ArticleCancers2024
Discrimination of Lung Cancer and Benign Lung Diseases Using BALF Exosome DNA Methylation Profile.
Article in Cancers, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed.
- Review
- Circulating extracellular vesicle PTPRO methylation: an exploratory biomarker for minimally invasive diagnosis of early-stage lung adenocarcinoma.Cancer cell international · 2026Article
- Quantification of EV-associated miRNA in liquid biopsies for biomarker signature development.Extracellular vesicles and circulating nucleic acids · 2026Review
- Long interspersed nuclear element 1 methylation in non-small cell lung cancer: implications for diagnosis, prognosis, and therapeutic targeting.Cell communication and signaling : CCS · 2025Review
- Construction and analysis of the invasive prediction model for pulmonary nodules: based on clinical, CT image and DNA methylation characteristics.Journal of thoracic disease · 2025Article
- The detection, biological function, and liquid biopsy application of extracellular vesicle-associated DNA.Biomarker research · 2024Review
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Benign lung diseases are common and often do not require specific treatment, but they pose challenges in the distinguishing of them from lung cancer during low-dose computed tomography (LDCT). This study presents a comprehensive methylation analysis using real-time PCR for minimally invasive diagnoses of lung cancer via employing BALF exosome DNA. A panel of seven epigenetic biomarkers was identified, exhibiting specific methylation patterns in lung cancer BALF exosome DNA. This panel achieved an area under the curve (AUC) of 0.97, with sensitivity and specificity rates of 88.24% and 97.14%, respectively. Each biomarker showed significantly higher mean methylation levels (MMLs) in both non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC) compared to non-cancer groups, with fold changes from 1.7 to 13.36. The MMLs of the biomarkers were found to be moderately elevated with increasing patient age and smoking history, regardless of sex. A strong correlation was found between the MMLs and NSCLC stage progression, with detection sensitivities of 79% for early stages and 92% for advanced stages. In the validation cohort, the model demonstrated an AUC of 0.95, with 94% sensitivity and specificity. Sensitivity for early-stage NSCLC detection improved from 88.00% to 92.00% when smoking history was included as an additional risk factor.
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Registered trials
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