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Establishment of an Experimental Mouse Model of Endometrioma to Study its Related Infertility
Published on: April 5, 2024
The Role of Molecular Characterization in Precision Medicine in Endometriosis
Indel Travis Niles1, Martina Scialabba, Roxanne Lacouline Boulanger
1Department of Pathology and the Department of Obstetrics and Gynecology, Faculty of Medicine and Health Sciences, the Faculty of Medicine and Health Sciences, and the Department of Physiology, McGill University, the Research Institute of the McGill University Health Centre, the Department of Pathology, McGill University Health Centre, Glen Site, and the Endometriosis Centre for the Advancement of Research and Surgery, McGill University Health Centre, Montreal, Quebec, Canada; and Università degli Studi di Milano, Statale, Milano, Italy.
Abstract:
Endometriosis is a chronic condition in which tissue similar to the lining of the uterus grows in other parts of the body. It affects roughly 1 in 10 women of reproductive age, often causing severe pelvic pain and infertility. Despite how common it is, patients frequently wait nearly a decade for an accurate diagnosis, and current treatments often rely on trial and error rather than targeted science. This review simplifies the complex biologic "blueprint" of the disease to explain why it behaves the way it does. Recent research shows that endometriosis is more than a one-dimensional hormonal imbalance; it involves several key biologic factors, including genetic drivers, hormonal status, and physical changes such as neuroangiogenesis or fibrosis. Currently, no simple laboratory test or biomarker can predict how the disease will progress, largely because of the heterogeneity and small, retrospective nature of studies. To move toward personalized medicine, larger, more diverse studies that connect each patient's specific genetic profile to their symptoms and disease phenotype are needed. By mapping these molecular details, we can progress toward faster diagnoses, tailored care to each individual's disease burden, and recurrence risk stratification and surgical planning based on molecular characteristics.
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