Abstract
Objectives
Different chemical forms of selenium (Se) regulate distinct sets of genes and have different metabolic effects. We previously showed that mixtures of different Se compounds can have greater inhibitory effects on prostate cancer cell viability than individual chemical forms. Further, we showed that blends of different Se forms can be optimized using response surface methodology. Previous investigators showed that single forms of Se can potentiate the effects of chemotherapeutic and other agents. We hypothesized that optimized mixtures of different forms of Se would be more effective than individual Se compounds in enhancing the efficacy of Se-drug combinations. Our objective was to provide proof of principle for this hypothesis.
Methods
Response surface methodology was used to optimize a blend of methylseleninic acid (MSA), selenite (SEL) and Nano Se to achieve maximum reduction of cell viability in LNCaP prostate cancer cells. Apalutamide (APA), Enzalutamide (ENZ), Docetaxel (DOC), and Mitoxantrone (MIT) were each combined with a single Se compound, or with the optimized blend. Cell viability assays were done using Alamar Blue.
Results
The optimized mix of Se forms, determined using response surface methodology, was a 50:50 blend of MSA and SEL, that surprisingly did not include Nano Se. All medium supplemented with Se compounds contained 10 μM Se. MIT treatment alone reduced cell viability >90% and showed no further reductions due to added Se. Addition of either form of Se to APA, DOC, or ENZ significantly decreased cell viability compared to treatment with the drug alone (P values: 0.008 - 0.041). Similarly, in 5 out of 6 cases, combination of the optimized blend of Se compounds with the drug resulted in further decreases in cell viability, compared to the mix of drug plus one chemical form of Se (P values: 0.013 – < 0.001).
Conclusions
These results provide proof of principle that the substitution of an optimized blend of Se compounds for a single Se form, may increase the efficacy of previously reported drug-Se combinations and treatments. Optimization of blends of different Se compounds can be done under conditions customized to their intended use to achieve a desired outcome.
Funding Sources
This work was funded by the BYU Simmons Center for Cancer Research.
Response Surface Regressions for Critical Value Bounds and Approximate p‐values in Equilibrium Correction Models1
