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 com-pounds was measured in the alveolar air of 45 control subjects, 36 patients with lung adenocarci-noma, 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 iterat-ed least absolute shrinkage and selection operator multivariate logistic regression model was used to generate specific algorithms and discriminate control subjects from patients with differ-ent 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 car-cinoma 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 pa-tients with three different kinds of cancer, suggest dissimilar biological-biochemistry condi-tions; each kind of cancer has probably got a specific alveolar profile.

Discriminant Profiles of Volatile Compounds in the Alveolar Air of Patients with Squamous Cell Lung Cancer, Lung Adenocarcinoma or Colon Cancer / Politi, Leonardo; Monasta, Lorenzo; Rigressi, Maria Novella; Princivalle, Andrea; Gonfiotti, Alessandro; Camiciottoli, Gianna; Perbellini, Luigi. - In: MOLECULES. - ISSN 1420-3049. - ELETTRONICO. - 26:(2021), pp. 0-0. [10.3390/molecules26030550]

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

Politi, Leonardo;Gonfiotti, Alessandro;Camiciottoli, Gianna;
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 com-pounds was measured in the alveolar air of 45 control subjects, 36 patients with lung adenocarci-noma, 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 iterat-ed least absolute shrinkage and selection operator multivariate logistic regression model was used to generate specific algorithms and discriminate control subjects from patients with differ-ent 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 car-cinoma 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 pa-tients with three different kinds of cancer, suggest dissimilar biological-biochemistry condi-tions; each kind of cancer has probably got a specific alveolar profile.
26
0
0
Politi, Leonardo; Monasta, Lorenzo; Rigressi, Maria Novella; Princivalle, Andrea; Gonfiotti, Alessandro; Camiciottoli, Gianna; Perbellini, Luigi
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2158/1286754
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 6
  • ???jsp.display-item.citation.isi??? ND
social impact