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An EMT-related genes signature as a prognostic biomarker for patients with endometrial cancer

BACKGROUND: The epithelial-mesenchymal transition (EMT) plays an indispensable role in the development and progression of Endometrial cancer (EC). Nevertheless, little evidence is reported to uncover the functionality and application of EMT-related molecules in the prognosis of EC. This study aims t...

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Autores principales: Yu, Yonghui, Zhang, Yiwen, Li, Zhi, Dong, Yongshun, Huang, Hongmei, Yang, Binyao, Zhao, Eryong, Chen, Yongxiu, Yang, Lei, Lu, Jiachun, Qiu, Fuman
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10506329/
https://www.ncbi.nlm.nih.gov/pubmed/37723477
http://dx.doi.org/10.1186/s12885-023-11358-4
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author Yu, Yonghui
Zhang, Yiwen
Li, Zhi
Dong, Yongshun
Huang, Hongmei
Yang, Binyao
Zhao, Eryong
Chen, Yongxiu
Yang, Lei
Lu, Jiachun
Qiu, Fuman
author_facet Yu, Yonghui
Zhang, Yiwen
Li, Zhi
Dong, Yongshun
Huang, Hongmei
Yang, Binyao
Zhao, Eryong
Chen, Yongxiu
Yang, Lei
Lu, Jiachun
Qiu, Fuman
author_sort Yu, Yonghui
collection PubMed
description BACKGROUND: The epithelial-mesenchymal transition (EMT) plays an indispensable role in the development and progression of Endometrial cancer (EC). Nevertheless, little evidence is reported to uncover the functionality and application of EMT-related molecules in the prognosis of EC. This study aims to develop novel molecular markers for prognosis prediction in patients with EC. METHODS: RNA sequencing profiles of EC patients obtained from The Cancer Genome Atlas (TCGA) database were used to screen differential expression genes (DEGs) between tumors and normal tissues. The Cox regression model with the LASSO method was utilized to identify survival-related DEGs and to establish a prognostic signature whose performance was evaluated by Kaplan–Meier curve, receiver operating characteristic (ROC) and calibration curve. Eventually, functional enrichment analysis and cellular experiments were performed to reveal the roles of prognosis-related genes in EC progression. RESULTS: A total of 540 EMT-related DEGs in EC were screened, and subsequently a four-gene risk signature comprising SIRT2, SIX1, CDKN2A and PGR was established to predict overall survival of EC. This risk signature could serve as a meaningfully independent indicator for EC prognosis via multivariate Cox regression (HR = 2.002, 95%CI = 1.433–2.798; P < 0.001). The nomogram integrating the risk signature and clinical characteristics exhibited robust validity and performance at predicting EC overall survival indicated by ROC and calibration curve. Functional enrichment analysis revealed that the EMT-related genes risk signature was associated with extracellular matrix organization, mesenchymal development and cellular component morphogenesis, suggesting its possible relevance to epithelial-mesenchymal transition and cancer progression. Functionally, we demonstrated that the silencing of SIX1, SIRT2 and CDKN2A expression could accelerate the migratory and invasive capacities of tumor cells, whereas the downregulation of PGR dramatically inhibited cancer cells migration and invasion. CONCLUSIONS: Altogether, a novel four-EMT-related genes signature was a potential biomarker for EC prognosis. These findings might help to ameliorate the individualized prognostication and therapeutic treatment of EC patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-023-11358-4.
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spelling pubmed-105063292023-09-19 An EMT-related genes signature as a prognostic biomarker for patients with endometrial cancer Yu, Yonghui Zhang, Yiwen Li, Zhi Dong, Yongshun Huang, Hongmei Yang, Binyao Zhao, Eryong Chen, Yongxiu Yang, Lei Lu, Jiachun Qiu, Fuman BMC Cancer Research BACKGROUND: The epithelial-mesenchymal transition (EMT) plays an indispensable role in the development and progression of Endometrial cancer (EC). Nevertheless, little evidence is reported to uncover the functionality and application of EMT-related molecules in the prognosis of EC. This study aims to develop novel molecular markers for prognosis prediction in patients with EC. METHODS: RNA sequencing profiles of EC patients obtained from The Cancer Genome Atlas (TCGA) database were used to screen differential expression genes (DEGs) between tumors and normal tissues. The Cox regression model with the LASSO method was utilized to identify survival-related DEGs and to establish a prognostic signature whose performance was evaluated by Kaplan–Meier curve, receiver operating characteristic (ROC) and calibration curve. Eventually, functional enrichment analysis and cellular experiments were performed to reveal the roles of prognosis-related genes in EC progression. RESULTS: A total of 540 EMT-related DEGs in EC were screened, and subsequently a four-gene risk signature comprising SIRT2, SIX1, CDKN2A and PGR was established to predict overall survival of EC. This risk signature could serve as a meaningfully independent indicator for EC prognosis via multivariate Cox regression (HR = 2.002, 95%CI = 1.433–2.798; P < 0.001). The nomogram integrating the risk signature and clinical characteristics exhibited robust validity and performance at predicting EC overall survival indicated by ROC and calibration curve. Functional enrichment analysis revealed that the EMT-related genes risk signature was associated with extracellular matrix organization, mesenchymal development and cellular component morphogenesis, suggesting its possible relevance to epithelial-mesenchymal transition and cancer progression. Functionally, we demonstrated that the silencing of SIX1, SIRT2 and CDKN2A expression could accelerate the migratory and invasive capacities of tumor cells, whereas the downregulation of PGR dramatically inhibited cancer cells migration and invasion. CONCLUSIONS: Altogether, a novel four-EMT-related genes signature was a potential biomarker for EC prognosis. These findings might help to ameliorate the individualized prognostication and therapeutic treatment of EC patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-023-11358-4. BioMed Central 2023-09-18 /pmc/articles/PMC10506329/ /pubmed/37723477 http://dx.doi.org/10.1186/s12885-023-11358-4 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Yu, Yonghui
Zhang, Yiwen
Li, Zhi
Dong, Yongshun
Huang, Hongmei
Yang, Binyao
Zhao, Eryong
Chen, Yongxiu
Yang, Lei
Lu, Jiachun
Qiu, Fuman
An EMT-related genes signature as a prognostic biomarker for patients with endometrial cancer
title An EMT-related genes signature as a prognostic biomarker for patients with endometrial cancer
title_full An EMT-related genes signature as a prognostic biomarker for patients with endometrial cancer
title_fullStr An EMT-related genes signature as a prognostic biomarker for patients with endometrial cancer
title_full_unstemmed An EMT-related genes signature as a prognostic biomarker for patients with endometrial cancer
title_short An EMT-related genes signature as a prognostic biomarker for patients with endometrial cancer
title_sort emt-related genes signature as a prognostic biomarker for patients with endometrial cancer
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10506329/
https://www.ncbi.nlm.nih.gov/pubmed/37723477
http://dx.doi.org/10.1186/s12885-023-11358-4
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