Protein Panel of Serum-Derived Small Extracellular Vesicles for the Screening and Diagnosis of Epithelial Ovarian Cancer

Abstract

Although ovarian cancer, a gynecological malignancy, has the highest fatality rate, it still lacks highly specific biomarkers, and the differential diagnosis of ovarian masses remains difficult to determine for gynecologists. Our study aimed to obtain ovarian cancer-specific protein candidates from the circulating small extracellular vesicles (sEVs) and develop a protein panel for ovarian cancer screening and differential diagnosis of ovarian masses. In our study, sEVs derived from the serum of healthy controls and patients with cystadenoma and ovarian cancer were investigated to obtain a cancer-specific proteomic profile. In a discovery cohort, 1119 proteins were identified, and significant differences in the protein profiles of EVs were observed among groups. Then, 23 differentially expressed proteins were assessed using the parallel reaction monitoring in a validation cohort. Through univariate and multivariate logistic regression analyses, a novel model comprising three proteins (fibrinogen gamma gene (FGG), mucin 16 (MUC16), and apolipoprotein (APOA4)) was established to screen patients with ovarian cancer. This model exhibited an area under the receiver operating characteristic curve (AUC) of 0.936 (95% CI, 0.888–0.984) with 92.0% sensitivity and 82.9% specificity. Another panel comprising serum CA125, sEV-APOA4, and sEV-CD5L showed excellent performance (AUC 0.945 (95% CI, 0.890–1.000), sensitivity of 88.0%, specificity of 93.3%, and accuracy of 89.2%) to distinguish malignancy from benign ovarian masses. Altogether, our study provided a proteomic signature of circulating sEVs in ovarian cancer. The diagnostic proteomic panel may complement current clinical diagnostic measures for screening ovarian cancer in the general population and the differential diagnosis of ovarian masses.

Proteomic profiles of peritoneal fluid-derived small extracellular vesicles correlate with patient outcome in ovarian cancer

“…Moreover, additional biomarkers presented a similar trend in terms of PFD-sEV cargo when compared with the data previously described ( Supplemental Figure 3B ) ( 23 ). In accordance with the results obtained by Lai et al ( 16 ) by means of protein profiling in peripheral blood–derived exosomes, our data also confirmed the diagnostic value of FGG and APOA4, but not of MUC16 (which showed an opposite expression ratio) ( Figure 3C ). Paralleling the conclusion drawn from the PAX8 immunoblotting results, the robust correlation with these OvCa markers may suggest that our PFD-sEV extracts represent biological specimens of interest for the study of the mechanisms involved in the progression and prognosis of HGSOC.…”

“…Another relevant line of investigation focused on the assessment of the potential of serum sEVs as early diagnostic tools. In this regard, several microRNAs and microRNA signatures ( 14 , 15 , 31 ) and, to a lesser extent, sEV proteins ( 16 ) have been detected in OvCa while being absent in healthy controls. However, as expected in a tumor with limited hematogenous spread, the proportion of tumoral sEVs is minimal, and the correlation with clinical outcome was uncertain in most cases.…”

“…Minor differences observed for the remaining biomarkers could be attributable, not only to the different origin of the samples, but also to the contribution of the tumor microenvironment to the proteomic profile of OvCa-derived PFD-sEVs. In this sense, Lai et al recently proposed an OvCa-diagnostic signature based on the isolation of sEV-derived serum markers (FGG, APOA4, and MUC16 [also known as CA125]) ( 16 ). Although we confirmed the diagnostic role of FGG and APOA4 in the PFD-sEV fraction, this was not the case for MUC16.…”

“…( C ) Graphs showing normalized ratios of FGG, APOA4, and MUC16 protein expression in PFD-sEVs comparing samples from our discovery cohort (patients with HGSOC [ n = 23] vs. controls [ n = 10]). These factors have previously been described as diagnostic markers for OvCa in serum-derived sEVs ( 16 ). Benjamini-Hochberg adjusted P values: * P < 0.05, *** P < 0.001, Mann-Whitney test.…”

The current trend of exosome in epithelial ovarian cancer studies: A bibliometric review

“…Only articles published in English were included. After the exclusion of duplicate, irrelevant journal articles and non-journal articles, 39 articles on exosome and EOC were selected for bibliometric analysis; 36 of which were original articles ( Zhang et al, 2016a ; Meng et al, 2016b ; Zhang et al, 2016b ; Labani-Motlagh et al, 2016 ; Ying et al, 2016 ; Chen et al, 2017 ; Hu et al, 2017 ; Li et al, 2017 ; Wu et al, 2017 ; Chen et al, 2018 ; Qiu et al, 2018 ; Zhang et al, 2018 ; Zhou et al, 2018 ; Zhang et al, 2019a ; Keserű et al, 2019 ; Tang et al, 2019 ; Zhu et al, 2019 ; Cheng et al, 2020 ; Li et al, 2020 ; Lu et al, 2020 ; Luo and Gui, 2020 ; Maeda et al, 2020 ; Masoumi-Dehghi et al, 2020 ; Alharbi et al, 2021 ; Xiong et al, 2021a ; Cai et al, 2021 ; Gao et al, 2021 ; Li et al, 2021 ; Liu et al, 2021 ; Ma et al, 2021 ; Zhu et al, 2022a ; Chen et al, 2022 ; Jeon et al, 2022 ; Lai et al, 2022 ; Yang et al, 2022 ), and the rest of them were review articles ( Li and Wang, 2017 ; Lucidi et al, 2020 ; Shiao et al, 2021 ). The first English article is “Characterization of exosomes derived from ovarian cancer cells and normal ovarian epithelial cells by nanoparticle tracking analysis” in 2015 ( Zhang et al, 2016a ).…”