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Response Surface Methodology as a Model for Combination Drug Therapy in Human Prostate Cancer Cells
Author(s) -
Oblad Richard,
Kenealey Jason
Publication year - 2017
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.31.1_supplement.1064.7
Subject(s) - cabazitaxel , mitoxantrone , docetaxel , combination therapy , prostate cancer , pharmacology , drug , resveratrol , cancer , medicine , cancer research , chemistry , chemotherapy , androgen deprivation therapy
Combining chemotherapeutic drugs to treat malignant tumors has been proven to be effective at preventing drug resistance, tumor regression, and reducing tumor size. Most combinations come from a regimen of treatments that were used in the past, or were devised using synergistic drugs that were identified using the Chou Talalay method. We modeled combination drug therapy in PC‐3 human prostate cancer cells using conventional chemotherapeutics (Mitoxantrone Hydrochloride, Cabazitaxel, and Docetaxel) and natural bioactive compounds (Resveratrol, Piperlongumine, and Flavopiridol). We measured cell viability via the Alamar Blue assay to identify effective concentrations and combinations of drugs. Three drugs were used per combination at varying concentrations. Those points were then used to plot a response surface using the statistical software JMP. The response surface generated provided us with an area of effective combinations which allowed us to differentiate between combinatorial and synergistic combinations. Strong synergistic effects between resveratrol, piperlongumine, cabazitaxel, and flavopiridol were observed, with weaker interactions between the aforementioned drugs and mitoxantrone. Cabazitaxel and docetaxel, both microtubule synthesis inhibitors, showed additive effects when used in combination, but were both effective when used in combination with other drugs. We propose response surface methodology as an effective tool in devising combination treatments based on the response of tumorigenic cell lines. Support or Funding Information BYU Life Science Startup Grant