Establishment and application of a predictive model for gefitinib-induced severe rash based on pharmacometabolomic profiling and polymorphisms of transporters in non-small cell lung cancer.

Abstract

BACKGROUND:

Rash is a well-known predictor of survival for patients with gefitinib therapy with non-small cell lung cancer (NSCLC). However, whether patients with more severe rash obtain the more survival benefits from gefitinib is still unknown, and predicted model for severe rash is needed.

METHODS:

The relationship between gefitinib-induced rash and progression free survival (PFS) was primarily explored in the retrospective cohort. The association between rash and gefitinib/metabolites concentration and genetic polymorphisms were determined by pharmacometabolomic and pharmacogenomics methods in the exploratory cohort and validated in an external cohort.

RESULTS:

The survival for patients with rash was significantly higher than that of patients without rash (p = 0.0002, p = 0.0089), but no difference was found between grade 1/2 or grade 3/4. Only the concentration of gefitinib, but not its metabolites, was found to be associated with severe rash, and the cutoff value of gefitinib was 204.6 ng/mL conducted by ROC curve analysis (AUC=0.685). A predictive model for severe rash was established: gefitinib concentration (OR = 11.523, 95% CI = 2.898-64.016, p = 0.0016), SLC22A8 rs4149179(CT vs CC, OR = 3.156, 95% CI = 0.958-11.164, p = 0.0629), SLC22A1 rs4709400(CG vs CC, OR = 10.267, 95% CI = 2.067-72.465, p = 0.0087; GG vs CC, OR = 5.103, 95% CI = 1.032-33.938, p = 0.061). This model was confirmed in the validation cohort with an excellent predictive ability (AUC = 0.749, 95% CI = 0.710-0.951).

CONCLUSIONS:

Our finding demonstrated that the incidence, not the severity, of gefitinib-induced rash predicted improved survival, the gefitinib concentration and polymorphisms of SLC22A8 and SLC22A1 were recommended to manage severe rash.

• Authors: Shaoxing Guan, Xi Chen, Shuang Xin, Shu Liu, Yunpeng Yang, Wenfeng Fang, Yan Huang, Hongyun Zhao, Xia Zhu, Wei Zhuang, Fei Wang, Wei Feng, Xiaoxu Zhang, Min Huang, Xueding Wang, Li Zhang
• Journal: Translational oncology (Transl Oncol) Vol. 14 Issue 1 Pg. 100951 (Jan 2021) ISSN: 1936-5233 [Print] United States
• PMID: 33221684 (Publication Type: Journal Article)
• Copyright: Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.