L Zhao, JLS Au, MG Wientjes
Current Cancer Drug Targets, 2017;17:735-755
Background—Commonly used methods for analyzing interactivity between drugs (e.g., synergy, antagonism) such as isobologram, combination index, and curve shift are based on the Loewe Additivity principle of dose equivalence and the inherent assumption of similar concentration-effect (C-E) including parallel curves and equal maximum effects (Emax), and therefore are not suitable for drugs with dissimilar C-E. This study describes a new method that is without this limitation and has the additional advantage of enabling statistical analysis.
Method and Results—The method comprises two steps. First, based on the dose equivalence principle, the experimentally obtained C-E of one drug was used to calculate the equally effective C-E of the other drug at no interactivity; the resulting two zero-interactivity C-E formed the upper and lower boundaries of Additivity Envelope. Next, 95% confidence intervals calculated from experimental data were added to Additivity Envelope to obtain Uncertainty Envelope (UE). Experimentally observed effects of drug combinations (C-Ecomb,observed) located within UE indicate additivity whereas C-Ecomb,observed located above or below UE indicate statistically significant (p<0.05) synergy or antagonism, respectively. Additional in silico studies demonstrated the shape and size of Additivity Envelope, which determines the ability to detect drug interactivity, depending on the Drug A-to-B concentration ratios and the ratios of their C-E curve shape parameter. Analyses of experimental results of combinations of drugs with nonparallel C-E and/or unequal Emax indicated UE as more versatile and provided more information, compared to earlier methods.
Conclusion—UE is a broadly applicable method for analysis, including statistical significance assessment, of drug interactivity.
J Wang, BZ Yeung, MJ Cui, CJ Peer, Z Lu, WD Figg, MG Wientjes, S Woo, JLS Au
Journal of Controlled Release, 2017;268:147-158
Purpose: Exosomes are small membrane vesicles (30-100nm in diameter) secreted by cells into extracellular space. The present study evaluated the effect of chemotherapeutic agents on exosome production and/or release, and quantified the contribution of exosomes to intercellular drug transfer and pharmacodynamics.
Methods: Human cancer cells (breast MCF7, breast-to-lung metastatic LM2, ovarian A2780 and OVCAR4) were treated with paclitaxel (PTX, 2-1000nM) or doxorubicin (DOX, 20-1000nM) for 24-48h. Exosomes were isolated from the culture medium of drug-treated donor cells (Donor cells) using ultra-centrifugation, and analyzed for acetylcholinesterase activity, total proteins, drug concentrations, and biological effects (cytotoxicity and anti-migration) on drug-naïve recipient cells (Recipient cells). These results were used to develop computational predictive quantitative pharmacology models.
Results: Cells in exponential growth phase released ~220 exosomes/cell in culture medium. PTX and DOX significantly promoted exosome production and/or release in a dose- and time-dependent manner, with greater effects in ovarian cancer cells than in breast cancer cells. Exosomes isolated from Donor cells contained appreciable drug levels (2-7pmole/106 cells after 24h treatment with 100-1000nM PTX), and caused cytotoxicity and inhibited migration of Recipient cells. Quantitative pharmacology models that integrated cellular PTX pharmacokinetics with PTX pharmacodynamics successfully predicted effects of exosomes on intercellular drug transfer, cytotoxicity of PTX on Donor cells and cytotoxicity of PTX-containing exosomes on Recipient cells. Additional model simulations indicate that within clinically achievable PTX concentrations, the contribution of exosomes to active drug efflux increased with drug concentration and exceeded the p-glycoprotein efflux when the latter was saturated.
Conclusions: Our results indicate (a) chemotherapeutic agents stimulate exosome production or release, and (b) exosome is a mechanism of intercellular drug transfer that contributes to pharmacodynamics of neighboring cells.