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A Potential Prognostic Gene Signature for Predicting Survival for Glioblastoma Patients
Joint Authors
Hou, Ziming
Yang, Jun
Wang, Hao
Liu, Dongyuan
Zhang, Hongbing
Source
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-03-26
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Objective.
This study aimed to screen prognostic gene signature of glioblastoma (GBM) to construct prognostic model.
Methods.
Based on the GBM information in the Cancer Genome Atlas (TCGA, training set), prognostic genes (Set X) were screened by Cox regression.
Then, the optimized prognostic gene signature (Set Y) was further screened by the Cox-Proportional Hazards (Cox-PH).
Next, two prognostic models were constructed: model A was based on the Set Y; model B was based on part of the Set X.
The samples were divided into low- and high-risk groups according to the median prognosis index (PI).
GBM datasets in Gene Expression Ominous (GEO, GSE13041) and Chinese Glioma Genome Atlas (CGGA) were used as the testing datasets to confirm the prognostic models constructed based on TCGA.
Results.
We identified that the prognostic 14-gene signature was significantly associated with the overall survival (OS) in the TCGA.
In model A, patients in high- and low-risk groups showed the significantly different OS (P = 7.47 × 10−9, area under curve (AUC) 0.995) and the prognostic ability were also confirmed in testing sets (P=0.0098 and 0.037).
The model B in training set was significant but failed in testing sets.
Conclusion.
The prognostic model which was constructed based on the prognostic 14-gene signature presented a high predictive ability for GBM.
The 14-gene signature may have clinical implications in the subclassification of GBM.
American Psychological Association (APA)
Hou, Ziming& Yang, Jun& Wang, Hao& Liu, Dongyuan& Zhang, Hongbing. 2019. A Potential Prognostic Gene Signature for Predicting Survival for Glioblastoma Patients. BioMed Research International،Vol. 2019, no. 2019, pp.1-9.
https://search.emarefa.net/detail/BIM-1128587
Modern Language Association (MLA)
Hou, Ziming…[et al.]. A Potential Prognostic Gene Signature for Predicting Survival for Glioblastoma Patients. BioMed Research International No. 2019 (2019), pp.1-9.
https://search.emarefa.net/detail/BIM-1128587
American Medical Association (AMA)
Hou, Ziming& Yang, Jun& Wang, Hao& Liu, Dongyuan& Zhang, Hongbing. A Potential Prognostic Gene Signature for Predicting Survival for Glioblastoma Patients. BioMed Research International. 2019. Vol. 2019, no. 2019, pp.1-9.
https://search.emarefa.net/detail/BIM-1128587
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1128587