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BioMed Research International
Volume 2017 (2017), Article ID 7653101, 7 pages
https://doi.org/10.1155/2017/7653101
Research Article

Prediction and Analysis of Key Genes in Glioblastoma Based on Bioinformatics

1Department of Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, China
2Department of Neurosurgery, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510665, China
3Department of General Surgery, Shanghai Ninth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200011, China

Correspondence should be addressed to Haizhong Huo and Ye Song

Received 1 September 2016; Accepted 21 November 2016; Published 16 January 2017

Academic Editor: Jens Schittenhelm

Copyright © 2017 Hao Long et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Understanding the mechanisms of glioblastoma at the molecular and structural level is not only interesting for basic science but also valuable for biotechnological application, such as the clinical treatment. In the present study, bioinformatics analysis was performed to reveal and identify the key genes of glioblastoma multiforme (GBM). The results obtained in the present study signified the importance of some genes, such as COL3A1, FN1, and MMP9, for glioblastoma. Based on the selected genes, a prediction model was built, which achieved 94.4% prediction accuracy. These findings might provide more insights into the genetic basis of glioblastoma.