Non-invasive diagnosis of pulmonary nodules by circulating tumor DNA methylation: A prospective multicenter study

IF 4.5 2区 医学 Q1 ONCOLOGY
Ying Li , Fangfang Xie , Qiang Zheng , Yujun Zhang , Wei Li , Minjie Xu , Qiye He , Yuan Li , Jiayuan Sun
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引用次数: 0

Abstract

Background

With the popularization of computed tomography, more and more pulmonary nodules (PNs) are being detected. Risk stratification of PNs is essential for detecting early-stage lung cancer while minimizing the overdiagnosis of benign nodules. This study aimed to develop a circulating tumor DNA (ctDNA) methylation-based, non-invasive model for the risk stratification of PNs.

Methods

A blood-based assay (“LUNG-TRAC”) was designed to include novel lung cancer ctDNA methylation markers identified from in-house reduced representative bisulfite sequencing data and known markers from the literature. A stratification model was trained based on 183 ctDNA samples derived from patients with benign or malignant PNs and validated in 62 patients. LUNG-TRAC was further single-blindly tested in a single- and multi-center cohort.

Results

The LUNG-TRAC model achieved an area under the curve (AUC) of 0.810 (sensitivity = 74.4 % and specificity = 73.7 %) in the validation set. Two test sets were used to evaluate the performance of LUNG-TRAC, with an AUC of 0.815 in the single-center test (N = 61; sensitivity = 67.5 % and specificity = 76.2 %) and 0.761 in the multi-center test (N = 95; sensitivity = 50.7 % and specificity = 80.8 %). The clinical utility of LUNG-TRAC was further assessed by comparing it to two established risk stratification models: the Mayo Clinic and Veteran Administration models. It outperformed both in the validation and the single-center test sets.

Conclusion

The LUNG-TRAC model demonstrated accuracy and consistency in stratifying PNs for the risk of malignancy, suggesting its utility as a non-invasive diagnostic aid for early-stage peripheral lung cancer.

Clinical trial registration

www.clinicaltrials.gov (NCT03989219).

通过循环肿瘤 DNA 甲基化对肺结节进行无创诊断:一项前瞻性多中心研究
背景随着计算机断层扫描的普及,越来越多的肺结节(PNs)被发现。对肺结节进行风险分层对于检测早期肺癌同时减少良性结节的过度诊断至关重要。本研究旨在开发一种基于循环肿瘤 DNA(ctDNA)甲基化的无创模型,用于对肺结节进行风险分层。方法设计了一种基于血液的检测方法("LUNG-TRAC"),其中包括从内部还原的代表性亚硫酸氢盐测序数据中确定的新型肺癌ctDNA甲基化标记物和文献中的已知标记物。根据良性或恶性肺结核患者的 183 份 ctDNA 样本训练了分层模型,并在 62 名患者中进行了验证。结果LUNG-TRAC模型在验证集中的曲线下面积(AUC)达到0.810(灵敏度=74.4%,特异度=73.7%)。两个测试集用于评估 LUNG-TRAC 的性能,单中心测试的 AUC 为 0.815(样本数=61;灵敏度=67.5%,特异度=76.2%),多中心测试的 AUC 为 0.761(样本数=95;灵敏度=50.7%,特异度=80.8%)。通过将 LUNG-TRAC 与两种成熟的风险分层模型(梅奥诊所模型和退伍军人管理局模型)进行比较,进一步评估了 LUNG-TRAC 的临床实用性。结论LUNG-TRAC模型在对PN进行恶性肿瘤风险分层方面表现出了准确性和一致性,表明它可以作为早期周围型肺癌的无创诊断辅助工具。临床试验注册www.clinicaltrials.gov (NCT03989219)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Lung Cancer
Lung Cancer 医学-呼吸系统
CiteScore
9.40
自引率
3.80%
发文量
407
审稿时长
25 days
期刊介绍: Lung Cancer is an international publication covering the clinical, translational and basic science of malignancies of the lung and chest region.Original research articles, early reports, review articles, editorials and correspondence covering the prevention, epidemiology and etiology, basic biology, pathology, clinical assessment, surgery, chemotherapy, radiotherapy, combined treatment modalities, other treatment modalities and outcomes of lung cancer are welcome.
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