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Biomed Res Int. 2018 Mar 1;2018:5238760. doi: 10.1155/2018/5238760. eCollection 2018.

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

Author information

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

Abstract

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.

PMID:
29687002
PMCID:
PMC5852899
DOI:
10.1155/2018/5238760
[Indexed for MEDLINE]
Free PMC Article

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