Identification of therapeutic targets for glioblastoma by network analysis.
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ABSTRACT:
SUBMITTER: Friedmann-Morvinski D
PROVIDER: S-EPMC4641815 | biostudies-literature | 2016 Feb
REPOSITORIES: biostudies-literature
Publications
Identification of therapeutic targets for glioblastoma by network analysis.
Friedmann-Morvinski D D Bhargava V V Gupta S S Verma I M IM Subramaniam S S
Oncogene 20150511 5
Glioblastoma can originate from terminally differentiated astrocytes and neurons, which can dedifferentiate to a stem cell-like state upon transformation. In this study, we confirmed that transformed dedifferentiated astrocytes and neurons acquired a stem/progenitor cell state, although they still retained gene expression memory from their parental cell. Transcriptional network analysis on these cells identified upregulated genes in three main pathways: Wnt signaling, cell cycle and focal adhesi ...[more]
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Project description:In this study, we confirmed that transformed dedifferentiated astrocytes and neurons acquired a stem/progenitor cell state, although they still retained gene expression memory from their parental cell-type. Transcriptional network analysis on transformed cells revealed up-regulation of genes involved in three signaling pathways: Wnt signaling, cell cycle and focal adhesion with the gene Spp1, also known as osteopontin (OPN) serving as a key node connecting these three pathways. Inhibition of OPN blocked the formation of aggregated neurospheres, affected the proliferative capacity of transformed cell-types and reduced the expression levels of neural stem cell markers. Specific inhibition of OPN in murine glioma tumors prolonged mice survival. We conclude that OPN is an important player in dedifferentiation of cells during tumor formation, hence its inhibition can be a therapeutic target for glioblastoma. Cortical neurons and astrocytes were derived from 11 days old SynapsinI-Cre and GFAP-Cre mice, respectively. The cells were cultured in their respective media to maintain their identity. These cells were then transduced with HRas-shp53 lentivirus with a transduction efficiency of >90%. The transduced neurons and astrocytes were later switched to neural stem cell media devoid of serum and supplemented with FGF-2 (NSC media). Within one week, these cells became proliferative and aggregated to form free-floating neurospheres. These cells, hereinafter referred to as NSynR53 and AGR53, respectively, were later harvested and mRNA collected for sequencing library generation using DP-seq. To assess the regression of these cells to an undifferentiated state along the differentiation axis, enriched populations of mESC and NSC were also grown in vitro and mRNA obtained from these cells were subjected to sequencing library preparation.
2015-05-11 | E-GEOD-64411 | biostudies-arrayexpress
Project description:In this study, we confirmed that transformed dedifferentiated astrocytes and neurons acquired a stem/progenitor cell state, although they still retained gene expression memory from their parental cell-type. Transcriptional network analysis on transformed cells revealed up-regulation of genes involved in three signaling pathways: Wnt signaling, cell cycle and focal adhesion with the gene Spp1, also known as osteopontin (OPN) serving as a key node connecting these three pathways. Inhibition of OPN blocked the formation of aggregated neurospheres, affected the proliferative capacity of transformed cell-types and reduced the expression levels of neural stem cell markers. Specific inhibition of OPN in murine glioma tumors prolonged mice survival. We conclude that OPN is an important player in dedifferentiation of cells during tumor formation, hence its inhibition can be a therapeutic target for glioblastoma.
2015-05-11 | GSE64411 | GEO
Project description:BackgroundGlioblastoma (GBM) is the most malignant grade of glioma. Highly aggressive characteristics of GBM and poor prognosis cause GBM-related deaths. The potential prognostic biomarkers remain to be demonstrated. This research builds up predictive gene targets of expression alterations in GBM utilizing bioinformatics analysis.Methods and resultsThe microarray datasets (GSE15824 and GSE16011) associated with GBM were obtained from Gene Expression Omnibus (GEO) database to identify the differentially expressed genes (DEGs) between GBM and non-tumor tissues. In total, 719 DEGs were obtained and subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) for function enrichment analysis. Furthermore, we constructed protein-protein Interaction (PPI) network among DEGs utilizing Search Tool for the Retrieval of Interacting Genes (STRING) online tool and Cytoscape software. The DEGs of degree > 10 was selected as hub genes, including 73 upregulated genes and 21 downregulated genes. Moreover, MCODE application in Cytoscape software was employed to identify three key modules involved in GBM development and prognosis. Additionally, we used the Gene expression profiling and interactive analyses (GEPIA) online tool to further confirm four genes involving in poor prognosis of GBM patients, including interferon-gamma-inducible protein 30 (IFI30), major histocompatibility complex class II-DM alpha (HLA-DMA), Prolyl 4-hydroxylase beta polypeptide (P4HB) and reticulocalbin-1 (RCN1). Furthermore, the correlation analysis indicated that the expression of IFI30, an acknowledged biomarker in glioma, was positively correlated with HLA-DMA, P4HB and RCN1. RCN1 expression was positively correlated with P4HB and HLA-DMA. Moreover, qRT-PCR and immunohistochemistry analysis further validated the upregulation of four prognostic markers in GBM tissues.ConclusionsAnalysis of multiple datasets combined with global network information and experimental verification presents a successful approach to uncover the risk hub genes and prognostic markers of GBM. Our study identified four risk- and prognostic-related gene signatures, including IFI30, HLA-DMA, P4HB and RCN1. This gene sets contribute a new perspective to improve the diagnostic, prognostic, and therapeutic outcomes of GBM.
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