WERF Endometriosis Phenome and Biobanking Harmonisation Project for Experimental Models in Endometriosis Research (EPHect-EM-Organoids): endometrial organoids as an emerging technology for endometriosis research

Abstract

The aetiology of endometriosis remains poorly understood. In vitro model systems provide the opportunity to identify the mechanisms driving disease pathogenesis using human cells. Three-dimensional models, particularly organoid systems, have revolutionized how we study epithelial biology and are powerful tools for modelling endometriosis. As an emerging model system, it is important to define protocols and identify the remaining challenges surrounding endometrial organoid culture to increase reproducibility and scientific rigour in endometriosis research. The World Endometriosis Research Foundation (WERF) established an international working group comprised of experts using in vitro approaches for the study of endometriosis. This working group harmonized protocols and documentation of existing and emerging organoid systems to maximize comparison and replication across the field and guide specific research hypotheses testing. This evaluation of organoid protocols, limitations, challenges, and alternative approaches assessed both published and grey literature papers across several disciplines pertinent to endometriosis research. Recommendations for protocol and documentation harmonization are presented, and we created the first-ever decision tree diagram to guide and facilitate the selection of existing models best suited for specific areas of endometriosis research. Rigorous and systematic assessment of emerging organoid systems, recognizing the inferential strengths and limitations of these approaches, is vital for endometriosis research. This comprehensive review of the benefits, limitations, and utilization of organoid models, as well as the consequent integration of protocols and documentation, will contribute to the scientific knowledge base by maximizing the reproducibility, comparability, and interpretation of research studies in endometriosis. Additionally, these newly developed protocols and documentation should serve as a resource for, and facilitate collaboration between, endometriosis investigators using organoids in their research methods.

Keywords: collaboration; emerging models; endometriosis; experimental models; organoids; research.

Figure 1.

Characterization of endometrial epithelial organoids (EEOs). EEOs are in vitro gland-like structures generated from adult-derived primary endometrial epithelial glands. (A) Schematic of the generation of organoids from endometrial glands. (B) Immunofluorescent staining confirms the epithelial phenotype of EEOs, with epithelial marker EpCAM (red) staining organoid epithelial cells, while F-actin (green) staining highlights the polarization and architecture of pseudostratified columnar epithelial cells. Scale bar = 50 μm. (C) Time-lapse imaging of EEOs derived from a single cell across 14 days of culture. EEOs are clonal and can be maintained in 3D hydrogel cultures for multiple weeks to generate multicellular structures. Scale bar = 500 μm. (D) EEOs stain positively for secretory markers such as progestogen-associated endometrial protein (PAEP), with secretory cells that will secrete into the luminal centre of the organoid. EEOs also stain positively on the luminal cell surface of polarized epithelial cells for cilia via acetylated α-tubulin (Ac. α-tubulin). Scale bars = 100 μm (left) and 5 μm (right). Panels B and C were adapted from Turco et al. (2017), Fig. 5a (cropped) and Fig. 5c, respectively (Turco et al., 2017) used by permission under a Creative Commons Attribution License CC BY (2012).

Figure 2.

Principles and key steps in the generation of endometrial epithelial organoids (EEOs). Schematic of the generation of endometrial organoids. EEOs are sourced from primary endometrial epithelial glands, embedded in Matrigel* (or another 3D matrix) and then supplemented with defined media to support organoid formation and growth. Organoids can be enzymatically and mechanically digested to single cells then passaged, and the process can be repeated to build libraries of EEOs from various donors. The scale bars in images represent 400 μm (top) and 800 μm (bottom).

Figure 3.

Disease modelling of endometrial disorders using organoids. Multiple studies have generated endometrial organoids from diseased or unique tissue sources, as highlighted in the leftmost panel. Research Rabbit was utilized, an open-source platform that collates relevant papers based on a cited collection (citations from the leftmost list were input and are highlighted in green), which connects researchers to associated works based on citations and manuscript tags (displayed in blue). This platform was utilized to ensure comprehensive coverage of the organoid field, and many highlighted blue citations are discussed within this article.

Figure 4.

Existing in vitro technologies for endometriosis research. An overview of the range of desired applications, design principles to consider, and existing cell sources and modelling platforms that can be used to perform in vitro endometrial research. Cell sourcing from healthy or diseased tissues can be paired with design principles that mimic the in vivo environment pertinent to the research question at the appropriate scale and throughput. These design principles include the mechanics, dimensionality, cellular complexity, and throughput of systems to yield different modelling platforms for healthy or diseased endometrial in vitro models. Far left panel: AUB, abnormal uterine bleeding. Created in BioRender. Marr (2025). https://BioRender.com/caj893u.

Figure 5.

A decision tree framework for guiding endometriosis model selection. Beginning at the top left, responses will guide researchers to models best suited for their experimental set-up, and are focused on cell populations of interest, scale, microenvironment, and disease state. This decision tree is a starting framework focused on in vitro models such as those covered in this paper. ECM, extracellular matrix.