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Metabolites

Title:		Non-Invasive Lung Cancer Diagnostics through Metabolites in Exhaled Breath: Influence of the Disease Variability and Comorbidities
Author(s):		Temerdashev AZ; Gashimova EM; Porkhanov VA; Polyakov IS; Perunov DV; Dmitrieva EV;
Address:		"Department of Analytical Chemistry, Kuban State University, Stavropol'skaya St. 149, Krasnodar 350040, Russia. Research Institute-Regional Clinical Hospital N degrees 1 n.a. Prof. S.V. Ochapovsky, 1 May St. 167, Krasnodar 350086, Russia"
Journal Title:		Metabolites
Year:		2023
Volume:		20230130
Issue:		2
Page Number:		-
DOI:		10.3390/metabo13020203
ISSN/ISBN:		2218-1989 (Print) 2218-1989 (Electronic) 2218-1989 (Linking)
Abstract:		"Non-invasive, simple, and fast tests for lung cancer diagnostics are one of the urgent needs for clinical practice. The work describes the results of exhaled breath analysis of 112 lung cancer patients and 120 healthy individuals using gas chromatography-mass spectrometry (GC-MS). Volatile organic compound (VOC) peak areas and their ratios were considered for data analysis. VOC profiles of patients with various histological types, tumor localization, TNM stage, and treatment status were considered. The effect of non-pulmonary comorbidities (chronic heart failure, hypertension, anemia, acute cerebrovascular accident, obesity, diabetes) on exhaled breath composition of lung cancer patients was studied for the first time. Significant correlations between some VOC peak areas and their ratios and these factors were found. Diagnostic models were created using gradient boosted decision trees (GBDT) and artificial neural network (ANN). The performance of developed models was compared. ANN model was the most accurate: 82-88% sensitivity and 80-86% specificity on the test data"
Keywords:		Gc-ms comorbidities exhaled breath lung cancer thermal desorption volatile organic compounds;
Notes:		"PubMed-not-MEDLINETemerdashev, Azamat Z Gashimova, Elina M Porkhanov, Vladimir A Polyakov, Igor S Perunov, Dmitry V Dmitrieva, Ekaterina V eng 22-13-20018/Russian Science Foundation/ Switzerland 2023/02/26 Metabolites. 2023 Jan 30; 13(2):203. doi: 10.3390/metabo13020203"