Exploratory Study Using Urinary Volatile Organic Compounds for the Detection of Hepatocellular Carcinoma

Gas chromatography-ion mobility spectrometry for the detection of human disease: a review

Gas chromatography-ion mobility spectrometry (GC-IMS) is an advanced technique used for detecting trace compounds, due to its non-destructive, straightforward, and rapid analytical capabilities. However, the application of GC-IMS in human disease screening is barely reported. This review summarizes the application and related parameters of GC-IMS in human disease diagnosis. GC-IMS detects volatile organic compounds in human breath, feces, urine, bile, etc. It can be applied to diagnose diseases, such as respiratory diseases, cancer, enteropathy, Alzheimer's disease, bacterial infection, and metabolic diseases. Several potential disease markers have been identified by GC-IMS, including ethanal (COVID-19), 2-heptanone (lung cancer) and 3-pentanone (pulmonary cryptococcosis). In conclusion, GC-IMS offers a non-invasive approach to monitor and diagnose human diseases with broad applications.

Volatile organic compounds (VOCs) in terrestrial extreme environments: implications for life detection beyond Earth

Covering: 1961 to 2024Discovering and identifying unique natural products/biosignatures (signatures that can be used as evidence for past or present life) that are abundant, and complex enough that they indicate robust evidence of life is a multifaceted process. One distinct category of biosignatures being explored is organic compounds. A subdivision of these compounds not yet readily investigated are volatile organic compound (VOCs). When assessing these VOCs as a group (volatilome) a fingerprint of all VOCs within an environment allows the complex patterns in metabolic data to be unravelled. As a technique already successfully applied to many biological and ecological fields, this paper explores how analysis of volatilomes in terrestrial extreme environments could be used to enhance processes (such as metabolomics and metagenomics) already utilised in life detection beyond Earth. By overcoming some of the complexities of collecting VOCs in remote field sites, a variety of lab based analytical equipment and techniques can then be utilised. Researching volatilomics in astrobiology requires time to characterise the patterns of VOCs. They must then be differentiated from abiotic (non-living) signals within extreme environments similar to those found on other planetary bodies (analogue sites) or in lab-based simulated environments or microcosms. Such an effort is critical for understanding data returned from past or upcoming missions, but it requires a step change in approach which explores the volatilome as a vital additional tool to current 'Omics techniques.

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

BACKGROUND

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

AIM OF REVIEW

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

KEY SCIENTIFIC CONCEPTS OF REVIEW

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

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

BACKGROUND

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSIONS

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

The Diagnostic Utility of Volatile Organic Compounds in Inflammatory Bowel Disease: A Systematic Review and Meta-Analysis

BACKGROUND

Volatile organic compounds [VOCs] show promise as potential biomarkers of for ulcerative colitis and Crohn's disease, two chronic, idiopathic, gastrointestinal disorders with diagnostic and management challenges. Non-invasive biomarkers aid early diagnosis and management. In this study we review studies of diagnostic accuracy of VOCs in inflammatory bowel disease.

METHODS

A systematic search was carried out on the Pubmed and Scopus databases; with 16 studies reviewed and meta-analysis carried out on 10.

RESULTS

Meta-analysis of 696 inflammatory bowel disease [IBD] cases against 605 controls revealed a pooled sensitivity and specificity of 87% (95% confidence interval [CI], 0.79 - 0.92) and 83% [95% CI, 0.73 - 0.90], respectively. Area under the curve [AUC] was 0.92.

CONCLUSION

VOCs perform very well as non-invasive biomarkers of IBD, with much scope for future improvement and research.

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

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

Identification of urinary volatile organic compounds as a potential non-invasive biomarker for esophageal cancer

Early diagnosis of esophageal cancer (EC) is extremely challenging. The study presented herein aimed to assess whether urinary volatile organic compounds (VOCs) may be emerging diagnostic biomarkers for EC. Urine samples were collected from EC patients and healthy controls (HCs). Gas chromatography-ion mobility spectrometry (GC-IMS) was next utilised for volatile organic compound detection and predictive models were constructed using machine learning algorithms. ROC curve analysis indicated that an 8-VOCs based machine learning model could aid the diagnosis of EC, with the Random Forests having a maximum AUC of 0.874 and sensitivities and specificities of 84.2% and 90.6%, respectively. Urine VOC analysis aids in the diagnosis of EC.

Urinary biomarkers for hepatocellular carcinoma: current knowledge for clinicians

Hepatocellular carcinoma (HCC) is the most predominant primary liver cancer, causing many illnesses and deaths worldwide. The insidious clinical presentation, difficulty in early diagnosis, and the highly malignant nature make the prognosis of HCC extremely poor. The complex and heterogeneous pathogenesis of HCC poses significant challenges to developing therapies. Urine-based biomarkers for HCC, including diagnostic, prognostic, and monitoring markers, may be valuable supplements to current tools such as serum α-fetoprotein (AFP) and seem promising for progress in precision medicine. Herein, we reviewed the major urinary biomarkers for HCC and assessed their potential for clinical application. Molecular types, testing platforms, and methods for building multimolecule models in the included studies have shown great diversity, thus providing abundant novel tools for future clinical transformation and applications.

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.

Sensitivity and specificity of in vivo COVID-19 screening by detection dogs: Results of the C19-Screendog multicenter study

Trained dogs can recognize the volatile organic compounds contained in biological samples of patients with COVID-19 infection. We assessed the sensitivity and specificity of in vivo SARS-CoV-2 screening by trained dogs. We recruited five dog-handler dyads. In the operant conditioning phase, the dogs were taught to distinguish between positive and negative sweat samples collected from volunteers' underarms in polymeric tubes. The conditioning was validated by tests involving 16 positive and 48 negative samples held or worn in such a way that the samples were invisible to the dog and handler. In the screening phase the dogs were led by their handlers to a drive-through facility for in vivo screening of volunteers who had just received a nasopharyngeal swab from nursing staff. Each volunteer who had already swabbed was subsequently tested by two dogs, whose responses were recorded as positive, negative, or inconclusive. The dogs' behavior was constantly monitored for attentiveness and wellbeing. All the dogs passed the conditioning phase, their responses showing a sensitivity of 83-100% and a specificity of 94-100%. The in vivo screening phase involved 1251 subjects, of whom 205 had a COVID-19 positive swab and two dogs per each subject to be screened. Screening sensitivity and specificity were respectively 91.6-97.6% and 96.3-100% when only one dog was involved, whereas combined screening by two dogs provided a higher sensitivity. Dog wellbeing was also analyzed: monitoring of stress and fatigue suggested that the screening activity did not adversely impact the dogs' wellbeing. This work, by screening a large number of subjects, strengthen recent findings that trained dogs can discriminate between COVID-19 infected and healthy human subjects and introduce two novel research aspects: i) assessement of signs of fatigue and stress in dogs during training and testing, and ii) combining screening by two dogs to improve detection sensitivity and specificity. Using some precautions to reduce the risk of infection and spillover, in vivo COVID-19 screening by a dog-handler dyad can be suitable to quickly screen large numbers of people: it is rapid, non-invasive and economical, since it does not involve actual sampling, lab resources or waste management, and is suitable to screen large numbers of people.

A Systematic Review and Meta-Analysis: Volatile Organic Compound Analysis in the Detection of Hepatobiliary and Pancreatic Cancers

BACKGROUND

Hepatobiliary cancers are notoriously difficult to detect, frequently leading to diagnosis in later stages of disease when curative treatment is not an option. The currently used biomarkers such as AFP (alpha-fetoprotein) and CA19.9 lack sensitivity and specificity. Hence, there is an unmet need for an alternative biomarker.

AIM

To evaluate the diagnostic accuracy of volatile organic compounds (VOCs) for the detection of hepatobiliary and pancreatic cancers.

METHODS

A systematic review of VOCs' use in the detection of hepatobiliary and pancreatic cancers was performed. A meta-analysis was performed using the software R. Heterogeneity was explored through meta-regression analysis.

RESULTS

A total of 18 studies looking at 2296 patients were evaluated. Pooled sensitivity and specificity of VOCs for the detection of hepatobiliary and pancreatic cancer were 0.79 (95% CI, 0.72-0.85) and 0.81 (97.5% CI, 0.76-0.85), respectively. The area under the curve was 0.86. Meta-regression analysis showed that the sample media used contributed to heterogeneity. Bile-based VOCs showed the highest precision values, although urine and breath are preferred for their feasibility.

CONCLUSIONS

Volatile organic compounds have the potential to be used as an adjunct tool to aid in the early diagnosis of hepatobiliary cancers.

Circulating Biomarkers for the Early Diagnosis and Management of Hepatocellular Carcinoma with Potential Application in Resource-Limited Settings

Hepatocellular carcinoma (HCC) is among the world's third most lethal cancers. In resource-limited settings (RLS), up to 70% of HCCs are diagnosed with limited curative treatments at an advanced symptomatic stage. Even when HCC is detected early and resection surgery is offered, the post-operative recurrence rate after resection exceeds 70% in five years, of which about 50% occur within two years of surgery. There are no specific biomarkers addressing the surveillance of HCC recurrence due to the limited sensitivity of the available methods. The primary goal in the early diagnosis and management of HCC is to cure disease and improve survival, respectively. Circulating biomarkers can be used as screening, diagnostic, prognostic, and predictive biomarkers to achieve the primary goal of HCC. In this review, we highlighted key circulating blood- or urine-based HCC biomarkers and considered their potential applications in resource-limited settings, where the unmet medical needs of HCC are disproportionately highly significant.

The Influence of Mechanical Bowel Preparation on Volatile Organic Compounds for the Detection of Gastrointestinal Disease-A Systematic Review

(1) Background: Colorectal cancer is the second commonest cause of cancer deaths worldwide; recently, volatile organic compounds (VOCs) have been proposed as potential biomarkers of this disease. In this paper, we aim to identify and review the available literature on the influence of mechanical bowel preparation on VOC production and measurement. (2) Methods: A systematic search for studies was carried out for articles relevant to mechanical bowel preparation and its effects on volatile organic compounds. A total of 4 of 1349 papers initially derived from the search were selected. (3) Results: Two studies with a total of 134 patients found no difference in measured breath VOC profiles after bowel preparation; one other study found an increase in breath acetone in 61 patients after bowel preparation, but no other compounds were affected. Finally, the last study showed the alteration of urinary VOC profiles. (4) Conclusions: There is limited data on the effect of bowel preparation on VOC production in the body. As further studies of VOCs are conducted in patients with symptoms of gastrointestinal disease, the quantification of the effect of bowel preparation on their abundance is required.

Pancreatic Cystic Lesions: A Focused Review on Cyst Clinicopathological Features and Advanced Diagnostics

Macroscopic, endomicroscopic, and histologic findings and correlation are an integral part of the diagnostic evaluation of pancreatic cystic lesions (PCLs), as complementing morphologic features seen by different specialties are combined to contribute to a final diagnosis. However, malignancy risk stratification of PCLs with worrisome features can still be challenging even after endoscopic ultrasound guided-fine needle aspiration (EUS-FNA) with cytological evaluation. This review aims to summarize cyst clinicopathological features from the pathologists' perspective, coupled with knowledge from advanced diagnostics-confocal laser endomicroscopy and cyst fluid molecular analysis, to demonstrate the state-of-art risk stratification of PCLs. This review includes illustrative photos of surgical specimens, endomicroscopic and histologic images, and a summary of cyst fluid molecular markers.

Urinary volatile Organic compounds in non-alcoholic fatty liver disease (NAFLD), type two diabetes mellitus (T2DM) and NAFLD-T2DM coexistence

INTRODUCTION

Accumulating evidence have shown a significant correlation between urinary volatile organic compounds (VOCs) profile and the manifestation of several physiological and pathological states, including liver diseases. Previous studies have investigated the urinary metabolic signature as a non-invasive tool for the early discrimination between non-alcoholic fatty liver (NAFL) and non-alcoholic steatohepatitis (NASH), which nowadays represents one of the most important challenges in this context, feasible only by carrying out liver biopsy.

OBJECTIVES

The aim of the study was to investigate the differences in the urinary VOCs profiles of non-alcoholic fatty liver disease (NAFLD) patients, diabetes mellitus (T2DM) subjects and NAFLD/T2DM patients.

METHODS

Headspace solid-phase microextraction (HS-SPME) coupled with gas chromatography-mass spectrometry (GC-MS) was applied to profile the urinary VOCs. Urine samples were analysed both under acid and alkaline conditions, to obtain a range of urinary volatiles with different physicochemical properties.

RESULTS

Urinary VOCs profiles of 13 NAFLD patients, 13 T2DM subjects and 13 NAFLD/T2DM patients were investigated by multivariate and univariate data analysis techniques which allowed to identify 21 volatiles under alkaline conditions able to describe the NAFLD/T2DM group concerning the other two groups.

CONCLUSION

Our results suggest that VOCs signatures can improve the knowledge of the pathological condition where NAFLD coexists with T2DM and discovering new features that are not simply the sum of the two diseases. These preliminary findings may be considered as hypothesis-generating, to be clearly confirmed by larger prospective investigations.

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.

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.

Diagnostic Ability of Volatile Organic Compounds in Digestive Cancer: A Systematic Review With Meta-Analysis

Background:

Volatile organic compounds (VOCs) have been involved in cancer diagnosis via breath, urine, and feces. We aimed to assess the diagnostic ability of VOCs on digestive cancers.

Methods:

We systematically reviewed prospective clinical trials evaluating VOCs’ diagnostic ability on esophageal, gastric, colorectal, hepatic, and pancreatic cancer (PC). Databases including PubMed and Ovid-Medline were searched.

Results:

A total of 35 trials with 5314 patient-times qualified for inclusion. The pooled sensitivity of VOCs diagnosing gastroesophageal cancer from healthy controls is 0.89 (95% confidence interval [CI]: 0.82-0.94), the pooled specificity is 0.890 (95% CI: 0.84-0.93), and area under the curve (AUC) of the summary receiver operating characteristic curve is 0.95 (95% CI: 0.93-0.95). The pooled sensitivity of VOCs diagnosing colorectal cancer from heathy controls is 0.92 (95% CI: 0.85-0.96), the pooled specificity is 0.88 (95% CI: 0.77-0.94), and the AUC is 0.96 (95% CI: 0.94-0.97). The pooled sensitivity of VOCs distinguishing gastrointestinal (GI) cancer from precancerous lesions is 0.84 (95% CI: 0.67-0.92), the pooled specificity is 0.74 (95% CI: 0.43-0.91), and the AUC is 0.87 (95% CI: 0.84-0.89). The pooled sensitivity of VOCs diagnosing hepatocellular carcinoma is 0.68 (95% CI: 0.52-0.81), the pooled specificity is 0.81 (95% CI: 0.47-0.96), and the AUC is 0.78 (95% CI: 0.74-0.81). The pooled sensitivity of VOCs diagnosing PC is 0.88 (95% CI: 0.80-0.93), the pooled specificity is 0.82 (95% CI: 0.62-0.93), and the AUC is 0.92 (95% CI: 0.89-0.94).

Conclusions:

Volatile organic compounds have potential role in diagnosing GI cancer with comparatively high sensitivity, specificity, and AUC (PROSPERO registration number: CRD42021260039).

Minimal Gluten Exposure Alters Urinary Volatile Organic Compounds in Stable Coeliac Disease

Coeliac disease (CD) patients are distinguishable from healthy individuals via urinary volatile organic compounds (VOCs) analysis. We exposed 20 stable CD patients on gluten-free diet (GFDs) to a 14-day, 3 g/day gluten challenge (GCh), and assessed urinary VOC changes. A control cohort of 20 patients continued on GFD. Urine samples from Days 0, 7, 14, 28 and 56 were analysed using Lonestar FAIMS and Markes Gas Chromatography-Time of Flight-Mass Spectrometer (GC-TOF-MS). VOC signatures on D (day) 7-56 were compared with D0. Statistical analysis was performed using R. In GCh patients, FAIMS revealed significant VOC differences for all time points compared to D0. GC-TOF-MS revealed significant changes at D7 and D14 only. In control samples, FAIMS revealed significant differences at D7 only. GC-TOF-MS detected no significant differences. Chemical analysis via GC-MS-TOF revealed 12 chemicals with significantly altered intensities at D7 vs. D0 for GCh patients. The alterations persisted for six chemicals at D14 and one (N-methyltaurine) remained altered after D14. This low-dose, short-duration challenge was well tolerated. FAIMS and GC-TOF-MS detected VOC signature changes in CD patients when undergoing a minimal GCh. These findings suggest urinary VOCs could have a role in monitoring dietary compliance in CD patients.

Detection of spontaneous preterm birth by maternal urinary volatile organic compound analysis: A prospective cohort study

Accurate prediction of preterm birth is currently challenging, resulting in unnecessary maternal hospital admittance and fetal overexposure to antenatal corticosteroids. Novel biomarkers like volatile organic compounds (VOCs) hold potential for predictive, bed-side clinical applicability. In a proof of principle study, we aimed to assess the predictive potential of urinary volatile organic compounds in the identification of pregnant women at risk for preterm birth. Urine samples of women with a high risk for preterm birth (≧24 + 0 until 36 + 6 weeks) were collected prospectively and analyzed for VOCs using gas chromatography coupled with an ion mobility spectrometer (GS-IMS). Urinary VOCs of women delivering preterm were compared with urine samples of women with suspicion of preterm birth collected at the same gestation period but delivering at term. Additionally, the results were also interpreted in combination with patient characteristics, such as physical examination at admission, microbial cultures, and placental pathology. In our cohort, we found that urinary VOCs of women admitted for imminent preterm birth were not significantly different in the overall group of women delivering preterm vs. term. However, urinary VOCs of women admitted for imminent preterm birth and delivering between 28 + 0 until 36 + 6 weeks compared to women with a high risk for preterm birth during the same gestation period and eventually delivering at term (>37 + 0 weeks) differed significantly (area under the curve: 0.70). In addition, based on the same urinary VOCs, we could identify women with a confirmed chorioamnionitis (area under the curve: 0.72) and urinary tract infection (area under the curve: 0.97). In conclusion, urinary VOCs hold potential for non-invasive, bedside prediction of preterm birth and on the spot identification of intra-uterine infection and urinary tract infections. We suggest these observations are further explored in larger populations.

Application of Mass Spectrometry in Pancreatic Cancer Translational Research

Pancreatic cancer (PC) is one of the most common malignant tumors in the digestive tract worldwide, with increased morbidity and mortality. In recent years, with the development of surgery, chemotherapy, radiotherapy, targeted therapy, and immunotherapy, and the change of the medical thinking model, remarkable progress has been made in researching comprehensive diagnosis and treatment of PC. However, the present situation of diagnostic and treatment of PC is still unsatisfactory. There is an urgent need for academia to fully integrate the basic research and clinical data from PC to form a research model conducive to clinical translation and promote the proper treatment of PC. This paper summarized the translation progress of mass spectrometry (MS) in the pathogenesis, diagnosis, prognosis, and PC treatment to promote the basic research results of PC into clinical diagnosis and treatment.

Liver Impairment-The Potential Application of Volatile Organic Compounds in Hepatology

Liver diseases are currently diagnosed through liver biopsy. Its invasiveness, costs, and relatively low diagnostic accuracy require new techniques to be sought. Analysis of volatile organic compounds (VOCs) in human bio-matrices has received a lot of attention. It is known that a musty odour characterises liver impairment, resulting in the elucidation of volatile chemicals in the breath and other body fluids such as urine and stool, which may serve as biomarkers of a disease. Aims: This study aims to review all the studies found in the literature regarding VOCs in liver diseases, and to summarise all the identified compounds that could be used as diagnostic or prognostic biomarkers. The literature search was conducted on ScienceDirect and PubMed, and each eligible publication was qualitatively assessed by two independent evaluators using the SANRA critical appraisal tool. Results: In the search, 58 publications were found, and 28 were kept for inclusion: 23 were about VOCs in the breath, one in the bile, three in urine, and one in faeces. Each publication was graded from zero to ten. A graphical summary of the metabolic pathways showcasing the known liver disease-related VOCs and suggestions on how VOC analysis on liver impairment could be applied in clinical practice are given.

Non-Invasive Detection and Staging of Colorectal Cancer Using a Portable Electronic Nose

Electronic noses (e-nose) offer potential for the detection of cancer in its early stages. The ability to analyse samples in real time, at a low cost, applying easy-to-use and portable equipment, gives e-noses advantages over other technologies, such as Gas Chromatography-Mass Spectrometry (GC-MS). For diseases such as cancer with a high mortality, a technology that can provide fast results for use in routine clinical applications is important. Colorectal cancer (CRC) is among the highest occurring cancers and has high mortality rates, if diagnosed late. In our study, we investigated the use of portable electronic nose (PEN3), with further analysis using GC-TOF-MS, for the analysis of gases and volatile organic compounds (VOCs) to profile the urinary metabolome of colorectal cancer. We also compared the different cancer stages with non-cancers using the PEN3 and GC-TOF-MS. Results obtained from PEN3, and GC-TOF-MS demonstrated high accuracy for the separation of CRC and non-cancer. PEN3 separated CRC from non-cancerous group with 0.81 AUC (Area Under the Curve). We used data from GC-TOF-MS to obtain a VOC profile for CRC, which identified 23 potential biomarker VOCs for CRC. Thus, the PEN3 and GC-TOF-MS were found to successfully separate the cancer group from the non-cancer group.