Response Surface Methodology to Optimize the Combination Treatment of Paclitaxel, Bufalin and Cinobufagin for Hepatoma Therapy

Author:

Zhang Jinghui1,Shu Chenyan1,Yi Xiaojiao1,Zhu Junfeng2,Lian Xiaoyuan1,Wu Yongjiang1ORCID

Affiliation:

1. College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China

2. Zhejiang Cancer Hospital, Hangzhou 310022, China

Abstract

Background: Hepatoma is a common malignancy in the world with high morbidity and mortality. The treatment of hepatoma is limited by its poor response to many chemotherapeutic agents. Although paclitaxel (PTX) is widely used in clinical chemotherapy, the low sensitivity to hepatoma restricts its application. Combination therapy is a promising approach to resolve this dilemma. Objective: To evaluate the interaction between paclitaxel, bufalin (BFL) and cinobufagin (CBF), and explore the optimum combination efficiently. Methods: HepG2 cells were treated with PTX, BFL and CBF individually or in combination. Their interactions were evaluated by two classical models (Chou-Talalay model and Bliss independence). Response surface methodology (RSM) was used to explore the optimum combination. Furthermore, the optimum drug combination was verified by the morphological experiment. Results: Synergistic effects were observed when cells were exposed to binary mixtures of PTX+CBF and BFL+CBF. Although the interaction of PTX and BFL was summative, a strong synergistic effect was observed when cells were exposed to ternary mixtures of PTX+BFL+CBF. The interaction results of RSM were consistent with classical models, but more efficient. Moreover, the optimum combination dose was given by RSM without the combinatorial explosion of exhaustive testing. Conclusion: The combination of BFL and CBF synergistically enhanced the potency of PTX against HepG2 cells. RSM could give an accurate evaluation for drug interactions and efficient prediction of optimum combination.

Funder

National Natural Science Foundation of China

Publisher

Bentham Science Publishers Ltd.

Subject

Organic Chemistry,Computer Science Applications,Drug Discovery,General Medicine

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