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Identification of a 3-miRNA Signature Associated With the Prediction of Prognosis in Nasopharyngeal Carcinoma

Nasopharyngeal carcinoma (NPC) is a malignant tumor caused by an infection of the epithelial cells of the nasopharynx, which is highly metastatic and aggressive. Due to the deep anatomical site and atypical early symptoms, the majority of NPC patients are diagnosed at terminal stages. There is growi...

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Autores principales: Zhou, Jinhui, Zhang, Bo, Zhang, Xin, Wang, Chengyu, Xu, Yu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8828644/
https://www.ncbi.nlm.nih.gov/pubmed/35155213
http://dx.doi.org/10.3389/fonc.2021.823603
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author Zhou, Jinhui
Zhang, Bo
Zhang, Xin
Wang, Chengyu
Xu, Yu
author_facet Zhou, Jinhui
Zhang, Bo
Zhang, Xin
Wang, Chengyu
Xu, Yu
author_sort Zhou, Jinhui
collection PubMed
description Nasopharyngeal carcinoma (NPC) is a malignant tumor caused by an infection of the epithelial cells of the nasopharynx, which is highly metastatic and aggressive. Due to the deep anatomical site and atypical early symptoms, the majority of NPC patients are diagnosed at terminal stages. There is growing evidence that microRNAs offer options for early detection, accurate diagnosis, and prediction of malignancy treatment response. Therefore, the purpose of this article was to identify microRNAs that predict the prognosis of patients with NPC by integrating biological information analysis. In this study, we utilized the GSE36682 dataset rooted in the Gene Expression Omnibus (GEO) data bank, including 62 cases of NPC tissues and six cases of non-cancerous tissues. The miRNAs were subjected to weighted gene co-expression network analysis, and hub miRNAs were screened for differentially upregulated miRNAs from modules highly correlated with tumor progression. We took a lot of time to calculate the risk scores of miRNA markers for 62 NPC patients, and incidentally combined the clinical survival information of patients to finally identify the three key miRNAs, and then divided the patients into low- and high-risk groups. Kaplan-Meier curve analysis revealed that the overall survival of patients in the high-risk group was obviously shorter than that of the low-risk group. Subsequently, the target genes of the three miRNAs were predicted and analyzed for functional enrichment. In summary, a prognostic predictive risk model based on three miRNA profiles may increase prognostic predictive value and provide reference information for the precise treatment of nasopharyngeal carcinoma.
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spelling pubmed-88286442022-02-11 Identification of a 3-miRNA Signature Associated With the Prediction of Prognosis in Nasopharyngeal Carcinoma Zhou, Jinhui Zhang, Bo Zhang, Xin Wang, Chengyu Xu, Yu Front Oncol Oncology Nasopharyngeal carcinoma (NPC) is a malignant tumor caused by an infection of the epithelial cells of the nasopharynx, which is highly metastatic and aggressive. Due to the deep anatomical site and atypical early symptoms, the majority of NPC patients are diagnosed at terminal stages. There is growing evidence that microRNAs offer options for early detection, accurate diagnosis, and prediction of malignancy treatment response. Therefore, the purpose of this article was to identify microRNAs that predict the prognosis of patients with NPC by integrating biological information analysis. In this study, we utilized the GSE36682 dataset rooted in the Gene Expression Omnibus (GEO) data bank, including 62 cases of NPC tissues and six cases of non-cancerous tissues. The miRNAs were subjected to weighted gene co-expression network analysis, and hub miRNAs were screened for differentially upregulated miRNAs from modules highly correlated with tumor progression. We took a lot of time to calculate the risk scores of miRNA markers for 62 NPC patients, and incidentally combined the clinical survival information of patients to finally identify the three key miRNAs, and then divided the patients into low- and high-risk groups. Kaplan-Meier curve analysis revealed that the overall survival of patients in the high-risk group was obviously shorter than that of the low-risk group. Subsequently, the target genes of the three miRNAs were predicted and analyzed for functional enrichment. In summary, a prognostic predictive risk model based on three miRNA profiles may increase prognostic predictive value and provide reference information for the precise treatment of nasopharyngeal carcinoma. Frontiers Media S.A. 2022-01-27 /pmc/articles/PMC8828644/ /pubmed/35155213 http://dx.doi.org/10.3389/fonc.2021.823603 Text en Copyright © 2022 Zhou, Zhang, Zhang, Wang and Xu 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 Oncology
Zhou, Jinhui
Zhang, Bo
Zhang, Xin
Wang, Chengyu
Xu, Yu
Identification of a 3-miRNA Signature Associated With the Prediction of Prognosis in Nasopharyngeal Carcinoma
title Identification of a 3-miRNA Signature Associated With the Prediction of Prognosis in Nasopharyngeal Carcinoma
title_full Identification of a 3-miRNA Signature Associated With the Prediction of Prognosis in Nasopharyngeal Carcinoma
title_fullStr Identification of a 3-miRNA Signature Associated With the Prediction of Prognosis in Nasopharyngeal Carcinoma
title_full_unstemmed Identification of a 3-miRNA Signature Associated With the Prediction of Prognosis in Nasopharyngeal Carcinoma
title_short Identification of a 3-miRNA Signature Associated With the Prediction of Prognosis in Nasopharyngeal Carcinoma
title_sort identification of a 3-mirna signature associated with the prediction of prognosis in nasopharyngeal carcinoma
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8828644/
https://www.ncbi.nlm.nih.gov/pubmed/35155213
http://dx.doi.org/10.3389/fonc.2021.823603
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