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| Early Diagnosis of Lung Cancer Based on Breath Specific VOCs Screening and Model Assessment |
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| DOI： |
| KeyWord:lung cancer volatile organic compounds breath biomarkers diagnosis model gas chromatography－mass spectrometry |
| Author | Institution |
| RU Li-hua，L? Wei，WANG Xiang-qi，ZHANG Zhi-juan |
1. College of Pharmacy，Henan University of Chinese Medicine，Zhengzhou ，China; 2. The Third Affiliated Hospital of Henan University of Chinese Medicine，Zhengzhou ，China; 3. Institute of Mass Spectrometer and Atmospheric Environment，Jinan University，Guangzhou ，China |
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| Abstract: |
| A gas chromatography－mass spectrometry（GC－MS） was adopted to detect the breath samples of 180 subjects in this paper，including 79 patients with lung cancer and 101 healthy controls. A total of 92 volatile organic compounds（VOCs） were detected. Furthermore，10 potential characteristic VOCs for lung cancer patients were screened out by orthogonal partial least－squares discrimination analysis（OPLS－DA） model combined with Mann－Whitney test，including benzaldehyde，cis-2-butene，2-butanone，naphthalene，vinyl acetate，ethylene，2，2，4-trimethylpentane，3-methylpentane，hexanal and 2-methylpentane. Thereafter，the metabolic differences in different populations and possible related metabolic mechanisms were analyzed using statistical method. Then，the diagnostic performance of candidate breath VOC biomarkers for lung cancer were verified by establishing machine learning models. The results showed that，the diagnostic accuracy，precision，sensitivity and specificity of random forests were 96.25%，96.21%，95.76% and 96.67%，respectively，and the Matthews correlation coefficient（MCC） was 0.93，the area under ROC curve was 0.96. All the 10 compounds could be taken as the potential breath VOC biomarkers for discriminating lung cancer and health people，which have supplied rich basic data for early diagnosis of lung cancer. |
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