Rongrong Tang , Yunshan Zhu , Lingfeng Chen , Jinfei Tong , Xudong Ma , Fangying Sun , Limei Zheng , Hailan Yu , Jianhua Yang
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引用次数: 0
Abstract
Background
Ovarian cancer is insidious and usually detected in advanced stages of the disease. As the ovaries are pelvic organs, changes in their pelvic fluid metabolites may be associated with ovarian cancer.
Methods
Metabolomic changes in the pelvic fluid were detected using liquid chromatography-tandem mass spectrometry (LC-MS/MS) in patients with ovarian cancer, ovarian cysts and uterine fibroids. Area under the curve (AUC) analysis was used to assess the diagnostic performance of lipid metabolites and blood tumor indices. The Pearson correlation algorithm was used to analyze the correlation between clinical characteristics and lipid metabolites in ovarian cancer patients.
Results
There were 24 lipid metabolites significantly changed in the pelvic fluid of ovarian cancer patients (p < 0.05). Palmitoylcarnitine, lipoamide, lipid metabolites, and blood tumor indices (CA15–3 and CA125) showed AUC > 0.8, with palmitoylcarnitine reaching a high of 0.942. In addition, we found that some lipid metabolites were significantly associated with the clinical stage, abdominal water volume, lymphatic metastasis, and recurrence (p < 0.05, r > 0.5).
Conclusion
Levels of specific lipid metabolites are potential biomarkers of ovarian cancer and may play a key role in the early diagnosis and prognostic assessment of ovarian cancer.
Significance
Our results showed that pelvic metabolites, especially some lipid metabolites, play an important role in the diagnosis of ovarian cancer. Meanwhile, partial lipid metabolites were closely associated with the clinical presentation and prognosis of patients with ovarian cancer. We believe that our study makes a significant contribution to the literature because it provides a potential approach that is more effective for ovarian cancer detection.
期刊介绍:
Journal of Proteomics is aimed at protein scientists and analytical chemists in the field of proteomics, biomarker discovery, protein analytics, plant proteomics, microbial and animal proteomics, human studies, tissue imaging by mass spectrometry, non-conventional and non-model organism proteomics, and protein bioinformatics. The journal welcomes papers in new and upcoming areas such as metabolomics, genomics, systems biology, toxicogenomics, pharmacoproteomics.
Journal of Proteomics unifies both fundamental scientists and clinicians, and includes translational research. Suggestions for reviews, webinars and thematic issues are welcome.