MiR-6924-5p-rich exosomes derived from genetically modified Scleraxis-overexpressing PDGFRα(+) BMMSCs as novel nanotherapeutics for treating osteolysis during tendon-bone healing and improving healing strength.

Osteolysis at the tendon-bone interface can impair pullout strength during tendon-bone healing and lead to surgery failure, but the effects of clinical treatments are not satisfactory. Mesenchymal stem cell (MSC)-derived exosomes have been used as potent and feasible natural nanocarriers for drug delivery and have been proven to enhance tendon-bone healing strength, indicating that MSC-derived exosomes could be a promising therapeutic strategy. In this study, we explored Scleraxis (Scx) dynamically expressed in PDGFRα(+) bone marrow-derived mesenchymal stem cells (BMMSCs) during natural tendon-bone healing. Then, we investigated the role of PDGFRα(+) BMMSCs in tendon-bone healing after Scx overexpression as well as the underlying mechanisms. Our data demonstrated that Scx-overexpressing PDGFRα(+) BMMSCs (BMMSCScx) could efficiently inhibit peritunnel osteolysis and enhance tendon-bone healing strength by preventing osteoclastogenesis in an exosomes-dependent manner. Exosomal RNA-seq revealed that the abundance of a novel miRNA, miR-6924-5p, was highest among miRNAs. miR-6924-5p could directly inhibit osteoclast formation by binding to the 3'-untranslated regions (3'UTRs) of OCSTAMP and CXCL12. Inhibition of miR-6924-5p expression reversed the prevention of osteoclastogenic differentiation by BMMSCScx derived exosomes (BMMSCScx-exos). Local injection of BMMSCScx-exos or miR-6924-5p dramatically reduced osteoclast formation and improved tendon-bone healing strength. Furthermore, delivery of miR-6924-5p efficiently inhibited the osteoclastogenesis of human monocytes. In brief, our study demonstrates that BMMSCScx-exos or miR-6924-5p could serve as a potential therapy for the treatment of osteolysis during tendon-bone healing and improve the outcome.

Screening of key biomarkers of tendinopathy based on bioinformatics and machine learning algorithms.

Tendinopathy is a complex multifaceted tendinopathy often associated with overuse and with its high prevalence resulting in significant health care costs. At present, the pathogenesis and effective treatment of tendinopathy are still not sufficiently elucidated. The purpose of this research is to intensely explore the genes, functional pathways, and immune infiltration characteristics of the occurrence and development of tendinopathy. The gene expression profile of GSE106292, GSE26051 and GSE167226 are downloaded from GEO (NCBI comprehensive gene expression database) and analyzed by WGCNA software bag using R software, GSE26051, GSE167226 data set is combined to screen the differential gene analysis. We subsequently performed gene enrichment analysis of Gene Ontology (GO) and "Kyoto Encyclopedia of Genes and Genomes" (KEGG), and immune cell infiltration analysis. By constructing the LASSO regression model, Support vector machine (SVM-REF) and Gaussian mixture model (GMMs) algorithms are used to screen, to identify early diagnostic genes. We have obtained a total of 171 DEGs through WGCNA analysis and differentially expressed genes (DEGs) screening. By GO and KEGG enrichment analysis, it is found that these dysregulated genes were related to mTOR, HIF-1, MAPK, NF-κB and VEGF signaling pathways. Immune infiltration analysis showed that M1 macrophages, activated mast cells and activated NK cells had infiltration significance. After analysis of THE LASSO SVM-REF and GMMs algorithms, we found that the gene MACROD1 may be a gene for early diagnosis. We identified the potential of tendon disease early diagnosis way and immune gene regulation MACROD1 key infiltration characteristics based on comprehensive bioinformatics analysis. These hub genes and functional pathways may as early biomarkers of tendon injuries and molecular therapy level target is used to guide drug and basic research.