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Volatilomics is a powerful tool capable of providing novel biomarkers for the diagnosis of gastric cancer. The main objective of this study was to characterize the volatilomic signatures of gastric juice in order to identify potential alterations induced by gastric cancer. Gas chromatography with mass spectrometric detection, coupled with headspace solid phase microextraction as the pre-concentration technique, was used to identify volatile organic compounds (VOCs) released by gastric juice samples collected from 78 gastric cancer patients and two cohorts of controls (80 and 96 subjects) from four different locations (Latvia, Ukraine, Brazil, and Colombia). 1440 distinct compounds were identified in samples obtained from patients and 1422 in samples provided by controls. However, only 6% of the VOCs exhibited an incidence higher than 20%. Amongst the volatiles emitted, 18 showed differences in their headspace concentrations above gastric juice of cancer patients and controls. Ten of these (1-propanol, 2,3-butanedione, 2-pentanone, benzeneacetaldehyde, 3-methylbutanal, butylated hydroxytoluene, 2-pentyl-furan, 2-ethylhexanal, 2-methylpropanal and phenol) appeared at significantly higher levels in the headspace of the gastric juice samples obtained from patients; whereas, eight species showed lower abundance in patients than found in controls. Given that the difference in the volatilomic signatures can be explained by cancer-related changes in the activity of certain enzymes or pathways, the former set can be considered potential biomarkers for gastric cancer, which may assist in developing non-invasive breath tests for the diagnosis of this disease. Further studies are required to elucidate further the mechanisms that underlie the changes in the volatilomic profile as a result of gastric cancer., (© 2024 IOP Publishing Ltd.)

Breath analysis holds great promise for real-time and non-invasive medical diagnosis. Thus, there is a considerable need for simple-in-use and portable analyzers for rapid detection of breath indicators for different diseases in their early stages. Sensor technology meets all of these demands. However, miniaturized breath analyzers require adequate breath sampling methods. In this context, we propose non-contact sampling; namely the collection of breath samples by exhalation from a distance into a miniaturized collector without bringing the mouth into direct contact with the analyzing device. To evaluate this approach different breathing maneuvers have been tested in a real-time regime on a cohort of 23 volunteers using proton transfer reaction mass spectrometry. The breathing maneuvers embraced distinct depths of respiration, exhalation manners, size of the mouth opening and different sampling distances. Two inhalation modes (normal, relaxed breathing and deep breathing) and two exhalation manners (via smaller and wider lips opening) forming four sampling scenarios were selected. A sampling distance of approximately 2 cm was found to be a reasonable trade-off between sample dilution and requirement of no physical contact of the subject with the analyzer. All four scenarios exhibited comparable measurement reproducibility spread of around 10%. For normal, relaxed inspiration both dead-space and end-tidal phases of exhalation lasted approximately 1.5 s for both expiration protocols. Deep inhalation prolongs the end-tidal phase to about 3 s in the case of blowing via a small lips opening, and by 50% when the air is exhaled via a wide one. In conclusion, non-contact breath sampling can be considered as a promising alternative to the existing breath sampling methods, being relatively close to natural spontaneous breathing.

Background: Detection of diseases via exhaled breath remains an attractive idea despite persisting gaps in understanding the origin of volatile organic compounds (VOCs) and their relationship with the disease of interest. Data on factors potentially influencing the results of breath analysis remain rather sparse and often controversial. In this study, we aimed to investigate the associations of common VOCs in exhaled breath of average-risk individuals with socio-demographic and lifestyle factors, medical conditions as well as diet., Methods: Alveolar breath samples of 1447 men and women were collected in the morning after fasting and were analyzed using gas-chromatography linked with mass-spectrometry. Study participants were 40-64 years old, cancer-free, with overall good health status. The associations between selected VOCs and various factors determined from the questionnaire data were assessed using two-part-Wilcoxon test and Jonckheere-Terpstra trend test., Results: Fifteen VOCs where each of them was detected in at least 80% of the study population were included in this analysis. Statistically significant associations with various VOCs were demonstrated for gender and consumption of certain foods, such as coffee, leeks and garlic, while smoking was not associated with any of the analyzed compounds., Conclusion: Factors potentially modifying the composition of exhaled breath, such as dietary factors, deserve careful attention in the design and analysis of studies accessing the use of VOCs as diagnostic markers.

The presence of certain volatile organic compounds (VOCs) in the breath of patients with gastric cancer has been reported by a number of research groups; however, the source of these compounds remains controversial. Comparison of VOCs emitted from gastric cancer tissue to those emitted from non-cancerous tissue would help in understanding which of the VOCs are associated with gastric cancer and provide a deeper knowledge on their generation. Gas chromatography with mass spectrometric detection (GC-MS) coupled with head-space needle trap extraction (HS-NTE) as the pre-concentration technique, was used to identify and quantify VOCs released by gastric cancer and non-cancerous tissue samples collected from 41 patients during surgery. Excluding contaminants, a total of 32 VOCs were liberated by the tissue samples. The emission of four of them (carbon disulfide, pyridine, 3-methyl-2-butanone and 2-pentanone) was significantly higher from cancer tissue, whereas three compounds (isoprene, γ-butyrolactone and dimethyl sulfide) were in greater concentration from the non-cancerous tissues (Wilcoxon signed-rank test, p < 0.05). Furthermore, the levels of three VOCs (2-methyl-1-propene, 2-propenenitrile and pyrrole) were correlated with the occurrence of H. pylori; and four compounds (acetonitrile, pyridine, toluene and 3-methylpyridine) were associated with tobacco smoking. Ex vivo analysis of VOCs emitted by human tissue samples provides a unique opportunity to identify chemical patterns associated with a cancerous state and can be considered as a complementary source of information on volatile biomarkers found in breath, blood or urine.

Discovering the volatile signature of cancer cells is an emerging approach in cancer research, as it may contribute to a fast and simple diagnosis of tumors in vivo and in vitro. One of the main contributors to such a volatile signature is hyperglycolysis, which characterizes the cancerous cell. The metabolic perturbation in cancer cells is known as the Warburg effect; glycolysis is preferred over oxidative phosphorylation (OXPHOS), even in the presence of oxygen. The precise mitochondrial alterations that underlie the increased dependence of cancer cells on aerobic glycolysis for energy generation have remained a mystery. We aimed to profile the volatile signature of the glycolysis activity in lung cancer cells. For that an in vitro model, using lung cancer cell line cultures (A549, H2030, H358, H322), was developed. The volatile signature was measured by proton transfer reaction mass spectrometry under normal conditions and glycolysis inhibition. Glycolysis inhibition and mitochondrial activity were also assessed by mitochondrial respiration capacity measurements. Cells were divided into two groups upon their glycolytic profile (PET positive and PET negative). Glycolysis blockade had a unique characteristic that was shared by all cells. Furthermore, each group had a characteristic volatile signature that enabled us to discriminate between those sub-groups of cells. In conclusion, lung cancer cells may have different subpopulations of cells upon low and high mitochondrial capacity. In both groups, glycolysis blockade induced a unique volatile signature.

Volatile organic compound (VOC) testing in breath has potential in gastric cancer (GC) detection. Our objective was to assess the reproducibility of VOCs in GC, and the effects of conditions modifying gut microbiome on the test results. Ten patients with GC were sampled for VOC over three consecutive days; 17 patients were sampled before and after H. pylori eradication therapy combined with a yeast probiotic; 61 patients were sampled before and after bowel cleansing (interventions affecting the microbiome). The samples were analyzed by: (1) gas chromatography linked to mass spectrometry (GC-MS), applying the non-parametric Wilcoxon test (level of significance p  <  0.05); (2) by cross-reactive nanoarrays combined with pattern recognition. Discriminant function analysis (DFA) was used to build the classification models; and leave-one-out cross-validation analysis was used to classify the findings. Exhaled VOCs profiles were stable for GC patients over a three day period. Alpha pinene (p  =  0.028) and ethyl acetate (p  =  0.030) increased after the antibiotic containing eradication regimen; acetone (p  =  0.0001) increased following bowel cleansing prior to colonoscopy. We further hypothesize that S. boulardii given with the standard eradication regimen to re-establish the gut microbiome was the source for long-term ethyl acetate production. Differences between the initial and the follow-up sample were also revealed in the DFA analysis of the sensor data. VOC measurement results are well-reproducible in GC patients indicating a useful basis for potential disease diagnostics. However, interventions with a potential effect on the gut microbiome may have an effect upon the VOC results, and therefore should be considered for diagnostic accuracy.

Cancer cells prefer hyperglycolysis versus oxidative phosphorylation, even in the presence of oxygen. This phenomenon is used through the FDG-PET scans, and may affect the exhaled volatile signature. This study investigates the volatile signature in lung cancer (LC) before and after an oral glucose tolerance test (OGTT) to determine if tumor cells' hyperglycolysis would affect the volatile signature. Blood glucose levels and exhaled breath samples were analyzed before the OGTT, and 90 min after, in both LC patients and controls. The volatile signature was measured by proton transfer reaction mass spectrometry (PTR-MS). Twenty-two LC patients (age 66.6  ±  12.7) with adenocarcinoma (n  =  14), squamous (n  =  6), small cell carcinoma (n  =  2), and twenty-one controls (age 54.4  ±  13.7; 10 non-smokers and 11 smokers) were included. All LC patients showed a hyperglycolytic state in their FDG-PET scans. Both baseline and post OGTT volatile signatures discriminate between the groups. The OGTT has a minimal effect in LC (a decrease in m/z 54 by 39%, p v  =  0.0499); whereas in the control group, five masses (m/z 64, 87,88, 142 and 161) changed by  -13%, -49%, -40% and  -29% and 46% respectively. To conclude, OGTT has a minimal effect on the VOC signature in LC patients, where a hyperglycolytic state already exists. In contrast, in the control group the OGTT has a profound effect in which induced hyperglycolysis significantly changed the VOC pattern. We hypothesized that a ceiling effect in cancerous patients is responsible for this discrepancy.

Profiling the body chemistry by means of volatile organic compounds (VOCs) in the breath opens exciting new avenues in medical diagnostics. Gas sensors could provide ideal platforms for realizing portable, hand-held breath testing devices in the near future. This review summarizes the latest developments and applications in the field of chemical sensors for diagnostic breath testing that were presented at the Breath Analysis Summit 2013 in Wallerfangen, Germany. Considerable progress has been made towards clinically applicable breath testing devices, especially by utilizing chemo-sensitive nanomaterials. Examples of several specialized breath testing applications are presented that are either based on stand-alone nanomaterial-based sensors being highly sensitive and specific to individual breath compounds over others, or on combinations of several highly specific sensors, or on experimental nanomaterial-based sensors arrays. Other interesting approaches include the adaption of a commercially available MOx-based sensor array to indirect breath testing applications, using a sample pre-concentration method, and the development of compact integrated GC-sensor systems. The recent trend towards device integration has led to the development of fully integrated prototypes of point-of-care devices. We describe and compare the performance of several prototypes that are based on different sensing technologies and evaluate their potential as low-cost and readily available next-generation medical devices.

The current review provides an assessment of the exhalation kinetics of volatile organic compounds (VOCs) that have been linked with cancer. Towards this end, we evaluate various physicochemical properties, such as 'breath:air' and 'blood:fat' partition coefficients, of 112 VOCs that have been suggested over the past decade as potential markers of cancer. With these data, we show that the cancer VOC concentrations in the blood and in the fat span over 12 and 8 orders of magnitude, respectively, in order to provide a specific counterpart concentration in the exhaled breath (e.g., 1 ppb). This finding suggests that these 112 different compounds have different storage compartments in the body and that their exhalation kinetics depends on one or a combination of the following factors: (i) the VOC concentrations in different parts of the body; (ii) the VOC synthesis and metabolism rates; (iii) the partition coefficients between tissue(s), blood and air; and (iv) the VOCs' diffusion constants. Based on this analysis, we discuss how this knowledge allows modeling and simulating the behavior of a specific VOC under different sampling protocols (with and without exertion of effort). We end this review by a brief discussion on the potential role of these scenarios in screening and therapeutic monitoring of cancer.

Breath-gas analysis has demonstrated that concentration profiles of volatile organic compounds (VOCs) could be used for detecting a variety of diseases, among them gastric cancer (GC) and peptic ulcer disease (PUD). Here, we explore how geographical variation affects the disease-specific changes in the chemical composition of breath samples, as compared to control states (less severe gastric conditions). Alveolar exhaled breath samples from 260 patients were collected at two remotely different geographic locations (China and Latvia), following similar breath-collection protocols. Each cohort included 130 patients that were matched in terms of diagnosis (37 GC/32 PUD/61 controls), average age, gender ratio and smoking habits. Helicobacter Pylori infection, which is a major cause for GC and PUD, was found in part of the patients, as well as in part of the controls, at both locations. The breath samples were analyzed by gas chromatography/mass spectrometry, using the same equipment and protocol-of-experiment. We observed similar characteristic differences in the chemical composition of the breath samples between the study groups at the two locations, even though the exact composition of the breath samples differed. Both in China and Latvia, the GC patients and controls could be distinguished by differences in the average levels of 6-methyl-5-hepten-2-one; PUD patients were distinguished from controls by the levels of aromatic compounds and alcohols; GC and PUD patients could not be distinguished at either site. This pilot study indicates the limitations of chemical breath-gas analysis alone for identifying gastric diseases based on the concentration profiles of separate VOCs in international patient cohorts. We assume that these limitations would apply to other diseases as well. The presented data could potentially be useful for developing an alternative, universally applicable diagnostic method that relies on the detection of changes in the collective patterns of the disease-specific classes of exhaled VOCs.