Correa Geyer Felipe, Reis-Filho Jorge Sergio
Molecular Pathology Laboratory, Breakthrough Breast Cancer Research Centre, Institute of Cancer Research, London, UK.
Int J Surg Pathol. 2009 Aug;17(4):285-302. doi: 10.1177/1066896908328577. Epub 2008 Dec 22.
Breast cancer is a heterogeneous disease, encompassing several histological types and clinical behaviors. Current histopathological classification systems are based on descriptive entities with prognostic significance. Few prognostic and predictive markers beyond those offered by histopathological analysis are available. High-throughput molecular technologies are reshaping our understanding of breast cancer, of which microarray-based gene expression has received most attention. This method has been used to derive a molecular taxonomy for breast cancer, which has provided interesting insights into the biology of the disease. Class prediction studies have generated a multitude of prognostic/predictive signatures, which herald the promise for an improvement in treatment decision making. However, most of the signatures developed to date seem to have discriminatory power almost restricted to estrogen receptor-positive disease. This review addresses the contribution of gene expression profiling to our understanding of breast cancer and its clinical management.
乳腺癌是一种异质性疾病,涵盖多种组织学类型和临床行为。当前的组织病理学分类系统基于具有预后意义的描述性实体。除了组织病理学分析所提供的标志物外,可用的预后和预测标志物很少。高通量分子技术正在重塑我们对乳腺癌的理解,其中基于微阵列的基因表达受到了最多关注。该方法已被用于推导乳腺癌的分子分类法,这为该疾病的生物学特性提供了有趣的见解。类别预测研究已经产生了大量的预后/预测特征,这预示着治疗决策有望得到改善。然而,迄今为止开发的大多数特征似乎仅对雌激素受体阳性疾病具有鉴别能力。本综述探讨了基因表达谱分析对我们理解乳腺癌及其临床管理的贡献。