COL1A1+ Epithelial Cells Orchestrate VEGFA-VEGFR Signaling in Endometritis Revealed by Single-Cell Analysis.

BACKGROUND

Endometritis is linked to adverse reproductive outcomes, but epithelial programs in disease initiation and persistence remain unclear. We aimed to systematically define inflammation-associated epithelial states and regulation in endometritis using single-cell analysis.

METHOD: The single-cell RNA sequencing (scRNA-seq) data from Gene Expression Omnibus (GEO) were processed using Seurat. After quality control, data were normalized with SCTransform and batch-corrected using the Harmony package. Cell types were annotated based on canonical markers. Differential expression analysis was performed to identify genes altered in endometritis. Epithelial cells were subsetted for reclustering and trajectory inference using Monocle2. Cell-cell communication was inferred with CellChat, and transcriptional regulon activity was assessed using SCENIC and AUCell methods.

RESULTS

A total of 153,877 cells formed 14 clusters across seven lineages, with lower epithelial proportion in endometritis. Epithelial cells included four subpopulations (SPDEF+, MT1H+, Ciliated, COL1A1+), with SPDEF+ and COL1A1+ expanded in disease. Upregulated epithelial genes enriched in ribosome, antigen processing/presentation, and estrogen-related pathways. Pseudotime showed a continuous trajectory splitting into two fates: one ferroptosis-related with glutathione metabolism and mineral absorption, the other ribosome and antigen presentation. Communication networks were denser in endometritis, with COL1A1+ epithelium as a hub and enhanced VEGFA-VEGFR signaling. SCENIC revealed elevated regulon activity in disease, especially AP-1 (JUN/FOS) modules.

CONCLUSION

This epithelial-centric single-cell atlas delineates disease-associated states, fate decisions, signaling axes, and regulatory programs in endometritis. The data support a model of epithelial fate remodeling coupled to angiogenic signaling and AP-1-driven transcription, nominating testable targets for mechanistic validation and potential translation.