Clinical Research Papers:

Pharmacogenetics-based area-under-curve model can predict efficacy and adverse events from axitinib in individual patients with advanced renal cell carcinoma

Yoshiaki Yamamoto, Ryouichi Tsunedomi, Yusuke Fujita, Toru Otori, Mitsuyoshi Ohba, Yoshihisa Kawai, Hiroshi Hirata, Hiroaki Matsumoto, Jun Haginaka, Shigeo Suzuki, Rajvir Dahiya, Yoshihiko Hamamoto, Kenji Matsuyama, Shoichi Hazama, Hiroaki Nagano and Hideyasu Matsuyama _

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Oncotarget. 2018; 9:17160-17170. https://doi.org/10.18632/oncotarget.24715

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Yoshiaki Yamamoto1, Ryouichi Tsunedomi2, Yusuke Fujita3, Toru Otori4, Mitsuyoshi Ohba5, Yoshihisa Kawai1, Hiroshi Hirata1, Hiroaki Matsumoto1, Jun Haginaka6, Shigeo Suzuki7, Rajvir Dahiya8, Yoshihiko Hamamoto3, Kenji Matsuyama9, Shoichi Hazama10, Hiroaki Nagano2 and Hideyasu Matsuyama1

1Department of Urology, Graduate School of Medicine, Yamaguchi University, Ube, Yamaguchi, Japan

2Department of Gastroenterological, Breast and Endocrine Surgery, Yamaguchi University Graduate School of Medicine, Ube, Yamaguchi, Japan

3Department of Computer Science and Systems Engineering, Yamaguchi University Graduate School of Sciences and Technology for Innovation, Ube, Yamaguchi, Japan

4Faculty of Pharmacy, Kindai University, Higashiosaka, Osaka, Japan

5Technical Research Laboratory, Toyo Kohan Company Ltd., Kudamatsu, Yamaguchi, Japan

6School of Pharmacy and Pharmaceutical Sciences, Mukogawa Women's University, Nishinomiya, Hyogo, Japan

7Department of Laboratory of Analytical Chemistry for Pharmaceutical Sciences, Kindai University, Higashiosaka, Osaka, Japan

8Department of Urology, San Francisco Veterans Affairs Medical Center and University of California at San Francisco, San Francisco, California, USA

9Faculty of Pharmacy, Daiichi College of Pharmaceutical Sciences, Fukuoka, Fukuoka, Japan

10Department of Translational Research and Developmental Therapeutics Against Cancer, Yamaguchi University Faculty of Medicine, Ube, Yamaguchi, Japan

Correspondence to:

Hideyasu Matsuyama, email: hidde@yamaguchi-u.ac.jp

Keywords: axitinib; pharmacogenetics; renal cell carcinoma; gene polymorphisms; area under the plasma concentration–time curve

Received: November 03, 2017     Accepted: February 26, 2018     Published: March 30, 2018


We investigated the relationship between axitinib pharmacogenetics and clinical efficacy/adverse events in advanced renal cell carcinoma (RCC) and established a model to predict clinical efficacy and adverse events using pharmacokinetic and gene polymorphisms related to drug metabolism and efflux in a phase II trial. We prospectively evaluated the area under the plasma concentration–time curve (AUC) of axitinib, objective response rate, and adverse events in 44 consecutive advanced RCC patients treated with axitinib. To establish a model for predicting clinical efficacy and adverse events, polymorphisms in genes including ABC transporters (ABCB1 and ABCG2), UGT1A, and OR2B11 were analyzed by whole-exome sequencing, Sanger sequencing, and DNA microarray. To validate this prediction model, calculated AUC by 6 gene polymorphisms was compared with actual AUC in 16 additional consecutive patients prospectively. Actual AUC significantly correlated with the objective response rate (P = 0.0002) and adverse events (hand-foot syndrome, P = 0.0055; and hypothyroidism, P = 0.0381). Calculated AUC significantly correlated with actual AUC (P < 0.0001), and correctly predicted objective response rate (P = 0.0044) as well as adverse events (P = 0.0191 and 0.0082, respectively). In the validation study, calculated AUC prior to axitinib treatment precisely predicted actual AUC after axitinib treatment (P = 0.0066). Our pharmacogenetics-based AUC prediction model may determine the optimal initial dose of axitinib, and thus facilitate better treatment of patients with advanced RCC.

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