The Joint Annual Scientific Meetings of the Endocrine Society of Australia and the Society for Reproductive Biology 2018

Targeting the androgen receptor in estrogen receptor-α (ER) positive breast cancer (#117)

Wayne Tilley 1
  1. Dame Roma Mitchell Cancer Research Laboratories, Adelaide Medical School, University of Adelaide, Adelaide, Australia

Therapies that modulate estrogen receptor-α (ER) action have improved the survival of patients with ER-positive breast cancer, but resistance to treatment is a major clinical problem. Targeting alternative or parallel signalling pathways has potential to improve the efficacy and benefit of currently available treatments. For example, emerging data have shown that other sex hormone receptors may regulate the sites at which ER binds to DNA to suppress the oncogenic activity of ER in breast cancer. The ER, progesterone receptor (PR) and androgen receptor (AR) are ligand-activated transcription factors that bind DNA and interact with a host of other nuclear proteins to regulate gene expression. The cognate hormones and their receptors are structurally and functionally related. ERα is the prototype from which AR and then PR evolved. Our recent findings indicate that cross-talk between PR or AR with ER in breast cancer can influence response to ER-target therapies and disease outcomes. We recently showed that the PR can reprogram the ER DNA binding landscape towards genes associated with a favourable outcome. Similarly, the AR, which is expressed in the majority of breast cancers, can reprogram ER DNA binding to inhibit the growth of ER-positive tumours. Despite the potential benefit of targeting AR in ER-positive breast cancer, uncertainties remain. For example, AR antagonists as well as selective androgen receptor modulators (SARMs) that activate AR in breast cancer cells are currently being evaluated as potential therapeutic strategies. It is therefore critical that the mechanisms of crosstalk between ER and AR be fully elucidated and the effect on reprogramming of ER is tested in optimal preclinical models to better inform the design of clinical trials.