Volatile Organic Compounds Patterns Research Articles

Volatile Emissions from Mycobacterium avium subsp. paratuberculosis Mirror Bacterial Growth and Enable Distinction of Different Strains

Control of paratuberculosis in livestock is hampered by the low sensitivity of established direct and indirect diagnostic methods. Like other bacteria, Mycobacterium avium subsp. paratuberculosis (MAP) emits volatile organic compounds (VOCs). Differences of VOC patterns in breath and feces of infected and not infected animals were described in first pilot experiments but detailed information on potential marker substances is missing. This study was intended to look for characteristic volatile substances in the headspace of cultures of different MAP strains and to find out how the emission of VOCs was affected by density of bacterial growth. One laboratory adapted and four field strains, three of MAP C-type and one MAP S-type were cultivated on Herrold’s egg yolk medium in dilutions of 10-0, 10-2, 10-4 and 10-6. Volatile substances were pre-concentrated from the headspace over the MAP cultures by means of Solid Phase Micro Extraction (SPME), thermally desorbed from the SPME fibers and separated and identified by means of GC-MS. Out of the large number of compounds found in the headspace over MAP cultures, 34 volatile marker substances could be identified as potential biomarkers for growth and metabolic activity. All five MAP strains could clearly be distinguished from blank culture media by means of emission patterns based on these 34 substances. In addition, patterns of volatiles emitted by the reference strain were significantly different from the field strains. Headspace concentrations of 2-ethylfuran, 2-methylfuran, 3-methylfuran, 2-pentylfuran, ethyl acetate, 1-methyl-1-H-pyrrole and dimethyldisulfide varied with density of bacterial growth. Analysis of VOCs emitted from mycobacterial cultures can be used to identify bacterial growth and, in addition, to differentiate between different bacterial strains. VOC emission patterns may be used to approximate bacterial growth density. In a perspective volatile marker substances could be used to diagnose MAP infections in animals and to identify different bacterial strains and origins.

Exhaust emissions of volatile organic compounds of powered two-wheelers: Effect of cold start and vehicle speed. Contribution to greenhouse effect and tropospheric ozone formation

Powered two-wheeler (PTW) vehicles complying with recent European type approval standards (stages Euro 2 and Euro 3) were tested on chassis dynamometer in order to measure exhaust emissions of about 25 volatile organic compounds (VOCs) in the range C1–C7, including carcinogenic compounds as benzene and 1,3-butadiene. The fleet consists of a moped (engine capacity≤50cm3) and three fuel injection motorcycles of different engine capacities (150, 300 and 400cm3). Different driving conditions were tested (US FPT cycle, constant speed). Due to the poor control of the combustion and catalyst efficiency, moped is the highest pollutant emitter. In fact, fuel injection strategy and three way catalyst with lambda sensor are able to reduce VOC motorcycles' emission of about one order of magnitude with respect to moped. Cold start effect, that is crucial for the assessment of actual emission of PTWs in urban areas, was significant: 30–51% of extra emission for methane. In the investigated speed range, moped showed a significant maximum of VOC emission factor at minimum speed (10km/h) and a slightly decreasing trend from 20 to 60km/h; motorcycles showed on the average a less significant peak at 10km/h, a minimum at 30–40km/h and then an increasing trend with a maximum emission factor at 90km/h. Carcinogenic VOCs show the same pattern of total VOCs. Ozone Formation Potential (OFP) was estimated by using Maximum Incremental Reactivity scale. The greatest contribution to tropospheric ozone formation comes from alkenes group which account for 50–80% to the total OFP. VOC contribution effect on greenhouse effect is negligible with respect to CO2 emitted.

Herbivory by the insect diaphorina citri induces greater change in citrus plant volatile profile than does infection by the bacterium, Candidatus Liberibacter asiaticus

The volatile organic compound (VOC) profile in plant leaves often changes after biotic and abiotic stresses. Monitoring changes in VOCs in plant leaves could provide valuable information about multitrophic interactions. In the current study, we investigated the effect of Asian citrus psyllid (ACP) infestation, citrus greening pathogen (Candidatus Liberibacter asiaticus [CLas]) infection, and simultaneous attack by ACP and CLas on the VOC content of citrus leaves. Leaf volatiles were extracted using hexane and analyzed with gas chromatography-mass spectrometry (GC-MS). Although ACP is a phloem-sucking insect that causes minimal damage to plant tissues, the relative amount of 21 out of the 27 VOCs increased 2- to 10-fold in ACP-infested plants. The relative amount of d-limonene, β-phelandrene, citronellal, and undecanal were increased 4- to 20- fold in CLas-infected plants. A principle component analysis (PCA) and cluster analysis (CA) showed that VOC patterns of ACP-infested and CLas-infected plants were different from each other and were also different from the controls, while the VOC pattern of double-attacked plants was more like that of the controls than that of ACP-infested or CLas-infected plants. VOC amounts from leaves were compromised when plants were attacked by ACP and CLas. The results of this study showed that a simple direct extraction of citrus leaf volatiles could be successfully used to discriminate between healthy and CLas-infected plants. Information about the effects of insect and pathogen attack on the VOC content profile of plants might contribute to a better understanding of biotic stress.

Electronic nose can discriminate colorectal carcinoma and advanced adenomas by fecal volatile biomarker analysis: proof of principle study

In the course and prognosis of colorectal cancer (CRC), early detection and treatment are essential factors. Fecal immunochemical tests (FITs) are currently the most commonly used non-invasive screening tests for CRC and premalignant (advanced) adenomas, however, with restricted sensitivity. We hypothesized that fecal volatile organic compounds (VOCs) may serve as a diagnostic biomarker of CRC and adenomas. In this proof of concept study, we aimed to assess disease-specific VOC smellprints in fecal gas to distinguish patients with CRC and advanced adenomas from healthy controls. Fecal samples of patients who were scheduled to undergo an elective colonoscopy were collected. An electronic nose (Cyranose 320) was used to measure VOC patterns in fecal gas from patients with histopathologically proven CRC, with advanced adenomas and from controls (no abnormalities seen at colonoscopy). Receiver operator characteristic curves and corresponding sensitivity and specificity for detection of CRC and advanced adenomas were calculated. A total of 157 stool samples (40 patients with CRC, 60 patients with advanced adenomas, and 57 healthy controls) were analyzed by electronic nose. Fecal VOC profiles of patients with CRC differed significantly from controls (area under curve ± 95%CI, p-value, sensitivity, specificity; 0.92 ± 0.03, <0.001, 85%, 87%). Also VOC profiles of patients with advanced adenomas could be discriminated from controls (0.79 ± 0.04, <0.001, 62%, 86%). The results of this proof of concept study suggest that fecal gas analysis by an electronic nose seems to hold promise as a novel screening tool for the (early) detection of advanced neoplasia and CRC.

PTH-018 Towards Novel Non Invasive Methods to Diagnose Colorectal Cancer Using an Electronic Noses (E-Nose) And Field Asymmetric Ion Mobility Spectrometry (Faims)

IntroductionUsing an electronic nose (E-nose) we have previously demonstrated its ability to detect inflammatory bowel disease (IBD) by shifts in the patterns of volatile organic compounds (VOCs) in the gases...

PTH-187 A Novel Non-Invasive Approach to Diagnose Bile Acid Diarrhoea (Bad) using an Electronic Nose (E-Nose) and Field Asymmetric Ion Mobility Spectroscopy (Faims)

IntroductionA third of diarrhoea predominant irritable bowel syndrome (D-IBS) results from bile acid malabsorption (BAM); diagnosed by 75SeHCAT retention test. We have previously demonstrated the ability of using an E-nose...

Detection and validation of volatile metabolic patterns over different strains of two human pathogenic bacteria during their growth in a complex medium using multi-capillary column-ion mobility spectrometry (MCC-IMS)

Headspace analyses over microbial cultures using multi-capillary column-ion mobility spectrometry (MCC-IMS) could lead to a faster, safe and cost-effective method for the identification of pathogens. Recent studies have shown that MCC-IMS allows identification of bacteria and fungi, but no information is available from when on during their growth a differentiation between bacteria is possible. Therefore, we analysed the headspace over human pathogenic reference strains of Escherichia coli and Pseudomonas aeruginosa at four time points during their growth in a complex fluid medium. In order to validate our findings and to answer the question if the results of one bacterial strain can be transferred to other strains of the same species, we also analysed the headspace over cultures from isolates of random clinical origin. We detected 19 different volatile organic compounds (VOCs) that appeared or changed their signal intensity during bacterial growth. These included six VOCs exclusively changing over E. coli cultures and seven exclusively changing over P. aeruginosa cultures. Most changes occurred in the late logarithmic or static growth phases. We did not find differences in timing or trends in signal intensity between VOC patterns of different strains of one species. Our results show that differentiation of human pathogenic bacteria by headspace analyses using MCC-IMS technology is best possible during the late phases of bacterial growth. Our findings also show that VOC patterns of a bacterial strain can be transferred to other strains of the same species.

Volatile fingerprints of cancer specific genetic mutations

We report on a new concept for profiling genetic mutations of (lung) cancer cells, based on the detection of patterns of volatile organic compounds (VOCs) emitted from cell membranes, using an array of nanomaterial-based sensors. In this in-vitro pilot study we have derived a volatile fingerprint assay for representative genetic mutations in cancer cells that are known to be associated with targeted cancer therapy. Five VOCs were associated with the studied oncogenes, using complementary chemical analysis, and were discussed in terms of possible metabolic pathways. The reported approach could lead to the development of novel methods for guiding treatments, so that patients could benefit from safer, more timely and effective interventions that improve survival and quality of life while avoiding unnecessary invasive procedures. Studying clinical samples (tissue/blood/breath) will be required as next step in order to determine whether this cell-line study can be translated into a clinically useful tool. From the Clinical EditorIn this novel study, a new concept for profiling genetic mutations of (lung) cancer cells is described, based on the detection of patterns of volatile organic compounds emitted from cell membranes, using an array of nano-gold based sensors.

Overcoming an Environmental Surprise with Innovative, Fast-Track Technology

As the Tennessee Department of Transportation (DOT) was finalizing the future route of I-69 through northwest Tennessee, a previously unknown, unregulated landfill was discovered directly beneath the proposed route near its juncture with a continuing segment into Kentucky. The Tennessee DOT, cooperating with the Tennessee Department of Environment and Conservation, implemented a rapid-response, technology-driven strategy to assess the potential costs and liabilities of crossing the landfill versus avoiding it. After a concerted site-history investigation, an electromagnetic geophysical survey mapped the land-fill boundaries, established the area of fill, and identified areas of higher metal content within the fill. A concurrent soil–gas survey showed only isolated patterns of volatile organic compounds, often a driver for environmental mitigation costs. These results were used to optimize locations for subsurface drilling that employed the waste-minimizing sonic drilling technique. Depth of fill from exploratory drilling was combined with the geophysical delineation of landfill boundaries to yield an estimated waste volume of 65,000 m3 (85,000 yd3) within the proposed I-69 footprint. Chemical analyses were done for subsurface sonic rig soil cores, surface soil samples, the contents of drums scattered across the surface, and surface water. These analyses showed relatively modest environmental risk; it was suggested that if the landfill were excavated, most of the soil could be handled as nontoxic special waste. Nevertheless, considering both design–build factors and environmental issues, the cost of excavating and building through the landfill ($33.5 million) exceeded that of rerouting slightly east of the landfill ($29.5 million), and the route was diverted to avoid the landfill.

Hydrothermally carbonized plant materials: Patterns of volatile organic compounds detected by gas chromatography

The nature and concentrations of volatile organic compounds (VOCs) in chars generated by hydrothermal carbonization (HTC) is of concern considering their application as soil amendment. Therefore, the presence of VOCs in solid HTC products obtained from wheat straw, biogas digestate and four woody materials was investigated using headspace gas chromatography. A variety of potentially harmful benzenic, phenolic and furanic volatiles along with various aldehydes and ketones were identified in feedstock- and temperature-specific patterns. The total amount of VOCs observed after equilibration between headspace and char samples produced at 270°C ranged between 2000 and 16,000μg/g (0.2–1.6wt.%). Depending on feedstock 50–9000μg/g of benzenes and 300–1800μg/g of phenols were observed. Substances potentially harmful to soil ecology such as benzofurans (200–800μg/g) and p-cymene (up to 6000μg/g in pine wood char) exhibited concentrations that suggest restrained application of fresh hydrochar as soil amendment or for water purification.

Exhaled volatile organic compounds identify patients with colorectal cancer

An effective screening tool for colorectal cancer is still lacking. Analysis of the volatile organic compounds (VOCs) linked to cancer is a new frontier in cancer screening, as tumour growth involves several metabolic changes leading to the production of specific compounds that can be detected in exhaled breath. This study investigated whether patients with colorectal cancer have a specific VOC pattern compared with the healthy population. Exhaled breath was collected in an inert bag (Tedlar(®) ) from patients with colorectal cancer and healthy controls (negative at colonoscopy), and processed offline by thermal-desorber gas chromatography-mass spectrometry to evaluate the VOC profile. During the trial phase VOCs of interest were identified and selected, and VOC patterns able to discriminate patients from controls were set up; in the validation phase their discriminant performance was tested on blinded samples. A probabilistic neural network (PNN) validated by the leave-one-out method was used to identify the pattern of VOCs that better discriminated between the two groups. Some 37 patients and 41 controls were included in the trial phase. Application of a PNN to a pattern of 15 compounds showed a discriminant performance with a sensitivity of 86 per cent, a specificity of 83 per cent and an accuracy of 85 per cent (area under the receiver operating characteristic (ROC) curve 0·852). The accuracy of PNN analysis was confirmed in the validation phase on a further 25 subjects; the model correctly assigned 19 patients, giving an overall accuracy of 76 per cent. The pattern of VOCs in patients with colorectal cancer was different from that in healthy controls. The PNN in this study was able to discriminate patients with colorectal cancer with an accuracy of over 75 per cent. Breath VOC analysis appears to have potential clinical application in colorectal cancer screening, although further studies are required to confirm its reliability in heterogeneous clinical settings.

A study of volatile organic compound concentrations in a new school building over one year period

Volatile organic compounds (VOCs) are defined as carbon-based organic compounds that put negative impacts on nervous system through respiration. The objective of this study was to assess concentrations of VOCs at a new school building and to compare the concentration by different variables. Samples were collected from inside and outside of four rooms in a new constructed building for a year in Seoul, Korea. Then, they were analyzed by using a gas chromatography with flame ionization detector (GC-FID). Total volatile organic compounds (TVOC) and toluene highly exceeded the standard level right after construction. The concentration patterns of VOCs significantly decreased for six months. Correlation analysis showed strong positive correlation between TVOC and toluene and weak positive correlation between heptane and tetradecane. Therefore, some cautions are needed to avoid the exposure of VOCs emitted from new buildings until six months after the construction.

Plant pest and disease diagnosis using electronic nose and support vector machine approach

In this paper, we evaluate the use of an electronic nose (EN) containing 13 conducting polymer gas sensors to discriminate between patterns of volatile organic compounds (VOCs) emitted by plants. The VOC patterns examined were produced by tomato, cucumber and pepper plants under both healthy and infected or infested conditions. Leaves from the plants were subjected to mechanical damage or pest and disease attacks (i.e. spider mites infested or mildew infected) and others were judged against undamaged healthy leaves. Support vector machines (SVMs) with linear, polynomial and Gaussian radial basis function (RBF) kernels were used to process and classify the raw data collected. The SVM illustrated an ability to discriminate between different VOC patterns and hence was able to classify correctly the infected leaves using the EN data. The results indicate that the array of 13 EN gas sensors can discriminate among VOC patterns from undamaged and artificially damaged leaves of the three plant species. This study demonstrates the potential application of such an EN technology coupled with suitable pattern recognition and signal processing methods to be used as a real time pest and disease detection system in the greenhouse environment.

PWE-004 A study of faecal volatile organic compounds metabolome in healthy population across the countries

IntroductionFaecal biomarkers are emerging non-invasive tools for diagnosing gastrointestinal disorders. Faecal volatile organic compounds (VOCs) have been studied more recently in clinical diagnosis. Pattern of faecal VOCs in healthy population...

The versatile use of exhaled volatile organic compounds in human health and disease

Exhaled breath contains thousands of volatile organic compounds (VOCs) of which the composition varies depending on health status. Various metabolic processes within the body produce volatile products that are released into the blood and will be passed on to the airway once the blood reaches the lungs. Moreover, the occurrence of chronic inflammation and/or oxidative stress can result in the excretion of volatile compounds that generate unique VOC patterns. Consequently, measuring the total amount of VOCs in exhaled air, a kind of metabolomics also referred to as breathomics, for clinical diagnosis and monitoring purposes gained increased interest over the last years. This paper describes the currently available methodologies regarding sampling, sample analysis and data processing as well as their advantages and potential drawbacks. Additionally, different application possibilities of VOC profiling are discussed. Until now, breathomics has merely been applied for diagnostic purposes. Exhaled air analysis can, however, also be applied as an analytical or monitoring tool. Within the analytic perspective, the use of VOCs as biomarkers of oxidative stress, inflammation or carcinogenesis is described. As monitoring tool, breathomics can be applied to elucidate the heterogeneity observed in chronic diseases, to study the pathogen(s) responsible for occurring infections and to monitor treatment efficacy.

Detection of volatile organic compounds in cattle naturally infected with Mycobacterium bovis

Abstract We report here on a novel methodology in detecting Mycobacterium bovis (M. bovis) infection in cattle, based on identifying unique volatile organic compounds (VOCs) or a VOC profile in the breath of cattle. The study was conducted on an M. bovis-infected dairy located in southern Colorado, USA, and on two tuberculosis-free dairies from northern Colorado examined as negative controls. Gas-chromatography/mass-spectrometry analysis revealed the presence of 2 VOCs associated with M. bovis infection and 2 other VOCs associated with the healthy state in the exhaled breath of M. bovis-infected and not infected animals, yielding distinctly different VOC patterns for the two study groups. Based on these results, a nanotechnology-based array of sensors was then tailored for detection of M. bovis-infected cattle via breath. Our system successfully identified all M. bovis-infected animals, while 21% of the not infected animals were classified as M. bovis-infected. This technique could form the basis for a real-time cattle monitoring system that allows efficient and non-invasive screening for new M. bovis infections on dairy farms.

The emission patterns of volatile organic compounds during aerobic biotreatment of municipal solid waste using continuous and intermittent aeration

Because volatile organic compounds (VOCs) are one of the main concerns during municipal solid waste (MSW) treatment, the release patterns and the environmental effects of VOCs were investigated during laboratory-scale aerobic biotreatments of MSW with continuous and intermittent negative ventilation. When the same airflow amounts were used, intermittent ventilation was found to reduce the total VOC emissions from continuous ventilation process by 28%. In this study, 23 types of volatile organic compounds were analyzed, of which butyraldehyde, ethanol, and butanone were emitted in the highest concentrations of 748, 372, and 260 mg/m3, respectively. During the aerobic biotreatment process, ketones, aldehydes, and alcohols were primarily released during the first 4 days, accounting for 86−98% of the total VOC emissions during this period. The emission concentrations of malodorous sulfide compounds displayed two peaks on day 4 and day 9, with the contribution to the total VOC emissions being enhanced from less than 10% to 76−83%. The release of terpenes and aromatics lasted for more than 10 days with no significant emission peaks and the proportions of those compounds in the total VOCs increased gradually, but no more than 50% even at the end of the process. Considering the strength of the odors, aldehydes were the predominant contributors at the beginning of the experiment, whereas malodorous sulfide compounds became the most odorous compound as the biological process continued. Most of the VOCs emitted at the concentrations beneath the level causing health threat to the workers. Implications: In aerobic biotreatment plants of MSW, volatile organic compounds (VOCs) are among the major pollutants in exhaust gases. Understanding the emission patterns of VOCs (e.g., identifying the dominant VOC components during the different biotreatment stages) are of importance for VOC control and treatment, and can also provide a new index to evaluate the different biotreatment operations. This paper is of interest to scientists, the operators of MSW biotreatment plants, and those concerned with odor management practices.

Ion mobility spectrometry for microbial volatile organic compounds: a new identification tool for human pathogenic bacteria

Presently, 2 to 4 days elapse between sampling at infection suspicion and result of microbial diagnostics. This delay for the identification of pathogens causes quite often a late and/or inappropriate initiation of therapy for patients suffering from infections. Bad outcome and high hospitalization costs are the consequences of these currently existing limited pathogen identification possibilities. For this reason, we aimed to apply the innovative method multi-capillary column–ion mobility spectrometry (MCC-IMS) for a fast identification of human pathogenic bacteria by determination of their characteristic volatile metabolomes. We determined volatile organic compound (VOC) patterns in headspace of 15 human pathogenic bacteria, which were grown for 24 h on Columbia blood agar plates. Besides MCC-IMS determination, we also used thermal desorption–gas chromatography–mass spectrometry measurements to confirm and evaluate obtained MCC-IMS data and if possible to assign volatile compounds to unknown MCC-IMS signals. Up to 21 specific signals have been determined by MCC-IMS for Proteus mirabilis possessing the most VOCs of all investigated strains. Of particular importance is the result that all investigated strains showed different VOC patterns by MCC-IMS using positive and negative ion mode for every single strain. Thus, the discrimination of investigated bacteria is possible by detection of their volatile organic compounds in the chosen experimental setup with the fast and cost-effective method MCC-IMS. In a hospital routine, this method could enable the identification of pathogens already after 24 h with the consequence that a specific therapy could be initiated significantly earlier.

Abstract A36: Breath Biomarkers in the Post NLST-era for the Discrimination between Malignant from Benign Pulmonary Nodules

Abstract Background: The recent National Lung Cancer Screening Trial (NLST) has proven that screening for lung cancer by low dose CT (LDCT) scans reduces the related mortality rate by 20%. However, in this program, the false positive rate was extremely high: 96% out of the 24% positive CT findings were non-cancerous. A high rate of false positives leads to unnecessary invasive procedures, which are both costly and associated with significant morbidity and mortality. It is now widely anticipated that LDCT screening programs will be launched in many countries in the near future. This will lead to a dramatically increased detection of small solitary pulmonary nodules (SPNs) for invasive investigation. Consequently, additional non-invasive biomarker approach to distinguish between benign and cancerous conditions is necessary. For that purpose, we evaluated in this study the role of exhale breath analysis as a potential non-invasive biomarker to discriminate between benign and malignant SPNs in the post NLST-era. Objectives: Developing a signature of volatile organic compounds (VOCs) in the exhaled breath that aids to distinguishes between benign and cancerous SPNs, and therefore also aids in 1) Early detection of lung cancer, 2) Improves the specificity of the NLST screening protocol in high risk cohorts, 3) helps prevent unnecessary invasive procedures, 4) results in the early treatment of lung cancer, and 5) Improves the costeffectiveness of the NLST screening program. Specifically, in this study we report the VOCs signature that discriminates benign from malignant SPNs, between NSCLC and SCLC and between early and advanced NSCLC. Methods: Cross-sectional comparative survey from 74 patients with solitary pulmonary nodules (SPNs) attending the University of Colorado Cancer Center or Denver Veterans Affairs Medical Center; USA. Breath samples were taken and the VOC profiles for malignant and benign lung nodules were determined by gas-chromatography/mass-spectrometry (GCMS), and the corresponding collective VOCs patterns were identified by a nanomaterialbased array of sensors. Results: Among the 74 high risk patients with SPNs on their LDCTs, 53 were malignant and 21 were benign. Age, smoking history, co-morbidity and medications were similar in both groups. Nodule sizes were 2.7±1.7 cm vs. 1.9±1.1 cm accordingly (NS). Within the malignant group, 47 were NSCLC and 6 were SCLC. Thirty had early disease (stage I-II/limited) and 23 had advanced disease (stage III-IV/extensive). GC-MS analysis identified two VOCs in the exhaled breath of nodule positive patients that showed statistically significant differences in concentration for benign and malignant lung nodules (N=11, 28 respectively; Benzene, 1-methyl-4-(1-methylethyl) and 1-Octene). The sensor array could distinguish between the corresponding collective VOCs patterns with an accuracy of 89.4%. Among the malignant SPNs we could further distinguish between SCLC and NSCLC (accuracy 93.9%) and between early and advanced disease (89.7%). Conclusions: An array of nanomaterial-based sensors could discriminate significantly between benign and malignant SPNs in a high-risk cohort with positive LDCTs based on lung cancer related VOCs profiles. Further, it was able to discriminate between NSCLC and SCLC, as well as between early and advanced disease. These results could promote the development of a non-invasive, fast and potentially cost-effective diagnostic tool for the management of nodule-positive patients that could help to eliminate risky invasive procedures in patients with benign nodules in the post NLST-era.

The scent fingerprint of hepatocarcinoma: in-vitro metastasis prediction with volatile organic compounds (VOCs).

Background:Hepatocellular carcinoma (HCC) is a common and aggressive form of cancer. Due to a high rate of postoperative recurrence, the prognosis for HCC is poor. Subclinical metastasis is the major cause of tumor recurrence and patient mortality. Currently, there is no reliable prognostic method of invasion.Aim:To investigate the feasibility of fingerprints of volatile organic compounds (VOCs) for the in-vitro prediction of metastasis.Methods:Headspace gases were collected from 36 cell cultures (HCC with high and low metastatic potential and normal cells) and analyzed using nanomaterial-based sensors. Predictive models were built by employing discriminant factor analysis pattern recognition, and the classification success was determined using leave-one-out cross-validation. The chemical composition of each headspace sample was studied using gas chromatography coupled with mass spectrometry (GC-MS).Results:Excellent discrimination was achieved using the nanomaterial-based sensors between (i) all HCC and normal controls; (ii) low metastatic HCC and normal controls; (iii) high metastatic HCC and normal controls; and (iv) high and low HCC. Several HCC-related VOCs that could be associated with biochemical cellular processes were identified through GC-MS analysis.Conclusion:The presented results constitute a proof-of-concept for the in-vitro prediction of the metastatic potential of HCC from VOC fingerprints using nanotechnology. Further studies on a larger number of more diverse cell cultures are needed to evaluate the robustness of the VOC patterns. These findings could benefit the development of a fast and potentially inexpensive laboratory test for subclinical HCC metastasis.