Cargando…

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

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 b...

Descripción completa

Detalles Bibliográficos
Autores principales: Guo, Shicheng, Yan, Fengyang, Xu, Jibin, Bao, Yang, Zhu, Ji, Wang, Xiaotian, Wu, Junjie, Li, Yi, Pu, Weilin, Liu, Yan, Jiang, Zhengwen, Ma, Yanyun, Chen, Xiaofeng, Xiong, Momiao, Jin, Li, Wang, Jiucun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4318209/
https://www.ncbi.nlm.nih.gov/pubmed/25657825
http://dx.doi.org/10.1186/s13148-014-0035-3
_version_ 1782355823581724672
author Guo, Shicheng
Yan, Fengyang
Xu, Jibin
Bao, Yang
Zhu, Ji
Wang, Xiaotian
Wu, Junjie
Li, Yi
Pu, Weilin
Liu, Yan
Jiang, Zhengwen
Ma, Yanyun
Chen, Xiaofeng
Xiong, Momiao
Jin, Li
Wang, Jiucun
author_facet Guo, Shicheng
Yan, Fengyang
Xu, Jibin
Bao, Yang
Zhu, Ji
Wang, Xiaotian
Wu, Junjie
Li, Yi
Pu, Weilin
Liu, Yan
Jiang, Zhengwen
Ma, Yanyun
Chen, Xiaofeng
Xiong, Momiao
Jin, Li
Wang, Jiucun
author_sort Guo, Shicheng
collection PubMed
description 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13148-014-0035-3) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-4318209
institution National Center for Biotechnology Information
language English
publishDate 2015
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-43182092015-02-06 Identification and validation of the methylation biomarkers of non-small cell lung cancer (NSCLC) Guo, Shicheng Yan, Fengyang Xu, Jibin Bao, Yang Zhu, Ji Wang, Xiaotian Wu, Junjie Li, Yi Pu, Weilin Liu, Yan Jiang, Zhengwen Ma, Yanyun Chen, Xiaofeng Xiong, Momiao Jin, Li Wang, Jiucun Clin Epigenetics Research 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13148-014-0035-3) contains supplementary material, which is available to authorized users. BioMed Central 2015-01-22 /pmc/articles/PMC4318209/ /pubmed/25657825 http://dx.doi.org/10.1186/s13148-014-0035-3 Text en © Guo et al.; licensee BioMed Central. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Guo, Shicheng
Yan, Fengyang
Xu, Jibin
Bao, Yang
Zhu, Ji
Wang, Xiaotian
Wu, Junjie
Li, Yi
Pu, Weilin
Liu, Yan
Jiang, Zhengwen
Ma, Yanyun
Chen, Xiaofeng
Xiong, Momiao
Jin, Li
Wang, Jiucun
Identification and validation of the methylation biomarkers of non-small cell lung cancer (NSCLC)
title Identification and validation of the methylation biomarkers of non-small cell lung cancer (NSCLC)
title_full Identification and validation of the methylation biomarkers of non-small cell lung cancer (NSCLC)
title_fullStr Identification and validation of the methylation biomarkers of non-small cell lung cancer (NSCLC)
title_full_unstemmed Identification and validation of the methylation biomarkers of non-small cell lung cancer (NSCLC)
title_short Identification and validation of the methylation biomarkers of non-small cell lung cancer (NSCLC)
title_sort identification and validation of the methylation biomarkers of non-small cell lung cancer (nsclc)
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4318209/
https://www.ncbi.nlm.nih.gov/pubmed/25657825
http://dx.doi.org/10.1186/s13148-014-0035-3
work_keys_str_mv AT guoshicheng identificationandvalidationofthemethylationbiomarkersofnonsmallcelllungcancernsclc
AT yanfengyang identificationandvalidationofthemethylationbiomarkersofnonsmallcelllungcancernsclc
AT xujibin identificationandvalidationofthemethylationbiomarkersofnonsmallcelllungcancernsclc
AT baoyang identificationandvalidationofthemethylationbiomarkersofnonsmallcelllungcancernsclc
AT zhuji identificationandvalidationofthemethylationbiomarkersofnonsmallcelllungcancernsclc
AT wangxiaotian identificationandvalidationofthemethylationbiomarkersofnonsmallcelllungcancernsclc
AT wujunjie identificationandvalidationofthemethylationbiomarkersofnonsmallcelllungcancernsclc
AT liyi identificationandvalidationofthemethylationbiomarkersofnonsmallcelllungcancernsclc
AT puweilin identificationandvalidationofthemethylationbiomarkersofnonsmallcelllungcancernsclc
AT liuyan identificationandvalidationofthemethylationbiomarkersofnonsmallcelllungcancernsclc
AT jiangzhengwen identificationandvalidationofthemethylationbiomarkersofnonsmallcelllungcancernsclc
AT mayanyun identificationandvalidationofthemethylationbiomarkersofnonsmallcelllungcancernsclc
AT chenxiaofeng identificationandvalidationofthemethylationbiomarkersofnonsmallcelllungcancernsclc
AT xiongmomiao identificationandvalidationofthemethylationbiomarkersofnonsmallcelllungcancernsclc
AT jinli identificationandvalidationofthemethylationbiomarkersofnonsmallcelllungcancernsclc
AT wangjiucun identificationandvalidationofthemethylationbiomarkersofnonsmallcelllungcancernsclc