Rethinking estrogen receptor evaluation in breast cancer: beyond binary classification

Estrogen receptor (ER) immunohistochemistry (IHC) represents a central indicator in the classification of breast cancer and in guiding therapeutic decision-making. However, despite the inherently continuous and heterogeneous nature of ER expression, it is often interpreted in routine clinical practice on the basis of fixed cut-off values. In particular, cases showing weak ER staining are not adequately positioned within current classification systems, posing challenges in both diagnosis and treatment selection. In this article, I re-examine ER immunohistochemistry from biological and pathological perspectives and propose a conceptual framework based on two independent parameters: the proportion of ER-positive tumour cells and ER staining intensity. These parameters should not be reduced to a single criterion or an additive scoring system, but rather interpreted as orthogonal axes within a continuous and multidimensional biological space. Within this framework, ER expression cannot be regarded as a direct indicator of cellular proliferative capacity, but instead should be positioned as a marker reflecting tumour cell differentiation status and functional heterogeneity. Evaluation of ER expression based on fixed cut-off values may oversimplify continuous biological phenomena and give rise to structural ambiguity in treatment selection, particularly in ER weakly positive tumours. This issue carries practical clinical significance in the current setting, where treatment algorithms presupposing ER status are incorporated into routine care. ER immunohistochemistry should therefore be understood not merely as a binary positive-negative test, but as a semi-quantitative and multidimensional descriptor of tumour biology. Separate documentation and evaluation of the proportion of ER-positive cells and staining intensity may provide clinically meaningful information beyond binary classification and offer a conceptual foundation for reconsidering the role of pathological assessment in therapeutic decision-making.