Application of chemoresistive gas sensors and chemometric analysis to differentiate the fingerprints of global volatile organic compounds from diseases. Preliminary results of COPD, lung cancer and breast cancer
| Autor: | Carlos Domínguez-Reyes, Patricia Gorocica-Rosete, Rogelio Pérez-Padilla, Rogelio Flores-Ramírez, Lorena Díaz de León-Martínez, Garima Mehta, Blanca Nohemí Zamora-Mendoza, Omar Ornelas-Rebolledo, Maribel Rodríguez-Aguilar, Juan Alberto Tenorio-Torres |
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| Rok vydání: | 2021 |
| Předmět: |
0301 basic medicine
Oncology medicine.medical_specialty Multivariate analysis Lung Neoplasms Screening test Clinical Biochemistry Breast Neoplasms Biochemistry 03 medical and health sciences Pulmonary Disease Chronic Obstructive 0302 clinical medicine Breast cancer Internal medicine medicine Humans Single-Blind Method Lung cancer COPD Volatile Organic Compounds Electronic nose business.industry Biochemistry (medical) General Medicine medicine.disease Control subjects 030104 developmental biology Cross-Sectional Studies Breath Tests 030220 oncology & carcinogenesis Principal component analysis Female business |
| Zdroj: | Clinica chimica acta; international journal of clinical chemistry. 518 |
| ISSN: | 1873-3492 |
| Popis: | Background Analysis of volatile organic compounds (VOCs) in exhaled breath has been proposed as a screening method that discriminates between disease and healthy subjects, few studies evaluate whether these chemical fingerprints are specific when compared between diseases. We evaluated global VOCs and their discrimination capacity in chronic obstructive pulmonary disease (COPD), lung cancer, breast cancer and healthy subjects by chemoresistive sensors and chemometric analysis. Methods A cross-sectional study was conducted with the participation of 30 patients with lung cancer, 50 with breast cancer, 50 with COPD and 50 control subjects. Each participant's exhaled breath was analyzed with the electronic nose. A multivariate analysis was carried: principal component analysis (PCA) and, canonical analysis of principal coordinates (CAP). Twenty single-blind samples from the 4 study groups were evaluated by CAP. Results A separation between the groups of patients to the controls was achieved through PCA with explanations of >90% of the data and with a correct classification of 100%. In the CAP of the 4 study groups, discrimination between the diseases was obtained with 2 canonical axes with a correct general classification of 91.35%. This model was used for the prediction of the single-blind samples resulting in correct classification of 100%. Conclusions The application of chemoresistive gas sensors and chemometric analysis can be used as a useful tool for a screening test for lung cancer, breast cancer and COPD since this equipment detects the set of VOCs present in the exhaled breath to generate a characteristic chemical fingerprint of each disease. |
| Databáze: | OpenAIRE |
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