In addition, a recent report describing a novel protein expression defined a breast cancer subgroup which was mainly characterized by stromal/microenvironmental components. This subgroup termed “reactive I” consisted

primarily of a subset of luminal A tumors as defined by mRNA profiling with high caveolin-1 expression as the major feature [3]. Hierarchical clustering of expression levels of the four bootfs-selected proteins indicated that histologic G2 tumors do not form a separate group but rather display molecular features of histologic G1-like or G3-like samples as was previously also reported from gene expression profiling studies of human breast cancer [ [45] and [46]]. In order to assign individual tumor samples either to the low or high risk group of cancer relapse according AZD8055 ic50 Epacadostat purchase to the biomarker marker profile, a risk classification score named R2LC was developed. The performance of R2LC was successfully validated on an independent set of hormone receptor-positive tumors. Furthermore, analysis of differentially expressed genes of tumor samples with intermediate histologic grade revealed that R2LC was indeed able to separate this group into two distinct molecular entities. Differentially expressed genes were mainly involved in processes like cell division and response to hormone stimuli. In addition, it will be necessary to test the performance of the R2LC risk classification score on a tumor sample

set with appropriate disease-free survival information to evaluate R2LC for correct reclassification of histologic G2 tumor samples into low and high risk groups of cancer recurrence. Regulation of cell proliferation presents also the common driving force behind prognostic information provided by different gene expression signatures as reviewed by Ignatiadis and Sotiriou [47]. The St Gallen international expert consensus on the primary therapy of early breast cancer 2011 has acknowledged such findings

by suggesting the use of Ki-67 staining besides histologic grading as convenient approximation for risk classification in early stage luminal Tryptophan synthase breast cancer [48]. However, a recent study points out that Ki-67 quantification suffers from high inter- and intra-observer variabilities impeding the risk assessment especially for moderately differentiated breast carcinomas [49], further underlining the need to identify a robust and quantitative biomarker signature. Immunohistochemistry is routinely used in breast cancer to determine estrogen and progesterone receptor status as well as HER2 receptor status. Obtaining information on HER2 expression in addition to assessing hormone receptor status presents a widely accepted basis for therapeutic decisions [[50] and [51]]. However, little progress was made in recent years to translate newly identified biomarkers into immunohistochemistry-based scores that would be suitable for routine clinical application.