Department of Oncology, Zhongnan Hospital of Wuhan University, Wuchang District, Wuhan 430071, PR China.
Biomaterials. 2011 Oct;32(30):7592-9. doi: 10.1016/j.biomaterials.2011.06.029. Epub 2011 Jul 13.
The emerging molecular breast cancer (BC) classification based on key molecules, including hormone receptors (HRs), and human epidermal growth factor receptor 2 (HER2) has been playing an important part of clinical practice guideline. The current molecular classification mainly based on their fingerprints, however, could not provide enough essential information for treatment decision making. The molecular information on both patterns and quantities could be more helpful to heterogeneities understanding for BC personalized medicine. Here we conduct quantitative determination of HRs and HER2 by quantum dots (QDs)-based quantitative spectral analysis, which had excellent consistence with traditional method. Moreover, we establish a new molecular classification system of BC by integrating the quantitative information of HER2 and HRs, which could better reveal BC heterogeneity and identify 5 molecular subtypes with different 5-year prognosis. Furthermore, the emerging 5 molecular subtypes based on simple quantitative molecules information could be as informative as multi-genes analysis in routine practice, and might help formulate a more personalized comprehensive therapy strategy and prognosis prediction.
新兴的基于关键分子的分子乳腺癌（BC）分类，包括激素受体（HRs）和人表皮生长因子受体 2（HER2），在临床实践指南中发挥着重要作用。目前的分子分类主要基于它们的指纹，但不能为治疗决策提供足够的必要信息。BC 个体化医学更需要了解关于模式和数量的分子信息。在这里，我们通过基于量子点（QDs）的定量光谱分析来定量测定 HRs 和 HER2，这与传统方法具有极好的一致性。此外，我们通过整合 HER2 和 HRs 的定量信息，建立了一个新的 BC 分子分类系统，该系统能够更好地揭示 BC 的异质性，并识别出 5 种具有不同 5 年预后的分子亚型。此外，基于简单定量分子信息的新兴 5 种分子亚型与常规实践中的多基因分析一样具有信息量，可能有助于制定更个性化的综合治疗策略和预后预测。
