BACKGROUND: Basal-like (BL) breast cancer is an aggressive form of breast cancer with limited treatment options. Recent work has identified BL breast cancer as a biologically distinct form of triple-negative breast cancer, with a worse outlook. The receptor tyrosine kinase c-Met is a novel therapeutic target associated with reduced survival in breast cancer. Few studies have specifically addressed the association between c-Met and molecular subtype of breast cancer, yet this is a key consideration when selecting patients for clinical trials. The aim of this study is to evaluate c-Met expression in a large cohort of invasive breast cancers and in particular, its correlation with molecular subtype. METHODS: Immunohistochemistry for c-Met was performed and evaluated on 1274 invasive breast cancers using tissue microarray technology. The c-Met scores were correlated with molecular subtype, survival, and other standard clinicopathological prognostic factors. RESULTS: Multivariate logistic regression showed c-Met was independently associated with BL status (odds ratio=6.44, 95% confidence interval=1.74-23.78, P=.005). There was a positive correlation between c-Met and Her2 (P=.005) and an inverse correlation with tumor size (P<.001). C-Met was an independent poor prognostic factor at Cox regression analysis in all subtypes (hazard ratio=1.85, 95% confidence interval=1.07-3.19, P=.027) and there was a trend toward reduced survival in BL tumors overexpressing c-Met, but this was not significant. CONCLUSIONS: C-Met is independently associated with BL breast cancer. In the future, patients with BL tumors should be included in clinical trials of anti-c-Met therapy.
BACKGROUND: Basal-like (BL) breast cancer is an aggressive form of breast cancer with limited treatment options. Recent work has identified BL breast cancer as a biologically distinct form of triple-negative breast cancer, with a worse outlook. The receptor tyrosine kinase c-Met is a novel therapeutic target associated with reduced survival in breast cancer. Few studies have specifically addressed the association between c-Met and molecular subtype of breast cancer, yet this is a key consideration when selecting patients for clinical trials. The aim of this study is to evaluate c-Met expression in a large cohort of invasive breast cancers and in particular, its correlation with molecular subtype. METHODS: Immunohistochemistry for c-Met was performed and evaluated on 1274 invasive breast cancers using tissue microarray technology. The c-Met scores were correlated with molecular subtype, survival, and other standard clinicopathological prognostic factors. RESULTS: Multivariate logistic regression showed c-Met was independently associated with BL status (odds ratio=6.44, 95% confidence interval=1.74-23.78, P=.005). There was a positive correlation between c-Met and Her2 (P=.005) and an inverse correlation with tumor size (P<.001). C-Met was an independent poor prognostic factor at Cox regression analysis in all subtypes (hazard ratio=1.85, 95% confidence interval=1.07-3.19, P=.027) and there was a trend toward reduced survival in BL tumors overexpressing c-Met, but this was not significant. CONCLUSIONS: C-Met is independently associated with BL breast cancer. In the future, patients with BL tumors should be included in clinical trials of anti-c-Met therapy.
Authors: Mansoureh Sameni; Elizabeth A Tovar; Curt J Essenburg; Anita Chalasani; Erik S Linklater; Andrew Borgman; David M Cherba; Arulselvi Anbalagan; Mary E Winn; Carrie R Graveel; Bonnie F Sloane Journal: Clin Cancer Res Date: 2015-10-02 Impact factor: 12.531
Authors: Qin Ye; Andreana Holowatyj; Jack Wu; Hui Liu; Lihong Zhang; Takayoshi Suzuki; Zeng-Quan Yang Journal: Am J Cancer Res Date: 2015-03-15 Impact factor: 6.166
Authors: Julia Tchou; Yangbing Zhao; Bruce L Levine; Paul J Zhang; Megan M Davis; Jan Joseph Melenhorst; Irina Kulikovskaya; Andrea L Brennan; Xiaojun Liu; Simon F Lacey; Avery D Posey; Austin D Williams; Alycia So; Jose R Conejo-Garcia; Gabriela Plesa; Regina M Young; Shannon McGettigan; Jean Campbell; Robert H Pierce; Jennifer M Matro; Angela M DeMichele; Amy S Clark; Laurence J Cooper; Lynn M Schuchter; Robert H Vonderheide; Carl H June Journal: Cancer Immunol Res Date: 2017-11-06 Impact factor: 11.151
Authors: Sara M Tolaney; David R Ziehr; Hao Guo; Mei R Ng; William T Barry; Michaela J Higgins; Steven J Isakoff; Jane E Brock; Elena V Ivanova; Cloud P Paweletz; Michelle K Demeo; Nikhil H Ramaiya; Beth A Overmoyer; Rakesh K Jain; Eric P Winer; Dan G Duda Journal: Oncologist Date: 2016-10-27 Impact factor: 5.837