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BioMed Research International
Volume 2018 (2018), Article ID 5238760, 12 pages
Research Article

Identification of Key Candidate Proteins and Pathways Associated with Temozolomide Resistance in Glioblastoma Based on Subcellular Proteomics and Bioinformatical Analysis

1Department of Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, China
2The Laboratory for Precision Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, China
3Department of Neurosurgery, The First Affiliated Hospital, Southwest Medical University, Luzhou, Sichuan 646000, China
4Department of General Intensive Care Unit, The Third Affiliated Hospital of Sun Yat-sen University of Medical Sciences, Guangzhou 510630, China
5Guangdong Provincial Key Laboratory of Molecular Oncologic Pathology, Guangzhou, Guangdong 510515, China
6School of Traditional Chinese Medicine, Southern Medical University, Guangzhou, Guangdong 510515, China
7Center for Clinical Medical Education, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, China
8Nanfang Glioma Center, Guangzhou, Guangdong 510515, China

Correspondence should be addressed to Song-tao Qi; moc.621@yyfnoatgnosiq and Ya-wei Liu; moc.361@kcudpmil

Received 10 October 2017; Revised 11 December 2017; Accepted 28 December 2017; Published 1 March 2018

Academic Editor: Steven De Vleeschouwer

Copyright © 2018 Guo-zhong Yi 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.


TMZ resistance remains one of the main reasons why treatment of glioblastoma (GBM) fails. In order to investigate the underlying proteins and pathways associated with TMZ resistance, we conducted a cytoplasmic proteome research of U87 cells treated with TMZ for 1 week, followed by differentially expressed proteins (DEPs) screening, KEGG pathway analysis, protein–protein interaction (PPI) network construction, and validation of key candidate proteins in TCGA dataset. A total of 161 DEPs including 65 upregulated proteins and 96 downregulated proteins were identified. Upregulated DEPs were mainly related to regulation in actin cytoskeleton, focal adhesion, and phagosome and PI3K-AKT signaling pathways which were consistent with our previous studies. Further, the most significant module consisted of 28 downregulated proteins that were filtered from the PPI network, and 9 proteins (DHX9, HNRNPR, RPL3, HNRNPA3, SF1, DDX5, EIF5B, BTF3, and RPL8) among them were identified as the key candidate proteins, which were significantly associated with prognosis of GBM patients and mainly involved in ribosome and spliceosome pathway. Taking the above into consideration, we firstly identified candidate proteins and pathways associated with TMZ resistance in GBM using proteomics and bioinformatic analysis, and these proteins could be potential biomarkers for prevention or prediction of TMZ resistance in the future.