Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Serum-volatile organic compounds in the diagnostics of esophageal cancer.

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

SUBMITTER: Liu Q

PROVIDER: S-EPMC11291479 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Serum-volatile organic compounds in the diagnostics of esophageal cancer.

Liu Qi Q Li Shuhai S Mao Mai M Gui Xinru X Zhang Yanli Y Zhao Yuxiao Y Yu Longchen L Zhang Xin X Zhang Yi Y

Scientific reports 20240731 1

The early diagnosis of esophageal cancer (EC) is extremely challenging due to a lack of effective diagnostic methods. The study presented herein aims to assess whether serum volatile organic compounds (VOCs) could be utilised as emerging diagnostic biomarkers for EC. Gas chromatography-ion mobility spectrometry (GC-IMS) was used to detect VOCs in the serum samples of 55 patients with EC, with samples from 84 healthy controls (HCs) patients analysed as a comparison. All machine learning analyses ...[more]

PMID: 39085271

Similar Datasets

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

Exposure to polycyclic aromatic hydrocarbons, volatile organic compounds, and tobacco-specific nitrosamines and incidence of esophageal cancer.

Project description:BackgroundStudying carcinogens in tobacco and nontobacco sources may be key to understanding the pathogenesis and geographic distribution of esophageal cancer.MethodsThe Golestan Cohort Study has been conducted since 2004 in a region with high rates of esophageal squamous cell carcinoma. For this nested study, the cases comprised of all incident cases by January 1, 2018; controls were matched to the case by age, sex, residence, time in cohort, and tobacco use. We measured urinary concentrations of 33 exposure biomarkers of nicotine, polycyclic aromatic hydrocarbons, volatile organic compounds, and tobacco-specific nitrosamines. We used conditional logistic regression to calculate odds ratios (ORs) and 95% confidence intervals for associations between the 90th vs the 10th percentiles of the biomarker concentrations and incident esophageal squamous cell carcinoma.ResultsAmong individuals who did not currently use tobacco (148 cases and 163 controls), 2 acrolein metabolites, 2 acrylonitrile metabolites, 1 propylene oxide metabolite, and one 1,3-butadiene metabolite were significantly associated with incident esophageal squamous cell carcinoma (adjusted odds ratios between 1.8 and 4.3). Among tobacco users (57 cases and 63 controls), metabolites of 2 other volatile organic compounds (styrene and xylene) were associated with esophageal squamous cell carcinoma (OR = 6.2 and 9.0, respectively). In tobacco users, 2 tobacco-specific nitrosamines (NNN and N'-Nitrosoanatabine) were also associated with esophageal squamous cell carcinoma. Suggestive associations were seen with some polycyclic aromatic hydrocarbons (especially 2-hydroxynaphthalene) in nonusers of tobacco products and other tobacco-specific nitrosamines in tobacco users.ConclusionThese novel associations based on individual-level data and samples collected many years before cancer diagnosis, from a population without occupational exposure, have important public health implications.

| S-EPMC10919344 | 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

Arabidopsis thaliana seedlings: Control vs Erwinia amylovora nicrobial Volatile Organic Compounds

Project description:Arabidopsis seedling were exposed in co-culture to E. amylovora mVOC and data show that mVOCs promote plant growth and early responses

2023-04-04 | GSE223760 | GEO

Volatile Organic Compounds (VOCs) Profile in Colorectal Cancer Patients and Healthy Controls.

Project description:Volatile organic compounds (VOCs) are low molecular weight (<1 kDa) compounds which represent the final products of cell metabolism. Their composition can be affected by several factors including diet, hormones, environment and the presence of diseases, in particular, cancer. Colorectal cancer (CRC) is one of the commonest tumours and is an important cause of cancer-related mortality. The expression of VOCs in breath that are linked to a patient’s disease state could offers a powerful, non-invasive approach to identifying CRC patients.

| 2326074 | ecrin-mdr-crc

Exhaled volatile organic compounds as lung cancer biomarkers during one-lung ventilation.

Project description:In this study, single-lung ventilation was used to detect differences in the volatile organic compound (VOCs) profiles between lung tissues in healthy and affected lungs. In addition, changes that occurred after lung cancer resection in both the VOCs profiles of exhaled breath from ipsilateral and contralateral lungs and the VOCs profiles of exhaled breath and blood sample headspaces were also determined. Eighteen patients with non-small cell carcinoma were enrolled. Alveolar breath samples were taken separately from healthy and diseased lungs before and after the tumor resection. Solid phase microextraction-gas chromatography/mass spectrometry was used to assess the exhaled VOCs of the study participants. The VOCs exhibited significant differences between the contralateral and ipsilateral lungs before surgery, the contralateral and ipsilateral lungs after surgery, the ipsilateral lungs before and after surgery, and the blood samples from before and after surgery; 12, 19, 12 and 5 characteristic metabolites played decisive roles in sample classification, respectively. 2,2-Dimethyldecane, tetradecane, 2,2,4,6,6-pentamethylheptane, 2,3,4-trimethyldecane, nonane, 3,4,5,6-tetramethyloctane, and hexadecane may be generated from lipid peroxidation during surgery. Caprolactam and propanoic acid may be more promising exhaled breath biomarkers for lung cancer.

| S-EPMC4258651 | biostudies-other

Urinary Volatile Organic Compounds for the Detection of Prostate Cancer.

Project description: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.

| S-EPMC4657998 | biostudies-literature

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

Exhaled volatile organic compounds for cholangiocarcinoma diagnosis.

Project description:ObjectivesThe difficulties in the early detection consequent to the lack of sensitive biomarkers render patients with cholangiocarcinoma (CCA) to have poor outcomes. Recently, sensitive and specific volatile organic compounds (VOCs) were identified in several cancers. However, the VOC profiles in CCA are not well-studied. Thus, we investigated the VOC profiles in exhaled breath of CCA patients and controls.MethodsWe prospectively collected exhaled breath samples from 30 consecutive patients newly diagnosed with CCA and 30 controls who did not have CCA (seven had benign biliary strictures and 23 had other medical conditions). Exhaled VOCs were identified using gas chromatography mass spectrometry Triple Quadrupoles system. Analysis of the significant differences in VOCs between cases and controls was conducted using supervised multivariate regression analysis. Further validation was performed for these VOCs in another cohort of 18 CCA patients and 22 controls.ResultsLevels of six compounds were significantly different between CCA patients and controls, namely, acetone, isopropyl alcohol, dimethyl sulfide, 1,4-pentadiene, allyl methyl sulfide, and N,N-dimethylacetamide. Acetone and dimethyl sulfide were independently associated with CCA as demonstrated in the multivariate analysis. Using the cut-off value of 8.59 × 107 arbitrary unit (AU), acetone had a sensitivity and specificity of 82.1% and 75.8%, respectively, with an area under the receiving operator curve (AUROC) of 0.85 for the CCA diagnosis. Acetone level was also significantly different between cases and controls in the validation cohort. Using the same cut-off value, the sensitivity, specificity, and AUROC was 59.1%, 66.7%, and 0.85, respectively.ConclusionBreath analysis may potentially be useful for CCA diagnosis. A cohort of patients with early-stage CCA in further studies is needed to confirm the ability of exhaled VOCs for the early detection of CCA.

| S-EPMC11791817 | biostudies-literature

Exploiting volatile organic compounds as eco-friendly alternatives against the phytopathogenic fungus Thielaviopsis ethacetica

Project description:In this study, we showed that three bacteria were able to inhibit the mycelial growth of the phytopathogenic fungus Thielaviopsis ethacetica, by the emission of microbial volatile organic compounds (mVOCs). Aiming to understand the molecular mechanisms of these interactions, we evaluated the transcriptomic response of T. ethacetica to the mVOCs produced by one of these bacterial isolates.

2021-07-22 | GSE158776 | GEO

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