Exploration of Potential Diagnostic Value of Protein Content in Serum Small Extracellular Vesicles for Early-Stage Epithelial Ovarian Carcinoma

Extracellular vesicles in cancer: challenges and opportunities for clinical laboratories

Extracellular vesicles (EVs) are nano-sized particles secreted by most cells. They transport different types of biomolecules (nucleic acids, proteins, and lipids) characteristic of their tissue or cellular origin that can mediate long-distance intercellular communication. In the case of cancer, EVs participate in tumor progression by modifying the tumor microenvironment, favoring immune tolerance and metastasis development. Consequently, EVs have great potential in liquid biopsy for cancer diagnosis, prognosis and follow-up. In addition, EVs could have a role in cancer treatment as a targeted drug delivery system. The intense research in the EV field has resulted in hundreds of patents and the creation of biomedical companies. However, methodological issues and heterogeneity in EV composition have hampered the advancement of EV validation trials and the development of EV-based diagnostic and therapeutic products. Consequently, only a few EV biomarkers have moved from research to clinical laboratories, such as the ExoDx Prostate IntelliScore (EPI) test, a CLIA/FDA-approved EV prostate cancer diagnostic test. In addition, the number of large-scale multicenter studies that would clearly define biomarker performance is limited. In this review, we will critically describe the different types of EVs, the methods for their enrichment and characterization, and their biological role in cancer. Then, we will specially focus on the parameters to be considered for the translation of EV biology to the clinic laboratory, the advances already made in the field of EVs related to cancer diagnosis and treatment, and the issues still pending to be solved before EVs could be used as a routine tool in oncology.

Exosomal biomarkers in the differential diagnosis of ovarian tumors: the emerging roles of CA125, HE4, and C5a

OBJECTIVE

Investigating the utility of serum exosomal markers CA125, HE4, and C5a, both individually and in combination, for distinguishing between benign and malignant ovarian tumors.

METHODS

In this study, we selected a total of 234 patients diagnosed with ovarian tumors, including 34 with malignant tumors, 10 with borderline ovarian tumors, and 190 with benign tumors. This study conducted comparisons of exosomal levels of CA125, HE4, and C5a among distinct groups, as well as making comparisons between serum and exosomal levels of CA125 and HE4. Furthermore, the diagnostic performance was assessed through Receiver Operating Characteristic (ROC) curve analysis. The Area Under the Curve (AUC) was computed, and a comparative evaluation of sensitivity and specificity was conducted to ascertain their effectiveness in determining the nature of ovarian tumors across different markers.

RESULTS

Serum CA125 and HE4 levels, the ROMA index, exosomal CA125, HE4, C5a levels, and their combined applied value (OCS value) were notably elevated in the ovarian non-benign tumor group compared to the benign tumor group, with statistical significance (P < 0.05). Exosomal and serum levels of CA125 and HE4 exhibited a positive correlation, with concentrations of these markers in serum surpassing those in exosomes. The combined OCS (AUC = 0.871) for CA125, HE4, and C5a in exosomes demonstrated superior sensitivity (0.773) and specificity (0.932) compared to serum tumor markers (CA125, HE4) and the ROMA index. The tumor stage represents an autonomous risk factor influencing the prognosis of individuals with ovarian malignancies.

CONCLUSION

The stage of ovarian malignancy is an independent risk factor for its prognosis. The combination of exosomal CA125, HE4 and C5a has a higher clinical value for the identification of the nature of ovarian tumours.

Identifying Serum Small Extracellular Vesicle MicroRNA as a Noninvasive Diagnostic and Prognostic Biomarker for Ovarian Cancer

There remains a lack of effective and noninvasive methods for the diagnosis and prognosis prediction of epithelial ovarian carcinoma (EOC). Here, we investigated the possibility of serum-derived small extracellular vesicle (sEV) microRNAs (miRNAs) as potential biomarkers for distinguishing between benign and malignant adnexal masses and predicting the prognosis of EOC patients. A serum sEV miRNA model for identifying the EOC (sEVmiR-EOC) was successfully established in the training cohort. Furthermore, the sEVmiR-EOC model was confirmed in the testing cohort and validation cohort, demonstrating robust diagnostic accuracy. The sEVmiR-EOC model showed better performance than carbohydrate antigen 125 (CA125) in discriminating patients with stage I EOC from benign patients. Using EOC samples and follow-up data, we identified miR-141-3p and miR-200c-3p as potential prognostic predictors. Finally, we confirmed the change of the sEVmiR-EOC RiskScore between the preoperative and postoperative samples and found that the sEVmiR-EOC model could predict the prognosis of EOC patients.

Molecular Profile Study of Extracellular Vesicles for the Identification of Useful Small “Hit” in Cancer Diagnosis

Tumor-secreted extracellular vesicles (EVs) are the main mediators of cell-cell communication, permitting cells to exchange proteins, lipids, and metabolites in varying physiological and pathological conditions. They contain signature tumor-derived molecules that reflect the intracellular status of their cell of origin. Recent studies have shown that tumor cell-derived EVs can aid in cancer metastasis through the modulation of the tumor microenvironment, suppression of the immune system, pre-metastatic niche formation, and subsequent metastasis. EVs can easily be isolated from a variety of biological fluids, and their content makes them useful biomarkers for the diagnosis, prognosis, monitorization of cancer progression, and response to treatment. This review aims to explore the biomarkers of cancer cell-derived EVs obtained from liquid biopsies, in order to understand cancer progression and metastatic evolution for early diagnosis and precision therapy.