ArticleCancers2022
Protein Panel of Serum-Derived Small Extracellular Vesicles for the Screening and Diagnosis of Epithelial Ovarian Cancer.
Article in Cancers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 2 of them syntheses that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
16 citing papers in PubMed, 2 syntheses or guidelines pooled it, 29 citations in OpenAlex.
- Machine learning-based analysis of cancer cell-derived vesicular proteins revealed significant tumor-specificity and predictive potential of extracellular vesicles for cell invasion and proliferation - A meta-analysis.Cell communication and signaling : CCS · 2023Pooled it
- The current trend of exosome in epithelial ovarian cancer studies: A bibliometric review.Frontiers in pharmacology · 2023Pooled it
- Cancer and Aging Biomarkers: Classification, Early Detection Technologies and Emerging Research Trends.Biosensors · 2025Review
- Machine learning-based prognosis prediction for serous ovarian cancer using the SEER database and data from a single center in China.Translational cancer research · 2025Article
- Bacterial Extracellular Vesicles in Oncology: Molecular Mechanisms and Future Clinical Applications.Cancers · 2025Review
- Extracellular vesicles in cancer´s communication: messages we can read and how to answer.Molecular cancer · 2025Review
- Article
- Novel applications of gene and cell therapies in the treatment of gynecological disorders.Frontiers in medicine · 2025Review
- Advancements in artificial intelligence for ultrasound diagnosis of ovarian cancer: a comprehensive review.Frontiers in oncology · 2025Review
- Highly Efficient Synergistic Chemotherapy and Magnetic Resonance Imaging for Targeted Ovarian Cancer Therapy Using Hyaluronic Acid-Coated Coordination Polymer Nanoparticles.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Quantitative proteomics combined independent PRM analysis reveals the mitochondrial and synaptic mechanism underlying norisoboldine's antidepressant effects.Translational psychiatry · 2024Article
- Proteomic profiles of peritoneal fluid-derived small extracellular vesicles correlate with patient outcome in ovarian cancer.The Journal of clinical investigation · 2024Observational
- Extracellular Vesicles as Liquid Biopsy Biomarkers across the Cancer Journey: From Early Detection to Recurrence.Clinical chemistry · 2024Review
- The role of extracellular vesicles in the pathogenesis of gynecological cancer.Frontiers in oncology · 2024Review
- Serum proteomic profiling of precancerous gastric lesions and early gastric cancer reveals signatures associated with systemic inflammatory response and metaplastic differentiation.Frontiers in molecular biosciences · 2024Article
- Overview of fuzuloparib in the treatment of ovarian cancer: background and future perspective.Journal of gynecologic oncology · 2022Review
Corrections and comments
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Authors and funding
11 authors at 2 institutions in 1 country.
Funding
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.