E‐cadherin expression in invasive non‐lobular carcinoma of the breast and its prognostic significance

Abstract

E-cadherin is a cell adhesion molecule that is expressed in normal breast tissue and is often considered useful as a phenotypic marker in breast cancer diagnosis, with absence of its expression frequently observed in tumours of lobular subtype. However, the clinicopathological and prognostic value of E-cadherin in the more frequent non-lobular types of breast carcinoma is unclear. E-cadherin expression was assessed immunohistochemically in a large and well-characterized series of invasive non-lobular breast carcinoma types (n=1665) with long-term clinical follow-up (median 56 months) using tissue microarray technology, to determine the relationship between its expression and primary tumour characteristics and disease outcome. Only membranous expression of E-cadherin was considered in this study and its expression was categorized as normal (H-score>100) or reduced [absent or below the median (score</=100)]. Complete absence of its expression (score=0) was detected in 7.2% of cases. On univariate analysis, reduced E-cadherin expression was associated with a reduced disease-free interval and overall survival and also with indicators of poor prognosis including larger tumour size, higher histological grade, development of distant metastasis and tumours negative for oestrogen receptors. No association between E-cadherin expression and lymph node status was found. On multivariate analysis, E-cadherin was an independent predictor of disease-free interval [hazards ratio (HR) 1.56, 95% confidence intrerval (CI) 1.23, 1.99; P<0.001] and overall survival (HR 1.53, 95% CI 1.09, 2.14; P=0.013) and there was some evidence that the prognostic value was greater in those with positive lymph nodes (P interaction=0.099). These results suggest that E-cadherin loss may play a role in progression, development of distant metastasis and recurrence in non-lobular invasive carcinomas of the breast and its assessment by immunohistochemistry may help in the identification of patients with poor outcomes.