Browse
Submit Data
Databases
API
Help

Dataset Information

25 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Urinary Volatile Organic Compounds for the Detection of Prostate Cancer.

ABSTRACT: The aim of this work was to investigate volatile organic compounds (VOCs) emanating from urine samples to determine whether they can be used to classify samples into those from prostate cancer and non-cancer groups. Participants were men referred for a trans-rectal ultrasound-guided prostate biopsy because of an elevated prostate specific antigen (PSA) level or abnormal findings on digital rectal examination. Urine samples were collected from patients with prostate cancer (n = 59) and cancer-free controls (n = 43), on the day of their biopsy, prior to their procedure. VOCs from the headspace of basified urine samples were extracted using solid-phase micro-extraction and analysed by gas chromatography/mass spectrometry. Classifiers were developed using Random Forest (RF) and Linear Discriminant Analysis (LDA) classification techniques. PSA alone had an accuracy of 62-64% in these samples. A model based on 4 VOCs, 2,6-dimethyl-7-octen-2-ol, pentanal, 3-octanone, and 2-octanone, was marginally more accurate 63-65%. When combined, PSA level and these four VOCs had mean accuracies of 74% and 65%, using RF and LDA, respectively. With repeated double cross-validation, the mean accuracies fell to 71% and 65%, using RF and LDA, respectively. Results from VOC profiling of urine headspace are encouraging and suggest that there are other metabolomic avenues worth exploring which could help improve the stratification of men at risk of prostate cancer. This study also adds to our knowledge on the profile of compounds found in basified urine, from controls and cancer patients, which is useful information for future studies comparing the urine from patients with other disease states.

SUBMITTER: Khalid T

PROVIDER: S-EPMC4657998 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Volatile organic compounds for early detection of prostate cancer from urine.

Project description:Prostate cancer (PCa) is one of the most common cancers in men worldwide. Early diagnosis of PCa is extremely challenging due to the lack of effective diagnostic methods. The study presented here aims to evaluate whether urine volatile organic compounds (VOCs) can be used as an emerging diagnostic biomarker for PCa. Gas chromatography-ion mobility spectrometry (GC-IMS) was used to detect VOCs in urine samples from 66 patients with PCa and to comparatively analyze samples from 87 patients with non-cancerous controls (NCs). A total of 86 substance peak heights were detected in urine samples from all patients. Analysis using four machine learning algorithms suggested that the diagnosis of PCa could be effectively facilitated. Ultimately, diagnostic models were constructed based on the four VOCs selected. The AUC for the RF and SVM model were 0.955 and 0.981, respectively. Both the NN and DT diagnostic models also achieved an AUC of 0.8 or more, but their sensitivity or specificity was poor compared to the RF and SVM models.

| S-EPMC10250727 | biostudies-literature

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

Project description: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.

| S-EPMC7065633 | biostudies-literature

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

Project description:Hepatocellular carcinoma (HCC) biomarkers are lacking in clinical practice. We therefore explored the pattern and composition of urinary volatile organic compounds (VOCs) in HCC patients. This was done in order to assess the feasibility of a potential non-invasive test for HCC, and to enhance our understanding of the disease. This pilot study recruited 58 participants, of whom 20 were HCC cases and 38 were non-HCC cases. The non-HCC cases included healthy individuals and patients with various stages of non-alcoholic fatty liver disease (NAFLD), including those with and without fibrosis. Urine was analysed using gas chromatography-ion mobility spectrometry (GC-IMS) and gas chromatography-time-of-flight mass spectrometry (GC-TOF-MS). GC-IMS was able to separate HCC from fibrotic cases with an area under the curve (AUC) of 0.97 (0.91-1.00), and from non-fibrotic cases with an AUC of 0.62 (0.48-0.76). For GC-TOF-MS, a subset of samples was analysed in which seven chemicals were identified and tentatively linked with HCC. These include 4-methyl-2,4-bis(p-hydroxyphenyl)pent-1-ene (2TMS derivative), 2-butanone, 2-hexanone, benzene, 1-ethyl-2-methyl-, 3-butene-1,2-diol, 1-(2-furanyl)-, bicyclo(4.1.0)heptane, 3,7,7-trimethyl-, [1S-(1a,3β,6a)]-, and sulpiride. Urinary VOC analysis using both GC-IMS and GC-TOF-MS proved to be a feasible method of identifying HCC cases, and was also able to enhance our understanding of HCC pathogenesis.

| S-EPMC8122735 | biostudies-literature

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

Project description: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.

| S-EPMC10616168 | biostudies-literature

Utilizing volatile organic compounds for early detection of Fusarium circinatum.

Project description:Fusarium circinatum, a fungal pathogen deadly to many Pinus species, can cause significant economic and ecological losses, especially if it were to become more widely established in Europe. Early detection tools with high-throughput capacity can increase our readiness to implement mitigation actions against new incursions. This study sought to develop a disease detection method based on volatile organic compound (VOC) emissions to detect F. circinatum on different Pinus species. The complete pipeline applied here, entailing gas chromatography-mass spectrometry of VOCs, automated data analysis and machine learning, distinguished diseased from healthy seedlings of Pinus sylvestris and Pinus radiata. In P. radiata, this distinction was possible even before the seedlings became visibly symptomatic, suggesting the possibility for this method to identify latently infected, yet healthy looking plants. Pinus pinea, which is known to be relatively resistant to F. circinatum, remained asymptomatic and showed no changes in VOCs over 28 days. In a separate analysis of in vitro VOCs collected from different species of Fusarium, we showed that even closely related Fusarium spp. can be readily distinguished based on their VOC profiles. The results further substantiate the potential for volatilomics to be used for early disease detection and diagnostic recognition.

| S-EPMC9755288 | biostudies-literature

Ambient exposures to selected volatile organic compounds and the risk of prostate cancer in Montreal.

Project description:Little is known about environmental factors that may increase the risk of prostate cancer. We estimated associations between incident prostate cancer and environmental concentrations of five ambient volatile organic compounds (VOCs): benzene; n-decane; ethylbenzene; hexane; and 1,2,4-trimethylbenzene.MethodsThis study is based on a population-based case-control study of incident prostate cancer (PROtEuS) in men ≤ 75 years of age living in Montreal, Canada, in 2005 to 2012. We included 1172 cases and 1177 population controls. We had personal information, lifetime residential addresses, occupational exposures, and a variety of area-wide covariables. We inferred concentrations of the five VOCs using Bayesian geostatistical models using data from a dense environmental survey conducted in Montreal in 2005 to 2006. We used different sets of adjustments to estimate odds ratios (OR) and confidence intervals.ResultsWe found nonlinear associations such that the ORs increased monotonically and then either flattened or fell off with increased exposures. The model that contained other environmental variables and contextual variables led to lower ORs and results were similar when we restricted analyses to controls recently screened or tested for prostate cancer or cases with low- or high-grade tumors. A change from the 5th to 25th percentile in mean environmental benzene levels led to an adjusted OR of 2.00 (95% confidence interval = 1.47, 2.71).ConclusionWe found positive associations between prostate cancer and concentrations of benzene and ethylbenzene, independently of previous testing for prostate cancer or tumor grade, suggesting that exposure to certain ambient VOCs may increase incidence.

| S-EPMC9746733 | biostudies-literature

Ants detect cancer cells through volatile organic compounds.

Project description:Cancer is among the world's leading causes of death. A critical challenge for public health is to develop a noninvasive, inexpensive, and efficient tool for early cancer detection. Cancer cells are characterized by an altered metabolism, producing unique patterns of volatile organic compounds (VOCs) that can be used as cancer biomarkers. Dogs can detect VOCs via olfactory associative learning, but training dogs is costly and time-consuming. Insects, such as ants, have a refined sense of smell and can be rapidly trained. We show that individual ants need only a few training trials to learn, memorize, and reliably detect the odor of human cancer cells. These performances rely on specific VOC patterns, as shown by gas chromatography/mass spectrometry. Our findings suggest that using ants as living tools to detect biomarkers of human cancer is feasible, fast, and less laborious than using other animals.

| S-EPMC8914326 | biostudies-literature

An Impedimetric Biosensor for Detection of Volatile Organic Compounds in Food.

Project description:The demand for a wide choice of food that is safe and palatable increases every day. Consumers do not accept off-flavors that have atypical odors resulting from internal deterioration or contamination by substances alien to the food. Odor response depends on the volatile organic compounds (VOCs), and their detection can provide information about food quality. Gas chromatography/mass spectrometry is the most powerful method available for the detection of VOC. However, it is laborious, costly, and requires the presence of a trained operator. To develop a faster analytic tool, we designed a non-Faradaic impedimetric biosensor for monitoring the presence of VOCs involved in food spoilage. The biosensor is based on the use of the pig odorant-binding protein (pOBP) as the molecular recognition element. We evaluated the affinity of pOBP for three different volatile organic compounds (1-octen-3-ol, trans-2-hexen-1-ol, and hexanal) related to food spoilage. We developed an electrochemical biosensor conducting impedimetric measurements in liquid and air samples. The impedance changes allowed us to detect each VOC sample at a minimum concentration of 0.1 μM.

| S-EPMC10046769 | biostudies-literature

Detection of volatile organic compounds by weight-detectable sensors coated with metal-organic frameworks.

Project description:Detection of volatile organic compounds (VOCs) using weight-detectable quartz microbalance and silicon-based microcantilever sensors coated with crystalline metal-organic framework (MOF) thin films is described in this paper. The thin films of two MOFs were grown from COOH-terminated self-assembled monolayers onto the gold electrodes of sensor platforms. The MOF layers worked as the effective concentrators of VOC gases, and the adsorption/desorption processes of the VOCs could be monitored by the frequency changes of weight-detectable sensors. Moreover, the MOF layers provided VOC sensing selectivity to the weight-detectable sensors through the size-selective adsorption of the VOCs within the regulated nanospace of the MOFs.

| S-EPMC4150105 | biostudies-literature

Sniffing Out Urinary Tract Infection-Diagnosis Based on Volatile Organic Compounds and Smell Profile.

Project description:Current available methods for the clinical diagnosis of urinary tract infection (UTI) rely on a urine dipstick test or culturing of pathogens. The dipstick test is rapid (available in 1-2 min), but has a low positive predictive value, while culturing is time-consuming and delays diagnosis (24-72 h between sample collection and pathogen identification). Due to this delay, broad-spectrum antibiotics are often prescribed immediately. The over-prescription of antibiotics should be limited, in order to prevent the development of antimicrobial resistance. As a result, there is a growing need for alternative diagnostic tools. This paper reviews applications of chemical-analysis instruments, such as gas chromatography-mass spectrometry (GC-MS), selected ion flow tube mass spectrometry (SIFT-MS), ion mobility spectrometry (IMS), field asymmetric ion mobility spectrometry (FAIMS) and electronic noses (eNoses) used for the diagnosis of UTI. These methods analyse volatile organic compounds (VOCs) that emanate from the headspace of collected urine samples to identify the bacterial pathogen and even determine the causative agent's resistance to different antibiotics. There is great potential for these technologies to gain wide-spread and routine use in clinical settings, since the analysis can be automated, and test results can be available within minutes after sample collection. This could significantly reduce the necessity to prescribe broad-spectrum antibiotics and allow the faster and more effective use of narrow-spectrum antibiotics.

| S-EPMC7460005 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data