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OSlgg: An Online Prognostic Biomarker Analysis Tool for Low-Grade Glioma
Glioma is the most frequent primary brain tumor that causes high mortality and morbidity with poor prognosis. There are four grades of gliomas, I to IV, among which grade II and III are low-grade glioma (LGG). Although less aggressive, LGG almost universally progresses to high-grade glioma and event...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7381343/ https://www.ncbi.nlm.nih.gov/pubmed/32775301 http://dx.doi.org/10.3389/fonc.2020.01097 |
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author | An, Yang Wang, Qiang Zhang, Lu Sun, Fengjie Zhang, Guosen Dong, Huan Li, Yingkun Peng, Yanyu Li, Haojie Zhu, Wan Ji, Shaoping Wang, Yunlong Guo, Xiangqian |
author_facet | An, Yang Wang, Qiang Zhang, Lu Sun, Fengjie Zhang, Guosen Dong, Huan Li, Yingkun Peng, Yanyu Li, Haojie Zhu, Wan Ji, Shaoping Wang, Yunlong Guo, Xiangqian |
author_sort | An, Yang |
collection | PubMed |
description | Glioma is the most frequent primary brain tumor that causes high mortality and morbidity with poor prognosis. There are four grades of gliomas, I to IV, among which grade II and III are low-grade glioma (LGG). Although less aggressive, LGG almost universally progresses to high-grade glioma and eventual causes death if lacking of intervention. Current LGG treatment mainly depends on surgical resection followed by radiotherapy and chemotherapy, but the survival rates of LGG patients are low. Therefore, it is necessary to use prognostic biomarkers to classify patients into subgroups with different risks and guide clinical managements. Using gene expression profiling and long-term follow-up data, we established an Online consensus Survival analysis tool for LGG named OSlgg. OSlgg is comprised of 720 LGG cases from two independent cohorts. To evaluate the prognostic potency of genes, OSlgg employs the Kaplan-Meier plot with hazard ratio and p value to assess the prognostic significance of genes of interest. The reliability of OSlgg was verified by analyzing 86 previously published prognostic biomarkers of LGG. Using OSlgg, we discovered two novel potential prognostic biomarkers (CD302 and FABP5) of LGG, and patients with the elevated expression of either CD302 or FABP5 present the unfavorable survival outcome. These two genes may be novel risk predictors for LGG patients after further validation. OSlgg is public and free to the users at http://bioinfo.henu.edu.cn/LGG/LGGList.jsp. |
format | Online Article Text |
id | pubmed-7381343 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-73813432020-08-06 OSlgg: An Online Prognostic Biomarker Analysis Tool for Low-Grade Glioma An, Yang Wang, Qiang Zhang, Lu Sun, Fengjie Zhang, Guosen Dong, Huan Li, Yingkun Peng, Yanyu Li, Haojie Zhu, Wan Ji, Shaoping Wang, Yunlong Guo, Xiangqian Front Oncol Oncology Glioma is the most frequent primary brain tumor that causes high mortality and morbidity with poor prognosis. There are four grades of gliomas, I to IV, among which grade II and III are low-grade glioma (LGG). Although less aggressive, LGG almost universally progresses to high-grade glioma and eventual causes death if lacking of intervention. Current LGG treatment mainly depends on surgical resection followed by radiotherapy and chemotherapy, but the survival rates of LGG patients are low. Therefore, it is necessary to use prognostic biomarkers to classify patients into subgroups with different risks and guide clinical managements. Using gene expression profiling and long-term follow-up data, we established an Online consensus Survival analysis tool for LGG named OSlgg. OSlgg is comprised of 720 LGG cases from two independent cohorts. To evaluate the prognostic potency of genes, OSlgg employs the Kaplan-Meier plot with hazard ratio and p value to assess the prognostic significance of genes of interest. The reliability of OSlgg was verified by analyzing 86 previously published prognostic biomarkers of LGG. Using OSlgg, we discovered two novel potential prognostic biomarkers (CD302 and FABP5) of LGG, and patients with the elevated expression of either CD302 or FABP5 present the unfavorable survival outcome. These two genes may be novel risk predictors for LGG patients after further validation. OSlgg is public and free to the users at http://bioinfo.henu.edu.cn/LGG/LGGList.jsp. Frontiers Media S.A. 2020-07-07 /pmc/articles/PMC7381343/ /pubmed/32775301 http://dx.doi.org/10.3389/fonc.2020.01097 Text en Copyright © 2020 An, Wang, Zhang, Sun, Zhang, Dong, Li, Peng, Li, Zhu, Ji, Wang and Guo. 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 | Oncology An, Yang Wang, Qiang Zhang, Lu Sun, Fengjie Zhang, Guosen Dong, Huan Li, Yingkun Peng, Yanyu Li, Haojie Zhu, Wan Ji, Shaoping Wang, Yunlong Guo, Xiangqian OSlgg: An Online Prognostic Biomarker Analysis Tool for Low-Grade Glioma |
title | OSlgg: An Online Prognostic Biomarker Analysis Tool for Low-Grade Glioma |
title_full | OSlgg: An Online Prognostic Biomarker Analysis Tool for Low-Grade Glioma |
title_fullStr | OSlgg: An Online Prognostic Biomarker Analysis Tool for Low-Grade Glioma |
title_full_unstemmed | OSlgg: An Online Prognostic Biomarker Analysis Tool for Low-Grade Glioma |
title_short | OSlgg: An Online Prognostic Biomarker Analysis Tool for Low-Grade Glioma |
title_sort | oslgg: an online prognostic biomarker analysis tool for low-grade glioma |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7381343/ https://www.ncbi.nlm.nih.gov/pubmed/32775301 http://dx.doi.org/10.3389/fonc.2020.01097 |
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