Current Challenges in Volatile Organic Compounds Analysis as Potential Biomarkers of Cancer

Miniaturized Sniffing Device based on an Array of Fluorescent Carbon Quantum Dots and Metallic Nanoclusters Efficiently Identifies Hematologic Malignancy in Adults

The study demonstrates the potential of an optical nose made by depositing an array of fluorescent nanomaterials on a paper substrate for the early detection of leukemia in adults. This is based on the fact that blood volatile organic compounds (VOCs) are useful leukemia biomarkers. The integrated design was miniaturized and comprised both sensing zones and a sample holding zone, which were installed on a small sheet of paper within a miniature cubic reaction chamber fabricated by using 3D printing technology. The sensing device, comprising seven fluorescent sensing elements, namely, metal nanoclusters, quantum dots, and carbon dots was capable of detecting VOCs in the blood headspace and providing a colorimetric signature that could discriminate between blood samples from healthy and cancerous individuals. A total of 70 new leukemia cases and 51 healthy controls aged 20-50 years were studied. The device required a 60 μL portion of the blood sample and reacted to blood VOCs after 3 h when kept at 50 °C. The imaging data from the device was processed by linear discriminant analysis, and the results confirmed efficient identification of patient samples from healthy samples with 100% accuracy. Overall, the array system is noninvasive (or minimally invasive), portable, fast, inexpensive, and requires only a small amount of blood sample.

Early Detection of Ventilator-associated Pneumonia From Exhaled Breath in Intensive Care Unit Patients

OBJECTIVE

Evaluate associations between volatile organic compounds (VOCs) in heat and moisture exchange (HME) filters and the presence of ventilator-associated pneumonia (VAP).

BACKGROUND

Clinical diagnostic criteria for VAP have poor interobserver reliability, and cultures are slow to result. Exhaled breath contains VOCs related to gram-negative bacterial proliferation, the most identified organisms in VAP. We hypothesized that exhaled VOCs on HME filters can predict nascent VAP in mechanically ventilated intensive care unit patients.

METHODS

Gas chromatography-mass spectrometry was used to analyze 111 HME filters from 12 intubated patients who developed VAP. Identities and relative amounts of VOCs were associated with dates of clinical suspicion and culture confirmation of VAP. Matched pairs t tests were performed to compare VOC abundances in HME filters collected within 3 days pre and postclinical suspicion of VAP (pneumonia days), versus outside of these days (non-pneumonia days). A receiver operating characteristic curve was generated to determine the diagnostic potential of VOCs.

RESULTS

Carbon disulfide, associated with the proliferation of certain gram-negative bacteria, was found in samples collected during pneumonia days for 11 of 12 patients. Carbon disulfide levels were significantly greater ( P = 0.0163) for filters on pneumonia days. The Area Under the Curve of the Reciever Operating Characteristic curve (AUC ROC) for carbon disulfide was 0.649 (95% CI: 0.419-0.88).

CONCLUSIONS

Carbon disulfide associated with gram-negative VAP can be identified on HME filters up to 3 days before the initial clinical suspicion, and approximately a week before culture confirmation. This suggests VOC sensors may have potential as an adjunctive method for early detection of VAP.

Identification of volatile biomarkers for lung cancer from different histological sources: A comprehensive study

The identification of noninvasive volatile biomarkers for lung cancer is a significant clinical challenge. Through in vitro studies, the recognition of altered metabolism in cell volatile organic compound (VOC) emitting profile, along with the occurrence of oncogenesis, provides insight into the biochemical pathways involved in the production and metabolism of lung cancer volatile biomarkers. In this research, for the first time, a comprehensive comparative analysis of the volatile metabolites in NSCLS cells (A549), SCLC cells (H446), lung normal cells (BEAS-2B), as well as metabolites in both the oxidative stress (OS) group and control group. Specifically, the combination of eleven VOCs, including n-dodecane, acetaldehyde, isopropylbenzene, p-ethyltoluene and cis-1,3-dichloropropene, exhibited potential as volatile biomarkers for lung cancer originating from two different histological sources. Furthermore, the screening process in A549 cell lines resulted in the identification of three exclusive biomarkers, isopropylbenzene, formaldehyde and bromoform. Similarly, the exclusive biomarkers 1,2,4-trimethylbenzene, p-ethyltoluene, and cis-1,3-dichloropropene were present in the H446 cell line. Additionally, significant changes in trans-2-pentene, acetaldehyde, 1,2,4-trimethylbenzene, and bromoform were observed, indicating a strong association with OS. These findings highlight the potential of volatile biomarkers profiling as a means of noninvasive identification for lung cancer diagnosis.

Metabolomics for searching validated biomarkers in cancer studies: a decade in review

INTRODUCTION

In the dynamic landscape of modern healthcare, the ability to anticipate and diagnose diseases, particularly in cases where early treatment significantly impacts outcomes, is paramount. Cancer, a complex and heterogeneous disease, underscores the critical importance of early diagnosis for patient survival. The integration of metabolomics information has emerged as a crucial tool, complementing the genotype-phenotype landscape and providing insights into active metabolic mechanisms and disease-induced dysregulated pathways.

AREAS COVERED

This review explores a decade of developments in the search for biomarkers validated within the realm of cancer studies. By critically assessing a diverse array of research articles, clinical trials, and studies, this review aims to present an overview of the methodologies employed and the progress achieved in identifying and validating biomarkers in metabolomics results for various cancer types.

EXPERT OPINION

Through an exploration of more than 800 studies, this review has allowed to establish a general idea about state-of-art in the search of biomarkers in metabolomics studies involving cancer which include certain level of results validation. The potential for metabolites as diagnostic markers to reach the clinic and make a real difference in patient health is substantial, but challenges remain to be explored.

Volatile communication in Actinobacteria: a language for secondary metabolism regulation

BACKGROUND

Volatile compounds are key elements in the interaction and communication between organisms at both interspecific and intraspecific levels. In complex bacterial communities, the emission of these fast-acting chemical messengers allows an exchange of information even at a certain distance that can cause different types of responses in the receiving organisms. The changes in secondary metabolism as a consequence of this interaction arouse great interest in the field of searching for bioactive compounds since they can be used as a tool to activate silenced metabolic pathways. Regarding the great metabolic potential that the Actinobacteria group presents in the production of compounds with attractive properties, we evaluated the reply the emitted volatile compounds can generate in other individuals of the same group.

RESULTS

We recently reported that volatile compounds released by different streptomycete species trigger the modulation of biosynthetic gene clusters in Streptomyces spp. which finally leads to the activation/repression of the production of secondary metabolites in the recipient strains. Here we present the application of this rationale in a broader bacterial community to evaluate volatiles as signaling effectors that drive the activation of biosynthesis of bioactive compounds in other members of the Actinobacteria group. Using cocultures of different actinobacteria (where only the volatile compounds reach the recipient strain) we were able to modify the bacterial secondary metabolism that drives overproduction (e.g., granaticins, actiphenol, chromomycins) and/or de novo production (e.g., collismycins, skyllamycins, cosmomycins) of compounds belonging to different chemical species that present important biological activities.

CONCLUSIONS

This work shows how the secondary metabolism of different Actinobacteria species can vary significantly when exposed in co-culture to the volatile compounds of other phylum-shared bacteria, these effects being variable depending on strains and culture media. This approach can be applied to the field of new drug discovery to increase the battery of bioactive compounds produced by bacteria that can potentially be used in treatments for humans and animals.

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.

Optimization of volatile organic compounds sampling from dairy cow exhaled breath using polymer-based solid-phase extraction cartridges for gas chromatographic analysis

We explored appropriate technical setups for the detection of volatile organic compounds (VOCs) from exhaled cow breath by comparing six different polymer-based solid-phase extraction (SPE) cartridges currently on the market for gas chromatography/mass spectrometry (GC-MS) screening. Exhaled breath was sampled at a single timepoint from five lactating dairy cows using six different SPE cartridges (Bond Elut ENV (ENV); Chromabond HRX (HRX); Chromabond HRP (HRP); Chromabond HLB (HLB); Chromabond HR-XCW (XCW) and Chromabond HR-XAW (XAW)). The trapped VOCs were analyzed by dynamic headspace vacuum in-tube extraction GC-MS (DHS-V-ITEX-GC-MS). Depending on the SPE cartridge, we detected 1174-1312 VOCs per cartridge. Most VOCs were alkenes, alkanes, esters, ketones, alcohols, aldehydes, amines, nitriles, ethers, amides, carboxylic acids, alkynes, azoles, terpenes, pyridines, or sulfur-containing compounds. The six SPE cartridges differed in their specificity for the chemical compounds, with the XAW cartridge showing the best specificity for ketones. The greatest differences between the tested SPE cartridges appeared in the detection of specific VOCs. In total, 176 different VOCs were detected with a match factor >80%. The greatest number of specific VOCs was captured by XAW (149), followed by ENV (118), HLB (117), HRP (115), HRX (114), and XCW (114). We conclude that the tested SPE cartridges are suitable for VOC sampling from exhaled cow breath, but the SPE cartridge choice enormously affects the detected chemical groups and the number of detected VOCs. Therefore, an appropriate SPE adsorbent cartridge should be selected according to our proposed inclusion criteria. For targeted metabolomics approaches, the SPE cartridge choice depends on the VOCs or chemical compound groups of interest based on our provided VOC list. For untargeted approaches without information on the animals' metabolic condition, we suggest using multi-sorbent SPE cartridges or multiple cartridges per animal.

Identification of breath volatile organic compounds to distinguish pancreatic adenocarcinoma, pancreatic cystic neoplasm, and patients without pancreatic lesions

BACKGROUND

Volatile organic compounds (VOCs) are a promising potential biomarker that may be able to identify the presence of cancers.

AIM

To identify exhaled breath VOCs that distinguish pancreatic ductal adenocarcinoma (PDAC) from intraductal papillary mucinous neoplasm (IPMN) and healthy volunteers.

METHODS

We collected exhaled breath from histologically proven PDAC patients, radiological diagnosis IPMN, and healthy volunteers using the ReCIVA® device between 10/2021-11/2022. VOCs were identified by thermal desorption-gas chromatography/field-asymmetric ion mobility spectrometry and compared between groups.

RESULTS

A total of 156 participants (44% male, mean age 62.6 ± 10.6) were enrolled (54 PDAC, 42 IPMN, and 60 controls). Among the nine VOCs identified, two VOCs that showed differences between groups were dimethyl sulfide [0.73 vs 0.74 vs 0.94 arbitrary units (AU), respectively; P = 0.008] and acetone dimers (3.95 vs 4.49 vs 5.19 AU, respectively; P < 0.001). After adjusting for the imbalance parameters, PDAC showed higher dimethyl sulfide levels than the control and IPMN groups, with adjusted odds ratio (aOR) of 6.98 (95%CI: 1.15-42.17) and 4.56 (1.03-20.20), respectively (P < 0.05 both). Acetone dimer levels were also higher in PDAC compared to controls and IPMN (aOR: 5.12 (1.80-14.57) and aOR: 3.35 (1.47-7.63), respectively (P < 0.05 both). Acetone dimer, but not dimethyl sulfide, performed better than CA19-9 in PDAC diagnosis (AUROC 0.910 vs 0.796). The AUROC of acetone dimer increased to 0.936 when combined with CA19-9, which was better than CA19-9 alone (P < 0.05).

CONCLUSION

Dimethyl sulfide and acetone dimer are VOCs that potentially distinguish PDAC from IPMN and healthy participants. Additional prospective studies are required to validate these findings.

Interaction of the III-As monolayer with SARS-CoV-2 biomarkers: implications for biosensor development

The emergence of SARS-CoV-2 in 2019 led to the global COVID-19 pandemic, highlighting the urgency for developing cost-effective and non-invasive methods to detect diseases at an early stage. Human breath, rich in volatile organic compounds (VOCs), is promising for cost-effective and rapid disease detection, with specific VOCs like methanol, ethanal, butanone, acetone, and ethyl butyrate linked to COVID-19. Recent advances in biomarker detection and gas sensing with 2D materials, particularly III-As monolayers like BAs, GaAs, and AlAs, offer high sensitivity at low concentrations, providing a novel avenue for exploring their potential in detecting COVID-19 biomarkers. This article aims to examine the effects of adsorption on different properties of III-Arsenide (BAs, GaAs and AlAs) monolayers, particularly in connection with SARS-CoV-2 biomarkers. In order to examine the interaction between the monolayers and biomarkers, first-principles computations within the framework of density functional theory (DFT) are utilized. The present study involves an investigation of the modifications in the band structure, density of states (DOS), work function, electron density difference, and optical properties (reflectance and absorbance) of III-As monolayers, with the aim of assessing their viability for the detection of SARS-CoV-2 biomarkers along with interfering gases such as CO2 and H2O. It is observed that VOCs induce a notable change in the work function of GaAs which serves as an indicator of the presence of these biomarkers. However, the changes in work function are not as substantial as those for AlAs and BAs. Additionally, the chemiresistive sensitivity, optical sensitivity and recovery time of III-As are investigated. The findings suggest that the pristine GaAs monolayer displays a significant level of sensitivity and selectivity towards the SARS-CoV-2 biomarkers, rendering it a material with potential for utilization in sensing applications. Furthermore, it has been observed that the recovery time of the GaAs monolayer subsequent to its exposure to the VOC biomarkers lies within an acceptable threshold. Upon exposure to UV light, the recovery time is further reduced. The outcomes of our study indicate that GaAs monolayers exhibit considerable potential as chemiresistive, work function-based and optical sensors for the precise and discerning identification of VOCs linked to the SARS-CoV-2 virus compared to the other two III-As monolayers.

Dogs can detect an odor profile associated with Staphylococcus aureus biofilms in cultures and biological samples

Introduction

The study investigated the utilization of odor detection dogs to identify the odor profile of Staphylococcus aureus (S. aureus) biofilms in pure in vitro samples and in in vivo biosamples from animals and humans with S. aureus periprosthetic joint infection (PJI). Biofilms form when bacterial communities aggregate on orthopedic implants leading to recalcitrant infections that are difficult to treat. Identifying PJI biofilm infections is challenging, and traditional microbiological cultures may yield negative results even in the presence of clinical signs.

Methods

Dogs were trained on pure in vitro S. aureus biofilms and tested on lacrimal fluid samples from an in vivo animal model (rabbits) and human patients with confirmed S. aureus PJI.

Results

The results demonstrated that dogs achieved a high degree of sensitivity and specificity in detecting the odor profile associated with S. aureus biofilms in rabbit samples. Preliminary results suggest that dogs can recognize S. aureus volatile organic compounds (VOCs) in human lacrimal fluid samples.

Discussion

Training odor detection dogs on in vitro S. aureus, may provide an alternative to obtaining clinical samples for training and mitigates biosecurity hazards. The findings hold promise for culture-independent diagnostics, enabling early disease detection, and improved antimicrobial stewardship. In conclusion, this research demonstrates that dogs trained on in vitro S. aureus samples can identify the consistent VOC profile of PJI S. aureus biofilm infections. The study opens avenues for further investigations into a retained VOC profile of S. aureus biofilm infection. These advancements could revolutionize infectious disease diagnosis and treatment, leading to better patient outcomes and addressing the global challenge of antimicrobial resistance.

Exploring stingless bee honey from selected regions of Peninsular Malaysia through gas chromatography-mass spectrometry-based untargeted metabolomics

Volatile organic compounds in honey are known for their considerable impact on the organoleptic properties of honey, such as aroma, flavor, taste, and texture. The type and composition of volatile organic compounds are influenced by entomological, geographical, and botanical origins; thus, these compounds have the potential to be chemical markers. Sixty-two volatile compounds were identified using gas chromatography-mass spectrometry from 30 Heterotrigona itama (H. itama) honey samples from 3 different geographical origins. Hydrocarbons and benzene derivatives were the dominant classes of volatile organic compounds in the samples. Both clustering and discriminant analyses demonstrated a clear separation between samples from distant origins (Kedah and Perak), and the volcano plot supported it. The reliability and predictability of the partial least squares-discriminant analysis model from the discriminant analysis were validated using cross-validation (R2 : 0.93; Q2 : 0.83; accuracy: 0.97) and the permutation test (p < 0.001), and the output depicted that the model is legitimate. In combination with the variable importance of projection (VIP > 1.0) and the Kruskal-Wallis test (p < 0.01), 19 volatile organic compounds (encompassed aldehydes, benzene derivatives, esters, hydrocarbons, and terpenoids) were sorted and named potent chemical markers in classifying honey samples from three geographical origins. In brief, this study illustrated that volatile organic compounds of stingless honey originated from the same bee species, but different geographical origins could be applied as chemical markers.

Detection of urological cancers by the signature of organic volatile compounds in urine, from dogs to electronic noses

PURPOSE OF REVIEW

Urine volatile organic compound (VOC) testing for early detection of urological cancers is a minimally invasive and promising method. The objective of this review was to present the results of recently published work on this subject.

RECENT FINDINGS

Organic volatile compounds are produced through oxidative stress and peroxidation of cell membranes, and they are eliminated through feces, urine, and sweat. Studies looking for VOCs in urine for the diagnosis of urological cancers have mostly focused on bladder and prostate cancers. However, the number of patients included in the studies was small. The electronic nose was the most widely used means of detecting VOCs in urine for the detection of urological cancers. MOS sensors and pattern recognition machine learning were more used for the composition of electronic noses. Early detection of urological cancers by detection of VOCs in urine is a method with encouraging results with sensitivities ranging from 27 to 100% and specificities ranging from 72 to 94%.

SUMMARY

The olfactory signature of urine from patients with urological cancers is a promising biomarker for the early diagnosis of urological cancers. The electronic nose with its ability to recognize complex odors is an excellent alterative to canine diagnosis and analytical techniques. Nevertheless, additional research improving the technology of Enoses and the methodology of the studies is necessary for its implementation in daily clinical practice.

Does the last 20 years paradigm of clinical research using volatile organic compounds to non-invasively diagnose cancer need to change? Challenges and future direction

PURPOSE

Volatile organic compounds (VOCs) have shown great potential as novel biomarkers for cancer detection; however, comprehensive quantitative analysis is lacking. In this study, we performed a bibliometric analysis of non-invasive cancer diagnosis using VOCs to better characterise international trends and to predict future hotspots in this field, and then we focussed on human studies to analyse clinical characteristics for presenting the current controversies and future perspectives of further clinical work.

METHODS

Publications, from 2002 to 2022, were retrieved from the Web of Science Core Collection database. CiteSpace and VOSviewer were used to generate network maps and identify the annual publications, top countries, authors, institutions, journals, references, and keywords. Then, we further screened clinical trials, and the key information was extracted into Microsoft Excel for further systematical analysis.

RESULTS

Six hundred and forty-one articles were identified to evaluate research trends, of which 301 clinical trials were selected for further systematical analysis. Overall, the annual publications in this area increased, with an overall upward trend, while the quality of clinical research remains remarkably uneven.

CONCLUSION

The study of non-invasive cancer diagnosis using VOCs would continue to be an active field. However, without stringent clinical design criteria, most suitable acquisition and analysis devices and statistical approaches, a list of exclusive, specific, reliable and reproducible VOCs to identify a disease and these VOCs appearing in a breath at detectable levels at early stage disease, the clinical utility of VOC tests will be difficult to have any breakthroughs.

Identification of Volatile Markers of Colorectal Cancer from Tumor Tissues Using Volatilomic Approach

The human body releases numerous volatile organic compounds (VOCs) through tissues and various body fluids, including breath. These compounds form a specific chemical profile that may be used to detect the colorectal cancer CRC-related changes in human metabolism and thereby diagnose this type of cancer. The main goal of this study was to investigate the volatile signatures formed by VOCs released from the CRC tissue. For this purpose, headspace solid-phase microextraction gas chromatography-mass spectrometry was applied. In total, 163 compounds were detected. Both cancerous and non-cancerous tissues emitted 138 common VOCs. Ten volatiles (2-butanone; dodecane; benzaldehyde; pyridine; octane; 2-pentanone; toluene; p-xylene; n-pentane; 2-methyl-2-propanol) occurred in at least 90% of both types of samples; 1-propanol in cancer tissue (86% in normal one), acetone in normal tissue (82% in cancer one). Four compounds (1-propanol, pyridine, isoprene, methyl thiolacetate) were found to have increased emissions from cancer tissue, whereas eleven showed reduced release from this type of tissue (2-butanone; 2-pentanone; 2-methyl-2-propanol; ethyl acetate; 3-methyl-1-butanol; d-limonene; tetradecane; dodecanal; tridecane; 2-ethyl-1-hexanol; cyclohexanone). The outcomes of this study provide evidence that the VOCs signature of the CRC tissue is altered by the CRC. The volatile constituents of this distinct signature can be emitted through exhalation and serve as potential biomarkers for identifying the presence of CRC. Reliable identification of the VOCs associated with CRC is essential to guide and tune the development of advanced sensor technologies that can effectively and sensitively detect and quantify these markers.

A Novel Urine Test Biosensor Platform for Early Lung Cancer Detection

Lung cancer is the leading cause of cancer-related mortality worldwide. Early detection is essential to achieving a better outcome and prognosis. Volatile organic compounds (VOCs) reflect alterations in the pathophysiology and body metabolism processes, as shown in various types of cancers. The biosensor platform (BSP) urine test uses animals' unique, proficient, and accurate ability to scent lung cancer VOCs. The BSP is a testing platform for the binary (negative/positive) recognition of the signature VOCs of lung cancer by trained and qualified Long-Evans rats as biosensors (BSs). The results of the current double-blind study show high accuracy in lung cancer VOC recognition, with 93% sensitivity and 91% specificity. The BSP test is safe, rapid, objective and can be performed repetitively, enabling periodic cancer monitoring as well as an aid to existing diagnostic methods. The future implementation of such urine tests as routine screening and monitoring tools has the potential to significantly increase detection rate as well as curability rates with lower healthcare expenditure. This paper offers a first instructive clinical platform utilizing VOC's in urine for detection of lung cancer using the innovative BSP to deal with the pressing need for an early lung cancer detection test tool.

Fugitive emissions of volatile organic compounds from the pharmaceutical industry in China based on leak detection and repair monitoring, atmospheric prediction, and health risk assessment

In this study, a leak detection and repair program was conducted on five pharmaceutical factories in China to analyze the volatile organic compounds (VOCs) emission characteristics of leaking equipment. The results indicated that the monitored components were mainly flanges, accounting for 70.23% of the total, and open-ended lines were the components most prone to leaks. The overall percentage of VOCs emissions reduction after the repair was 20.50%, and flanges were the most repairable components, with an average emission reduction of 47.5 kg/a for each flange. In addition, atmospheric predictions were conducted for the VOCs emissions before and after the repair of the components at the research factories. The atmospheric predictions showed that emissions from equipment and facilities have a noticeable impact on VOCs concentration at boundary and the emissions are positively correlated with the pollution source strength. The hazard quotient of the investigated factories was lower than the acceptable risk level set by the US Environmental Protection Agency (EPA). The quantitative assessment of the lifetime cancer risk showed that the risk levels of factories A, C, and D exceeded the EPA's acceptable risk level, and the on-site workers were exposed to inhalation cancer risk.

Chemoresistive Nanosensors Employed to Detect Blood Tumor Markers in Patients Affected by Colorectal Cancer in a One-Year Follow Up

Colorectal cancer (CRC) represents 10% of the annual tumor diagnosis and deaths occurring worldwide. Given the lack of specific symptoms, which could determine a late diagnosis, the research for specific CRC biomarkers and for innovative low-invasive methods to detect them is crucial. Therefore, on the basis of previously published results, some volatile organic compounds (VOCs), detectable through gas sensors, resulted in particularly promising CRC biomarkers, making these sensors suitable candidates to be employed in CRC screening devices. A new device was employed here to analyze the exhalations of blood samples collected from CRC-affected patients at different stages of their pre- and post-surgery therapeutic path, in order to assess the sensor’s capability for discriminating among these samples. The stages considered were: the same day of the surgical treatment (T1); before the hospital discharge (T2); after one month and after 10–12 months from surgery (T3 and T4, respectively). This device, equipped with four different sensors based on different metal–oxide mixtures, enabled a distinction between T1 and T4 with a sensitivity and specificity of 93% and 82%, respectively, making it suitable for clinical follow-up protocols, patient health status monitoring and to detect possible post-treatment relapses.

Hybrid volatilomics in cancer diagnosis by HS-GC-FID fingerprinting

Assessing volatile organic compounds (VOCs) as cancer signatures is one of the most promising techniques toward developing non-invasive, simple, and affordable diagnosis. Here, we have evaluated the feasibility of employing static headspace extraction (HS) followed by gas chromatography with flame ionization detector (GC-FID) as a screening tool to discriminate between cancer patients (head and neck-HNC,n= 15; and gastrointestinal cancer-GIC,n= 19) and healthy controls (n= 37) on the basis of a non-target (fingerprinting) analysis of oral fluid and urine. We evaluated the discrimination considering a single bodily fluid and adopting the hybrid approach, in which the oral fluid and urinary VOCs profiles were combined through data fusion. We used supervised orthogonal partial least squares discriminant analysis for classification, and we assessed the prediction power of the models by analyzing the values of goodness of prediction (Q²Y), area under the curve (AUC), sensitivity, and specificity. The individual models HNC urine, HNC oral fluid, and GIC oral fluid successfully discriminated between healthy controls and positive samples (Q²Y = 0.560, 0.525, and 0.559; AUC = 0.814, 0.850, and 0.926; sensitivity = 84.8, 70.2, and 78.6%; and specificity = 82.3; 81.5; 87.5%, respectively), whereas GIC urine was not adequate (Q²Y = 0.292, AUC = 0.694, sensitivity = 66.1%, and specificity = 77.0%). Compared to the respective individual models, Q²Y for the hybrid models increased (0.623 for hybrid HNC and 0.562 for hybrid GIC). However, sensitivity was higher for HNC urine and GIC oral fluid than for hybrid HNC (75.6%) and hybrid GIC (69.8%), respectively. These results suggested that HS-GC-FID fingerprinting is suitable and holds great potential for cancer screening. Additionally, the hybrid approach tends to increase the predictive power if the individual models present suitable quality parameter values. Otherwise, it is more advantageous to use a single body fluid for analysis.

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.

Remote Medical Scent Detection of Cancer and Infectious Diseases With Dogs and Rats: A Systematic Review

BACKGROUND

Remote medical scent detection of cancer and infectious diseases with dogs and rats has been an increasing field of research these last 20 years. If validated, the possibility of implementing such a technique in the clinic raises many hopes. This systematic review was performed to determine the evidence and performance of such methods and assess their potential relevance in the clinic.

METHODS

Pubmed and Web of Science databases were independently searched based on PRISMA standards between 01/01/2000 and 01/05/2021. We included studies aiming at detecting cancers and infectious diseases affecting humans with dogs or rats. We excluded studies using other animals, studies aiming to detect agricultural diseases, diseases affecting animals, and others such as diabetes and neurodegenerative diseases. Only original articles were included. Data about patients' selection, samples, animal characteristics, animal training, testing configurations, and performances were recorded.

RESULTS

A total of 62 studies were included. Sensitivity and specificity varied a lot among studies: While some publications report low sensitivities of 0.17 and specificities around 0.29, others achieve rates of 1 sensitivity and specificity. Only 6 studies were evaluated in a double-blind screening-like situation. In general, the risk of performance bias was high in most evaluated studies, and the quality of the evidence found was low.

CONCLUSIONS

Medical detection using animals' sense of smell lacks evidence and performances so far to be applied in the clinic. What odors the animals detect is not well understood. Further research should be conducted, focusing on patient selection, samples (choice of materials, standardization), and testing conditions. Interpolations of such results to free running detection (direct contact with humans) should be taken with extreme caution. Considering this synthesis, we discuss the challenges and highlight the excellent odor detection threshold exhibited by animals which represents a potential opportunity to develop an accessible and non-invasive method for disease detection.

Volatilomics as an Emerging Strategy to Determine Potential Biomarkers of Female Infertility: A Pilot Study

Due to its high prevalence, infertility has become a prominent public health issue, posing a significant challenge to modern reproductive medicine. Some clinical conditions that lead to female infertility include polycystic ovary syndrome (PCOS), endometriosis, and premature ovarian failure (POF). Follicular fluid (FF) is the biological matrix that has the most contact with the oocyte and can, therefore, be used as a predictor of its quality. Volatilomics has emerged as a non-invasive, straightforward, affordable, and simple method for characterizing various diseases and determining the effectiveness of their current therapies. In order to find potential biomarkers of infertility, this study set out to determine the volatomic pattern of the follicular fluid from patients with PCOS, endometriosis, and POF. The chromatographic data integration was performed through solid-phase microextraction (SPME), followed by gas chromatography–mass spectrometry (GC-MS). The findings pointed to specific metabolite patterns as potential biomarkers for the studied diseases. These open the door for further research into the relevant metabolomic pathways to enhance infertility knowledge and diagnostic tools. An extended investigation may, however, produce a new mechanistic understanding of the pathophysiology of the diseases.

Mapping of Urinary Volatile Organic Compounds by a Rapid Analytical Method Using Gas Chromatography Coupled to Ion Mobility Spectrometry (GC–IMS)

Volatile organic compounds (VOCs) are a differentiated class of molecules, continuously generated in the human body and released as products of metabolic pathways. Their concentrations vary depending on pathophysiological conditions. They are detectable in a wide variety of biological samples, such as exhaled breath, faeces, and urine. In particular, urine represents an easily accessible specimen widely used in clinics. The most used techniques for VOCs detections are expensive and time-consuming, thus not allowing for rapid clinical analysis. In this perspective, the aim of this study is a comprehensive characterisation of the urine volatilome by the development of an alternative rapid analytical method. Briefly, 115 urine samples are collected; sample treatment is not needed. VOCs are detected in the urine headspace using gas chromatography coupled to ion mobility spectrometry (GC–IMS) by an extremely fast analysis (10 min). The method is analytically validated; the analysis is sensitive and robust with results comparable to those reported with other techniques. Twenty-three molecules are identified, including ketones, aldehydes, alcohols, and sulphur compounds, whose concentration is altered in several pathological states such as cancer and metabolic disorders. Therefore, it opens new perspectives for fast diagnosis and screening, showing great potential for clinical applications.

Dogs can discriminate between human baseline and psychological stress condition odours

Previous research suggests that dogs can detect when humans are experiencing stress. This study tested whether baseline and stress odours were distinguishable to dogs, using a double-blind, two-phase, three-alternative forced-choice procedure. Combined breath and sweat samples were obtained from participants at baseline, and after a stress-inducing (mental arithmetic) task. Participants’ stress was validated with self-report and physiological measures recorded via a Biopac MP150 system. Thirty-six participants’ samples were presented to four dogs across 36 sessions (16, 11, 7 and 2 sessions, respectively). Each session consisted of 10 Phase One training trials and 20 Phase Two discrimination trials. In Phase One, the dog was presented with a participant’s stress sample (taken immediately post-task) alongside two blanks (the sample materials without breath or sweat), and was required to identify the stress sample with an alert behaviour. In Phase Two, the dog was presented with the stress sample, the same participant’s baseline sample (taken pre-task), and a blank. Which sample (blank, baseline, or stress) the dog performed their alert behaviour on was measured. If dogs can correctly alert on the stress sample in Phase Two (when the baseline sample was present), it suggests that baseline and stress odours are distinguishable. Performance ranged from 90.00% to 96.88% accuracy with a combined accuracy of 93.75% (N trials = 720). A binomial test (where probability of success on a single trial was 0.33, and alpha was 0.05) showed that the proportion of correct trials was greater than that expected by chance (p < 0.001). Results indicate that the physiological processes associated with an acute psychological stress response produce changes in the volatile organic compounds emanating from breath and/or sweat that are detectable to dogs. These results add to our understanding of human-dog relationships and could have applications to Emotional Support and Post Traumatic Stress Disorder (PTSD) service dogs.

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.

Volatolomic urinary profile analysis for diagnosis of the early stage of lung cancer

Nowadays in clinical practice there is a pressing need for potential biomarkers that can identify lung cancer at early stage before becoming symptomatic or detectable by conventional means. Several researchers have independently pointed out that the volatile organic compounds (VOCs) profile can be considered as a lung cancer fingerprint useful for diagnosis. In particular, 16% of volatiles contributing to the human volatilome are found in urine, which is therefore an ideal sample medium. Its analysis through non-invasive, relatively low-cost and straightforward techniques could offer great potential for the early diagnosis of lung cancer. In this study, urinary VOCs were analysed with a gas chromatography-ion mobility spectrometer (GC-IMS) and an electronic nose (e-nose) made by a matrix of twelve quartz microbalances (QMBs) complemented by a photoionization detector (PID). This clinical prospective study involved 127 individuals, divided into two groups: 46 with lung cancer stage I-II-III confirmed by computerized tomography (CT) or positron emission tomography-(PET) imaging techniques and histology (biopsy), and 81 healthy controls. Both instruments provided a multivariate signal which, after being analysed by a machine learning algorithm, identified eight VOCs that could distinguish lung cancer patients from healthy ones. The eight VOCs are 2-pentanone, 2-hexenal, 2-hexen-1-ol, hept-4-en-2-ol, 2-heptanone, 3-octen-2-one, 4-methylpentanol, 4-methyl-octane. Results show that GC-IMS identifies lung cancer with respect to the control group with a diagnostic accuracy of 88%. Sensitivity resulted as being 85%, and specificity was 90% - Area Under the Receiver Operating Characteristics (AUROC): 0.91. The contribution made by the e-nose was also important, even though the results were slightly less sensitive with an accuracy of 71.6%. Moreover, of the eight VOCs identified as potential biomarkers, five VOCs had a high sensitivity (p≤ 0.06) for early stage (stage I) lung cancer.

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.

VOC Mixture Sensing with a MOF Film Sensor Array: Detection and Discrimination of Xylene Isomers and Their Ternary Blends

Detection and recognition of volatile organic compounds (VOCs) are crucial in many applications. While pure VOCs can be detected by various sensors, the discrimination of VOCs in mixtures, especially of similar molecules, is hindered by cross-sensitivities. Isomer identification in mixtures is even harder. Metal-organic frameworks (MOFs) with their well-defined, nanoporous, and versatile structures have the potential to improve the VOC sensing performance by tailoring the adsorption affinities. Here, we detect and identify ternary xylene isomer mixtures by using an array of six gravimetric, quartz crystal microbalance (QCM)-based sensors coated with selected MOF films with different isomer affinities. We use classical molecular simulations to provide insights into the sensing mechanism. In addition to the attractive interaction between the analytes and the MOF film, the isomer discrimination is caused by the rigid crystalline framework sterically controlling the access of the isomers to different adsorption sites in the MOFs. The sensor array has a very low limit of detection of 1 ppm for each pure isomer and allows the isomer discrimination in mixtures. At 100 ppm, 16 different ternary o-p-m-xylene mixtures were identified with high classification accuracy (96.5%). This work shows the unprecedented performance of MOF-sensor arrays, also referred to as MOF-electronic nose (MOF-e-nose), for sensing VOC mixtures. Based on the study, guidelines for detecting and discriminating complex mixtures of volatile molecules are also provided.

Diagnostic Performance of Electronic Noses in Cancer Diagnoses Using Exhaled Breath: A Systematic Review and Meta-analysis

IMPORTANCE

There has been a growing interest in the use of electronic noses (e-noses) in detecting volatile organic compounds in exhaled breath for the diagnosis of cancer. However, no systematic evaluation has been performed of the overall diagnostic accuracy and methodologic challenges of using e-noses for cancer detection in exhaled breath.

OBJECTIVE

To provide an overview of the diagnostic accuracy and methodologic challenges of using e-noses for the detection of cancer.

DATA SOURCES

An electronic search was performed in the PubMed and Embase databases (January 1, 2000, to July 1, 2021).

STUDY SELECTION

Inclusion criteria were the following: (1) use of e-nose technology, (2) detection of cancer, and (3) analysis of exhaled breath. Exclusion criteria were (1) studies published before 2000; (2) studies not performed in humans; (3) studies not performed in adults; (4) studies that only analyzed biofluids; and (5) studies that exclusively used gas chromatography-mass spectrometry to analyze exhaled breath samples.

DATA EXTRACTION AND SYNTHESIS

PRISMA guidelines were used for the identification, screening, eligibility, and selection process. Quality assessment was performed using Quality Assessment of Diagnostic Accuracy Studies 2. Generalized mixed-effects bivariate meta-analysis was performed.

MAIN OUTCOMES AND MEASURES

Main outcomes were sensitivity, specificity, and mean area under the receiver operating characteristic curve.

RESULTS

This review identified 52 articles with a total of 3677 patients with cancer. All studies were feasibility studies. The sensitivity of e-noses ranged from 48.3% to 95.8% and the specificity from 10.0% to 100.0%. Pooled analysis resulted in a mean (SE) area under the receiver operating characteristic curve of 94% (95% CI, 92%-96%), a sensitivity of 90% (95% CI, 88%-92%), and a specificity of 87% (95% CI, 81%-92%). Considerable heterogeneity existed among the studies because of differences in the selection of patients, endogenous and exogenous factors, and collection of exhaled breath.

CONCLUSIONS AND RELEVANCE

Results of this review indicate that e-noses have a high diagnostic accuracy for the detection of cancer in exhaled breath. However, most studies were feasibility studies with small sample sizes, a lack of standardization, and a high risk of bias. The lack of standardization and reproducibility of e-nose research should be addressed in future research.

Headspace Volatile Organic Compound Profiling of Pleural Mesothelioma and Lung Cancer Cell Lines as Translational Bridge for Breath Research

Introduction

Malignant pleural mesothelioma (MPM) is a lethal cancer for which early-stage diagnosis remains a major challenge. Volatile organic compounds (VOCs) in breath proved to be potential biomarkers for MPM diagnosis, but translational studies are needed to elucidate which VOCs originate from the tumor itself and thus are specifically related to MPM cell metabolism.

Methods

An in vitro model was set-up to characterize the headspace VOC profiles of six MPM and two lung cancer cell lines using thermal desorption-gas chromatography-mass spectrometry. A comparative analysis was carried out to identify VOCs that could discriminate between MPM and lung cancer, as well as between the histological subtypes within MPM (epithelioid, sarcomatoid and biphasic).

Results

VOC profiles were identified capable of distinguishing MPM (subtypes) and lung cancer cells with high accuracy. Alkanes, aldehydes, ketones and alcohols represented many of the discriminating VOCs. Discrepancies with clinical findings were observed, supporting the need for studies examining breath and tumor cells of the same patients and studying metabolization and kinetics of in vitro discovered VOCs in a clinical setting.

Conclusion

While the relationship between in vitro and in vivo VOCs is yet to be established, both could complement each other in generating a clinically useful breath model for MPM.

An Experimental Apparatus for E-Nose Breath Analysis in Respiratory Failure Patients

Background: Non-invasive, bedside diagnostic tools are extremely important for tailo ring the management of respiratory failure patients. The use of electronic noses (ENs) for exhaled breath analysis has the potential to provide useful information for phenotyping different respiratory disorders and improving diagnosis, but their application in respiratory failure patients remains a challenge. We developed a novel measurement apparatus for analysing exhaled breath in such patients. Methods: The breath sampling apparatus uses hospital medical air and oxygen pipeline systems to control the fraction of inspired oxygen and prevent contamination of exhaled gas from ambient Volatile Organic Compounds (VOCs) It is designed to minimise the dead space and respiratory load imposed on patients. Breath odour fingerprints were assessed using a commercial EN with custom MOX sensors. We carried out a feasibility study on 33 SARS-CoV-2 patients (25 with respiratory failure and 8 asymptomatic) and 22 controls to gather data on tolerability and for a preliminary assessment of sensitivity and specificity. The most significant features for the discrimination between breath-odour fingerprints from respiratory failure patients and controls were identified using the Boruta algorithm and then implemented in the development of a support vector machine (SVM) classification model. Results: The novel sampling system was well-tolerated by all patients. The SVM differentiated between respiratory failure patients and controls with an accuracy of 0.81 (area under the ROC curve) and a sensitivity and specificity of 0.920 and 0.682, respectively. The selected features were significantly different in SARS-CoV-2 patients with respiratory failure versus controls and asymptomatic SARS-CoV-2 patients (p < 0.001 and 0.046, respectively). Conclusions: the developed system is suitable for the collection of exhaled breath samples from respiratory failure patients. Our preliminary results suggest that breath-odour fingerprints may be sensitive markers of lung disease severity and aetiology.

Prostate cancer detection: a systematic review of urinary biosensors

BACKGROUND

Current diagnostic methods for prostate cancer are invasive and lack specificity towards aggressive forms of the disease, which can lead to overtreatment. A new class of non-invasive alternatives is under development, in which urinary biomarkers are detected using biosensing devices to offer rapid and accurate prostate cancer diagnosis. These different approaches are systematically reviewed and their potential for translation to clinical practice is evaluated.

METHODS

A systematic review of the literature was performed in May 2021 using PubMed Medline database, Embase, and Web of Science. The objective was to review the structural designs and performance of biosensors tested on urine samples from patients with prostate cancer.

RESULTS

A total of 76 records were identified. After screening and eligibility, 14 articles were included and are discussed in this paper. The biosensors were discussed based on the target biomarkers and detection technologies used, as well as the results of the clinical studies. Most of the works reported good discrimination between patients with prostate cancer and controls.

CONCLUSIONS

This review highlights the potential of urinary biosensors for non-invasive prostate cancer detection. However, clinical studies have so far only been conducted on small cohorts of patient, with large scale trials still needed to validate the proposed approaches. Overall, the consensus arising from the proof of concepts studies reviewed here, is that an adequate combination of biomarkers into multiplex biosensor platforms is required to achieve accurate diagnostic tests. Furthermore, whether such devices can discriminate between aggressive and indolent cancer has not yet been addressed, because it entails optimized biomarkers panels and long-term clinical trials.

[Advances on Collection and Analysis of Volatile Organic Compounds in the Diagnosis of Lung Cancer]

Lung cancer is a leading cause of cancer-related morbidity and mortality globally, which is the biggest menace to the health and life of the population. Screening and early detection of lung cancer are effective in reducing its mortality, and the measurement of volatile organic compounds (VOCs) has become a promising clinical means for early detection, course detection and prognosis management of lung cancer, with advantages of rapid speed, non-invasiveness and convenience. Now, a variety of VOCs collection ways and analysis methods have emerged at home and abroad. This report summarized three aspects, including VOCs collection, multiple methods of analysis and progress in the diagnosis and treatment of lung cancer. At last, we discussed the limitations and prospects of VOCs analysis.
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A novel approach to the analysis of spin-trapped free radicals using dimethyl sulfoxide and gas chromatography - mass spectrometry (GC-MS) with both solvent extraction and headspace solid phase microextraction (HS-SPME)

In this study, we have utilized a novel strategy based upon the use of dimethyl sulfoxide (DMSO) and gas chromatography-mass spectrometry (GC-MS) for the detection and identification of spin-trapped free radicals. Hydroxymethyl (^.CH₂OH) radicals, generated by Fenton-type chemistry, have been trapped by N-tert-butyl-α-phenylnitrone (PBN) or one of its derivatives in the presence of DMSO to form a 1,3-diadduct [PBN-(CH₂OH)(CH₃)], which may be detected directly in the reaction mixture following chloroform extraction or in the reaction vial headspace by sampling with SPME. Separation and identification have been carried out by capillary gas chromatography coupled to electron-ionization mass spectrometry (EI-MS). The results demonstrate that using DMSO aids GC-MS analysis of spin-trapped free radicals via the formation of radical-methyl di-adducts that are sufficiently volatile to be sampled both in the headspace or by an extracting solvent without the need for a derivatization step using silylating agents.

Recent advancements in the exploitation of the gut microbiome in the diagnosis and treatment of colorectal cancer

Over the last few decades it has been established that the complex interaction between the host and the multitude of organisms that compose the intestinal microbiota plays an important role in human metabolic health and disease. Whilst there is no defined consensus on the composition of a healthy microbiome due to confounding factors such as ethnicity, geographical locations, age and sex, there are undoubtably populations of microbes that are consistently dysregulated in gut diseases including colorectal cancer (CRC). In this review, we discuss the most recent advances in the application of the gut microbiota, not just bacteria, and derived microbial compounds in the diagnosis of CRC and the potential to exploit microbes as novel agents in the management and treatment of CRC. We highlight examples of the microbiota, and their derivatives, that have the potential to become standalone diagnostic tools or be used in combination with current screening techniques to improve sensitivity and specificity for earlier CRC diagnoses and provide a perspective on their potential as biotherapeutics with translatability to clinical trials.

Preliminary accuracy of COVID-19 odor detection by canines and HS-SPME-GC-MS using exhaled breath samples

The novel coronavirus SARS-CoV-2, since its initial outbreak in Wuhan, China has led to a worldwide pandemic and has shut down nations. As with any outbreak, there is a general strategy of detection, containment, treatment and/or cure. The authors would argue that rapid and efficient detection is critical and required to successful management of a disease. The current study explores and successfully demonstrates the use of canines to detect COVID-19 disease in exhaled breath. The intended use was to detect the odor of COVID-19 on contaminated surfaces inferring recent deposition of infectious material from a COVID-19 positive individual. Using masks obtained from hospitalized patients that tested positive for COVID-19 disease, four canines were trained and evaluated for their ability to detect the disease. All four canines obtained an accuracy >90% and positive predictive values ranging from ~73 to 93% after just one month of training.

Breath analysis for the detection of digestive tract malignancies: systematic review

Background

In recent decades there has been growing interest in the use of volatile organic compounds (VOCs) in exhaled breath as biomarkers for the diagnosis of multiple variants of cancer. This review aimed to evaluate the diagnostic accuracy and current status of VOC analysis in exhaled breath for the detection of cancer in the digestive tract.

Methods

PubMed and the Cochrane Library database were searched for VOC analysis studies, in which exhaled air was used to detect gastro-oesophageal, liver, pancreatic, and intestinal cancer in humans, Quality assessment was performed using the QUADAS-2 criteria. Data on diagnostic performance, VOCs with discriminative power, and methodological information were extracted from the included articles.

Results

Twenty-three articles were included (gastro-oesophageal cancer n = 14, liver cancer n = 1, pancreatic cancer n = 2, colorectal cancer n = 6). Methodological issues included different modalities of patient preparation and sampling and platform used. The sensitivity and specificity of VOC analysis ranged from 66.7 to 100 per cent and from 48.1 to 97.9 per cent respectively. Owing to heterogeneity of the studies, no pooling of the results could be performed. Of the VOCs found, 32 were identified in more than one study. Nineteen were reported as cancer type-specific, whereas 13 were found in different cancer types. Overall, decanal, nonanal, and acetone were the most frequently identified.

Conclusion

The literature on VOC analysis has documented a lack of standardization in study designs. Heterogeneity between the studies and insufficient validation of the results make interpretation of the outcomes challenging. To reach clinical applicability, future studies on breath analysis should provide an accurate description of the methodology and validate their findings.

Needle Trap Device-GC-MS for Characterization of Lung Diseases Based on Breath VOC Profiles

Volatile organic compounds (VOCs) have been assessed in breath samples as possible indicators of diseases. The present study aimed to quantify 29 VOCs (previously reported as potential biomarkers of lung diseases) in breath samples collected from controls and individuals with lung cancer, chronic obstructive pulmonary disease and asthma. Besides that, global VOC profiles were investigated. A needle trap device (NTD) was used as pre-concentration technique, associated to gas chromatography-mass spectrometry (GC-MS) analysis. Univariate and multivariate approaches were applied to assess VOC distributions according to the studied diseases. Limits of quantitation ranged from 0.003 to 6.21 ppbv and calculated relative standard deviations did not exceed 10%. At least 15 of the quantified targets presented themselves as discriminating features. A random forest (RF) method was performed in order to classify enrolled conditions according to VOCs' latent patterns, considering VOCs responses in global profiles. The developed model was based on 12 discriminating features and provided overall balanced accuracy of 85.7%. Ultimately, multinomial logistic regression (MLR) analysis was conducted using the concentration of the nine most discriminative targets (2-propanol, 3-methylpentane, (E)-ocimene, limonene, m-cymene, benzonitrile, undecane, terpineol, phenol) as input and provided an average overall accuracy of 95.5% for multiclass prediction.

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.

Advances and Perspectives in Prostate Cancer Biomarker Discovery in the Last 5 Years through Tissue and Urine Metabolomics

Prostate cancer (PCa) is the second most diagnosed cancer in men worldwide. For its screening, serum prostate specific antigen (PSA) test has been largely performed over the past decade, despite its lack of accuracy and inability to distinguish indolent from aggressive disease. Metabolomics has been widely applied in cancer biomarker discovery due to the well-known metabolic reprogramming characteristic of cancer cells. Most of the metabolomic studies have reported alterations in urine of PCa patients due its noninvasive collection, but the analysis of prostate tissue metabolome is an ideal approach to disclose specific modifications in PCa development. This review aims to summarize and discuss the most recent findings from tissue and urine metabolomic studies applied to PCa biomarker discovery. Eighteen metabolites were found consistently altered in PCa tissue among different studies, including alanine, arginine, uracil, glutamate, fumarate, and citrate. Urine metabolomic studies also showed consistency in the dysregulation of 15 metabolites and, interestingly, alterations in the levels of valine, taurine, leucine and citrate were found in common between urine and tissue studies. These findings unveil that the impact of PCa development in human metabolome may offer a promising strategy to find novel biomarkers for PCa diagnosis.

COVID-19 detection by dogs: from physiology to field application-a review article

For years, the dog, man's best friend, was the most widely employed scent-detector tool for civilian and military purposes. Recently, many studies highlighted the role of canine olfactory ability in the medical field, specifically in detecting different infectious, metabolic and neoplastic conditions. The objective of this literature review is to clarify the rationale behind dog's ability to detect diseases, to assess the possible application for COVID-19 detection and to discuss the evidence available on the matter. Available evidence shows that properly trained disease-detector dogs are an efficient tool for identification of specific disease-associated volatile organic compounds marker profiles for a particular disease. And since COVID-19 positive persons have a specific volatilome different from non-infected persons, they can be recognised by the dogs, by sniffing different body fluids consequently aiding in the diagnosis of COVID-19. Possible applications of dogs as COVID-19 detectors will be an easy real-time mobile diagnostic aid with low cost and good performance. More evidence is needed to be able to describe standardised measures concerning the best fluid to test, testing procedure, time of possible detection according to disease evolution, risks associated with the dog exposure and to translate the good results in study setting into the real-life operational one.

Induced volatolomics of pathologies

Volatolomics allows us to elucidate cell metabolic processes in real time. In particular, a volatile organic compound (VOC) excreted from our bodies may be specific for a certain disease, such that measuring this VOC may afford a simple, fast, accessible and safe diagnostic approach. Yet, finding the optimal endogenous volatile marker specific to a pathology is non-trivial because of interlaboratory disparities in sample preparation and analysis, as well as high interindividual variability. These limit the sensitivity and specificity of volatolomics and its applications in biological and clinical fields but have motivated the development of induced volatolomics. This approach aims to overcome issues by measuring VOCs that result not from an endogenous metabolite but, rather, from the pathogen-specific or metabolic-specific enzymatic metabolism of an exogenous biological or chemical probe. In this Review, we introduce volatile-compound-based probes and discuss how they can be exploited to detect and discriminate pathogenic infections, to assess organ function and to diagnose and monitor cancers in real time. We focus on cases in which labelled probes have informed us about metabolic processes and consider the potential and drawbacks of the probes for clinical trials. Beyond diagnostics, VOC-based probes may also be effective tools to explore biological processes more generally.

Optimisation of Urine Sample Preparation for Headspace-Solid Phase Microextraction Gas Chromatography-Mass Spectrometry: Altering Sample pH, Sulphuric Acid Concentration and Phase Ratio

Headspace-solid phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC-MS) can be used to measure volatile organic compounds (VOCs) in human urine. However, there is no widely adopted standardised protocol for the preparation of urine samples for analysis resulting in an inability to compare studies reliably between laboratories. This paper investigated the effect of altering urine sample pH, volume, and vial size for optimising detection of VOCs when using HS-SPME-GC-MS. This is the first, direct comparison of H₂SO₄, HCl, and NaOH as treatment techniques prior to HS-SPME-GC-MS analysis. Altering urine sample pH indicates that H₂SO₄ is more effective at optimising detection of VOCs than HCl or NaOH. H₂SO₄ resulted in a significantly larger mean number of VOCs being identified per sample (on average, 33.5 VOCs to 24.3 in HCl or 12.2 in NaOH treated urine) and more unique VOCs, produced a more diverse range of classes of VOCs, and led to less HS-SPME-GC-MS degradation. We propose that adding 0.2 mL of 2.5 M H₂SO₄ to 1 mL of urine within a 10 mL headspace vial is the optimal sample preparation prior to HS-SPME-GC-MS analysis. We hope the use of our optimised method for urinary HS-SPME-GC-MS analysis will enhance our understanding of human disease and bolster metabolic biomarker identification.

Volatile organic compounds in a headspace sampling system and asthmatics sputum samples

Background:The headspace of a biological sample contains exogenous VOCs present within the sampling environment which represent the background signal.Study aims:This study aimed to characterise the background signal generated from a headspace sampling system in a clinical site, to evaluate intra- and inter-day variation of background VOC and to understand the impact of a sample itself upon commonly reported background VOC using sputum headspace samples from severe asthmatics.Methods:The headspace, in absence of a biological sample, was collected hourly from 11am to 3pm within a day (time of clinical samples acquisition), and from Monday to Friday in a week, and analysed by thermal desorption-gas chromatography-mass spectrometry (TD-GC-MS). Chemometric analysis identified 1120 features, 37 of which were present in at least the 80% of all the samples. The analyses of intra- and inter-day background variations were performed on thirteen of the most abundant features, ubiquitously present in headspace samples. The concentration ratios relative to background were reported for the selected abundant VOC in 36 asthmatic sputum samples, acquired from 36 stable severe asthma patients recruited at Glenfield Hospital, Leicester, UK.Results:The results identified no significant intra- or inter-day variations in compounds levels and no systematic bias of z-scores, with the exclusion of benzothiazole, whose abundance increased linearly between 11am and 3pm with a maximal intra-day fold change of 2.13. Many of the identified background features are reported in literature as components of headspace of biological samples and are considered potential biomarkers for several diseases. The selected background features were identified in headspace of all severe asthma sputum samples, albeit with varying levels of enrichment relative to background.Conclusion:Our observations support the need to consider the background signal derived from the headspace sampling system when developing and validating headspace biomarker signatures using clinical samples.

Breath indeed carries significant information about a disease: Potential biomarkers of cerebral palsy

Objective and reliable noninvasive medical diagnostics of a large variety of diseases is still a dream. As a step in the direction of realization, a spectroscopic breath study of cerebral palsy (CP) was performed. Principal component analysis revealed data clustering for a healthy group and CP individuals was observed, with a P-value below 10^-5 . Learning algorithms resulted in 91% accuracy in distinguishing the groups. With the help of manual analysis of absorption spectral features of breath samples, two volatile organic compounds were identified that demonstrate significant deviations in the groups. These represent two esters of propionic acid (PPAE). A transportation scheme was hypothesized that links the gut where propionic acid (PPA) and PPAE are produced, the brain of CP patients, through which PPA and PPAE transmit, and the lungs where PPAE releases. The results show a possibility to detect one more brain-related disorder via breath, in this case CP.

Analysis of urinary VOCs using mass spectrometric methods to diagnose cancer: A review

The development of non-invasive screening techniques for early cancer detection is one of the greatest scientific challenges of the 21st century. One promising emerging method is the analysis of volatile organic compounds (VOCs). VOCs are low molecular weight substances generated as final products of cellular metabolism and emitted through a variety of biological matrices, such as breath, blood, saliva and urine. Urine stands out for its non-invasive nature, availability in large volumes, and the high concentration of VOCs in the kidneys. This review provides an overview of the available data on urinary VOCs that have been investigated in cancer-focused clinical studies using mass spectrometric (MS) techniques. A literature search was conducted in ScienceDirect, Pubmed and Web of Science, using the keywords "Urinary VOCs", "VOCs biomarkers" and "Volatile cancer biomarkers" in combination with the term "Mass spectrometry". Only studies in English published between January 2011 and May 2020 were selected. The three most evaluated types of cancers in the reviewed studies were lung, breast and prostate, and the most frequently identified urinary VOC biomarkers were hexanal, dimethyl disulfide and phenol; with the latter seeming to be closely related to breast cancer. Additionally, the challenges of analyzing urinary VOCs using MS-based techniques and translation to clinical utility are discussed. The outcome of this review may provide valuable information to future studies regarding cancer urinary VOCs.

A density functional theory study on the interaction of toluene with transition metal decorated carbon nanotubes: a promising platform for early detection of lung cancer from human breath

In this study, single-wall carbon nanotubes (SWCNTs) decorated by platinum-group transition metals (Pt, Pd, Rh, or Ru) were introduced as promising nanosensors for the detection of toluene, an important biomarker in the exhaled breath of the lung cancer patients. First-principle calculations based on density functional theory (DFT) was employed to scrutinize the impact of an individual toluene gas molecule on the structural, electronic, and magnetic properties of pristine and metal decorated SWCNTs. It was discovered that toluene is physisorbed on the pristine SWCNT through the interaction of the π orbitals of the carbon atoms in the toluene and the nanotube. Decoration of the SWCNT with metal atoms enhanced the adsorption energies significantly by means of strong overlapping between d orbital of the metal atoms and p orbital of C atoms in the benzene ring of toluene. Investigations showed that toluene is strongly chemisorbed on Rh- and Ru-SWCNT systems via strong covalent bonds with the superior response (-96.98% and -99.98%, respectively), and moderately chemisorbed on Pt-SWCNTs (-27.3%) and Pd-SWCNTs (61.60%). Our findings propose metal decorated SWCNT molecular sensors are attractive candidates for the detection of toluene and other lung cancer biomarkers in the exhaled breath of the lung cancer patients.

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.