GC-MS-based untargeted metabolic profiling of malignant mesothelioma plasma

Author:

Wang Ding123,Zhu Jing13,Li Na4,Lu Hongyang13,Gao Yun13,Zhuang Lei23,Chen Zhongjian13,Mao Weimin13

Affiliation:

1. Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, China

2. The Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, China

3. Key Laboratory Diagnosis and Treatment Technology on Thoracic Oncology, Hangzhou, China

4. Shaoxing No. 2 Hospital Medical Community General Hospital, Shaoxing, China

Abstract

Background 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. Methods 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. Results Using samples from MM (n = 19) and healthy control (n = 22) participants, 20 metabolites were annotated. Seven metabolic pathways were disrupted, involving alanine, aspartate, and glutamate metabolism; glyoxylate and dicarboxylate metabolism; arginine and proline metabolism; butanoate and histidine metabolism; beta-alanine metabolism; and pentose phosphate metabolic pathway. The AUC was used to identify potential plasma biomarkers. Using a threshold of AUC = 0.9, five metabolites were identified, including xanthurenic acid, (s)-3,4-hydroxybutyric acid, D-arabinose, gluconic acid, and beta-d-glucopyranuronic acid. Conclusions To the best of our knowledge, this is the first report of a plasma metabolomics analysis using GC-MS analyses of Asian MM patients. Our identification of these metabolic abnormalities is critical for identifying plasma biomarkers in patients with MM. However, additional research using a larger population is needed to validate our findings.

Funder

National Natural Science Foundation of China

Key R&D Program Projects in Zhejiang Province

Medical and the Health Science Project of Zhejiang Province

Zhejiang Provincial Natural Science Foundation of China

Publisher

PeerJ

Subject

General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

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