Molecular Profiles of Serum-Derived Extracellular Vesicles in High-Grade Serous Ovarian Cancer

CANCERS(2022)

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摘要
Simple Summary Ovarian cancer is the deadliest gynecological malignancy worldwide, and the biggest issue faced by patients is disease relapse after primary treatment. Understanding up front how patients will respond to therapy is an important and compelling challenge. On these premises, our goal was to understand if a simple blood sample can give us this information, before the patients start chemotherapy. We determined that circulating extracellular vesicles isolated at diagnosis can distinguish between patients who will respond differently to the treatment. These results, if corroborated, will pave the way for a novel, much needed predictive marker of response. Patients with high-grade serous ovarian cancer (HGSC) who have no visible residual disease (R0) after primary surgery have the best clinical outcomes, followed by patients who undergo neoadjuvant chemotherapy (NACT) and have a response enabling interval cytoreductive surgery. Clinically useful biomarkers for predicting these outcomes are still lacking. Extracellular vesicles (EVs) have been recognized as liquid biopsy-based biomarkers for early cancer detection and disease surveillance in other disease settings. In this study, we performed extensive molecular characterization of serum-derived EVs and correlated the findings with therapeutic outcomes in patients with HGSC. Using EV-DNA whole-genome sequencing and EV-RNA sequencing, we identified distinct somatic EV-DNA alterations in cancer-hallmark genes and in ovarian cancer genes, as well as significantly altered oncogenic pathways between the R0 group and NACT groups. We also found significantly altered EV-RNA transcriptomic variations and enriched pathways between the groups. Taken together, our data suggest that the molecular characteristics of EVs could enable prediction of patients with HGSC who could undergo R0 surgery or respond to chemotherapy.
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关键词
extracellular vesicle, high-grade serous ovarian cancer, whole-genome sequencing, RNA sequencing, chemotherapy response
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