Approximately 70% of all newly diagnosed breast cancers express estrogen receptor (ER)-α. Although inhibiting ER action using targeted therapies such as fulvestrant (ICI) is often effective, later emergence of antiestrogen resistance limits clinical use. We used antiestrogen-sensitive and -resistant cells to determine the effect of antiestrogens/ERα on regulating autophagy and unfolded protein response (UPR) signaling. Knockdown of ERα significantly increased the sensitivity of LCC1 cells (sensitive) and also resensitized LCC9 cells (resistant) to antiestrogen drugs. Interestingly, ERα knockdown, but not ICI, reduced nuclear factor (erythroid-derived 2)-like (NRF)-2 (UPR-induced antioxidant protein) and increased cytosolic kelch-like ECH-associated protein (KEAP)-1 (NRF2 inhibitor), consistent with the observed increase in ROS production. Furthermore, autophagy induction by antiestrogens was prosurvival but did not prevent ERα knockdown-mediated death. We built a novel mathematical model to elucidate the interactions among UPR, autophagy, ER signaling, and ROS regulation of breast cancer cell survival. The experimentally validated mathematical model explains the counterintuitive result that knocking down the main target of ICI (ERα) increased the effectiveness of ICI. Specifically, the model indicated that ERα is no longer present in excess and that the effect on proliferation from further reductions in its level by ICI cannot be compensated for by increased autophagy. The stimulation of signaling that can confer resistance suggests that combining autophagy or UPR inhibitors with antiestrogens would reduce the development of resistance in some breast cancers.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4139896PMC
http://dx.doi.org/10.1096/fj.13-247353DOI Listing

Publication Analysis

Top Keywords

unfolded protein
8
protein response
8
breast cancer
8
cancer cell
8
breast cancers
8
erα increased
8
mathematical model
8
autophagy
6
ici
5
erα
5

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!