Establishment of an efficacy prediction model for gefitinib in non-small cell lung cancer patients based on ABCB1 and ABCG2 gene polymorphisms
10.3760/cma.j.cn371439-20210901-00062
- VernacularTitle:基于ABCB1和ABCG2基因多态性建立非小细胞肺癌患者吉非替尼疗效预测模型
- Author:
Yan ZHANG
1
;
Lei PAN
;
Shuting LIU
Author Information
1. 河北省沧州中西医结合医院肺病科，沧州 061000
- Keywords:
Carcinoma, non-small-cell lung;
Risk factors;
Gefitinib
- From:
Journal of International Oncology
2022;49(6):327-333
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the relationship between ABCB1 or ABCG2 gene polymorphisms and therapeutic effects of gefitinib in non-small cell lung cancer (NSCLC) patients, and establish a prediction model of efficacy.Methods:A total of 176 NSCLC patients with epidermal growth factor receptor (EGFR) -sensitive mutation treated with gefitinib admitted to Department of Pulmonary Disease of Cangzhou Hospital of Integrated Traditional Chinese and Western Medicine of Hebei Province from December 2018 to December 2020 were employed as subjects, and all patients were detected ABCB1 and ABCG2 gene polymorphisms. Patients were divided into remission group and non-remission group according to curative effect after 3 months of gefitinib treatment. The clinical data, ABCB1 and ABCG2 gene polymorphisms, levels of serum carcinoembryonic antigen (CEA) and carbohydrate antigen 125 (CA125) were compared between the two groups. The related factors of failure to remission after treatment were analyzed by multivariate logistic regression analysis. Combined with ABCB1 and ABCG2 gene polymorphisms, the prediction model for gefitinib efficacy was constructed and the nomogram was drawn.Results:During the follow-up period, 5 patients were lost to follow-up and 7 patients withdrew from the trial due to intolerable adverse effects, finally 108 patients were employed as remission group, and 56 patients were employed as non-remission group. The numbers of GG, GT and TT at ABCB1 rs2032582 in the remission group were 49, 50 and 9, and those in the non-remission group were 12, 35 and 9, with a statistically significant difference ( χ2=9.56, P=0.008). The numbers of GG, GA and AA at ABCG2 rs2231137 in the remission group were 13, 72 and 23, and those in the non-remission group were 11, 42 and 3, with a statistically significant difference ( χ2=7.74, P=0.021). Before treatment, the levels of serum CEA in the remission group and the non-remission group were (34.28±5.11) ng/ml and (37.88±7.05) ng/ml, with a statistically significant difference ( t=3.74, P<0.001). The levels of CA125 of the two groups were (27.24±6.50) U/ml and (33.31±6.09) U/ml, with a statistically significant difference ( t=-5.79, P<0.001). Multivariate logistic regression analysis showed that TT at rs2032582 of ABCB1 gene ( OR=12.99, 95% CI: 3.17-53.23, P<0.001), GG at rs2231137 of ABCG2 gene ( OR=7.75, 95% CI: 1.36-44.07, P=0.021) and GA ( OR=6.94, 95% CI: 1.47-32.84, P=0.015), CA125 ( OR=1.18, 95% CI: 1.10-1.28, P<0.001) were independent risk factors of failure to remission in NSCLC patients with EGFR sensitive mutation after treatment. The consistency index (C-index) of nomogram for predicting failure to remission was 0.92 (95% CI: 0.86-0.94) . Conclusion:ABCB1 rs2032582 and ABCG2 rs2231137 polymorphisms are related to therapeutic effects of gefitinib in the NSCLC patients, the nomogram based on the two genes combined with serum CA125 can predict efficacy of gefitinib.
