Recent studies on gene molecular profiling using cDNA microarray in a relatively small series of breast cancer have identified biologically distinct groups with apparent clinical and prognostic relevance. The validation of such new taxonomies should be confirmed on larger series of cases prior to acceptance in clinical practice. The development of tissue microarray (TMA) technology provides methodology for high-throughput concomitant analyses of multiple proteins on large numbers of archival tumour samples. In our study, we have used immunohistochemistry techniques applied to TMA preparations of 1,076 cases of invasive breast cancer to study the combined protein expression profiles of a large panel of well-characterized commercially available biomarkers related to epithelial cell lineage, differentiation, hormone and growth factor receptors and gene products known to be altered in some forms of breast cancer. Using hierarchical clustering methodology, 5 groups with distinct patterns of protein expression were identified. A sixth group of only 4 cases was also identified but deemed too small for further detailed assessment. Further analysis of these clusters was performed using multiple layer perceptron (MLP)-artificial neural network (ANN) with a back propagation algorithm to identify key biomarkers driving the membership of each group. We have identified 2 large groups by their expression of luminal epithelial cell phenotypic characteristics, hormone receptors positivity, absence of basal epithelial phenotype characteristics and lack of c-erbB-2 protein overexpression. Two additional groups were characterized by high c-erbB-2 positivity and negative or weak hormone receptors expression but showed differences in MUC1 and E-cadherin expression. The final group was characterized by strong basal epithelial characteristics, p53 positivity, absent hormone receptors and weak to low luminal epithelial cytokeratin expression. In addition, we have identified significant differences between clusters identified in this series with respect to established prognostic factors including tumour grade, size and histologic tumour type as well as differences in patient outcomes. The different protein expression profiles identified in our study confirm the biologic heterogeneity of breast cancer and demonstrate the clinical relevance of classification in this manner. These observations could form the basis of revision of existing traditional classification systems for breast cancer. ' 2005 Wiley-Liss, Inc.Key words: breast cancer; classification; protein expression; tissue microarray Routine clinical management of breast cancer relies on traditional histopathologic classification including tumour grade, histologic tumour type, carcinoma size and lymph node stage. Despite the overall association of these variables with prognosis and outcome, 1 these systems remain relatively weakly predictive of behaviour in some circumstances. Tumours of apparently homogenous morphologic character vary in response to therapy and have divergent outc...

BACKGROUND: Although lymphovascular invasion (LVI) has been associated with a poor outcome in patients with breast cancer, it is not included in most internationally recognized staging systems, including the American Joint Committee on Cancer tumor, lymph node, metastasis (TNM) classification. This is mainly because it remains unclear whether the presence of LVI is an independent, high-risk criterion in clinically relevant staging subgroups. METHODS: The current study was based on a large and well characterized consecutive series of patients who had operable (pathologic T1 [pT1]-pT2, pathologic N0 [pN0]-pN3, M0) breast cancer (3812 informative cases) who were treated according to standard protocols at a single institution and who had long-term follow-up to assess the prognostic value of definite LVI in clinically and molecularly relevant staging subgroups. RESULTS: LVI was strongly associated with both breast cancer-specific survival (BCSS) and distant metastasis-free survival (DMFS) in the entire series and in different subgroups. Multivariate analyses identified LVI as an independent predictor of both BCSS and DMFS in patients with operable breast cancer overall; in the TNM clinical subgroups pT1a-pT1c/pN0 and pT2/pN0; and in the molecular classes estrogen receptor (ER)-positive, ER-negative, human epidermal growth factor 2 [HER2]-negative, and triple-negative. In patients who had lymph node-negative tumors, LVI could be used as a high-risk criterion providing survival disadvantage equivalent to that provided by 1 or 2 involved lymph nodes (pN0 to pN1) and to that provided by 1 size category (pT1 to pT2). The use of immunohistochemistry for detecting an endothelial-specific marker contributed to the prognostic significance of LVI when applied to routine LVI negative/possible cases. CONCLUSIONS: LVI provided a strong predictor of outcome in patients with invasive breast cancer and should be incorporated into breast cancer staging systems.

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