Cell-free DNA assay for malignancy classification of high-risk lung nodules.

Autor:	Wang S; Department of Thoracic Surgery, Jiangsu Key Laboratory of Molecular and Translational Cancer Research, Nanjing Medical University Affiliated Cancer Hospital & Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research, Nanjing, Jiangsu, China; Clinical Research Institute of Traditional Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, The Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China., Meng F; Department of Thoracic Surgery, Jiangsu Key Laboratory of Molecular and Translational Cancer Research, Nanjing Medical University Affiliated Cancer Hospital & Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research, Nanjing, Jiangsu, China., Chen P; Department of Thoracic Surgery, Jiangsu Key Laboratory of Molecular and Translational Cancer Research, Nanjing Medical University Affiliated Cancer Hospital & Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research, Nanjing, Jiangsu, China., Lv Y; Department of Information Center, The Affiliated Jiangning Hospital of Nanjing Medical University, Nanjing, Jiangsu, China., Wu M; Geneseeq Research Institute, Nanjing Geneseeq Technology Inc, Nanjing, Jiangsu, China., Tang H; Geneseeq Research Institute, Nanjing Geneseeq Technology Inc, Nanjing, Jiangsu, China., Bao H; Geneseeq Research Institute, Nanjing Geneseeq Technology Inc, Nanjing, Jiangsu, China., Wu X; Geneseeq Research Institute, Nanjing Geneseeq Technology Inc, Nanjing, Jiangsu, China., Shao Y; Geneseeq Research Institute, Nanjing Geneseeq Technology Inc, Nanjing, Jiangsu, China; School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China., Wang J; Department of Science and Technology, Nanjing Medical University Affiliated Cancer Hospital & Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research, Nanjing, Jiangsu, China; Biobank of Lung Cancer, Jiangsu Biobank of Clinical Resources, Nanjing, Jiangsu, China., Dai J; School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China; Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, Jiangsu, China., Xu L; Department of Thoracic Surgery, Jiangsu Key Laboratory of Molecular and Translational Cancer Research, Nanjing Medical University Affiliated Cancer Hospital & Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research, Nanjing, Jiangsu, China; Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, Jiangsu, China., Wang X; Clinical Research Institute of Traditional Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, The Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China. Electronic address: wxx1201@hotmail.com., Yin R; Department of Thoracic Surgery, Jiangsu Key Laboratory of Molecular and Translational Cancer Research, Nanjing Medical University Affiliated Cancer Hospital & Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research, Nanjing, Jiangsu, China; Department of Science and Technology, Nanjing Medical University Affiliated Cancer Hospital & Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research, Nanjing, Jiangsu, China; Biobank of Lung Cancer, Jiangsu Biobank of Clinical Resources, Nanjing, Jiangsu, China; Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, Jiangsu, China. Electronic address: rong_yin@njmu.edu.cn.
Jazyk:	angličtina
Zdroj:	The Journal of thoracic and cardiovascular surgery [J Thorac Cardiovasc Surg] 2024 Nov; Vol. 168 (5), pp. e140-e175. Date of Electronic Publication: 2024 Apr 24.
DOI:	10.1016/j.jtcvs.2024.04.026
Abstrakt:	Objective: Although low-dose computed tomography has been proven effective to reduce lung cancer-specific mortality, a considerable proportion of surgically resected high-risk lung nodules were still confirmed pathologically benign. There is an unmet need of a novel method for malignancy classification in lung nodules. Methods: We recruited 307 patients with high-risk lung nodules who underwent curative surgery, and 247 and 60 cases were pathologically confirmed malignant and benign lung lesions, respectively. Plasma samples from each patient were collected before surgery and performed low-depth (5×) whole-genome sequencing. We extracted cell-free DNA characteristics and determined radiomic features. We built models to classify the malignancy using our data and further validated models with 2 independent lung nodule cohorts. Results: Our models using one type of profile were able to distinguish lung cancer and benign lung nodules at an area under the curve metrics of 0.69 to 0.91 in the study cohort. Integrating all the 5 base models using cell-free DNA profiles, the cell-free DNA-based ensemble model achieved an area under the curve of 0.95 (95% CI, 0.92-0.97) in the study cohort and 0.98 (95% CI, 0.96-1.00) in the validation cohort. At a specificity of 95.0%, the sensitivity reached 80.0% in the study cohort. With the same threshold, the specificity and sensitivity had similar performances in both validation cohorts. Furthermore, the performance of area under the curve reached 0.97 in both the study and validation cohorts when considering the radiomic profile. Conclusions: The cell-free DNA profiles-based method is an efficient noninvasive tool to distinguish malignancies and high-risk but pathologically benign lung nodules. Competing Interests: Conflict of Interest Statement M.W., H.T, H.B., X.W., and Y.S. are employees of Nanjing Geneseeq Technology Inc. M.W., H.T, H.B., X.W., and Y.S. report personal fees from Nanjing Geneseeq Technology Inc., during the conduct of the study and outside the submitted work. All other authors reported no conflicts of interest. The Journal policy requires editors and reviewers to disclose conflicts of interest and to decline handling or reviewing manuscripts for which they may have a conflict of interest. The editors and reviewers of this article have no conflicts of interest. (Copyright © 2024 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.)
Databáze:	MEDLINE
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