Review ArticlesMolecular Classification of Breast CancerTsang, Julia Y.S. PhD; Tse, Gary M. FRCPCAuthor Information Department of Anatomical and Cellular Pathology, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong The authors have no funding or conflicts of interest to disclose. Reprints: Gary M. Tse, FRCPC, Department of Anatomical and Cellular Pathology, Prince of Wales Hospital, Ngan Shing Street, Shatin, Hong Kong SAR (e-mail: email@example.com). Online date: April 30, 2019 Advances In Anatomic Pathology: January 2020 - Volume 27 - Issue 1 - p 27-35 doi: 10.1097/PAP.0000000000000232 Buy Metrics Abstract Cancer classification aims to provide an accurate diagnosis of the disease and prediction of tumor behavior to facilitate oncologic decision making. Traditional breast cancer classification, mainly based on clinicopathologic features and assessment of routine biomarkers, may not capture the varied clinical courses of individual breast cancers. The underlying biology in cancer development and progression is complicated. Recent findings from high-throughput technologies added important information with regard to the underlying genetic alterations and the biological events in breast cancer. The information provides insights into new treatment strategies and patient stratifications that impact on the management of breast cancer patients. This review provides an overview of recent data on high throughput analysis of breast cancers, and it analyzes the relationship of these findings with traditional breast cancer classification and their clinical potentials. Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.