Abstract
The aim of the present study was to investigate the ability of breath analysis to distinguish lung cancer (LC) patients from patients with other respiratory diseases and healthy people. The population sample consisted of 51 patients with confirmed LC, 38 patients with pathological computed tomography (CT) findings not diagnosed with LC, and 53 healthy controls. The concentrations of 19 volatile organic compounds (VOCs) were quantified in the exhaled breath of study participants by solid phase microextraction (SPME) of the VOCs and subsequent gas chromatography-mass spectrometry (GC-MS) analysis. Kruskal–Wallis and Mann–Whitney tests were used to identify significant differences between subgroups. Machine learning methods were used to determine the discriminant power of the method. Several compounds were found to differ significantly between LC patients and healthy controls. Strong associations were identified for 2-propanol, 1-propanol, toluene, ethylbenzene, and styrene (p-values < 0.001–0.006). These associations remained significant when ambient air concentrations were subtracted from breath concentrations. VOC levels were found to be affected by ambient air concentrations and a few by smoking status. The random forest machine learning algorithm achieved a correct classification of patients of 88.5% (area under the curve—AUC 0.94). However, none of the methods used achieved adequate discrimination between LC patients and patients with abnormal computed tomography (CT) findings. Biomarker sets, consisting mainly of the exogenous monoaromatic compounds and 1- and 2- propanol, adequately discriminated LC patients from healthy controls. The breath concentrations of these compounds may reflect the alterations in patient’s physiological and biochemical status and perhaps can be used as probes for the investigation of these statuses or normalization of patient-related factors in breath analysis.
Highlights
According to the World Health Organization (WHO), cancer is the second leading cause of death globally, exceeded only by heart disease, while lung cancer is the leading cause of all cancer-related deaths [1]
We investigated the possibility of breath analysis to distinguish: (i) lung cancer patients from patients with other respiratory diseases, and (ii) lung cancer patients from healthy people on the basis of 19 breath volatile organic compounds (VOCs), previously indicated as potential lung cancer biomarkers
From the 89 patients with pathological computed tomography (CT) findings who underwent bronchoscopy with transbronchial biopsy (TBBX) and/or endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA), lung cancer was diagnosed in 51 patients, according to the results of the cytological/histological examinations
Summary
According to the World Health Organization (WHO), cancer is the second leading cause of death globally, exceeded only by heart disease, while lung cancer is the leading cause of all cancer-related deaths [1]. Cancer detection by effective screening tests has substantially decreased death rates for breast cancer, melanoma, cervical cancer, and colorectal cancer [3,4] Given these successful achievements and general acceptance of the concept that population preventive screening will reduce cancer mortality, there are currently great investments into the development of new effective screening tests and new screening strategies [5,6]. In this context, breath analysis is considered to have great potential.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
