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A Novel Three-LncRNA Signature Predicting Tumor Recurrence in Nonfunctioning Pituitary Adenomas

The nonfunctioning pituitary adenoma (NFPA) recurrence rate is relatively high after surgical resection. Here, we constructed effective long noncoding RNA (lncRNA) signatures to predict NFPA prognosis. LncRNAs expression microarray sequencing profiles were obtained from 66 NFPAs. Sixty-six patients...

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Autores principales: Cheng, Sen, Guo, Jing, Wang, Dawei, Fang, Qiuyue, Liu, Yulou, Xie, Weiyan, Zhang, Yazhuo, Li, Chuzhong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8564111/
https://www.ncbi.nlm.nih.gov/pubmed/34745223
http://dx.doi.org/10.3389/fgene.2021.754503
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author Cheng, Sen
Guo, Jing
Wang, Dawei
Fang, Qiuyue
Liu, Yulou
Xie, Weiyan
Zhang, Yazhuo
Li, Chuzhong
author_facet Cheng, Sen
Guo, Jing
Wang, Dawei
Fang, Qiuyue
Liu, Yulou
Xie, Weiyan
Zhang, Yazhuo
Li, Chuzhong
author_sort Cheng, Sen
collection PubMed
description The nonfunctioning pituitary adenoma (NFPA) recurrence rate is relatively high after surgical resection. Here, we constructed effective long noncoding RNA (lncRNA) signatures to predict NFPA prognosis. LncRNAs expression microarray sequencing profiles were obtained from 66 NFPAs. Sixty-six patients were randomly separated into a training (n = 33) and test group (n = 33). Univariable Cox regression and a machine learning algorithm was used to filter lncRNAs. Time-dependent receiver operating characteristic (ROC) analysis was performed to improve the prediction signature. Three lncRNAs (LOC101927765, RP11-23N2.4 and RP4-533D7.4) were included in a prognostic signature with high prediction accuracy for tumor recurrence, which had the largest area under ROC curve (AUC) value in the training/test group (AUC = 0.87/0.73). The predictive ability of the signature was validated by Kaplan-Meier survival analysis. A signature-based risk score model divied patients into two risk group, and the recurrence-free survival rates of the groups were significantly different (log-rank p < 0.001). In addition, the ROC analysis showed that the lncRNA signature predictive ability was significantly better than that of age in the training/testing/entire group (AUC = 0.87/0.726/0.798 vs. AUC = 0.683/0.676/0.679). We constructed and verified a three-lncRNA signature predictive of recurrence, suggesting potential therapeutic targets for NFPA.
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spelling pubmed-85641112021-11-04 A Novel Three-LncRNA Signature Predicting Tumor Recurrence in Nonfunctioning Pituitary Adenomas Cheng, Sen Guo, Jing Wang, Dawei Fang, Qiuyue Liu, Yulou Xie, Weiyan Zhang, Yazhuo Li, Chuzhong Front Genet Genetics The nonfunctioning pituitary adenoma (NFPA) recurrence rate is relatively high after surgical resection. Here, we constructed effective long noncoding RNA (lncRNA) signatures to predict NFPA prognosis. LncRNAs expression microarray sequencing profiles were obtained from 66 NFPAs. Sixty-six patients were randomly separated into a training (n = 33) and test group (n = 33). Univariable Cox regression and a machine learning algorithm was used to filter lncRNAs. Time-dependent receiver operating characteristic (ROC) analysis was performed to improve the prediction signature. Three lncRNAs (LOC101927765, RP11-23N2.4 and RP4-533D7.4) were included in a prognostic signature with high prediction accuracy for tumor recurrence, which had the largest area under ROC curve (AUC) value in the training/test group (AUC = 0.87/0.73). The predictive ability of the signature was validated by Kaplan-Meier survival analysis. A signature-based risk score model divied patients into two risk group, and the recurrence-free survival rates of the groups were significantly different (log-rank p < 0.001). In addition, the ROC analysis showed that the lncRNA signature predictive ability was significantly better than that of age in the training/testing/entire group (AUC = 0.87/0.726/0.798 vs. AUC = 0.683/0.676/0.679). We constructed and verified a three-lncRNA signature predictive of recurrence, suggesting potential therapeutic targets for NFPA. Frontiers Media S.A. 2021-10-20 /pmc/articles/PMC8564111/ /pubmed/34745223 http://dx.doi.org/10.3389/fgene.2021.754503 Text en Copyright © 2021 Cheng, Guo, Wang, Fang, Liu, Xie, Zhang and Li. 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 Genetics
Cheng, Sen
Guo, Jing
Wang, Dawei
Fang, Qiuyue
Liu, Yulou
Xie, Weiyan
Zhang, Yazhuo
Li, Chuzhong
A Novel Three-LncRNA Signature Predicting Tumor Recurrence in Nonfunctioning Pituitary Adenomas
title A Novel Three-LncRNA Signature Predicting Tumor Recurrence in Nonfunctioning Pituitary Adenomas
title_full A Novel Three-LncRNA Signature Predicting Tumor Recurrence in Nonfunctioning Pituitary Adenomas
title_fullStr A Novel Three-LncRNA Signature Predicting Tumor Recurrence in Nonfunctioning Pituitary Adenomas
title_full_unstemmed A Novel Three-LncRNA Signature Predicting Tumor Recurrence in Nonfunctioning Pituitary Adenomas
title_short A Novel Three-LncRNA Signature Predicting Tumor Recurrence in Nonfunctioning Pituitary Adenomas
title_sort novel three-lncrna signature predicting tumor recurrence in nonfunctioning pituitary adenomas
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8564111/
https://www.ncbi.nlm.nih.gov/pubmed/34745223
http://dx.doi.org/10.3389/fgene.2021.754503
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