乳腺癌
外科肿瘤学
医学
肿瘤科
临床意义
病态的
癌症
内科学
临床实习
病理
生物信息学
生物
家庭医学
作者
Emad A. Rakha,Jorge S. Reis‐Filho,Frederick L. Baehner,David J. Dabbs,Thomas Decker,Vincenzo Eusebi,Stephen B. Fox,Shu Ichihara,Jocelyne Jacquemier,Sunil R. Lakhani,José Palacios,Andrea L. Richardson,Stuart J. Schnitt,Fernando Schmitt,Puay‐Hoon Tan,Gary M. Tse,Sunil Badve,Ian O. Ellis
摘要
Breast cancer is a heterogeneous disease with varied morphological appearances, molecular features, behavior, and response to therapy. Current routine clinical management of breast cancer relies on the availability of robust clinical and pathological prognostic and predictive factors to support clinical and patient decision making in which potentially suitable treatment options are increasingly available. One of the best-established prognostic factors in breast cancer is histological grade, which represents the morphological assessment of tumor biological characteristics and has been shown to be able to generate important information related to the clinical behavior of breast cancers. Genome-wide microarray-based expression profiling studies have unraveled several characteristics of breast cancer biology and have provided further evidence that the biological features captured by histological grade are important in determining tumor behavior. Also, expression profiling studies have generated clinically useful data that have significantly improved our understanding of the biology of breast cancer, and these studies are undergoing evaluation as improved prognostic and predictive tools in clinical practice. Clinical acceptance of these molecular assays will require them to be more than expensive surrogates of established traditional factors such as histological grade. It is essential that they provide additional prognostic or predictive information above and beyond that offered by current parameters. Here, we present an analysis of the validity of histological grade as a prognostic factor and a consensus view on the significance of histological grade and its role in breast cancer classification and staging systems in this era of emerging clinical use of molecular classifiers.
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