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Immune micro-environment and drug analysis of peritoneal endometriosis based on epithelial-mesenchymal transition classification
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 interactio...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9745086/ https://www.ncbi.nlm.nih.gov/pubmed/36523599 http://dx.doi.org/10.3389/fendo.2022.1035158 |
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author | Quan, Qingli Wu, Jiabao Yu, Meixing Tang, Jia |
author_facet | Quan, Qingli Wu, Jiabao Yu, Meixing Tang, Jia |
author_sort | Quan, Qingli |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9745086 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-97450862022-12-14 Immune micro-environment and drug analysis of peritoneal endometriosis based on epithelial-mesenchymal transition classification Quan, Qingli Wu, Jiabao Yu, Meixing Tang, Jia Front Endocrinol (Lausanne) Endocrinology 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. Frontiers Media S.A. 2022-11-29 /pmc/articles/PMC9745086/ /pubmed/36523599 http://dx.doi.org/10.3389/fendo.2022.1035158 Text en Copyright © 2022 Quan, Wu, Yu and Tang https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Endocrinology Quan, Qingli Wu, Jiabao Yu, Meixing Tang, Jia Immune micro-environment and drug analysis of peritoneal endometriosis based on epithelial-mesenchymal transition classification |
title | Immune micro-environment and drug analysis of peritoneal endometriosis based on epithelial-mesenchymal transition classification |
title_full | Immune micro-environment and drug analysis of peritoneal endometriosis based on epithelial-mesenchymal transition classification |
title_fullStr | Immune micro-environment and drug analysis of peritoneal endometriosis based on epithelial-mesenchymal transition classification |
title_full_unstemmed | Immune micro-environment and drug analysis of peritoneal endometriosis based on epithelial-mesenchymal transition classification |
title_short | Immune micro-environment and drug analysis of peritoneal endometriosis based on epithelial-mesenchymal transition classification |
title_sort | immune micro-environment and drug analysis of peritoneal endometriosis based on epithelial-mesenchymal transition classification |
topic | Endocrinology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9745086/ https://www.ncbi.nlm.nih.gov/pubmed/36523599 http://dx.doi.org/10.3389/fendo.2022.1035158 |
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