A pilot study combining a GC-sensor device with a statistical model for the identification of bladder cancer from urine headspace

Pilot study for bladder cancer detection with volatile organic compounds using ion mobility spectrometry: a novel urine-based approach

PURPOSE

Despite many efforts, no reliable urinary marker system has so far shown the potential to substitute cystoscopy. Measuring volatile organic compounds (VOCs) from urine is a promising alternative. VOCs are metabolic products which can be measured from the headspace of urine samples. Previous studies confirmed that the urine of bladder tumor patients has a different VOC profile than healthy controls. In this pilot study, the feasibility of discriminating VOCs from urine of bladder cancer patients from that of healthy control subjects was investigated. Aim of this study was to investigate whether VOC-based diagnosis of bladder cancer from urine samples is feasible using multicapillary column ion mobility spectrometry (MCC/IMS) and to identify potential molecular correlates to the relevant analytes.

METHODS

Headspace measurements of urine samples of 30 patients with confirmed transitional cell carcinoma (TCC) and 30 healthy controls were performed using MCC/IMS. In the results of the measurements, peaks showing significant differences between both groups were identified and implemented into a decision tree with respect to achieve group separation. Molecular correlates were predicted using a pre-defined dataset.

RESULTS

Eight peaks with significantly differing intensity were identified, 5 of which were highly significant. Using a six-step decision tree, MCC/IMS showed a sensitivity of 90% and specificity of 100% in group separation.

CONCLUSION

VOC-based detection of bladder cancer is feasible. MCC/IMS is a suitable method for urine-based diagnosis and should be further validated. The molecular characteristics and metabolic background of the analytes require further workup.

Exploiting volatile fingerprints for bladder cancer diagnosis: A scoping review of metabolomics and sensor-based approaches

Bladder cancer (BC) represents a significant global health concern, for which early detection is essential to improve patient outcomes. This review evaluates the potential of the urinary volatile organic compounds (VOCs) as biomarkers for detecting and staging BC. The methods used include gas chromatography-mass spectrometry (GC-MS)-based metabolomics and electronic-nose (e-nose) sensors. The GC-MS studies that have been published reveal diverse results in terms of diagnostic performance. The sensitivities range from 27 % to an impressive 97 %, while specificities vary between 43 % and 94 %. Furthermore, the accuracies reported in these studies range from 80 to 89 %. In the urine of BC patients, a total of 80 VOCs were discovered to be significantly altered when compared to controls. These VOCs encompassed a variety of chemical classes such as alcohols, aldehydes, alkanes, aromatic compounds, fatty acids, ketones, and terpenoids, among others. Conversely, e-nose-based studies displayed sensitivities from 60 to 100 %, specificities from 53 to 96 %, and accuracies from 65 to 97 %. Interestingly, conductive polymer-based sensors performed better, followed by metal oxide semiconductor and optical sensors. GC-MS studies have shown improved performance in detecting early stages and low-grade tumors, providing valuable insights into staging. Based on these findings, VOC-based diagnostic tools hold great promise for early BC detection and staging. Further studies are needed to validate biomarkers and their classification performance. In the future, advancements in VOC profiling technologies may significantly contribute to improving the overall survival and quality of life for BC patients.

Urine Metabolomic Signature of People Diagnosed with Balkan Endemic Nephropathy and Other Types of Chronic Kidney Disease Compared with Healthy Subjects in Romania

Metabolomic analysis methods were employed to determine biomarkers for various chronic kidney diseases (CKDs). Modern analytical methods were developed and applied successfully to find a specific metabolomic profile in urine samples from CKD and Balkan endemic nephropathy (BEN) patients. The aim was to explore a specific metabolomic profile defined by feasible/easy-to-identify molecular markers. Urine samples were collected from patients with CKDs and BEN, and from healthy subjects from endemic and nonendemic areas in Romania. Metabolomic analysis of urine samples, extracted by the liquid-liquid extraction (LLE) method, was performed by gas chromatography-mass spectrometry (GC-MS). The statistical exploration of the results was performed through a principal component analysis (PCA) evaluation. Urine samples were statistically analyzed using a classification based on six types of metabolites. Most urinary metabolites are distributed in the center of a loading plot, meaning that these compounds do not represent significant markers for BEN. One of the most frequent and higher-concentration urinary metabolites in BEN patients was p-Cresol, a phenolic compound that implies a severe injury of the renal filtration function. The presence of p-Cresol was associated with protein-bound uremic toxins, which have specific functional groups such as indole and phenyl. In prospective studies for future investigation, prevention, and disease treatment, we suggest a larger sample size, sample extraction using other methods, and analysis using other chromatography techniques coupled with mass spectrometry, which can generate a more significant data set for statistical analysis.

GC-MS Techniques Investigating Potential Biomarkers of Dying in the Last Weeks with Lung Cancer

Predicting when a patient with advanced cancer is dying is a challenge and currently no prognostic test is available. We hypothesised that a dying process from cancer is associated with metabolic changes and specifically with changes in volatile organic compounds (VOCs). We analysed urine from patients with lung cancer in the last weeks of life by headspace gas chromatography mass spectrometry. Urine was acidified or alkalinised before analysis. VOC changes in the last weeks of life were identified using univariate, multivariate and linear regression analysis; 12 VOCs increased (11 from the acid dataset, 2 from the alkali dataset) and 25 VOCs decreased (23 from the acid dataset and 3 from the alkali dataset). A Cox Lasso prediction model using 8 VOCs predicted dying with an AUC of 0.77, 0.78 and 0.85 at 30, 20 and 10 days and stratified patients into a low (median 10 days), medium (median 50 days) or high risk of survival. Our data supports the hypothesis there are specific metabolic changes associated with the dying. The VOCs identified are potential biomarkers of dying in lung cancer and could be used as a tool to provide additional prognostic information to inform expert clinician judgement and subsequent decision making.

Investigation of urinary volatile organic compounds as novel diagnostic and surveillance biomarkers of bladder cancer

BACKGROUND

The diagnosis and surveillance of urothelial bladder cancer (UBC) require cystoscopy. There is a need for biomarkers to reduce the frequency of cystoscopy in surveillance; urinary volatile organic compound (VOC) analysis could fulfil this role. This cross-sectional study compared the VOC profiles of patients with and without UBC, to investigate metabolomic signatures as biomarkers.

METHODS

Urine samples were collected from haematuria clinic patients undergoing diagnostic cystoscopy and UBC patients undergoing surveillance. Urinary headspace sampling utilised solid-phase microextraction and VOC analysis applied gas chromatography-mass spectrometry; the output underwent metabolomic analysis.

RESULTS

The median participant age was 70 years, 66.2% were male. Of the haematuria patients, 21 had a new UBC diagnosis, 125 had no cancer. In the surveillance group, 75 had recurrent UBC, 84 were recurrence-free. A distinctive VOC profile was observed in UBC patients compared with controls. Ten VOCs had statistically significant abundances useful to classify patients (false discovery rate range 1.9 × 10-7-2.8 × 10-2). Two prediction models were evaluated using internal validation. An eight-VOC diagnostic biomarker panel achieved AUROC 0.77 (sensitivity 0.71, specificity 0.72). A six-VOC surveillance biomarker panel obtained AUROC 0.80 (sensitivity 0.71 and specificity 0.80).

CONCLUSIONS

Urinary VOC analysis could aid the diagnosis and surveillance of UBC.

Artificially Intelligent Olfaction for Fast and Noninvasive Diagnosis of Bladder Cancer from Urine

Globally, bladder cancer (BLC) is one of the most common cancers and has a high recurrence and mortality rate. Current clinical diagnostic approaches are either invasive or inaccurate. Here, we report on a cost-efficient, artificially intelligent chemiresistive sensor array made of polyaniline (PANI) derivatives that can noninvasively diagnose BLC at an early stage and maintain postoperative surveillance through ″smelling″ clinical urine samples at room temperature. In clinical trials, 18 healthy controls and 76 BLC patients (60 and 16 at early and advanced stages, respectively) are assessed by the artificial olfactory system. With the assistance of a support vector machine (SVM), very high sensitivity and accuracy from healthy controls are achieved, exceeding those obtained by the current techniques in practice. In addition, the recurrences of both early and advanced stages are diagnosed well, with the effect of confounding factors on the performance of the artificial olfactory system found to have a negligible influence on the diagnostic performance. Overall, this study contributes a novel, noninvasive, easy-to-use, inexpensive, real-time, accurate method for urine disease diagnosis, which can be useful for personalized care/diagnosis and postoperative surveillance, resulting in saving more lives.

Urinary Volatiles and Chemical Characterisation for the Non-Invasive Detection of Prostate and Bladder Cancers

Bladder cancer (BCa) and prostate cancer (PCa) are some of the most common cancers in the world. In both BCa and PCa, the diagnosis is often confirmed with an invasive technique that carries a risk to the patient. Consequently, a non-invasive diagnostic approach would be medically desirable and beneficial to the patient. The use of volatile organic compounds (VOCs) for disease diagnosis, including cancer, is a promising research area that could support the diagnosis process. In this study, we investigated the urinary VOC profiles in BCa, PCa patients and non-cancerous controls by using gas chromatography-ion mobility spectrometry (GC-IMS) and gas chromatography time-of-flight mass spectrometry (GC-TOF-MS) to analyse patient samples. GC-IMS separated BCa from PCa (area under the curve: AUC: 0.97 (0.93-1.00)), BCa vs. non-cancerous (AUC: 0.95 (0.90-0.99)) and PCa vs. non-cancerous (AUC: 0.89 (0.83-0.94)) whereas GC-TOF-MS differentiated BCa from PCa (AUC: 0.84 (0.73-0.93)), BCa vs. non-cancerous (AUC: 0.81 (0.70-0.90)) and PCa vs. non-cancerous (AUC: 0.94 (0.90-0.97)). According to our study, a total of 34 biomarkers were found using GC-TOF-MS data, of which 13 VOCs were associated with BCa, seven were associated with PCa, and 14 VOCs were found in the comparison of BCa and PCa.

Odors and cancer: Current status and future directions

Cancer is the second leading cause of death in the world. Because tumors detected at early stages are easier to treat, the search for biomarkers-especially non-invasive ones-that allow early detection of malignancies remains a central goal to reduce cancer mortality. Cancer, like other pathologies, often alters body odors, and much has been done by scientists over the last few decades to assess the value of volatile organic compounds (VOCs) as signatures of cancers. We present here a quantitative review of 208 studies carried out between 1984 and 2020 that explore VOCs as potential biomarkers of cancers. We analyzed the main findings of these studies, listing and classifying VOCs related to different cancer types while considering both sampling methods and analysis techniques. Considering this synthesis, we discuss several of the challenges and the most promising prospects of this research direction in the war against cancer.

Improved Non-Invasive Diagnosis of Bladder Cancer with an Electronic Nose: A Large Pilot Study

BACKGROUND

Bladder cancer (BCa) emits specific volatile organic compounds (VOCs) in the urine headspace that can be detected by an electronic nose. The diagnostic performance of an electronic nose in detecting BCa was investigated in a pilot study.

METHODS

A prospective, single-center, controlled, non-randomized, phase 2 study was carried out on 198 consecutive subjects (102 with proven BCa, 96 controls). Urine samples were evaluated with an electronic nose provided with 32 volatile gas analyzer sensors. The tests were repeated at least two times per sample. Accuracy, sensitivity, specificity, and variability were evaluated using mainly the non-parametric combination method, permutation tests, and discriminant analysis classification.

RESULTS

Statistically significant differences between BCa patients and controls were reported by 28 (87.5%) of the 32 sensors. The overall discriminatory power, sensitivity, and specificity were 78.8%, 74.1%, and 76%, respectively; 13/96 (13.5%) controls and 29/102 (28.4%) BCa patients were misclassified as false positive and false negative, respectively. Where the most efficient sensors were selected, the sensitivity and specificity increased up to 91.1% (72.5-100) and 89.1% (81-95.8), respectively. None of the tumor characteristics represented independent predictors of device responsiveness.

CONCLUSIONS

The electronic nose might represent a potentially reliable, quick, accurate, and cost-effective tool for non-invasive BCa diagnosis.

Developing non-invasive bladder cancer screening methodology through potentiometric multisensor urine analysis

We report on the feasibility study exploring the potential of a simple electrochemical multisensor system as a tool for distinguishing between urine samples from patients with confirmed bladder cancer (36 samples) and healthy volunteers (51 samples). The potentiometric sensor responses obtained in urine samples were employed as the input data for various machine learning classification algorithms (logistic regression, random forest, extreme gradient boosting classifier, support vector machine, and voting classifier). The performance metrics of the classifiers were evaluated via Monte-Carlo cross-validation. The best model combining all the acquired data from the people aged 19-88 with different tumor grades and malignancies, including patients with recurrent bladder cancer, yielded 72% accuracy, 71% sensitivity, and 58% specificity. It was found that these metrics can be improved to 76% accuracy, 80% sensitivity, and 75% specificity when only a limited age group (50-88 years of age) is considered. Taking into account the simplicity of the proposed screening method, this technique appears to be a promising tool for further research.

Differentiating cancer types using a urine test for volatile organic compounds

BACKGROUND

In the human body, volatile organic compounds (VOCs) are produced by different tissues then secreted in different body fluids and subsequently excreted. Here we explore a non-invasive method for the detection of liver, prostate and bladder cancers.

METHODS

We recruited 140 cases. There were 31 hepatocellular carcinomas (HCC), 62 prostate carcinomas, 29 bladder carcinomas and 18 non-cancer cases. Male to female ratio was 5:1 and mean age was 72 years. Urinary VOCs were detected by applying solid-phase microextraction (SPME) technique.

RESULTS

The sensitivity for detection of HCC with normal alpha fetoprotein (AFP) was 68% (SE 0.06, 95% CI 0.54 to 0.81 and P < 0.005). The VOCs sensitivity in the detection of HCC cases with raised AFP was 83%. (SE 0.05, 95% CI 0.73 to 0.93 and P < 0.0001). The VOCs sensitivity for prostate cancer detection was 70% (SE 0.049, 95% CI 0.60 to 0.79 and P < 0.0002) and sensitivity for bladder cancer detection was 81% (SE 0.052, 95% CI 0.70 to 0.91 and P < 0.0001).

CONCLUSIONS

SPME urinary VOCs analysis was able to differentiate between controls and each of hepatocellular, prostate and bladder cancers. This suggests that urinary VOCs are cancer specific and could potentially be used as a diagnostic method.

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.

Breath analysis for detection of viral infection, the current position of the field

The COVID-19 pandemic has highlighted the importance of rapid, cost effective, accurate, and non-invasive testing for viral infections. Volatile compounds (VCs) have been suggested for several decades as fulfilling these criteria. However currently very little work has been done in trying to diagnose viral infections using VCs. Much of the work carried out to date involves the differentiation of bacterial and viral sources of infection and often the detection of bacterial and viral co-infection. However, this has usually been done in vitro and very little work has involved the use of human participants. Viruses hijack the host cell metabolism and do not produce their own metabolites so identifying virus specific VCs is at best a challenging task. However, there are proteins and lipids that are potential candidates as markers of viral infection. The current understanding is that host cell glycolysis is upregulated under viral infection to increase the available energy for viral replication. There is some evidence that viral infection leads to the increase of production of fatty acids, alkanes, and alkanes related products. For instance, 2,3-butandione, aldehydes, 2,8-dimethyl-undecane and n-propyl acetate have all been correlated with viral infection. Currently, the literature points to markers of oxidative stress (e.g. nitric oxide, aldehydes etc) being the most useful in the determination of viral infection. The issue, however, is that there are also many other conditions that can lead to oxidative stress markers being produced. In this review a range of (mainly mass spectrometric) methods are discussed for viral detection in breath, including breath condensate. Currently MALDI-ToF-MS is likely to be the preferred method for the identification of viral strains and variants of those strains, however it is limited by its need for the viral strains to have been sequenced and logged in a database.

Fluorometric optical sensor arrays for the detection of urinary bladder cancer specific volatile organic compounds in the urine of patients with frank hematuria: a prospective case-control study

This study outlines a simple fluorometric optical sensor system for the sensitive, real time measurement of volatile organic compounds (VOCs) as biomarkers of urinary bladder cancer in patients presenting with frank hematuria and confirmed to have the disease on histopathology. Arrays of 24 sensor points based on fluorescence VOC sensitive materials were made. Urine samples of 38 consecutive patients with pathologically confirmed bladder tumours and 41 age and gender matched healthy controls were recruited and analysed using this sensor array. This system correctly classified 68 out of 79 urine samples with 84.21% sensitivity and 87.80% specificity; the system also achieved 66.67% sensitivity and 75.00% specificity for classification of high-grade and low-grade bladder cancer patients. This study showed promising results in the detection of urinary bladder cancer as well as to classify high grade versus low grade bladder cancers.

Non-invasive Biodiversified Sensors: A Modernized Screening Technology for Cancer

Background:

Biological sensors revolutionize the method of diagnoses of diseases from early to final stages using the biomarkers present in the body. Biosensors are advantageous due to the involvement of minimal sample collection with improved specificity and sensitivity for the detection of biomarkers.

Methods:

Conventional biopsies restrict problems like patient non-compliance, cross-infection and high cost and to overcome these issues biological samples like saliva, sweat, urine, tears and sputum progress into clinical and diagnostic research for the development of non-invasive biosensors. This article covers various non-invasive measurements of biological samples, optical-based, mass-based, wearable and smartphone-based biosensors for the detection of cancer.

Results:

The demand for non-invasive, rapid and economic analysis techniques escalated due to the modernization of the introduction of self-diagnostics and miniature forms of devices. Biosensors have high sensitivity and specificity for whole cells, microorganisms, enzymes, antibodies, and genetic materials.

Conclusion:

Biosensors provide a reliable early diagnosis of cancer, which results in faster therapeutic outcomes with in-depth fundamental understanding of the disease progression.

Optical sensory arrays for the detection of urinary bladder cancer-related volatile organic compounds

Non-invasive detection of urinary bladder cancer remains a significant challenge. Urinary volatile organic compounds (VOCs) are a promising alternative to cell-based biomarkers. Herein, we demonstrate a novel diagnosis system based on an optic fluorescence sensor array for detecting urinary bladder cancer VOCs biomarkers. This study describes a fluorescence-based VOCs sensor array detecting system in detail. The choice of VOCs for the initial part was based on an extensive systematic search of the literature and then followed up using urinary samples from patients with urinary bladder transitional cell carcinoma. Canonical discriminant analysis and partial least squares discriminant analysis (PLS-DA) were employed and correctly detected 31/48 urinary bladder cancer VOC biomarkers and achieved an overall 77.75% sensitivity and 93.25% specificity by PLS-DA modelling. All five urine samples from bladder cancer patients, and five healthy controls were successfully identified with the same sensor arrays. Overall, the experiments in this study describe a real-time platform for non-invasive bladder cancer diagnosis using fluorescence-based gas-sensor arrays. Pure VOCs and urine samples from the patients proved such a system to be promising; however, further research is required using a larger population sample.

Review and Comparison of Cancer Biomarker Trends in Urine as a Basis for New Diagnostic Pathways

Cancer is one of the major causes of mortality worldwide and its already large burden is projected to increase significantly in the near future with a predicted 22 million new cancer cases and 13 million cancer-related deaths occurring annually by 2030. Unfortunately, current procedures for diagnosis are characterized by low diagnostic accuracies. Given the proved correlation between cancer presence and alterations of biological fluid composition, many researchers suggested their characterization to improve cancer detection at early stages. This paper reviews the information that can be found in the scientific literature, regarding the correlation of different cancer forms with the presence of specific metabolites in human urine, in a schematic and easily interpretable form, because of the huge amount of relevant literature. The originality of this paper relies on the attempt to point out the odor properties of such metabolites, and thus to highlight the correlation between urine odor alterations and cancer presence, which is proven by recent literature suggesting the analysis of urine odor for diagnostic purposes. This investigation aims to evaluate the possibility to compare the results of studies based on different approaches to be able in the future to identify those compounds responsible for urine odor alteration.

Urinary metabolites for urological cancer detection: a review on the application of volatile organic compounds for cancers

Cancer is one of the most devastating human diseases that causes a great number of mortalities each year worldwide. Thus, finding and treating cancers early is of increasing interest to the public and presents great opportunity for research. It is well known that the metabolism of cancer cells differs from that of normal tissues. Analysis of volatile organic compounds (VOCs), a group of small molecule metabolites, provides an emerging approach for cancer screening and disease monitoring. VOCs are continuously generated in human body and released through breath, blood, skin, urine and fecal samples, which carry information of the physiological and metabolic status. Furthermore, the development of effective analytical methods for VOCs detection is one of the challenging aspects in cancer research. In this review, the analytical methods such as solid-phase mirco-extraction (SPME) and stir bar sorptive extraction (SBSE) coupled with gas chromatography/mass spectrometry (GC-MS), the application of VOCs in urological cancers diagnosis and potential molecules pathways related to VOCs profile for cancer detection are discussed.

Exhaled-breath Testing for Prostate Cancer Based on Volatile Organic Compound Profiling Using an Electronic Nose Device (Aeonose™): A Preliminary Report

BACKGROUND

Prostate biopsy, an invasive examination, is the gold standard for diagnosing prostate cancer (PCa). There is a need for a novel noninvasive diagnostic tool that achieves a significantly high pretest probability for PCa, reducing unnecessary biopsy numbers. Recent studies have shown that volatile organic compounds (VOCs) in exhaled breath can be used to detect different types of cancers via training of an artificial neural network (ANN).

OBJECTIVE

To determine whether exhaled-breath analysis using a handheld electronic nose device can be used to discriminate between VOC patterns between PCa patients and healthy individuals.

DESIGN, SETTING, AND PARTICIPANTS

This prospective pilot study was conducted in the outpatient urology clinic of the Maastricht University Medical Center, the Netherlands. Patients with histologically proven PCa were already included before initial biopsy or during follow-up, with no prior treatment for their PCa. Urological patients with negative biopsies in the past year or patients with prostate enlargement (PE) with low or stable serum prostate-specific antigen were used as controls. Exhaled breath was probed from 85 patients: 32 with PCa and 53 controls (30 having negative biopsies and 23 PE).

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Patient characteristics were statistically analyzed using independent sample t test and Pearson's chi-square test. Data analysis was performed by Aethena software after data compression using the TUCKER3 algorithm. ANN models were trained and evaluated using the leave-10%-out cross-validation method.

RESULTS AND LIMITATIONS

Our trained ANN showed an accuracy of 0.75, with an area under the curve of 0.79 with sensitivity and specificity of 0.84 (95% confidence interval [CI] 0.66-0.94) and 0.70 (95% CI 0.55-0.81) respectively, comparing PCa with control individuals. The negative predictive value was found to be 0.88. The main limitation is the relatively small sample size.

CONCLUSIONS

Our findings imply that the Aeonose allows us to discriminate between patients with untreated, histologically proven primary PCa and control patients based on exhaled-breath analysis.

PATIENT SUMMARY

We explored the possibility of exhaled-breath analysis using an electronic nose, to be used as a noninvasive tool in clinical practice, as a pretest for diagnosing prostate cancer. We found that the electronic nose was able to discriminate between prostate cancer patients and control individuals.

Detection of Volatile Organic Compounds in a Drop of Urine by Ultrasonic Nebulization Extraction Proton Transfer Reaction Mass Spectrometry

Detection of volatile organic compounds (VOCs) in human urine has potential application value in screening for disease and toxin exposure. However, the current technologies are too slow to detect the concentration of VOCs in fresh urine. In this study, we developed a novel ultrasonic nebulization extraction proton transfer reaction mass spectrometry (UNE-PTR-MS) technology. The urinary VOCs can be rapidly extracted to gaseous VOCs using the UNE system and then delivered using a carrier gas to the PTR-MS instrument for rapid detection. The carrier gas flow and sample size were optimized to 100 mL/min and 100 μL, respectively. The limits of detection (LODs) and response time of the UNE-PTR-MS were evaluated by detecting three VOCs that are common in human urine: methanol, acetaldehyde, and acetone. The LODs determined for methanol (4.47 μg/L), acetaldehyde (1.98 μg/L), and acetone (3.47 μg/L) are 2-3 orders of magnitude lower than the mean concentrations of that in healthy human urine. The response time of the UNE-PTR-MS is 34 s and only 0.66 mL of urine is required for a full scan. The repeatability of this UNE-PTR-MS was evaluated, and the relative standard deviations of 5 independent determinations were between 4.62% and 5.21%. Lastly, the UNE-PTR-MS was applied for detection of methanol, acetaldehyde, and acetone in real human urine to test matrix effects, yielding relative recoveries of between 88.39% and 94.54%. These results indicate the UNE-PTR-MS can be used for the rapid detection of VOCs in a drop of urine and has practical potential for diagnosing disease or toxin exposure.

Urinary Volatile Organic Compounds as Potential Biomarkers in Idiopathic Membranous Nephropathy

OBJECTIVE

To detect urinary volatile organic compounds (VOCs) in patients with idiopathic membranous nephropathy (iMN) and normal controls, and to examine whether or not urinary VOCs can act as biomarkers for the diagnosis of iMN independent of renal biopsy.

MATERIALS AND METHODS

Gas chromatography/mass spectrometry (GC/MS) was used to assess the urine collected from 63 iMN patients and 15 normal controls. The statistical methods of principal component analysis and partial least squares discriminant analysis were performed to process the final data in Common Data Format which were converted from GC/MS data.

RESULTS

Six VOCs in the urine samples of iMN patients exhibited significant differences from those of normal controls: carbamic acid monoammonium salt, 2-pentanone, 2,4-dimethyl-pentanal, hydrogen azide, thiourea, and 4-heptanone were significantly higher than in controls (p < 0.05).

CONCLUSIONS

Six urinary VOCs were isolated from patients with iMN using GC/MS. The analysis of urinary VOCs using GC/MS could be developed into a non-invasive method for the detection of iMN.

Detection of inflammatory biomarkers in saliva and urine: Potential in diagnosis, prevention, and treatment for chronic diseases

Inflammation is a part of the complex biological response of inflammatory cells to harmful stimuli, such as pathogens, irritants, or damaged cells. This inflammation has been linked to several chronic diseases including cancer, atherosclerosis, rheumatoid arthritis, and multiple sclerosis. Major biomarkers of inflammation include tumor necrosis factor, interleukins (IL)-1, IL-6, IL-8, chemokines, cyclooxygenase, 5-lipooxygenase, and C-reactive protein, all of which are regulated by the transcription factor nuclear factor-kappaB. Although examining inflammatory biomarkers in blood is a standard practice, its identification in saliva and/or urine is more convenient and non-invasive. In this review, we aim to (1) discuss the detection of these inflammatory biomarkers in urine and saliva; (2) advantages of using salivary and urinary inflammatory biomarkers over blood, while also weighing on the challenges and/or limitations of their use; (3) examine their role(s) in connection with diagnosis, prevention, treatment, and drug development for several chronic diseases with inflammatory consequences, including cancer; and (4) explore the use of innovative salivary and urine based biosensor strategies that may permit the testing of biomarkers quickly, reliably, and cost-effectively, in a decentralized setting.

The use of a gas chromatography-sensor system combined with advanced statistical methods, towards the diagnosis of urological malignancies

Prostate cancer is one of the most common cancers. Serum prostate-specific antigen (PSA) is used to aid the selection of men undergoing biopsies. Its use remains controversial. We propose a GC-sensor algorithm system for classifying urine samples from patients with urological symptoms. This pilot study includes 155 men presenting to urology clinics, 58 were diagnosed with prostate cancer, 24 with bladder cancer and 73 with haematuria and or poor stream, without cancer. Principal component analysis (PCA) was applied to assess the discrimination achieved, while linear discriminant analysis (LDA) and support vector machine (SVM) were used as statistical models for sample classification. Leave-one-out cross-validation (LOOCV), repeated 10-fold cross-validation (10FoldCV), repeated double cross-validation (DoubleCV) and Monte Carlo permutations were applied to assess performance. Significant separation was found between prostate cancer and control samples, bladder cancer and controls and between bladder and prostate cancer samples. For prostate cancer diagnosis, the GC/SVM system classified samples with 95% sensitivity and 96% specificity after LOOCV. For bladder cancer diagnosis, the SVM reported 96% sensitivity and 100% specificity after LOOCV, while the DoubleCV reported 87% sensitivity and 99% specificity, with SVM showing 78% and 98% sensitivity between prostate and bladder cancer samples. Evaluation of the results of the Monte Carlo permutation of class labels obtained chance-like accuracy values around 50% suggesting the observed results for bladder cancer and prostate cancer detection are not due to over fitting. The results of the pilot study presented here indicate that the GC system is able to successfully identify patterns that allow classification of urine samples from patients with urological cancers. An accurate diagnosis based on urine samples would reduce the number of negative prostate biopsies performed, and the frequency of surveillance cystoscopy for bladder cancer patients. Larger cohort studies are planned to investigate the potential of this system. Future work may lead to non-invasive breath analyses for diagnosing urological conditions.

Quantification of selected volatile organic compounds in human urine by gas chromatography selective reagent ionization time of flight mass spectrometry (GC-SRI-TOF-MS) coupled with head-space solid-phase microextraction (HS-SPME)

Selective reagent ionization time of flight mass spectrometry with NO⁺as the reagent ion in conjunction with gas chromatography and head-space solid-phase microextraction was used to determine 16 volatiles in human urine.

The possibility of inventing new technologies in the detection of cancer by applying elements of the canine olfactory apparatus

In order to find better tools in the diagnosis of cancer in an earlier and more precise manner, researchers have explored the use of volatile organic compound (VOCs) as a way to detect this disease. Interestingly, the canine olfactory apparatus was observed to detect cancer in two anecdotal reports. After the description of these events, researchers began to study this phenomenon in a structured way in order to assess the ability of canines in detecting cancer-related VOCs. Due to the fact that some of these studies have shown that the canine olfactory apparatus is highly proficient in the detection of cancer-related VOCs, in this article we assess the possibility of constructing a bioelectronic-nose, based on canine olfactory receptors (ORs), for the purpose of diagnosing cancer in a more sensitive, specific, and cost effective manner than what is available nowadays. Furthermore, in order to prove the feasibility and the need of the proposed apparatus, we searched for the following type of articles: all of the studies that have examined, to our knowledge, the ability of dogs in detecting cancer; articles that assess the dog olfactory receptor (OR) gene repertoire, since a central part of the proposed bioelectronic nose is being able to recognize the odorant that emanates from the cancerous lesion, and for that purpose is necessary to express the canine ORs in heterologous cells; examples of articles that depict different devices that have been built for the purpose of detecting cancer-related VOCs, so as to assess if the construction of the proposed apparatus is needed; and articles that describe examples of already constructed bioelectronic noses, in order to demonstrate the existence of a technical precedent and thus the plausibility of the proposed device.

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

An early diagnosis and appropriate treatment are crucial in reducing mortality among people suffering from cancer. There is a lack of characteristic early clinical symptoms in most forms of cancer, which highlights the importance of investigating new methods for its early detection. One of the most promising methods is the analysis of volatile organic compounds (VOCs). VOCs are a diverse group of carbon-based chemicals that are present in exhaled breath and biofluids and may be collected from the headspace of these matrices. Different patterns of VOCs have been correlated with various diseases, cancer among them. Studies have also shown that cancer cells in vitro produce or consume specific VOCs that can serve as potential biomarkers that differentiate them from noncancerous cells. This review identifies the current challenges in the investigation of VOCs as potential cancer biomarkers, by the critical evaluation of available matrices for the in vivo and in vitro approaches in this field and by comparison of the main extraction and detection techniques that have been applied to date in this area of study. It also summarises complementary in vivo, ex vivo, and in vitro studies conducted to date in order to try to identify volatile biomarkers of cancer.

Detection of colorectal cancer (CRC) by urinary volatile organic compound analysis

Colorectal cancer (CRC) is a leading cause of cancer related death in Europe and the USA. There is no universally accepted effective non-invasive screening test for CRC. Guaiac based faecal occult blood (gFOB) testing has largely been superseded by Faecal Immunochemical testing (FIT), but sensitivity still remains poor. The uptake of population based FOBt testing in the UK is also low at around 50%. The detection of volatile organic compounds (VOCs) signature(s) for many cancer subtypes is receiving increasing interest using a variety of gas phase analytical instruments. One such example is FAIMS (Field Asymmetric Ion Mobility Spectrometer). FAIMS is able to identify Inflammatory Bowel disease (IBD) patients by analysing shifts in VOCs patterns in both urine and faeces. This study extends this concept to determine whether CRC patients can be identified through non-invasive analysis of urine, using FAIMS. 133 patients were recruited; 83 CRC patients and 50 healthy controls. Urine was collected at the time of CRC diagnosis and headspace analysis undertaken using a FAIMS instrument (Owlstone, Lonestar, UK). Data was processed using Fisher Discriminant Analysis (FDA) after feature extraction from the raw data. FAIMS analyses demonstrated that the VOC profiles of CRC patients were tightly clustered and could be distinguished from healthy controls. Sensitivity and specificity for CRC detection with FAIMS were 88% and 60% respectively. This study suggests that VOC signatures emanating from urine can be detected in patients with CRC using ion mobility spectroscopy technology (FAIMS) with potential as a novel screening tool.

The human volatilome: volatile organic compounds (VOCs) in exhaled breath, skin emanations, urine, feces and saliva

Breath analysis is a young field of research with its roots in antiquity. Antoine Lavoisier discovered carbon dioxide in exhaled breath during the period 1777-1783, Wilhelm (Vilém) Petters discovered acetone in breath in 1857 and Johannes Müller reported the first quantitative measurements of acetone in 1898. A recent review reported 1765 volatile compounds appearing in exhaled breath, skin emanations, urine, saliva, human breast milk, blood and feces. For a large number of compounds, real-time analysis of exhaled breath or skin emanations has been performed, e.g., during exertion of effort on a stationary bicycle or during sleep. Volatile compounds in exhaled breath, which record historical exposure, are called the 'exposome'. Changes in biogenic volatile organic compound concentrations can be used to mirror metabolic or (patho)physiological processes in the whole body or blood concentrations of drugs (e.g. propofol) in clinical settings-even during artificial ventilation or during surgery. Also compounds released by bacterial strains like Pseudomonas aeruginosa or Streptococcus pneumonia could be very interesting. Methyl methacrylate (CAS 80-62-6), for example, was observed in the headspace of Streptococcus pneumonia in concentrations up to 1420 ppb. Fecal volatiles have been implicated in differentiating certain infectious bowel diseases such as Clostridium difficile, Campylobacter, Salmonella and Cholera. They have also been used to differentiate other non-infectious conditions such as irritable bowel syndrome and inflammatory bowel disease. In addition, alterations in urine volatiles have been used to detect urinary tract infections, bladder, prostate and other cancers. Peroxidation of lipids and other biomolecules by reactive oxygen species produce volatile compounds like ethane and 1-pentane. Noninvasive detection and therapeutic monitoring of oxidative stress would be highly desirable in autoimmunological, neurological, inflammatory diseases and cancer, but also during surgery and in intensive care units. The investigation of cell cultures opens up new possibilities for elucidation of the biochemical background of volatile compounds. In future studies, combined investigations of a particular compound with regard to human matrices such as breath, urine, saliva and cell culture investigations will lead to novel scientific progress in the field.

The use of a gas chromatograph coupled to a metal oxide sensor for rapid assessment of stool samples from irritable bowel syndrome and inflammatory bowel disease patients

There is much clinical interest in the development of a low-cost and reliable test for diagnosing inflammatory bowel disease (IBD) and irritable bowel syndrome (IBS), two very distinct diseases that can present with similar symptoms. The assessment of stool samples for the diagnosis of gastro-intestinal diseases is in principle an ideal non-invasive testing method. This paper presents an approach to stool analysis using headspace gas chromatography and a single metal oxide sensor coupled to artificial neural network software. Currently, the system is able to distinguish samples from patients with IBS from patients with IBD with a sensitivity and specificity of 76% and 88% respectively, with an overall mean predictive accuracy of 76%.

Towards point of care testing for C. difficile infection by volatile profiling, using the combination of a short multi-capillary gas chromatography column with metal oxide sensor detection

Rapid volatile profiling of stool sample headspace was achieved using a combination of short multi-capillary chromatography column (SMCC), highly sensitive heated metal oxide semiconductor (MOS) sensor and artificial neural network (ANN) software. For direct analysis of biological samples this prototype offers alternatives to conventional GC detectors and electronic nose technology. The performance was compared to an identical instrument incorporating a long single capillary column (LSCC). The ability of the prototypes to separate complex mixtures was assessed using gas standards and homogenised in house 'standard' stool samples, with both capable of detecting more than 24 peaks per sample. The elution time was considerably faster with the SMCC resulting in a run time of 10 minutes compared to 30 minutes for the LSCC. The diagnostic potential of the prototypes was assessed using 50 C. difficile positive and 50 negative samples. The prototypes demonstrated similar capability of discriminating between positive and negative samples with sensitivity and specificity of 85% and 80% respectively. C. difficile is an important cause of hospital acquired diarrhoea, with significant morbidity and mortality around the world. A device capable of rapidly diagnosing the disease at the point of care would reduce cases, deaths and financial burden.

Review article: next generation diagnostic modalities in gastroenterology--gas phase volatile compound biomarker detection

BACKGROUND

The detection of airborne gas phase biomarkers that emanate from biological samples like urine, breath and faeces may herald a new age of non-invasive diagnostics. These biomarkers may reflect status in health and disease and can be detected by humans and other animals, to some extent, but far more consistently with instruments. The continued advancement in micro and nanotechnology has produced a range of compact and sophisticated gas analysis sensors and sensor systems, focussed primarily towards environmental and security applications. These instruments are now increasingly adapted for use in clinical testing and with the discovery of new gas volatile compound biomarkers, lead naturally to a new era of non-invasive diagnostics.

AIM

To review current sensor instruments like the electronic nose (e-nose) and ion mobility spectroscopy (IMS), existing technology like gas chromatography-mass spectroscopy (GC-MS) and their application in the detection of gas phase volatile compound biomarkers in medicine - focussing on gastroenterology.

METHODS

A systematic search on Medline and Pubmed databases was performed to identify articles relevant to gas and volatile organic compounds.

RESULTS

E-nose and IMS instruments achieve sensitivities and specificities ranging from 75 to 92% in differentiating between inflammatory bowel disease, bile acid diarrhoea and colon cancer from controls. For pulmonary disease, the sensitivities and specificities exceed 90% in differentiating between pulmonary malignancy, pneumonia and obstructive airways disease. These sensitivity levels also hold true for diabetes (92%) and bladder cancer (90%) when GC-MS is combined with an e-nose.

CONCLUSIONS

The accurate reproducible sensing of volatile organic compounds (VOCs) using portable near-patient devices is a goal within reach for today's clinicians.