Exhaled breath analysis in suspected cases of non-small-cell lung cancer: a cross-sectional study

Biomarkers Suitable for Early Detection of Intrathoracic Cancers in Primary Care: A Systematic Review

Intrathoracic cancers, including lung cancer, mesothelioma, and thymoma, present diagnostic challenges in primary care. Biomarkers could resolve some challenges. We synthesized evidence on biomarker performance for intrathoracic cancer detection in low-prevalence settings. A search in Embase and MEDLINE included studies that recruited participants with suspected intrathoracic cancer and reported on at least one diagnostic measure for a validated, noninvasive biomarker. Studies were excluded if participants were recruited based on a preestablished diagnosis. A total of 52 studies were included, reporting on 108 individual biomarkers and panels. Carcinoembryonic antigen, CYFRA 21-1, and VEGF were evaluated for lung cancer and mesothelioma. For lung cancer, carcinoembryonic antigen and CYFRA 21-1 were the most studied, with AUCs of 0.48 to -0.90 and 0.48 to -0.83, respectively. Pro-gastrin-releasing peptide (Pro-GRP) and neuron-specific enolase (NSE) had the highest negative predictive values (NPV) (98.2% and 96.9%, respectively), whereas Early Cancer Detection Test - Lung (Early CDT) and miRNA signature classifier panels showed NPVs of 99.3% and 99.0%, respectively, in smokers. For mesothelioma, fibrillin-3 and mesothelin plus osteopontin had AUCs of 0.93 and 0.91, respectively. Thymoma panels (binding AcHR + StrAb and binding AcHR + modulating AcHR + StrAb) had 100% NPVs in patients with myasthenia gravis. The review highlights the performance of some biomarkers. However, few were evaluated in low-prevalence settings. Further evaluation is necessary before implementing these biomarkers for intrathoracic cancers in primary care.

Diagnosis of Lung Cancer Through Exhaled Breath: A Comprehensive Study

OBJECTIVES

Exhaled breath analysis is an attractive lung cancer diagnostic tool. However, various factors that are not related to the disease status, comorbidities, and other diseases must be considered to obtain a reliable diagnostic model.

METHODS

Exhaled breath samples from 646 individuals including 273 patients with lung cancer (LC), 90 patients with cancer of other localizations (OC), 150 patients with noncancer lung diseases (NLD), and 133 healthy controls (HC) were analyzed using gas chromatography-mass spectrometry (GC-MS). The samples were collected in Tedlar bags. Volatile organic compounds (VOCs) were preconcentrated on Tenax TA sorbent tubes with subsequent two-stage thermal desorption followed by GC-MS analysis. The influence of age, gender, smoking status, time since last food consumption, and comorbidities on exhaled breath were evaluated. Also, the effect of histology, TNM, tumor localization, treatment status, and the presence of a tumor on VOC profile of patients with lung cancer were assessed. Intergroup statistics were estimated, diagnostic models were created using artificial neural networks (ANNs) and gradient boosted decision trees (GBDTs).

RESULTS

Smoking status and food consumption affect exhaled breath VOC profile: benzene, ethylbenzene, toluene, 1,3-pentadiene 1,4-pentadiene acetonitrile, and some ratios are significantly different in exhaled breath of smokers and nonsmokers; the ratios 2,3-butandione/2-pentanone, 2,3-butandione/dimethylsulfide, and 2-butanone/2-pentanone are affected by time since last food consumption. Exhaled breath of LC is affected by the form of the disease and comorbidities. One-pentanol and 2-butanone were different in exhaled breath of patients with various tumor localization; 2-butanone was different in exhaled breath of patients before and during treatment. Diabetes as a comorbidity affects the pentanal level in exhaled breath; obesity affects the ratios of 2,3-butanedione/dimethylsulfide and 2-butanone/isoprene. Sensitivity and specificity of diagnostic models aimed to discriminate LC and HC, OC, and NLD were 78.7% and 51.0%, 62.2% and 53.4%, and 60.4% and 58.0%, respectively. HC and patients, regardless of the disease, can be classified with sensitivity of 76.6% and specificity of 68.2%.

CONCLUSIONS

The models created to diagnose lung cancer can also classify OC and NLD as patients with lung cancer. Additionally, the influence of comorbidities and factors not related to the disease status must be considered before the creation of diagnostic models to avoid false results.

Breathomics: may it become an affordable, new tool for early diagnosis of non-small-cell lung cancer? An exploratory study on a cohort of 60 patients

OBJECTIVES

Analysis of breath, specifically the patterns of volatile organic compounds (VOCs), has shown the potential to distinguish between patients with lung cancer (LC) and healthy individuals (HC). However, the current technology relies on complex, expensive and low throughput analytical platforms, which provide an offline response, making it unsuitable for mass screening. A new portable device has been developed to enable fast and on-site LC diagnosis, and its reliability is being tested.

METHODS

Breath samples were collected from patients with histologically proven non-small-cell lung cancer (NSCLC) and healthy controls using Tedlar bags and a Nafion filter attached to a one-way mouthpiece. These samples were then analysed using an automated micro portable gas chromatography device that was developed in-house. The device consisted of a thermal desorption tube, thermal injector, separation column, photoionization detector, as well as other accessories such as pumps, valves and a helium cartridge. The resulting chromatograms were analysed using both chemometrics and machine learning techniques.

RESULTS

Thirty NSCLC patients and 30 HC entered the study. After a training set (20 NSCLC and 20 HC) and a testing set (10 NSCLC and 10 HC), an overall specificity of 83.3%, a sensitivity of 86.7% and an accuracy of 85.0% to identify NSCLC patients were found based on 3 VOCs.

CONCLUSIONS

These results are a significant step towards creating a low-cost, user-friendly and accessible tool for rapid on-site LC screening.

CLINICAL REGISTRATION NUMBER

ClinicalTrials.gov Identifier: NCT06034730.

Exhaled VOC detection in lung cancer screening: a comprehensive meta-analysis

BACKGROUND

Lung cancer (LC), characterized by high incidence and mortality rates, presents a significant challenge in oncology. Despite advancements in treatments, early detection remains crucial for improving patient outcomes. The accuracy of screening for LC by detecting volatile organic compounds (VOCs) in exhaled breath remains to be determined.

METHODS

Our systematic review, following PRISMA guidelines and analyzing data from 25 studies up to October 1, 2023, evaluates the effectiveness of different techniques in detecting VOCs. We registered the review protocol with PROSPERO and performed a systematic search in PubMed, EMBASE and Web of Science. Reviewers screened the studies' titles/abstracts and full texts, and used QUADAS-2 tool for quality assessment. Then performed meta-analysis by adopting a bivariate model for sensitivity and specificity.

RESULTS

This study explores the potential of VOCs in exhaled breath as biomarkers for LC screening, offering a non-invasive alternative to traditional methods. In all studies, exhaled VOCs discriminated LC from controls. The meta-analysis indicates an integrated sensitivity and specificity of 85% and 86%, respectively, with an AUC of 0.93 for VOC detection. We also conducted a systematic analysis of the source of the substance with the highest frequency of occurrence in the tested compounds. Despite the promising results, variability in study quality and methodological challenges highlight the need for further research.

CONCLUSION

This review emphasizes the potential of VOC analysis as a cost-effective, non-invasive screening tool for early LC detection, which could significantly improve patient management and survival rates.

Diagnostic performance of volatile organic compounds analysis and electronic noses for detecting colorectal cancer: a systematic review and meta-analysis

Introduction

The detection of Volatile Organic Compounds (VOCs) could provide a potential diagnostic modality for the early detection and surveillance of colorectal cancers. However, the overall diagnostic accuracy of the proposed tests remains uncertain.

Objective

This systematic review is to ascertain the diagnostic accuracy of using VOC analysis techniques and electronic noses (e-noses) as noninvasive diagnostic methods for colorectal cancer within the realm of clinical practice.

Methods

A systematic search was undertaken on PubMed, EMBASE, Web of Science, and the Cochrane Library to scrutinize pertinent studies published from their inception to September 1, 2023. Only studies conducted on human subjects were included. Meta-analysis was performed using a bivariate model to obtain summary estimates of sensitivity, specificity, and positive and negative likelihood ratios. The Quality Assessment of Diagnostic Accuracy Studies 2 tool was deployed for quality assessment. The protocol for this systematic review was registered in PROSPERO, and PRISMA guidelines were used for the identification, screening, eligibility, and selection process.

Results

This review encompassed 32 studies, 22 studies for VOC analysis and 9 studies for e-nose, one for both, with a total of 4688 subjects in the analysis. The pooled sensitivity and specificity of VOC analysis for CRC detection were 0.88 (95% CI, 0.83-0.92) and 0.85 (95% CI, 0.78-0.90), respectively. In the case of e-nose, the pooled sensitivity was 0.87 (95% CI, 0.83-0.90), and the pooled specificity was 0.78 (95% CI, 0.62-0.88). The area under the receiver operating characteristic analysis (ROC) curve for VOC analysis and e-noses were 0.93 (95% CI, 0.90-0.95) and 0.90 (95% CI, 0.87-0.92), respectively.

Conclusion

The outcomes of this review substantiate the commendable accuracy of VOC analysis and e-nose technology in detecting CRC. VOC analysis has a higher specificity than e-nose for the diagnosis of CRC and a sensitivity comparable to that of e-nose. However, numerous limitations, including a modest sample size, absence of standardized collection methods, lack of external validation, and a notable risk of bias, were identified. Consequently, there exists an imperative need for expansive, multi-center clinical studies to elucidate the applicability and reproducibility of VOC analysis or e-nose in the noninvasive diagnosis of colorectal cancer.

Systematic review registration

https://www.crd.york.ac.uk/prospero/#recordDetails, identifier CRD42023398465.

Real-Time Monitoring of Air Pollution Health Impacts Using Breath-Borne Gaseous Biomarkers from Rats

Offline techniques are adopted for studying air pollution health impacts, thus failing to provide in situ observations. Here, we have demonstrated their real-time monitoring by online analyzing an array of gaseous biomarkers from rats' exhaled breath using an integrated exhaled breath array sensor (IEBAS) developed. The biomarkers include total volatile organic compounds (TVOC), CO2, CO, NO, H2S, H2O2, O2, and NH3. Specific breath-borne VOCs were also analyzed by a gas chromatography-ion mobility spectrometer (GC-IMS). After real-life ambient air pollution exposures (2 h), the pollution levels of PM2.5 and O3 were both found to significantly affect the relative levels of multiple gaseous biomarkers in rats' breath. Eleven biomarkers, especially NO, H2S, and 1-propanol, were detected as significantly correlated with PM2.5 concentration, while heptanal was shown to be significantly correlated with O3. Likewise, significant changes were also detected in multiple breath-borne biomarkers from rats under lab-controlled O3 exposures with levels of 150, 300, and 1000 μg/m3 (2 h), compared to synthetic air exposure. Importantly, heptanal was experimentally confirmed as a reliable biomarker for O3 exposure, with a notable dose-response relationship. In contrast, conventional biomarkers of inflammation and oxidative stress in rat sera exhibited insignificant differences after the 2 h exposures. The results imply that breath-borne gaseous biomarkers can serve as an early and sensitive indicator for ambient pollutant exposure. This work pioneered a new research paradigm for online monitoring of air pollution health impacts while obtaining important candidate biomarker information for PM2.5 and O3 exposures.

GC-MS-based metabolomics of volatile organic compounds in exhaled breath: applications in health and disease. A review

Exhaled breath analysis, with particular emphasis on volatile organic compounds, represents a growing area of clinical research due to its obvious advantages over other diagnostic tests. Numerous pathologies have been extensively investigated for the identification of specific biomarkers in exhalates through metabolomics. However, the transference of breath tests to clinics remains limited, mainly due to deficiency in methodological standardization. Critical steps include the selection of breath sample types, collection devices, and enrichment techniques. GC-MS is the reference analytical technique for the analysis of volatile organic compounds in exhalates, especially during the biomarker discovery phase in metabolomics. This review comprehensively examines and compares metabolomic studies focusing on cancer, lung diseases, and infectious diseases. In addition to delving into the experimental designs reported, it also provides a critical discussion of the methodological aspects, ranging from the experimental design and sample collection to the identification of potential pathology-specific biomarkers.

Breath Analysis for Lung Cancer Early Detection-A Clinical Study

This clinical study presents a comprehensive investigation into the utility of breath analysis as a non-invasive method for the early detection of lung cancer. The study enrolled 14 lung cancer patients, 14 non-lung cancer controls with diverse medical conditions, and 3 tuberculosis (TB) patients for biomarker discovery. Matching criteria including age, gender, smoking history, and comorbidities were strictly followed to ensure reliable comparisons. A systematic breath sampling protocol utilizing a BIO-VOC sampler was employed, followed by VOC analysis using Thermal Desorption-Gas Chromatography-Mass Spectrometry (TD-GC/MS). The resulting VOC profiles were subjected to stringent statistical analysis, including Orthogonal Projections to Latent Structures-Discriminant Analysis (OPLS-DA), Kruskal-Wallis test, and Receiver Operating Characteristic (ROC) analysis. Notably, 13 VOCs exhibited statistically significant differences between lung cancer patients and controls. The combination of eight VOCs (hexanal, heptanal, octanal, benzaldehyde, undecane, phenylacetaldehyde, decanal, and benzoic acid) demonstrated substantial discriminatory power with an area under the curve (AUC) of 0.85, a sensitivity of 82%, and a specificity of 76% in the discovery set. Validation in an independent cohort yielded an AUC of 0.78, a sensitivity of 78%, and a specificity of 64%. Further analysis revealed that elevated aldehyde levels in lung cancer patients' breath could be attributed to overactivated Alcohol Dehydrogenase (ADH) pathways in cancerous tissues. Addressing methodological challenges, this study employed a matching of physiological and pathological confounders, controlled room air samples, and standardized breath sampling techniques. Despite the limitations, this study's findings emphasize the potential of breath analysis as a diagnostic tool for lung cancer and suggest its utility in differentiating tuberculosis from lung cancer. However, further research and validation are warranted for the translation of these findings into clinical practice.

A feasibility study on exhaled breath analysis using UV spectroscopy to detect COVID-19

A 23-subject feasibility study is reported to assess how UV absorbance measurements on exhaled breath samples collected from silicon microreactors can be used to detect COVID-19. The silicon microreactor technology chemoselectively preconcentrates exhaled carbonyl volatile organic compounds and subsequent methanol elution provides samples for analysis. The underlying scientific rationale that viral infection will induce an increase in exhaled carbonyls appears to be supported by the results of the feasibility study. The data indicate statistically significant differences in measured UV absorbance values between healthy and symptomatic COVID-19 positive subjects in the wavelength range from 235 nm to 305 nm. Factors such as subject age were noted as potential confounding variables.

Alveolar gradients in breath analysis. A pilot study with comparison of room air and inhaled air by simultaneous measurements using ion mobility spectrometry

Analyzing exhaled breath samples, especially using a highly sensitive method such as MCC/IMS (multi-capillary column/ion mobility spectrometry), may also detect analytes that are derived from exogenous production. In this regard, there is a discussion about the optimal interpretation of exhaled breath, either by considering volatile organic compounds (VOCs) only in exhaled breath or by additionally considering the composition of room air and calculating the alveolar gradients. However, there are no data on whether the composition and concentration of VOCs in room air are identical to those in truly inhaled air directly before analyzing the exhaled breath. The current study aimed to determine whether the VOCs in room air, which are usually used for the calculation of alveolar gradients, are identical to the VOCs in truly inhaled air. For the measurement of inhaled air and room air, two IMS, each coupled with an MCC that provided a pre-separation of the VOCs, were used in parallel. One device was used for sampling room air and the other for sampling inhaled air. Each device was coupled with a newly invented system that cleaned room air and provided a clean carrier gas, whereas formerly synthetic air had to be used as a carrier gas. In this pilot study, a healthy volunteer underwent three subsequent runs of sampling of inhaled air and simultaneous sampling and analysis of room air. Three of the selected 11 peaks (P4-unknown, P5-1-Butanol, and P9-Furan, 2-methyl-) had significantly higher intensities during inspiration than in room air, and four peaks (P1-1-Propanamine, N-(phenylmethylene), P2-2-Nonanone, P3-Benzene, 1,2,4-trimethyl-, and P11-Acetyl valeryl) had higher intensities in room air. Furthermore, four peaks (P6-Benzaldehyde, P7-Pentane, 2-methyl-, P8-Acetone, and P10-2-Propanamine) showed inconsistent differences in peak intensities between inhaled air and room air. To the best of our knowledge, this is the first study to compare simultaneous sampling of room air and inhaled air using MCC/IMS. The simultaneous measurement of inhaled air and room air showed that using room air for the calculation of alveolar gradients in breath analysis resulted in different alveolar gradient values than those obtained by measuring truly inhaled air.

Development of an analytical chip for colorimetric detection of medium-chain aldehydes by reaction with pararosaniline in porous glass

Medium-chain aldehydes are common human biogases that can be detected in the breath of patients with lung diseases. As such, the measurement of medium-chain aldehyde gases in human breath can provide significant, noninvasive, and diagnostic information related to the potential presence of such diseases. In this study, an analytical chip is developed for the detection of medium-chain aldehydes without interference from short-chain aldehydes. This analytical chip is composed of porous glass impregnated with pararosaniline and an acid (i.e., acetic acid with small amount of phosphoric acid). After exposure to medium-chain aldehydes, the red analytical chip became violet in color, and an absorption peak was observed at 620 nm. It was found that a non-reversible reaction occurred in the porous glass, therefore, the analytical chip functions in a cumulative manner. A linear relationship was determined between the absorbance change of the analytical chip at 620 nm and the nonanal exposure concentration. Importantly, the developed analytical chip successfully detected nonanal at concentrations of 8-270 ppb as calculated from the absorbance change at 620 nm after a 24 h exposure time. In addition, nonanal concentration was estimated using the change in the R value of the analytical chip photograph. This method is suitable for point-of-care breath analysis. Finally, the analytical chip was also found to be active toward octanal and decanal with a relative sensitivity of 0.7 compared to that of nonanal; it was not active toward short-chain aldehydes.

GC/MS analysis of hypoxic volatile metabolic markers in the MDA-MB-231 breast cancer cell line

Hypoxia in disease describes persistent low oxygen conditions, observed in a range of pathologies, including cancer. In the discovery of biomarkers in biological models, pathophysiological traits present a source of translatable metabolic products for the diagnosis of disease in humans. Part of the metabolome is represented by its volatile, gaseous fraction; the volatilome. Human volatile profiles, such as those found in breath, are able to diagnose disease, however accurate volatile biomarker discovery is required to target reliable biomarkers to develop new diagnostic tools. Using custom chambers to control oxygen levels and facilitate headspace sampling, the MDA-MB-231 breast cancer cell line was exposed to hypoxia (1% oxygen) for 24 h. The maintenance of hypoxic conditions in the system was successfully validated over this time period. Targeted and untargeted gas chromatography mass spectrometry approaches revealed four significantly altered volatile organic compounds when compared to control cells. Three compounds were actively consumed by cells: methyl chloride, acetone and n-Hexane. Cells under hypoxia also produced significant amounts of styrene. This work presents a novel methodology for identification of volatile metabolisms under controlled gas conditions with novel observations of volatile metabolisms by breast cancer cells.

Exhaled metabolic markers and relevant dysregulated pathways of lung cancer: a pilot study

INTRODUCTION

The clinical application of lung cancer detection based on breath test is still challenging due to lack of predictive molecular markers in exhaled breath. This study explored potential lung cancer biomarkers and their related pathways using a typical process for metabolomics investigation.

MATERIAL AND METHODS

Breath samples from 60 lung cancer patients and 176 healthy people were analyzed by GC-MS. The original data were GC-MS peak intensity removing background signal. Differential metabolites were selected after univariate statistical analysis and multivariate statistical analysis based on OPLS-DA and Spearman rank correlation analysis. A multivariate PLS-DA model was established based on differential metabolites for pattern recognition. Subsequently, pathway enrichment analysis was performed on differential metabolites.

RESULTS

The discriminant capability was assessed by ROC curve of whom the average AUC and average accuracy in 100-fold cross validations were 0.871 and 0.787, respectively. Eight potential biomarkers were involved in a total of 18 metabolic pathways. Among them, 11 metabolic pathways have p-value smaller than .1.

DISCUSSION

Some pathways among them are related to risk factors or therapies of lung cancer. However, more of them are dysregulated pathways of lung cancer reported in studies based on genome or transcriptome data.

CONCLUSION

We believe that it opens the possibility of using metabolomics methods to analyze data of exhaled breath and promotes involvement of knowledge dataset to cover more volatile metabolites.

CLINICAL SIGNIFICANCE

Although a series of related research reported diagnostic models with highly sensitive and specific prediction, the clinical application of lung cancer detection based on breath test is still challenging due to disease heterogeneity and lack of predictive molecular markers in exhaled breath. This study may promote the clinical application of this technique which is suitable for large-scale screening thanks to its low-cost and non-invasiveness. As a result, the mortality of lung cancer may be decreased in future.Key messagesIn the present study, 11 pathways involving 8 potential biomarkers were discovered to be dysregulated pathways of lung cancer.We found that it is possible to apply metabolomics methods in analysis of data from breath test, which is meaningful to discover convinced volatile markers with definite pathological and histological significance.

Non-invasive Exhaled Breath and Skin Analysis to Diagnose Lung Cancer: Study of Age Effect on Diagnostic Accuracy

Development of simple, fast, and non-invasive tests for lung cancer diagnostics is essential for clinical practice. In this paper, exhaled breath and skin were studied as potential objects to diagnose lung cancer. The influence of age on the performance of diagnostic models was studied. Gas chromatography in combination with mass spectrometry (MS) was used to analyze the exhaled breath of 110 lung cancer patients and 212 healthy individuals of various ages. Peak area ratios of volatile organic compounds (VOCs) were used for data analysis instead of VOC peak areas. Various machine learning algorithms were applied to create diagnostic models, and their performance was compared. The best results on the test data set were achieved using artificial neural networks (ANNs): classification of patients with lung cancer and young healthy volunteers: 88 ± 4% sensitivity and 83 ± 3% specificity; classification of patients with lung cancer and old healthy individuals: 81 ± 3% sensitivity and 85 ± 1% specificity. The difference between performance of models based on young and old healthy groups was minor. The results obtained have shown that metabolic dysregulation driven by the disease biology is too high, which significantly overlaps the age effect. The influence of tumor localization and histological type on exhaled breath samples of lung cancer patients was studied. Statistically significant differences between some parameters in these samples were observed. A possibility of assessing the disease status by skin analysis in the Zakharyin-Ged zones using an electronic nose based on the quartz crystal microbalance sensor system was evaluated. Diagnostic models created using ANNs allow us to classify the skin composition of patients with lung cancer and healthy subjects of different ages with a sensitivity of 69 ± 2% and a specificity of 68 ± 8% for the young healthy group and a sensitivity of 74 ± 7% and a specificity of 66 ± 6% for the old healthy group. Primary results of skin analysis in the Zakharyin-Ged zones for the lung cancer diagnosis have shown its utility, but further investigation is required to confirm the results obtained.

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

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

Exhaled Aldehydes as Biomarkers for Lung Diseases: A Narrative Review

Breath analysis provides great potential as a fast and non-invasive diagnostic tool for several diseases. Straight-chain aliphatic aldehydes were repeatedly detected in the breath of patients suffering from lung diseases using a variety of methods, such as mass spectrometry, ion mobility spectrometry, or electro-chemical sensors. Several studies found increased concentrations of exhaled aldehydes in patients suffering from lung cancer, inflammatory and infectious lung diseases, and mechanical lung injury. This article reviews the origin of exhaled straight-chain aliphatic aldehydes, available detection methods, and studies that found increased aldehyde exhalation in lung diseases.

Lipid Peroxidation Produces a Diverse Mixture of Saturated and Unsaturated Aldehydes in Exhaled Breath That Can Serve as Biomarkers of Lung Cancer-A Review

The peroxidation of unsaturated fatty acids is a widely recognized metabolic process that creates a complex mixture of volatile organic compounds including aldehydes. Elevated levels of reactive oxygen species in cancer cells promote random lipid peroxidation, which leads to a variety of aldehydes. In the case of lung cancer, many of these volatile aldehydes are exhaled and are of interest as potential markers of the disease. Relevant studies reporting aldehydes in the exhaled breath of lung cancer patients were collected for this review by searching the PubMed and SciFinderⁿ databases until 25 May 2022. Information on breath test results, including the biomarker collection, preconcentration, and quantification methods, was extracted and tabulated. Overall, 44 studies were included spanning a period of 34 years. The data show that, as a class, aldehydes are significantly elevated in the breath of lung cancer patients at all stages of the disease relative to healthy control subjects. The type of aldehyde detected and/or deemed to be a biomarker is highly dependent on the method of exhaled breath sampling and analysis. Unsaturated aldehydes, detected primarily when derivatized during preconcentration, are underrepresented as biomarkers given that they are also likely products of lipid peroxidation. Pentanal, hexanal, and heptanal were the most reported aldehydes in studies of exhaled breath from lung cancer patients.

Exhaled Breath Volatile Organic Compound Analysis for the Detection of Lung Cancer- A Systematic Review

A rapid and effective diagnostic method is essential for lung cancer since it shows symptoms only at its advanced stage. Research is being carried out in the area of exhaled breath analysis for the diagnosis of various pulmonary diseases including lung cancer. In this method exhaled breath volatile organic compounds (VOC) are analyzed with various techniques such as gas chromatography-mass spectrometry, ion mobility spectrometry, and electronic noses. The VOC analysis is suitable for lung cancer detection since it is non-invasive, fast, and also a low-cost method. In addition, this technique can detect primary stage nodules. This paper presents a systematic review of the various method employed by researchers in the breath analysis field. The articles were selected through various search engines like EMBASE, Google Scholar, Pubmed, and Google. In the initial screening process, 214 research papers were selected using various inclusion and exclusion criteria and finally, 55 articles were selected for the review. The results of the reviewed studies show that detection of lung cancer can be effectively done using the VOC analysis of exhaled breath. The results also show that this method can be used for detecting the different stages and histology of lung cancer. The exhaled breath VOC analysis technique will be popular in the future, bypassing the existing imaging techniques. This systematic review conveys the recent research opportunities, obstacles, difficulties, motivations, and suggestions associated with the breath analysis method for lung cancer detection.

Odors and cancer: Current status and future directions

Cancer is the second leading cause of death in the world. Because tumors detected at early stages are easier to treat, the search for biomarkers-especially non-invasive ones-that allow early detection of malignancies remains a central goal to reduce cancer mortality. Cancer, like other pathologies, often alters body odors, and much has been done by scientists over the last few decades to assess the value of volatile organic compounds (VOCs) as signatures of cancers. We present here a quantitative review of 208 studies carried out between 1984 and 2020 that explore VOCs as potential biomarkers of cancers. We analyzed the main findings of these studies, listing and classifying VOCs related to different cancer types while considering both sampling methods and analysis techniques. Considering this synthesis, we discuss several of the challenges and the most promising prospects of this research direction in the war against cancer.

Breathomics: Review of Sample Collection and Analysis, Data Modeling and Clinical Applications

Metabolomics research is rapidly gaining momentum in disease diagnosis, on top of other Omics technologies. Breathomics, as a branch of metabolomics is developing in various frontiers, for early and noninvasive monitoring of disease. This review starts with a brief introduction to metabolomics and breathomics. A number of important technical issues in exhaled breath collection and factors affecting the sampling procedures are presented. We review the recent progress in metabolomics approaches and a summary of their applications on the respiratory and non-respiratory diseases investigated by breath analysis. Recent reports on breathomics studies retrieved from Scopus and Pubmed were reviewed in this work. We conclude that analyzing breath metabolites (both volatile and nonvolatile) is valuable in disease diagnoses, and therefore believe that breathomics will turn into a promising noninvasive discipline in biomarker discovery and early disease detection in personalized medicine. The problem of wide variations in the reported metabolite concentrations from breathomics studies should be tackled by developing more accurate analytical methods and sophisticated numerical analytical alogorithms.

Calculated indices of volatile organic compounds (VOCs) in exhalation for lung cancer screening and early detection

BACKGROUND

Breath analysis is a promising noninvasive technique that offers a wide range of opportunities to facilitate early diagnosis of lung cancer (LC).

METHOD

Exhaled breath samples of 352 subjects including 160 with lung cancer (LC), 70 with benign pulmonary nodule (BPN) and 122 healthy controls (HC) were analyzed through thermal desorption coupled with gas chromatography-mass spectrometry (TD-GC-MS) to obtain the metabolic information from volatile organic compounds (VOCs). Statistical classification models were used to find diagnostic clusters of VOCs for the discrimination of HC, BPN and LC patients' early and advanced stages, as well as subtypes of LC. Receiver operator characteristics (ROC) curves with 5-fold validations were used to evaluate the accuracy of these models.

RESULTS

The analysis revealed that 20, 19, 19, and 20 VOCs discriminated LC from HC, LC from BPN, histology and LC stages respectively. The calculated diagnostic indices showed a large area under the curve (AUC) to distinguish HC from LC (AUC: 0.987, 95 % confidence interval (CI): 0.976-0.997), BPN from LC (AUC: 0.809, 95 % CI: 0.758-0.860), NSCLC from SCLC (AUC: 0.939, 95 % CI: 0.875-0.995) and Stage III from stage III-IV (AUC: 0.827, 95 % CI: 0.768-0.886). The comparison between the high-risk groups (BPN and HC smokers) and early stages LC resulted in the AUC of 0.756 (95 %CI: 0.681-0.817) for BPN vs. early stage LC and AUC of 0.986 (95 % CI: 0.972-0.994) for HC smoker vs. early stage LC.

CONCLUSION

Volatome of breath of the LC patients was significantly different from that of both BPN patients and HC and showed an ability of distinguishing early from advance stage LC and NSCLC from SCLC. We conclude that the volatome has a potential to help improve early diagnosis of LC.

Occupational exposure to graphene and silica nanoparticles. Part II: pilot study to identify a panel of sensitive biomarkers of genotoxic, oxidative and inflammatory effects on suitable biological matrices

The available biomonitoring studies on workers producing/handling nanomaterials (NMs) focused on potential effects on respiratory, immune and cardio-vascular system. Aim of this study was to identify a panel of sensitive biomarkers and suitable biological matrices to evaluate particularly genotoxic and oxidative effects induced on workers unintentionally exposed to graphene or silica nanoparticles during the production process. These nanomaterials have been chosen for 'NanoKey' project, integrating the workplace exposure assessment (reported in part I) with the biomonitoring of exposed workers reported in the present work. Simultaneously to workplace exposure characterization, we monitored the workers using: Buccal Micronucleus Cytome (BMCyt) assay, fpg-comet test (lymphocytes), oxidized DNA bases 8-oxoGua, 8-oxoGuo and 8-oxodGuo measurements (urine), analysis of oxidative stress biomarkers in exhaled breath condensate (EBC), FENO measurement and cytokines release detection (serum). Since buccal cells are among the main targets of NM occupational exposure, particular attention was posed to the BMCyt assay that represents a noninvasive assay. This pilot study, performed on 12 workers vs.11 controls, demonstrates that BMCyt and fpg-comet assays are the most sensitive biomarkers of early, still reparable, genotoxic and oxidative effects. The findings suggest that these biomarkers could represent useful tools for the biomonitoring of workers exposed to nanoparticles, but they need to be confirmed on a high number of subjects. However, such biomarkers don't discriminate the effects of NM from those due to other chemicals used in the NM production process. Therefore, they could be suitable for the biomonitoring of workers exposed to complex scenario, including nanoparticles exposure.

Non-Invasive Diagnosis of Malignancies Based on the Analysis of Markers in Exhaled Air

Novel non-invasive methods for the diagnosis of malignancies should be effective for early diagnosis, reproducible, inexpensive, and independent from the human factor. Our aim was to establish the applicability of the non-invasive method, based on the analysis of air exhaled by patients who are at different stages of oropharyngeal, larynx and lung cancer. The diagnostic device includes semiconductor sensors capable of measuring the concentrations of gas components in exhaled air, with the high sensitivity of 1 ppm. The neural network uses signals from these sensors to perform classification and identify cancer patients. Prior to the diagnostic procedure of the non-invasive method, we clarified the extent and stage of the tumor according to current international standards and recommendations for the diagnosis of malignancies. The statistical dataset for neural network training and method validation included samples from 121 patients with the most common tumor localizations (lungs, oropharyngeal region and larynx). The largest number of cases (21 patients) were lung cancer, while the number of patients with oropharyngeal or laryngeal cancer varied from 1 to 9, depending on tumor localization (oropharyngeal, tongue, oral cavity, larynx and mucosa of the lower jaw). In the case of lung cancer, the parameters of the diagnostic device are determined as follows: sensitivity—95.24%, specificity—76.19%. For oropharyngeal cancer and laryngeal cancer, these parameters were 67.74% and 87.1%, respectively. This non-invasive method could lead to relevant medicinal findings and provide an opportunity for clinical utility and patient benefit upon early diagnosis of malignancies.

Target Analysis of Volatile Organic Compounds in Exhaled Breath for Lung Cancer Discrimination from Other Pulmonary Diseases and Healthy Persons

The aim of the present study was to investigate the ability of breath analysis to distinguish lung cancer (LC) patients from patients with other respiratory diseases and healthy people. The population sample consisted of 51 patients with confirmed LC, 38 patients with pathological computed tomography (CT) findings not diagnosed with LC, and 53 healthy controls. The concentrations of 19 volatile organic compounds (VOCs) were quantified in the exhaled breath of study participants by solid phase microextraction (SPME) of the VOCs and subsequent gas chromatography-mass spectrometry (GC-MS) analysis. Kruskal-Wallis and Mann-Whitney tests were used to identify significant differences between subgroups. Machine learning methods were used to determine the discriminant power of the method. Several compounds were found to differ significantly between LC patients and healthy controls. Strong associations were identified for 2-propanol, 1-propanol, toluene, ethylbenzene, and styrene (p-values < 0.001-0.006). These associations remained significant when ambient air concentrations were subtracted from breath concentrations. VOC levels were found to be affected by ambient air concentrations and a few by smoking status. The random forest machine learning algorithm achieved a correct classification of patients of 88.5% (area under the curve-AUC 0.94). However, none of the methods used achieved adequate discrimination between LC patients and patients with abnormal computed tomography (CT) findings. Biomarker sets, consisting mainly of the exogenous monoaromatic compounds and 1- and 2- propanol, adequately discriminated LC patients from healthy controls. The breath concentrations of these compounds may reflect the alterations in patient's physiological and biochemical status and perhaps can be used as probes for the investigation of these statuses or normalization of patient-related factors in breath analysis.

Comet Test in Saliva Leukocytes of Pre-School Children Exposed to Air Pollution in North Italy: The Respira Study

Air pollution is a well-known problem for human health, especially for children living in highly polluted urban areas. This study aimed to assess the relationship between airborne pollutants concentration and biomarkers of DNA damage in the buccal mucosa cells of pre-school children. DNA damage was investigated with comet test in saliva leukocytes taken from sputum of 3- to 6-year-old children living in Brescia, Northern Italy, collected during two consecutive winter seasons (2012-2013). The daily levels of PM10, PM2.5, NO2, CO, SO2, benzene and O3 in urban air were collected for the whole period. A questionnaire filled in by the children's parents was used to evaluate indoor and outdoor exposure. DNA damage in saliva leukocytes was evaluated in 152 children and the means of tail intensity and visual score as DNA damage were 6.2 ± 4.3 and 182.1 ± 30.9, respectively. No demographic and indoor or outdoor exposure variable was associated with the two measures of DNA damage. No significant association between air pollution and DNA damage in children's buccal leukocytes was found. In this study, the comet assay does not appear to be a valuable biomarker to detect DNA damage in children exposed to high levels of air pollutants, such as PM10, PM2.5 and NO2.

Improving lung cancer diagnosis by combining exhaled-breath data and clinical parameters

Introduction

Exhaled-breath analysis of volatile organic compounds could detect lung cancer earlier, possibly leading to improved outcomes. Combining exhaled-breath data with clinical parameters may improve lung cancer diagnosis.

Methods

Based on data from a previous multi-centre study, this article reports additional analyses. 138 subjects with non-small cell lung cancer (NSCLC) and 143 controls without NSCLC breathed into the Aeonose. The diagnostic accuracy, presented as area under the receiver operating characteristic curve (AUC-ROC), of the Aeonose itself was compared with 1) performing a multivariate logistic regression analysis of the distinct clinical parameters obtained, and 2) using this clinical information beforehand in the training process of the artificial neural network (ANN) for the breath analysis.

Results

NSCLC patients (mean±sd age 67.1±9.1 years, 58% male) were compared with controls (62.1±7.0 years, 40.6% male). The AUC-ROC of the classification value of the Aeonose itself was 0.75 (95% CI 0.69–0.81). Adding age, number of pack-years and presence of COPD to this value in a multivariate regression analysis resulted in an improved performance with an AUC-ROC of 0.86 (95% CI 0.81–0.90). Adding these clinical variables beforehand to the ANN for classifying the breath print also led to an improved performance with an AUC-ROC of 0.84 (95% CI 0.79–0.89).

Conclusions

Adding readily available clinical information to the classification value of exhaled-breath analysis with the Aeonose, either post hoc in a multivariate regression analysis or a priori to the ANN, significantly improves the diagnostic accuracy to detect the presence or absence of lung cancer.

Adding readily available clinical information to the classification value of exhaled-breath analysis with the Aeonose significantly improves the diagnostic accuracy to detect the presence or absence of lung cancerhttp://bit.ly/38ps6fH

Comparison of breath sampling methods: a post hoc analysis from observational cohort studies

In this report, we present a post hoc analysis from two observational cohorts, comparing the global breath volatile profile captured when using polymer sampling bags (mixed breath) versus Bio-VOC™ (alveolar breath). The cohorts were originally designed to characterize the breath volatile profiles of Malawian children with and without uncomplicated falciparum malaria. Children aged 3-15 years were recruited from ambulatory pediatric centers in Lilongwe, Malawi. Breath sampling was carried out two months apart (one study using a Bio-VOC™ and the second using sampling bags), and all samples were analyzed by gas chromatography/mass spectrometry. The efficacy of breath collection was assessed by quantifying levels of two high prevalence breath compounds, acetone and isoprene, as well as determining the overall number of breath compounds collected and their abundance. We found that the mean number of volatiles detected using sampling bags was substantially higher than when using the Bio-VOC™ (137 vs. 47). Breath collection by Bio-VOC™ also yielded reduced levels of endogenous breath volatiles, isoprene and acetone, even after breath volume correction. This suggests that the Bio-VOC™ dilutes the volatiles and introduces dead air or ambient air. Our results suggest that sampling bags are better suited for biomarker discovery and untargeted search of volatiles in pediatric populations, as evidenced by superior breath volatile detection.

Critical Review of Volatile Organic Compound Analysis in Breath and In Vitro Cell Culture for Detection of Lung Cancer

Breath analysis is a promising technique for lung cancer screening. Despite the rapid development of breathomics in the last four decades, no consistent, robust, and validated volatile organic compound (VOC) signature for lung cancer has been identified. This review summarizes the identified VOC biomarkers from both exhaled breath analysis and in vitro cultured lung cell lines. Both clinical and in vitro studies have produced inconsistent, and even contradictory, results. Methodological issues that lead to these inconsistencies are reviewed and discussed in detail. Recommendations on addressing specific issues for more accurate biomarker studies have also been made.

Accuracy and Methodologic Challenges of Volatile Organic Compound-Based Exhaled Breath Tests for Cancer Diagnosis: A Systematic Review and Meta-analysis

Importance

The detection and quantification of volatile organic compounds (VOCs) within exhaled breath have evolved gradually for the diagnosis of cancer. The overall diagnostic accuracy of proposed tests remains unknown.

Objectives

To determine the diagnostic accuracy of VOC breath tests for the detection of cancer and to review sources of methodologic variability.

Data Sources

An electronic search (title and abstract) was performed using the Embase and MEDLINE databases (January 1, 2000, to May 28, 2017) through the OVID platform. The search terms cancer, neoplasm, malignancy, volatile organic compound, VOC, breath, and exhaled were used in combination with the Boolean operators AND and OR. A separate MEDLINE search that used the search terms breath AND methodology was also performed for studies that reported factors that influenced the concentration of VOCs within exhaled breath in humans.

Study Selection

The search was limited to human studies published in the English language. Trials that analyzed named endogenous VOCs within exhaled breath to diagnose or assess cancer were included in this review.

Data Extraction and Synthesis

Systematic review and pooled analysis were conducted in accordance with the recommendations of the Cochrane Library and Meta-analysis of Observational Studies in Epidemiology guidelines. Bivariate meta-analyses were performed to generate pooled point estimates of the hierarchal summary receiver operating characteristic curve of breath VOC analysis. Included studies were assessed according to the Standards for Reporting of Diagnostic Accuracy Studies checklist and Quality Assessment of Diagnostic Accuracy Studies 2 tool.

Main Outcomes and Measures

The principal outcome measure was pooled diagnostic accuracy of published VOC breath tests for cancer.

Results

The review identified 63 relevant publications and 3554 patients. All reports constituted phase 1 biomarker studies. Pooled analysis of findings found a mean (SE) area under the receiver operating characteristic analysis curve of 0.94 (0.01), sensitivity of 79% (95% CI, 77%-81%), and specificity of 89% (95% CI, 88%-90%). Factors that may influence variability in test results included breath collection method, patient physiologic condition, test environment, and method of analysis.

Conclusions and Relevance

The findings of our review suggest that standardization of breath collection methods and masked validation of breath test accuracy for cancer diagnosis is needed among the intended population in multicenter clinical trials. We propose a framework to guide the conduct of future breath tests in cancer studies.

Breath based volatile organic compounds in the detection of breast, lung, and colorectal cancers: A systematic review

BACKGROUND

Detecting volatile organic compounds (VOCs) could provide a rapid, noninvasive, and inexpensive screening tool for detecting cancer.

OBJECTIVE

In this systematic review, we identified specific exhaled breath VOCs correlated with lung, colorectal, and breast cancer.

METHODS

We identified relevant studies published in 2015 and 2016 by searching Pubmed and Web of Science. The protocol for this systematic review was registered in PROSPERO and the PRISMA guidelines were used in reporting. VOCs and performance data were extracted.

RESULTS

Three hundred and thirty three records were identified and 43 papers were included in the review, of which 20 were review articles themselves. We identified 17 studies that listed the VOCs with at least a subset of statistics on detection cutoff levels, sensitivity, specificity, area under the receiver operating characteristic curve (AUC), and gradient.

CONCLUSIONS

Breath analysis for cancer screening and early detection shows promise, because samples can be collected easily, safely, and frequently. While gas chromatography-mass spectrometry is considered the gold standard for identifying specific VOCs, breath analysis has moved into analyzing patterns of VOCs using a variety of different multiple sensor techniques, such as eNoses and nanomaterials. Further development of VOCs for early cancer detection requires clinical trials with standardized breath sampling methods.

Detection of volatile organic compounds in exhaled breath to screen lung cancer: a systematic review

To evaluate the clinical value of volatile organic compounds (VOCs) in exhaled breath for lung cancer (LC) screening, a systematic review was performed. Systematic search for studies about exhaled VOCs for LC screening was conducted according to PRISMA. Thirty eight studies with 4873 participants met the criteria for inclusion in this systematic review. Generally speaking, the results suggest that exhaled VOCs have potential to screen LC and more studies are needed in the future.

Detection of Lung Cancer: Concomitant Volatile Organic Compounds and Metabolomic Profiling of Six Cancer Cell Lines of Different Histological Origins

In recent years, there has been an extensive search for a non-invasive screening technique for early detection of lung cancer. Volatile organic compound (VOC) analysis in exhaled breath is one such promising technique. This approach is based on the fact that tumor growth is accompanied by unique oncogenesis, leading to detectable changes in VOC emitting profile. Here, we conducted a comprehensive profiling of VOCs and metabolites from six different lung cancer cell lines and one normal lung cell line using mass spectrometry. The concomitant VOCs and metabolite profiling allowed significant discrimination between lung cancer and normal cell, nonsmall cell lung cancer (NSCLC) and small cell lung cancer (SCLC), as well as between different subtypes of NSCLC. It was found that a combination of benzaldehyde, 2-ethylhexanol, and 2,4-decadien-1-ol could serve as potential volatile biomarkers for lung cancer. A detailed correlation between nonvolatile metabolites and VOCs can demonstrate possible biochemical pathways for VOC production by the cancer cells, thus enabling further optimization of VOCs as biomarkers. These findings could eventually lead to noninvasive early detection of lung cancer and differential diagnosis of lung cancer subtypes, thus revolutionizing lung cancer treatment.

Exhaled breath analysis: a review of 'breath-taking' methods for off-line analysis

BACKGROUND

The potential of exhaled breath sampling and analysis has long attracted interest in the areas of medical diagnosis and disease monitoring. This interest is attributed to its non-invasive nature, access to an unlimited sample supply (i.e., breath), and the potential to facilitate a rapid at patient diagnosis. However, progress from laboratory setting to routine clinical practice has been slow. Different methodologies of breath sampling, and the consequent difficulty in comparing and combining data, are considered to be a major contributor to this. To fulfil the potential of breath analysis within clinical and pre-clinical medicine, standardisation of some approaches to breath sampling and analysis will be beneficial.

OBJECTIVES

The aim of this review is to investigate the heterogeneity of breath sampling methods by performing an in depth bibliometric search to identify the current state of art in the area. In addition, the review will discuss and critique various breath sampling methods for off-line breath analysis.

METHODS

Literature search was carried out in databases MEDLINE, BIOSIS, EMBASE, INSPEC, COMPENDEX, PQSCITECH, and SCISEARCH using the STN platform which delivers peer-reviewed articles. Keywords searched for include breath, sampling, collection, pre-concentration, volatile. Forward and reverse search was then performed on initially included articles. The breath collection methodologies of all included articles was subsequently reviewed.

RESULTS

Sampling methods differs between research groups, for example regarding the portion of breath being targeted. Definition of late expiratory breath varies between studies.

CONCLUSIONS

Breath analysis is an interdisciplinary field of study using clinical, analytical chemistry, data processing, and metabolomics expertise. A move towards standardisation in breath sampling is currently being promoted within the breath research community with a view to harmonising analysis and thereby increasing robustness and inter-laboratory comparisons.

Real-time ultrasensitive VUV-PIMS detection of representative endogenous volatile markers in cancers

BACKGROUND

Identifying endogenous volatile organic compounds (VOCs) as markers for different cancers currently requires time-consuming procedures and specialized operators.

OBJECTIVE

The objective of this study was to develop a rapid and simple method for measuring VOCs at trace levels.

METHODS

A simple vacuum ultraviolet photoionization mass spectrometer (VUV-PIMS) was used to detect trace levels of dimethyl trisulfide (DMTS), dimethyl sulfide (DMS), and 2-butanone, which correspond to volatile biomarker candidates present in the exhaled breath of patients with breast, liver, and lung cancers, respectively. The practicality of measuring endogenous VOCs using VUV-PIMS was confirmed by detecting them in cultured cell lines.

RESULTS

The abovementioned VOCs were detected with high sensitivity by VUV-PIMS. The limits of detection (LODs) for DMTS, DMS, and 2-butanone were 3.1, 3.9, and 23.2 pptv, respectively, under ambient conditions, which surpass the sensitivity of nearly all other MS-based techniques. Moreover, relatively high concentrations of 2-butanone and DMS were observed in VOCs emitted from the A549 lung cancer cell line and the HepG2 liver cancer cell line, respectively.

CONCLUSIONS

Our results show that VUV-PIMS may serve as a reliable method for real-time measurement of endogenous volatile cancer biomarkers.

Recent analytical approaches to detect exhaled breath ammonia with special reference to renal patients

The ammonia odor from the exhaled breath of renal patients is associated with high levels of blood urea nitrogen. Typically, in the liver, ammonia and ammonium ions are converted into urea through the urea cycle. In the case of renal dysfunction, urea is unable to be removed and that causes a buildup of excessive ammonia. As small molecules, ammonia and ammonium ions can be forced into the blood-lung barrier and occur in exhaled breath. Therefore, people with renal failure have an ammonia (fishy) odor in their exhaled breath. Thus, exhaled breath ammonia can be a potential biomarker for monitoring renal diseases during hemodialyis. In this review, we have summarized the source of ammonia in the breath of end-stage renal disease patient, cause of renal disorders, exhaled breath condensate, and breath sampling. Further, various biosensor approaches to detect exhaled ammonia from renal patients and other ammonia systems are also discussed. We conclude with future perspectives, namely colorimetric-based real-time breathing diagnosis of renal failure, which might be useful for prospective studies.

Noninvasive detection of gastric cancer

Gastric cancer (GC) is the fifth most common cancer and the third common cause of cancer death worldwide. Endoscopy is the most effective method for GC screening, but its application is limited by the invasion. Therefore, continuous efforts have been made to develop noninvasive methods for GC detection and promising results have been reported. Here, we review the advances in GC detection by protein and nucleic acid tumor markers, circulating tumor cells, and tumor-associated autoantibodies in peripheral blood. Some potential new noninvasive methods for GC detection are also reviewed, including exhaled breath analysis, blood spectroscopy analysis and molecular imaging.

Electronic Noses for Well-Being: Breath Analysis and Energy Expenditure

The wealth of information concealed in a single human breath has been of interest for many years, promising not only disease detection, but also the monitoring of our general well-being. Recent developments in the fields of nano-sensor arrays and MEMS have enabled once bulky artificial olfactory sensor systems, or so-called "electronic noses", to become smaller, lower power and portable devices. At the same time, wearable health monitoring devices are now available, although reliable breath sensing equipment is somewhat missing from the market of physical, rather than chemical sensor gadgets. In this article, we report on the unprecedented rise in healthcare problems caused by an increasingly overweight population. We first review recently-developed electronic noses for the detection of diseases by the analysis of basic volatile organic compounds (VOCs). Then, we discuss the primary cause of obesity from over eating and the high calorific content of food. We present the need to measure our individual energy expenditure from our exhaled breath. Finally, we consider the future for handheld or wearable devices to measure energy expenditure; and the potential of these devices to revolutionize healthcare, both at home and in hospitals.

Lung Cancer Biomarkers

Lung cancer is the most frequently occurring cancer in the world and continually leads in mortality among cancers. The overall 5-year survival rate for lung cancer has risen only 4% (from 12% to 16%) over the past 4 decades, and late diagnosis is a major obstacle in improving lung cancer prognosis. Survival of patients undergoing lung resection is greater than 80%, suggesting that early detection and diagnosis of cancers before they become inoperable and lethal will greatly improve mortality. Lung cancer biomarkers can be used for screening, detection, diagnosis, prognosis, prediction, stratification, therapy response monitoring, and so on. This review focuses on noninvasive diagnostic and prognostic biomarkers. For that purpose, our discussion in this review will focus on biological fluid-based biomarkers. The body fluids include blood (serum or plasma), sputum, saliva, BAL, pleural effusion, and VOC. Since it is rich in different cellular and molecular elements and is one of the most convenient and routine clinical procedures, serum or plasma is the main source for the development and validation of many noninvasive biomarkers. In terms of molecular aspects, the most widely validated ones are proteins, some of which are used in the clinical sector, though in limited accessory purposes. We will also discuss the lung cancer (protein) biomarkers in clinical trials and currently in the validation phase with hundreds of samples. After proteins, we will discuss microRNAs, methylated DNA, and circulating tumor cells, which are being vigorously developed and validated as potential lung cancer biomarkers. The main aim of this review is to provide researchers and clinicians with an understanding of the potential noninvasive lung cancer biomarkers in biological fluids that have recently been discovered.