Diagnosis of pulmonary nodules by DNA methylation analysis in bronchoalveolar lavage fluids.
Bronchoalveolar lavage fluid
Diagnosis
Methylation markers
Pulmonary nodules
Journal
Clinical epigenetics
ISSN: 1868-7083
Titre abrégé: Clin Epigenetics
Pays: Germany
ID NLM: 101516977
Informations de publication
Date de publication:
07 10 2021
07 10 2021
Historique:
received:
16
06
2021
accepted:
30
08
2021
entrez:
8
10
2021
pubmed:
9
10
2021
medline:
19
2
2022
Statut:
epublish
Résumé
Lung cancer is the leading cause of cancer-related mortality. The alteration of DNA methylation plays a major role in the development of lung cancer. Methylation biomarkers become a possible method for lung cancer diagnosis. We identified eleven lung cancer-specific methylation markers (CDO1, GSHR, HOXA11, HOXB4-1, HOXB4-2, HOXB4-3, HOXB4-4, LHX9, MIR196A1, PTGER4-1, and PTGER4-2), which could differentiate benign and malignant pulmonary nodules. The methylation levels of these markers are significantly higher in malignant tissues. In bronchoalveolar lavage fluid (BALF) samples, the methylation signals maintain the same differential trend as in tissues. An optimal 5-marker model for pulmonary nodule diagnosis (malignant vs. benign) was developed from all possible combinations of the eleven markers. In the test set (57 tissue and 71 BALF samples), the area under curve (AUC) value achieves 0.93, and the overall sensitivity is 82% at the specificity of 91%. In an independent validation set (111 BALF samples), the AUC is 0.82 with a specificity of 82% and a sensitivity of 70%. This model can differentiate pulmonary adenocarcinoma and squamous carcinoma from benign diseases, especially for infection, inflammation, and tuberculosis. The model's performance is not affected by gender, age, smoking history, or the solid components of nodules.
Sections du résumé
BACKGROUND
Lung cancer is the leading cause of cancer-related mortality. The alteration of DNA methylation plays a major role in the development of lung cancer. Methylation biomarkers become a possible method for lung cancer diagnosis.
RESULTS
We identified eleven lung cancer-specific methylation markers (CDO1, GSHR, HOXA11, HOXB4-1, HOXB4-2, HOXB4-3, HOXB4-4, LHX9, MIR196A1, PTGER4-1, and PTGER4-2), which could differentiate benign and malignant pulmonary nodules. The methylation levels of these markers are significantly higher in malignant tissues. In bronchoalveolar lavage fluid (BALF) samples, the methylation signals maintain the same differential trend as in tissues. An optimal 5-marker model for pulmonary nodule diagnosis (malignant vs. benign) was developed from all possible combinations of the eleven markers. In the test set (57 tissue and 71 BALF samples), the area under curve (AUC) value achieves 0.93, and the overall sensitivity is 82% at the specificity of 91%. In an independent validation set (111 BALF samples), the AUC is 0.82 with a specificity of 82% and a sensitivity of 70%.
CONCLUSIONS
This model can differentiate pulmonary adenocarcinoma and squamous carcinoma from benign diseases, especially for infection, inflammation, and tuberculosis. The model's performance is not affected by gender, age, smoking history, or the solid components of nodules.
Identifiants
pubmed: 34620221
doi: 10.1186/s13148-021-01163-w
pii: 10.1186/s13148-021-01163-w
pmc: PMC8499516
doi:
Substances chimiques
Biomarkers, Tumor
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
185Subventions
Organisme : national natural science foundation of china
ID : 81871890
Organisme : national natural science foundation of china
ID : 91859203
Organisme : cams innovation fund for medical science
ID : 2019TX310002
Organisme : sichuan science and technology program
ID : 2019YFS0339
Organisme : sichuan science and technology program
ID : 18ZDYF2174
Organisme : chengdu science and technology program projects
ID : 2017-CY02-00017-GX
Organisme : sichuan international / hong kong, macao and taiwan science and technology innovation cooperation project
ID : 2018hh0161
Organisme : scheme of guangzhou economic and technological development district for leading talents in innovation and entrepreneurship grant
ID : 2017-L152
Organisme : scheme of guangzhou for leading talents in innovation and entrepreneurship grant
ID : 2016007
Organisme : scheme of guangzhou for leading team in innovation grant
ID : 201909010010
Organisme : science and technology planning project of guangdong province grant
ID : 2017B020226005
Informations de copyright
© 2021. The Author(s).
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