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Immune micro-environment and drug analysis of peritoneal endometriosis based on epithelial-mesenchymal transition classification

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Background Epithelial-mesenchymal transition (EMT) is a complex event that drives polar epithelial cells transform from adherent cells to motile mesenchymal cells, in which are involved immune cells and stroma cells.… Click to show full abstract

Background Epithelial-mesenchymal transition (EMT) is a complex event that drives polar epithelial cells transform from adherent cells to motile mesenchymal cells, in which are involved immune cells and stroma cells. EMT plays crucial roles in migration and invasion of endometriosis. The interaction of endometrial implants with the surrounding peritoneal micro-environment probably affects the development of peritoneal endometriosis. To date, very few studies have been carried out on peritoneal endometriosis sub-type classification and micro-environment analysis based on EMT. The purpose of this study is to investigate the potential application of EMT-based classification in precise diagnosis and treatment of peritoneal endometriosis. Method Based on EMT hallmark genes, 76 peritoneal endometriosis samples were classified into two clusters by consistent cluster classification. EMT scores, which calculated by Z score of 8 epithelial cell marker genes and 8 mesenchymal cell marker genes, were compared in two clusters. Then, immune scores and the abundances of corresponding immune cells, stroma scores and the abundances of corresponding stroma cells were analyzed by the “xCell” package. Futhermore, a diagnostic model was constructed based on 9 diagnostic markers which related to immune score and stroma score by Lasso-Logistic regression analysis. Finally, based on EMT classification, a total of 8 targeted drugs against two clusters were screened out by drug susceptibility analysis via “pRRophetic” package. Results Hallmark epithelial-mesenchymal transition was the mainly enriched pathway of differentially expressed genes between peritoneal endometriosis tissues and endometrium tissues. Compared with cluster 2, EMT score and the abundances of most infiltrating stroma cell were significantly higher, while the abundances of most infiltrating immune cells were dramatically less. The diagnostic model could accurately distinguish cluster 1 from cluster 2. Pathway analysis showed drug candidates targeting cluster 1 mainly act on the IGF-1 signaling pathway, and drug candidates targeting cluster 2 mainly block the EGFR signaling pathway. Conclusion In peritoneal endometriosis, EMT was probably promoted by stroma cell infiltration and inhibited by immune cell infiltration. Besides, our study highlighted the potential uses of the EMT classification in the precise diagnosis and treatment of peritoneal endometriosis.

Keywords: endometriosis; classification; cluster; analysis; emt; peritoneal endometriosis

Journal Title: Frontiers in Endocrinology
Year Published: 2022

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