Diagnosis of pulmonary nodules by DNA methylation analysis in bronchoalveolar lavage fluids
Autor: | Qiaoyun Huang, Yanying Liu, Weihe Liang, Jing Jin, Weimin Li, Sai Yang, Yingying Zhu, Zhujia Ye, Lei Li, Jiehan Xu, Jian-Bing Fan, Jinsheng Tao, Dan Liu, Hao Yang, Mengzhu Yang, Zhiwei Chen, Siyu Chen, Bo Wang |
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Rok vydání: | 2021 |
Předmět: |
Male
Pathology medicine.medical_specialty Tuberculosis Inflammation Methylation markers Diagnosis Biomarkers Tumor Genetics medicine Humans Lung cancer Lung Molecular Biology Genetics (clinical) Aged medicine.diagnostic_test business.industry Research Bronchoalveolar lavage fluid Methylation DNA Methylation Middle Aged medicine.disease Squamous carcinoma Bronchoalveolar lavage medicine.anatomical_structure DNA methylation Multiple Pulmonary Nodules Female medicine.symptom business Pulmonary nodules Developmental Biology |
Zdroj: | Clinical Epigenetics |
ISSN: | 1868-7083 1868-7075 |
DOI: | 10.1186/s13148-021-01163-w |
Popis: | BackgroundLung 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.ResultsWe identified eleven lung cancer-specific methylation markers (CDO1, GSHR, HOXA11, HOXB4-1, HOXB4-2, HOXB4-3, HOXB4-4, LHX9, MIR196A1,PTGER4-1,andPTGER4-2), 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%.ConclusionsThis 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. |
Databáze: | OpenAIRE |
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