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Accurate detection of early-stage lung cancer using a panel of circulating cell-free DNA methylation biomarkers

BACKGROUND: Lung cancer remains the leading cause of cancer mortality worldwide. Early detection of lung cancer helps improve treatment and survival. Numerous aberrant DNA methylations have been reported in early-stage lung cancer. Here, we sought to identify novel DNA methylation biomarkers that co...

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Autores principales: Hu, Shuo, Tao, Jinsheng, Peng, Minhua, Ye, Zhujia, Chen, Zhiwei, Chen, Haisheng, Yu, Haifeng, Wang, Bo, Fan, Jian-Bing, Ni, Bin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10134678/
https://www.ncbi.nlm.nih.gov/pubmed/37101220
http://dx.doi.org/10.1186/s40364-023-00486-5
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author Hu, Shuo
Tao, Jinsheng
Peng, Minhua
Ye, Zhujia
Chen, Zhiwei
Chen, Haisheng
Yu, Haifeng
Wang, Bo
Fan, Jian-Bing
Ni, Bin
author_facet Hu, Shuo
Tao, Jinsheng
Peng, Minhua
Ye, Zhujia
Chen, Zhiwei
Chen, Haisheng
Yu, Haifeng
Wang, Bo
Fan, Jian-Bing
Ni, Bin
author_sort Hu, Shuo
collection PubMed
description BACKGROUND: Lung cancer remains the leading cause of cancer mortality worldwide. Early detection of lung cancer helps improve treatment and survival. Numerous aberrant DNA methylations have been reported in early-stage lung cancer. Here, we sought to identify novel DNA methylation biomarkers that could potentially be used for noninvasive early diagnosis of lung cancers. METHODS: This prospective-specimen collection and retrospective-blinded-evaluation trial enrolled a total of 317 participants (198 tissues and 119 plasmas) comprising healthy controls, patients with lung cancer and benign disease between January 2020 and December 2021. Tissue and plasma samples were subjected to targeted bisulfite sequencing with a lung cancer specific panel targeting 9,307 differential methylation regions (DMRs). DMRs associated with lung cancer were identified by comparing the methylation profiles of tissue samples from patients with lung cancer and benign disease. Markers were selected with minimum redundancy and maximum relevance algorithm. A prediction model for lung cancer diagnosis was built through logistic regression algorithm and validated independently in tissue samples. Furthermore, the performance of this developed model was evaluated in a set of plasma cell-free DNA (cfDNA) samples. RESULTS: We identified 7 DMRs corresponding to 7 differentially methylated genes (DMGs) including HOXB4, HOXA7, HOXD8, ITGA4, ZNF808, PTGER4, and B3GNTL1 that were highly associated with lung cancer by comparing the methylation profiles of lung cancer and benign nodule tissue. Based on the 7-DMR biomarker panel, we developed a new diagnostic model in tissue samples, termed “7-DMR model”, to distinguish lung cancers from benign diseases, achieving AUCs of 0.97 (95%CI: 0.93-1.00)/0.96 (0.92-1.00), sensitivities of 0.89 (0.82–0.95)/0.92 (0.86–0.98), specificities of 0.94 (0.89–0.99)/1.00 (1.00–1.00), and accuracies of 0.90 (0.84–0.96)/0.94 (0.89–0.99) in the discovery cohort (n = 96) and the independent validation cohort (n = 81), respectively. Furthermore, the 7-DMR model was applied to noninvasive discrimination of lung cancers and non-lung cancers including benign lung diseases and healthy controls in an independent validation cohort of plasma samples (n = 106), yielding an AUC of 0.94 (0.86-1.00), sensitivity of 0.81 (0.73–0.88), specificity of 0.98 (0.95-1.00), and accuracy of 0.93 (0.89–0.98). CONCLUSION: The 7 novel DMRs could be promising methylation biomarkers that merits further development as a noninvasive test for early detection of lung cancer. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40364-023-00486-5.
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spelling pubmed-101346782023-04-28 Accurate detection of early-stage lung cancer using a panel of circulating cell-free DNA methylation biomarkers Hu, Shuo Tao, Jinsheng Peng, Minhua Ye, Zhujia Chen, Zhiwei Chen, Haisheng Yu, Haifeng Wang, Bo Fan, Jian-Bing Ni, Bin Biomark Res Research BACKGROUND: Lung cancer remains the leading cause of cancer mortality worldwide. Early detection of lung cancer helps improve treatment and survival. Numerous aberrant DNA methylations have been reported in early-stage lung cancer. Here, we sought to identify novel DNA methylation biomarkers that could potentially be used for noninvasive early diagnosis of lung cancers. METHODS: This prospective-specimen collection and retrospective-blinded-evaluation trial enrolled a total of 317 participants (198 tissues and 119 plasmas) comprising healthy controls, patients with lung cancer and benign disease between January 2020 and December 2021. Tissue and plasma samples were subjected to targeted bisulfite sequencing with a lung cancer specific panel targeting 9,307 differential methylation regions (DMRs). DMRs associated with lung cancer were identified by comparing the methylation profiles of tissue samples from patients with lung cancer and benign disease. Markers were selected with minimum redundancy and maximum relevance algorithm. A prediction model for lung cancer diagnosis was built through logistic regression algorithm and validated independently in tissue samples. Furthermore, the performance of this developed model was evaluated in a set of plasma cell-free DNA (cfDNA) samples. RESULTS: We identified 7 DMRs corresponding to 7 differentially methylated genes (DMGs) including HOXB4, HOXA7, HOXD8, ITGA4, ZNF808, PTGER4, and B3GNTL1 that were highly associated with lung cancer by comparing the methylation profiles of lung cancer and benign nodule tissue. Based on the 7-DMR biomarker panel, we developed a new diagnostic model in tissue samples, termed “7-DMR model”, to distinguish lung cancers from benign diseases, achieving AUCs of 0.97 (95%CI: 0.93-1.00)/0.96 (0.92-1.00), sensitivities of 0.89 (0.82–0.95)/0.92 (0.86–0.98), specificities of 0.94 (0.89–0.99)/1.00 (1.00–1.00), and accuracies of 0.90 (0.84–0.96)/0.94 (0.89–0.99) in the discovery cohort (n = 96) and the independent validation cohort (n = 81), respectively. Furthermore, the 7-DMR model was applied to noninvasive discrimination of lung cancers and non-lung cancers including benign lung diseases and healthy controls in an independent validation cohort of plasma samples (n = 106), yielding an AUC of 0.94 (0.86-1.00), sensitivity of 0.81 (0.73–0.88), specificity of 0.98 (0.95-1.00), and accuracy of 0.93 (0.89–0.98). CONCLUSION: The 7 novel DMRs could be promising methylation biomarkers that merits further development as a noninvasive test for early detection of lung cancer. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40364-023-00486-5. BioMed Central 2023-04-26 /pmc/articles/PMC10134678/ /pubmed/37101220 http://dx.doi.org/10.1186/s40364-023-00486-5 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Hu, Shuo
Tao, Jinsheng
Peng, Minhua
Ye, Zhujia
Chen, Zhiwei
Chen, Haisheng
Yu, Haifeng
Wang, Bo
Fan, Jian-Bing
Ni, Bin
Accurate detection of early-stage lung cancer using a panel of circulating cell-free DNA methylation biomarkers
title Accurate detection of early-stage lung cancer using a panel of circulating cell-free DNA methylation biomarkers
title_full Accurate detection of early-stage lung cancer using a panel of circulating cell-free DNA methylation biomarkers
title_fullStr Accurate detection of early-stage lung cancer using a panel of circulating cell-free DNA methylation biomarkers
title_full_unstemmed Accurate detection of early-stage lung cancer using a panel of circulating cell-free DNA methylation biomarkers
title_short Accurate detection of early-stage lung cancer using a panel of circulating cell-free DNA methylation biomarkers
title_sort accurate detection of early-stage lung cancer using a panel of circulating cell-free dna methylation biomarkers
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10134678/
https://www.ncbi.nlm.nih.gov/pubmed/37101220
http://dx.doi.org/10.1186/s40364-023-00486-5
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