Title: | Optimization of volatile markers of lung cancer to exclude interferences of non-malignant disease |
Author(s): | Zou Y; Zhang X; Chen X; Hu Y; Ying K; Wang P; |
Address: | "Biosensor National Special Lab, Key Lab for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, Zhejiang University, Hangzhou, Zhejiang, China. Zhejiang Sir Run Run Shaw Hospital, Department of Medicine, Zhejiang University, Hangzhou, Zhejiang, China" |
ISSN/ISBN: | 1875-8592 (Electronic) 1574-0153 (Linking) |
Abstract: | "BACKGROUND: Breath analysis became promising for noninvasive diagnosis of cancer with sophisticated spectrometry technology introduced. OBJECTIVE: This study aimed to select volatile markers for lung cancer detection, which exclude the influences from non-malignant lung diseases. METHODS: 171 subjects who were divided into three groups: patients with LC, patients with PNMD and healthy controls were enrolled in our studies as training cohort. The volatile organic compounds (VOCs) in their breath samples were analyzed with solid-phase micro-extraction/gas chromatography/mass spectrometry (SPME-GCMS). Markers were selected by receiver operating characteristic (ROC) curves. After that, 78 subjects with high morbidity of LC were employed as validation cohort. Their breath samples were analyzed by thermal desorption instrument/gas chromatography/mass spectrometry (TD-GCMS). RESULTS: Through a series of comparisons among lung cancer patients, pulmonary non-malignant diseases patients, and healthy participants in training cohort, Nonane,5-(2-methyl-)propyl-; phenol,2,6-di-tert-butyl-,4-methyl-; dodecane,2,6,11-trimethyl-; hexadecanal and pentadecane,8-hexyl- were selected as markers for lung cancer diagnosis. Principal component analysis was employ to process data from validation cohort. As results, satisfied distinctions have been obtained with detection of these five selected markers, although the detection method is not identical with that used for training cohort. CONCLUSIONS: In conclusion, with optimization method described in this paper, breath test could be an effective method for diagnosis of lung cancer and avoid the interference of pulmonary non-malignant diseases" |
Keywords: | "Biomarkers, Tumor/*metabolism Breath Tests/methods Case-Control Studies Female Humans Lung/metabolism/pathology Lung Neoplasms/*metabolism/*pathology Male Middle Aged ROC Curve Volatile Organic Compounds/*metabolism Lung cancer breath test pulmonary non-m;" |
Notes: | "MedlineZou, Yingchang Zhang, Xi Chen, Xing Hu, Yanjie Ying, Kejing Wang, Ping eng Research Support, Non-U.S. Gov't Netherlands 2014/08/30 Cancer Biomark. 2014; 14(5):371-9. doi: 10.3233/CBM-140418" |