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J Breath Res

Title:		Hybrid volatilomics in cancer diagnosis by HS-GC-FID fingerprinting
Author(s):		da Costa BRB; da Silva RR; Bigao V; Peria FM; De Martinis BS;
Address:		"Department of Clinical, Toxicological and Food Sciences, School of Pharmaceutical, Sciences of Ribeirao Preto, University of Sao Paulo, Ribeirao Preto CEP 14040-903, Brazil. Nucleo de Pesquisa em Produtos Naturais e Sinteticos (NPPNS), Department of Biomolecular Sciences, School of Pharmaceutical Sciences of Ribeirao Preto, University of Sao Paulo, Ribeirao Preto CEP 14040-903, Brazil. Division of Clinical Oncology, Ribeirao Preto Medical School, University of Sao Paulo, Ribeirao Preto CEP 14049-900, Brazil. Department of Chemistry, Faculty of Philosophy, Sciences and Letters of Ribeirao Preto, University of Sao Paulo, Ribeirao Preto CEP 14040-901, Brazil"
Journal Title:		J Breath Res
Year:		2023
Volume:		20230127
Issue:		2
Page Number:		-
DOI:		10.1088/1752-7163/acb284
ISSN/ISBN:		1752-7163 (Electronic) 1752-7155 (Linking)
Abstract:		"Assessing volatile organic compounds (VOCs) as cancer signatures is one of the most promising techniques toward developing non-invasive, simple, and affordable diagnosis. Here, we have evaluated the feasibility of employing static headspace extraction (HS) followed by gas chromatography with flame ionization detector (GC-FID) as a screening tool to discriminate between cancer patients (head and neck-HNC,n= 15; and gastrointestinal cancer-GIC,n= 19) and healthy controls (n= 37) on the basis of a non-target (fingerprinting) analysis of oral fluid and urine. We evaluated the discrimination considering a single bodily fluid and adopting the hybrid approach, in which the oral fluid and urinary VOCs profiles were combined through data fusion. We used supervised orthogonal partial least squares discriminant analysis for classification, and we assessed the prediction power of the models by analyzing the values of goodness of prediction (Q(2)Y), area under the curve (AUC), sensitivity, and specificity. The individual models HNC urine, HNC oral fluid, and GIC oral fluid successfully discriminated between healthy controls and positive samples (Q(2)Y = 0.560, 0.525, and 0.559; AUC = 0.814, 0.850, and 0.926; sensitivity = 84.8, 70.2, and 78.6%; and specificity = 82.3; 81.5; 87.5%, respectively), whereas GIC urine was not adequate (Q(2)Y = 0.292, AUC = 0.694, sensitivity = 66.1%, and specificity = 77.0%). Compared to the respective individual models, Q(2)Y for the hybrid models increased (0.623 for hybrid HNC and 0.562 for hybrid GIC). However, sensitivity was higher for HNC urine and GIC oral fluid than for hybrid HNC (75.6%) and hybrid GIC (69.8%), respectively. These results suggested that HS-GC-FID fingerprinting is suitable and holds great potential for cancer screening. Additionally, the hybrid approach tends to increase the predictive power if the individual models present suitable quality parameter values. Otherwise, it is more advantageous to use a single body fluid for analysis"
Keywords:		"Humans Flame Ionization/methods Breath Tests Chromatography, Gas/methods *Volatile Organic Compounds/analysis Least-Squares Analysis *Neoplasms/diagnosis DoE VOCs head and neck cancer headspace metabolomics optimization oral fluid;"
Notes:		"Medlineda Costa, Bruno Ruiz Brandao da Silva, Ricardo Roberto Bigao, Vitor Luiz Caleffo Piva Peria, Fernanda Maris De Martinis, Bruno Spinosa eng Research Support, Non-U.S. Gov't England 2023/01/13 J Breath Res. 2023 Jan 27; 17(2). doi: 10.1088/1752-7163/acb284"