Single‐Cell RNA Transcriptome of the Human Endometrium Reveals Epithelial Characterizations Associated with Recurrent Implantation Failure

Abstract

Recurrent implantation failure (RIF) remains a complex and poorly characterized disorder despite significant advancements in assisted reproductive technology. This study utilizes single‐cell transcriptome sequencing (scRNA‐seq) to characterize the mid‐secretory endometrium of RIF patients. Stromal fibroblast‐enriched and epithelium‐enriched populations are collected using a two‐step dissociation process. After quality control, 25,315 individual cells from 3 RIF patients are analyzed. The analysis identifies 12 distinct cell types, including 6 subtypes of epithelial cells. Significantly, the study reveals the replacement of glandular epithelia with MAP2K6+EPCAMDIM epithelia in the endometrial glands of RIF patients. Furthermore, the study demonstrates that endometrial gland organoids derived from RIF patients exhibit diminished responses to sex steroids compared to the controls. Single‐cell regulatory network inference and clustering (SCENIC) analysis identifies cell‐specific cis‐regulatory elements and constructed regulatory networks in both groups, showing alterations gene‐regulatory networks in RIF patients. Cell‐cell communication analysis distinguishes intercellular communication between the two groups, shedding light on disrupted cellular interactions associated with RIF. In summary, these findings provide valuable insights into the cellular and molecular mechanisms underlying RIF, highlighting the roles of epithelial cells in the implantation process.

Bioengineering approaches for the endometrial research and application

“…Apart from the application of the human endometrium, efforts have also highlighted progress in terms of the ovary, vagina, and cervix, allowing the generation of unprecedented insights into preclinical modeling for normal and impaired reproductive potentials [ 38 ]. Furthermore, combining these models with other microtechnologies (including single-cell analysis and gene editing) makes them suitable for individual therapies and personalized medicine [ 39 , 40 ].…”