Accurate classification is fundamental for breast cancer (BC) personalized care. Current BC classification based on the either traditional morphological staging or molecular signatures seems inefficient to reveal the"true"behaviors of invasive BC evolution. An appropriate approach combining the macro- and micro-pathologic information might be more useful academically as well as clinically. Here we explore a holistic approach by integrating a key molecular prognostic indicator of BC, HER2, with quantitative determination using quantum dots (QDs)--based nanotechnology and spectral analysis, and a key macropathologic indicator, tumor size, resulting a new indicator, total HER2 load. This indicator might better reveal BC heterogeneity and new subtypes of BC with different 5-year disease-free survival compared with current methods, which could be helpful in formulating a more personalized targeted therapy for BC. Furthermore, this mode integrating macro- and micro-pathological indicators might help gain new insights into invasive BC biological behaviors.
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