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

Content Provider	Springer Nature : BioMed Central
Author	Hu, Shuo Tao, Jinsheng Peng, Minhua Ye, Zhujia Chen, Zhiwei Chen, Haisheng Yu, Haifeng Wang, Bo Fan, Jian-Bing Ni, Bin
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
Related Links	https://biomarkerres.biomedcentral.com/counter/pdf/10.1186/s40364-023-00486-5.pdf
Ending Page	11
Page Count	11
Starting Page	1
File Format	HTM / HTML
ISSN	20507771
DOI	10.1186/s40364-023-00486-5
Journal	Biomarker Research
Issue Number	1
Volume Number	11
Language	English
Publisher	BioMed Central
Publisher Date	2023-04-26
Access Restriction	Open
Subject Keyword	Biomedicine Cancer Research DNA methylation Differential methylated region Early diagnosis Lung cancer Noninvasive
Content Type	Text
Resource Type	Article
Subject	Biochemistry (medical) Molecular Medicine Clinical Biochemistry
Journal Impact Factor	9.5/2023
5-Year Journal Impact Factor	9.4/2023

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