Volatile organic compounds in breath as markers of lung cancer: a cross-sectional study

Technical approaches for breath aldehyde biomarker detection and disease diagnosis: A review

Exhaled breath analysis holds promise as a non-invasive approach for disease diagnosis. Aldehydes represent a class of volatile organic compounds with diagnostic potential as breath biomarkers for cancers and other conditions. However, aldehydes exist at low concentrations in breath and have stability challenges. This review summarizes recent studies on breath aldehyde analysis, focusing on sample collection methodology, analytical techniques implemented, and key findings regarding aldehyde alterations in disease. Breath collection methods examined include commercial bags, end-tidal sampling devices, condensates, and direct analysis. Analytical techniques evaluated gas chromatography, mass spectrometry, and microextraction approaches. Emerging microextraction and sensing technologies are advancing real-time, non-invasive aldehyde detection. Overall, breath aldehyde biomarkers offer immense potential for diagnosis and screening, but continued research is needed to address current limitations. This review provides insights to guide future efforts focused on exhaled aldehyde analysis and disease detection.

Online monitoring and stable isotope tracing of cancer associated volatiles in murine model captures tumor associated markers in vivo

BACKGROUND

The imperative need for early cancer detection, which is crucial for improved survival rates in many severe cancers such as lung cancer, remains challenging due to the lack of reliable early-diagnosis technologies and robust biomarkers. To address this gap, innovative screening platforms are essential to unveil the chemical signatures of lung cancer and its treatments. It is established that the oxidative tumor environment induces alterations in host metabolic processes and influences endogenous volatile synthesis. Despite efforts, consensus on unique volatile markers for cancer detection has been elusive, partly due to genetic variation leading to metabolic heterogeneity in humans and the lack of standardized procedures for analytical analyses.

RESULTS

In this study, we utilized advanced secondary electrospray ionization (SESI) technique coupled with a high-resolution mass spectrometer (HRMS) to non-invasively monitor lung cancer volatiles in a pre-clinical mouse model in real time. Our findings revealed 651 dysregulated volatile features upon cancer onset and identified 36 features correlated with tumor size. Endogenous tracing of glucose metabolism highlighted the γ-glutamyl cycle as a downstream pathway implicated in lung cancer, driven by an imbalance in glutathione metabolism due to reactive oxygen species (ROS) accumulation. Notably, our study unveiled unique volatile changes associated with gemcitabine and cisplatin treatment, which significantly abrogated tumor growth in vivo. Furthermore, we identified 5-oxoproline as a volatile metabolite indicative of lung cancer response to treatment.

SIGNIFICANCE

In conclusion, our SESI-HRMS based analysis of pre-clinical model systematically explores the volatile signatures of lung cancer, and provides a novel non-invasive platform that possess great potential for the real-time, confident, and sensitive detection and monitoring of lung cancer.

Breath biomarkers for esophageal cancer: identification, quantification, and diagnostic modeling

Esophageal cancer is a major global health issue with a high mortality rate. Early diagnosis is crucial for improving patient outcomes, but traditional diagnostic methods are often invasive and costly. This study explores the potential of exhaled volatile organic compounds (VOCs) as a non-invasive diagnostic tool for esophageal cancer. Using gas chromatography-mass spectrometry (GC-MS), we analyzed the breath samples of 80 esophageal cancer patients and 60 healthy controls, identifying and quantifying over 100 VOCs. The results revealed significant differences in the concentrations of VOCs such as acetone, ethanol, and isoprene between the two groups. A multi-parameter regression diagnostic model based on a neural network algorithm achieved an accuracy of 90.3% in distinguishing esophageal cancer patients from healthy individuals. Further optimization incorporating physiological factors, including smoking, drinking, and dietary habits, improved the model's accuracy to 92.4%, with a specificity of 93.1%, representing a significant improvement over previous studies. These results suggest that VOCs analysis in exhaled breath holds great promise as a non-invasive, cost-effective, and accurate method for early detection of esophageal cancer.

Metal-organic framework-based SERS probes with enrichment capability for trace detection: applications in biomarkers and pollutants

Surface-enhanced Raman scattering (SERS) has emerged as a powerful tool for trace substances detection due to its exceptional sensitivity, high anti-interference capability, and ease of operation, enabling detection at the single-molecule level. This makes SERS particularly promising for applications such as environmental monitoring, biomedical diagnostics, and food safety. Despite these advantages, SERS faces limitations due to the difficulty of enriching trace substances and the small Raman scattering cross sections of certain molecules. Metal-organic frameworks (MOFs), characterized by their high surface areas and porosity, tunable structures, and diverse functionalities, offer a promising solution to these challenges. By integrating MOFs with SERS technology, we explore how MOF-based SERS probes can enhance the sensitivity, selectivity, and efficiency of trace substance detection through mechanisms such as analyte enrichment, selective molecular capture, and electromagnetic field manipulation. In this paper, a comprehensive review of the structure and synthesis of MOF-SERS composites is presented, with an emphasis on their application in the detection of trace substances. The paper also discusses key challenges in the design and optimization of MOF-based SERS probes, particularly in terms of stability, reproducibility, and integration with existing detection platforms, aiming to broaden their practical applications and improve their detection efficiency.

Diagnostic accuracy of breath tests based on volatile organic compounds for cancer: A systematic review and meta-analysis

Exhaled volatile organic compounds (VOCs) are being extensively studied for the purposes of noninvasive cancer diagnoses. This systematic review and meta-analysis aims to evaluate the diagnostic accuracy of breath tests based on VOCs for cancer detection, and to propose potential cancer biomarkers. This study was conducted in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines. Relevant studies up to February 2024 were retrieved from public databases, including PubMed, EMBASE, and Web of Science. A total of 114 articles were included, covering 125 non-duplicate studies involving 8768 cancer patients. Meta-analysis showed that the VOC breath test demonstrated a sensitivity of 87% and a specificity of 81% in cancer diagnosis, with an area under the receiver operating characteristic curve (AUC) of 0.93. Subgroup analyses based on cancer types and breath detection techniques also showed high sensitivity and specificity in diagnosing cancer patients. These suggest that breath analysis for VOCs has excellent diagnostic accuracy for cancer. The breath test based on VOCs, as a non-invasive detection method, shows great potential for cancer diagnosis.

Biomarkers in lung cancer diagnosis and bronchoscopy: Current landscape and future directions

Lung cancer is the leading cause of cancer death world-wide. Along the entire timeline of lung cancer identification, diagnosis and treatment, clinicians and patients face challenges in clinical decision-making that could be aided by useful biomarkers. In this review, we discuss the development of biomarkers and qualities that are ideal in a biomarker candidate, types of biospecimens that can be utilized for biomarker development in lung cancer, and how biomarkers could be clinically useful at various points along lung cancer timeline. We then review biomarkers that have been validated and are clinically available to assist with the management of lung nodules and diagnosis of lung cancer, which includes blood-based biomarkers to assist with decision-making prior to an invasive diagnostic procedure, as well as specimens obtained during a bronchoscopy and applied in cases of an inconclusive biopsy result. Finally, we discuss challenges in biomarker application and recent publications relevant to future lung cancer biomarker development.

Non-invasive early-stage cancer detection: current methods and future perspectives

This review paper explores the realm of non-invasive methods for early cancer detection. Early identification is crucial for effective therapeutic intervention, and non-invasive techniques have emerged as promising tools to enhance diagnostic accuracy and improve patient outcomes. The paper thoroughly examines the advantages, limitations, and prospects of various non-invasive approaches, including blood tests, non-blood-based tests, and diverse imaging modalities. It discusses the biomarkers found in blood for early-stage cancer detection, specifying the types of cancer associated with each biomarker. The non-blood-based tests focus on components in saliva, urine, and breath for cancer detection, alongside current studies and future perspectives on various cancers. Optical imaging methods covered in this review include fluorescence imaging in the near-infrared (NIR) region, bioluminescence imaging, and Raman spectroscopy for early-stage cancer detection. The review also highlights the pros and cons of ultrasound imaging in early-stage cancer detection. Additionally, the clinical implications of using AI for cancer detection, both present and future, are explored. This paper provides valuable insights for researchers and clinicians working in the field of non-invasive early-stage cancer detection.

The human volatilome meets cancer diagnostics: past, present, and future of noninvasive applications

BACKGROUND

Cancer is a significant public health problem, causing dozens of millions of deaths annually. New cancer screening programs are urgently needed for early cancer detection, as this approach can improve treatment outcomes and increase patient survival. The search for affordable, noninvasive, and highly accurate cancer detection methods revealed a valuable source of tumor-derived metabolites in the human metabolome through the exploration of volatile organic compounds (VOCs) in noninvasive biofluids.

AIM OF REVIEW

This review discusses volatilomics-based approaches for cancer detection using noninvasive biomatrices (breath, saliva, skin secretions, urine, feces, and earwax). We presented the historical background, the latest approaches, and the required stages for clinical validation of volatilomics-based methods, which are still lacking in terms of making noninvasive methods available and widespread to the population. Furthermore, insights into the usefulness and challenges of volatilomics in clinical implementation steps for each biofluid are highlighted.

KEY SCIENTIFIC CONCEPTS OF REVIEW

We outline the methodologies for using noninvasive biomatrices with up-and-coming clinical applications in cancer diagnostics. Several challenges and advantages associated with the use of each biomatrix are discussed, aiming at encouraging the scientific community to strengthen efforts toward the necessary steps to speed up the clinical translation of volatile-based cancer detection methods, as well as discussing in favor of (i) hybrid applications (i.e., using more than one biomatrix) to describe metabolite modulations that can be "cancer volatile fingerprints" and (ii) in multi-omics approaches integrating genomics, transcriptomics, and proteomics into the volatilomic data, which might be a breakthrough for diagnostic purposes, onco-pathway assessment, and biomarker validations.

Identification of acrolein as a novel diagnostic odor biomarker for 1,2,3-trichloropropane-induced hepatotoxicity in Sprague Dawley rats

Body odor is considered a diagnostic indicator of various infectious and chronic diseases. But, few studies have examined the odor markers for various toxic effects in the mammalian system. This study attempted to identify the novel diagnostic odor biomarkers for chemical-induced hepatotoxicity in animals. The changes in the concentration of odors were analyzed in the urine of Sprague Dawley (SD) rats treated with two dosages (100 or 200 mg/kg) of 1,2,3-trichloropropane (TCP) using gas chromatography-mass spectrometry (GC-MS). The TCP treatment induced significant toxicity, including a decrease in body weight, an increase in serum biochemical factors, and histopathological changes in the liver of SD rats. During this hepatotoxicity, the concentrations of six odors (ethyl alcohol, acrolein (2-propenal), methanesulfonyl chloride, methyl ethyl ketone, cyclotrisiloxane, and 2-heptanone) in urine changed significantly after the TCP treatment. Among them, acrolein, an acrid and pungent compound, showed the highest rate of increase in the TCP-treated group compared to the Vehicle-treated group. In addition, this increase in acrolein was accompanied by enhanced spermine oxidase (SMOX) expression, an acrolein metabolic enzyme, and the increased level of IL-6 transcription as a regulator factor that induces SMOX production. The correlation between acrolein and other parameters was conformed using correlagram analyses. These results provide scientific evidence that acrolein have potential as a novel diagnostic odor biomarker for TCP-induced hepatotoxicity.

Supplementary Information

The online version contains supplementary material available at 10.1007/s43188-024-00253-0.

Identification of exhaled volatile organic compounds that characterize asthma phenotypes: A J-VOCSA study

BACKGROUND

Asthma is characterized by phenotypes of different clinical, demographic, and pathological characteristics. Identifying the profile of exhaled volatile organic compounds (VOCs) in asthma phenotypes may facilitate establishing biomarkers and understanding asthma background pathogenesis. This study aimed to identify exhaled VOCs that characterize severe asthma phenotypes among patients with asthma.

METHODS

This was a multicenter cross-sectional study of patients with severe asthma in Japan. Clinical data were obtained from medical records, and questionnaires were collected. Exhaled breath was sampled and subjected to thermal desorption gas chromatography-mass spectrometry (GC/MS).

RESULTS

Using the decision tree established in the previous nationwide asthma cohort study, 245 patients with asthma were divided into five phenotypes and subjected to exhaled VOC analysis with 50 healthy controls (HCs). GC/MS detected 243 VOCs in exhaled breath samples, and 142 frequently detected VOCs (50% of all samples) were used for statistical analyses. Cluster analysis assigning the groups with similar VOC profile patterns showed the highest similarities between phenotypes 3 and 4 (early-onset asthma phenotypes), followed by the similarities between phenotypes 1 and 2 (late-onset asthma phenotypes). Comparisons between phenotypes 1-5 and HC revealed 19 VOCs, in which only methanesulfonic anhydride showed p < 0.05 adjusted by false discovery rate (FDR). Comparison of these phenotypes yielded several VOCs showing different trends (p < 0.05); however, no VOCs showed p < 0.05 adjusted by FDR.

CONCLUSIONS

Exhaled VOC profiles may be useful for distinguishing asthma and asthma phenotypes; however, these findings need to be validated, and their pathological roles should be clarified.

Precision detection of select human lung cancer biomarkers and cell lines using honeybee olfactory neural circuitry as a novel gas sensor

Human breath contains biomarkers (odorants) that can be targeted for early disease detection. It is well known that honeybees have a keen sense of smell and can detect a wide variety of odors at low concentrations. Here, we employ honeybee olfactory neuronal circuitry to classify human lung cancer volatile biomarkers at different concentrations and their mixtures at concentration ranges relevant to biomarkers in human breath from parts-per-billion to parts-per-trillion. We also validated this brain-based sensing technology by detecting human non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC) cell lines using the 'smell' of the cell cultures. Different lung cancer biomarkers evoked distinct spiking response dynamics in the honeybee antennal lobe neurons indicating that those neurons encoded biomarker-specific information. By investigating lung cancer biomarker-evoked population neuronal responses from the honeybee antennal lobe, we classified individual human lung cancer biomarkers successfully (88% success rate). When we mixed six lung cancer biomarkers at different concentrations to create 'synthetic lung cancer' vs. 'synthetic healthy' human breath, honeybee population neuronal responses were able to classify those complex breath mixtures reliably with exceedingly high accuracy (93-100% success rate with a leave-one-trial-out classification method). Finally, we employed this sensor to detect human NSCLC and SCLC cell lines and we demonstrated that honeybee brain olfactory neurons could distinguish between lung cancer vs. healthy cell lines and could differentiate between different NSCLC and SCLC cell lines successfully (82% classification success rate). These results indicate that the honeybee olfactory system can be used as a sensitive biological gas sensor to detect human lung cancer.

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

CLINICAL REGISTRATION NUMBER

ClinicalTrials.gov Identifier: NCT06034730.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Unlocking the secrets: Volatile Organic Compounds (VOCs) and their devastating effects on lung cancer

Lung cancer (LCs) is still a serious health problem globally, with many incidences attributed to environmental triggers such as Volatile Organic Compounds (VOCs). VOCs are a broad class of compounds that can be released via various sources, including industrial operations, automobile emissions, and indoor air pollution. VOC exposure has been linked to an elevated risk of lung cancer via multiple routes. These chemicals can be chemically converted into hazardous intermediate molecules, resulting in DNA damage and genetic alterations. VOCs can also cause oxidative stress, inflammation, and a breakdown in the cellular protective antioxidant framework, all of which contribute to the growth of lung cancer. Moreover, VOCs have been reported to alter critical biological reactions such as cell growth, apoptosis, and angiogenesis, leading to tumor development and metastasis. Epidemiological investigations have found a link between certain VOCs and a higher probability of LCs. Benzene, formaldehyde, and polycyclic aromatic hydrocarbons (PAHs) are some of the most well-researched VOCs, with comprehensive data confirming their cancer-causing potential. Nevertheless, the possible health concerns linked with many more VOCs and their combined use remain unknown, necessitating further research. Identifying the toxicological consequences of VOCs in LCs is critical for establishing focused preventative tactics and therapeutic strategies. Better legislation and monitoring mechanisms can limit VOC contamination in occupational and environmental contexts, possibly reducing the prevalence of LCs. Developing VOC exposure indicators and analyzing their associations with genetic susceptibility characteristics may also aid in early identification and targeted therapies.

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.

Real-time breath analysis towards a healthy human breath profile

The direct analysis of molecules contained within human breath has had significant implications for clinical and diagnostic applications in recent decades. However, attempts to compare one study to another or to reproduce previous work are hampered by: variability between sampling methodologies, human phenotypic variability, complex interactions between compounds within breath, and confounding signals from comorbidities. Towards this end, we have endeavored to create an averaged healthy human 'profile' against which follow-on studies might be compared. Through the use of direct secondary electrospray ionization combined with a high-resolution mass spectrometry and in-house bioinformatics pipeline, we seek to curate an average healthy human profile for breath and use this model to distinguish differences inter- and intra-day for human volunteers. Breath samples were significantly different in PERMANOVA analysis and ANOSIM analysis based on Time of Day, Participant ID, Date of Sample, Sex of Participant, and Age of Participant (p< 0.001). Optimal binning analysis identify strong associations between specific features and variables. These include 227 breath features identified as unique identifiers for 28 of the 31 participants. Four signals were identified to be strongly associated with female participants and one with male participants. A total of 37 signals were identified to be strongly associated with the time-of-day samples were taken. Threshold indicator taxa analysis indicated a shift in significant breath features across the age gradient of participants with peak disruption of breath metabolites occurring at around age 32. Forty-eight features were identified after filtering from which a healthy human breath profile for all participants was created.

Exhaled VOC Biomarkers from Rats Injected with PMs from Thirty-One Major Cities in China

Particulate matter (PMs) of different origins can cause diverse health effects. Here, a homemade box was used to facilitate real-time measurements of breath-borne volatile organic compounds (VOCs) by gas chromatography-ion mobility spectrometry. We have tracked exhaled VOC changes in 228 Wistar rats that were injected with water-soluble PM suspension filtrates (after 0.45 μm) from 31 China cities for 1 h to up to 1-6 days during the experiments. Rats exposed to the filtrates exhibited significant changes in breath-borne VOCs within hours, featuring dynamic fluctuations in the levels of acetone, butan-2-one, heptan-2-one-M, acetic acid-M, and ethanol. Subsequently, on the fifth to sixth day after the injection, there was a notable increase in the proportion of aldehydes (including hexanal-M, hexanal-D, pentanal, heptanal-M, and (E)-2-hexenal). The 10 dynamic VOC fingerprint patterns mentioned earlier showcased the capability to indirectly differentiate urban PM toxicity and categorize the 31 cities into four distinct groups based on their health effects. This study provides valuable insights into the mechanisms of exhaled VOCs and underscores their critical role as biomarkers for differentiating the toxicity of different PMs and detecting the early signs of potential diseases. The results from this work also provide a scientific basis for city-specific air pollution control and policy development.

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.

Ultrasensitive discrimination of volatile organic compounds using a microfluidic silicon SERS artificial intelligence chip

Current gaseous sensors hardly discriminate trace volatile organic compounds at the ppt level. Herein, we present an integrated platform for simultaneously enabling rapid preconcentration, reliable surface-enhanced Raman scattering, (SERS) detection and automatic identification of trace aldehydes at the ppt level. For rapid preconcentration, we demonstrate that the nozzle-like microfluidic concentrator allows the enrichment of rare gaseous analytes by five-fold in only 0.01 ms. The enriched gas is subsequently captured and detected by an integrated silicon-based SERS chip, which is made of zeolitic imidazolate framework-8 coated silver nanoparticles grown in situ on a silicon wafer. After SERS measurement, a fully connected deep neural network is built to extract faint features in the spectral dataset and discriminate volatile organic compound classes. We demonstrate that six kinds of gaseous aldehydes at 100 ppt could be detected and classified with an identification accuracy of ∼80.9% by using this platform.

Recent Advances in Gas Detection Methodologies with a Special Focus on Environmental Sensing and Health Monitoring Applications─A Critical Review

With the expansion of the Internet-of-Things (IoT), the use of gas sensors in the field of wearable technology, smart devices, and smart homes has increased manifold. These gas sensors have two key applications─one is the detection of gases present in the environment and the other is the detection of Volatile Organic Compounds (VOCs) that are found in the breath. In this review, we focus systematically on the advancements in the field of various spectroscopic methods such as mass spectrometry-based analysis and point-of-care approach to detect VOCs and gases for environmental monitoring and disease diagnosis. Additionally, we highlight the development of smart sensors that work on the principle of electrochemical detection and provide examples of the same through an extensive literature review. At the end of this review, we highlight various challenges and future perspectives.

Construction of High-Active SERS Cavities in a TiO2 Nanochannels-Based Membrane: A Selective Device for Identifying Volatile Aldehyde Biomarkers

The accurate, sensitive, and selective on-site screening of volatile aldehyde biomarkers for lung cancer is of utmost significance for preclinical cancer diagnosis and treatment. Applying surface-enhanced Raman scattering (SERS) for gas sensing remains difficult due to the small Raman cross section of most gaseous molecules and interference from other components in exhaled breath. Using an Au asymmetrically coated TiO2 nanochannel membrane (Au/TiO2 NM) as the substrate, a ZIF-8-covered Au/TiO2 NM SERS sensing substrate is designed for the detection of exhaled volatile organic compounds (VOCs). Au/TiO2 NM provides uniformly amplified Raman signals for trace measurements in this design. Importantly, the interfacial nanocavities between Au nanoparticles (NPs) and metal-organic frameworks (MOFs) served as gaseous confinement cavities, which is the key to enhancing the capture and adsorption ability toward gaseous analytes. Both ends of the membrane are left open, allowing gas molecules to pass through. This facilitates the diffusion of gaseous molecules and efficient capture of the target analyte. Using benzaldehyde as a typical gas marker model of lung cancer, the Schiff base reaction with a Raman-active probe molecule 4-aminothiophene (4-ATP) pregrafted on Au NPs enabled trace and multicomponent detection. Moreover, the combination of machine learning (ML) and Raman spectroscopy eliminates subjective assessments of gaseous aldehyde species with the use of a single feature peak, allowing for more accurate identification. This membrane sensing device offers a promising design for the development of a desktop SERS analysis system for lung cancer point-of-care testing (POCT).

Determination of hexanal and heptanal in saliva samples by an adapted magnetic headspace adsorptive microextraction for diagnosis of lung cancer

In this work, an analytical method for the determination of two endogenous aldehydes (hexanal and heptanal) as lung cancer biomarkers in saliva samples is presented for the first time. The method is based on a modification of magnetic headspace adsorptive microextraction (M-HS-AME) followed by gas chromatography coupled to mass spectrometry (GC-MS). For this purpose, an external magnetic field generated by a neodymium magnet is used to hold the magnetic sorbent (i.e., CoFe₂O₄ magnetic nanoparticles embedded into a reversed-phase polymer) in the headspace of a microtube to extract the volatilized aldehydes. Subsequently, the analytes are desorbed in the appropriate solvent and the extract is injected into the GC-MS system for separation and determination. Under the optimized conditions, the method was validated and showed good analytical features in terms of linearity (at least up to 50 ng mL^-1), limits of detection (0.22 and 0.26 ng mL^-1 for hexanal and heptanal, respectively), and repeatability (RSD ≤12%). This new approach was successfully applied to saliva samples from healthy volunteers and those with lung cancer, obtaining notably differences between both groups. These results reveal the prospect of the method as potential diagnostic tool for lung cancer by saliva analysis. This work contributes to the Analytical Chemistry field presenting a double novelty: on the one hand, the use of M-HS-AME in bioanalysis is unprecedentedly proposed, thus expanding the analytical potential of this technique, and, on the other hand, the determination of hexanal and heptanal is carried out in saliva samples for the first time.

Design of stretchable and self-powered sensing device for portable and remote trace biomarkers detection

Timely and remote biomarker detection is highly desired in personalized medicine and health protection but presents great challenges in the devices reported so far. Here, we present a cost-effective, flexible and self-powered sensing device for H2S biomarker analysis in various application scenarios based on the structure of galvanic cells. The sensing mechanism is attributed to the change in electrode potential resulting from the chemical adsorption of gas molecules on the electrode surfaces. Intrinsically stretchable organohydrogels are used as solid-state electrolytes to enable stable and long-term operation of devices under stretching deformation or in various environments. The resulting open-circuit sensing device exhibits high sensitivity, low detection limit, and excellent selectivity for H2S. Its application in the non-invasive halitosis diagnosis and identification of meat spoilage is demonstrated, emerging great commercial value in portable medical electronics and food security. A wireless sensory system has also been developed for remote H2S monitoring with the participation of Bluetooth and cloud technologies. This work breaks through the shortcomings in the traditional chemiresistive sensors, offering a direction and theoretical foundation for designing wearable sensors catering to other stimulus detection requirements.

Novel Screening Tools for Lung Cancer

Screening with low-dose computed tomography has been shown to decrease lung cancer mortality. However, the issues of low detection rates and false positive results remain, highlighting the need for adjunctive tools in lung cancer screening. To this end, researchers have investigated easily applicable, minimally invasive tests with high validity. We herein review some of the more promising novel markers utilizing plasma, sputum, and airway samples.

Assessing volatile organic compounds exposure and chronic obstructive pulmonary diseases in US adults

Background

Volatile organic compounds (VOCs) are a large group of chemicals widely used in People's Daily life. There is increasing evidence of the cumulative toxicity of VOCs. However, the association between VOCs and the risk of COPD has not been reported.

Objective

We comprehensively evaluated the association between VOCs and COPD.

Methods

Our study included a total of 1,477 subjects from the National Health and Nutrition Examination Survey, including VOCs, COPD, and other variables in the average US population. Multiple regression models and smooth-curve fitting (penalty splines) were constructed to examine potential associations, and stratified analyses were used to identify high-risk groups.

Results

We found a positive association between blood benzene and blood o-xylene concentrations and COPD risk and identified a concentration relationship between the two. That is, when the blood benzene and O-xylene concentrations reached 0.28 ng/mL and 0.08 ng/mL, respectively, the risk of COPD was the highest. In addition, we found that gender, age, and MET influence the relationship, especially in women, young people, and people with low MET.

Significance

This study revealed that blood benzene and blood o-xylene were independently and positively correlated with COPD risk, suggesting that long-term exposure to benzene and O-xylene may cause pulmonary diseases, and providing a new standard of related blood VOCs concentration for the prevention of COPD.

A SIFT-MS study of positive and negative ion chemistry of the ortho-, meta- and para-isomers of cymene, cresol, and ethylphenol

Selected Ion Flow Tube Mass Spectrometry (SIFT-MS) is a soft ionisation technique based on gas phase ion-molecule reaction kinetics for the quantification of trace amounts of volatile organic compound vapours. One of its previous limitations is difficulty in resolving isomers, although this can now be overcome using different reactivities of several available reagent cations and anions (H₃O⁺, NO⁺, O₂⁺˙, O^-˙, OH^-, O₂^-˙, NO₂^-, NO₃^-). Thus, the ion-molecule reactions of these eight ions with all isomers of the aromatic compounds cymene, cresol and ethylphenol were studied to explore the possibility of their immediate identification and quantification without chromatographic separation. Rate coefficients and product ion branching ratios determined experimentally for the 72 reactions are reported. DFT calculations of their energetics confirmed the feasibility of the suggested reaction pathways. All positive ion reactions proceeded fast but largely did not discriminate between the isomers. The reactivity of the anions was much more varied. In all cases, OH^- reacts by proton transfer forming (M-H); NO₂^- and NO₃^- were unreactive. The differences observed for product ion branching ratios can be used to identify isomers approximately.

Breath Testing in the Surgical Setting: Applications, Challenges, and Future Perspectives

BACKGROUND

The potential for exhaled breath to be a valuable diagnostic tool is often overlooked as it can be difficult to imagine how a barely visible sample of breath could hold such a rich source of information about the state of our health. However, technological advances over the last 50 years have enabled us to detect volatile organic compounds (VOCs) present in exhaled breath, and this provides the key to understanding the wealth of information contained within these readily available samples.

SUMMARY

VOCs are produced as a by-product of metabolism; hence, changes in the underlying physiological processes will be reflected in the exact composition of VOCs in exhaled breath. It has been shown that characteristic changes occur in the breath VOC profile associated with certain diseases including cancer, which may enable the non-invasive detection of cancer at primary care level for patients with vague symptoms. The use of breath testing as a diagnostic tool has many advantages. It is non-invasive and quick, and the test is widely accepted by patients and clinicians. However, breath samples provide a snapshot of the VOCs present in a particular patient at a given point in time, so this can be heavily influenced by external factors such as diet, smoking, and the environment. These must all be accounted for when attempting to draw conclusions about disease status. This review focuses on the current applications for breath testing in the field of surgery, as well as discussing the challenges encountered with developing a breath test in a clinical environment. The future of breath testing in the surgical setting is also discussed, including the translation of breath research into clinical practice.

KEY MESSAGES

Analysis of VOCs in exhaled breath can identify the presence of underlying disease including cancer as well as other infectious or inflammatory conditions. Despite the patient factors, environmental factors, storage, and transport considerations that must be accounted for, breath testing demonstrates ideal characteristics for a triage test, being non-invasive, simple, and universally acceptable to patients and clinicians. Many novel biomarkers and diagnostic tests fail to translate into clinical practice because their potential clinical application does not align with the requirements and unmet needs of the healthcare sector. Non-invasive breath testing, however, has the great potential to revolutionise the early detection of diseases, such as cancer, in the surgical setting for patients with vague symptoms.

Metabolic biomarkers in lung cancer screening and early diagnosis (Review)

Late diagnosis is one of the major contributing factors to the high mortality rate of lung cancer, which is now the leading cause of cancer-associated mortality worldwide. At present, low-dose CT (LDCT) screening in the high-risk population, in which lung cancer incidence is higher than that of the low-risk population is the predominant diagnostic strategy. Although this has efficiently reduced lung cancer mortality in large randomized trials, LDCT screening has high false-positive rates, resulting in excessive subsequent follow-up procedures and radiation exposure. Complementation of LDCT examination with biofluid-based biomarkers has been documented to increase efficacy, and this type of preliminary screening can potentially reduce potential radioactive damage to low-risk populations and the burden of hospital resources. Several molecular signatures based on components of the biofluid metabolome that can possibly discriminate patients with lung cancer from healthy individuals have been proposed over the past two decades. In the present review, advancements in currently available technologies in metabolomics were reviewed, with particular focus on their possible application in lung cancer screening and early detection.

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

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

Effect of Fat to Lean Meat Ratios on the Formation of Volatile Compounds in Mutton Shashliks

This study aimed to investigate the release of volatile compounds in mutton shashliks (named as F_xL_y, x-fat cubes: 0-4; y-lean cubes: 4-0) with different fat-lean ratios before and during consumption, respectively. In total, 67 volatile compounds were identified in shashliks using gas chromatography/mass spectrometry. Aldehyde, alcohol, and ketone were the major volatile substances, accounting for more than 75% of the total volatile compounds. There were significant differences in the volatile compounds of mutton shashliks with different fat-lean ratios. With the increase of the fat content, the types and content of volatile substances released also increase. However, when the percentage of fat exceeded 50%, the number of furans and pyrazine, which were characteristic of the volatile compounds of roasted meat, was decreased. The release of volatiles during the consumption of mutton shashliks was measured using the exhaled breath test and the results showed that adding an appropriate amount of fat (<50%) helps to enrich the volatile compound components in the mouth. However, shashliks with higher fat-lean ratios (>2:2) shorten the mastication duration and weaken the breakdown of bolus particles in the consumption process, which is not conducive to the release potential of volatile substances. Therefore, setting the fat to lean ratio to 2:2 is the best choice for making mutton shashliks, as it (F₂L₂) can provide rich flavor substances for mutton shashliks before and during consumption.

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.

Validation of volatile metabolites of pulmonary oxidative injury: a bench to bedside study

Background

Changes in exhaled volatile organic compounds (VOCs) can be used to discriminate between respiratory diseases, and increased concentrations of hydrocarbons are commonly linked to oxidative stress. However, the VOCs identified are inconsistent between studies, and translational studies are lacking.

Methods

In this bench to bedside study, we captured VOCs in the headspace of A549 epithelial cells after exposure to hydrogen peroxide (H₂O₂), to induce oxidative stress, using high-capacity polydimethylsiloxane sorbent fibres. Exposed and unexposed cells were compared using targeted and untargeted analysis. Breath samples of invasively ventilated intensive care unit patients (n=489) were collected on sorbent tubes and associated with the inspiratory oxygen fraction (F _IO2 ) to reflect pulmonary oxidative stress. Headspace samples and breath samples were analysed using gas chromatography and mass spectrometry.

Results

In the cell, headspace octane concentration was decreased after oxidative stress (p=0.0013), while the other VOCs were not affected. 2-ethyl-1-hexanol showed an increased concentration in the headspace of cells undergoing oxidative stress in untargeted analysis (p=0.00014). None of the VOCs that were linked to oxidative stress showed a significant correlation with F _IO2 (R_s range: -0.015 to -0.065) or discriminated between patients with F _IO2 ≥0.6 or below (area under the curve range: 0.48 to 0.55).

Conclusion

Despite a comprehensive translational approach, validation of known and novel volatile biomarkers of oxidative stress was not possible in patients at risk of pulmonary oxidative injury. The inconsistencies observed highlight the difficulties faced in VOC biomarker validation, and that caution is warranted in the interpretation of the pathophysiological origin of discovered exhaled breath biomarkers.

Exhaled Biomarkers for Point-of-Care Diagnosis: Recent Advances and New Challenges in Breathomics

Cancers, chronic diseases and respiratory infections are major causes of mortality and present diagnostic and therapeutic challenges for health care. There is an unmet medical need for non-invasive, easy-to-use biomarkers for the early diagnosis, phenotyping, predicting and monitoring of the therapeutic responses of these disorders. Exhaled breath sampling is an attractive choice that has gained attention in recent years. Exhaled nitric oxide measurement used as a predictive biomarker of the response to anti-eosinophil therapy in severe asthma has paved the way for other exhaled breath biomarkers. Advances in laser and nanosensor technologies and spectrometry together with widespread use of algorithms and artificial intelligence have facilitated research on volatile organic compounds and artificial olfaction systems to develop new exhaled biomarkers. We aim to provide an overview of the recent advances in and challenges of exhaled biomarker measurements with an emphasis on the applicability of their measurement as a non-invasive, point-of-care diagnostic and monitoring tool.

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.

Mapping the landscape of lung cancer breath analysis: A scoping review (ELCABA)

Lung cancer is the leading cause of cancer death worldwide due to its late-stage detection. Lung cancer screening, including low-dose computed tomography (low-dose CT), provides an initial clinical solution. Nevertheless, further innovations and refinements would help to alleviate remaining limitations. The non-invasive, gentle, and fast nature of breath analysis (BA) makes this technology highly attractive to supplement low-dose CT for an improved screening algorithm. However, BA has not taken hold in everyday clinical practice. One reason might be the heterogeneity and variety of BA methods. This scoping review is a comprehensive summary of study designs, breath analytical methods, and suggested biomarkers in lung cancer. Furthermore, this synthesis provides a framework with core outcomes for future studies in lung cancer BA. This work supports future research for evidence synthesis, meta-analysis, and translation into clinical routine workflows.

Chlorine-Coordinated Pd Single Atom Enhanced the Chlorine Resistance for Volatile Organic Compound Degradation: Mechanism Study

The development of catalysts with high chlorine resistance for volatile organic compound (VOC) degradation is of great significance to achieve air purification. Herein, Pd@ZrO₂ catalysts with monodispersed Pd atoms coordinated with Cl were prepared using an in situ grown Zr-based metal-organic framework (MOF) as the sacrifice templates to enhance the chlorine resistance for VOC elimination. The residual Cl species from the Zr-MOF coordinated with Pd, forming Pd₁-Cl species during the pyrolysis. Meanwhile, abundant oxygen vacancies (V_O) were generated, which enhanced the adsorption and activation of gaseous oxygen molecules, accelerating the degradation of VOCs. In addition, the Pd@ZrO₂ catalysts exhibited satisfactory water resistance, long-term stability, and great resistance to CO and dichloromethane (DCM) for VOC elimination. In situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) results elucidated that the generation of Pd₁-Cl species in Pd@ZrO₂ suppressed the absorption of DCM, releasing more active sites for toluene and its intermediate adsorption. Simultaneously, the monodispersed Pd atoms and V_O improved the reactivity of gaseous oxygen molecule adsorption and dissociation, boosting the deep decomposition of toluene and its intermediates. This work may provide a new strategy for rationally designing high-chlorine resistance catalysts for VOC elimination to improve the atmospheric environment.

Helicene-Hydrazide Encapsulated Ethyl Cellulose as a Potential Fluorescence Sensor for Highly Specific Detection of Nonanal in Aqueous Solutions and a Proof-of-Concept Clinical Study in Lung Fluid

Over the past years, lung cancer has been one of the vital cancer-related mortalities worldwide and has inevitably exhibited the highest death rate with the subsequent need for facile and convenient diagnosis approaches to identify the severity of cancer. Previous research has reported long-chain aldehyde compounds such as hexanal, heptanal, octanal, and nonanal as potential biomarkers of lung cancer. Herein, the helicene dye-encapsulated ethyl cellulose (EC@dye-NH) nanosensors have been applied for the potentially sensitive and specific detection of long-chain aldehydes in aqueous media. The sensors contain the intrinsic hydrazide group of dye-NH, which is capable of reacting an aldehyde group via imine formation and the EC backbone. This offers the synergistic forces of hydrophobic interactions with alkyl long-chain aldehydes, which could induce self-assembly encapsulation of EC@dye-NH nanosensors and strong fluorescence responses. The addition of long-chain aldehyde would induce the complete micellar-like nanoparticle formation within 15 min in acetate buffer pH 5.0. The limit of detection (LOD) values of EC@dye-NH nanosensors toward heptanal, octanal, and nonanal were 40, 100, and 10 μM, respectively, without interference from the lung fluid matrices and short-chain aldehydes. For practical applicability, this sensing platform was developed for quantification of the long-chain aldehydes in lung fluid samples with 98-101% recoveries. This EC@dye-NH nanosensor was applied to quantify nonanal contents in lung fluid samples. The results of this method based on EC@dye-NH nanosensors were then validated using standard gas chromatography-mass spectrometry (GC-MS), which gave results consistent with the proposed method. With intracellular imaging application, the EC@dye-NH nanosensors demonstrated excellent intracellular uptake and strong green fluorescence emission upon introducing the nonanal into the lung cancer cells (A549). Thus, the developed nanosensing approach served as the potential fluorescent probes in medical and biological fields, especially for lung cancer disease diagnosis based on highly selective and sensitive detection of long-chain aldehydes.

Measurement of Exhaled Volatile Organic Compounds as a Biomarker for Personalised Medicine: Assessment of Short-Term Repeatability in Severe Asthma

The measurement of exhaled volatile organic compounds (VOCs) in exhaled breath (breathomics) represents an exciting biomarker matrix for airways disease, with early research indicating a sensitivity to airway inflammation. One of the key aspects to analytical validity for any clinical biomarker is an understanding of the short-term repeatability of measures. We collected exhaled breath samples on 5 consecutive days in 14 subjects with severe asthma who had undergone extensive clinical characterisation. Principal component analysis on VOC abundance across all breath samples revealed no variance due to the day of sampling. Samples from the same patients clustered together and there was some separation according to T2 inflammatory markers. The intra-subject and between-subject variability of each VOC was calculated across the 70 samples and identified 30.35% of VOCs to be erratic: variable between subjects but also variable in the same subject. Exclusion of these erratic VOCs from machine learning approaches revealed no apparent loss of structure to the underlying data or loss of relationship with salient clinical characteristics. Moreover, cluster evaluation by the silhouette coefficient indicates more distinct clustering. We are able to describe the short-term repeatability of breath samples in a severe asthma population and corroborate its sensitivity to airway inflammation. We also describe a novel variance-based feature selection tool that, when applied to larger clinical studies, could improve machine learning model predictions.

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

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

Recent insights in the role of biomarkers in severe asthma management

Contemporary asthma management requires a proactive and individualized approach, combining precision diagnosis and personalized treatment. The introduction of biologic therapies for severe asthma to everyday clinical practice, increases the need for specific patient selection, prediction of outcomes and monitoring of these costly and long-lasting therapies. Several biomarkers have been used in asthma in disease identification, prediction of asthma severity and prognosis, and response to treatment. Novel advances in the area of personalized medicine regarding disease phenotyping and endotyping, encompass the development and application of reliable biomarkers, accurately quantified using robust and reproducible methods. The availability of powerful omics technologies, together with integrated and network-based genome data analysis, and microbiota changes quantified in serum, body fluids and exhaled air, will lead to a better classification of distinct phenotypes or endotypes. Herein, in this review we discuss on currently used and novel biomarkers for the diagnosis and treatment of asthma.

Liquid Crystal Droplet-Based Biosensors: Promising for Point-of-Care Testing

The development of biosensing platforms has been impressively accelerated by advancements in liquid crystal (LC) technology. High response rate, easy operation, and good stability of the LC droplet-based biosensors are all benefits of the long-range order of LC molecules. Bioprobes emerged when LC droplets were combined with biotechnology, and these bioprobes are used extensively for disease diagnosis, food safety, and environmental monitoring. The LC droplet biosensors have high sensitivity and excellent selectivity, making them an attractive tool for the label-free, economical, and real-time detection of different targets. Portable devices work well as the accessory kits for LC droplet-based biosensors to make them easier to use by anyone for on-site monitoring of targets. Herein, we offer a review of the latest developments in the design of LC droplet-based biosensors for qualitative target monitoring and quantitative target analysis.

Diagnostic Approaches For COVID-19: Lessons Learned and the Path Forward

Coronavirus disease 2019 (COVID-19) is a transmitted respiratory disease caused by the infection of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although humankind has experienced several outbreaks of infectious diseases, the COVID-19 pandemic has the highest rate of infection and has had high levels of social and economic repercussions. The current COVID-19 pandemic has highlighted the limitations of existing virological tests, which have failed to be adopted at a rate to properly slow the rapid spread of SARS-CoV-2. Pandemic preparedness has developed as a focus of many governments around the world in the event of a future outbreak. Despite the largely widespread availability of vaccines, the importance of testing has not diminished to monitor the evolution of the virus and the resulting stages of the pandemic. Therefore, developing diagnostic technology that serves as a line of defense has become imperative. In particular, that test should satisfy three criteria to be widely adopted: simplicity, economic feasibility, and accessibility. At the heart of it all, it must enable early diagnosis in the course of infection to reduce spread. However, diagnostic manufacturers need guidance on the optimal characteristics of a virological test to ensure pandemic preparedness and to aid in the effective treatment of viral infections. Nanomaterials are a decisive element in developing COVID-19 diagnostic kits as well as a key contributor to enhance the performance of existing tests. Our objective is to develop a profile of the criteria that should be available in a platform as the target product. In this work, virus detection tests were evaluated from the perspective of the COVID-19 pandemic, and then we generalized the requirements to develop a target product profile for a platform for virus detection.

Quantitative Analysis of Exhaled Breath Collected on Filter Substrates via Low-Temperature Plasma Desorption/Ionization Mass Spectrometry

Breath analysis has attracted increasing attention in recent years due to its great potential for disease diagnostics at early stages and for clinical drug monitoring. There are several recent examples of successful development of real-time, in vivo quantitative analysis of exhaled breath metabolites via mass spectrometry. On the other hand, current mass spectrometer accessibility limitations restrict point-of-care applications. Here now, an offline method is developed for quantitative analysis of exhaled breath collected on inexpensive filter substrates for direct desorption and ionization by using low-temperature plasma-mass spectrometry (LTP-MS). In particular, different operating conditions of the ionization source were systematically studied to optimize desorption/ionization by using glycerol, a low volatility compound. Applications with respect to propofol, γ-valprolactone, and nicotine analysis in exhaled breath are demonstrated in this study. The effects of several filter substrate properties, including filter material and pore size, on the analyte signal were characterized. Cellulose filter papers performed best with the present analytes. In addition, filters with smaller pores enabled a more efficient sample collection. Furthermore, sample-collection flow rate was determined to have a very significant effect, with slower flow rates yielding the best results. It was also found that filters loaded with sample can be successfully stored in glass vials with no observable sample loss even after 3 days. Limits of detection under optimized conditions are shown to be competitive or significantly better compared with relevant techniques and with additional benefits of cost-efficiency and sample storage capabilities.

Palladium-Doped Single-Walled Carbon Nanotubes as a New Adsorbent for Detecting and Trapping Volatile Organic Compounds: A First Principle Study

Volatile organic compounds (VOCs) are in the vapor state in the atmosphere and are considered pollutants. Density functional theory (DFT) calculations with the wb97xd exchange correlation functional and the 6-311+G(d,p) basis set are carried out to explore the potential possibility of palladium-doped single-walled carbon nanotubes (Pd/SWCNT-V), serving as the resource for detecting and/or adsorbing acetonitrile (ACN), styrene (STY), and perchloroethylene (PCE) molecules as VOCs. The suggested adsorbent in this study is discussed with structural parameters, frontier molecular orbital theory, molecular electrical potential surfaces (MEPSs), natural bond orbital (NBO) analyses, and the density of states. Furthermore, following the Bader theory of atoms in molecules (AIM), the topological properties of the electron density contributions for intermolecular interactions are analyzed. The obtained results show efficient VOC loading via a strong chemisorption process with a mean adsorption energy of −0.94, −1.27, and −0.54 eV for ACN, STY, and PCE, respectively. Our results show that the Pd/SWCNT-V can be considered a good candidate for VOC removal from the environment.

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.

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

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

Predictive performance of selected breath volatile organic carbon compounds in stage 1 lung cancer

Background

Lung cancer remains the leading cause of cancer deaths accounting for almost 25% of all cancer deaths. Breath-based volatile organic compounds (VOCs) have been studied in lung cancer but previous studies have numerous limitations. We conducted a prospective matched case to control study of the ability of preidentified VOC performance in the diagnosis of stage 1 lung cancer (S1LC).

Methods

Study participants were enrolled in a matched case to two controls study. A case was defined as a patient with biopsy-confirmed S1LC. Controls included a matched control, by risk factors, and a housemate control who resided in the same residence as the case. We included 88 cases, 88 risk-matched, and 49 housemate controls. Each participant exhaled into a Tedlar^® bag which was analyzed using gas chromatography-mass spectrometry. For each study participant’s breath sample, the concentration of thirteen previously identified VOCs were quantified and assessed using area under the curve in the detection of lung cancer.

Results

Four VOCs were above the limit of detection in more than 10% of the samples. Acetoin was the only compound that was significantly associated with S1LC. Acetoin concentration below the 10^th percentile (0.026 µg/L) in the training data had accuracy of 0.610 (sensitivity =0.649; specificity =0.583) in the test data. In multivariate logistic models, the best performing models included Acetoin alone (AUC =0.650).

Conclusions

Concentration of Acetoin in exhaled breath has low discrimination performance for S1LC cases and controls, while there was not enough evidence for twelve additional published VOCs.