Extracellular Vesicles-Based Biomarkers Represent a Promising Liquid Biopsy in Endometrial Cancer.
Carolina HerreroAlexandre de la FuenteCarlos Casas-ArozamenaVictor Sebastian CabezaMartin PrietoManuel ArrueboAlicia AbaloEva ColásGema Moreno-BuenoAntonio Gil-MorenoAna VilarJuan CuevaMiguel AbalLaura Muinelo-RomayPublished in: Cancers (2019)
Tumor-derived extracellular vesicles (EVs) are secreted in large amounts into biological fluids of cancer patients. The analysis of EVs cargoes has been associated with patient´s outcome and response to therapy. However, current technologies for EVs isolation are tedious and low cost-efficient for routine clinical implementation. To explore the clinical value of circulating EVs analysis we attempted a proof-of-concept in endometrial cancer (EC) with ExoGAG, an easy to use and highly efficient new technology to enrich EVs. Technical performance was first evaluated using EVs secreted by Hec1A cells. Then, the clinical value of this strategy was questioned by analyzing the levels of two well-known tissue biomarkers in EC, L1 cell adhesion molecule (L1CAM) and Annexin A2 (ANXA2), in EVs purified from plasma in a cohort of 41 EC patients and 20 healthy controls. The results demonstrated the specific content of ANXA2 in the purified EVs fraction, with an accurate sensitivity and specificity for EC diagnosis. Importantly, high ANXA2 levels in circulating EVs were associated with high risk of recurrence and non-endometrioid histology suggesting a potential value as a prognostic biomarker in EC. These results also confirmed ExoGAG technology as a robust technique for the clinical implementation of circulating EVs analyses.
Keyphrases
- endometrial cancer
- highly efficient
- primary care
- healthcare
- low cost
- cell adhesion
- end stage renal disease
- induced apoptosis
- ejection fraction
- case report
- newly diagnosed
- cell proliferation
- risk assessment
- quality improvement
- prognostic factors
- climate change
- high resolution
- bone marrow
- ultrasound guided
- peritoneal dialysis
- oxidative stress
- data analysis
- endoplasmic reticulum stress