Identification and validation of the methylation biomarkers of non-small cell lung cancer (NSCLC)

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• 作者：Shicheng Guo (1) (9)
  Fengyang Yan (1)
  Jibin Xu (2)
  Yang Bao (3)
  Ji Zhu (4)
  Xiaotian Wang (1)
  Junjie Wu (1) (5)
  Yi Li (1)
  Weilin Pu (1)
  Yan Liu (6)
  Zhengwen Jiang (6)
  Yanyun Ma (1)
  Xiaofeng Chen (7)
  Momiao Xiong (8)
  Li Jin (1) (9)
  Jiucun Wang (1) (9)
  
• 关键词：Non ; small cell lung cancer ; DNA methylation ; Biomarker ; Batch effect elimination ; Diagnosis
• 刊名：Clinical Epigenetics
• 出版年：2015
• 出版时间：December 2015
• 年：2015
• 卷：7
• 期：1
• 全文大小：1,763 KB
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• 作者单位：Shicheng Guo (1) (9)
  Fengyang Yan (1)
  Jibin Xu (2)
  Yang Bao (3)
  Ji Zhu (4)
  Xiaotian Wang (1)
  Junjie Wu (1) (5)
  Yi Li (1)
  Weilin Pu (1)
  Yan Liu (6)
  Zhengwen Jiang (6)
  Yanyun Ma (1)
  Xiaofeng Chen (7)
  Momiao Xiong (8)
  Li Jin (1) (9)
  Jiucun Wang (1) (9)
  
  1. State Key Laboratory of Genetic Engineering and Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences and Institutes of Biomedical Sciences, Fudan University Jiangwan Campus, 2005 Songhu Road, Shanghai, 200438, China
  9. Fudan-Taizhou Institute of Health Sciences, 1 Yaocheng Road, Taizhou, Jiangsu, 225300, China
  2. Department of Cardiothoracic Surgery, Changzheng Hospital of Shanghai, Fengyang Road 415, Shanghai, 200000, China
  3. Yangzhou No.1 People鈥檚 Hospital, 368 Hanjiang Road, Yangzhou, 225001, China
  4. Department of Cardiothoracic Surgery, Changhai Hospital of Shanghai, Changhai Road 168, Shanghai, 200433, China
  5. Department of Pneumology, Changhai Hospital of Shanghai, Changhai Road 168, Shanghai, 200433, China
  6. Center for Genetic & Genomic Analysis, Genesky Biotechnologies Inc., 787 Kangqiao Road, Shanghai, 201203, China
  7. Department of Cardiothoracic Surgery, Huashan Hospital, Fudan University, 12 Wulumuqi Road, Shanghai, 200040, China
  8. Human Genetics Center, The University of Texas School of Public Health, 1200 Herman Pressler, Houston, Texas, 77030, USA
  
• 刊物主题：Human Genetics; Gene Function;
• 出版者：BioMed Central
• ISSN：1868-7083

文摘

Background DNA methylation was suggested as the promising biomarker for lung cancer diagnosis. However, it is a great challenge to search for the optimal combination of methylation biomarkers to obtain maximum diagnostic performance. Results In this study, we developed a panel of DNA methylation biomarkers and validated their diagnostic efficiency for non-small cell lung cancer (NSCLC) in a large Chinese Han NSCLC retrospective cohort. Three high-throughput DNA methylation microarray datasets (458 samples) were collected in the discovery stage. After normalization, batch effect elimination and integration, significantly differentially methylated genes and the best combination of the biomarkers were determined by the leave-one-out SVM (support vector machine) feature selection procedure. Then, candidate promoters were examined by the methylation status determined single nucleotide primer extension technique (MSD-SNuPET) in an independent set of 150 pairwise NSCLC/normal tissues. Four statistical models with fivefold cross-validation were used to evaluate the performance of the discriminatory algorithms. The sensitivity, specificity and accuracy were 86.3%, 95.7% and 91%, respectively, in Bayes tree model. The logistic regression model incorporated five gene methylation signatures at AGTR1, GALR1, SLC5A8, ZMYND10 and NTSR1, adjusted for age, sex and smoking, showed robust performances in which the sensitivity, specificity, accuracy, and area under the curve (AUC) were 78%, 97%, 87%, and 0.91, respectively. Conclusions In summary, a high-throughput DNA methylation microarray dataset followed by batch effect elimination can be a good strategy to discover optimal DNA methylation diagnostic panels. Methylation profiles of AGTR1, GALR1, SLC5A8, ZMYND10 and NTSR1, could be an effective methylation-based assay for NSCLC diagnosis.