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Osteoarthritis (OA) leads to chronic pain and disability, and traditional conservative treatments are not effective in the long term. The intra-articular injection of mesenchymal stem cells (MSCs) is considered a novel therapy for OA whose efficacy mainly relies on the adaptive release of paracrine molecules which are either soluble or extracellular vesicles (EVs) embedded. The correct quantification of EV-miRNAs using reliable reference genes (RGs) is a crucial step in optimizing this future therapeutic cell-free approach. The purpose of this study is to rate the stabilities of literature-selected proposed RGs for EV-miRNAs in adipose derived-MSCs (ASCs). EVs were isolated by ultracentrifugation from ASCs cultured with or without inflammatory priming mimicking OA synovial fluid condition. Expression of putative RGs (let-7a-5p, miR-16-5p, miR-23a-3p, miR-26a-5p, miR-101-3p, miR-103a-3p, miR-221-3p, miR-423-5p, miR-425-5p, U6 snRNA) was scored by using the algorithms geNorm, NormFinder, BestKeeper and ΔCt method. miR-16a-5p/miR-23a-3p yielded the most stable RGs, whereas let-7a-5p/miR-425-5p performed poorly. Outcomes were validated by qRT-PCR on miR-146a-5p, reported to be ASC-EVs enriched and involved in OA. Incorrect RG selection affected the evaluation of miR-146a-5p abundance and modulation by inflammation, with both values resulting strongly donor-dependent. Our findings demonstrated that an integrated approach of multiple algorithms is necessary to identify reliable, stable RGs for ASC-EVs miRNAs evaluation. A correct approach would increase the accuracy of embedded molecule assessments aimed to develop therapeutic strategies for the treatment of OA based on EVs.

Identification of miRNA Reference Genes in Extracellular Vesicles from Adipose Derived Mesenchymal Stem Cells for Studying Osteoarthritis