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ABSTRACT: Background
Ovarian cancer is the most lethal tumor of the female reproductive system. Establishing a methodology to screen and diagnose ovarian cancer in the early stage is important. Exosomes have been shown to be loaded with tumor-associated molecules. In this study, we compared the proteins loaded in exosomes from the peripheral circulation of epithelial ovarian carcinoma (EOC) patients and controls. Methods
Exosomes were purified via ultracentrifugation plus 0.22 µm filtration from the blood of EOC patients and patients with pelvic floor dysfunction (PFD). Tumor tissues and normal ovarian tissues were also obtained. Proteomic analyses of exosomes and tumor/normal ovarian tissues were performed with isobaric tags for relative and absolute quantitation (iTRAQ) and high-performance liquid chromatography/mass spectrometry (HPLC/MS) analyses. The LocDB (http://www.rostlab.org/services/locDB), PANTHER (http://www.pantherdb.org/) and Vesiclepedia databases were used for biological information analysis. Results
We identified 408 differentially expressed proteins in exosomes from EOC patients and noncancer controls. Furthermore, we identified 954 differentially expressed proteins from ovarian cancer tissues and normal ovarian tissues. Thirty-five proteins exhibited upregulation in both cancer patient exosomes and cancer tissues. Among these 35 proteins, eight proteins (chloride intracellular channel protein 4, serine/threonine-protein kinase 1, aminoacyl tRNA synthetase complex-interacting multifunctional protein 1, sorting nexin-3, protein FAM49B, fermitin family homolog 3, tubulin beta-3 chain and lactotransferrin) were confirmed in both exosome databases and other studies. Conclusions
We isolated exosomes from the peripheral blood of EOC patients and noncancer controls and identified 35 proteins that were upregulated in both EOC patient exosomes and ovarian cancer tissues. Comparisons with the exosome molecular databases and other studies identified eight proteins as potential tumor markers, which might offer new tools for the early diagnosis of ovarian cancer.
SUBMITTER: Peng P
PROVIDER: S-EPMC8798066 | biostudies-literature |
REPOSITORIES: biostudies-literature