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ASPM promotes glioblastoma growth by regulating G1 restriction point progression and Wnt-?-catenin signaling.


ABSTRACT: Increasing evidence has indicated that the disorganized expression of certain genes promotes tumour progression. In this study, we elucidate the potential key differentially expressed genes (DEGs) between glioblastoma (GBM) and normal brain tissue by analysing three different mRNA expression profiles downloaded from the Gene Expression Omnibus (GEO) database. DEGs were sorted, and key candidate genes and signalling pathway enrichments were analysed. In our analysis, the highest fold change DEG was found to be abnormal spindle-like microcephaly associated (ASPM). The ASPM expression pattern from the database showed that it is highly expressed in GBM tissue, and patients with high expression of ASPM have a poor prognosis. Moreover, ASPM showed aberrantly high expression in GBM cell lines. Loss-of-function assay indicated that ASPM enhances tumorigenesis in GBM cells in vitro. Xenograft growth verified the oncogenic activity of ASPM in vivo. Furthermore, downregulation of ASPM could arrest the cell cycle of GBM cells at the G0/G1 phase and attenuate the Wnt/?-catenin signalling activity in GBM. These data suggest that ASPM may serve as a new target for the therapeutic treatment of GBM.

SUBMITTER: Chen X 

PROVIDER: S-EPMC6977704 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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ASPM promotes glioblastoma growth by regulating G1 restriction point progression and Wnt-β-catenin signaling.

Chen Xin X   Huang Lijie L   Yang Yang Y   Chen Suhua S   Sun Jianjun J   Ma Changcheng C   Xie Jingcheng J   Song Yongmei Y   Yang Jun J  

Aging 20200106 1


Increasing evidence has indicated that the disorganized expression of certain genes promotes tumour progression. In this study, we elucidate the potential key differentially expressed genes (DEGs) between glioblastoma (GBM) and normal brain tissue by analysing three different mRNA expression profiles downloaded from the Gene Expression Omnibus (GEO) database. DEGs were sorted, and key candidate genes and signalling pathway enrichments were analysed. In our analysis, the highest fold change DEG w  ...[more]

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