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A Risk Score Model Incorporating Three m6A RNA Methylation Regulators and a Related Network of miRNAs-m6A Regulators-m6A Target Genes to Predict the Prognosis of Patients With Ovarian Cancer
Ovarian cancer (OC) is the leading cause of cancer-related death among all gynecological tumors. N6-methyladenosine (m6A)-related regulators play essential roles in various tumors, including OC. However, the expression of m6A RNA methylation regulators and the related regulatory network in OC and th...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8495156/ https://www.ncbi.nlm.nih.gov/pubmed/34631700 http://dx.doi.org/10.3389/fcell.2021.703969 |
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author | Li, Qian Ren, Chen-Chen Chen, Yan-Nan Yang, Li Zhang, Feng Wang, Bao-Jin Zhu, Yuan-Hang Li, Fei-Yan Yang, Jun Zhang, Zhen-An |
author_facet | Li, Qian Ren, Chen-Chen Chen, Yan-Nan Yang, Li Zhang, Feng Wang, Bao-Jin Zhu, Yuan-Hang Li, Fei-Yan Yang, Jun Zhang, Zhen-An |
author_sort | Li, Qian |
collection | PubMed |
description | Ovarian cancer (OC) is the leading cause of cancer-related death among all gynecological tumors. N6-methyladenosine (m6A)-related regulators play essential roles in various tumors, including OC. However, the expression of m6A RNA methylation regulators and the related regulatory network in OC and their correlations with prognosis remain largely unknown. In the current study, we obtained the genome datasets of OC from GDC and GTEx database and analyzed the mRNA levels of 21 key m6A regulators in OC and normal human ovarian tissues. The expression levels of 7 m6A regulators were lower in both the OC tissues and the high-stage group. Notably, the 5-year survival rate of patients with OC presenting low VIRMA expression or high HNRNPA2B1 expression was higher than that of the controls. Next, a risk score model based on the three selected m6A regulators (VIRMA, IGF2BP1, and HNRNPA2B1) was built by performing a LASSO regression analysis, and the moderate accuracy of the risk score model to predict the prognosis of patients with OC was examined by performing ROC curve, nomogram, and univariate and multivariate Cox regression analyses. In addition, a regulatory network of miRNAs-m6A regulators-m6A target genes, including 2 miRNAs, 3 m6A regulators, and 47 mRNAs, was constructed, and one of the pathways, namely, miR-196b-5p-IGF2BP1-PTEN, was initially validated based on bioinformatic analysis and assay verification. These results demonstrated that the risk score model composed of three m6A RNA methylation regulators and the related network of miRNAs-m6A regulators-m6A target genes is valuable for predicting the prognosis of patients with OC, and these molecules may serve as potential biomarkers or therapeutic targets in the future. |
format | Online Article Text |
id | pubmed-8495156 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-84951562021-10-08 A Risk Score Model Incorporating Three m6A RNA Methylation Regulators and a Related Network of miRNAs-m6A Regulators-m6A Target Genes to Predict the Prognosis of Patients With Ovarian Cancer Li, Qian Ren, Chen-Chen Chen, Yan-Nan Yang, Li Zhang, Feng Wang, Bao-Jin Zhu, Yuan-Hang Li, Fei-Yan Yang, Jun Zhang, Zhen-An Front Cell Dev Biol Cell and Developmental Biology Ovarian cancer (OC) is the leading cause of cancer-related death among all gynecological tumors. N6-methyladenosine (m6A)-related regulators play essential roles in various tumors, including OC. However, the expression of m6A RNA methylation regulators and the related regulatory network in OC and their correlations with prognosis remain largely unknown. In the current study, we obtained the genome datasets of OC from GDC and GTEx database and analyzed the mRNA levels of 21 key m6A regulators in OC and normal human ovarian tissues. The expression levels of 7 m6A regulators were lower in both the OC tissues and the high-stage group. Notably, the 5-year survival rate of patients with OC presenting low VIRMA expression or high HNRNPA2B1 expression was higher than that of the controls. Next, a risk score model based on the three selected m6A regulators (VIRMA, IGF2BP1, and HNRNPA2B1) was built by performing a LASSO regression analysis, and the moderate accuracy of the risk score model to predict the prognosis of patients with OC was examined by performing ROC curve, nomogram, and univariate and multivariate Cox regression analyses. In addition, a regulatory network of miRNAs-m6A regulators-m6A target genes, including 2 miRNAs, 3 m6A regulators, and 47 mRNAs, was constructed, and one of the pathways, namely, miR-196b-5p-IGF2BP1-PTEN, was initially validated based on bioinformatic analysis and assay verification. These results demonstrated that the risk score model composed of three m6A RNA methylation regulators and the related network of miRNAs-m6A regulators-m6A target genes is valuable for predicting the prognosis of patients with OC, and these molecules may serve as potential biomarkers or therapeutic targets in the future. Frontiers Media S.A. 2021-09-23 /pmc/articles/PMC8495156/ /pubmed/34631700 http://dx.doi.org/10.3389/fcell.2021.703969 Text en Copyright © 2021 Li, Ren, Chen, Yang, Zhang, Wang, Zhu, Li, Yang and Zhang. 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 | Cell and Developmental Biology Li, Qian Ren, Chen-Chen Chen, Yan-Nan Yang, Li Zhang, Feng Wang, Bao-Jin Zhu, Yuan-Hang Li, Fei-Yan Yang, Jun Zhang, Zhen-An A Risk Score Model Incorporating Three m6A RNA Methylation Regulators and a Related Network of miRNAs-m6A Regulators-m6A Target Genes to Predict the Prognosis of Patients With Ovarian Cancer |
title | A Risk Score Model Incorporating Three m6A RNA Methylation Regulators and a Related Network of miRNAs-m6A Regulators-m6A Target Genes to Predict the Prognosis of Patients With Ovarian Cancer |
title_full | A Risk Score Model Incorporating Three m6A RNA Methylation Regulators and a Related Network of miRNAs-m6A Regulators-m6A Target Genes to Predict the Prognosis of Patients With Ovarian Cancer |
title_fullStr | A Risk Score Model Incorporating Three m6A RNA Methylation Regulators and a Related Network of miRNAs-m6A Regulators-m6A Target Genes to Predict the Prognosis of Patients With Ovarian Cancer |
title_full_unstemmed | A Risk Score Model Incorporating Three m6A RNA Methylation Regulators and a Related Network of miRNAs-m6A Regulators-m6A Target Genes to Predict the Prognosis of Patients With Ovarian Cancer |
title_short | A Risk Score Model Incorporating Three m6A RNA Methylation Regulators and a Related Network of miRNAs-m6A Regulators-m6A Target Genes to Predict the Prognosis of Patients With Ovarian Cancer |
title_sort | risk score model incorporating three m6a rna methylation regulators and a related network of mirnas-m6a regulators-m6a target genes to predict the prognosis of patients with ovarian cancer |
topic | Cell and Developmental Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8495156/ https://www.ncbi.nlm.nih.gov/pubmed/34631700 http://dx.doi.org/10.3389/fcell.2021.703969 |
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