Abstract

Abstract Abstract #5068 Background: Breast cancers are traditionally divided into hormone receptor positive and negative cases that guide patient management. The two luminal subtypes in gene expression profiling , A and B, are defined by high expression of ER, GATA3, and FOXA1. There is a little doubt that ER status is a strong predictor of response to endocrine therapy. Prognostic immunohistochemical biomarkers for ER-positive breast cancer include progesterone (PR) and androgen (AR) receptors, proteins related to proliferation or apoptotic resistance. The aim of this study was to identify the best predictors of success of hormonal therapy among immunohistochemical and classical factors.
 Methods: We studied 10 markers in a consecutive series of 832 cases of breast carcinoma treated at the Paoli-Calmettes Institute from 1990 to 2002 and deposited onto tissue-micro arrays (TMA): luminal-related ER, PR, AR, FOXA1, and GATA3 factors, proliferation-related KI67 and CCND1, ERBB2, anti-apoptotic BCL2, and p53. We also measured the vascular peritumoral invasion (VPI) size, Grade and lymph nodes involvement (N). On these series 145 cases had been profiled on Affymetrix microarrays. The patients had been treated with adjuvant chemotherapy and/or hormonal therapy . The 132 events observed and taken into account were metastases (MF).
 Results: Of the 67 luminal A cases of this series 63 were ER-positive, 98% were FOXA1-positive; only half of them expressed the five luminal-related markers. In 584 ER-positive patients, 200 did not receive adjuvant hormonal therapy with a highly significant difference in MF with those who received Tamoxifen (p=0.017). For the 240 cases who received hormonal therapy, the factors associated to the MF in multivariate analysis were:
 
 A prognostic score can be established summing the impact of each four parameters with a significant Logrank test : p= 0.0003.
 
 Discussion: A panel of three antibodies (Ki67, P53 and GATA3), associated with VPI can significantly improve the traditional prognosticators in predicting outcome for ER-positive breast cancer patients receiving hormonal therapy. Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 5068.

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