapy. CONCLUSIONS: Our results show the possibility of profiling breast cancers by means of traditional markers, and have novel clin. implications on the definition of the prognosis of cancer patients. These findings support the existence of a tumor subtype that responds poorly to hormone therapy, characterized by HER2/NEU overexpression. [on SciFinder (R)]