Combining chemotherapeutics to treat malignant tumors has been shown to be effective in preventing drug resistance, tumor recurrence, and reducing tumor size. We modeled combination drug therapy in PC-3 human prostate cancer cells using mixture design response surface methodology (MDRSM), a statistical technique designed to optimize compositions to achieve the most desirable result. Conventional chemotherapeutics (mitoxantrone, cabazitaxel, and docetaxel) and natural bioactive compounds (resveratrol, piperlongumine, and flavopiridol) were used in twelve different combinations containing three different drugs at varying concentrations. Cell viability and cell cycle data were collected and used to plot response surfaces in MDRSM that identified the most effective concentrations of each drug in combination. The use of MDRSM for defining combinations of chemotherapeutics is novel. MDRSM allows for extrapolation of data from three or more compounds in non-constant ratio combinations, unlike the Chou-Talalay method. MDRSM combinations were compared with combination index data from the Chou-Talalay method and were found to coincide. We propose MDRSM as an effective tool in devising combination treatments that can improve treatment effectiveness, and increase treatment personalization because MDRSM measures effectiveness rather than synergism, potentiation or antagonism.
Molecular pharmacology. 2018 Jun 08 [Epub ahead of print]
Richard V Oblad, Hayden Doughty, John Lawson, Merrill Christensen, Jason Kenealey
Brigham Young University., Brigham Young University .