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Pancreatic ductal adenocarcinoma can be detected by analysis of volatile organic compounds (VOCs) in alveolar air.

ABSTRACT: BACKGROUND:In the last decade many studies showed that the exhaled breath of subjects suffering from several pathological conditions has a peculiar volatile organic compound (VOC) profile. The objective of the present work was to analyse the VOCs in alveolar air to build a diagnostic tool able to identify the presence of pancreatic ductal adenocarcinoma in patients with histologically confirmed disease. METHODS:The concentration of 92 compounds was measured in the end-tidal breath of 65 cases and 102 controls. VOCs were measured with an ion-molecule reaction mass spectrometry. To distinguish between subjects with pancreatic adenocarcinomas and controls, an iterated Least Absolute Shrinkage and Selection Operator multivariate Logistic Regression model was elaborated. RESULTS:The final predictive model, based on 10 VOCs, significantly and independently associated with the outcome had a sensitivity and specificity of 100 and 84% respectively, and an area under the ROC curve of 0.99. For further validation, the model was run on 50 other subjects: 24 cases and 26 controls; 23 patients with histological diagnosis of pancreatic adenocarcinomas and 25 controls were correctly identified by the model. CONCLUSIONS:Pancreatic cancer is able to alter the concentration of some molecules in the blood and hence of VOCs in the alveolar air in equilibrium. The detection and statistical rendering of alveolar VOC composition can be useful for the clinical diagnostic approach of pancreatic neoplasms with excellent sensitivity and specificity.

SUBMITTER: Princivalle A

PROVIDER: S-EPMC5935919 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Plants emit volatile organic compounds (VOCs) that induce metabolomic, transcriptomic, and behavioral reactions in receiver organisms, including insect pollinators and herbivores. VOCs' composition and concentration may influence plant-insect or plant-plant interactions and affect soil microbes that may interfere in plant-plant communication. Many Trichoderma fungi act as biocontrol agents of phytopathogens and plant growth promoters. Moreover, they can stimulate plant defense mechanisms against insect pests. This study evaluated VOCs' emission by olive trees (Olea europaea L.) when selected Trichoderma fungi or metabolites were used as soil treatments. Trichoderma harzianum strains M10, T22, and TH1, T. asperellum strain KV906, T. virens strain GV41, and their secondary metabolites harzianic acid (HA), and 6-pentyl-α-pyrone (6PP) were applied to olive trees. Charcoal cartridges were employed to adsorb olive VOCs, and gas chromatography mass spectrometry (GC-MS) analysis allowed their identification and quantification. A total of 45 volatile compounds were detected, and among these, twenty-five represented environmental pollutants and nineteen compounds were related to olive plant emission. Trichoderma strains and metabolites differentially enhanced VOCs production, affecting three biosynthetic pathways: methylerythritol 1-phosphate (MEP), lipid-signaling, and shikimate pathways. Multivariate analysis models showed a characteristic fingerprint of each plant-fungus/metabolite relationship, reflecting a different emission of VOCs by the treated plants. Specifically, strain M10 and the metabolites 6PP and HA enhanced the monoterpene syntheses by controlling the MEP pathway. Strains GV41, KV906, and the metabolite HA stimulated the hydrocarbon aldehyde formation (nonanal) by regulating the lipid-signaling pathway. Finally, Trichoderma strains GV41, M10, T22, TH1, and the metabolites HA and 6PP improve aromatic syntheses at different steps of the shikimate pathway.

Project description:BackgroundPoison frogs are known for the outstanding diversity of alkaloid-based chemical defences with promising therapeutic applications. However, current knowledge about chemical defences in Dendrobatoidea superfamily has two sources of bias. First, cryptic, brown-colored species have been neglected in comparison to those conspicuously colored, and second, there has been little interest in characterizing metabolites other than alkaloids mediating defensive functions. In an effort to contribute to fill the gap of knowledge about cryptic species and broadening the spectrum of compounds analyzed we have applied head-space solid phase microextraction coupled to gas chromatography and mass spectrometry (HS-SPME/GC-MS) for extracting amphibian alkaloids and volatile organic compounds (VOCs) from Silverstoneia punctiventris.ResultsUsing the skin from 8 specimens in 4 biological replicates we have found 33 different compounds. Twenty of them were classified as VOCs into 15 chemical classes including alkanes, alcohols, carbonyl compounds, methylpyridines, benzothiazoles, N-alkylpyrrolidines, pyrazines, and sesquiterpenoids, some of which were previously reported as repellents, defence compounds or defence pheromones in other organisms, and as sex pheromones in a treefrog. Interestingly, six of the remaining compounds were identified as alkaloids previously reported in other toxic/unpalatable dendrobatid frogs.ConclusionsThis is the first report of alkaloids and VOCs found in the Silverstoneia genus, which has been assumed for decades as non-chemically defended. This study establishes HS-SPME/GC-MS as a new application for a simultaneous approach to amphibian alkaloids and VOCs in poison frogs while opens up new research questions to assess the co-occurrence of both type of compounds and to investigate the evolutionary significance of a defence gradient that includes olfactory avoidance, unpalatability, and toxicity in dendrobatids. In addition, our results show that amphibian alkaloids could have a dual function (olfactory at distance, taste by contact) never explored before neither in Silverstonaeia nor in any other dendrobatid species.

Project description:Malignant pleural mesothelioma (MPM) is a rare neoplasm, mainly caused by asbestos exposure, with a high mortality rate. The management of patients with MPM is controversial due to a long latency period between exposure and diagnosis and because of non-specific symptoms generally appearing at advanced stage of the disease. Breath analysis, aimed at the identification of diagnostic Volatile Organic Compounds (VOCs) pattern in exhaled breath, is believed to improve early detection of MPM. Therefore, in this study, breath samples from 14 MPM patients and 20 healthy controls (HC) were collected and analyzed by Thermal Desorption-Gas Chromatography-Mass Spectrometry (TD-GC/MS). Nonparametric test allowed to identify the most weighting variables to discriminate between MPM and HC breath samples and multivariate statistics were applied. Considering that MPM is an aggressive neoplasm leading to a late diagnosis and thus the recruitment of patients is very difficult, a promising data mining approach was developed and validated in order to discriminate between MPM patients and healthy controls, even if no large population data are available. Three different machine learning algorithms were applied to perform the classification task with a leave-one-out cross-validation approach, leading to remarkable results (Area Under Curve AUC = 93%). Ten VOCs, such as ketones, alkanes and methylate derivates, as well as hydrocarbons, were able to discriminate between MPM patients and healthy controls and for each compound which resulted diagnostic for MPM, the metabolic pathway was studied in order to identify the link between VOC and the neoplasm. Moreover, five breath samples from asymptomatic asbestos-exposed persons (AEx) were exploratively analyzed, processed and tested by the validated statistical method as blinded samples in order to evaluate the performance for the early recognition of patients affected by MPM among asbestos-exposed persons. Good agreement was found between the information obtained by gold-standard diagnostic methods such as computed tomography CT and model output.

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Pancreatic ductal adenocarcinoma can be detected by analysis of volatile organic compounds (VOCs) in alveolar air.

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