{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["11"],"submitter":["Wang D"],"pubmed_abstract":["<h4>Background</h4>Malignant mesothelioma (MM) is a cancer caused mainly by asbestos exposure, and is aggressive and incurable. This study aimed to identify differential metabolites and metabolic pathways involved in the pathogenesis and diagnosis of malignant mesothelioma.<h4>Methods</h4>By using gas chromatography-mass spectrometry (GC-MS), this study examined the plasma metabolic profile of human malignant mesothelioma. We performed univariate and multivariate analyses and pathway analyses to identify differential metabolites, enriched metabolism pathways, and potential metabolic targets. The area under the receiver-operating curve (AUC) criterion was used to identify possible plasma biomarkers.<h4>Results</h4>Using samples from MM (<i>n</i> = 19) and healthy control (<i>n</i> = 22) par"],"journal":["PeerJ"],"pagination":["e15302"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC10200095"],"repository":["biostudies-literature"],"pubmed_title":["GC-MS-based untargeted metabolic profiling of malignant mesothelioma plasma."],"pmcid":["PMC10200095"],"pubmed_authors":["Zhu J","Lu H","Chen Z","Wang D","Gao Y","Mao W","Zhuang L","Li N"],"additional_accession":[]},"is_claimable":false,"name":"GC-MS-based untargeted metabolic profiling of malignant mesothelioma plasma.","description":"<h4>Background</h4>Malignant mesothelioma (MM) is a cancer caused mainly by asbestos exposure, and is aggressive and incurable. This study aimed to identify differential metabolites and metabolic pathways involved in the pathogenesis and diagnosis of malignant mesothelioma.<h4>Methods</h4>By using gas chromatography-mass spectrometry (GC-MS), this study examined the plasma metabolic profile of human malignant mesothelioma. We performed univariate and multivariate analyses and pathway analyses to identify differential metabolites, enriched metabolism pathways, and potential metabolic targets. The area under the receiver-operating curve (AUC) criterion was used to identify possible plasma biomarkers.<h4>Results</h4>Using samples from MM (<i>n</i> = 19) and healthy control (<i>n</i> = 22) par","dates":{"release":"2023-01-01T00:00:00Z","publication":"2023","modification":"2025-04-04T09:58:23.707Z","creation":"2025-04-04T09:58:23.707Z"},"accession":"S-EPMC10200095","cross_references":{"pubmed":["37220527"],"doi":["10.7717/peerj.15302"]}}