Unknown

Dataset Information

0

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


ABSTRACT: 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.

SUBMITTER: Yamamoto Y 

PROVIDER: S-EPMC5908314 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

altmetric image

Publications

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

Yamamoto Yoshiaki Y   Tsunedomi Ryouichi R   Fujita Yusuke Y   Otori Toru T   Ohba Mitsuyoshi M   Kawai Yoshihisa Y   Hirata Hiroshi H   Matsumoto Hiroaki H   Haginaka Jun J   Suzuki Shigeo S   Dahiya Rajvir R   Hamamoto Yoshihiko Y   Matsuyama Kenji K   Hazama Shoichi S   Nagano Hiroaki H   Matsuyama Hideyasu H  

Oncotarget 20180330 24


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  ...[more]

Similar Datasets

| S-EPMC7786826 | biostudies-literature
| S-EPMC10769506 | biostudies-literature
| S-EPMC6716603 | biostudies-literature
| S-EPMC8798318 | biostudies-literature
| S-EPMC5572665 | biostudies-literature
| S-EPMC9738341 | biostudies-literature
| S-EPMC3588609 | biostudies-other
| S-EPMC8459336 | biostudies-literature
| S-EPMC7060483 | biostudies-literature
| S-EPMC8265348 | biostudies-literature