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Identification of Potential Prognostic Genes for Neuroblastoma
Background and Objective: Neuroblastoma (NB), the most common pediatric solid tumor apart from brain tumor, is associated with dismal long-term survival. The aim of this study was to identify a gene signature to predict the prognosis of NB patients. Materials and Methods: GSE49710 dataset from the G...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6282001/ https://www.ncbi.nlm.nih.gov/pubmed/30555514 http://dx.doi.org/10.3389/fgene.2018.00589 |
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author | Zhong, Xiaodan Liu, Yuanning Liu, Haiming Zhang, Yutong Wang, Linyu Zhang, Hao |
author_facet | Zhong, Xiaodan Liu, Yuanning Liu, Haiming Zhang, Yutong Wang, Linyu Zhang, Hao |
author_sort | Zhong, Xiaodan |
collection | PubMed |
description | Background and Objective: Neuroblastoma (NB), the most common pediatric solid tumor apart from brain tumor, is associated with dismal long-term survival. The aim of this study was to identify a gene signature to predict the prognosis of NB patients. Materials and Methods: GSE49710 dataset from the Gene Expression Omnibus (GEO) database was downloaded and differentially expressed genes (DEGs) were analyzed using R package “limma” and SPSS software. The gene ontology (GO) and pathway enrichment analysis were established via DAVID database. Random forest (RF) and risk score model were used to pick out the gene signature in predicting the prognosis of NB patients. Simultaneously, the receiving operating characteristic (ROC) and Kaplan-Meier curve were plotted. GSE45480 and GSE16476 datasets were employed to validate the robustness of the gene signature. Results: A total of 131 DEGs were identified, which were mainly enriched in cancer-related pathways. Four genes (ERCC6L, AHCY, STK33, and NCAN) were selected as a gene signature, which was included in the top six important features in RF model, to predict the prognosis in NB patients, its area under the curve (AUC) could reach 0.86, and Cox regression analysis revealed that the 4-gene signature was an independent prognostic factor of overall survival and event-free survival. As well as in GSE16476. Additionally, the robustness of discriminating different groups of the 4-gene signature was verified to have a commendable performance in GSE45480 and GSE49710. Conclusion: The present study identified a gene-signature in predicting the prognosis in NB, which may provide novel prognostic markers, and some of the genes may be as treatment targets according to biological experiments in the future. |
format | Online Article Text |
id | pubmed-6282001 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-62820012018-12-14 Identification of Potential Prognostic Genes for Neuroblastoma Zhong, Xiaodan Liu, Yuanning Liu, Haiming Zhang, Yutong Wang, Linyu Zhang, Hao Front Genet Genetics Background and Objective: Neuroblastoma (NB), the most common pediatric solid tumor apart from brain tumor, is associated with dismal long-term survival. The aim of this study was to identify a gene signature to predict the prognosis of NB patients. Materials and Methods: GSE49710 dataset from the Gene Expression Omnibus (GEO) database was downloaded and differentially expressed genes (DEGs) were analyzed using R package “limma” and SPSS software. The gene ontology (GO) and pathway enrichment analysis were established via DAVID database. Random forest (RF) and risk score model were used to pick out the gene signature in predicting the prognosis of NB patients. Simultaneously, the receiving operating characteristic (ROC) and Kaplan-Meier curve were plotted. GSE45480 and GSE16476 datasets were employed to validate the robustness of the gene signature. Results: A total of 131 DEGs were identified, which were mainly enriched in cancer-related pathways. Four genes (ERCC6L, AHCY, STK33, and NCAN) were selected as a gene signature, which was included in the top six important features in RF model, to predict the prognosis in NB patients, its area under the curve (AUC) could reach 0.86, and Cox regression analysis revealed that the 4-gene signature was an independent prognostic factor of overall survival and event-free survival. As well as in GSE16476. Additionally, the robustness of discriminating different groups of the 4-gene signature was verified to have a commendable performance in GSE45480 and GSE49710. Conclusion: The present study identified a gene-signature in predicting the prognosis in NB, which may provide novel prognostic markers, and some of the genes may be as treatment targets according to biological experiments in the future. Frontiers Media S.A. 2018-11-29 /pmc/articles/PMC6282001/ /pubmed/30555514 http://dx.doi.org/10.3389/fgene.2018.00589 Text en Copyright © 2018 Zhong, Liu, Liu, Zhang, Wang and Zhang. http://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 Zhong, Xiaodan Liu, Yuanning Liu, Haiming Zhang, Yutong Wang, Linyu Zhang, Hao Identification of Potential Prognostic Genes for Neuroblastoma |
title | Identification of Potential Prognostic Genes for Neuroblastoma |
title_full | Identification of Potential Prognostic Genes for Neuroblastoma |
title_fullStr | Identification of Potential Prognostic Genes for Neuroblastoma |
title_full_unstemmed | Identification of Potential Prognostic Genes for Neuroblastoma |
title_short | Identification of Potential Prognostic Genes for Neuroblastoma |
title_sort | identification of potential prognostic genes for neuroblastoma |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6282001/ https://www.ncbi.nlm.nih.gov/pubmed/30555514 http://dx.doi.org/10.3389/fgene.2018.00589 |
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