Xiao Qi, Mao Chenxue, Gao Ying, Huang Hanxue, Yu Bing, Yu Lulu, Li Xi, Mao Xiaoyuan, Zhang Wei, Yin Jiye, Liu Zhaoqian
Department of Clinical Pharmacology, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha 410008, China.
Institute of Clinical Pharmacology, Central South University, Hunan Key Laboratory of Pharmacogenetics, 110 Xiangya Road, Changsha 410078, China.
J Clin Med. 2023 Feb 7;12(4):1318. doi: 10.3390/jcm12041318.
Platinum drugs combined with other agents have been the first-line treatment for non-small cell lung cancer (NSCLC) in the past decades. To better evaluate the efficacy of platinum-based chemotherapy in NSCLC, we establish a platinum chemotherapy response prediction model. Here, a total of 217 samples from Xiangya Hospital of Central South University were selected as the discovery cohort for a genome-wide association analysis (GWAS) to select SNPs. Another 216 samples were genotyped as a validation cohort. In the discovery cohort, using linkage disequilibrium (LD) pruning, we extract a subset that does not contain correlated SNPs. The SNPs with < 10 and < 10 are selected for modeling. Subsequently, we validate our model in the validation cohort. Finally, clinical factors are incorporated into the model. The final model includes four SNPs (rs7463048, rs17176196, rs527646, and rs11134542) as well as two clinical factors that contributed to the efficacy of platinum chemotherapy in NSCLC, with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.726.
在过去几十年中,铂类药物联合其他药物一直是非小细胞肺癌(NSCLC)的一线治疗方法。为了更好地评估铂类化疗在NSCLC中的疗效,我们建立了一个铂类化疗反应预测模型。在此,共选取中南大学湘雅医院的217个样本作为发现队列进行全基因组关联分析(GWAS)以选择单核苷酸多态性(SNP)。另外216个样本进行基因分型作为验证队列。在发现队列中,使用连锁不平衡(LD)修剪,我们提取了一个不包含相关SNP的子集。选择P值<10⁻⁵和r²<10⁻²的SNP进行建模。随后,我们在验证队列中验证我们的模型。最后,将临床因素纳入模型。最终模型包括四个SNP(rs7463048、rs17176196、rs527646和rs11134542)以及两个有助于NSCLC铂类化疗疗效的临床因素,其受试者工作特征(ROC)曲线下面积(AUC)为0.726。