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Current issues with luminal subtype classification in terms of prediction of benefit from endocrine therapy in early breast cancer
Author(s) -
Alfarsi Lutfi,
Johnston Simon,
Liu DongXu,
Rakha Emad,
Green Andrew R
Publication year - 2018
Publication title -
histopathology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.626
H-Index - 124
eISSN - 1365-2559
pISSN - 0309-0167
DOI - 10.1111/his.13523
Subject(s) - endocrine system , medicine , breast cancer , cancer , oncology , targeted therapy , limiting , oestrogen receptor , bioinformatics , hormone , biology , mechanical engineering , engineering
Endocrine 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 approximately three‐quarters of all breast malignancies, are biologically heterogeneous, with no distinct, clinically defined subclasses 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.