Breast cancer detection using volatile compound profiles in exhaled breath via selected ion-flow tube mass spectrometry

Abstract

This study aimed to evaluate volatile compounds in exhaled breath as a non-invasive screening method to detect breast neoplasms. Exhaled breath samples were collected from patients with breast cancer (BC; n = 45) and non-breast cancer (NBC; n = 51) controls. Selected ion-flow tube mass spectrometry was used to quantify the volatile compounds. A multiple logistic regression (MLR) model was developed by combining multiple compounds to discriminate between BC and NBC samples. Amongst the 672 quantified peaks, 17 showed significant differences between BC and NBC samples (P < 0.05 corrected by false discovery rate). Pathway analysis revealed a significant difference in glycerophospholipid metabolism. The MLR model showed an area under the receiver operating characteristic curve (AUC) of 0.719 (95% confidence interval: 0.615-0.822, P < 0.0002). Cross-validation under various conditions resulted in a slight fluctuation in the AUC values, indicating the high generalizability of the MLR model. The model showed a higher BC probability for advanced-stage subjects and higher Ki67 (⩾30) for BC subjects. This study suggests the potential of volatile compounds in exhaled breath as a noninvasive screening method for BC.