Salinomycin enhances doxorubicin-induced cytotoxicity in multidrug resistant MCF-7/MDR human breast cancer cells via decreased efflux of doxorubicin

Salinomycin is a monocarboxylic polyether antibiotic, which is widely used as an anticoccidial agent. The anticancer property of salinomycin has been recognized and is based on its ability to induce apoptosis in human multidrug resistance (MDR). The present study investigated whether salinomycin reverses MDR towards chemotherapeutic agents in doxorubicin-resistant MCF-7/MDR human breast cancer cells. The results demonstrated that doxorubicin-mediated cytotoxicity was significantly enhanced by salinomycin in the MCF-7/MDR cells, and this occurred in a dose-dependent manner. This finding was consistent with subsequent observations made under a confocal microscope, in which the doxorubicin fluorescence signals of the salinomycin-treated cells were higher compared with the cells treated with doxorubicin alone. In addition, flow cytometric analysis revealed that salinomycin significantly increased the net cellular uptake and decreased the efflux of doxorubicin. The expression levels of MDR-1 and MRP-1 were not altered at either the mRNA or protein levels in the cells treated with salinomycin. These results indicated that salinomycin was mediated by its ability to increase the uptake and decrease the efflux of doxorubicin in MCF-7/MDR cells. Salinomycin reversed the resistance of doxorubicin, suggesting that chemotherapy in combination with salinomycin may benefit MDR cancer therapyopen

Modeling allosteric signal propagation using protein structure networks

Allosteric communication in proteins can be induced by the binding of effective ligands, mutations or covalent modifications that regulate a site distant from the perturbed region. To understand allosteric regulation, it is important to identify the remote sites that are affected by the perturbation-induced signals and how these allosteric perturbations are transmitted within the protein structure. In this study, by constructing a protein structure network and modeling signal transmission with a Markov random walk, we developed a method to estimate the signal propagation and the resulting effects. In our model, the global perturbation effects from a particular signal initiation site were estimated by calculating the expected visiting time (EVT), which describes the signal-induced effects caused by signal transmission through all possible routes. We hypothesized that the residues with high EVT values play important roles in allosteric signaling. We applied our model to two protein structures as examples, and verified the validity of our model using various types of experimental data. We also found that the hot spots in protein binding interfaces have significantly high EVT values, which suggests that they play roles in mediating signal communication between protein domains

Stochastic Modeling of B Lymphocyte Terminal Differentiation and Its Suppression by Dioxin

<p>Abstract</p> <p>Background</p> <p>Upon antigen encounter, naïve B lymphocytes differentiate into antibody-secreting plasma cells. This humoral immune response is suppressed by the environmental contaminant 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) and other dioxin-like compounds, which belong to the family of aryl hydrocarbon receptor (AhR) agonists.</p> <p>Results</p> <p>To achieve a better understanding of the immunotoxicity of AhR agonists and their associated health risks, we have used computer simulations to study the behavior of the gene regulatory network underlying B cell terminal differentiation. The core of this network consists of two coupled double-negative feedback loops involving transcriptional repressors Bcl-6, Blimp-1, and Pax5. Bifurcation analysis indicates that the feedback network can constitute a bistable system with two mutually exclusive transcriptional profiles corresponding to naïve B cells and plasma cells. Although individual B cells switch to the plasma cell state in an all-or-none fashion when stimulated by the polyclonal activator lipopolysaccharide (LPS), stochastic fluctuations in gene expression make the switching event probabilistic, leading to heterogeneous differentiation response among individual B cells. Moreover, stochastic gene expression renders the dose-response behavior of a population of B cells substantially graded, a result that is consistent with experimental observations. The steepness of the dose response curve for the number of plasma cells formed vs. LPS dose, as evaluated by the apparent Hill coefficient, is found to be inversely correlated to the noise level in Blimp-1 gene expression. Simulations illustrate how, through AhR-mediated repression of the AP-1 protein, TCDD reduces the probability of LPS-stimulated B cell differentiation. Interestingly, stochastic simulations predict that TCDD may destabilize the plasma cell state, possibly leading to a reversal to the B cell phenotype.</p> <p>Conclusion</p> <p>Our results suggest that stochasticity in gene expression, which renders a graded response at the cell population level, may have been exploited by the immune system to launch humoral immune response of a magnitude appropriately tuned to the antigen dose. In addition to suppressing the initiation of the humoral immune response, dioxin-like compounds may also disrupt the maintenance of the acquired immunity.</p