Cross-platform mass spectrometry annotation in breathomics of oesophageal-gastric cancer

Serum-volatile organic compounds in the diagnostics of esophageal cancer

The early diagnosis of esophageal cancer (EC) is extremely challenging due to a lack of effective diagnostic methods. The study presented herein aims to assess whether serum volatile organic compounds (VOCs) could be utilised as emerging diagnostic biomarkers for EC. Gas chromatography-ion mobility spectrometry (GC-IMS) was used to detect VOCs in the serum samples of 55 patients with EC, with samples from 84 healthy controls (HCs) patients analysed as a comparison. All machine learning analyses were based on data from serum VOCs obtained by GC-IMS. A total of 33 substance peak heights were detected in all patient serum samples. The ROC analysis revealed that four machine learning models were effective in facilitating the diagnosis of EC. In addition, the random forests model for 5 VOCs had an AUC of 0.951, with sensitivities and specificities of 94.1 and 96.0%, respectively.

Sample Collection and Processing in Volatile Organic Compound Analysis for Gastrointestinal Cancers

Volatile organic compounds have drawn significant attention in recent years as a novel tool for non-invasive detection of a wide range of diseases, including gastrointestinal cancers, for which the need for effective, affordable, and non-invasive screening methods is substantial. Sample preparation is a fundamental step that greatly influences the quality of results and the feasibility of wide-range applications. This review summarizes sampling methods used in studies aiming at testing the diagnostic value of volatile organic compounds in gastrointestinal cancers, discussing in detail some of the recent advancements in automated sampling techniques. Finally, we propose some directions in which sample collection and processing can improve for VOC analysis to be popularized in clinical settings.

Breathomics Detect the Cardiovascular Disease: Delusion or Dilution of the Metabolomic Signature

Volatile organic compounds (VOCs) can be subdivided into exogenous and endogenous categories based on their origin. Analyzing the endogenous VOCs can provide insights into maintaining the internal organs' homeostasis. Despite the ongoing development and the current understanding, studies have suggested a link between cardiovascular metabolic alterations in patients with ischemic heart disease and elevated levels of ethane and isoprene detectable through exhaled breath analysis. Conversely, patients with chronic heart failure exhibit elevated acetone and pentane in their exhaled air. These substances originate from disturbances in the heart tissue, including cellular and subcellular modulations. Hypothetically, ethane levels in the exhaled breath analysis can demonstrate the severity of ischemic heart disease and, consequently, the risk of death in the next 10 years due to cardiovascular disease (CVD). Real-time direct mass spectrometry is the preferred method for assessing VOCs in exhaled breath analysis. The accuracy of this analysis depends on several factors, including the selection of the relevant breath fraction, the type of breath collection container (if used), and the pre-concentration technique.

Diagnosis by Volatile Organic Compounds in Exhaled Breath in Exhaled Breath from Patients with Gastric and Colorectal Cancers

One in three cancer deaths worldwide are caused by gastric and colorectal cancer malignancies. Although the incidence and fatality rates differ significantly from country to country, the rates of these cancers in East Asian nations such as South Korea and Japan have been increasing each year. Above all, the biggest danger of this disease is how challenging it is to recognize in its early stages. Moreover, most patients with these cancers do not present with any disease symptoms before receiving a definitive diagnosis. Currently, volatile organic compounds (VOCs) are being used for the early prediction of several other diseases, and research has been carried out on these applications. Exhaled VOCs from patients possess remarkable potential as novel biomarkers, and their analysis could be transformative in the prevention and early diagnosis of colon and stomach cancers. VOCs have been spotlighted in recent studies due to their ease of use. Diagnosis on the basis of patient VOC analysis takes less time than methods using gas chromatography, and results in the literature demonstrate that it is possible to determine whether a patient has certain diseases by using organic compounds in their breath as indicators. This study describes how VOCs can be used to precisely detect cancers; as more data are accumulated, the accuracy of this method will increase, and it can be applied in more fields.

Fast and noninvasive electronic nose for sniffing out COVID-19 based on exhaled breath-print recognition

The reverse transcription-quantitative polymerase chain reaction (RT-qPCR) approach has been widely used to detect the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, instead of using it alone, clinicians often prefer to diagnose the coronavirus disease 2019 (COVID-19) by utilizing a combination of clinical signs and symptoms, laboratory test, imaging measurement (e.g., chest computed tomography scan), and multivariable clinical prediction models, including the electronic nose. Here, we report on the development and use of a low cost, noninvasive method to rapidly sniff out COVID-19 based on a portable electronic nose (GeNose C19) integrating an array of metal oxide semiconductor gas sensors, optimized feature extraction, and machine learning models. This approach was evaluated in profiling tests involving a total of 615 breath samples composed of 333 positive and 282 negative samples. The samples were obtained from 43 positive and 40 negative COVID-19 patients, respectively, and confirmed with RT-qPCR at two hospitals located in the Special Region of Yogyakarta, Indonesia. Four different machine learning algorithms (i.e., linear discriminant analysis, support vector machine, stacked multilayer perceptron, and deep neural network) were utilized to identify the top-performing pattern recognition methods and to obtain a high system detection accuracy (88–95%), sensitivity (86–94%), and specificity (88–95%) levels from the testing datasets. Our results suggest that GeNose C19 can be considered a highly potential breathalyzer for fast COVID-19 screening.

Noninvasive Diagnosis of Gastric Cancer Based on Breath Analysis with a Tubular Surface-Enhanced Raman Scattering Sensor

SERS-based breath analysis as an emerging technique has attracted increasing attention in cancer screening. Here, eight aldehydes and ketones in the human breath are reported as the VOC biomarkers identified by gas chromatography-mass spectrometry (GC-MS) and applied further for the noninvasive diagnosis of gastric cancer (GC) with a tubular SERS sensor. The tubular SERS sensor is prepared with a glass capillary loaded with ZIF-67-coated silver particles (Ag@ZIF-67), which offers Raman enhancement from the plasmonic nanoparticles and gas enrichment from the metal-organic framework (MOF) shells. The composite materials are modified with 4-aminothiophenol (4-ATP) to capture different aldehyde and ketone compounds. The tubular sensor is served simultaneously as a gas flow channel and a detection chamber, bringing a higher gas capture efficiency than the planar SERS sensor. As a proof-of-concept, the tubular SERS sensor is successfully employed to screen gastric cancer patients with an accuracy of 89.83%, based on the noninvasive, rapid, and easily operated breath analysis. The results demonstrate that the established breath analysis method provides an excellent alternative for the screening of GC and other diseases.

Diagnostic Application of Volatile Organic Compounds as Potential Biomarkers for Detecting Digestive Neoplasia: A Systematic Review

Volatile organic compounds (VOCs) are part of the exhaled breath that were proposed as non-invasive breath biomarkers via different human discharge products like saliva, breath, urine, blood, or tissues. Particularly, due to the non-invasive approach, VOCs were considered as potential biomarkers for non-invasive early cancer detection. We herein aimed to review the data over VOCs utility in digestive neoplasia as early diagnosis or monitoring biomarkers. A systematic literature search was done using MEDLINE via PubMed, Cochrane Library, and Thomson Reuters' Web of Science Core Collection. We identified sixteen articles that were included in the final analysis. Based on the current knowledge, we cannot identify a single VOC as a specific non-invasive biomarker for digestive neoplasia. Several combinations of up to twelve VOCs seem promising for accurately detecting some neoplasia types. A combination of different VOCs breath expression are promising tools for digestive neoplasia screening.

Selected ion flow tube mass spectrometry for targeted analysis of volatile organic compounds in human breath

The analysis of volatile organic compounds (VOCs) within breath for noninvasive disease detection and monitoring is an emergent research field that has the potential to reshape current clinical practice. However, adoption of breath testing has been limited by a lack of standardization. This protocol provides a comprehensive workflow for online and offline breath analysis using selected ion flow tube mass spectrometry (SIFT-MS). Following the suggested protocol, 50 human breath samples can be analyzed and interpreted in <3 h. Key advantages of SIFT-MS are exploited, including the acquisition of real-time results and direct compound quantification without need for calibration curves. The protocol includes details of methods developed for targeted analysis of disease-specific VOCs, specifically short-chain fatty acids, aldehydes, phenols, alcohols and alkanes. A procedure to make custom breath collection bags is also described. This standardized protocol for VOC analysis using SIFT-MS is intended to provide a basis for wider application and the use of breath analysis in clinical studies.

Cross Platform Analysis of Volatile Organic Compounds Using Selected Ion Flow Tube and Proton-Transfer-Reaction Mass Spectrometry

Volatile breath metabolites serve as potential disease biomarkers. Online mass spectrometry (MS) presents real-time quantification of breath volatile organic compounds (VOCs). The study aims to assess the relationship between two online analytical mass spectrometry techniques in the quantification of target breath metabolites: selected ion flow tube mass spectrometry (SIFT-MS) and proton-transfer-reaction time-of-flight mass spectrometry (PTR-ToF-MS). The two following techniques were employed: (i) direct injection with bag sampling using SIFT-MS and PTR-ToF-MS and (ii) direct injection and thermal desorption (TD) tube comparison using PTR-ToF-MS. The concentration of abundant breath metabolites, acetone and isoprene, demonstrated a strong positive linear correlation between both mass spectrometry techniques (r = 0.97, r = 0.89, respectively; p < 0.001) and between direct injection and TD tube (r = 0.97, r = 0.92, respectively; p < 0.001) breath sampling techniques. This was reflected for the majority of short chain fatty acids and alcohols tested (r > 0.80, p < 0.001). Analyte concentrations were notably higher with the direct injection of a sampling bag compared to the TD method. All metabolites produced a high degree of agreement in the detection range of VOCs between SIFT-MS and PTR-ToF-MS, with the majority of compounds falling within 95% of the limits of agreement with Bland-Altman analysis. The cross platform analysis of exhaled breath demonstrates strong positive correlation coefficients, linear regression, and agreement in target metabolite detection rates between both breath sampling techniques. The study demonstrates the transferability of using data outputs between SIFT-MS and PTR-ToF-MS. It supports the implementation of a TD platform in multi-site studies for breath biomarker research in order to facilitate sample transport between clinics and the laboratory.

Feasibility and acceptability of breath research in primary care: a prospective, cross-sectional, observational study

OBJECTIVES

To examine the feasibility and acceptability of breath research in primary care.

DESIGN

Non-randomised, prospective, mixed-methods cross-sectional observational study.

SETTING

Twenty-six urban primary care practices.

PARTICIPANTS

1002 patients aged 18-90 years with gastrointestinal symptoms.

MAIN OUTCOME MEASURES

During the first 6 months of the study (phase 1), feasibility of patient enrolment using face-to-face, telephone or SMS-messaging (Short Message Service) enrolment strategies, as well as processes for breath testing at local primary care practices, were evaluated. A mixed-method iterative study design was adopted and outcomes evaluated using weekly Plan-Do-Study-Act cycles, focus groups and general practitioner (GP) questionnaires.During the second 6 months of the study (phase 2), patient and GP acceptability of the breath test and testing process was assessed using questionnaires. In addition a 'single practice' recruitment model was compared with a 'hub and spoke' centralised recruitment model with regards to enrolment ability and patient acceptability.Throughout the study feasibility of the collection of a large number of breath samples by clinical staff over multiple study sites was evaluated and quantified by the analysis of these samples using mass spectrometry.

RESULTS

1002 patients were recruited within 192 sampling days. Both 'single practice' and 'hub and spoke' recruitment models were effective with an average of 5.3 and 4.3 patients accrued per day, respectively. The 'hub and spoke' model with SMS messaging was the most efficient combined method of patient accrual. Acceptability of the test was high among both patients and GPs. The methodology for collection, handling and analysis of breath samples was effective, with 95% of samples meeting quality criteria.

CONCLUSIONS

Large-scale breath testing in primary care was feasible and acceptable. This study provides a practical framework to guide the design of Phase III trials examining the performance of breath testing in primary care.

Exhaled breath analysis in disease detection

Investigating the use of exhaled breath analysis to diagnose and monitor different diseases has attracted much interest in recent years. This review introduces conventionally used methods and some emerging technologies aimed at breath analysis and their relevance to lung disease, airway inflammation, gastrointestinal disorders, metabolic disorders and kidney diseases. One section correlates breath components and specific diseases, whereas the other discusses some unique ideas, strategies, and devices to analyze exhaled breath for the diagnosis of some common diseases. This review aims to briefly introduce the potential application of exhaled breath analysis for the diagnosis and screening of various diseases, thereby providing a new avenue for the detection of non-invasive diseases.

Biological Applications for LC-MS-Based Proteomics

Since its inception, liquid chromatography-mass spectrometry (LC-MS) has been continuously improved upon in many aspects, including instrument capabilities, sensitivity, and resolution. Moreover, the costs to purchase and operate mass spectrometers and liquid chromatography systems have decreased, thus increasing affordability and availability in sectors outside of academic and industrial research. Processing power has also grown immensely, cutting the time required to analyze samples, allowing more data to be feasibly processed, and allowing for standardized processing pipelines. As a result, proteomics via LC-MS has become popular in many areas of biological sciences, forging an important seat for itself in targeted and untargeted assays, pure and applied science, the laboratory, and the clinic. In this chapter, many of these applications of LC-MS-based proteomics and an outline of how they can be executed will be covered. Since the field of personalized medicine has matured alongside proteomics, it has also come to rely on various mass spectrometry methods and will be elaborated upon as well. As time goes on and mass spectrometry evolves, there is no doubt that its presence in these areas, and others, will only continue to grow.

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.

Evolution and Evaluation of GC Columns

A chromatographic column is the fundamental element required for gas-chromatographic analysis. The separation of components coming from complex mixtures, prior to their detection was leading to a prominent revolution in different areas of science. Moreover, current advances in gas chromatographic (GC) columns technology and development have been providing almost unlimited possibilities for analysis employing diverse matrices. We aim through this review article to describe the evolution of chromatographic columns, by pointing the most important stages, as well as the new trends and future perspectives predicted for the new generation of GC columns. Furthermore, it was in our scope to present the main fundamentals regarding the theoretical relationships that describe the chromatographic separation, to introduce concepts related to columns selection in accordance with the required application as well as to discuss the available evaluation parameters for columns efficiency. Consequently, the early stages of first columns preparation up to the development of GC capillary columns used nowadays, together with examples of their applications are also reported and described in detail.

Hybrid Analytical Platform Based on Field-Asymmetric Ion Mobility Spectrometry, Infrared Sensing, and Luminescence-Based Oxygen Sensing for Exhaled Breath Analysis

The reliable online analysis of volatile compounds in exhaled breath remains a challenge, as a plethora of molecules occur in different concentration ranges (i.e., ppt to %) and need to be detected against an extremely complex background matrix. Although this complexity is commonly addressed by hyphenating a specific analytical technique with appropriate preconcentration and/or preseparation strategies prior to detection, we herein propose the combination of three different detector types based on truly orthogonal measurement principles as an alternative solution: Field-asymmetric ion mobility spectrometry (FAIMS), Fourier-transform infrared (FTIR) spectroscopy-based sensors utilizing substrate-integrated hollow waveguides (iHWG), and luminescence sensing (LS). By carefully aligning the experimental needs and measurement protocols of all three methods, they were successfully integrated into a single compact analytical platform suitable for online measurements. The analytical performance of this prototype system was tested via artificial breath samples containing nitrogen (N₂), oxygen (O₂), carbon dioxide (CO₂), and acetone as a model volatile organic compound (VOC) commonly present in breath. All three target analytes could be detected within their respectively breath-relevant concentration range, i.e., CO₂ and O₂ at 3-5 % and at ~19.6 %, respectively, while acetone could be detected with LOQs as low as 165-405 ppt. Orthogonality of the three methods operating in concert was clearly proven, which is essential to cover a possibly wide range of detectable analytes. Finally, the remaining challenges toward the implementation of the developed hybrid FAIMS-FTIR-LS system for exhaled breath analysis for metabolic studies in small animal intensive care units are discussed.

Mass-Spectrometry Analysis of Mixed-Breath, Isolated-Bronchial-Breath, and Gastric-Endoluminal-Air Volatile Fatty Acids in Esophagogastric Cancer

A noninvasive breath test has the potential to improve survival from esophagogastric cancer by facilitating earlier detection. This study aimed to investigate the production of target volatile fatty acids (VFAs) in esophagogastric cancer through analysis of the ex vivo headspace above underivatized tissues and in vivo analysis within defined anatomical compartments, including analysis of mixed breath, isolated bronchial breath, and gastric-endoluminal air. VFAs were measured by PTR-ToF-MS and GC-MS. Levels of VFAs (acetic, butyric, pentanoic, and hexanoic acids) and acetone were elevated in ex vivo experiments in the headspace above esophagogastric cancer compared with the levels in samples from control subjects with morphologically normal and benign conditions of the upper gastrointestinal tract. In 25 patients with esophagogastric cancer and 20 control subjects, receiver-operating-characteristic analysis for the cancer-specific VFAs butyric acid ( P < 0.001) and pentatonic acid ( P = 0.005) within in vivo gastric-endoluminal air gave an area under the curve of 0.80 (95% confidence interval of 0.65 to 0.93, P = 0.01). Compared with mixed- and bronchial-breath samples, all examined VFAs were found in highest concentrations within esophagogastric-endoluminal air. In addition, VFAs were higher in all samples derived from cancer patients compared with in the controls. Equivalence of VFA levels within the mixed and bronchial breath of cancer patients suggests that their origin within breath is principally derived from the lungs and, by inference, from the systemic circulation as opposed to direct passage from the upper gastrointestinal tract. These findings highlight the potential to utilize VFAs for endoluminal-gas biopsies and noninvasive mixed-exhaled-breath testing for esophagogastric-cancer detection.

Metabolomics and Biomarker Discovery

Recently, metabolomics-the study of metabolite profiles within biological samples-has found a wide range of applications. This chapter describes the different techniques available for metabolomic analysis, the various samples that can be utilised for analysis and applications of both global and targeted metabolomic analysis to biomarker discovery in medicine.

Methodological considerations for large-scale breath analysis studies: lessons from the U-BIOPRED severe asthma project

Methods for breath sampling and analysis require robust quality assessment to minimise the risk of false discoveries. Planning large-scale multi-site breath metabolite profiling studies also requires careful consideration of systematic and random variation as a result of sampling and analysis techniques. In this study we use breath sample data from the recent U-BIOPRED cohort to evaluate and discuss some important methodological considerations such as batch variation and correction, variation between sites, storage and transportation, as well as inter-instrument analytical differences. Based on this we provide a summary of recommended best practices for new large scale multi-site studies.