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PPIC, EMP3 and CHI3L1 Are Novel Prognostic Markers for High Grade Glioma
Current treatment methods for patients diagnosed with gliomas have shown limited success. This is partly due to the lack of prognostic genes available to accurately predict disease outcomes. The aim of this study was to investigate novel prognostic genes based on the molecular profile of tumor sampl...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5133809/ https://www.ncbi.nlm.nih.gov/pubmed/27801851 http://dx.doi.org/10.3390/ijms17111808 |
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author | Gao, Yuan-Feng Zhu, Tao Mao, Chen-Xue Liu, Zhi-Xiong Wang, Zhi-Bin Mao, Xiao-Yuan Li, Ling Yin, Ji-Ye Zhou, Hong-Hao Liu, Zhao-Qian |
author_facet | Gao, Yuan-Feng Zhu, Tao Mao, Chen-Xue Liu, Zhi-Xiong Wang, Zhi-Bin Mao, Xiao-Yuan Li, Ling Yin, Ji-Ye Zhou, Hong-Hao Liu, Zhao-Qian |
author_sort | Gao, Yuan-Feng |
collection | PubMed |
description | Current treatment methods for patients diagnosed with gliomas have shown limited success. This is partly due to the lack of prognostic genes available to accurately predict disease outcomes. The aim of this study was to investigate novel prognostic genes based on the molecular profile of tumor samples and their correlation with clinical parameters. In the current study, microarray data (GSE4412 and GSE7696) downloaded from Gene Expression Omnibus were used to identify differentially expressed prognostic genes (DEPGs) by significant analysis of microarray (SAM) between long-term survivors (>2 years) and short-term survivors (≤2 years). DEPGs generated from these two datasets were intersected to obtain a list of common DEPGs. The expression of a subset of common DEPGs was then independently validated by real-time reverse transcription quantitative PCR (qPCR). Survival value of the common DEPGs was validated using known survival data from the GSE4412 and TCGA dataset. After intersecting DEPGs generated from the above two datasets, three genes were identified which may potentially be used to determine glioma patient prognosis. Independent validation with glioma patients tissue (n = 70) and normal brain tissue (n = 19) found PPIC, EMP3 and CHI3L1 were up-regulated in glioma tissue. Survival value validation showed that the three genes correlated with patient survival by Kaplan-Meir analysis, including grades, age and therapy. |
format | Online Article Text |
id | pubmed-5133809 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-51338092016-12-12 PPIC, EMP3 and CHI3L1 Are Novel Prognostic Markers for High Grade Glioma Gao, Yuan-Feng Zhu, Tao Mao, Chen-Xue Liu, Zhi-Xiong Wang, Zhi-Bin Mao, Xiao-Yuan Li, Ling Yin, Ji-Ye Zhou, Hong-Hao Liu, Zhao-Qian Int J Mol Sci Article Current treatment methods for patients diagnosed with gliomas have shown limited success. This is partly due to the lack of prognostic genes available to accurately predict disease outcomes. The aim of this study was to investigate novel prognostic genes based on the molecular profile of tumor samples and their correlation with clinical parameters. In the current study, microarray data (GSE4412 and GSE7696) downloaded from Gene Expression Omnibus were used to identify differentially expressed prognostic genes (DEPGs) by significant analysis of microarray (SAM) between long-term survivors (>2 years) and short-term survivors (≤2 years). DEPGs generated from these two datasets were intersected to obtain a list of common DEPGs. The expression of a subset of common DEPGs was then independently validated by real-time reverse transcription quantitative PCR (qPCR). Survival value of the common DEPGs was validated using known survival data from the GSE4412 and TCGA dataset. After intersecting DEPGs generated from the above two datasets, three genes were identified which may potentially be used to determine glioma patient prognosis. Independent validation with glioma patients tissue (n = 70) and normal brain tissue (n = 19) found PPIC, EMP3 and CHI3L1 were up-regulated in glioma tissue. Survival value validation showed that the three genes correlated with patient survival by Kaplan-Meir analysis, including grades, age and therapy. MDPI 2016-10-28 /pmc/articles/PMC5133809/ /pubmed/27801851 http://dx.doi.org/10.3390/ijms17111808 Text en © 2016 by the authors; 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 (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Gao, Yuan-Feng Zhu, Tao Mao, Chen-Xue Liu, Zhi-Xiong Wang, Zhi-Bin Mao, Xiao-Yuan Li, Ling Yin, Ji-Ye Zhou, Hong-Hao Liu, Zhao-Qian PPIC, EMP3 and CHI3L1 Are Novel Prognostic Markers for High Grade Glioma |
title | PPIC, EMP3 and CHI3L1 Are Novel Prognostic Markers for High Grade Glioma |
title_full | PPIC, EMP3 and CHI3L1 Are Novel Prognostic Markers for High Grade Glioma |
title_fullStr | PPIC, EMP3 and CHI3L1 Are Novel Prognostic Markers for High Grade Glioma |
title_full_unstemmed | PPIC, EMP3 and CHI3L1 Are Novel Prognostic Markers for High Grade Glioma |
title_short | PPIC, EMP3 and CHI3L1 Are Novel Prognostic Markers for High Grade Glioma |
title_sort | ppic, emp3 and chi3l1 are novel prognostic markers for high grade glioma |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5133809/ https://www.ncbi.nlm.nih.gov/pubmed/27801851 http://dx.doi.org/10.3390/ijms17111808 |
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