Wang Chenji, Pu Weilin, Zhao Dunmei, Zhou Yinghui, Lu Ting, Chen Sidi, He Zhenglei, Feng Xulong, Wang Ying, Li Caihua, Li Shilin, Jin Li, Guo Shicheng, Wang Jiucun, Wang Minghua
Department of Biochemistry and Molecular Biology, Medical College, Soochow University, Suzhou, China.
State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China.
Front Genet. 2018 Sep 5;9:356. doi: 10.3389/fgene.2018.00356. eCollection 2018.
DNA methylation-based biomarkers were suggested to be promising for early cancer diagnosis. However, DNA methylation-based biomarkers for esophageal squamous cell carcinoma (ESCC), especially in Chinese Han populations have not been identified and evaluated quantitatively. Candidate tumor suppressor genes ( = 65) were selected through literature searching and four public high-throughput DNA methylation microarray datasets including 136 samples totally were collected for initial confirmation. Targeted bisulfite sequencing was applied in an independent cohort of 94 pairs of ESCC and normal tissues from a Chinese Han population for eventual validation. We applied nine different classification algorithms for the prediction to evaluate to the prediction performance. and were identified and validated in the ESCC samples from a Chinese Han population. All four candidate regions were validated to be significantly hyper-methylated in ESCC samples through Wilcoxon rank-sum test (, = 1.7 × 10; , = 2.9 × 10; , = 3.9 × 10; , = 3.4 × 10). Logistic regression based prediction model shown a moderately ESCC classification performance (Sensitivity = 66%, Specificity = 87%, AUC = 0.81). Moreover, advanced classification method had better performances (random forest and naive Bayes). Interestingly, the diagnostic performance could be improved in non-alcohol use subgroup (AUC = 0.84). In conclusion, our data demonstrate the methylation panel of , , and could be an effective methylation-based diagnostic assay for ESCC.
基于DNA甲基化的生物标志物被认为在癌症早期诊断方面具有潜力。然而,针对食管鳞状细胞癌(ESCC)的基于DNA甲基化的生物标志物,尤其是在中国汉族人群中,尚未得到鉴定和定量评估。通过文献检索选择了65个候选肿瘤抑制基因,并收集了四个公共高通量DNA甲基化微阵列数据集(共136个样本)进行初步验证。在一个来自中国汉族人群的94对ESCC和正常组织的独立队列中应用靶向亚硫酸氢盐测序进行最终验证。我们应用九种不同的分类算法进行预测,以评估预测性能。在中国汉族人群的ESCC样本中鉴定并验证了相关基因。通过Wilcoxon秩和检验,所有四个候选区域在ESCC样本中均被验证为显著高甲基化(区域1,P = 1.7 × 10;区域2,P = 2.9 × 10;区域3,P = 3.9 × 10;区域4,P = 3.4 × 10)。基于逻辑回归的预测模型显示出中等的ESCC分类性能(敏感性 = 66%,特异性 = 87%,AUC = 0.81)。此外,先进的分类方法表现更好(随机森林和朴素贝叶斯)。有趣的是,在不饮酒亚组中诊断性能可以提高(AUC = 0.84)。总之,我们的数据表明,相关基因的甲基化面板可能是一种有效的基于甲基化的ESCC诊断检测方法。