Identification of the potential oncogenes in glioblastoma based on bioinformatic analysis and elucidation of the underlying mechanisms

Abstract

Glioblastoma (GBM) is a common malignant tumour in the human brain, but its molecular mechanisms have not been systematically evaluated. The aim of this study was to identify potential key oncogenes associated with the progression of GBM and to elucidate their mechanisms. The gene expression profile of GSE50161, selected from the Gene Expression Omnibus database, was analysed to find cancer-associated genes and gene functions in GBM. In total, 486 differentially expressed genes, including 128 upregulated genes, were identified. The function and pathway enrichment of these genes were analysed through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. Survival analysis for three selected partially upregulated genes, CDK1, CCNB1 and CDC20, showed that their high expression was significantly associated with poor survival in GBM. CDK1 was selected for validation of its function and molecular mechanism in GBM. This gene was significantly overexpressed in GBM cancer tissues and cells compared with normal control cells. In addition, knockdown of CDK1 clearly inhibited GBM cell proliferation. Notably, we demonstrated that CDK1 was involved in the Akt signalling pathway, where it promotes the process involved in GBM malignancy.

Identification of differentially expressed genes in pancreatic ductal adenocarcinoma and normal pancreatic tissues based on microarray datasets

“…a meta-analysis, as a large-sample study, has an advantage in addressing this limitation due to its enhanced statistical power (19). Prior meta-analyses have been applied to study tumors to confirm deGs between tumor tissue and normal tissue in glioma (20,21), lung cancer (22), bladder cancer (23), breast cancer (24), osteosarcoma (25), liver cancer (26) and pancreatic cancer (27). In the present study, integrative meta-analysis of expression data (inMeX) was used to conduct a meta-analysis based on 11 qualified microarray datasets, with the aim to identify crucial deGs between Pdac samples and normal pancreatic samples that may serve as biomarkers for Pdac treatment and prognosis.…”

Oncogenic RAS activity predicts response to chemotherapy and outcome in lung adenocarcinoma

“…pancreatic, colorectal and lung cancers 36, 37 ) and others not (e.g. uveal melanoma 38 , glioblastoma 39 , kidney cancer 40 ). To determine how RAS84 varied across cancer types, we quantified it against all 32 TCGA solid cancers in a pan-cancer analysis.…”

Bioinformatic analysis of the potential molecular mechanism of PAK7 expression in glioblastoma

“…Wei et al (36) identified deGs regulated by transcription factors in GBM by analyzing the GSe4290 dataset downloaded from the Gene expression omnibus (Geo) database. Zhang et al (37) selected GSe50161 from Geo database to identify potential oncogenes associated with GBM progression. Moreover, liu et al (38) analyzed the glioma gene expression profile dataset GSe4290 for the identification of deGs.…”