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An epigenetic classifier for early stage lung cancer
BACKGROUND: Methylated genes detected in sputum are promise biomarkers for lung cancer. Yet the current PCR technologies for quantification of DNA methylation and diagnostic value of the sputum biomarkers are not sufficient to be used for lung cancer early detection. The emerging droplet digital PCR...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5964676/ https://www.ncbi.nlm.nih.gov/pubmed/29796119 http://dx.doi.org/10.1186/s13148-018-0502-3 |
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author | Su, Yun Fang, Hong Bin Jiang, Feng |
author_facet | Su, Yun Fang, Hong Bin Jiang, Feng |
author_sort | Su, Yun |
collection | PubMed |
description | BACKGROUND: Methylated genes detected in sputum are promise biomarkers for lung cancer. Yet the current PCR technologies for quantification of DNA methylation and diagnostic value of the sputum biomarkers are not sufficient to be used for lung cancer early detection. The emerging droplet digital PCR (ddPCR) is a straightforward means for precise, direct, and absolute quantification of nucleic acids. Here, we investigate whether ddPCR can sensitively and robustly quantify DNA methylation in sputum for more precise diagnosis of lung cancer. RESULTS: First, the analytic performance of methylation-specific ddPCR (ddMSP) and quantitative methylation-specific PCR (qMSP) is determined in methylated and unmethylated DNA samples. Second, 29 genes, previously proposed as potential sputum biomarkers for lung cancer, are analyzed by using ddMSP in a training set of 127 lung cancer patients and 159 controls. ddMSP has higher sensitivity, precision, and reproducibility for quantification of methylation compared with qMSP (all p < 0.05). A classifier comprising four sputum methylation biomarkers for lung cancer is developed by using ddMSP, producing 86.6% sensitivity and 90.6% specificity, independent of stage and histology of lung cancer (all p > 0.05). The classifier has higher accuracy compared with sputum cytology (88.8 vs. 70.6%, p < 0.01). The diagnostic performance is confirmed in a testing set of 89 cases and 107 controls. CONCLUSIONS: ddMSP is a robust tool for reliable quantification of DNA methylation in sputum, and the epigenetic classifier could help diagnose lung cancer at the early stage. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13148-018-0502-3) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5964676 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-59646762018-05-24 An epigenetic classifier for early stage lung cancer Su, Yun Fang, Hong Bin Jiang, Feng Clin Epigenetics Research BACKGROUND: Methylated genes detected in sputum are promise biomarkers for lung cancer. Yet the current PCR technologies for quantification of DNA methylation and diagnostic value of the sputum biomarkers are not sufficient to be used for lung cancer early detection. The emerging droplet digital PCR (ddPCR) is a straightforward means for precise, direct, and absolute quantification of nucleic acids. Here, we investigate whether ddPCR can sensitively and robustly quantify DNA methylation in sputum for more precise diagnosis of lung cancer. RESULTS: First, the analytic performance of methylation-specific ddPCR (ddMSP) and quantitative methylation-specific PCR (qMSP) is determined in methylated and unmethylated DNA samples. Second, 29 genes, previously proposed as potential sputum biomarkers for lung cancer, are analyzed by using ddMSP in a training set of 127 lung cancer patients and 159 controls. ddMSP has higher sensitivity, precision, and reproducibility for quantification of methylation compared with qMSP (all p < 0.05). A classifier comprising four sputum methylation biomarkers for lung cancer is developed by using ddMSP, producing 86.6% sensitivity and 90.6% specificity, independent of stage and histology of lung cancer (all p > 0.05). The classifier has higher accuracy compared with sputum cytology (88.8 vs. 70.6%, p < 0.01). The diagnostic performance is confirmed in a testing set of 89 cases and 107 controls. CONCLUSIONS: ddMSP is a robust tool for reliable quantification of DNA methylation in sputum, and the epigenetic classifier could help diagnose lung cancer at the early stage. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13148-018-0502-3) contains supplementary material, which is available to authorized users. BioMed Central 2018-05-22 /pmc/articles/PMC5964676/ /pubmed/29796119 http://dx.doi.org/10.1186/s13148-018-0502-3 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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 Su, Yun Fang, Hong Bin Jiang, Feng An epigenetic classifier for early stage lung cancer |
title | An epigenetic classifier for early stage lung cancer |
title_full | An epigenetic classifier for early stage lung cancer |
title_fullStr | An epigenetic classifier for early stage lung cancer |
title_full_unstemmed | An epigenetic classifier for early stage lung cancer |
title_short | An epigenetic classifier for early stage lung cancer |
title_sort | epigenetic classifier for early stage lung cancer |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5964676/ https://www.ncbi.nlm.nih.gov/pubmed/29796119 http://dx.doi.org/10.1186/s13148-018-0502-3 |
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