A new non-invasive and potentially inexpensive frontier in the diagnosis of cancer relies on the detection of volatile organic compounds (VOCs) in exhaled breath samples. Breath can be sampled and analyzed in real-time, leading to fascinating and cost-effective clinical diagnostic procedures. Nevertheless, breath analysis is a very young field of research and faces challenges, mainly because the biochemical mechanisms behind the cancer-related VOCs are largely unknown. In this review, we present a list of 115 validated cancer-related VOCs published in the literature during the past decade, and classify them with respect to their “fat-to-blood” and “blood-to-air” partition coefficients. These partition coefficients provide an estimation of the relative concentrations of VOCs in alveolar breath, in blood and in the fat compartments of the human body. Additionally, we try to clarify controversial issues concerning possible experimental malpractice in the field, and propose ways to translate the basic science results as well as the mechanistic understanding to tools (sensors) that could serve as point-of-care diagnostics of cancer. We end this review with a conclusion and a future perspective.

Background: Lung cancer is one of the leading causes of death in Europe and the western world. At present, diagnosis of lung cancer very often happens late in the course of the disease since inexpensive, non-invasive and sufficiently sensitive and specific screening methods are not available. Even though the CT diagnostic methods are good, it must be assured that "screening benefit outweighs risk, across all individuals screened, not only those with lung cancer". An early non-invasive diagnosis of lung cancer would improve prognosis and enlarge treatment options. Analysis of exhaled breath would be an ideal diagnostic method, since it is non-invasive and totally painless. Methods: Exhaled breath and inhaled room air samples were analyzed using proton transfer reaction mass spectrometry (PTR-MS) and solid phase microextraction with subsequent gas chromatography mass spectrometry (SPME-GCMS). For the PTR-MS measurements, 220 lung cancer patients and 441 healthy volunteers were recruited. For the GCMS measurements, we collected samples from 65 lung cancer patients and 31 healthy volunteers. Lung cancer patients were in different disease stages and under treatment with different regimes. Mixed expiratory and indoor air samples were collected in Tedlar bags, and either analyzed directly by PTR-MS or transferred to glass vials and analyzed by gas chromatography mass spectrometry (GCMS). Only those measurements of compounds were considered, which showed at least a 15% higher concentration in exhaled breath than in indoor air. Compounds related to smoking behavior such as acetonitrile and benzene were not used to differentiate between lung cancer patients and healthy volunteers. Results: Isoprene, acetone and methanol are compounds appearing in everybody's exhaled breath. These three main compounds of exhaled breath show slightly lower concentrations in lung cancer patients as compared to healthy volunteers (p < 0.01 for isoprene and acetone, p = 0.011 for methanol; PTR-MS measurements). A comparison of the GCMS-results of 65 lung cancer patients with those of 31 healthy volunteers revealed differences in concentration for more than 50 compounds. Sensitivity for detection of lung cancer patients based on presence of (one of) 4 different compounds not arising in exhaled breath of healthy volunteers was 52% with a specificity of 100%. Using 15 (or 21) different compounds for distinction, sensitivity was 71% (80%) with a specificity of 100%. Potential marker compounds are alcohols, aldehydes, ketones and hydrocarbons. Conclusion: GCMS-SPME is a relatively insensitive method. Hence compounds not appearing in exhaled breath of healthy volunteers may be below the limit of detection (LOD). PTR-MS, on the other hand, does not need preconcentration and gives much more reliable quantitative results then GCMS-SPME. The shortcoming of PTR-MS is that it cannot identify compounds with certainty. Hence SPME-GCMS and PTR-MS complement each other, each method having its particular advantages and disadvantages. Exhaled breath analysis is promising to become a future non-invasive lung cancer screening method. In order to proceed towards this goal, precise identification of compounds observed in exhaled breath of lung cancer patients is necessary. Comparison with compounds released from lung cancer cell cultures, and additional information on exhaled breath composition in other cancer forms will be important.

A real-time recording setup combining exhaled breath volatile organic compound (VOC) measurements by proton transfer reaction-mass spectrometry (PTR-MS) with hemodynamic and respiratory data is presented. Continuous automatic sampling of exhaled breath is implemented on the basis of measured respiratory flow: a flow-controlled shutter mechanism guarantees that only end-tidal exhalation segments are drawn into the mass spectrometer for analysis. Exhaled breath concentration profiles of two prototypic compounds, isoprene and acetone, during several exercise regimes were acquired, reaffirming and complementing earlier experimental findings regarding the dynamic response of these compounds reported by Senthilmohan et al (2000 Redox Rep. 5 151–3) and Karl et al (2001 J. Appl. Physiol. 91 762–70). While isoprene tends to react very sensitively to changes in pulmonary ventilation and perfusion due to its lipophilic behavior and low Henry constant, hydrophilic acetone shows a rather stable behavior. Characteristic (median) values for breath isoprene concentration and molar flow, i.e., the amount of isoprene exhaled per minute are 100 ppb and 29 nmol min−1, respectively, with some intra-individual day-to-day variation. At the onset of exercise breath isoprene concentration increases drastically, usually by a factor of ~3–4 within about 1 min. Due to a simultaneous increase in ventilation, the associated rise in molar flow is even more pronounced, leading to a ratio between peak molar flow and molar flow at rest of ~11. Our setup holds great potential in capturing continuous dynamics of non-polar, low-soluble VOCs over a wide measurement range with simultaneous appraisal of decisive physiological factors affecting exhalation kinetics. In particular, data appear to favor the hypothesis that short-term effects visible in breath isoprene levels are mainly caused by changes in pulmonary gas exchange patterns rather than fluctuations in endogenous synthesis.

Background: The routinely used microbiological diagnosis of ventilator associated pneumonia (VAP) is time consuming and often requires invasive methods for collection of human specimens (e.g. bronchoscopy). Therefore, it is of utmost interest to develop a non-invasive method for the early detection of bacterial infection in ventilated patients, preferably allowing the identification of the specific pathogens. The present work is an attempt to identify pathogen-derived volatile biomarkers in breath that can be used for early and non- invasive diagnosis of ventilator associated pneumonia (VAP). For this purpose, in vitro experiments with bacteria most frequently found in VAP patients, i.e. Staphylococcus aureus and Pseudomonas aeruginosa, were performed to investigate the release or consumption of volatile organic compounds (VOCs). Results: Headspace samples were collected and preconcentrated on multibed sorption tubes at different time points and subsequently analyzed with gas chromatography mass spectrometry (GC-MS). As many as 32 and 37 volatile metabolites were released by S. aureus and P. aeruginosa, respectively. Distinct differences in the bacteria-specific VOC profiles were found, especially with regard to aldehydes (e.g. acetaldehyde, 3-methylbutanal), which were taken up only by P. aeruginosa but released by S. aureus. Differences in concentration profiles were also found for acids (e.g. isovaleric acid), ketones (e.g. acetoin, 2-nonanone), hydrocarbons (e.g. 2-butene, 1,10-undecadiene), alcohols (e.g. 2-methyl-1-propanol, 2-butanol), esters (e.g. ethyl formate, methyl 2-methylbutyrate), volatile sulfur compounds (VSCs, e.g. dimethylsulfide) and volatile nitrogen compounds (VNCs, e.g. 3-methylpyrrole). Importantly, a significant VOC release was found already 1.5 hours after culture start, corresponding to cell numbers of ~8*10⁶ [CFUs/ml]. Conclusions: The results obtained provide strong evidence that the detection and perhaps even identification of bacteria could be achieved by determination of characteristic volatile metabolites, supporting the clinical use of breath-gas analysis as non-invasive method for early detection of bacterial lung infections.

Analysis of exhaled breath is a promising diagnostic method. Sampling of exhaled breath is non-invasive and can be performed as often as considered desirable. There are indications that the concentration and presence of certain of volatile compounds in exhaled breath of lung cancer patients is different from concentrations in healthy volunteers. This might lead to a future diagnostic test for lung cancer. Exhaled breath samples from 65 patients with different stages of lung cancer and undergoing different treatment regimes were analysed. Mixed expiratory and indoor air samples were collected. Solid phase microextraction (SPME) with carboxen/polydimethylsiloxane (CAR/PDMS) sorbent was applied. Compounds were analysed by means of gas chromatography (GC) and mass spectrometry (MS). The method we used allowed identification with the spectral library of 103 compounds showing at least 15% higher concentration in exhaled breath than in inhaled air. Among those 103 compounds, 84 were confirmed by determination of the retention time using standards based on the respective pure compound. Approximately, one third of the compounds detected were hydrocarbons. We found aromatic hydrocarbons, alcohols, aldehydes, ketones, esters, ethers, sulfur compounds, nitrogen-containing compounds and halogenated compounds. Acetonitrile and benzene were two of 10 compounds which correlated with smoking behaviour. A comparison of results from cancer patients with those of 31 healthy volunteers revealed differences in the concentration and presence of certain compounds. The sensitivity for detection of lung cancer patients based on eight different compounds not seen in exhaled breath of healthy volunteers was 51% and the specificity was 100%. These eight potential markers for detection of lung cancer are 1-propanol, 2-butanone, 3-butyn-2-ol, benzaldehyde, 2-methyl-pentane, 3-methyl-pentane, n-pentane and n-hexane. SPME is a relatively insensitive method and compounds not observed in exhaled breath may be present at a concentration lower than LOD. The main achievement of the present work is the validated identification of compounds observed in exhaled breath of lung cancer patients. This identification is indispensible for future work on the biochemical sources of these compounds and their metabolic pathways.

Breath analysis is a young field of research with great clinical potential. As a result of this interest, researchers have developed new analytical techniques that permit real-time analysis of exhaled breath with breath-to-breath resolution in addition to the conventional central laboratory methods using gas chromatography–mass spectrometry. Breath tests are based on endogenously produced volatiles, metabolites of ingested precursors, metabolites produced by bacteria in the gut or the airways, or volatiles appearing after environmental exposure. The composition of exhaled breath may contain valuable information for patients presenting with asthma, renal and liver diseases, lung cancer, chronic obstructive pulmonary disease, inflammatory lung disease, or metabolic disorders. In addition, oxidative stress status may be monitored via volatile products of lipid peroxidation. Measurement of enzyme activity provides phenotypic information important in personalized medicine, whereas breath measurements provide insight into perturbations of the human exposome and can be interpreted as preclinical signals of adverse outcome pathways.