PURPOSE: The prognosis of a patient with estrogen receptor (ER) and/or progesterone receptor (PR) -positive breast cancer can be highly variable. Therefore, we developed a gene expression-based outcome predictor for ER+ and/or PR+ (ie, luminal) breast cancer patients using biologic differences among these tumors. MATERIALS AND METHODS: The ER+ MCF-7 breast cancer cell line was treated with 17beta-estradiol to identify estrogen-regulated genes. These genes were used to develop an outcome predictor on a training set of 65 luminal epithelial primary breast carcinomas. The outcome predictor was then validated on three independent published data sets. Results The estrogen-induced gene set identified in MCF-7 cells was used to hierarchically cluster a 65 tumor training set into two groups, which showed significant differences in survival (P = .0004). Supervised analyses identified 822 genes that optimally defined these two groups, with the poor-prognosis group IIE showing high expression of cell proliferation and antiapoptosis genes. The good prognosis group IE showed high expression of estrogen- and GATA3-regulated genes. Mean expression profiles (ie, centroids) created for each group were applied to ER+ and/or PR+ tumors from three published data sets. For all data sets, Kaplan-Meier survival analyses showed significant differences in relapse-free and overall survival between group IE and IIE tumors. Multivariate Cox analysis of the largest test data set showed that this predictor added significant prognostic information independent of standard clinical predictors and other gene expression-based predictors. CONCLUSION: This study provides new biologic information concerning differences within hormone receptor-positive breast cancers and a means of predicting long-term outcomes in tamoxifen-treated patients.
PURPOSE: The prognosis of a patient with estrogen receptor (ER) and/or progesterone receptor (PR) -positive breast cancer can be highly variable. Therefore, we developed a gene expression-based outcome predictor for ER+ and/or PR+ (ie, luminal) breast cancerpatients using biologic differences among these tumors. MATERIALS AND METHODS: The ER+ MCF-7 breast cancer cell line was treated with 17beta-estradiol to identify estrogen-regulated genes. These genes were used to develop an outcome predictor on a training set of 65 luminal epithelial primary breast carcinomas. The outcome predictor was then validated on three independent published data sets. Results The estrogen-induced gene set identified in MCF-7 cells was used to hierarchically cluster a 65 tumor training set into two groups, which showed significant differences in survival (P = .0004). Supervised analyses identified 822 genes that optimally defined these two groups, with the poor-prognosis group IIE showing high expression of cell proliferation and antiapoptosis genes. The good prognosis group IE showed high expression of estrogen- and GATA3-regulated genes. Mean expression profiles (ie, centroids) created for each group were applied to ER+ and/or PR+ tumors from three published data sets. For all data sets, Kaplan-Meier survival analyses showed significant differences in relapse-free and overall survival between group IE and IIE tumors. Multivariate Cox analysis of the largest test data set showed that this predictor added significant prognostic information independent of standard clinical predictors and other gene expression-based predictors. CONCLUSION: This study provides new biologic information concerning differences within hormone receptor-positive breast cancers and a means of predicting long-term outcomes in tamoxifen-treated patients.
Authors: Maïa Chanrion; Vincent Negre; Hélène Fontaine; Nicolas Salvetat; Frédéric Bibeau; Gaëtan Mac Grogan; Louis Mauriac; Dionyssios Katsaros; Franck Molina; Charles Theillet; Jean-Marie Darbon Journal: Clin Cancer Res Date: 2008-03-15 Impact factor: 12.531
Authors: Julie A Vendrell; Katherine E Robertson; Patrice Ravel; Susan E Bray; Agathe Bajard; Colin A Purdie; Catherine Nguyen; Sirwan M Hadad; Ivan Bieche; Sylvie Chabaud; Thomas Bachelot; Alastair M Thompson; Pascale A Cohen Journal: Breast Cancer Res Date: 2008-10-17 Impact factor: 6.466
Authors: Marc A Bollet; Alexia Savignoni; Leanne De Koning; Carine Tran-Perennou; Catherine Barbaroux; Armelle Degeorges; Brigitte Sigal-Zafrani; Geneviève Almouzni; Paul Cottu; Rémy Salmon; Nicolas Servant; Alain Fourquet; Patricia de Cremoux Journal: Breast Cancer Res Date: 2009-07-28 Impact factor: 6.466