Dataset Information

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

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.

SUBMITTER: Yi GZ

PROVIDER: S-EPMC5852899 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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

Yi Guo-Zhong GZ Xiang Wei W Feng Wen-Yan WY Chen Zi-Yang ZY Li Yao-Min YM Deng Sheng-Ze SZ Guo Man-Lan ML Zhao Liang L Sun Xue-Gang XG He Min-Yi MY Qi Song-Tao ST Liu Ya-Wei YW

BioMed research international 20180301

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 ...[more]

PMID: 29687002

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Project description:: Preeclampsia is a pregnancy-specific disorder characterized by the presence of hypertension with the onset of either proteinuria, maternal organ or uteroplacental dysfunction. Preeclampsia is one of the leading causes of maternal and fetal mortality and morbidity worldwide. However, the etiopathologies of preeclampsia are not fully understood. Many studies have indicated that genes are differentially expressed between normal and in the disease state. Hence, this study systematically searched the literature on human gene expression that was differentially expressed in preeclampsia. An electronic search was performed through 2019 through PubMed, Scopus, Ovid-Medline, and Gene Expression Omnibus where the following MeSH (Medical Subject Heading) terms were used and they had been specified as the primary focus of the articles: Gene, placenta, preeclampsia, and pregnancy in the title or abstract. We also found additional MeSH terms through Cochrane Library: Transcript, sequencing, and profiling. From 687 studies retrieved from the search, only original publications that had performed high throughput sequencing of human placental tissues that reported on differentially expressed genes in pregnancies with preeclampsia were included. Two reviewers independently scrutinized the titles and abstracts before examining the eligibility of studies that met the inclusion criteria. For each study, study design, sample size, sampling type, and method for gene analysis and gene were identified. The genes listed were further analyzed with the DAVID, STRING and Cytoscape MCODE. Three original research articles involving preeclampsia comprising the datasets in gene expression were included. By combining three studies together, 250 differentially expressed genes were produced at a significance setting of p < 0.05. We identified candidate genes: LEP, NRIP1, SASH1, and ZADHHC8P1. Through GO analysis, we found extracellular matrix organization as the highly significant enriched ontology in a group of upregulated genes and immune process in downregulated genes. Studies on a genetic level have the potential to provide new insights into the regulation and to widen the basis for identification of changes in the mechanism of preeclampsia. Integrated bioinformatics could identify differentially expressed genes which could be candidate genes and potential pathways in preeclampsia that may improve our understanding of the cause and underlying molecular mechanisms that could be used as potential biomarkers for risk stratification and treatment.

Dataset Information

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

Publications

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

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