Co-Inhibition of BCL-W and BCL2 Restores Antiestrogen Sensitivity through BECN1 and Promotes an Autophagy-Associated Necrosis

Abstract

BCL2 family members affect cell fate decisions in breast cancer but the role of BCL-W (BCL2L2) is unknown. We now show the integrated roles of the antiapoptotic BCL-W and BCL2 in affecting responsiveness to the antiestrogen ICI 182,780 (ICI; Fulvestrant Faslodex), using both molecular (siRNA; shRNA) and pharmacologic (YC137) approaches in three breast cancer variants; MCF-7/LCC1 (ICI sensitive), MCF-7/LCC9 (ICI resistant), and LY2 (ICI resistant). YC137 inhibits BCL-W and BCL2 and restores ICI sensitivity in resistant cells. Co-inhibition of BCL-W and BCL2 is both necessary and sufficient to restore sensitivity to ICI, and explains mechanistically the action of YC137. These data implicate functional cooperation and/or redundancy in signaling between BCL-W and BCL2, and suggest that broad BCL2 family member inhibitors will have greater therapeutic value than targeting only individual proteins. Whereas ICI sensitive MCF-7/LCC1 cells undergo increased apoptosis in response to ICI following BCL-W±BCL2 co-inhibition, the consequent resensitization of resistant MCF-7/LCC9 and LY2 cells reflects increases in autophagy (LC3 cleavage; p62/SQSTM1 expression) and necrosis but not apoptosis or cell cycle arrest. Thus, de novo sensitive cells and resensitized resistant cells die through different mechanisms. Following BCL-W+BCL2 co-inhibition, suppression of functional autophagy by 3-methyladenine or BECN1 shRNA reduces ICI-induced necrosis but restores the ability of resistant cells to die through apoptosis. These data demonstrate the plasticity of cell fate mechanisms in breast cancer cells in the context of antiestrogen responsiveness. Restoration of ICI sensitivity in resistant cells appears to occur through an increase in autophagy-associated necrosis. BCL-W, BCL2, and BECN1 integrate important functions in determining antiestrogen responsiveness, and the presence of functional autophagy may influence the balance between apoptosis and necrosis.

Preferential Estrogen Receptor β Ligands Reduce Bcl-2 Expression in Hormone-Resistant Breast Cancer Cells to Increase Autophagy

“…LCC9 cells have been shown to express higher basal levels of Bcl-2 relative to parental MCF-7 cells, and RNA interference (RNAi) for Bcl-2 induces an autophagic response in these cells (32). We previously reported that Bcl-2 is regulated in response to E2 (33) and consistent with this, E2 strongly induced Bcl-2 expression in MCF-7 cells (Fig.…”

XBP1, Unfolded Protein Response, and Endocrine Responsiveness

“…From the perspective of XBP1, proposed connections with BCL2 and NF-kB would be present only with estrogens and lost with the addition of Fulvestrant. BCL2 is a key determinant for maintaining cell survival with the UPR (28), and we now know that BCL2 is overexpressed in antiestrogen resistant cells that also overexpress the endogenous XBP1(s) (52). Estrogenic induction of BCL2 is well known, and we have shown that XBP1 is also a likely regulator of BCL2, which is overexpressed in cells that have been transfected with XBP1 (33).…”

“…We have recently shown that the full effect of the small molecule BCL2 inhibitors is mimicked only when both BCL2 and BCLW are coinhibited (52). Other interactions also occur but these are not directly reflected in this model.…”

“…When considered together, these data strongly suggest that some breast cancer cells can use the cooperation between ER and XBP1 to provide redundant signaling and increase the likelihood of cell survival despite any concurrent EnR stress ( Figure 3B). Importantly, antiestrogen resistant cells that overexpress BCL2 are more sensitive to growth inhibition by small molecule inhibitors of BCL2 (52).…”

“…Article in press -uncorrected proof binding and sequestering BECN1. These interactions prevent the induction of prodeath autophagy and can contribute to antiestrogen resistance (52). However, these events are further downstream and occur primarily in the proteome, and thus might not be reflected in a model based primarily on transcriptome data.…”