c-erbB-2 oncoprotein overexpression identifies a subgroup of estrogen receptor positive (ER+) breast cancer patients with poor prognosis

Purpose: To investigate the predictive value of c-erbB-2 oncoprotein expression as compared with established histopathological and cytometric indicators of disease evolution in breast carcinoma. Patients and methods: A short-term retrospective study was conducted on a series of 306 breast cancer patients. Classic prognostic factors included tumour size, nodal involvement, histological grading, and hormone receptor status. Flow cytometric DNA ploidy and S-phase fraction (SPF) were also assessed. A Cox proportional hazards regression model was used for multivariate statistical analysis. Results: c-erbB-2 overexpression was present in 43 out of 295 (14.6%) tumours, and showed a statistically significant correlation with high histological grade, DNA aneuploidy, high SPF and lack of estrogen receptors (ER). Univariate analysis revealed its association with worse disease-free survival (DFS) and overall survival (OS). The combined evaluation of c-erbB-2 with ploidy and SPF defines a variable (P + S + c) that showed a significant correlation with disease outcome. By multivariate analysis, only nodal status (P < 0.001) and P + S + c subgrouping (group 2: P = 0.002; group 3: P = 0.001) in relation to DFS, and nodal status (P = 0.001) and DNA ploidy (P = 0.006) in relation to OS, retained independent prognostic significance. Subset analyses showed that cytometric parameters, P + S + c subgrouping and hormone receptors were significantly correlated with disease outcome in node-positive patients, whereas in node-negative subgroup no prognostic indicators were found. c-erbB-2 overexpression exhibited a trend in node-positive breast cancer (DFS: P = 0.068; OS: P = 0.086), and significant correlation with poor clinical evolution in ER positive patients (DFS: P = 0.015; OS: P = 0.004), mostly receiving tamoxifen. Conclusions: c-erbB-2 is an independent prognostic indicator of DFS when evaluated in conjunction with ploidy and SPF. It also seems to predict response to tamoxifen therapy, by identifying a subgroup of ER positive (ER+) breast cancer patients with poor prognosis.