کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
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5137899 | 1494589 | 2017 | 5 صفحه PDF | دانلود رایگان |
- SPME-GC-MS as valuable tool for the identification of lung cancer biomarkers.
- Use of multivariate data analysis for discriminating healthy and carcinogenic tissues.
- Seven potential lung cancer biomarkers were identified.
- Correct classification of more than 98% of the samples.
Solid-phase microextraction and gas chromatography-mass spectrometry followed by multivariate data analysis were used to analyze lung tissues from both healthy and carcinogenic patients. A total of 78 volatile compounds belonging to different chemical classes were identified, seven of which were able to discriminate between the two groups. Discriminant analysis allowed to correctly classify 98.3% of the cases. By using the leave-one-method, 100% of the cross-validated samples belonging to the “tumor” group was correctly classified, whereas 2 cross-validated healthy samples out of 48 were erroneously allocated in the “tumor” group. Achieved results suggest the need of further investigation to assess the role of the seven identified compounds as lung cancer biomarkers in breath analysis, thus allowing the development of low-cost diagnostic devices.
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Journal: Journal of Pharmaceutical and Biomedical Analysis - Volume 146, 30 November 2017, Pages 329-333