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

Abstract 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...

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Main Authors: Shuo Hu, Jinsheng Tao, Minhua Peng, Zhujia Ye, Zhiwei Chen, Haisheng Chen, Haifeng Yu, Bo Wang, Jian-Bing Fan, Bin Ni
Format: Article
Language:English
Published: BMC 2023-04-01
Series:Biomarker Research
Subjects:
Online Access:https://doi.org/10.1186/s40364-023-00486-5
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author Shuo Hu
Jinsheng Tao
Minhua Peng
Zhujia Ye
Zhiwei Chen
Haisheng Chen
Haifeng Yu
Bo Wang
Jian-Bing Fan
Bin Ni
author_facet Shuo Hu
Jinsheng Tao
Minhua Peng
Zhujia Ye
Zhiwei Chen
Haisheng Chen
Haifeng Yu
Bo Wang
Jian-Bing Fan
Bin Ni
author_sort Shuo Hu
collection DOAJ
description Abstract 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
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spelling doaj.art-2d45502f47cc46e796c244662a708fe12023-04-30T11:23:04ZengBMCBiomarker Research2050-77712023-04-0111111110.1186/s40364-023-00486-5Accurate detection of early-stage lung cancer using a panel of circulating cell-free DNA methylation biomarkersShuo Hu0Jinsheng Tao1Minhua Peng2Zhujia Ye3Zhiwei Chen4Haisheng Chen5Haifeng Yu6Bo Wang7Jian-Bing Fan8Bin Ni9Department of Thoracic Surgery, The First Affiliated Hospital of Soochow UniversityAnchordx Medical Co., LtdAnchordx Medical Co., LtdAnchordx Medical Co., LtdAnchordx Medical Co., LtdHaian People’s HospitalThe Fifth People’s Hospital of WuxiAnchordx Medical Co., LtdAnchordx Medical Co., LtdDepartment of Thoracic Surgery, The First Affiliated Hospital of Soochow UniversityAbstract 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 abstracthttps://doi.org/10.1186/s40364-023-00486-5DNA methylationDifferential methylated regionEarly diagnosisLung cancerNoninvasive
spellingShingle Shuo Hu
Jinsheng Tao
Minhua Peng
Zhujia Ye
Zhiwei Chen
Haisheng Chen
Haifeng Yu
Bo Wang
Jian-Bing Fan
Bin Ni
Accurate detection of early-stage lung cancer using a panel of circulating cell-free DNA methylation biomarkers
Biomarker Research
DNA methylation
Differential methylated region
Early diagnosis
Lung cancer
Noninvasive
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 DNA methylation
Differential methylated region
Early diagnosis
Lung cancer
Noninvasive
url https://doi.org/10.1186/s40364-023-00486-5
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