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Discriminant Profiles of Volatile Compounds in the Alveolar Air of Patients with Squamous Cell Lung Cancer, Lung Adenocarcinoma or Colon Cancer

Authors :
Leonardo Politi
Lorenzo Monasta
Maria Novella Rigressi
Andrea Princivalle
Alessandro Gonfiotti
Gianna Camiciottoli
Luigi Perbellini
Source :
Molecules, Vol 26, Iss 3, p 550 (2021)
Publication Year :
2021
Publisher :
MDPI AG, 2021.

Abstract

The objective of the present work was to analyze volatile compounds in alveolar air in patients with squamous cell lung cancer, lung adenocarcinoma or colon cancer, to prepare algorithms able to discriminate such specific pathological conditions. The concentration of 95 volatile compounds was measured in the alveolar air of 45 control subjects, 36 patients with lung adenocarcinoma, 25 patients with squamous cell lung cancer and 52 patients with colon cancer. Volatile compounds were measured with ion molecule reaction mass spectrometry (IMR-MS). An iterated least absolute shrinkage and selection operator multivariate logistic regression model was used to generate specific algorithms and discriminate control subjects from patients with different kinds of cancer. The final predictive models reached the following performance: by using 11 compounds, patients with lung adenocarcinoma were identified with a sensitivity of 86% and specificity of 84%; nine compounds allowed us to identify patients with lung squamous cell carcinoma with a sensitivity of 88% and specificity of 84%; patients with colon adenocarcinoma could be identified with a sensitivity of 96% and a specificity of 73% using a model comprising 13 volatile compounds. The different alveolar profiles of volatile compounds, obtained from patients with three different kinds of cancer, suggest dissimilar biological–biochemistry conditions; each kind of cancer has probably got a specific alveolar profile.

Details

Language :
English
ISSN :
14203049
Volume :
26
Issue :
3
Database :
Directory of Open Access Journals
Journal :
Molecules
Publication Type :
Academic Journal
Accession number :
edsdoj.226c9bda6a3c4473aeba77731bf84053
Document Type :
article
Full Text :
https://doi.org/10.3390/molecules26030550