scRNAseq-Endometrium

Gang Xu1, *, Tao Pan1, *, Si Li1, *, Jing Guo1, Ya Zhang1, Qi Xu1, Renwei Chen2,*, Yanlin Ma1,* and Yongsheng Li1,*

1 Hainan Provincial Key Laboratory for Human Reproductive Medicine and Genetic Research, Reproductive Medical Center, National Center for International Research, The First Affiliated Hospital of Hainan Medical University, College of Biomedical Information and Engineering, Hainan Medical University, Haikou, Hainan 571199, China.

2 Hainan Women and Children's Medical Center, Hainan Medical University, Haikou, Hainan 571199, China.

Gang Xu1, *;

Tao Pan1, *;

Si Li1, *.

*These authors contributed equally to this work. 

* Correspondence: 

Yongsheng Li, liyongsheng@hainmc.edu.cn (Y.L.);

Yanlin Ma, mayanlinma@hotmail.com (Y.M.);

Renwei Chen, chenrenwei@sina.com (R.C.).

Deconvolution of immune microenvironment that drive transcriptional programs throughout the menstrual cycle is key to understanding regulatory biology of endometrium. Herein, we comprehensively analyzed single cell transcriptome of 10 human endometrium samples and revealed the dynamic cellular heterogeneity throughout the menstrual cycle. In particular, we identified two perivascular cell subtypes, four epithelial subtypes and four fibroblast cell types in endometrium. Moreover, we inferred the cell type-specific transcription factor (TF) activities and linked critical TFs to transcriptional output of diverse immune cell types, highlighting the importance of transcriptional regulation in endometrium. Dynamic interactions between various types of cells in endometrium contribute to a range of biological pathways regulating differentiation of secretory. Integration of the molecular biomarkers identified in endometrium and bulk transcriptome of 535 endometrial cancers (EC), we revealed five molecular subtypes of EC with highly intratumoral heterogeneity and different clinical manifestations. Mechanism analysis uncovered clinically relevant pathways for pathogenesis of EC. In summary, dynamic immune microenvironment analyses provide novel insights into future development of treatments for endometriosis and endometrial carcinoma.