Smell, Lung Cancer, Electronic Nose and Trained Dogs

Abstract

Lung cancer (LC) represents a problem of high magnitude for the medical systems due to its morbidity and mortality, also because of the huge human and economical efforts and costs that it catalyzes. Only in Europe, the average life-time cost of lung cancer patients ranges between €46,000 and €61,000 per patient. Secondary prevention, which consists in mass-screening of the high-risk population, could result of high benefit. For this aim to become a reality in the future, a potentially inexpensive and non-invasive approach for LC (pre)diagnosing is emerging. Such possibility relies on the detection of volatile biomarkers emitted from cell membranes. Tumor growth is accompanied by gene changes that may lead to oxidative stress, and the per oxidation of the cell membrane species causes volatile biomarkers to be emitted. Some of these biomarkers appear in distinctively different mixture compositions, depending on whether a cell is healthy or cancerous. These volatile biomarkers can be detected, among others, through the analysis of the exhaled breath, because the cancer-related changes in the blood chemistry are reflected in measurable changes to the breath through exchange via the lung. Importantly, these volatiles or their metabolic products are transmitted to the alveolar exhaled breath through exchange via the lung even at the very onset of the disease. There are several methods that can be applied to analyses the exhaled breath for the identification of a specific pattern of volatile biomarkers related with the target medical condition. The feasibility of three strategies, and the possible synergic effect of their concomitant application as a powerful pre-estimation tool for mass-screening of LC high-risk population: i. Spectrographic techniques such as Gas-Chromatography coupled to Mass-Spectrometry (GC-MS), which relies on reference libraries of analyses mass spectra to structurally identify and track the analyses in gaseous samples. ii. Electronic-nose (e-nose), which consists in a matrix of chemical gas sensors specifically trained for the target application by means of a pattern recognition algorithm.