A promising future for endometriosis diagnosis and therapy: extracellular vesicles - a systematic review.

Endometriosis is a chronic, inflammatory gynaecological disease that can have severe negative impacts on quality of life and fertility, placing burden on patients and the healthcare system. Due to the heterogeneous nature of endometriosis, and the lack of correlation between symptom and surgical disease severity, diagnosis and treatment remain a significant clinical challenge. Extracellular vesicles (EVs) are biologically active particles containing molecular cargo involved in intercellular communication, that can be exploited for diagnostic and therapeutic purposes.We systematically reviewed studies exploring EVs and their role in endometriosis, specifically addressing diagnostic and therapeutic potential and current understanding of pathophysiology. Five databases (Pubmed, Embase, Medline, Web of Science, Google Scholar) were searched for keywords 'endometriosis' and either 'extracellular vesicles' or 'exosomes'.There were 28 studies included in the review. Endometrium derived EVs contribute to the development of endometriosis. EVs derived from endometriosis lesions contribute to angiogenesis, immunomodulation and fibrosis. Such EVs can be detected in blood, with early data demonstrating utility in diagnosis and recurrence detection. EV isolation techniques varied between studies and only eight of twenty-eight studies fully characterised EVs according to current recommended standards. Reporting/type of endometriosis was limited across studies. Varied patient population, type of sample and isolation techniques created bias and difficulty in comparing studies.EVs hold promise for improving care for symptomatic patients who have never had surgery, as well as those with recurrent symptoms after previous surgery. We encourage further EV research in endometriosis with the inclusion of rigorous reporting of both the patient population and technical methodology used, with the ultimate goal of achieving clinical utility for diagnosis, prognosis and eventually treatment.