Prediction of lung cancer using volatile biomarkers in breath1

Headspace measurements of irradiated in vitro cultured cells using PTR-MS

A pilot study was performed to evaluate a new concept for a radiation biodosimetry method. Proton transfer reaction-mass spectrometry (PTR-MS) was used to find out whether radiation induces changes in the composition of volatile organic compounds (VOCs) in the headspace of in vitro cultured cells. Two different cell lines, retinal pigment epithelium cells hTERT-RPE1 and lung epithelium cells A-549, were irradiated with gamma radiation at doses of 4 Gy and 8 Gy. For measuring the cell-specific effects, the VOC concentrations in the headspace of flasks containing cells plus medium, as well as of flasks containing pure medium were analyzed for changes before and after irradiation. No significant radiation-induced alterations in VOC concentrations in the headspace could be observed after irradiation.

The screening of volatile markers for hepatocellular carcinoma

BACKGROUND

Breath analysis became promising for noninvasive diagnoses of cancer with sophisticated spectrometry technology introduced. This study aimed to screen volatile markers for hepatocellular carcinoma (HCC).

METHODS

Breath samples were collected from 30 HCC patients who were comorbid with type B hepatitis and cirrhosis and from 27 hepatocirrhosis patients and 36 healthy persons, both taken as controls. The volatile organic compounds in the samples were analyzed with gas chromatography/mass spectrometry and the markers were selected by comparing their levels between groups. Each of the markers was evaluated by receiver operating characteristic (ROC) curves and a discriminant function using the markers was established. The relationships of alpha-fetoprotein (AFP) levels and clinical stages with the concentrations of the markers were also investigated.

RESULTS

3-Hydroxy-2-butanone, styrene, and decane were screened as potential markers, among which 3-hydroxy-2-butanone was found to have the best diagnostic value. The diagnostic function using these markers had a sensitivity of 86.7% and a specificity of 91.7% between HCC patients and normal controls and a sensitivity of 83.3% and a specificity of 91.7% by cross-validation. No statistically significance (P > 0.05) was found for the concentration differences of these markers between HCC patients with AFP >400 or <400 microg/L or between stage I-II and stage III-IV patients.

CONCLUSION

These volatile organic compounds could be useful as breath markers of HCC patients, independent of AFP levels or clinical stages.

IMPACT

Breath analysis could be useful for early diagnosis of HCC, especially for AFP-negative HCC.

Differential volatile signatures from skin, naevi and melanoma: a novel approach to detect a pathological process

Background

Early detection of melanoma is of great importance to reduce mortality. Discovering new melanoma biomarkers would improve early detection and diagnosis. Here, we present a novel approach to detect volatile compounds from skin.

Methods and Findings

We used Head Space Solid Phase Micro-Extraction (HS-SPME) and gas chromatography/mass spectrometry (GC/MS) to identify volatile signatures from melanoma, naevi and skin samples. We hypothesized that the metabolic state of tissue alters the profile of volatile compounds. Volatiles released from fresh biopsy tissue of melanoma and benign naevus were compared based on their difference in frequency distribution and their expression level. We also analyzed volatile profiles from frozen tissue, including skin and melanoma.

Conclusions

Three volatiles, 4-methyl decane, dodecane and undecane were preferentially expressed in both fresh and frozen melanoma, indicating that they are candidate biomarkers. Twelve candidate biomarkers evaluated by fuzzy logic analysis of frozen samples distinguished melanoma from skin with 89% sensitivity and 90% specificity. Our results demonstrate proof-of-principle that there is differential expression of volatiles in melanoma. Our volatile metabolomic approach will lead to a better understanding of melanoma and can enable development of new diagnostic and treatment strategies based on altered metabolism.

Breath biomarkers for personalized medicine

Personalized medicine, in the near future, has the potential to revolutionize healthcare by allowing physicians to individualize therapy for patients through the early diagnosis of disease and risk assessment to optimize clinical response with minimal toxicity. The identification of biomarkers could detect, diagnose and help guide therapy to improve survival and quality of life by the early identification of responders to the drugs. Volatile organic compounds and stable isotope-labeled 13CO2 in breath can be uniquely utilized as in vivo diagnostic biomarkers of disease and/or lack of enzyme activity to aid physicians to personalize medication. Noninvasive detection of ailments and monitoring therapy by human breath analysis is an emerging field of medical diagnostics representing a rapid, economic and simple alternative to standard invasive blood analysis, endoscopy or harmful imaging techniques such as x-ray and CT scans.

Breath analysis in asbestos-related disorders: a review of the literature and potential future applications

Asbestos usage was very common worldwide in the last century and continues in several countries today. Several diseases occur due to asbestos exposure, including malignant tumours such as malignant mesothelioma of the pleura and lung cancer, which have a very poor prognosis. Asbestos inhalation may also result in more benign conditions such as asbestosis (or pulmonary fibrosis due to asbestos), pleural plaques and pleural thickening. It is predicted that asbestos-associated mortality and morbidity will continue to increase, but methods for diagnosing asbestos-related disease are currently invasive and unsuitable for an increasingly elderly population. New non-invasive methods such as analysis of exhaled breath biomarkers e.g. exhaled nitric oxide (F(E)NO), exhaled breath condensate or of exhaled volatile organic compounds could potentially be extremely useful in these conditions. This article reviews the current literature on this topic and suggests areas for their application in the future.

Electronic-nose technology using sputum samples in diagnosis of patients with tuberculosis

We investigated the potential of two different electronic noses (EN; code named "Rob" and "Walter") to differentiate between sputum headspace samples from tuberculosis (TB) patients and non-TB patients. Only samples from Ziehl-Neelsen stain (ZN)- and Mycobacterium tuberculosis culture-positive (TBPOS) sputum samples and ZN- and culture-negative (TBNEG) samples were used for headspace analysis; with EN Rob, we used 284 samples from TB suspects (56 TBPOS and 228 TBNEG samples), and with EN Walter, we used 323 samples from TB suspects (80 TBPOS and 243 TBNEG samples). The best results were obtained using advanced data extraction and linear discriminant function analysis, resulting in a sensitivity of 68%, a specificity of 69%, and an accuracy of 69% for EN Rob; for EN Walter, the results were 75%, 67%, and 69%, respectively. Further research is still required to improve the sensitivity and specificity by choosing more selective sensors and type of sampling technique.

A novel breath analysis system based on electronic olfaction

Certain gases in the breath are known to be indicators of the presence of diseases and clinical conditions. These gases have been identified as biomarkers using equipments such as gas chromatography (GC) and electronic nose (e-nose). GC is very accurate but is expensive, time consuming, and non-portable. E-nose has the advantages of low-cost and easy operation, but is not particular for analyzing breath odor and hence has a limited application in diseases diagnosis. This article proposes a novel system that is special for breath analysis. We selected chemical sensors that are sensitive to the biomarkers and compositions in human breath, developed the system, and introduced the odor signal preprocessing and classification method. To evaluate the system performance, we captured breath samples from healthy persons and patients known to be afflicted with diabetes, renal disease, and airway inflammation repectively and conducted experiments on medical treatment evaluation and disease identification. The results show that the system is not only able to distinguish between breath samples from subjects suffering from various diseases or conditions (diabetes, renal disease, and airway inflammation) and breath samples from healthy subjects, but in the case of renal failure is also helpful in evaluating the efficacy of hemodialysis (treatment for renal failure).

TD-GC-MS analysis of volatile metabolites of human lung cancer and normal cells in vitro

The aim of this study was to confirm the existence of volatile organic compounds (VOC) specifically released or consumed by the lung cancer cell line A549, which could be used in future screens as biomarkers for the early detection of lung cancer. For comparison, primary human bronchial epithelial cells (HBEpC) and human fibroblasts (hFB) were included. VOCs were detected in the headspace of cell cultures or medium controls following adsorption on solid sorbents, thermodesorption, and analysis by gas chromatography mass spectrometry. Using this approach, we identified VOCs that behaved similarly in normal and transformed cells. Thus, concentrations of 2-pentanone and 2,4-dimethyl-1-heptene were found to increase in the headspace of A549, HBEpC, and hFB cell cultures. In addition, the ethers methyl tert-butyl ether and ethyl tert-butyl ether could be detected at elevated levels in the case of A549 cells and one of the untransformed cell lines. However, especially branched hydrocarbons and alcohols were seen increased more frequently in untransformed than A549 cells. A big variety of predominantly aldehydes and the ester n-butyl acetate were found at decreased concentrations in the headspace of all cell lines tested compared with medium controls. Again, more different aldehydes were found to be decreased in hFB and HBEpC cells compared with A549 cells and 2-butenal was metabolized exclusively by both control cell lines. These data suggest that certain groups of VOCs may be preferentially associated with the transformed phenotype.

Volatile biomarkers in the breath of women with breast cancer

We sought biomarkers of breast cancer in the breath because the disease is accompanied by increased oxidative stress and induction of cytochrome P450 enzymes, both of which generate volatile organic compounds (VOCs) that are excreted in breath. We analyzed breath VOCs in 54 women with biopsy-proven breast cancer and 204 cancer-free controls, using gas chromatography/mass spectroscopy. Chromatograms were converted into a series of data points by segmenting them into 900 time slices (8 s duration, 4 s overlap) and determining their alveolar gradients (abundance in breath minus abundance in ambient room air). Monte Carlo simulations identified time slices with better than random accuracy as biomarkers of breast cancer by excluding random identifiers. Patients were randomly allocated to training sets or test sets in 2:1 data splits. In the training sets, time slices were ranked according their C-statistic values (area under curve of receiver operating characteristic), and the top ten time slices were combined in multivariate algorithms that were cross-validated in the test sets. Monte Carlo simulations identified an excess of correct over random time slices, consistent with non-random biomarkers of breast cancer in the breath. The outcomes of ten random data splits (mean (standard deviation)) in the training sets were sensitivity = 78.5% (6.14), specificity = 88.3% (5.47), C-statistic = 0.89 (0.03) and in the test sets, sensitivity = 75.3% (7.22), specificity = 84.8 (9.97), C-statistic = 0.83 (0.06). A breath test identified women with breast cancer, employing a combination of volatile biomarkers in a multivariate algorithm.

Breath biomarkers of active pulmonary tuberculosis

BACKGROUND

Volatile organic compounds (VOCs) in breath may contain biomarkers of active pulmonary tuberculosis derived from the infectious organism (metabolites of Mycobacterium tuberculosis) and from the infected host (products of oxidative stress).

METHODS

We analyzed breath VOCs in 226 symptomatic high-risk patients in USA, Philippines, and UK, using gas chromatography/mass spectroscopy. Diagnosis of disease was based on sputum culture, smear microscopy, chest radiography and clinical suspicion of tuberculosis (CSTB). Chromatograms were converted to a series of 8s overlapping time slices. Biomarkers of active pulmonary tuberculosis were identified with a Monte Carlo analysis of time-slice alveolar gradients (abundance in breath minus abundance in room air).

RESULTS

Breath VOCs contained apparent biomarkers of active pulmonary tuberculosis comprising oxidative stress products (alkanes and alkane derivatives) and volatile metabolites of M. tuberculosis (cyclohexane and benzene derivatives). Breath biomarkers identified active pulmonary tuberculosis with C-statistic (area under curve of receiver operating characteristic)=0.85 (i.e. 85% overall accuracy, sensitivity=84.0%, specificity=64.7%) when sputum culture, microscopy, and chest radiography were either all positive or all negative. Employing a single criterion of disease, C-statistic=0.76 (smear microscopy), 0.68 (sputum culture), 0.66 (chest radiography) and 0.65 (CSTB).

CONCLUSION

A breath test identified apparent biomarkers of active pulmonary tuberculosis with 85% accuracy in symptomatic high-risk subjects.

Determination of aldehydes in exhaled breath of patients with lung cancer by means of on-fiber-derivatisation SPME-GC/MS

A number of volatile organic compounds (VOCs) have been identified and used in preliminary clinical studies of the early diagnosis of lung cancer. The aim of this study was to evaluate the potential of aldehydes (known biomarkers of oxidative stress) in the diagnosis of patients with non-small cell lung cancer (NSCLC). We used an on-fiber-derivatisation SPME sampling technique coupled with GC/MS analysis to measure straight aldehydes C3-C9 in exhaled breath. Linearity was established over two orders of magnitude (range: 3.3-333.3×10(-12) M); the LOD and LOQ of all the aldehydes were respectively 1×10(-12) M and 3×10(-12) M. Accuracy was within 93% and precision calculated as % RSD was 7.2-15.1%. Aldehyde stability in a Bio-VOC(®) tube stored at +4°C was 10-17 h, but this became >10 days using a specific fiber storage device. Finally, exhaled aldehydes were measured in 38 asymptomatic non-smokers (controls) and 40 NSCLC patients. The levels of all of the aldehydes were increased in the NSCLC patients without any significant effect of smoking habits and little effect of age. The good discriminant power of the aldehyde pattern (90%) was confirmed by multivariate analysis. These results show that straight aldehydes may be promising biomarkers associated with NSCLC, and increase the sensitivity and specificity of previously identified VOC patterns.

A profile of volatile organic compounds in breath discriminates COPD patients from controls

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is an inflammatory condition characterized by oxidative stress and the formation of volatile organic compounds (VOCs) secreted via the lungs. We recently developed a methodological approach able to identify profiles of VOCs in breath unique for patient groups. Here we applied this recently developed methodology regarding diagnosis of COPD patients.

METHODS

Fifty COPD patients and 29 controls provided their breath and VOCs were analyzed by gas chromatography-mass spectrometry to identify relevant VOCs. An additional 16 COPD patients and 16 controls were sampled in order to validate the model, and 15 steroid naïve COPD patients were sampled to determine whether steroid use affects performance.

FINDINGS

1179 different VOCs were detected, of which 13 were sufficient to correctly classify all 79 subjects. Six of these 13 VOCs classified 92% of the subjects correctly (sensitivity: 98%, specificity: 88%) and correctly classified 29 of 32 subjects (sensitivity: 100%, specificity: 81%) from the independent validation population. Fourteen out of 15 steroid naïve COPD patients were correctly classified thus excluding treatment influences.

INTERPRETATION

This is the first study distinguishing COPD subjects from controls solely based on the presence of VOCs in breath. Analysis of VOCs might be highly relevant for diagnosis of COPD.

Noninvasive detection of lung cancer by analysis of exhaled breath

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.

Volatile organic compounds in exhaled breath as a diagnostic tool for asthma in children

BACKGROUND

The correct diagnosis of asthma in young children is often hard to achieve, resulting in undertreatment of asthmatic children and overtreatment in transient wheezers.

OBJECTIVES

To develop a new diagnostic tool that better discriminates between asthma and transient wheezing and that leads to a more accurate diagnosis and hence less undertreatment and overtreatment. A first stage in the development of such a tool is the ability to discriminate between asthmatic children and healthy controls. The integrative analysis of large numbers of volatile organic compounds (VOC) in exhaled breath has the potential to discriminate between various inflammatory conditions of the respiratory tract.

METHODS

Breath samples were obtained and analysed for VOC by gas chromatography-mass spectrometry from asthmatic children (n=63) and healthy controls (n=57). A total of 945 determined compounds were subjected to discriminant analysis to find those that could discriminate diseased from healthy children. A set of samples from both asthmatic and healthy children was selected to construct a model that was subsequently used to predict the asthma or the healthy status of a test group. In this way, the predictive value of the model could be tested.

MEASUREMENTS AND MAIN RESULTS

The discriminant analyses demonstrated that asthma and healthy groups are distinct from one another. A total of eight components discriminated between asthmatic and healthy children with a 92% correct classification, achieving a sensitivity of 89% and a specificity of 95%. Conclusion The results show that a limited number of VOC in exhaled air can well be used to distinguish children with asthma from healthy children.

Determination of volatile organic compounds in exhaled breath of patients with lung cancer using solid phase microextraction and gas chromatography mass spectrometry

BACKGROUND

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.

METHODS

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).

RESULTS

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.

CONCLUSIONS

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.

Volatile compounds characteristic of sinus-related bacteria and infected sinus mucus: analysis by solid-phase microextraction and gas chromatography-mass spectrometry

Volatile compounds from human breath are a potential source of information for disease diagnosis. Breath may include volatile organic compounds (VOCs) originating in the nasal sinuses. If the sinuses are infected, disease-specific volatiles may enter exhaled air. Sinus infections are commonly caused by several known bacteria. We examined the volatiles characteristic of infectious bacteria in culture using solid-phase microextraction to collect and gas chromatography-mass spectrometry as well as gas chromatography with flame photometric detection to separate and analyze the resulting VOCs. Infected sinus mucus samples were also collected and their VOCs examined. Similar characteristic volatiles were seen from both cultures of individual "pure" bacteria and several mucus samples. However, the relative amounts of characteristic VOCs from individual bacteria differ greatly between cultures and sinus mucus. New compounds, not seen in culture were also seen in some mucus samples. Our results suggest an important role for growth substrate and environment. Our data further suggests that in some sinus mucus samples identification of bacteria-specific volatiles is possible and can suggest the identity of an infecting organism to physicians. Knowledge of these bacteria-related volatiles is necessary to create electronic nose-based, volatile-specific sensors for non-invasive examination for suspected sinus infection.

Metabolomics: moving to the clinic

Assessment of a biological system by means of global and non-targeted metabolite profiling--metabolomics or metabonomics--provides the investigator with molecular information that is close to the phenotype in question in the sense that metabolites are an ultimate product of gene, mRNA, and protein activity. Over the last few years, there has been a rapidly growing number of metabolomics applications aimed at finding biomarkers which could assist diagnosis, provide therapy guidance, and evaluate response to therapy for particular diseases. Also, within the fields of drug discovery, drug toxicology, and personalized pharmacology, metabolomics is emerging as a powerful tool. This review seeks to update the reader on analytical strategies, biomarker findings, and implications of metabolomics for the clinic. Particular attention is paid to recent biomarkers found related to neurological, cardiovascular, and cancer diseases. Moreover, the impact of metabolomics in the drug discovery and development process is examined.

Metabolomics-based methods for early disease diagnostics

The emerging field of metabolomics, in which a large number of small-molecule metabolites from body fluids or tissues are detected quantitatively in a single step, promises immense potential for early diagnosis, therapy monitoring and for understanding the pathogenesis of many diseases. Metabolomics methods are mostly focused on the information-rich analytical techniques of NMR spectroscopy and mass spectrometry (MS). Analysis of the data from these high-resolution methods using advanced chemometric approaches provides a powerful platform for translational and clinical research and diagnostic applications. In this review, the current trends and recent advances in NMR- and MS-based metabolomics are described with a focus on the development of advanced NMR and MS methods, improved multivariate statistical data analysis and recent applications in the area of cancer, diabetes, inborn errors of metabolism and cardiovascular diseases.

Release of volatile organic compounds (VOCs) from the lung cancer cell line CALU-1 in vitro

Background

The aim of this work was to confirm the existence of volatile organic compounds (VOCs) specifically released or consumed by lung cancer cells.

Methods

50 million cells of the human non-small cell lung cancer (NSCLC) cell line CALU-1 were incubated in a sealed fermenter for 4 h or over night (18 hours). Then air samples from the headspace of the culture vessel were collected and preconcentrated by adsorption on solid sorbents with subsequent thermodesorption and analysis by means of gas chromatography mass spectrometry (GC-MS). Identification of altogether 60 compounds in GCMS measurement was done not only by spectral library match, but also by determination of retention times established with calibration mixtures of the respective pure compounds.

Results

The results showed a significant increase in the concentrations of 2,3,3-trimethylpentane, 2,3,5-trimethylhexane, 2,4-dimethylheptane and 4-methyloctane in the headspace of CALU-1 cell culture as compared to medium controls after 18 h. Decreased concentrations after 18 h of incubation were found for acetaldehyde, 3-methylbutanal, butyl acetate, acetonitrile, acrolein, methacrolein, 2-methylpropanal, 2-butanone, 2-methoxy-2-methylpropane, 2-ethoxy-2-methylpropane, and hexanal.

Conclusion

Our findings demonstrate that certain volatile compounds can be cancer-cell derived and thus indicative of the presence of a tumor, whereas other compounds are not released but seem to be consumed by CALU-1 cells.

An electronic nose in the discrimination of patients with non-small cell lung cancer and COPD

BACKGROUND

Exhaled breath contains thousands of gaseous volatile organic compounds (VOCs) that may be used as non-invasive markers of lung disease. The electronic nose analyzes VOCs by composite nano-sensor arrays with learning algorithms. It has been shown that an electronic nose can distinguish the VOCs pattern in exhaled breath of lung cancer patients from healthy controls. We hypothesized that an electronic nose can discriminate patients with lung cancer from COPD patients and healthy controls by analyzing the VOC-profile in exhaled breath.

METHODS

30 subjects participated in a cross-sectional study: 10 patients with non-small cell lung cancer (NSCLC, [age 66.4+/-9.0, FEV(1) 86.3+/-20.7]), 10 patients with COPD (age 61.4+/-5.5, FEV(1) 70.0+/-14.8) and 10 healthy controls (age 58.3+/-8.1, FEV(1) 108.9+/-14.6). After 5 min tidal breathing through a non-rebreathing valve with inspiratory VOC-filter, subjects performed a single vital capacity maneuver to collect dried exhaled air into a Tedlar bag. The bag was connected to the electronic nose (Cyranose 320) within 10 min, with VOC-filtered room air as baseline. The smellprints were analyzed by onboard statistical software.

RESULTS

Smellprints from NSCLC patients clustered distinctly from those of COPD subjects (cross validation value [CVV]: 85%; M-distance: 3.73). NSCLC patients could also be discriminated from healthy controls in duplicate measurements (CVV: 90% and 80%, respectively; M-distance: 2.96 and 2.26).

CONCLUSION

VOC-patterns of exhaled breath discriminates patients with lung cancer from COPD patients as well as healthy controls. The electronic nose may qualify as a non-invasive diagnostic tool for lung cancer in the future.

Progress in the development of a diagnostic test for lung cancer through the analysis of breath volatiles

In this paper I will describe some of the challenges faced in the management of lung cancer. I will describe the rationale for studying breath testing for volatile organic compounds as a diagnostic test for lung cancer, and outline the evidence that suggests the potential of this line of investigation. I will conclude by speculating about the progress that needs to occur for breath testing to become clinically useful, capable of meeting some of the challenges of this major public health problem.

Analysis of volatile organic compounds in the exhaled breath for the diagnosis of lung cancer

Volatile organic compounds are able to be detected in the exhaled breath by a variety of sensing techniques. These volatiles may be produced by cellular metabolic processes, or inhaled/absorbed from exogenous sources. Lung cancer cells may produce and process these compounds different than normal cells. The differences may be detectable in the breath. The following manuscript will review the evidence supporting the premise that a unique chemical signature can be detected in the breath of patients with lung cancer, discuss the results of studies using mass spectrometry and nonspecific chemical sensing techniques to detect the unique lung cancer signature, and speculate on the advancements that must occur to develop a breath test accurate enough to be clinically useful.

New screening method for lung cancer by detecting volatile organic compounds in breath

Lung cancer is a frequent cause of cancer-related deaths in the world. There is no valid screening process and this limits its detection to the late stages, with consequently high mortality rates. Volatile organic compounds (VOC) are chemical compounds (mainly the products of cell catabolism) found as gases in the human breath. Different methods have been developed to analyse VOCs and to compare them in healthy subjects and lung cancer patients. In this review, we summarise the different techniques used to analyse VOC. Many reports have been published with promising results similar to those achieved with accepted screening methods such as mammography. These methods show good perspectives on lung cancer screening.

Prediction of lung cancer using volatile biomarkers in breath

BACKGROUND

Normal metabolism generates several volatile organic compounds (VOCs) that are excreted in the breath (e.g. alkanes). In patients with lung cancer, induction of high-risk cytochrome p450 genotypes may accelerate catabolism of these VOCs, so that their altered abundance in breath may provide biomarkers of lung cancer.

METHODS

VOCs in 1.0 L alveolar breath were analyzed in 193 subjects with primary lung cancer and 211 controls with a negative chest CT. Subjects were randomly assigned to a training set or to a prediction set in a 2:1 split. A fuzzy logic model of breath biomarkers of lung cancer was constructed in the training set and then tested in subjects in the prediction set by generating their typicality scores for lung cancer.

RESULTS

Mean typicality scores employing a 16 VOC model were significantly higher in lung cancer patients than in the control group (p<0.0001 in all TNM stages). The model predicted primary lung cancer with 84.6% sensitivity, 80.0% specificity, and 0.88 area under curve (AUC) of the receiver operating characteristic (ROC) curve. Predictive accuracy was similar in TNM stages 1 through 4, and was not affected by current or former tobacco smoking. The predictive model achieved near-maximal performance with six breath VOCs, and was progressively degraded by random classifiers. Predictions with fuzzy logic were consistently superior to multilinear analysis. If applied to a population with 2% prevalence of lung cancer, a screening breath test would have a negative predictive value of 0.985 and a positive predictive value of 0.163 (true positive rate =0.277, false positive rate =0.029).

CONCLUSIONS

A two-minute breath test predicted lung cancer with accuracy comparable to screening CT of chest. The accuracy of the test was not affected by TNM stage of disease or tobacco smoking. Alterations in breath VOCs in lung cancer were consistent with a non-linear pathophysiologic process, such as an off-on switch controlling high-risk cytochrome p450 activity. Further research is needed to determine if detection of lung cancer with this test will reduce mortality.