Polydiacetylene/copolymer sensors to detect lung cancer breath volatile organic compounds

Abstract

Early lung cancer detection is imperative to increase the 5-year survival rate and reduce cancer mortality. Existing diagnosis techniques involve costly, time-consuming, and often invasive tests. The emergence of volatile organic compounds (VOCs) as a disease biomarker offers a non-invasive avenue for early detection of lung cancer through breath analysis. Recently, polydiacetylene (PDA)-based colorimetric sensors have shown the potential to detect VOCs. In this work, we developed PDA/copolymer paper sensors to detect 5 potential early lung cancer VOC biomarkers, including ethylbenzene, 2-butanone, hexanal, 2-ethylhexanol, and undecane. Polymethyl methacrylate (PMMA), polyvinylpyrrolidone (PVP), polystyrene (PST), and polyethylene glycol (PEG) were selected as copolymers based on their chemical affinity and solvating properties. Different copolymer molecular weights and PDA/copolymer mixing ratios were investigated and their responses to standard breath temperature and relative humidity (35 °C, 60% RH and 90% RH) were evaluated. We then developed an array containing 11 PDA/copolymers and exposed them to gaseous VOC biomarkers and common breath interferents (ethanol, acetone, and isoprene) in a custom-built reactor. The colorimetric data were simultaneously analyzed using principal component analysis and results showed highly discriminating properties. We demonstrated the detection of 2-butanone (LOD = 267 ppmv), ethylbenzene (LOD = 457 ppmv), and ethanol (LOD = 269 ppmv) within 15 min. This study aims to establish a cost-effective, user-friendly, and non-invasive methodology for early detection of lung cancer.