良性肺部疾病很常见，通常不需要特殊治疗，但在低剂量计算机断层扫描 (LDCT) 期间将良性肺部疾病与肺癌区分开来提出了挑战。本研究采用实时 PCR 进行全面的甲基化分析，通过 BALF 外泌体 DNA 进行肺癌微创诊断。鉴定出一组七个表观遗传生物标志物，在肺癌 BALF 外泌体 DNA 中表现出特定的甲基化模式。该面板的曲线下面积 (AUC) 为 0.97，敏感性和特异性率分别为 88.24% 和 97.14%。与非癌症组相比，非小细胞肺癌 (NSCLC) 和小细胞肺癌 (SCLC) 中每种生物标志物的平均甲基化水平 (MML) 均显着升高，倍数变化范围为 1.7 至 13.36。研究发现，无论性别如何，生物标志物的 MML 都会随着患者年龄和吸烟史的增加而适度升高。 MML 与 NSCLC 分期进展之间存在很强的相关性，早期阶段的检测灵敏度为 79%，晚期阶段的检测灵敏度为 92%。在验证队列中，该模型的 AUC 为 0.95，敏感性和特异性均为 94%。当吸烟史作为额外的危险因素时，早期 NSCLC 检测的敏感性从 88.00% 提高到 92.00%。

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.