Prediction by bioinformatics analysis of the ability of micrornas in the secretome of menstrual blood-derived stem cells (menscs) as a treatment for ENDOMETRiosis

Abstract Introduction Hormonal therapies and laparoscopic surgery are currently the gold standard treatments for endometriosis. However, their effectiveness is limited, with high recurrence rates observed in treated patients. This underscores the need for novel therapeutic approaches. This study aims to evaluate, in silico, the potential therapeutic effects of microRNAs present in the secretome released by menstrual blood-derived stem cells (S-MenSCs) in databases of patients with endometriosis. Methods MenSCs (n=3) were cultured in DMEM supplemented with 1% ITS for 96 hours. The conditioned medium was ultrafiltered (3 kDa) to isolate the secretome, and the expression of microRNAs was analysed by next-generation sequencing (NGS). Bioinformatics analysis was performed using the MalaCards database to identify differentially expressed genes (DEGs) in endometriotic tissues. The DIANA tools programme was used to assess the interaction capacity of the most abundant microRNAs with these DEGs. Cytoscape 3.8.1 was used to generate the interaction network. Results The analysis revealed an interaction network between 26 microRNAs identified in S-MenSCs and 24 DEGs identified in endometriosis. Each DEG interacted with at least three or more microRNAs, creating a network of numerous interactions. This suggests that the secretome may have the potential to modulate gene expression associated with endometriosis pathology. Conclusion MicroRNAs present in S-MenSCs may offer the potential to modulate the altered gene response in endometriosis. However, further studies are required to validate these findings and explore their clinical applications.