Identifying potential breath biomarkers for early diagnosis of papillary thyroid cancer based on solid-phase microextraction gas chromatography-high resolution mass spectrometry with metabolomics

INTRODUCTION

Thyroid cancer incidence rate has increased substantially worldwide in recent years. Fine needle aspiration biopsy (FNAB) is currently the golden standard of thyroid cancer diagnosis, which however, is invasive and costly. In contrast, breath analysis is a non-invasive, safe and simple sampling method combined with a promising metabolomics approach, which is suitable for early cancer diagnosis in high volume population.

OBJECTIVES

This study aims to achieve a more comprehensive and definitive exhaled breath metabolism profile in papillary thyroid cancer patients (PTCs).

METHODS

We studied both end-tidal and mixed expiratory breath, solid-phase microextraction gas chromatography coupled with high resolution mass spectrometry (SPME-GC-HRMS) was used to analyze the breath samples. Multivariate combined univariate analysis was applied to identify potential breath biomarkers.

RESULTS

The biomarkers identified in end-tidal and mixed expiratory breath mainly included alkanes, olefins, enols, enones, esters, aromatic compounds, and fluorine and chlorine containing organic compounds. The area under the curve (AUC) values of combined biomarkers were 0.974 (sensitivity: 96.1%, specificity: 90.2%) and 0.909 (sensitivity: 98.0%, specificity: 74.5%), respectively, for the end-tidal and mixed expiratory breath, indicating of reliability of the sampling and analysis method CONCLUSION: This work not only successfully established a standard metabolomic approach for early diagnosis of PTC, but also revealed the necessity of using both the two breath types for comprehensive analysis of the biomarkers.

Sub-PPB Detection with Gas-Phase Multiphoton Electron Extraction Spectroscopy under Ambient Conditions

Multiphoton electron extraction spectroscopy (MEES) is an advanced analytical technique that has demonstrated exceptional sensitivity and specificity for detecting molecular traces on solid and liquid surfaces. Building upon the solid-state MEES foundations, this study introduces the first application of MEES in the gas phase (gas-phase MEES), specifically designed for quantitative detection of gas traces at sub-part per billion (sub-PPB) concentrations under ambient atmospheric conditions. Our experimental setup utilizes resonant multiphoton ionization processes using ns laser pulses under a high electrical field. The generated photoelectron charges are recorded as a function of the laser's wavelength. This research showcases the high sensitivity of gas-phase MEES, achieving high spectral resolution with resonant peak widths less than 0.02 nm FWHM. We present results from quantitative analysis of benzene and aniline, two industrially and environmentally significant compounds, demonstrating linear responses in the sub-PPM and sub-PPB ranges. The enhanced sensitivity and resolution of gas-phase MEES offer a powerful approach to trace gas analysis, with potential applications in environmental monitoring, industrial safety, security screening, and medical diagnostics. This study confirms the advantages of gas-phase MEES over many traditional optical spectroscopic methods and demonstrates its potential in direct gas-trace sensing in ambient atmosphere.

Breath biopsy, a novel technology to identify head and neck squamous cell carcinoma: A systematic review

Head and neck cancers are a heterogeneous group of neoplasms, which together comprise the sixth most common cancer globally. Breath biopsies are a non-invasive clinical investigation that detect volatile organic compounds (VOCs) in exhaled breath. This systematic review examines current applications of breath biopsy for the diagnosis of head and neck squamous cell carcinoma (HNSCC), including data on efficacy and utility, and speculates on the future uses of this non-invasive detection method. Medline, PubMed, Web of Science, Cochrane and Scopus, as well as the grey literature were searched using a search strategy developed to identify relevant studies on the role of breath biopsy in the diagnosis of HNSCC. All included studies were subject to a thorough methodological quality assessment. The initial search generated a total of 1443 articles, 20 of which were eligible for review. A total of 660 HNSCC samples were investigated across the included studies. 3,7-dimethylundecane and benzaldehyde were among several VOCs to be significantly correlated with the presence of HNSCC compared to healthy controls. We show that current breath biopsy methods have high accuracy, specificity and sensitivity for identifying HNSCC. However, further studies are needed given the reported poor quality of the included studies.

Rapid identification and monitoring of cooking oil fume-based toxic volatile organic aldehydes in lung tissue for predicting exposure level and cancer risks

Cooking oil fumes (COFs) comprised of a mixture of cancer-causing volatile organic aldehydes (VOAs), particularly trans, trans-2,4-decadienal (t,t-DDE), 4-hydroxy-hexenal (4-HHE), and 4-hydroxy-nonenal (4-HNE). Monitoring toxic VOAs levels in people exposed to different cooking conditions is vital to predicting the cancer risk. For this purpose, we developed a fast tissue extraction (FaTEx) technique combined with UHPLC-MS/MS to monitor three toxic VOAs in mice lung tissue samples. FaTEx pre-treatment protocol was developed by combining two syringes for extraction and clean-up process. The various procedural steps affecting the FaTEx sample pre-treatment process were optimized to enhance the target VOAs' extraction efficiency from the sample matrix. Under the optimal experimental conditions, results exhibit good correlation coefficient values > 0.99, detection limits were between 0.5-3 ng/g, quantification limits were between 1-10 ng/g, and the matrix effect was <18.1%. Furthermore, the extraction recovery values of the spiked tissue exhibited between 88.9-109.6% with <8.6% of RSD. Cooking oil fume (containing t,t-DDE) treated mice at various time durations were sacrificed to validate the developed technique, and it was found that t,t-DDE concentrations were from 14.8 to 33.8 μg/g. The obtained results were found to be a fast, reliable, and semi-automated sample pre-treatment technique with good extraction efficiency, trace level detection limit, and less matrix effect. Therefore, this method can be applied as a potential analytical method to determine the VOAs in humans exposed to long-term cooking oil fumes.

Nano-biosensor for SARS-CoV-2/COVID-19 detection: methods, mechanism and interface design

The epidemic of coronavirus disease 2019 (COVID-19) was a huge disaster to human society. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which led to COVID-19, has resulted in a large number of deaths. Even though the reverse transcription-polymerase chain reaction (RT-PCR) is the most efficient method for the detection of SARS-CoV-2, the disadvantages (such as long detection time, professional operators, expensive instruments, and laboratory equipment) limit its application. In this review, the different kinds of nano-biosensors based on surface-enhanced Raman scattering (SERS), surface plasmon resonance (SPR), field-effect transistor (FET), fluorescence methods, and electrochemical methods are summarized, starting with a concise description of their sensing mechanism. The different bioprobes (such as ACE2, S protein-antibody, IgG antibody, IgM antibody, and SARS-CoV-2 DNA probes) with different bio-principles are introduced. The key structural components of the biosensors are briefly introduced to give readers an understanding of the principles behind the testing methods. In particular, SARS-CoV-2-related RNA mutation detection and its challenges are also briefly described. We hope that this review will encourage readers with different research backgrounds to design SARS-CoV-2 nano-biosensors with high selectivity and sensitivity.

Non-Invasive Disease Specific Biomarker Detection Using Infrared Spectroscopy: A Review

Many life-threatening diseases remain obscure in their early disease stages. Symptoms appear only at the advanced stage when the survival rate is poor. A non-invasive diagnostic tool may be able to identify disease even at the asymptotic stage and save lives. Volatile metabolites-based diagnostics hold a lot of promise to fulfil this demand. Many experimental techniques are being developed to establish a reliable non-invasive diagnostic tool; however, none of them are yet able to fulfil clinicians' demands. Infrared spectroscopy-based gaseous biofluid analysis demonstrated promising results to fulfil clinicians' expectations. The recent development of the standard operating procedure (SOP), sample measurement, and data analysis techniques for infrared spectroscopy are summarized in this review article. It has also outlined the applicability of infrared spectroscopy to identify the specific biomarkers for diseases such as diabetes, acute gastritis caused by bacterial infection, cerebral palsy, and prostate cancer.

Prognostic Value of UBE2T and Its Correlation with Immune Infiltrates in Lung Adenocarcinoma

Non-small cell lung cancer has a subtype with a high morbidity and mortality rate called lung adenocarcinoma (LUAD). It is critical to locate reliable prognostic biomarkers for LUAD at this time. Ubiquitin-conjugating enzyme E2T (UBE2T) has been found in numerous malignancies; however, its expression level and potential functions in LUAD are not completely understood at this time. A differentially expressed gene (DEG) screening method was used to identify genes that were expressed differently in 516 samples from LUAD and 59 samples from TCGA datasets. Clinicopathological markers were correlated with UBE2T expression. Using the Kaplan–Meier plotter database, UBE2T was evaluated for its prognostic value in the context of LUAD. In order to examine the importance of independent prognostic factors, both univariable and multivariable Cox regression models were applied. TIMER and CIBERSORT were utilized in order to investigate the connection that exists between UBE2T expression and tumor-infiltrating immune cells. This study collected 578 DEGs in total, as follows: 171 genes were significantly increased, while 408 genes were significantly decreased. We identified 9 survival-related DEGs in LUAD, including ASF1B, CA9, CCNB2, CCNE1, RRM2, SAPCD2, TCN1, TPX2, and UBE2T. Our attention focused on UBE2T, which was highly expressed in LUAD. A correlation was also found between high UBE2T expression and gender, age, advanced clinical stage, and decreased overall survival. In addition, multivariate analysis demonstrated UBE2T expression to be a significant independent diagnostic factor for patients suffering from LUAD. UBE2T was positively correlated with resting T cell CD4+ memory, myeloid dendritic cell resting, mast cell activated, macrophage M2, and B cell plasma, whereas it was negatively correlated with resting T cell CD4+ memory, MDC resting, MDC activated, macrophage M2, and B cell plasma. Overall, high expression levels of UBE2T correlated with poor overall survival in patients with LUAD, and UBE2T was an independent predictor involved in immune infiltration of LUAD. These findings offer fresh perspectives that contribute to our comprehension of the evolution of LUAD.

Smartphone-Based Platforms for Clinical Detections in Lung-Cancer-Related Exhaled Breath Biomarkers: A Review

Lung cancer has been studied for decades because of its high morbidity and high mortality. Traditional methods involving bronchoscopy and needle biopsy are invasive and expensive, which makes patients suffer more risks and costs. Various noninvasive lung cancer markers, such as medical imaging indices, volatile organic compounds (VOCs), and exhaled breath condensates (EBCs), have been discovered for application in screening, diagnosis, and prognosis. However, the detection of markers still relies on bulky and professional instruments, which are limited to training personnel or laboratories. This seriously hinders population screening for early diagnosis of lung cancer. Advanced smartphones integrated with powerful applications can provide easy operation and real-time monitoring for healthcare, which demonstrates tremendous application scenarios in the biomedical analysis region from medical institutions or laboratories to personalized medicine. In this review, we propose an overview of lung-cancer-related noninvasive markers from exhaled breath, focusing on the novel development of smartphone-based platforms for the detection of these biomarkers. Lastly, we discuss the current limitations and potential solutions.

Effect of household air pollutants on the composition of exhaled breath characterized by solid-phase microextraction and needle-trap devices

Exposure to household air pollutants is becoming a serious environmental health risk. Various methods can be applied to assess humans' exposure status to indoor pollutants, with breath monitoring being among the best options. Breath sampling is fast and non-invasive, and contains compounds that can be used as markers for evaluating exposure length and estimating internal concentrations of pollutants. However, the distribution of compounds between gas and droplets in breath samples represents one of the key challenges associated with this analytical method. In this work, a needle-trap device (NTD) was prepared by packing the needle with a porous filter, divinyl benzene, and Carboxen to enable the exhaustive capture of both droplet-bound and gaseous components. Furthermore, fiber-based solid-phase microextraction (SPME) was also applied to extract compounds from only the gas phase to distinguish this portion of analytes from the total concentration in the sample. Dynamic, real-time breath sampling was enabled via a new sampling tube equipped with 2 one-way valves, which was specially designed for this work. Both methods provided satisfactory reproducibility, repeatability, and sensitivity, with detection limits as low as 0.05 ng mL^-1. To investigate the real-world applicability of the proposed devices, breath samples were obtained from volunteers who had been exposed to candle and incense smoke and aerosol sprays, or had smoked cannabis. The results revealed the high concentration of organic air pollutants in inhaled air (maximum of 215 ng mL^-1) and exhaled breath (maximum of 14.4 ng mL^-1) and a correlation between the components in inhaled air and exhaled breath. Significantly, the findings further revealed that the developed NTD has enhanced breath-sample determinations, especially for polar compounds, which tend to remain trapped in breath droplets.

Nematode-Applied Technology for Human Tumor Microenvironment Research and Development

Nematodes, such as Caenorhabditis elegans, have been instrumental to the study of cancer. Recently, their significance as powerful cancer biodiagnostic tools has emerged, but also for mechanism analysis and drug discovery. It is expected that nematode-applied technology will facilitate research and development on the human tumor microenvironment. In the history of cancer research, which has been spurred by numerous discoveries since the last century, nematodes have been important model organisms for the discovery of cancer microenvironment. First, microRNAs (miRNAs), which are noncoding small RNAs that exert various functions to control cell differentiation, were first discovered in C. elegans and have been actively incorporated into cancer research, especially in the study of cancer genome defects. Second, the excellent sense of smell of nematodes has been applied to the diagnosis of diseases, especially refractory tumors, such as human pancreatic cancer, by sensing complex volatile compounds derived from heterogeneous cancer microenvironment, which are difficult to analyze using ordinary analytical methods. Third, a nematode model system can help evaluate invadosomes, the phenomenon of cell invasion by direct observation, which has provided a new direction for cancer research by contributing to the elucidation of complex cell–cell communications. In this cutting-edge review, we highlight milestones in cancer research history and, from a unique viewpoint, focus on recent information on the contributions of nematodes in cancer research towards precision medicine in humans.

Volatile compounds in human breath: critical review and meta-analysis

Volatile compounds contained in human breath reflect the inner workings of the body. A large number of studies have been published that link individual components of breath to disease, but diagnostic applications remain limited, in part due to inconsistent and conflicting identification of breath biomarkers. New approaches are therefore required to identify effective biomarker targets. Here, volatile organic compounds have been identified in the literature from four metabolically and physiologically distinct diseases and grouped into chemical functional groups (e.g. - methylated hydrocarbons or aldehydes; based on known metabolic and enzymatic pathways) to support biomarker discovery and provide new insight on existing data. Using this functional grouping approach, principal component analysis doubled explanatory capacity from 19.1% to 38% relative to single individual compound approaches. Random forest and linear discriminant analysis reveal 93% classification accuracy for cancer. This review and meta-analysis provides insight for future research design by identifying volatile functional groups associated with disease. By incorporating our understanding of the complexities of the human body, along with accounting for variability in methodological and analytical approaches, this work demonstrates that a suite of targeted, functional volatile biomarkers, rather than individual biomarker compounds, will improve accuracy and success in diagnostic research and application.

Pumilio RNA Binding Family Member 2 Promotes the Proliferation and Metastasis of Lung Cancer Cells by Regulating Ca2+ Signaling Pathway via Targeting C-X-C Chemokine Receptor Type 4

The aim of the present study was to investigate the mechanism by which pumilio RNA binding family member 2 (PUM2), an RNA-binding protein (RBP) of C-X-C chemokine receptor type 4 (CXCR4), exerts its effects on the development of lung cancer. RT-qPCR and western blot analysis were utilized to measure the expression of PUM2 in several lung cancer cell lines. Cell Counting Kit-8 (CCK-8), colony formation assay, transwell- and wound healing assays were employed to determine the proliferation, invasion and migration of NCI-H520 cells, respectively. Next, the expression of CXCR4 was measured using western blot analysis, and the combination between PUM2 and CXCR4 was verified by RNA immunoprecipitation (RIP) assay and RNA pull down assay. Finally, whether the expression of PUM2 can affect the Ca2+ signaling pathway was confirmed by western blot assay. Results revealed that the expression level of PUM2 was notably upregulated in lung cancer cells, and knockdown of PUM2 significantly inhibited the proliferation, invasion and migration of NCI-H520 cells. PUM2 was confirmed to be the RBP of CXCR4, and PUM2 knockdown decreased the expression of CXCR4. In addition, PUM2 silencing inhibited the phosphorylation of CaMKII, ERK, and MEK. Taken together, these findings demonstrated that PUM2 could promote the proliferation and metastasis of lung cancer cells by regulating Ca2+ signaling pathway via targeting CXCR4, which may provide a novel insight for the future treatment of lung cancer.

The investigation of the volatile metabolites of lung cancer from the microenvironment of malignant pleural effusion

For malignant pleural effusions, pleural fluid cytology is a diagnostic method, but sensitivity is low. The pleural fluid contains metabolites directly released from cancer cells. The objective of this study was to diagnose lung cancer with malignant pleural effusion using the volatilomic profiling method. We recruited lung cancer patients with malignant pleural effusion and patients with nonmalignant diseases with pleural effusion as controls. We analyzed the headspace air of the pleural effusion by gas chromatography-mass spectrometry. We used partial least squares discriminant analysis (PLS-DA) to identify metabolites and the support vector machine (SVM) to establish the prediction model. We split data into a training set (80%) and a testing set (20%) to validate the accuracy. A total of 68 subjects were included in the final analysis. The PLS-DA showed high discrimination with an R² of 0.95 and Q² of 0.58. The accuracy of the SVM in the test set was 0.93 (95% CI 0.66, 0.998), the sensitivity was 83%, the specificity was 100%, and kappa was 0.85, and the area under the receiver operating characteristic curve was 0.96 (95% CI 0.86, 1.00). Volatile metabolites of pleural effusion might be used in patients with cytology-negative pleural effusion to rule out malignancy.

Relationship between Lung Carcinogenesis and Chronic Inflammation in Rodents

Simple Summary

Lung cancer is the most common cause of cancer-related deaths worldwide. There are various risk factors for lung cancer, including tobacco smoking, inhalation of dust particles, chronic inflammation, and genetic factors. Chronic inflammation has been considered a key factor that promotes tumor progression via production of cytokines, chemokines, cytotoxic mediators, and reactive oxygen species by inflammatory cells. Here, we review rodent models of lung tumor induced by tobacco, tobacco-related products, and pro-inflammatory materials as well as genetic modifications, and discuss the relationship between chronic inflammation and lung tumor. Through this review, we hope to clarify the effects of chronic inflammation on lung carcinogenesis and help develop new treatments for lung cancer.

Abstract

Lung cancer remains the leading cause of cancer-related deaths, with an estimated 1.76 million deaths reported in 2018. Numerous studies have focused on the prevention and treatment of lung cancer using rodent models. Various chemicals, including tobacco-derived agents induce lung cancer and pre-cancerous lesions in rodents. In recent years, transgenic engineered rodents, in particular, those generated with a focus on the well-known gene mutations in human lung cancer (KRAS, EGFR, and p53 mutations) have been widely studied. Animal studies have revealed that chronic inflammation significantly enhances lung carcinogenesis, and inhibition of inflammation suppresses cancer progression. Moreover, the reduction in tumor size by suppression of inflammation in animal experiments suggests that chronic inflammation influences the promotion of tumorigenesis. Here, we review rodent lung tumor models induced by various chemical carcinogens, including tobacco-related carcinogens, and transgenics, and discuss the roles of chronic inflammation in lung carcinogenesis.

Breathomics for the clinician: the use of volatile organic compounds in respiratory diseases

Exhaled breath analysis has the potential to provide valuable insight on the status of various metabolic pathways taking place in the lungs locally and other vital organs, via systemic circulation. For years, volatile organic compounds (VOCs) have been proposed as feasible alternative diagnostic and prognostic biomarkers for different respiratory pathologies.We reviewed the currently published literature on the discovery of exhaled breath VOCs and their utilisation in various respiratory diseasesKey barriers in the development of clinical breath tests include the lack of unified consensus for breath collection and analysis and the complexity of understanding the relationship between the exhaled VOCs and the underlying metabolic pathways. We present a comprehensive overview, in light of published literature and our experience from coordinating a national breathomics centre, of the progress made to date and some of the key challenges in the field and ways to overcome them. We particularly focus on the relevance of breathomics to clinicians and the valuable insights it adds to diagnostics and disease monitoring.Breathomics holds great promise and our findings merit further large-scale multicentre diagnostic studies using standardised protocols to help position this novel technology at the centre of respiratory disease diagnostics.

Volatile Organic Compound Vapour Measurements Using a Localised Surface Plasmon Resonance Optical Fibre Sensor Decorated with a Metal-Organic Framework

A tip-based fibreoptic localised surface plasmon resonance (LSPR) sensor is reported for the sensing of volatile organic compounds (VOCs). The sensor is developed by coating the tip of a multi-mode optical fibre with gold nanoparticles (size: 40 nm) via a chemisorption process and further functionalisation with the HKUST-1 metal–organic framework (MOF) via a layer-by-layer process. Sensors coated with different cycles of MOFs (40, 80 and 120) corresponding to different crystallisation processes are reported. There is no measurable response to all tested volatile organic compounds (acetone, ethanol and methanol) in the sensor with 40 coating cycles. However, sensors with 80 and 120 coating cycles show a significant redshift of resonance wavelength (up to ~9 nm) to all tested volatile organic compounds as a result of an increase in the local refractive index induced by VOC capture into the HKUST-1 thin film. Sensors gradually saturate as VOC concentration increases (up to 3.41%, 4.30% and 6.18% in acetone, ethanol and methanol measurement, respectively) and show a fully reversible response when the concentration decreases. The sensor with the thickest film exhibits slightly higher sensitivity than the sensor with a thinner film. The sensitivity of the 120-cycle-coated MOF sensor is 13.7 nm/% (R² = 0.951) with a limit of detection (LoD) of 0.005% in the measurement of acetone, 15.5 nm/% (R² = 0.996) with an LoD of 0.003% in the measurement of ethanol and 6.7 nm/% (R² = 0.998) with an LoD of 0.011% in the measurement of methanol. The response and recovery times were calculated as 9.35 and 3.85 min for acetone; 5.35 and 2.12 min for ethanol; and 2.39 and 1.44 min for methanol. The humidity and temperature crosstalk of 120-cycle-coated MOF was measured as 0.5 ± 0.2 nm and 0.5 ± 0.1 nm in the humidity range of 50–75% relative humidity (RH) and temperature range of 20–25 °C, respectively.

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.

High performance exhaled breath biomarkers for diagnosis of lung cancer and potential biomarkers for classification of lung cancer

Exhaled breath analysis has emerged as a promising non-invasive method for diagnosing lung cancer (LC), whereas reliable biomarkers are lacking. Herein, a standardized and systematic study was presented for LC diagnosis, classification and metabolism exploration. To improve the reliability of biomarkers, a validation group was included, and quality control for breath sampling and analysis, comprehensive pollutants analysis, and strict biomarker screening were performed. The performance of exhaled breath biomarkers was shown to be excellent in diagnosing LC even in early stages (stage I and II) with surpassing 0.930 area under the receiver operating characteristic (ROC) curve (AUC), 90% of sensitivity and 88% of specificity both in the discovery and validation analyses. Meanwhile, in these two groups, diagnosing subtypes of LC attained AUCs over 0.930 and reached 1.00 in the two subtypes of adenocarcinomas. It is demonstrated that the metabolism changes in LC are possibly related to lipid oxidation, gut microbial, cytochrome P450 and glutathione S-transferase, and glutathione pathways change in LC progression. Overall, the reliable biomarkers contribute to the clinical application of breath analysis in screening LC patients as well as those in early stages.

Recent Progress in Graphene Derivatives/Metal Oxides Binary Nanocomposites Based Chemi-resistive Sensors for Disease Diagnosis by Breath Analysis

Background::

The scientific and clinical interest of breath analysis for non-invasive disease diagnosis has been focused by the scientific community over the past decade. This was due to the exhalation of prominent volatile organic compounds (VOCs) corresponding to the metabolic activities in the body and their concentration variation. To identify these biomarkers, various analytical techniques have been used in the past and the threshold concentration was established between a healthy and diseased state. Subsequently, various nanomaterials-based gas sensors were explored for their demand in quantifying these biomarkers for real-time, low cost and portable breathalyzers along with the essential sensor performances.

Methods::

We focus on the classification of graphene derivatives and their composites’ gas sensing efficiency for the application in the development of breathalyzers. The review begins with the feasibility of the application of nanomaterial gas sensors for healthcare applications. Then, we systematically report the gas sensing performance of various graphene derivatives/semiconductor metal oxides (SMO) binary nanocomposites and their optimizing strategies in selective detection of biomarkers specific to diseases. Finally, we provide insights on the challenges, opportunity and future research directions for the development of breathalyzers using other graphene derivatives/SMO binary nanocomposites.

Results::

On the basis of these analyses, graphene and its derivatives/metal oxides based binary nanocomposites have been a choice for gas sensing material owing to their high electrical conductivity and extraordinary thickness-dependent physicochemical properties. Moreover, the presence of oxygen vacancies in SMO does not only alter the conductivity but also accelerates the carrier transport rate and influence the adsorption behavior of target analyte on the sensing materials. Hence researchers are exploring the search of ultrathin graphene and metal oxide counterpart for high sensing performances.

Conclusion::

Their impressive properties compared to their bulk counterpart have been uncovered towards sensitive and selective detection of biomarkers for its use in portable breathalyzers.

Volatile organic compounds in human matrices as lung cancer biomarkers: a systematic review

Volatile organic compounds (VOCs) have shown potential as non-invasive breath biomarkers for lung cancer, but their unclear biological origin currently limits clinical applications. This systematic review explores headspace analysis of VOCs in patient-derived body fluids and lung cancer cell lines to pinpoint lung cancer-specific VOCs and uncover their biological origin. A search was performed in the databases MEDLINE and Web of Science. Twenty-two articles were included in this systematic review. Since there is no standardised approach to analyse VOCs, a plethora of techniques and matrices/cell lines were explored, which is reflected in the various VOCs identified. However, comparing VOCs in the headspace of urine, blood and pleural effusions from patients and lung cancer cell lines showed some overlapping VOCs, indicating their potential use in lung cancer diagnosis. This review demonstrates that VOCs are promising biomarkers for lung cancer. However, due to lack of inter-matrix consensus, standardised prospective trials will have to be conducted to validate clinically relevant biomarkers.

Volatile compounds released by Nalophan; implications for selected ion flow tube mass spectrometry and other chemical ionisation mass spectrometry analytical methods

Nalophan bags are commonly used to collect breath samples for volatile metabolite analysis. Volatile organic compounds (VOCs) released from the polymer can, however, be mistaken as breath metabolites when analyses are performed by selected ion flow tube mass spectrometry, SIFT-MS, or techniques that depend on a proper understanding of ion chemistry.

METHODS

Three analytical techniques were used to analyse the VOCs released into the nitrogen used to expand Nalophan bags, viz. gas chromatography/mass spectrometry (GC/MS), secondary electrospray ionization mass spectrometry (SESI-MS) and selected ion flow tube mass spectrometry (SIFT-MS). The most significant VOCs were identified and quantified by SIFT-MS as a function of storage time, temperature and humidity.

RESULTS

The consistent results obtained by these three analytical methods identify 1,2-ethanediol (ethylene glycol) and 2-methyl-1,3-dioxolane as the major VOCs released by the Nalophan. Their concentrations are enhanced by increasing the bag storage temperature and time, reaching 170 parts-per-billion by volume (ppbv) for ethylene glycol and 34 ppbv for 2-methyl-1,3-dioxolane in humid nitrogen (absolute humidity of 5%) contained in an 8-L Nalophan bag stored at 37°C for 160 min.

CONCLUSIONS

Using H₃ O⁺ reagent ions for SIFT-MS and SESI-MS analyses, the following analyte ions (m/z values) are affected by the Nalophan impurities: 45, 63, 81, 89 and 99, which can compromise analyses of acetaldehyde, ethylene glycol, monoterpenes, acetoin, butyric acid, hexanal and heptane.

Two-step investigation of lung cancer detection by sniffer dogs

Early detection of lung cancer (LC) is a priority since LC is characterized by symptoms mimicking other respiratory conditions, but it remains the leading cause of oncological disease death. Properly trained dogs can perceive the volatile organic compounds (VOCs) related to cancer thanks to their acute sense of smell. The use of dogs for LC detection could be advantageous: reliably trained dogs would represent a valuable, cost-effective, non-invasive method of screening, which gives a clear-cut yes/no response. However, whether sniffer dogs are able to maintain their discriminative capacity under long-term control, and in different types of environments, needs further investigation. In this study, we sought to test two hypotheses: firstly, if dogs can be trained to perceive LC-related VOCs in human urine, a substrate which is not influenced by the carrier materials and may thus be a good candidate for large-number screening; and secondly, whether trained dogs retain their performance stability over time, even if the environment in which the tests are carried out varies. We have selected three family dogs that underwent a one-year training period (two weekly training sessions) by the clicker training method. At the end of the training, the dogs underwent two separate test phases, in two different locations, one year apart. All the other procedures had been maintained unchanged. The donors of the samples submitted to the dogs were recruited by the European Institute of Oncology (IEO), Milan, Italy. The results show that the dogs had different sensitivity (range: 45%-73%) and specificity rates (range: 89%-91%), and were deceived neither by lung conditions (that the dogs did not consider) nor by the existence of tumors in the beginning stage, that were correctly reported by the dogs. The one-year interruption of the research work and the changes in the test environment did not induce statistically significant differences in the dogs' perceptive capacity. To our knowledge, so far, these issues have never been highlighted.

Online breath analysis using metal oxide semiconductor sensors (electronic nose) for diagnosis of lung cancer

The analysis of exhaled breath is drawing a high degree of interest in the diagnostics of various diseases, including lung cancer. Electronic nose (E-nose) technology is one of the perspective approaches in the field due to its relative simplicity and cost efficiency. The use of an E-nose together with pattern recognition algorithms allow 'breath-prints' to be discriminated. The aim of this study was to develop an efficient online E-nose-based lung cancer diagnostic method via exhaled breath analysis with the use of some statistical classification methods. A developed multisensory system consisting of six metal oxide chemoresistance gas sensors was employed in three temperature regimes. This study involved 118 individuals: 65 in the lung cancer group (cytologically verified) and 53 in the healthy control group. The exhaled breath samples of the volunteers were analysed using the developed E-nose system. The dataset obtained, consisting of the sensor responses, was pre-processed and split into training (70%) and test (30%) subsets. The training data was used to fit the classification models; the test data was used for the estimation of prediction possibility. Logistic regression was found to be an adequate data-processing approach. The performance of the developed method was promising for the screening purposes (sensitivity-95.0%, specificity-100.0%, accuracy-97.2%). This shows the applicability of the gas-sensitive sensor array for the exhaled breath diagnostics. Metal oxide sensors are highly sensitive, low-cost and stable, and their poor sensitivity can be enhanced by integrating them with machine learning algorithms, as can be seen in this study. All experiments were carried out with the permission of the N.N. Petrov Research Institute of Oncology ethics committee no. 15/83 dated March 15, 2017.

Sensors for detecting pulmonary diseases from exhaled breath

This review presents and discusses a new frontier for fast, risk-free and potentially inexpensive diagnostics of respiratory diseases by detecting volatile organic compounds (VOCs) present in exhaled breath. One part of the review is a didactic presentation of the overlaying concept and the chemistry of exhaled breath. The other part discusses diverse sensors that have been developed and used for the detection of respiratory diseases (e.g. chronic obstructive pulmonary disease, asthma, lung cancer, pulmonary arterial hypertension, tuberculosis, cystic fibrosis, obstructive sleep apnoea syndrome and pneumoconiosis) by analysis of VOCs in exhaled breath. The strengths and pitfalls are discussed and criticised, particularly in the perspective in disseminating information regarding these advances. Ideas regarding the improvement of sensors, sensor arrays, sensing devices and the further planning of workflow are also discussed.

Detection of volatile organic compounds from exhaled breath by nanomaterial-based sensors is a new diagnostics frontier in the screening of pulmonary diseases.http://bit.ly/2JoBKXn

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.

A Study of Diagnostic Accuracy Using a Chemical Sensor Array and a Machine Learning Technique to Detect Lung Cancer

Lung cancer is the leading cause of cancer death around the world, and lung cancer screening remains challenging. This study aimed to develop a breath test for the detection of lung cancer using a chemical sensor array and a machine learning technique. We conducted a prospective study to enroll lung cancer cases and non-tumour controls between 2016 and 2018 and analysed alveolar air samples using carbon nanotube sensor arrays. A total of 117 cases and 199 controls were enrolled in the study of which 72 subjects were excluded due to having cancer at another site, benign lung tumours, metastatic lung cancer, carcinoma in situ, minimally invasive adenocarcinoma, received chemotherapy or other diseases. Subjects enrolled in 2016 and 2017 were used for the model derivation and internal validation. The model was externally validated in subjects recruited in 2018. The diagnostic accuracy was assessed using the pathological reports as the reference standard. In the external validation, the areas under the receiver operating characteristic curve (AUCs) were 0.91 (95% CI = 0.79–1.00) by linear discriminant analysis and 0.90 (95% CI = 0.80–0.99) by the supportive vector machine technique. The combination of the sensor array technique and machine learning can detect lung cancer with high accuracy.

Synergy between nanomaterials and volatile organic compounds for non-invasive medical evaluation

This article is an overview of the present and ongoing developments in the field of nanomaterial-based sensors for enabling fast, relatively inexpensive and minimally (or non-) invasive diagnostics of health conditions with follow-up by detecting volatile organic compounds (VOCs) excreted from one or combination of human body fluids and tissues (e.g., blood, urine, breath, skin). Part of the review provides a didactic examination of the concepts and approaches related to emerging sensing materials and transduction techniques linked with the VOC-based non-invasive medical evaluations. We also present and discuss diverse characteristics of these innovative sensors, such as their mode of operation, sensitivity, selectivity and response time, as well as the major approaches proposed for enhancing their ability as hybrid sensors to afford multidimensional sensing and information-based sensing. The other parts of the review give an updated compilation of the past and currently available VOC-based sensors for disease diagnostics. This compilation summarizes all VOCs identified in relation to sickness and sampling origin that links these data with advanced nanomaterial-based sensing technologies. Both strength and pitfalls are discussed and criticized, particularly from the perspective of the information and communication era. Further ideas regarding improvement of sensors, sensor arrays, sensing devices and the proposed workflow are also included.

Real-world volatile organic compound emission rates from seated adults and children for use in indoor air studies

Human beings emit many volatile organic compounds (VOCs) of both endogenous (internally produced) and exogenous (external source) origin. Here we present real-world emission rates of volatile organic compounds from cinema audiences (50-230 people) as a function of time in multiple screenings of three films. The cinema location and film selection allowed high-frequency measurement of human-emitted VOCs within a room flushed at a known rate so that emissions rates could be calculated for both adults and children. Gas-phase emission rates are analyzed as a function of time of day, variability during the film, and age of viewer. The average emission rates of CO₂ , acetone, and isoprene were lower (by a factor of ~1.2-1.4) for children under twelve compared to adults while for acetaldehyde emission rates were equivalent. Molecules influenced by exogenous sources such as decamethylcyclopentasiloxanes and methanol tended to decrease over the course of day and then rise for late evening screenings. These results represent average emission rates of people under real-world conditions and can be used in indoor air quality assessments and building design. Averaging over a large number of people generates emission rates that are less susceptible to individual behaviors.

A Prediction Model with a Combination of Variables for Diagnosis of Lung Cancer

Background

Multivariate models with a combination of variables can predict disease more accurately than a single variable employed alone. We developed a logistic regression model with a combination of variables and evaluated its ability to predict lung cancer.

Material/Methods

The exhaled breath from 57 patients with lung cancer and 72 healthy controls without cancer was collected. The VOCs of exhaled breath were examined qualitatively and quantitatively by a novel electronic nose (Z-nose4200 equipment). The VOCs in the 2 groups were compared using the Mann-Whitney U test, and the baseline data were compared between the 2 groups using the chi-square test or ANOVA. Variables from VOCs and baseline data were selected by stepwise logistic regression and subjected to a prediction model for the diagnosis of lung cancer as combined factors. The receiver operating characteristic (ROC) curve was used to evaluate the predictive ability of this prediction model.

Results

Nine VOCs in exhaled breath of lung cancer patients differed significantly from those of healthy controls. Four variables – age, hexane, 2,2,4,6,6-pentamethylheptane, and 1,2,6-trimethylnaphthalene – were entered into the prediction model, which could effectively separate the lung cancer samples from the control samples with an accuracy of 82.8%, a sensitivity of 76.0%, and a specificity of 94.0%.

Conclusions

The profile of VOCs in exhaled breath contained distinguishable biomarkers in the patients with lung cancers. The prediction model with 4 variables appears to provide a new technique for lung cancer detection.

Exhaled Breath Markers for Nonimaging and Noninvasive Measures for Detection of Multiple Sclerosis

Multiple sclerosis (MS) is the most common chronic neurological disease affecting young adults. MS diagnosis is based on clinical characteristics and confirmed by examination of the cerebrospinal fluids (CSF) or by magnetic resonance imaging (MRI) of the brain or spinal cord or both. However, neither of the current diagnostic procedures are adequate as a routine tool to determine disease state. Thus, diagnostic biomarkers are needed. In the current study, a novel approach that could meet these expectations is presented. The approach is based on noninvasive analysis of volatile organic compounds (VOCs) in breath. Exhaled breath was collected from 204 participants, 146 MS and 58 healthy control individuals. Analysis was performed by gas-chromatography mass-spectrometry (GC-MS) and nanomaterial-based sensor array. Predictive models were derived from the sensors, using artificial neural networks (ANNs). GC-MS analysis revealed significant differences in VOC abundance between MS patients and controls. Sensor data analysis on training sets was able to discriminate in binary comparisons between MS patients and controls with accuracies up to 90%. Blinded sets showed 95% positive predictive value (PPV) between MS-remission and control, 100% sensitivity with 100% negative predictive value (NPV) between MS not-treated (NT) and control, and 86% NPV between relapse and control. Possible links between VOC biomarkers and the MS pathogenesis were established. Preliminary results suggest the applicability of a new nanotechnology-based method for MS diagnostics.

Association of Smoking with Metabolic Volatile Organic Compounds in Exhaled Breath

Lung cancer (LC) screening will be more efficient if it is applied to a well-defined high-risk population. Characteristics including metabolic byproducts may be taken into account to access LC risk more precisely. Breath examination provides a non-invasive method to monitor metabolic byproducts. However, the association between volatile organic compounds (VOCs) in exhaled breath and LC risk or LC risk factors is not studied. Exhaled breath samples from 122 healthy persons, who were given routine annual exam from December 2015 to December 2016, were analyzed using thermal desorption coupled with gas chromatography mass spectrometry (TD-GC-MS). Smoking characteristics, air quality, and other risk factors for lung cancer were collected. Univariate and multivariate analyses were used to evaluate the relationship between VOCs and LC risk factors. 7, 7, 11, and 27 VOCs were correlated with smoking status, smoking intensity, years of smoking, and depth of inhalation, respectively. Exhaled VOCs are related to smoking and might have a potential to evaluate LC risk more precisely. Both an assessment of temporal stability and testing in a prospective study are needed to establish the performance of VOCs such as 2,5-dimethylfuranm and 4-methyloctane as lung cancer risk biomarkers.

The five commandments of efficient and effective care in the initial evaluation of lung cancer

PURPOSE OF REVIEW

Multiple recent studies have found an astounding lack of concordance with national guidelines in the workup of lung cancer in both community and academic settings. The resultant increase in complications and delays may potentially contribute to the overall dismal outcomes, as well as cost. This article aims to increase awareness among clinicians about the scope of this problem, and provides a simplified primer on the core concepts of how to perform an efficient and effective workup that is in-line with national guidelines.

RECENT FINDINGS

Although the basic principles underlying lung cancer evaluation have not changed in the last decade, there are new areas of debate which are outlined and discussed in this article. These include: the value of brain and bone imaging in asymptomatic patients, the best initial site to biopsy in the era of genomics, and the use of biomarkers with low-dose chest tomography screening.

SUMMARY

Given the huge stakes in lung cancer, the current national quality gap in initial evaluation is unacceptable. However, physician re-education can change this. This article provides a quick review of how to properly evaluate a patient with potential lung cancer, as well as an update on new and continuing controversies in the field.

Analytical methodologies for broad metabolite coverage of exhaled breath condensate

Breath analysis has been gaining popularity as a non-invasive technique that is amenable to a broad range of medical uses. One of the persistent problems hampering the wide application of the breath analysis method is measurement variability of metabolite abundances stemming from differences in both sampling and analysis methodologies used in various studies. Mass spectrometry has been a method of choice for comprehensive metabolomic analysis. For the first time in the present study, we juxtapose the most commonly employed mass spectrometry-based analysis methodologies and directly compare the resultant coverages of detected compounds in exhaled breath condensate in order to guide methodology choices for exhaled breath condensate analysis studies. Four methods were explored to broaden the range of measured compounds across both the volatile and non-volatile domain. Liquid phase sampling with polyacrylate Solid-Phase MicroExtraction fiber, liquid phase extraction with a polydimethylsiloxane patch, and headspace sampling using Carboxen/Polydimethylsiloxane Solid-Phase MicroExtraction (SPME) followed by gas chromatography mass spectrometry were tested for the analysis of volatile fraction. Hydrophilic interaction liquid chromatography and reversed-phase chromatography high performance liquid chromatography mass spectrometry were used for analysis of non-volatile fraction. We found that liquid phase breath condensate extraction was notably superior compared to headspace extraction and differences in employed sorbents manifested altered metabolite coverages. The most pronounced effect was substantially enhanced metabolite capture for larger, higher-boiling compounds using polyacrylate SPME liquid phase sampling. The analysis of the non-volatile fraction of breath condensate by hydrophilic and reverse phase high performance liquid chromatography mass spectrometry indicated orthogonal metabolite coverage by these chromatography modes. We found that the metabolite coverage could be enhanced significantly with the use of organic solvent as a device rinse after breath sampling to collect the non-aqueous fraction as opposed to neat breath condensate sample. Here, we show the detected ranges of compounds in each case and provide a practical guide for methodology selection for optimal detection of specific compounds.

A preliminary analysis of volatile metabolites of human induced pluripotent stem cells along the in vitro differentiation

Cellular metabolism of stem cell biology is still an unexplored field. However, considering the amount of information carried by metabolomes, this is a promising field for a fast identification of stem cells itself and during the differentiation process. One of the goals of such application is the identification of residual pluripotent cells before cell transplantation to avoid the occurrence of teratomas. In this paper, we investigated in vitro the volatile compounds (VOCs) released during human induced pluripotent stem cells (hiPSCs) reprogramming. In particular, we studied hiPSCs differentiation to floating and adherent embryoid bodies until early neural progenitor cells. A preliminary Gas Chromatographic/Mass Spectrometer (GC/MS) analysis, based on a single extraction method and chromatographic separation, indicated 17 volatile compounds whose relative abundance is altered in each step of the differentiation process. The pattern of VOCs shown by hiPSCs is well distinct and makes these cells sharply separated from the other steps of differentiations. Similar behaviour has also been observed with an array of metalloporphyrins based gas sensors. The use of electronic sensors to control the process of differentiation of pluripotent stem cells might suggest a novel perspective for a fast and on-line control of differentiation processes.

Clinical analysis on 113 patients with lung cancer treated by percutaneous CT-guided microwave ablation

BACKGROUND

Lung Cancer is a primary tumor with poor prognosis. For early stage lung cancer, treatment options include surgical resection and microwave techniques. Percutaneous ablative techniques emerged as best therapeutic options for nonsurgical patients.

METHODS

The aim of this study was to retrospectively analyze the clinical effect of CT-guided microwave ablation (MWA) treatment for patients with lung cancer who were not eligible for surgical resection. MWA was used to treat the tumor lesion of 113 patients with lung cancer who were in our hospital from Jan, 2013 to Jun, 2015. The median diameter of tumors was 3.1 cm (0.7-6 cm). Follow-up were paid to all the patients who received MWA therapy. The average follow-up was 22.1±8.6 months, and the median follow-up was 18 (7-40) months.

RESULTS

All of 113 cases of patients with lung cancer experienced MWA therapy, and their tumors were found to have vacuolization, lower density and much smaller distinct shrinkage of tumor size with varying degrees. The local progression rate or relapse rate of the whole group was 15.9%. The counterpart of patients in the early-stage group was 5.7% (2/35), and the diameter of tumors in the two patients was more than 3 cm. The local progression rate or relapse rate of patients in advanced-stage group was 20.5%, wherein, 81.3% of local progression or relapse occurred to the patients with a tumorous diameter of more than 3 cm. The results indicated that the patients in advanced-stage group were vulnerable to local progression or relapse, the tumorous with greater diameter had higher incidence of local relapse. No mortality occurred within 30 days after surgery, the survival rate of patients in early-stage group at first, second, third year was respectively 97.1%, 94.1% and 84.7%. The counterpart of patients in advanced-stage group was respectively 93.6%, 87.7% and 71.7%. The difference of survival rate between both groups was not statistically significant (P=0.576). No perioperative deaths occurred, and the main complications i.e., fever, pneumothorax, pleural effusion, hemoptysis, pneumonia, and pain were slight and tolerable.

CONCLUSIONS

MWA is an effective, safe and minimally invasive treatment for the patients with lung cancer who cannot be tolerated by surgical resection.

Volatolomics of breath as an emerging frontier in pulmonary arterial hypertension

There is accumulating evidence in support of the significant improvement in survival rates and clinical outcomes when pulmonary arterial hypertension (PAH) is diagnosed at early stages. Nevertheless, it remains a major clinical challenge and the outcomes are dependent on invasive right heart catheterisation.

Resulting from pathophysiological processes and detectable in exhaled breath, volatile organic compounds (VOCs) have been proposed as noninvasive biomarkers for PAH. Studies have confirmed significant alterations of the exhaled VOCs among PAH patients when compared to controls and/or patients with other respiratory diseases. This suggests exhaled breath analysis as a potential noninvasive medical application in the field of PAH.

In this article, we review and discuss the progress made so far in the field of exhaled volatolomics (the omics of VOCs) as a potential noninvasive diagnostics of PAH. In addition, we propose a model including possible biochemical pathways on the level of the remodelled artery, in which specific VOCs could be detectable in exhaled breath during the early phases of PAH. We debate the different analytical approaches used and recommend a diagram including a “bottom–top” strategy, from basic to translational studies, required for promoting the field.

A Compendium of Volatile Organic Compounds (VOCs) Released By Human Cell Lines

Volatile organic compounds (VOCs) offer unique insights into ongoing biochemical processes in healthy and diseased humans. Yet, their diagnostic use is hampered by the limited understanding of their biochemical or cellular origin and their frequently unclear link to the underlying diseases. Major advancements are expected from the analyses of human primary cells, cell lines and cultures of microorganisms. In this review, a database of 125 reliably identified VOCs previously reported for human healthy and diseased cells was assembled and their potential origin is discussed. The majority of them have also been observed in studies with other human matrices (breath, urine, saliva, feces, blood, skin emanations). Moreover, continuing improvements of qualitative and quantitative analyses, based on the recommendations of the ISO-11843 guidelines, are suggested for the necessary standardization of analytical procedures and better comparability of results. The data provided contribute to arriving at a more complete human volatilome and suggest potential volatile biomarkers for future validation.

Dedication: This review is dedicated to the memory of Prof. Dr. Anton Amann, who sadly passed away on January 6, 2015. He was motivator and motor for the field of breath research.

Diagnosis and Classification of 17 Diseases from 1404 Subjects via Pattern Analysis of Exhaled Molecules

We report on an artificially intelligent nanoarray based on molecularly modified gold nanoparticles and a random network of single-walled carbon nanotubes for noninvasive diagnosis and classification of a number of diseases from exhaled breath. The performance of this artificially intelligent nanoarray was clinically assessed on breath samples collected from 1404 subjects having one of 17 different disease conditions included in the study or having no evidence of any disease (healthy controls). Blind experiments showed that 86% accuracy could be achieved with the artificially intelligent nanoarray, allowing both detection and discrimination between the different disease conditions examined. Analysis of the artificially intelligent nanoarray also showed that each disease has its own unique breathprint, and that the presence of one disease would not screen out others. Cluster analysis showed a reasonable classification power of diseases from the same categories. The effect of confounding clinical and environmental factors on the performance of the nanoarray did not significantly alter the obtained results. The diagnosis and classification power of the nanoarray was also validated by an independent analytical technique, i.e., gas chromatography linked with mass spectrometry. This analysis found that 13 exhaled chemical species, called volatile organic compounds, are associated with certain diseases, and the composition of this assembly of volatile organic compounds differs from one disease to another. Overall, these findings could contribute to one of the most important criteria for successful health intervention in the modern era, viz. easy-to-use, inexpensive (affordable), and miniaturized tools that could also be used for personalized screening, diagnosis, and follow-up of a number of diseases, which can clearly be extended by further development.

From blood to breath: New horizons for esophageal cancer biomarkers

Esophageal cancer is a lethal cancer encompassing adenocarcinoma and squamous cell carcinoma sub-types. The global incidence of esophageal cancer is increasing world-wide, associated with the increased prevalence of associated risk factors. The asymptomatic nature of disease often leads to late diagnosis and five-year survival rates of less than 15%. Current diagnostic tools are restricted to invasive and costly endoscopy and biopsy for histopathology. Minimally and non-invasive biomarkers of esophageal cancer are needed to facilitate earlier detection and better clinical management of patients. This paper summarises recent insights into the development and clinical validation of esophageal cancer biomarkers, focussing on circulating markers in the blood, and the emerging area of breath and odorant biomarkers.

Significance of Exhaled Breath Test in Clinical Diagnosis: A Special Focus on the Detection of Diabetes Mellitus

Analysis of volatile organic compounds (VOCs) emanating from human exhaled breath can provide deep insight into the status of various biochemical processes in the human body. VOCs can serve as potential biomarkers of physiological and pathophysiological conditions related to several diseases. Breath VOC analysis, a noninvasive and quick biomonitoring approach, also has potential for the early detection and progress monitoring of several diseases. This paper gives an overview of the major VOCs present in human exhaled breath, possible biochemical pathways of breath VOC generation, diagnostic importance of their analysis, and analytical techniques used in the breath test. Breath analysis relating to diabetes mellitus and its characteristic breath biomarkers is focused on. Finally, some challenges and limitations of the breath test are discussed.

Canine scent detection for the diagnosis of lung cancer in a screening-like situation

The prognosis in lung cancer depends largely on early stage detection, and thus new screening methods are attracting increasing attention. Canine scent detection has shown promising results in lung cancer detection, but there has only been one previous study that reproduces a screening-like situation. Here breath samples were collected from 122 patients at risk for lung cancer (smokers and ex-smokers); 29 of the subjects had confirmed diagnosis of lung cancer but had not yet been treated and 93 subjects had no signs or symptoms of lung cancer at the time of inclusion. The breath samples were presented to a trained sniffer dog squadron in a double-blind manner. A rigid scientific protocol was used with respect to earlier canine scent detection studies, with one difference: instead of offering one in five positive samples to the dogs, we offered a random number of positive samples (zero to five). The final positive and negative predictive values of 30.9% and 84.0%, respectively, were rather low compared to other studies. The results differed from those of previous studies, indicating that canine scent detection might not be as powerful as is looked for in real screening situations. One main reason for the rather poor performance in our setting might be the higher stress from the lack of positive responses for dogs and handlers.

High-Resolution p-Type Metal Oxide Semiconductor Nanowire Array as an Ultrasensitive Sensor for Volatile Organic Compounds

The development of high-performance volatile organic compound (VOC) sensor based on a p-type metal oxide semiconductor (MOS) is one of the important topics in gas sensor research because of its unique sensing characteristics, namely, rapid recovery kinetics, low temperature dependence, high humidity or thermal stability, and high potential for p-n junction applications. Despite intensive efforts made in this area, the applications of such sensors are hindered because of drawbacks related to the low sensitivity and slow response or long recovery time of p-type MOSs. In this study, the VOC sensing performance of a p-type MOS was significantly enhanced by forming a patterned p-type polycrystalline MOS with an ultrathin, high-aspect-ratio (∼25) structure (∼14 nm thickness) composed of ultrasmall grains (∼5 nm size). A high-resolution polycrystalline p-type MOS nanowire array with a grain size of ∼5 nm was fabricated by secondary sputtering via Ar(+) bombardment. Various p-type nanowire arrays of CuO, NiO, and Cr2O3 were easily fabricated by simply changing the sputtering material. The VOC sensor thus fabricated exhibited higher sensitivity (ΔR/Ra = 30 at 1 ppm hexane using NiO channels), as well as faster response or shorter recovery time (∼30 s) than that of previously reported p-type MOS sensors. This result is attributed to the high resolution and small grain size of p-type MOSs, which lead to overlap of fully charged zones; as a result, electrical properties are predominantly determined by surface states. Our new approach may be used as a route for producing high-resolution MOSs with particle sizes of ∼5 nm within a highly ordered, tall nanowire array structure.

Analysis of volatile organic compounds liberated and metabolised by human umbilical vein endothelial cells (HUVEC) in vitro

Gas chromatography with mass spectrometric detection combined with head-space needle trap extraction as the pre-concentration technique was applied to identify and quantify volatile organic compounds released or metabolised by human umbilical vein endothelial cells. Amongst the consumed species there were eight aldehydes (2-methyl 2-propenal, 2-methyl propanal, 2-methyl butanal, 3-methyl butanal, n-hexanal, benzaldehyde, n-octanal and n-nonanal) and n-butyl acetate. Further eight compounds (ethyl acetate, ethyl propanoate, ethyl butyrate, 3-heptanone, 2-octanone, 2-nonanone, 2-methyl-5-(methylthio)-furan and toluene) were found to be emitted by the cells under study. Possible metabolic pathways leading to the uptake and release of these compounds by HUVEC are proposed and discussed. The uptake of aldehydes by endothelial cells questions the reliability of species from this chemical class as breath or blood markers of disease processes in human organism. The analysis of volatiles released or emitted by cell lines is shown to have a potential for the identification and assessment of enzymes activities and expression.