Abstract
Abstract Ovarian cancer is the most lethal gynecologic cancer in the world. Most patients are diagnosed at advanced stages with the formation of ascites. Extracellular vesicles (EVs) have been elucidated to play a pivotal role in cancer development and progression, also emerging as promising resources for clinical biomarkers in liquid biopsy. In this study, we aim to identify cancer-specific protein biomarkers in ascites-derived EVs for ovarian cancer diagnosis. Malignant ascites from high grade ovarian cancer patients (HGSOC) and benign peritoneal fluids from female patients with benign gynecologic diseases were collected with informed consent. EVs were isolated from these biofluids using the Exoquick kit. Meanwhile, HGSOC cell lines and normal cell lines were cultured in conditioned media supplemented with EVs-depleted FBS. EVs were isolated from the culture media. Proteins were extracted from EVs and fragmented into peptides. Tandem mass tag (TMT) hyper multiplex quantitation assay was carried out to detect the EV proteomic profiling. EVs isolated from biofluids and cell culture media were identified as double-membrane nanoparticles sizing ranging from 30nm to 200nm. Proteomic analysis of biofluids-derived EVs showed that malignant ascites-derived EVs displayed different proteomic profiling compared to benign peritoneal fluids-derived EVs. The differently expressed proteins between malignant ascites-derived EVs and benign peritoneal fluids-derived EVs were defined as candidate EV protein biomarkers. In addition, proteins that were expressed in at least one cancer cell line-derived EVs but not expressed in normal cell line-derived EVs were also identified as ovarian cancer-specific proteins. A diagnostic model constructed based on the integrative analysis of candidate EV protein biomarkers and ovarian cancer-specific proteins yielded a good discrimination ability between benign and cancer patients.In conclusion, this study demonstrates the distinct proteomic profiling in ascites- and cancer cell-derived EVs in ovarian cancer, which sheds new light on implementing EV proteins as a potential diagnostic strategy in clinical settings. Citation Format: Wenyu Wang, Dohyun Han, Yong Sang Song. Proteomic analysis of ascites- and cancer cell-derived EVs for identifying ovarian cancer diagnostic biomarkers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5081.
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