Department of Oncology, Zhongnan Hospital of Wuhan University, No 169 Donghu Road, Wuchang District, Wuhan 430071, PR China.
Biomaterials. 2010 Nov;31(33):8818-25. doi: 10.1016/j.biomaterials.2010.07.091. Epub 2010 Aug 17.
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.
准确的分类对于乳腺癌(BC)的个性化护理至关重要。目前基于传统形态学分期或分子特征的 BC 分类方法似乎无法有效揭示浸润性 BC 演进的“真实”行为。一种将宏观和微观病理信息相结合的适当方法,在学术和临床方面可能更有用。在这里,我们通过整合乳腺癌的一个关键分子预后指标 HER2 以及使用量子点(QDs)--基于纳米技术和光谱分析的定量测定,以及一个关键的宏观病理指标肿瘤大小,得到了一个新的指标,总 HER2 负荷。与目前的方法相比,这个指标可能更好地揭示了 BC 的异质性和不同 5 年无病生存率的新亚型,这有助于为 BC 制定更个性化的靶向治疗方案。此外,这种整合宏观和微观病理指标的模式可能有助于深入了解浸润性 BC 的生物学行为。