Usage Information
Abstract
The development and progression of endometriotic lesions are poorly understood, but immune cell dysfunction and inflammation are closely associated with the pathophysiology of endometriosis. There is a need for 3D in vitro models to permit the study of interactions between cell types and the microenvironment. To address this, we developed endometriotic spheroids (ES) to explore the role of epithelial-stromal interactions and model peritoneal invasion associated with lesion development. Using a nonadherent microwell culture system, spheroids were generated with immortalized endometriotic epithelial cells (12Z) combined with endometriotic stromal (iEc-ESC) or uterine stromal (iHUF) cell lines. Transcriptomic analysis found 4,522 differentially expressed genes in ES compared with spheroids containing uterine stromal cells. The top increased gene sets were inflammation-related pathways, and an overlap with baboon endometriotic lesions was highly significant. Finally, to mimic invasion of endometrial tissue into the peritoneum, a model was developed with human peritoneal mesothelial cells in an extracellular matrix. Invasion was increased in the presence of estradiol or pro-inflammatory macrophages and suppressed by a progestin. Taken together, our results strongly support the concept that ES are an appropriate model for dissecting mechanisms that contribute to endometriotic lesion development.
Authors
Yong Song, Gregory W. Burns, Niraj R. Joshi, Ripla Arora, J. Julie Kim, Asgerally T. Fazleabas
Usage data is cumulative from March 2025 through March 2026.
| Usage | JCI | PMC |
|---|---|---|
| Text version | 2,721 | 774 |
| 336 | 117 | |
| Figure | 796 | 19 |
| Table | 58 | 0 |
| Supplemental data | 323 | 23 |
| Citation downloads | 166 | 0 |
| Totals | 4,400 | 933 |
| Total Views | 5,333 | |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.
