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Mapping Single-Cell Transcriptomes of Endometrium Reveals Potential Biomarkers in Endometrial Cancer.
Gang Xu1,2, Tao Pan2, Si Li2,3
1College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China, Harbin, 150081, People's Republic of China.
Immunotargets and Therapy
|July 25, 2024
Summary
This study reveals the dynamic immune microenvironment of the human endometrium across the menstrual cycle. Findings offer new insights for developing RNA-based treatments for endometriosis and endometrial carcinoma.
Area of Science:
- Reproductive biology
- Genomics
- Immunology
Background:
- Endometrial cell heterogeneity and dynamics are crucial for menstrual cycle function.
- Endometrial dysfunction is linked to gynecological diseases.
- Understanding the immune microenvironment's transcriptional programs is key to endometrial biology.
Purpose of the Study:
- To comprehensively analyze the single-cell transcriptome of human endometrium across the menstrual cycle.
- To identify cell types, transcription factor activities, and cell-cell interactions.
- To reveal molecular subtypes of endometrial carcinoma (EC) and their pathogenesis.
Main Methods:
- Single-cell RNA sequencing of 59,397 cells from ten human endometrium samples.
- Identification of endometrial cell subtypes (perivascular, epithelial, fibroblast).
- Inference of cell type-specific transcription factor activities and integration with EC bulk transcriptomes.
Main Results:
- Characterization of two perivascular, four epithelial, and four fibroblast cell subtypes.
- Identification of critical transcription factors regulating endometrial cell function.
- Discovery of five RNA-based molecular subtypes of endometrial carcinoma with distinct clinical features.
Conclusions:
- The study elucidates the dynamic immune microenvironment of the endometrium.
- Novel insights are provided for RNA-based therapeutic strategies for endometriosis and endometrial carcinoma.
- Highlights the importance of transcriptional regulation in endometrial health and disease.
Keywords:
RNA biomarkersbiological pathwayscell–cell interactionmolecular subtypessingle-cell sequencing
