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Reviews

Aromatase inhibitors: prediction of response and nature of resistance

, BSc PhD DSc
Pages 1873-1887 | Published online: 25 May 2010
 

Abstract

Importance of the field: Aromatase inhibitors (AIs) are recommended for and central to endocrine management of breast cancer patients. Response rates can be high, but resistance is a major obstacle. Optimal management therefore requires accurate prediction of response and an understanding of the nature by which resistance occurs. These are the subjects of this review.

Areas covered in this review: The complications of assessing response in different clinical settings and the types of response in terms of clinical, pathological, proliferative and molecular endpoints are reviewed. The current status of predictors of response such as estrogen receptors (ERs), progesterone receptors, other markers of estrogen action, ER phosphorylation, ER coregulators and multigene signatures are assessed. Different types of resistance to AIs, their heterogeneity, diversity in mechanisms of resistance and their identification are also considered.

What the reader will gain: The review provides fundamental information on response and predictors of response to AIs as well as an understanding of the diversity of resistance mechanisms to such endocrine agents.

Take home messages: ER status is the only factor used routinely for treatment selection, but additional markers are needed to predict response. Other markers have some predictive powers, but are of limited utility. The hope is, therefore, that discovery strategies based on genome-wide searches will identify new markers. Assessments may be required both before and after a short period of treatment so that early changes can be used to predict subsequent clinical response. Mechanisms of resistance to AIs are diverse. Knowledge of specific resistance mechanisms in individual cases will be necessary if strategies to circumvent resistance are to be developed rationally. A future can be envisaged in which molecular phenotyping of individual tumors is used to decide not only which patients should be treated with AIs but also whether AIs should be used alone or in combination/sequence with other drug regimes.

Notes

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