Endometrial Organoids and Their Role in Modeling Human Infertility

Endometrial organoids (EOs) have emerged as a powerful three-dimensional (3D) model for studying the human endometrium, offering new insights into infertility and reproductive disorders. These self-organizing miniature structures closely mimic the cellular composition, hormonal responsiveness, and functional characteristics of the endometrium, making them valuable preclinical tools for investigating implantation failure, endometrial receptivity, and disease pathophysiology. This review explores the role of EOs in reproductive medicine, with a focus on their applications in infertility research, environmental toxicology, and regenerative therapies. Traditional 2D cell cultures fail to capture the complexity of these physiological and pathological interactions, whereas organoids provide a physiologically relevant system for studying implantation mechanisms. Additionally, co-culture models incorporating stromal and immune cells have further enhanced our understanding of the maternal-fetal interface. Beyond modeling infertility, EOs hold significant promise for therapeutic applications. Advances in organoid transplantation have demonstrated potential for treating endometrial dysfunction-related infertility, including conditions such as Asherman's syndrome and thin endometrium. Moreover, these models serve as a platform for drug screening and biomarker discovery, paving the way for personalized reproductive medicine. Despite their transformative potential, limitations remain, including the need for improved extracellular matrices, vascularization, and immune system integration. This review emphasizes the significant contributions of EOs to the field of infertility treatment and reproductive biology by examining recent advancements and emerging research. The continued refinement of these models would offer a paradigm for improving assisted reproductive technologies (ARTs) and regenerative medicine outcomes, offering new hope for individuals facing infertility challenges.