The Use of Breath Analysis in the Management of Lung Cancer: Is It Ready for Primetime?

Abstract

Breath analysis is a promising non-invasive method for the detection and management of lung cancer. Exhaled breath contains a complex mixture of volatile and non-volatile organic compounds that are produced as end-products of metabolism. Several studies have explored the patterns of these compounds and have postulated that a unique breath signature is emitted in the setting of lung cancer. Most studies have evaluated the use of gas chromatography and mass spectrometry to identify these unique breath signatures. With recent advances in the field of analytical chemistry and machine learning gaseous chemical sensing and identification devices have also been created to detect patterns of odorant molecules such as volatile organic compounds. These devices offer hope for a point-of-care test in the future. Several prospective studies have also explored the presence of specific genomic aberrations in the exhaled breath of patients with lung cancer as an alternative method for molecular analysis. Despite its potential, the use of breath analysis has largely been limited to translational research due to methodological issues, the lack of standardization or validation and the paucity of large multi-center studies. It is clear however that it offers a potentially non-invasive alternative to investigations such as tumor biopsy and blood sampling.

Physiology and Biomarkers for Surveillance of Occupational Lung Disease

“…For example, eNoses have been used to exclude active tuberculosis in an indigenous population, 82 to detect tuberculosis in badgers, 83 and to assist with lung cancer screening. 84 Many of these techniques are currently being evaluated in clinical trials and in population studies.…”

What's new in thoracic oncology

“…One such technology which is currently being validated in clinical studies is the analysis of exhaled breath samples using electronic nose (e‐nose) technology 32–34 . E‐nose technology uses machine learning algorithms to assay volatile organic compounds in the exhaled breath of patients, and in translational and preclinical studies it has demonstrated diagnostic accuracy in lung cancer patients as high as 86% 33 .…”

“…One such technology which is currently being validated in clinical studies is the analysis of exhaled breath samples using electronic nose (e-nose) technology. [32][33][34] E-nose technology uses machine learning algorithms to assay volatile organic compounds in the exhaled breath of patients, and in translational and preclinical studies it has demonstrated diagnostic accuracy in lung cancer patients as high as 86%. 33 As its development continues, e-nose technology appears poised to streamline the diagnosis of screen-detected lung cancers by offering reliable, realtime readouts of test results and averting the potential complications of invasive diagnostic procedures.…”

Non-invasive detection of orthotopic human lung tumors by microRNA expression profiling of mouse exhaled breath condensates and exhaled extracellular vesicles

“…Although there are known biomarkers for the detection of specific cancers (e.g., AFP+CEA+CA125 for primary breast cancer or PSA for prostate cancer), there are currently no blood-based biomarker assays that can predict the development of secondary lung cancer [23] . Even though direct airway collection strategies [i.e., nasal epithelial brushing, sputum, bronchial brushing, bronchioalveolar lavage (BAL), and exhaled breath condensate (EBC)] are being investigated for the detection of primary lung cancer, they have not been evaluated for the detection of secondary lung cancer [24][25][26][27][28][29][30][31][32] .…”