Current issues with luminal subtype classification in terms of prediction of benefit from endocrine therapy in early breast cancerTools Alfarsi, Lutfi, Johnston, Simon, Liu, Dong-Xu, Rakha, Emad and Green, Andrew (2018) Current issues with luminal subtype classification in terms of prediction of benefit from endocrine therapy in early breast cancer. Histopathology . ISSN 0309-0167
AbstractEndocrine therapy for oestrogen receptor‐positive (ER+) breast cancer (BC) is arguably the most successful targeted cancer therapy to date. Nevertheless, resistance to endocrine therapy still occurs in a significant proportion of patients, limiting its clinical utility. ER+ or luminal BC, which represents around three quarters of all breast malignancies, are biologically heterogeneous with no distinct, clinically defined sub‐classes able to predict the benefit of endocrine therapy in early settings. To improve patient outcomes, there is a clear need for improved understanding of the biology of the luminal BC, with subsequent translation into more effective methods of diagnosis to identify potential predictive biomarkers for endocrine therapy. This review summarises current knowledge of factors predictive of benefit of endocrine therapy, and discusses why molecular classification systems of BC have yet to be translated into the clinic.
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