Endocrine therapies exert potent tumor-suppressing effects in breast cancer (BC). Estrogen receptor (ER) positivity is generally considered the most powerful biomarker to predict therapy response in a neoadjuvant setting. However, due to the heterogeneity of BCs, many ER-positive cases do not necessarily respond to treatment. Therefore, identification of new biomarkers is warranted to predict treatment response and to detect acquired resistance to therapy. In this chapter, we discuss clinical factors of BC to predict treatment response and identify available pathological and immunohistochemical factors. Histologically, shrinkage of tumors as well as diminished mitosis is evidence of response to endocrine therapy (ET). Immunohistochemically, ER abundance and the Ki-67 labeling index are used to predict response to ET. In addition, we assess the utility of miRNAs, especially circulating miRNAs, as previous studies have indicated that these molecules may be the next generation of biomarkers to assess treatment response. Acquired resistance to ET is a major clinical obstacle, especially since there is no established biomarker to predict treatment response or resistance to aromatase inhibitors in the neoadjuvant setting of ET before surgery. Endocrine therapy (ET) for postmenopausal breast cancer (BC) is well established. At present, aromatase inhibitors (AIs) are first choice agents for adjuvant ET and are also gaining credibility for use in neoadjuvant ET. While it is generally assumed that all estrogen receptor (ER)-positive BCs are eligible for and respond to ET, the reality is different. Some ER-positive BCs do not respond to ET, and quite a few develop resistance after an initial response. Therefore, treatment resistance has become a major impediment in clinical practice. Thus, further research of biomarkers to predict response to ET is warranted. BC is one of the most intensely studied cancers, and various biomarkers to predict prognosis or therapeutic response have been reported. However, in terms of ET, in particular AIs, there are relatively few established biomarkers with high sensitivity and specificity that reflect response or resistance to treatment. ER positivity and postmenopausal status seem to be the most reliable biomarkers currently established to predict response to ET. However, the heterogeneity of luminal-type BC creates many exceptions, and therefore, monitoring these two biomarkers is insufficient to guarantee therapy efficacy. In this chapter, we discuss alterations of biomarkers by ET, mainly AIs, and scrutinize potential biomarkers to precisely predict response or resistance to ET.
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