Abstract
High-grade serous ovarian cancer (HGSOC) is the most aggressive type of ovarian cancer and is responsible for most deaths caused by gynecological cancers. Numerous candidate biomarkers were identified for this disease in the last decades, but most were not sensitive or specific enough for clinical applications. Hence, new biomarkers for HGSOC are urgently required. This study aimed to identify new markers by isolating different extracellular vesicle (EV) types from the ascites of ovarian cancer patients according to their affinities for lipid-binding proteins and analyzing their protein cargo. This approach circumvents the low signal-to-noise ratio when using biological fluids for biomarker discovery and the issue of contamination by large non-EV complexes. We isolated and analyzed three distinct EV populations from the ascites of patients with ovarian cancer or cirrhosis and observed that Annexin V-binding EVs have higher levels of matrix metalloproteinase 9 in malignant compared to portal-hypertensive ascites. As this protein was not detected in other EV populations, this study validates our approach of using different EV types for optimal biomarker discovery. Furthermore, MMP9 in Annexin V-binding EVs could be a HGSOC biomarker with enhanced specificity, because its identification requires detection of two distinct components, that is, lipid and protein.
Highlights
Ovarian cancer is the deadliest among gynecologic malignancies with a 5-year survival rate after diagnosis of 27% [1]
Consistent with this, we delete detected CD59 in extracellular vesicle (EV) from ovarian cancer ascites and we found that this protein was localized to Annexin V (AV)-binding EVs (Figure 2, lane 1)
We demonstrated here a proof of concept that using membrane lipid-binding ligands to isolate different EV subpopulations from ascites fluid is an efficient method for biomarker discovery as it will enhance the signal-tonoise ratio
Summary
Ovarian cancer is the deadliest among gynecologic malignancies with a 5-year survival rate after diagnosis of 27% [1]. Over the last few years, extracellular vesicles (EVs) have gained a lot of interest as potential sources of biomarkers in many diseases including ovarian cancer, because the secreted vesicles and their cargo resemble their cell of origin and, EVs can be accessed and isolated from any of our bodily fluids [3]. Individual classes of EVs, for instance, exosomes or microvesicles, are very difficult to discriminate, because they overlap in their physical characteristics like size or density and in their cargo molecules [11]. This lack of distinguishing criteria makes the isolation of pure vesicle populations almost impossible with currently used methods. Recent publications suggest that even within the earlier defined classes of EVs, there are more subclasses of vesicles with distinct cargo and functionality [12] adding another layer of complexity
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