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Construction of a miRNA-Based Nomogram Model to Predict the Prognosis of Endometrial Cancer
Objective: To investigate the differential expression of microRNA (miRNA) in patients with endometrial cancer and its relationship with prognosis and survival. Method: We used The Cancer Genome Atlas (TCGA) database to analyze differentially expressed miRNAs in endometrial cancer tissues and adjacen...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9318842/ https://www.ncbi.nlm.nih.gov/pubmed/35887651 http://dx.doi.org/10.3390/jpm12071154 |
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author | Ni, Leyi Tang, Chengyun Wang, Yuning Wan, Jiaming Charles, Morgan G. Zhang, Zilong Li, Chen Zeng, Ruijie Jin, Yiyao Song, Penghao Wei, Ming Li, Bocen Zhang, Jin Wu, Zhenghao |
author_facet | Ni, Leyi Tang, Chengyun Wang, Yuning Wan, Jiaming Charles, Morgan G. Zhang, Zilong Li, Chen Zeng, Ruijie Jin, Yiyao Song, Penghao Wei, Ming Li, Bocen Zhang, Jin Wu, Zhenghao |
author_sort | Ni, Leyi |
collection | PubMed |
description | Objective: To investigate the differential expression of microRNA (miRNA) in patients with endometrial cancer and its relationship with prognosis and survival. Method: We used The Cancer Genome Atlas (TCGA) database to analyze differentially expressed miRNAs in endometrial cancer tissues and adjacent normal tissues. In addition, we successfully screened out key microRNAs to build nomogram models for predicting prognosis and we performed survival analysis on the key miRNAs as well. Result: We identified 187 differentially expressed miRNAs, which includes 134 up-regulated miRNAs and 53 down-regulated miRNAs. Further univariate Cox regression analysis screened out 47 significantly differentially expressed miRNAs and selected 12 miRNAs from which the prognostic nomogram model for ECA patients by LASSO analysis was constructed. Survival analysis showed that high expression of hsa-mir-138-2, hsa-mir-548f-1, hsa-mir-934, hsa-mir-940, and hsa-mir-4758 as well as low-expression of hsa-mir-146a, hsa-mir-3170, hsa-mir-3614, hsa-mir-3616, and hsa-mir-4687 are associated with poor prognosis in EC patients. However, significant correlations between the expressions levels of has-mir-876 and hsa-mir-1269a and patients’ prognosis are not found. Conclusion: Our study found that 12 significantly differentially expressed miRNAs might promote the proliferation, invasion, and metastasis of cancer cells by regulating the expression of upstream target genes, thereby affecting the prognosis of patients with endometrial cancer. |
format | Online Article Text |
id | pubmed-9318842 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-93188422022-07-27 Construction of a miRNA-Based Nomogram Model to Predict the Prognosis of Endometrial Cancer Ni, Leyi Tang, Chengyun Wang, Yuning Wan, Jiaming Charles, Morgan G. Zhang, Zilong Li, Chen Zeng, Ruijie Jin, Yiyao Song, Penghao Wei, Ming Li, Bocen Zhang, Jin Wu, Zhenghao J Pers Med Article Objective: To investigate the differential expression of microRNA (miRNA) in patients with endometrial cancer and its relationship with prognosis and survival. Method: We used The Cancer Genome Atlas (TCGA) database to analyze differentially expressed miRNAs in endometrial cancer tissues and adjacent normal tissues. In addition, we successfully screened out key microRNAs to build nomogram models for predicting prognosis and we performed survival analysis on the key miRNAs as well. Result: We identified 187 differentially expressed miRNAs, which includes 134 up-regulated miRNAs and 53 down-regulated miRNAs. Further univariate Cox regression analysis screened out 47 significantly differentially expressed miRNAs and selected 12 miRNAs from which the prognostic nomogram model for ECA patients by LASSO analysis was constructed. Survival analysis showed that high expression of hsa-mir-138-2, hsa-mir-548f-1, hsa-mir-934, hsa-mir-940, and hsa-mir-4758 as well as low-expression of hsa-mir-146a, hsa-mir-3170, hsa-mir-3614, hsa-mir-3616, and hsa-mir-4687 are associated with poor prognosis in EC patients. However, significant correlations between the expressions levels of has-mir-876 and hsa-mir-1269a and patients’ prognosis are not found. Conclusion: Our study found that 12 significantly differentially expressed miRNAs might promote the proliferation, invasion, and metastasis of cancer cells by regulating the expression of upstream target genes, thereby affecting the prognosis of patients with endometrial cancer. MDPI 2022-07-17 /pmc/articles/PMC9318842/ /pubmed/35887651 http://dx.doi.org/10.3390/jpm12071154 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Ni, Leyi Tang, Chengyun Wang, Yuning Wan, Jiaming Charles, Morgan G. Zhang, Zilong Li, Chen Zeng, Ruijie Jin, Yiyao Song, Penghao Wei, Ming Li, Bocen Zhang, Jin Wu, Zhenghao Construction of a miRNA-Based Nomogram Model to Predict the Prognosis of Endometrial Cancer |
title | Construction of a miRNA-Based Nomogram Model to Predict the Prognosis of Endometrial Cancer |
title_full | Construction of a miRNA-Based Nomogram Model to Predict the Prognosis of Endometrial Cancer |
title_fullStr | Construction of a miRNA-Based Nomogram Model to Predict the Prognosis of Endometrial Cancer |
title_full_unstemmed | Construction of a miRNA-Based Nomogram Model to Predict the Prognosis of Endometrial Cancer |
title_short | Construction of a miRNA-Based Nomogram Model to Predict the Prognosis of Endometrial Cancer |
title_sort | construction of a mirna-based nomogram model to predict the prognosis of endometrial cancer |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9318842/ https://www.ncbi.nlm.nih.gov/pubmed/35887651 http://dx.doi.org/10.3390/jpm12071154 |
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