Breathomics: may it become an affordable, new tool for early diagnosis of non-small-cell lung cancer? An exploratory study on a cohort of 60 patients

Author:

Brascia Debora12ORCID,De Iaco Giulia3,Panza Teodora3,Signore Francesca3,Carleo Graziana3,Zang Wenzhe4,Sharma Ruchi4,Riahi Pamela4,Scott Jared4,Fan Xudong4,Marulli Giuseppe12

Affiliation:

1. Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy

2. Division of Thoracic Surgery, IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy

3. Thoracic Surgery Unit, Department of Precision and Regenerative Medicine and Jonic Area, University Hospital of Bari, Bari, Italy

4. Department of Biomedical Engineering, University of Michigan , Ann Arbor, MI, USA

Abstract

Abstract OBJECTIVES Analysis of breath, specifically the patterns of volatile organic compounds (VOCs), has shown the potential to distinguish between patients with lung cancer (LC) and healthy individuals (HC). However, the current technology relies on complex, expensive and low throughput analytical platforms, which provide an offline response, making it unsuitable for mass screening. A new portable device has been developed to enable fast and on-site LC diagnosis, and its reliability is being tested. METHODS Breath samples were collected from patients with histologically proven non-small-cell lung cancer (NSCLC) and healthy controls using Tedlar bags and a Nafion filter attached to a one-way mouthpiece. These samples were then analysed using an automated micro portable gas chromatography device that was developed in-house. The device consisted of a thermal desorption tube, thermal injector, separation column, photoionization detector, as well as other accessories such as pumps, valves and a helium cartridge. The resulting chromatograms were analysed using both chemometrics and machine learning techniques. RESULTS Thirty NSCLC patients and 30 HC entered the study. After a training set (20 NSCLC and 20 HC) and a testing set (10 NSCLC and 10 HC), an overall specificity of 83.3%, a sensitivity of 86.7% and an accuracy of 85.0% to identify NSCLC patients were found based on 3 VOCs. CONCLUSIONS These results are a significant step towards creating a low-cost, user-friendly and accessible tool for rapid on-site LC screening. CLINICAL REGISTRATION NUMBER ClinicalTrials.gov Identifier: NCT06034730.

Publisher

Oxford University Press (OUP)

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