Considerations regarding the selection, sampling, extraction, analysis, and modelling of biomarkers in exhaled breath for early lung cancer screening

Abstract

Lung cancer (LC) is the deadliest cancer due to the lack of efficient screening methods that detect the disease early. This review, covering the years 2011 – 2025, summarizes state-of-the-art LC screening through analysis of volatile organic compounds (VOCs) in exhaled breath. All fundamental parts of the methodology are covered, i.e., sampling, analysis, and multivariate data modelling. This review shows that breath is commonly collected in Tedlar® bags and subsequently analysed with solid phase micro-extraction gas chromatography mass spectrometry (SPME-GC-MS) or sensors. Data analysis has been made using multivariate methods like principal component analysis (PCA) or artificial neural networks (ANNs). The VOCs exhaled by LC patients and healthy subjects are in principle the same. However, concentration levels differ between the two groups. Therefore, LC patients are usually separated from healthy controls through multivariate modelling of a set of VOC biomarkers rather than by individual biomarkers. Although most exhaled VOCs are formed endogenously via metabolic processes and oxidative stress, some compounds also have exogenous origins, which must be taken into consideration. More than 200 different VOCs have been reported as potential biomarkers in the breath of LC patients, while the number of biomarkers per study were typically around 10–20 compounds. The 15 most common LC biomarkers were (from high to low frequency) acetone, isoprene, hexanal, benzene, butanone, styrene, ethylbenzene, 1-propanol, 2-propanol, toluene, pentanal, 2-pentanone, cyclohexane, nonanal and decane. Several methods showed, in combination with multivariate data analysis, potential to distinguish between LC patients and healthy controls.