Li Qi, Zhang Chan, Cheng Yujing, Yang Xin, Chen Wanlu, He Kunhua, Chen Mingwei
Department of Respiratory Medicine, The First Affiliated Hospital of School of Medicine of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Department of Blood Transfusion, The First People's Hospital of Yunnan Province, The Affiliated Hospital of Kunming University of Science and Technology, Kunming, China.
Front Genet. 2023 Aug 31;14:1183528. doi: 10.3389/fgene.2023.1183528. eCollection 2023.
Lung cancer is one of the most common human malignant diseases. In this study, we aimed to explore the association between genetic polymorphisms and lung cancer risk in the Chinese Han population. We selected and genotyped six SNPs in the gene using the Agena MassARRAY system in 507 lung cancer patients and 507 healthy controls. The association between variants and lung cancer risk was assessed using logistic regression to calculate odds ratios (ORs) and 95% confidence intervals (CIs). Multi-factor dimensionality reduction (MDR) was used to analyze the impact of SNP-SNP interactions on the risk of lung cancer. The results of overall analysis indicated that rs12479210 (T vs. C: OR = 1.42, FDR- = 0.002; TC vs. CC: OR = 1.70, FDR- < 0.0001; TT vs. CC: OR = 1.77, FDR- = 0.032; TT-TC vs. CC: OR = 1.71, FDR- = 0.001; additive: OR = 1.44, FDR- = 0.001) and rs1420101 (T vs. C: OR = 1.31, FDR- = 0.036; TT-TC vs. CC: OR = 1.42, FDR- = 0.031; additive: OR = 1.30, FDR- = 0.030) were associated with an increased the risk of lung cancer among the Chinese Han population. Stratified analysis also found the association between these two SNPs and lung cancer risk. However, there were no significant association observed between the other four SNPs (rs3771180, rs3771175, rs10208293, and rs10197862) in and lung cancer risk. Furthermore, MDR analysis showed that rs12479210 was the best single model with the highest testing accuracy (0.566) and perfect CVC (10/10) for predicting lung cancer risk. The expression level of the gene is lower in lung cancer tissue than normal tissue, and there are significant differences in the expression levels of between rs12479210 and rs1420101 genetypes in lung cancer tissue ( < 0.05). Our findings suggest that genetic variants (rs12479210 and rs1420101) are associated with an increased lung cancer risk in the Chinese Han population. These risk variants may serve as biomarkers for the prevention and treatment of lung cancer.
肺癌是人类最常见的恶性疾病之一。在本研究中，我们旨在探讨中国汉族人群中基因多态性与肺癌风险之间的关联。我们使用Agena MassARRAY系统对507例肺癌患者和507例健康对照者的该基因中的6个单核苷酸多态性（SNP）进行了选择和基因分型。使用逻辑回归计算比值比（OR）和95%置信区间（CI），评估这些变异与肺癌风险之间的关联。采用多因素降维法（MDR）分析SNP-SNP相互作用对肺癌风险的影响。总体分析结果表明，rs12479210（T与C相比：OR = 1.42，FDR校正P值 = 0.002；TC与CC相比：OR = 1.70，FDR校正P值 < 0.0001；TT与CC相比：OR = 1.77，FDR校正P值 = 0.032；TT-TC与CC相比：OR = 1.71，FDR校正P值 = 0.001；加性模型：OR = 1.44，FDR校正P值 = 0.001）和rs1420101（T与C相比：OR = 1.31，FDR校正P值 = 0.036；TT-TC与CC相比：OR = 1.42，FDR校正P值 = 0.031；加性模型：OR = 1.30，FDR校正P值 = 0.030）与中国汉族人群肺癌风险增加相关。分层分析也发现这两个SNP与肺癌风险之间存在关联。然而，未观察到其他四个SNP（rs3771180、rs3771175、rs10208293和rs10197862）与肺癌风险之间存在显著关联。此外，MDR分析表明，rs12479210是预测肺癌风险的最佳单因素模型，具有最高的检验准确性（0.566）和完美的交叉验证一致性（10/10）。该基因在肺癌组织中的表达水平低于正常组织，且肺癌组织中rs12479210和rs1420101基因型之间的表达水平存在显著差异（P < 0.05）。我们的研究结果表明，该基因变异（rs12479210和rs1420101）与中国汉族人群肺癌风险增加相关。这些风险变异可能作为肺癌预防和治疗的生物标志物。
