Investigation of potential breath biomarkers for the early diagnosis of breast cancer using gas chromatography–mass spectrometry

Clinical applications of volatilomic assays

The study of metabolomics is revealing immense potential for diagnosis, therapy monitoring, and understanding of pathogenesis processes. Volatilomics is a subcategory of metabolomics interested in the detection of molecules that are small enough to be released in the gas phase. Volatile compounds produced by cellular processes are released into the blood and lymph, and can reach the external environment through different pathways, such as the blood-air interface in the lung that are detected in breath, or the blood-water interface in the kidney that leads to volatile compounds detected in urine. Besides breath and urine, additional sources of volatile compounds such as saliva, blood, feces, and skin are available. Volatilomics traces its roots back over fifty years to the pioneering investigations in the 1970s. Despite extensive research, the field remains in its infancy, hindered by a lack of standardization despite ample experimental evidence. The proliferation of analytical instrumentations, sample preparations and methods of volatilome sampling still make it difficult to compare results from different studies and to establish a common standard approach to volatilomics. This review aims to provide an overview of volatilomics' diagnostic potential, focusing on two key technical aspects: sampling and analysis. Sampling poses a challenge due to the susceptibility of human samples to contamination and confounding factors from various sources like the environment and lifestyle. The discussion then delves into targeted and untargeted approaches in volatilomics. Some case studies are presented to exemplify the results obtained so far. Finally, the review concludes with a discussion on the necessary steps to fully integrate volatilomics into clinical practice.

Identification potential biomarkers for diagnosis, and progress of breast cancer by using high-pressure photon ionization time-of-flight mass spectrometry

BACKGROUND

In this study, exhaled breath testing has been considered a promising method for the detection and monitoring of breast cancer (BC).

METHODS

A high-pressure photon ionization time-of-flight mass spectrometry (HPPI-TOFMS) platform was used to detect volatile organic compounds (VOCs) in breath samples. Then, machine learning (ML) models were constructed on VOCs for the diagnosis of BC and its progression monitoring. Ultimately, 1981 women with useable breath samples were included in the study, of whom 937 (47.3 %) had been diagnosed with BC. VOC panels were used for ML model construction for BC detection and progression monitoring.

RESULTS

On the blinded testing cohort, this VOC-based model successfully differentiated patients with and without BC with sensitivity, specificity, and area under receiver operator characteristic curve (AUC) values of 85.9 %, 90.4 %, and 0.946. The corresponding AUC values when differentiating between patients with and without lymph node metastasis (LNM) or between patients with tumor-node-metastasis (TNM) stage 0/I/II or III/IV disease were 0.840 and 0.708, respectively. While developed VOC-based models exhibited poor performance when attempting to differentiate between patients based on pathological patterns (Ductal carcinoma in situ (DCIS) vs Invasive BC (IBC)) or molecular subtypes (Luminal vs Human epidermal growth factor receptor 2 (HER2+) vs Triple-negative BC (TNBC)) of BC.

CONCLUSION

Collectively, the HPPI-TOFMS-based breathomics approaches may offer value for the detection and progression monitoring of BC. Additional research is necessary to explore the fundamental mechanisms of the identified VOCs.

Facile Preparation of TiO2NTs/Au@MOF Nanocomposites for High-Sensitivity SERS Sensing of Gaseous VOC

Surface-enhanced Raman spectroscopy (SERS) is a promising and highly sensitive molecular fingerprint detection technology. However, the development of SERS nanocomposites that are label-free, highly sensitive, selective, stable, and reusable for gaseous volatile organic compounds (VOCs) detection remains a challenge. Here, we report a novel TiO2NTs/AuNPs@ZIF-8 nanocomposite for the ultrasensitive SERS detection of VOCs. The three-dimensional TiO2 nanotube structure with a large specific surface area provides abundant sites for the loading of Au NPs, which possess excellent local surface plasmon resonance (LSPR) effects, further leading to the formation of a large number of SERS active hotspots. The externally wrapped porous MOF structure adsorbs more gaseous VOC molecules onto the noble metal surface. Under the synergistic mechanism of physical and chemical enhancement, a better SERS enhancement effect can be achieved. By optimizing experimental conditions, the SERS detection limit for acetophenone, a common exhaled VOC, is as low as 10-11 M. And the relative standard deviation of SERS signal intensity from different points on the same nanocomposite surface is 4.7%. The acetophenone gas achieves a 1 min response and the signal reaches stability in 4 min. Under UV irradiation, the surface-adsorbed acetophenone can be completely degraded within 40 min. The experimental results demonstrate that this nanocomposite has good detection sensitivity, repeatability, selectivity, response speed, and reusability, making it a promising sensor for gaseous VOCs.

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.

Potentiality of phosphide-based nanotubes for breast cancer detection: A DFT investigation

Breast cancer is one of the most basilisk cancers for women due to its high mortality rate which can be prevented drastically with early-stage detection. In this work, the adsorption mechanism of two volatile organic compounds that are present in the breath of breast cancer patients, 2-Methyloctane and 3, 3-Dimethylpentane, has been investigated on aluminum phosphide nanotubes (AlPNT) and gallium phosphide nanotubes (GaPNT) in order to understand their feasibility as sensor materials to diagnosis breast cancer at early stage. We have used the quantum mechanical approach by employing density functional theory using B3LYP-D3 hybrid potential for noncovalent interaction along with the LanL2DZ basis in the Gaussian 09 software package. The adsorption properties analyses suggest that GaPNT exhibits better sensing behavior as well as proclaims 12.6% greater adsorption energy for 2-Methyloctane and 9.4% greater adsorption energy for 3, 3-Dimethylpentane than AlPNT. Other structural and electric properties analyses satisfy this conclusion and suggest that GaPNT exhibits higher stability than AlPNT and could possibly be a potential candidate for developing biosensors to detect breast cancer at the preliminary stages.

A multi-omics method for breast cancer diagnosis based on metabolites in exhaled breath, ultrasound imaging, and basic clinical information

Background and aims

Through a nested cohort study, we evaluated the diagnostic performance of breath-omics in differentiating between benign and malignant breast lesions, and assessed the diagnostic performance of a multi-omics approach that combines breath-omics, ultrasound radiomics, and clinic-omics in distinguishing between benign and malignant breast lesions.

Materials and methods

We recruited 1,723 consecutive patients who underwent an automated breast volume scanner (ABVS) examination. Breath samples were collected and analyzed by high-pressure photon ionization time-of-flight mass spectrometry (HPPI-TOF-MS) to obtain breath-omics features. 238 of 1,723 enrolled participants have received pathological confirmation of breast nodules finally. The breast lesions of the 238 participants were contoured manually based on ABVS images for ultrasound radiomics feature calculation. Then, single- and multi-omics models were constructed and evaluated for breast nodules diagnosis via five-fold cross-validation.

Results

The area under the curve (AUC) of the breath-omics model was 0.855. In comparison, the multi-omics model demonstrated superior diagnostic performance for breast cancer, with sensitivity, specificity, and AUC of 84.1 %, 89.9 %, and 0.946, respectively. The multi-omics performance was comparable to that of the Breast Imaging Reporting and Data System (BI-RADS) classification via senior ultrasound physician evaluation.

Conclusion

The multi-omics approach combining metabolites in exhaled breath, ultrasound imaging, and basic clinical information exhibits superior diagnostic performance and promises to be a non-invasive and reliable tool for breast cancer diagnosis.

Fluorescent-based micellar incorporated hydrogel materials for selective determination of long-chain aldehydes

A highly sensitive micelle-induced sensory has been developed for detection of long-chain aldehydes as potential biomarkers of respiratory cancers. The micelle-like sensor was fabricated through the partial self-assembly of CTAB and S2 surfactants, containing a fluorescent hydrazine-functionalized dye (Naph-NH2). In principle, long-chain aldehydes with amphiphilic character act as the induced-fit surfactants to form well-entrapped micellar particles, as well as react with Naph-NH2 to form hydrazone derivatives resulting in fluorescent enhancement. The limit of detection (LOD) of micellar Naph-NH2/CTAB/S2 platform was calculated to be ∼  64.09-80.98 µM for detection of long-chain aldehydes, which showed fluorescent imaging in lung cancer cells (A549). This micellar sensory probe demonstrated practical applicability for long-chain aldehyde sensing in human blood samples with an accepted percent recovery of ~ 94.02-102.4%. Beyond Naph-NH2/CTAB/S2 sensor, the milcellar hybrid sensor was successfully developed by incorporating a micelle-like platform with supramolecular gel regarding to carboxylate-based gelators (Gel1), which showed a tenfold improvement in sensitivity. Expectedly, the determination of long-chain aldehydes through these sensing platforms holds significant promise for point-of-care cancer diagnosis and therapy.

Exhaled breath analyses for bronchial thermoplasty in severe asthma patients

BACKGROUND

Bronchial thermoplasty (BT) is a bronchoscopic treatment for severe asthma. Although multiple trials have demonstrated clinical improvement after BT, optimal patient selection remains a challenge and the mechanism of action is incompletely understood. The aim of this study was to examine whether exhaled breath analysis can contribute to discriminate between BT-responders and non-responders at baseline and to explore pathophysiological insights of BT.

METHODS

Exhaled breath was collected from patients at baseline and six months post-BT. Patients were defined as responders or non-responders based on a half point increase in asthma quality of life questionnaire scores. Gas chromatography-mass spectrometry was used for volatile organic compounds (VOCs) detection and analyses. Analytical workflow consisted of: 1) detection of VOCs that differentiate between responders and non-responders and those that differ between baseline and six months post-BT, 2) identification of VOCs of interest and 3) explore correlations between clinical biomarkers and VOCs.

RESULTS

Data was available from 14 patients. Nonanal, 2-ethylhexanol and 3-thujol showed a significant difference in intensity between responders and non-responders at baseline (p = 0.04, p = 0.01 and p = 0.03, respectively). After BT, no difference was found in the compound intensity of these VOCs. A negative correlation was observed between nonanal and IgE and BALF eosinophils (r = -0.68, p < 0.01 and r = -0.61, p = 0.02 respectively) and 3-thujol with BALF neutrophils (r = -0.54, p = 0.04).

CONCLUSIONS

This explorative study identified discriminative VOCs in exhaled breath between BT responders and non-responders at baseline. Additionally, correlations were found between VOC's and inflammatory BALF cells. Once validated, these findings encourage research in breath analysis as a non-invasive easy to apply technique for identifying airway inflammatory profiles and eligibility for BT or immunotherapies in severe asthma.

Exhaled breath and urinary volatile organic compounds (VOCs) for cancer diagnoses, and microbial-related VOC metabolic pathway analysis: a systematic review and meta-analysis

BACKGROUND

The gradual evolution of the detection and quantification of volatile organic compounds (VOCs) has been instrumental in cancer diagnosis. The primary objective of this study was to assess the diagnostic potential of exhaled breath and urinary VOCs in cancer detection. As VOCs are indicative of tumor and human metabolism, our work also sought to investigate the metabolic pathways linked to the development of cancerous tumors.

MATERIALS AND METHODS

An electronic search was performed in the PubMed database. Original studies on VOCs within exhaled breath and urine for cancer detection with a control group were included. A meta-analysis was conducted using a bivariate model to assess the sensitivity and specificity of the VOCs for cancer detection. Fagan's nomogram was designed to leverage the findings from our diagnostic analysis for the purpose of estimating the likelihood of cancer in patients. Ultimately, MetOrigin was employed to conduct an analysis of the metabolic pathways associated with VOCs in relation to both human and/or microbiota.

RESULTS

The pooled sensitivity, specificity and the area under the curve for cancer screening utilizing exhaled breath and urinary VOCs were determined to be 0.89, 0.88, and 0.95, respectively. A pretest probability of 51% can be considered as the threshold for diagnosing cancers with VOCs. As the estimated pretest probability of cancer exceeds 51%, it becomes more appropriate to emphasize the 'ruling in' approach. Conversely, when the estimated pretest probability of cancer falls below 51%, it is more suitable to emphasize the 'ruling out' approach. A total of 14, 14, 6, and 7 microbiota-related VOCs were identified in relation to lung, colorectal, breast, and liver cancers, respectively. The enrichment analysis of volatile metabolites revealed a significant enrichment of butanoate metabolism in the aforementioned tumor types.

CONCLUSIONS

The analysis of exhaled breath and urinary VOCs showed promise for cancer screening. In addition, the enrichment analysis of volatile metabolites revealed a significant enrichment of butanoate metabolism in four tumor types, namely lung, colorectum, breast and liver. These findings hold significant implications for the prospective clinical application of multiomics correlation in disease management and the exploration of potential therapeutic targets.

A journey from omics to clinicomics in solid cancers: Success stories and challenges

The word 'cancer' encompasses a heterogenous group of distinct disease types characterized by a spectrum of pathological features, genetic alterations and response to therapies. According to the World Health Organization, cancer is the second leading cause of death worldwide, responsible for one in six deaths and hence imposes a significant burden on global healthcare systems. High-throughput omics technologies combined with advanced imaging tools, have revolutionized our ability to interrogate the molecular landscape of tumors and has provided unprecedented understanding of the disease. Yet, there is a gap between basic research discoveries and their translation into clinically meaningful therapies for improving patient care. To bridge this gap, there is a need to analyse the vast amounts of high dimensional datasets from multi-omics platforms. The integration of multi-omics data with clinical information like patient history, histological examination and imaging has led to the novel concept of clinicomics and may expedite the bench-to-bedside transition in cancer. The journey from omics to clinicomics has gained momentum with development of radiomics which involves extracting quantitative features from medical imaging data with the help of deep learning and artificial intelligence (AI) tools. These features capture detailed information about the tumor's shape, texture, intensity, and spatial distribution. Together, the related fields of multiomics, translational bioinformatics, radiomics and clinicomics may provide evidence-based recommendations tailored to the individual cancer patient's molecular profile and clinical characteristics. In this chapter, we summarize multiomics studies in solid cancers with a specific focus on breast cancer. We also review machine learning and AI based algorithms and their use in cancer diagnosis, subtyping, prognosis and predicting treatment resistance and relapse.

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.

Detection technologies of volatile organic compounds in the breath for cancer diagnoses

Although there are new approaches in both cancer treatment and diagnosis, overall mortality is a major concern. New technologies have attempted to look at breath volatile organic compounds (VOCs) detection to diagnose cancer. Gas Chromatography and Mass Spectrometry (GC - MS) have remained the gold standard of VOC analysis for decades, but it has limitations in differentiating VOCs between cancer subtypes. To increase efficacy and accuracy, new methods to analyze these breath VOCs have been introduced, such as Solid Phase Microextraction/Gas Chromatography-Mass Spectrometry (SPME/GC-MS), Selected Ion Flow Tube - Mass Spectrometry (SIFT-MS), Proton Transfer Reaction - Mass Spectrometry (PRT-MS), Ion Mobility Spectrometry (IMS), and Colorimetric Sensors. This article highlights new technologies that have been studied and applied in the detection and quantification of breath VOCs for possible cancer diagnoses.

Global Urinary Volatolomics with (GC×)GC-TOF-MS

Urinary volatolomics offers a noninvasive approach for disease detection and monitoring. Herein we present an improved methodology for global volatolomic profiling. Wide coverage was achieved by utilizing a multiphase sorbent for volatile organic compound (VOC) extraction. A single, midpolar column gas chromatography (GC) assay yielded substantially higher numbers of monitored VOCs compared to our previously reported single-sorbent method. Multidimensional GC (GC×GC) enhanced further biomarker discovery while data analysis was simplified by using a tile-based approach. At the same time, the required urine volume was reduced 5-fold from 2 to 0.4 mL. The applicability of the methodology was demonstrated in a pancreatic ductal adenocarcinoma cohort where previous findings were confirmed while a series of additional VOCs with diagnostic potential were discovered.

Diagnosis of Carcinogenic Pathologies through Breath Biomarkers: Present and Future Trends

The assessment of volatile breath biomarkers has been targeted with a lot of interest by the scientific and medical communities during the past decades due to their suitability for an accurate, painless, non-invasive, and rapid diagnosis of health states and pathological conditions. This paper reviews the most relevant bibliographic sources aiming to gather the most pertinent volatile organic compounds (VOCs) already identified as putative cancer biomarkers. Here, a total of 265 VOCs and the respective bibliographic sources are addressed regarding their scientifically proven suitability to diagnose a total of six carcinogenic diseases, namely lung, breast, gastric, colorectal, prostate, and squamous cell (oesophageal and laryngeal) cancers. In addition, future trends in the identification of five other forms of cancer, such as bladder, liver, ovarian, pancreatic, and thyroid cancer, through perspective volatile breath biomarkers are equally presented and discussed. All the results already achieved in the detection, identification, and quantification of endogenous metabolites produced by all kinds of normal and abnormal processes in the human body denote a promising and auspicious future for this alternative diagnostic tool, whose future passes by the development and employment of newer and more accurate collection and analysis techniques, and the certification for utilisation in real clinical scenarios.

Selectivity of Exhaled Breath Biomarkers of Lung Cancer in Relation to Cancer of Other Localizations

Lung cancer is a leading cause of death worldwide, mostly due to diagnostics in the advanced stage. Therefore, the development of a quick, simple, and non-invasive diagnostic tool to identify cancer is essential. However, the creation of a reliable diagnostic tool is possible only in case of selectivity to other diseases, particularly, cancer of other localizations. This paper is devoted to the study of the variability of exhaled breath samples among patients with lung cancer and cancer of other localizations, such as esophageal, breast, colorectal, kidney, stomach, prostate, cervix, and skin. For this, gas chromatography-mass spectrometry (GC-MS) was used. Two classification models were built. The first model separated patients with lung cancer and cancer of other localizations. The second model classified patients with lung, esophageal, breast, colorectal, and kidney cancer. Mann-Whitney U tests and Kruskal-Wallis H tests were applied to identify differences in investigated groups. Discriminant analysis (DA), gradient-boosted decision trees (GBDT), and artificial neural networks (ANN) were applied to create the models. In the case of classifying lung cancer and cancer of other localizations, average sensitivity and specificity were 68% and 69%, respectively. However, the accuracy of classifying groups of patients with lung, esophageal, breast, colorectal, and kidney cancer was poor.

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.

Odorant-responsive biological receptors and electronic noses for volatile organic compounds with aldehyde for human health and diseases: A perspective review

Volatile organic compounds (VOCs) are gaseous chemicals found in ambient air and exhaled breath. In particular, highly reactive aldehydes are frequently found in polluted air and have been linked to various diseases. Thus, extensive studies have been carried out to elucidate disease-specific aldehydes released from the body to develop potential biomarkers for diagnostic purposes. Mammals possess innate sensory systems, such as receptors and ion channels, to detect these VOCs and maintain physiological homeostasis. Recently, electronic biosensors such as the electronic nose have been developed for disease diagnosis. This review aims to present an overview of natural sensory receptors that can detect reactive aldehydes, as well as electronic noses that have the potential to diagnose certain diseases. In this regard, this review focuses on eight aldehydes that are well-defined as biomarkers in human health and disease. It offers insights into the biological aspects and technological advances in detecting aldehyde-containing VOCs. Therefore, this review will aid in understanding the role of aldehyde-containing VOCs in human health and disease and the technological advances for improved diagnosis.

Smelling the Disease: Diagnostic Potential of Breath Analysis

Breath analysis is a relatively recent field of research with much promise in scientific and clinical studies. Breath contains endogenously produced volatile organic components (VOCs) resulting from metabolites of ingested precursors, gut and air-passage bacteria, environmental contacts, etc. Numerous recent studies have suggested changes in breath composition during the course of many diseases, and breath analysis may lead to the diagnosis of such diseases. Therefore, it is important to identify the disease-specific variations in the concentration of breath to diagnose the diseases. In this review, we explore methods that are used to detect VOCs in laboratory settings, VOC constituents in exhaled air and other body fluids (e.g., sweat, saliva, skin, urine, blood, fecal matter, vaginal secretions, etc.), VOC identification in various diseases, and recently developed electronic (E)-nose-based sensors to detect VOCs. Identifying such VOCs and applying them as disease-specific biomarkers to obtain accurate, reproducible, and fast disease diagnosis could serve as an alternative to traditional invasive diagnosis methods. However, the success of VOC-based identification of diseases is limited to laboratory settings. Large-scale clinical data are warranted for establishing the robustness of disease diagnosis. Also, to identify specific VOCs associated with illness states, extensive clinical trials must be performed using both analytical instruments and electronic noses equipped with stable and precise sensors.

Development of a headspace-solid phase microextraction gas chromatography-high resolution mass spectrometry method for analyzing volatile organic compounds in urine: Application in breast cancer biomarker discovery

BACKGROUND AND AIM

Breast cancer (BC) is the leading cause of cancer-related death in females. The development of non-invasive methods for the early diagnosis of BC still remains challenge. Here, we aimed to discover the urinary volatile organic compounds (VOCs) pattern of BC patients and identify potential VOC biomarkers for BC diagnosis.

METHODS

Urine samples were analyzed by headspace-solid phase microextraction (HS-SPME) combined with gas chromatography-high resolution mass spectrometry (GC-HRMS). To assure reliable analysis, the factors influencing HS-SPME extraction efficiency were comprehensively investigated and optimized by combing the Plackett-Burman design (PBD) with the central composite design (CCD). The established HS-SPME/GC-HRMS method was validated and applied to analyze urine samples from BC patients (n = 80) and healthy controls (n = 88).

RESULTS

A total number of 134 VOCs belonging to distinct chemical classes were identified by GC-HRMS. BC patients demonstrated unique urinary VOCs pattern. Orthogonal partial least squares-discriminant analysis (OPLS-DA) showed a clear separation between BC patients and healthy controls. Eight potential VOC biomarkers were identified using multivariate and univariate statistical analysis. The predictive ability of candidate VOC biomarkers was further investigated by the random forest (RF) algorithm. The candidate VOC biomarkers yielded 76.3% sensitivity and 85.4% specificity on the training set, and achieved 76.0% sensitivity and 92.3% specificity on the validation set.

CONCLUSIONS

Overall, this work not only established a standardized HS-SPME/GC-HRMS approach for urinary VOCs analysis, but also highlighted the value of urinary VOCs for BC diagnosis. The knowledge gained from this study paves the way for early diagnosis of BC using urine in a non-invasive manner.

Potential Role of Oxidative Stress in the Production of Volatile Organic Compounds in Obesity

Obesity is associated with numerous health issues such as sleep disorders, asthma, hepatic dysfunction, cancer, renal dysfunction, diabetes, cardiovascular complications, and infertility. Previous research has shown that the distribution of excess body fat, rather than excess body weight, determines obesity-related risk factors. It is widely accepted that abdominal fat is a serious risk factor for illnesses associated with obesity and the accumulation of visceral fat promotes the release of pro-oxidants, pro-inflammatory, and reactive oxygen species (ROS). The metabolic process in the human body produces several volatile organic compounds (VOCs) via urine, saliva, breath, blood, skin secretions, milk, and feces. Several studies have shown that VOCs are released by the interaction of ROS with underlying cellular components leading to increased protein oxidation, lipid peroxidation, or DNA damage. These VOCs released via oxidative stress in obese individuals may serves as a biomarker for obesity-related metabolic alterations and disease. In this review, we focus on the relationship between oxidative stress and VOCs in obesity.

Harnessing insect olfactory neural circuits for detecting and discriminating human cancers

There is overwhelming evidence that presence of cancer alters cellular metabolic processes, and these changes are manifested in emitted volatile organic compound (VOC) compositions of cancer cells. Here, we take a novel forward engineering approach by developing an insect olfactory neural circuit-based VOC sensor for cancer detection. We obtained oral cancer cell culture VOC-evoked extracellular neural responses from in vivo insect (locust) antennal lobe neurons. We employed biological neural computations of the antennal lobe circuitry for generating spatiotemporal neuronal response templates corresponding to each cell culture VOC mixture, and employed these neuronal templates to distinguish oral cancer cell lines (SAS, Ca9-22, and HSC-3) vs. a non-cancer cell line (HaCaT). Our results demonstrate that three different human oral cancers can be robustly distinguished from each other and from a non-cancer oral cell line. By using high-dimensional population neuronal response analysis and leave-one-trial-out methodology, our approach yielded high classification success for each cell line tested. Our analyses achieved 76-100% success in identifying cell lines by using the population neural response (n = 194) collected for the entire duration of the cell culture study. We also demonstrate this cancer detection technique can distinguish between different types of oral cancers and non-cancer at different time-matched points of growth. This brain-based cancer detection approach is fast as it can differentiate between VOC mixtures within 250 ms of stimulus onset. Our brain-based cancer detection system comprises a novel VOC sensing methodology that incorporates entire biological chemosensory arrays, biological signal transduction, and neuronal computations in a form of a forward-engineered technology for cancer VOC detection.

A Wireless, Regeneratable Cocaine Sensing Scheme Enabled by Allosteric Regulation of pH Sensitive Aptamers

A key challenge for achieving continuous biosensing with existing technologies is the poor reusability of the biorecognition interface due to the difficulty in the dissociation of analytes from the bioreceptors upon surface saturation. In this work, we introduce a regeneratable biosensing scheme enabled by allosteric regulation of a re-engineered pH sensitive anti-cocaine aptamer. The aptamer can regain its affinity with target analytes due to proton-promoted duplex-to-triplex transition in DNA configuration followed by the release of adsorbed analytes. A Pd/PdH_x electrode placed next to the sensor can enable the pH regulation of the local chemical environment via electrochemical reactions. Demonstration of a "flower-shaped", stretchable, and inductively coupled electronic system with sensing and energy harvesting capabilities provides a promising route to designing wireless devices in biointegrated forms. These advances have the potential for future development of electronic sensing platforms with on-chip regeneration capability for continuous, quantitative, and real-time monitoring of chemical and biological markers.

Development and validation of a screening model for lung cancer using machine learning: A large-scale, multi-center study of biomarkers in breath

Objectives

Lung cancer (LC) is the largest single cause of death from cancer worldwide, and the lack of effective screening methods for early detection currently results in unsatisfactory curative treatments. We herein aimed to use breath analysis, a noninvasive and very simple method, to identify and validate biomarkers in breath for the screening of lung cancer.

Materials and methods

We enrolled a total of 2308 participants from two centers for online breath analyses using proton transfer reaction time-of-flight mass spectrometry (PTR-TOF-MS). The derivation cohort included 1007 patients with primary LC and 1036 healthy controls, and the external validation cohort included 158 LC patients and 107 healthy controls. We used eXtreme Gradient Boosting (XGBoost) to create a panel of predictive features and derived a prediction model to identify LC. The optimal number of features was determined by the greatest area under the receiver‐operating characteristic (ROC) curve (AUC).

Results

Six features were defined as a breath-biomarkers panel for the detection of LC. In the training dataset, the model had an AUC of 0.963 (95% CI, 0.941–0.982), and a sensitivity of 87.1% and specificity of 93.5% at a positivity threshold of 0.5. Our model was tested on the independent validation dataset and achieved an AUC of 0.771 (0.718–0.823), and sensitivity of 67.7% and specificity of 73.0%.

Conclusion

Our results suggested that breath analysis may serve as a valid method in screening lung cancer in a borderline population prior to hospital visits. Although our breath-biomarker panel is noninvasive, quick, and simple to use, it will require further calibration and validation in a prospective study within a primary care setting.

Breast cancer detection by analyzing the volatile organic compound (VOC) signature in human urine

A rising number of authors are drawing evidence on the diagnostic capacity of specific volatile organic compounds (VOCs) resulting from some body fluids. While cancer incidence in society is on the rise, it becomes clear that the analysis of these VOCs can yield new strategies to mitigate advanced cancer incidence rates. This paper presents the methodology implemented to test whether a device consisting of an electronic nose inspired by a dog's olfactory system and olfactory neurons is significantly informative to detect breast cancer (BC). To test this device, 90 human urine samples were collected from control subjects and BC patients at a hospital. To test this system, an artificial intelligence-based classification algorithm was developed. The algorithm was firstly trained and tested with data resulting from gas chromatography-mass spectrometry (GC-MS) urine readings, leading to a classification rate of 92.31%, sensitivity of 100.00%, and specificity of 85.71% (N = 90). Secondly, the same algorithm was trained and tested with data obtained with our eNose prototype hardware, and class prediction was achieved with a classification rate of 75%, sensitivity of 100%, and specificity of 50%.

Artificially Intelligent Nanoarray Detects Various Cancers by Liquid Biopsy of Volatile Markers

Cancer is usually not symptomatic in its early stages. However, early detection can vastly improve prognosis. Liquid biopsy holds great promise for early detection, although it still suffers from many disadvantages, mainly searching for specific cancer biomarkers. Here, a new approach for liquid biopsies is proposed, based on volatile organic compound (VOC) patterns in the blood headspace. An artificial intelligence nanoarray based on a varied set of chemi-sensitive nano-based structured films is developed and used to detect and stage cancer. As a proof-of-concept, three cancer models are tested showing high incidence and mortality rates in the population: breast cancer, ovarian cancer, and pancreatic cancer. The nanoarray has >84% accuracy, >81% sensitivity, and >80% specificity for early detection and >97% accuracy, 100% sensitivity, and >88% specificity for metastasis detection. Complementary mass spectrometry analysis validates these results. The ability to analyze such a complex biological fluid as blood, while considering data of many VOCs at a time using the artificially intelligent nanoarray, increases the sensitivity of predictive models and leads to a potential efficient early diagnosis and disease-monitoring tool for cancer.

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.

Analyses of lung cancer-derived volatiles in exhaled breath and in vitro models

Lung cancer is one of the leading causes of cancer incidence and cancer-related deaths in the world. Early diagnosis of pulmonary tumors results in improved survival compared to diagnosis with more advanced disease, yet early disease is not reliably indicated by symptoms. Despite of the improved testing and monitoring techniques for lung cancer in the past decades, most diagnostic tests, such as sputum cytology or tissue biopsies, are invasive and risky, rendering them unfeasible for large population screening. The non-invasive analysis of exhaled breath has gained attentions as an innovative screening method to measure chemical alterations within the human volatilome profile as a result of oncogenesis. More importantly, volatile organic compounds (VOCs) have been correlated to the pathophysiology of disease since the source of volatile compounds relies mostly on endogenous metabolic processes that are altered as a result of disease onset. Therefore, studying VOCs emitted from human breath may assist lung cancer diagnosis, treatment monitoring, and other surveillance of this devastating disease. In this mini review, we evaluated recent human studies that have attempted to identify lung cancer-derived volatiles in exhaled breath of patients. We also examined reported volatiles in cell cultures of lung cancer to better understand the origins of cancer-associated VOCs. We highlight the metabolic processes of lung cancer that could be responsible for the endogenous synthesis of these VOCs and pinpoint the protein-encoding genes involved in these pathways. Finally, we highlight the potential value of a breath test in lung cancer and propose prominent areas for future research required for the incorporation of VOCs-based testing into clinical settings.

Detection of volatile sulfur compounds (VSCs) in exhaled breath as a potential diagnostic method for oral squamous cell carcinoma

Background

Oral squamous cell carcinoma causes a significant proportion of global cancer morbidity and mortality. The aim of this study is to investigate whether the exhaled breath test can be a new, non-invasive, and effective method for diagnosing oral squamous cell carcinoma.

Methods

A comparative analysis of exhaled breath between patients with oral squamous cell carcinoma (OSCC) and healthy controls (HC) was performed with the Twin Breasor II™, a simple gas chromatography system.

Results

Both hydrogen sulfide (H₂S) and methyl mercaptan (Ch₃SH) were significantly higher in the OSCC group than in the HC group. The total sulfur concentration was also higher in the OSCC group, but there was no significant difference in the ratio of Ch₃SH to H₂S between the two groups. Using logistic regression, we constructed a new variable with an area under the curve (AUC) of 0.740, 68.0% sensitivity, and 72.0% specificity.

Conclusions

Exhaled gas analysis via simple gas chromatography can potentially serve as an accessory non-invasive method for OSCC diagnosis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12903-022-02301-3.

Volatile Organic Compounds Analysis as a Potential Novel Screening Tool for Breast Cancer: A Systematic Review

Introduction

An early diagnosis is crucial in reducing mortality among people who have breast cancer (BC). There is a shortfall of characteristic early clinical symptoms in BC patients, highlighting the importance of investigating new methods for its early detection. A promising novel approach is the analysis of volatile organic compounds (VOCs) produced and emitted through the metabolism of cancer cells.

Methods

The purpose of this systematic review is to outline the published research regarding BC-associated VOCs. For this, headspace analysis of VOCs was explored in patient-derived body fluids, animal model-derived fluids, and BC cell lines to identify BC-specific VOCs. A systematic search in PubMed and Web of Science databases was conducted according to the PRISMA guidelines.

Results

Thirty-two studies met the criteria for inclusion in this review. Results highlight that VOC analysis can be promising as a potential novel screening tool. However, results of in vivo, in vitro and case-control studies have delivered inconsistent results leading to a lack of inter-matrix consensus between different VOC sampling methods.

Discussion

Discrepant VOC results among BC studies have been obtained, highly due to methodological discrepancies. Therefore, methodological issues leading to disparities have been reviewed and recommendations have been made on the standardisation of VOC collection and analysis methods for BC screening, thereby improving future VOC clinical validation studies.

Changes of breath volatile organic compounds in healthy volunteers following segmental and inhalation endotoxin challenge

Background It is still unclear how airway inflammation affects the breath volatile organic compounds (VOC) profile in exhaled air. We therefore analyzed breath following well-defined pulmonary endotoxin (lipopolysaccharide, LPS) challenges. Methods Breath was collected from 10 healthy non-smoking subjects at eight time points before and after segmental and whole lung LPS inhalation challenge. Four Tenax-TA® adsorption tubes were simultaneously loaded from an aluminum reservoir cylinder and independently analyzed by two research groups using gas chromatography - mass spectrometry. Airway inflammation was assessed in bronchoalveolar lavage (BAL) and in sputum after segmental and inhaled LPS challenge, respectively. Results Segmental LPS challenge significantly increased the median (interquartile range, IQR) percentage of neutrophils in BAL from 3.0 (4.2) % to 64.0 (7.3) %. The inhalation challenge increased sputum neutrophils from 33.9 (26.8) % to 78.3 (13.5) %. We observed increases in breath aldehydes at both time points after segmental and inhaled LPS challenge. These results were confirmed by an independent laboratory. The longitudinal breath analysis also revealed distinct VOC patterns related to environmental exposures, clinical procedures, and to metabolic changes after food intake. Conclusions Changes in breath aldehydes suggest a relationship to LPS induced inflammation compatible with lipid peroxidation processes within the lung. Findings from our longitudinal data highlight the need for future studies to better consider the potential impact of the multiple VOCs from detergents, hygiene or lifestyle products a subject is continuously exposed to. We suspect that this very individual "owncloud" exposure is contributing to an increased variability of breath aldehydes, which might limit a use as inflammatory markers in daily clinical practice.

NH2NH-MOF: a reaction matrix for the specific determination of small aldehydes by MALDI-MS

Efficient determination of aldehydes by matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) is hampered mainly by the low mass and unstable nature of analytes. In the present work, we propose a combined strategy of a reactive metal-organic framework (MOF) matrix for the derivatization and detection of aldehydes. A novel reactive MOF matrix (NH₂NH-MOF) was synthesized in two steps. First, NR₃⁺-MOF was synthesized via Cu²⁺ and the quaternary amine ligand 4,4'-bipyridinium, 1,1″-(1,2-ethanediyl)bis-, dibromide (PyEtBr). Then, -NHNH₂ was introduced to NR₃⁺-MOF through electrostatic adsorption between the -NR₃⁺ and -HSO₃^- of 4-hydrazinylbenzenesulfonic acid to synthesize NH₂NH-MOF. The acid-base chemistry of NH₂NH-MOF led to uniform cocrystallization of the aldehyde-matrix mixtures and helped to achieve the detection of low-weight aldehydes with good relative standard deviations (RSDs = 0.07-12.35%). It was confirmed that this strategy can accurately quantify formaldehyde, valeraldehyde, and benzaldehyde with good linearity (r > 0.97). Furthermore, this strategy was applied to quantitatively detect benzaldehyde in wastewater, thus showing potential applications in environmental pollutant detection.

A headspace collection chamber for whole body volatilomics

The human body secretes a complex blend of volatile organic compounds (VOCs) via the skin, breath and bodily fluids. In this study, we have developed a headspace collection chamber for whole body volatilome profiling.

Recent advances in catalytic hairpin assembly signal amplification-based sensing strategies for microRNA detection

Accumulative evidences have indicated that abnormal expression of microRNAs (miRNAs) is closely associated with many health disorders, making them be regarded as potentialbiomarkers for early clinical diagnosis. Therefore, it is extremely necessary to develop a highly sensitive, specific and reliable approach for miRNA analysis. Catalytic hairpin assembly (CHA) signal amplification is an enzyme-free toehold-mediated strand displacement method, exhibiting significant potential in improving the sensitivity of miRNA detection strategies. In this review, we first describe the potential of miRNAs as disease biomarkers and therapeutics, and summarize the latest advances in CHA signal amplification-based sensing strategies for miRNA monitoring. We describe the characteristics and mechanism of CHA signal amplification and classify the CHA-based miRNA sensing strategies into several categories based on the "signal conversion substance", including fluorophores, enzymes, nanomaterials, and nucleotide sequences. Sensing performance, limit of detection, merits and disadvantages of these miRNA sensing strategies are discussed. Moreover, the current challenges and prospects are also presented.

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.

Breath volatile organic compound analysis: an emerging method for gastric cancer detection

Gastric cancer is a common malignancy, being the fifth most frequently diagnosed cancer and the fourth leading cause of cancer-related deaths worldwide. Diagnosis of gastric cancer at the early stage is critical to effectively improve the survival rate. However, a substantial proportion of patients with gastric cancer in the early stages lack specific symptoms or are asymptomatic. Moreover, the imaging techniques currently used for gastric cancer screening, such as computed tomography and barium examination, are usually radioactive and have low sensitivity and specificity. Even though endoscopy has high accuracy for gastric cancer screening, its application is limited by the invasiveness of the technique. Breath analysis is an economic, effective, easy to perform, non-invasive detection method, and has no undesirable side effects on subjects. Extensive worldwide research has been conducted on breath volatile organic compounds (VOCs), which reveals its prospect as a potential method for gastric cancer detection. Many interesting results have been obtained and innovative methods have been introduced in this subject; hence, an extensive review would be beneficial. By providing a comprehensive list of breath VOCs identified by gastric cancer would promote further research in this field. This review summarizes the commonly used technologies for exhaled breath analysis, focusing on the application of analytical instruments in the detection of breath VOCs in gastric cancers, and the alterations in the profile of breath biomarkers in gastric cancer patients are discussed as well.

Beyond liquid biopsy: Toward non-invasive assays for distanced cancer diagnostics in pandemics

Liquid biopsy technologies have seen a significant improvement in the last decade, offering the possibility of reliable analysis and diagnosis from several biological fluids. The use of these technologies can overcome the limits of standard clinical methods, related to invasiveness and poor patient compliance. Along with this there are now mature examples of lab-on-chips (LOC) which are available and could be an emerging and breakthrough technology for the present and near-future clinical demands that provide sample treatment, reagent addition and analysis in a sample-in/answer-out approach. The possibility of combining non-invasive liquid biopsy and LOC technologies could greatly assist in the current need for minimizing exposure and transmission risks. The recent and ongoing pandemic outbreak of SARS-CoV-2, indeed, has heavily influenced all aspects of life worldwide. Ordinary tasks have been forced to switch from “in presence” to “distanced”, limiting the possibilities for a large number of activities in all fields of life outside of the home. Unfortunately, one of the settings in which physical distancing has assumed noteworthy consequences is the screening, diagnosis and follow-up of diseases.

In this review, we analyse biological fluids that are easily collected without the intervention of specialized personnel and the possibility that they may be used -or not-for innovative diagnostic assays. We consider their advantages and limitations, mainly due to stability and storage and their integration into Point-of-Care diagnostics, demonstrating that technologies in some cases are mature enough to meet current clinical needs.

Hollow zeolitic imidazolate framework-7 coated stainless steel fiber for solid phase microextraction of volatile biomarkers in headspace gas of breast cancer cell lines

In this work, we reported the preparation of the hollow zeolitic imidazolate framework-7 (ZIF-7) via etching ZIF-7 with tannic acid, and further fabricated the hollow ZIF-7 coated fiber for the solid phase microextraction (SPME) of the five volatile biomarkers (acetone, isopropanol, hexanal, hexanol and decanal) generated from breast cancer cell lines. The hollow structure not only endowed higher extraction performance for the SPME of analytes, but also improved the diffusion rate of the analytes inside the hollow ZIF-7. Under the optimal conditions, the hollow ZIF-7 coated fiber offered high extraction capacity (25-153 mg g^-1) and enhancement factors (EFs, 2023-11250) for the five biomarkers, good linearity (R² > 0.9918) of acetone and isopropanol (2.5-500 μg L^-1) and hexanol, hexanal, and decanal (1.0-100 μg L^-1), low limits of detection (S/N = 3) of 0.07-0.53 μg L^-1 and the limit of quantifications (LOQs, S/N = 10) of 0.23-1.76 μg L^-1. The precisions (RSDs, %) for intra-day (n = 6), inter-day (n = 5) and fiber-to-fiber (n = 6) were 2.8-7.5%, 4.3-8.5%, and 4.2-14.6%, respectively. The high EFs of the hollow ZIF-7 coated fiber for the five biomarkers resulted from the integrated effects of the large surface area, the unique porous structure, hydrophobic interaction, gate-opening effect, and enhanced properties after etching including faster mass transport, multiple active components, and more exposed active sites. The fabricated hollow ZIF-7 coated fiber lasted at least 140 cycles of extraction/desorption/aging without obvious decrease of extraction ability and no change of crystal structure. Finally, the hollow ZIF-7 coated fiber combined with GC-FID had been successfully used to detect the five biomarkers in the headspace gas of human breast cancer cell lines (MDA-MB-231) and normal mammary cell lines (CCD-1095Sk) with the recoveries of 84-105%. These results revealed the prospect of hollow MOFs as efficient adsorbents for sample pretreatment.

A prediction model using 2-propanol and 2-butanone in urine distinguishes breast cancer

Safe and noninvasive methods for breast cancer screening with improved accuracy are urgently needed. Volatile organic compounds (VOCs) in biological samples such as breath and blood have been investigated as noninvasive novel markers of cancer. We investigated volatile organic compounds in urine to assess their potential for the detection of breast cancer. One hundred and ten women with biopsy-proven breast cancer and 177 healthy volunteers were enrolled. The subjects were divided into two groups: a training set and an external validation set. Urine samples were collected and analyzed by gas chromatography and mass spectrometry. A predictive model was constructed by multivariate analysis, and the sensitivity and specificity of the model were confirmed using both a training set and an external set with reproducibility tests. The training set included 60 breast cancer patients (age 34–88 years, mean 60.3) and 60 healthy controls (age 34–81 years, mean 58.7). The external validation set included 50 breast cancer patients (age 35–85 years, mean 58.8) and 117 healthy controls (age 18–84 years, mean 51.2). One hundred and ninety-one compounds detected in at least 80% of the samples from the training set were used for further analysis. The predictive model that best-detected breast cancer at various clinical stages was constructed using a combination of two of the compounds, 2-propanol and 2-butanone. The sensitivity and specificity in the training set were 93.3% and 83.3%, respectively. Triplicated reproducibility tests were performed by randomly choosing ten samples from each group, and the results showed a matching rate of 100% for the breast cancer patient group and 90% for the healthy control group. Our prediction model using two VOCs is a useful complement to the current diagnostic tools. Further studies inclusive of benign tumors and non-breast malignancies are warranted.

Volutrauma Increases Exhaled Pentanal in Rats: A Potential Breath Biomarker for Ventilator-Induced Lung Injury

BACKGROUND

Mechanical ventilation injures lungs, but there are currently no reliable methods for detecting early injury. We therefore evaluated whether exhaled pentanal, a lipid peroxidation product, might be a useful breath biomarker for stretch-induced lung injury in rats.

METHODS

A total of 150 male Sprague-Dawley rats were investigated in 2 substudies. The first randomly assigned 75 rats to 7 hours of mechanical ventilation at tidal volumes of 6, 8, 12, 16, and 20 mL·kg-1. The second included 75 rats. A reference group was ventilated at a tidal volume of 6 mL·kg-1 for 10 hours 4 interventional groups were ventilated at a tidal volume of 6 mL·kg-1 for 1 hour, and then for 0.5, 1, 2, or 3 hours at a tidal volume of 16 mL.kg-1 before returning to a tidal volume of 6 mL·kg-1 for additional 6 hours. Exhaled pentanal was monitored by multicapillary column-ion mobility spectrometry. The first substudy included cytokine and leukocyte measurements in blood and bronchoalveolar fluid, histological assessment of the proportion of alveolar space, and measurements of myeloperoxidase activity in lung tissue. The second substudy included measurements of pentanal in arterial blood plasma, cytokine and leukocyte concentrations in bronchoalveolar fluid, and cleaved caspase 3 in lung tissue.

RESULTS

Exhaled pentanal concentrations increased by only 0.5 ppb·h-1 (95% confidence interval [CI], 0.3-0.6) when rats were ventilated at 6 mL·kg-1. In contrast, exhaled pentanal concentrations increased substantially and roughly linearly at higher tidal volumes, up to 3.1 ppb·h-1 (95% CI, 2.3-3.8) at tidal volumes of 20 mL·kg-1. Exhaled pentanal increased at average rates between 1.0 ppb·h-1 (95% CI, 0.3-1.7) and 2.5 ppb·h-1 (95% CI, 1.4-3.6) after the onset of 16 mL·kg-1 tidal volumes and decreased rapidly by a median of 2 ppb (interquartile range [IQR], 0.9-3.2), corresponding to a 38% (IQR, 31-43) reduction when tidal volume returned to 6 mL·kg-1. Tidal volume, inspiratory pressure, and mechanical power were positively associated with pentanal exhalation. Exhaled and plasma pentanal were uncorrelated. Alveolar space decreased and inflammatory markers in bronchoalveolar lavage fluid increased in animals ventilated at high tidal volumes. Short, intermittent ventilation at high tidal volumes for up to 3 hours increased neither inflammatory markers in bronchoalveolar fluid nor the proportion of cleaved caspase 3 in lung tissue.

CONCLUSIONS

Exhaled pentanal is a potential biomarker for early detection of ventilator-induced lung injury in rats.

A unique volatile signature distinguishes malaria infection from other conditions that cause similar symptoms

Recent findings suggest that changes in human odors caused by malaria infection have significant potential as diagnostic biomarkers. However, uncertainty remains regarding the specificity of such biomarkers, particularly in populations where many different pathological conditions may elicit similar symptoms. We explored the ability of volatile biomarkers to predict malaria infection status in Kenyan schoolchildren exhibiting a range of malaria-like symptoms. Using genetic algorithm models to explore data from skin volatile collections, we were able to identify malaria infection with 100% accuracy among children with fever and 75% accuracy among children with other symptoms. While we observed characteristic changes in volatile patterns driven by symptomatology, our models also identified malaria-specific biomarkers with robust predictive capability even in the presence of other pathogens that elicit similar symptoms.

Quantification of Volatile Aldehydes Deriving from In Vitro Lipid Peroxidation in the Breath of Ventilated Patients

Exhaled aliphatic aldehydes were proposed as non-invasive biomarkers to detect increased lipid peroxidation in various diseases. As a prelude to clinical application of the multicapillary column–ion mobility spectrometry for the evaluation of aldehyde exhalation, we, therefore: (1) identified the most abundant volatile aliphatic aldehydes originating from in vitro oxidation of various polyunsaturated fatty acids; (2) evaluated emittance of aldehydes from plastic parts of the breathing circuit; (3) conducted a pilot study for in vivo quantification of exhaled aldehydes in mechanically ventilated patients. Pentanal, hexanal, heptanal, and nonanal were quantifiable in the headspace of oxidizing polyunsaturated fatty acids, with pentanal and hexanal predominating. Plastic parts of the breathing circuit emitted hexanal, octanal, nonanal, and decanal, whereby nonanal and decanal were ubiquitous and pentanal or heptanal not being detected. Only pentanal was quantifiable in breath of mechanically ventilated surgical patients with a mean exhaled concentration of 13 ± 5 ppb. An explorative analysis suggested that pentanal exhalation is associated with mechanical power—a measure for the invasiveness of mechanical ventilation. In conclusion, exhaled pentanal is a promising non-invasive biomarker for lipid peroxidation inducing pathologies, and should be evaluated in future clinical studies, particularly for detection of lung injury.

A literature survey of all volatiles from healthy human breath and bodily fluids: the human volatilome

This paper comprises an updated version of the 2014 review which reported 1846 volatile organic compounds (VOCs) identified from healthy humans. In total over 900 additional VOCs have been reported since the 2014 review and the VOCs from semen have been added. The numbers of VOCs found in breath and the other bodily fluids are: blood 379, breath 1488, faeces 443, milk 290, saliva 549, semen 196, skin 623 and urine 444. Compounds were assigned CAS registry numbers and named according to a common convention where possible. The compounds have been included in a single table with the source reference(s) for each VOC, an update on our 2014 paper. VOCs have also been grouped into tables according to their chemical class or functionality to permit easy comparison. Careful use of the database is needed, as a number of the identified VOCs only have level 2-putative assignment, and only a small fraction of the reported VOCs have been validated by standards. Some clear differences are observed, for instance, a lack of esters in urine with a high number in faeces and breath. However, the lack of compounds from matrices such a semen and milk compared to breath for example could be due to the techniques used or reflect the intensity of effort e.g. there are few publications on VOCs from milk and semen compared to a large number for breath. The large number of volatiles reported from skin is partly due to the methodologies used, e.g. by collecting skin sebum (with dissolved VOCs and semi VOCs) onto glass beads or cotton pads and then heating to a high temperature to desorb VOCs. All compounds have been included as reported (unless there was a clear discrepancy between name and chemical structure), but there may be some mistaken assignations arising from the original publications, particularly for isomers. It is the authors' intention that this work will not only be a useful database of VOCs listed in the literature but will stimulate further study of VOCs from healthy individuals; for example more work is required to confirm the identification of these VOCs adhering to the principles outlined in the metabolomics standards initiative. Establishing a list of volatiles emanating from healthy individuals and increased understanding of VOC metabolic pathways is an important step for differentiating between diseases using VOCs.

Application of chemoresistive gas sensors and chemometric analysis to differentiate the fingerprints of global volatile organic compounds from diseases. Preliminary results of COPD, lung cancer and breast cancer

BACKGROUND

Analysis of volatile organic compounds (VOCs) in exhaled breath has been proposed as a screening method that discriminates between disease and healthy subjects, few studies evaluate whether these chemical fingerprints are specific when compared between diseases. We evaluated global VOCs and their discrimination capacity in chronic obstructive pulmonary disease (COPD), lung cancer, breast cancer and healthy subjects by chemoresistive sensors and chemometric analysis.

METHODS

A cross-sectional study was conducted with the participation of 30 patients with lung cancer, 50 with breast cancer, 50 with COPD and 50 control subjects. Each participant's exhaled breath was analyzed with the electronic nose. A multivariate analysis was carried: principal component analysis (PCA) and, canonical analysis of principal coordinates (CAP). Twenty single-blind samples from the 4 study groups were evaluated by CAP.

RESULTS

A separation between the groups of patients to the controls was achieved through PCA with explanations of >90% of the data and with a correct classification of 100%. In the CAP of the 4 study groups, discrimination between the diseases was obtained with 2 canonical axes with a correct general classification of 91.35%. This model was used for the prediction of the single-blind samples resulting in correct classification of 100%.

CONCLUSIONS

The application of chemoresistive gas sensors and chemometric analysis can be used as a useful tool for a screening test for lung cancer, breast cancer and COPD since this equipment detects the set of VOCs present in the exhaled breath to generate a characteristic chemical fingerprint of each disease.

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.

Circulating microRNAs: Biomarkers of disease

MicroRNAs are a class of endogenous noncoding single-stranded RNA molecules with approximately 20-24 nucleotides and are associated with a broad range of biological processes. Researchers found that microRNAs are abundant in tissues, and more importantly, there are also trace circulating microRNAs that exist in biological fluids. In recent years, circulating microRNAs had emerged as promising diagnostic and prognostic biomarkers for the noninvasive detection of diseases with high specificity and sensitivity. More importantly, specific microRNA expression signatures reflect not only the existence of early-stage diseases but also the dynamic development of advanced-stage diseases, disease prognosis prediction, and drug resistance. To date, an increasing number of potential miRNA biomarkers have been reported, but their practical application prospects are still unclear. Therefore, microRNAs, as potential diagnostic and prognostic biomarkers in a variety of diseases, need to be updated, as they are of great importance in the diagnosis, prognosis and prediction of therapeutic responses. In this review, we summary our current understanding of microRNAs as potential biomarkers in the major diseases (e.g., cancers and cardio-cerebrovascular diseases), which provide the basis for the design of diagnosis and treatment plan and the improvement of the cure rate.

Urinary Volatile Organic Compound Analysis for the Diagnosis of Cancer: A Systematic Literature Review and Quality Assessment

The analysis of urinary volatile organic compounds (VOCs) is a promising field of research with the potential to discover new biomarkers for cancer early detection. This systematic review aims to summarise the published literature concerning cancer-associated urinary VOCs. A systematic online literature search was conducted to identify studies reporting urinary VOC biomarkers of cancers in accordance with the recommendations of the Cochrane Library and Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines. Thirteen studies comprising 1266 participants in total were included in the review. Studies reported urinary VOC profiles of five cancer subtypes: prostate cancer, gastrointestinal cancer, leukaemia/lymphoma, lung cancer, and bladder cancer. Forty-eight urinary VOCs belonging to eleven chemical classes were identified with high diagnostic performance. VOC profiles were distinctive for each cancer type with limited cross-over. The metabolic analysis suggested distinctive phenotypes for prostate and gastrointestinal cancers. The heterogenicity of study design, methodological and reporting quality may have contributed to inconsistencies between studies. Urinary VOC analysis has shown promising performance for non-invasive diagnosis of cancer. However, limitations in study design have resulted in inconsistencies between studies. These limitations are summarised and discussed in order to support future studies.

Non-Invasive Biomarkers for Early Detection of Breast Cancer

Breast cancer is the most common cancer in women worldwide. Accurate early diagnosis of breast cancer is critical in the management of the disease. Although mammogram screening has been widely used for breast cancer screening, high false-positive and false-negative rates and radiation from mammography have always been a concern. Over the last 20 years, the emergence of "omics" strategies has resulted in significant advances in the search for non-invasive biomarkers for breast cancer diagnosis at an early stage. Circulating carcinoma antigens, circulating tumor cells, circulating cell-free tumor nucleic acids (DNA or RNA), circulating microRNAs, and circulating extracellular vesicles in the peripheral blood, nipple aspirate fluid, sweat, urine, and tears, as well as volatile organic compounds in the breath, have emerged as potential non-invasive diagnostic biomarkers to supplement current clinical approaches to earlier detection of breast cancer. In this review, we summarize the current progress of research in these areas.

Identification of profiles of volatile organic compounds in exhaled breath by means of an electronic nose as a proposal for a screening method for breast cancer: a case-control study

The objective of the present study was to identify volatile prints from exhaled breath, termed breath-print, from breast cancer (BC) patients and healthy women by means of an electronic nose and to evaluate its potential use as a screening method. A cross-sectional study was performed on 443 exhaled breath samples from women, of whom 262 had been diagnosed with BC by biopsy and 181 were healthy women (control group). Breath-print analysis was performed utilizing the Cyranose 320 electronic nose. Group data were evaluated by principal component analysis (PCA), canonical discriminant analysis (CDA), and support vector machine (SVM), and the test's diagnostic power was evaluated by means of receiver operating characteristic (ROC) curves. The results obtained using the model generated from the CDA, which best describes the behavior of the assessed groups, indicated that the breath-print of BC patients was different from that of healthy women and that they presented with a variability of up to 98.8% and a correct classification of 98%. The sensitivity, specificity, negative predictive value, and positive predictive value reached 100% according to the ROC curve. The present study demonstrates the capability of the electronic nose to separate between healthy subjects and BC patients. This research could have a beneficial impact on clinical practice as we consider that this test could probably be used at the first point before the application of established gold tests (mammography, ultrasound, and biopsy) and substantially improve screening tests in the general population.

Exhaled Volatile Organic Compounds Are Able to Discriminate between Neutrophilic and Eosinophilic Asthma

Rationale: Analysis of exhaled breath for asthma phenotyping using endogenously generated volatile organic compounds (VOCs) offers the possibility of noninvasive diagnosis and therapeutic monitoring. Induced sputum is indeed not widely available and markers of neutrophilic asthma are still lacking.Objectives: To determine whether analysis of exhaled breath using endogenously generated VOCs can be a surrogate marker for recognition of sputum inflammatory phenotypes.Methods: We conducted a prospective study on 521 patients with asthma recruited from the University Asthma Clinic of Liege. Patients underwent VOC measurement, fraction of exhaled nitric oxide (Fe_NO) spirometry, sputum induction, and gave a blood sample. Subjects with asthma were classified in three inflammatory phenotypes according to their sputum granulocytic cell count.Measurements and Main Results: In the discovery study, seven potential biomarkers were highlighted by gas chromatography-mass spectrometry in a training cohort of 276 patients with asthma. In the replication study (n = 245), we confirmed four VOCs of interest to discriminate among asthma inflammatory phenotypes using comprehensive two-dimensional gas chromatography coupled to high-resolution time-of-flight mass spectrometry. Hexane and 2-hexanone were identified as compounds with the highest classification performance in eosinophilic asthma with accuracy comparable to that of blood eosinophils and Fe_NO. Moreover, the combination of Fe_NO, blood eosinophils, and VOCs gave a very good prediction of eosinophilic asthma (area under the receiver operating characteristic curve, 0.9). For neutrophilic asthma, the combination of nonanal, 1-propanol, and hexane had a classification performance similar to Fe_NO or blood eosinophils in eosinophilic asthma. Those compounds were found in higher levels in neutrophilic asthma.Conclusions: Our study is the first attempt to characterize VOCs according to sputum granulocytic profile in a large population of patients with asthma and provide surrogate markers for neutrophilic asthma.