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.

Autophagy is a conserved biological stress response in mammalian cells that is responsible for clearing damaged proteins and organelles from the cytoplasm and recycling their contents via the lysosomal pathway. In cases of mild stress, autophagy acts as a survival mechanism, while in cases of severe stress cells may switch to programmed cell death. Understanding the decision process that moves a cell from autophagy to apoptosis is important since abnormal regulation of autophagy occurs in many diseases, including cancer. To integrate existing knowledge about this decision process into a rigorous, analytical framework, we built a mathematical model of cell fate decisions mediated by autophagy. Our dynamical model is consistent with existing quantitative measurements of autophagy and apoptosis in rat kidney proximal tubular cells responding to cisplatin-induced stress.

Biological systems require precise copper homeostasis enabling metallation of cuproproteins while preventing metal toxicity. In bacteria, sensing, transport, and storage molecules act in coordination to fulfill these roles. However, there is not yet a kinetic schema explaining the system integration. Here, we report a model emerging from experimental and computational approaches that describes the dynamics of copper distribution in Pseudomonas aeruginosa. Based on copper uptake experiments, a minimal kinetic model describes well the copper distribution in the wild-type bacteria but is unable to explain the behavior of the mutant strain lacking CopA1, a key Cu efflux ATPase. The model was expanded through an iterative hypothesis-driven approach, arriving to a mechanism that considers the induction of compartmental pools and the parallel function of CopA and Cus efflux systems. Model simulations support the presence of a periplasmic copper storage with a crucial role under dyshomeostasis conditions in P. aeruginosa. Importantly, the model predicts not only the interplay of periplasmic and cytoplasmic pools but also the existence of a threshold in the concentration of external copper beyond which cells lose their ability to control copper levels.

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BackgroundIron is an essential element of most living organisms but is a dangerous substance when poorly liganded in solution. The hormone hepcidin regulates the export of iron from tissues to the plasma contributing to iron homeostasis and also restricting its availability to infectious agents. Disruption of iron regulation in mammals leads to disorders such as anemia and hemochromatosis, and contributes to the etiology of several other diseases such as cancer and neurodegenerative diseases. Here we test the hypothesis that hepcidin alone is able to regulate iron distribution in different dietary regimes in the mouse using a computational model of iron distribution calibrated with radioiron tracer data.ResultsA model was developed and calibrated to the data from adequate iron diet, which was able to simulate the iron distribution under a low iron diet. However simulation of high iron diet shows considerable deviations from the experimental data. Namely the model predicts more iron in red blood cells and less iron in the liver than what was observed in experiments.ConclusionsThese results suggest that hepcidin alone is not sufficient to regulate iron homeostasis in high iron conditions and that other factors are important. The model was able to simulate anemia when hepcidin was increased but was unable to simulate hemochromatosis when hepcidin was suppressed, suggesting that in high iron conditions additional regulatory interactions are important.Electronic supplementary materialThe online version of this article (doi:10.1186/s12918-017-0431-3) contains supplementary material, which is available to authorized users.