PURPOSE: Immunohistochemistry (IHC) is a newer technique for assessing the estrogen receptor (ER) status of breast cancers, with the potential to overcome many of the shortcomings associated with the traditional ligand-binding assay (LBA). The purpose of this study was to evaluate the ability of ER status determination by IHC, compared with LBA, to predict clinical outcome-especially response to adjuvant endocrine therapy-in a large number of patients with long-term clinical follow-up. PATIENTS AND METHODS: ER status was evaluated in 1,982 primary breast cancers by IHC on formalin-fixed paraffin-embedded tissue sections, using antibody 6F11 and standard methodology. Slides were scored on a scale representing the estimated proportion and intensity of positive-staining tumor cells (range, 0 to 8). Results were compared with ER values obtained by the LBA in the same tumors and to clinical outcome. RESULTS: An IHC score of greater than 2 (corresponding to as few as 1% to 10% weakly positive cells) was used to define ER positivity on the basis of a univariate cut-point analysis of all possible scores and disease-free survival (DFS) in patients receiving any adjuvant endocrine therapy. Using this definition, 71% of all tumors were determined to be ER-positive by IHC, and the level of agreement with the LBA was 86%. In multivariate analyses of patients receiving adjuvant endocrine therapy alone, ER status determined by IHC was better than that determined by the LBA at predicting improved DFS (hazard ratios/P = 0.474/.0008 and 0.707/.3214, respectively) and equivalent at predicting overall survival (0.379/.0001 and 0.381/.0003, respectively). CONCLUSION: IHC is superior to the LBA for assessing ER status in primary breast cancer because it is easier, safer, and less expensive, and has an equivalent or better ability to predict response to adjuvant endocrine therapy.
PURPOSE: Immunohistochemistry (IHC) is a newer technique for assessing the estrogen receptor (ER) status of breast cancers, with the potential to overcome many of the shortcomings associated with the traditional ligand-binding assay (LBA). The purpose of this study was to evaluate the ability of ER status determination by IHC, compared with LBA, to predict clinical outcome-especially response to adjuvant endocrine therapy-in a large number of patients with long-term clinical follow-up. PATIENTS AND METHODS: ER status was evaluated in 1,982 primary breast cancers by IHC on formalin-fixed paraffin-embedded tissue sections, using antibody 6F11 and standard methodology. Slides were scored on a scale representing the estimated proportion and intensity of positive-staining tumor cells (range, 0 to 8). Results were compared with ER values obtained by the LBA in the same tumors and to clinical outcome. RESULTS: An IHC score of greater than 2 (corresponding to as few as 1% to 10% weakly positive cells) was used to define ER positivity on the basis of a univariate cut-point analysis of all possible scores and disease-free survival (DFS) in patients receiving any adjuvant endocrine therapy. Using this definition, 71% of all tumors were determined to be ER-positive by IHC, and the level of agreement with the LBA was 86%. In multivariate analyses of patients receiving adjuvant endocrine therapy alone, ER status determined by IHC was better than that determined by the LBA at predicting improved DFS (hazard ratios/P = 0.474/.0008 and 0.707/.3214, respectively) and equivalent at predicting overall survival (0.379/.0001 and 0.381/.0003, respectively). CONCLUSION: IHC is superior to the LBA for assessing ER status in primary breast cancer because it is easier, safer, and less expensive, and has an equivalent or better ability to predict response to adjuvant endocrine therapy.
Authors: Zhao Zhang; Mauro E Cenciarini; Cecilia J Proietti; Yanming Wu; Matias Amasino; Tao Hong; Mei Yang; Yiji Liao; Huai-Chin Chiang; Virginia G Kaklamani; Rinath Jeselsohn; Ratna K Vadlamudi; Tim Hui-Ming Huang; Rong Li; Carmine De Angelis; Xiaoyong Fu; Patricia V Elizalde; Rachel Schiff; Myles Brown; Kexin Xu Journal: Cancer Res Date: 2017-12-06 Impact factor: 12.701
Authors: Joshua I Warrick; Matthew Kaag; Jay D Raman; Wilson Chan; Truc Tran; Sudhir Kunchala; Lauren Shuman; David DeGraff; Guoli Chen Journal: Virchows Arch Date: 2017-07-18 Impact factor: 4.064
Authors: E Fiore; E Giustarini; C Mammoli; F Fragomeni; D Campani; I Muller; A Pinchera; C Giani Journal: J Endocrinol Invest Date: 2007-10 Impact factor: 4.256
Authors: Veronique F Cocquyt; Vera R Schelfhout; Phillip N Blondeel; Herman T Depypere; Kristof K Daems; Rudolphe F Serreyn; Marleen M Praet; Simon J P Van Belle Journal: Med Oncol Date: 2003 Impact factor: 3.064