Wei Bo, Wang Le, Du Chao, Hu Guozhang, Wang Lina, Jin Ying, Kong Daliang
Department of Neurosurgery, China‑Japan Union Hospital of Jilin University, Changchun, Jilin 130033, P.R. China.
Department of Ophthalmology, The First Hospital of Jilin University, Changchun, Jilin 130021, P.R. China.
Mol Med Rep. 2015 Apr;11(4):2548-54. doi: 10.3892/mmr.2014.3094. Epub 2014 Dec 15.
The present study aimed to identify differentially expressed genes (DEGs) regulated by transcription factors (TFs) in glioblastoma, by conducting a bioinformatics analysis. The results of the present study may provide potential therapeutic targets that are involved in the development of glioblastoma. The GSE4290 raw data set was downloaded from the Gene Expression Omnibus database, and consisted of 23 non‑tumor samples and 77 glioblastoma (grade 4) tumor samples. Robust Multichip Averaging was used to identify DEGs between the glioblastoma and non‑tumor samples. Functional enrichment analysis of the DEGs was also performed. Based on the TRANSFAC® database, TFs associated with the glioblastoma gene expression profile were used to construct a regulatory network. Furthermore, trimmed subnets were identified according to calculated Z‑scores. A total of 676 DEGs were identified, of which 190 were upregulated and 496 were downregulated. Gene Ontology analysis demonstrated that the majority of these DEGs were functionally enriched in synaptic transmission, regulation of vesicle‑mediated transport and ion‑gated channel activity. In addition, the enriched Kyoto Encyclopedia of Genes and Genomes pathway included neuroactive ligand‑receptor interaction, calcium signaling pathway, p53 signaling pathway and cell cycle. Based on the TRANSFAC® database, transcriptional regulatory networks with 2,246 nodes and 4,515 regulatory pairs were constructed. According to the Z‑scores, the following candidate TFs were identified: TP53, SP1, JUN, STAT3 and SPI1; alongside their downstream DEGs. TP53 was the only differentially expressed TF. These candidate TFs and their downstream DEGs may have important roles in the progression of glioblastoma, and could be potential biomarkers for clinical treatment.
本研究旨在通过生物信息学分析，鉴定胶质母细胞瘤中转录因子（TFs）调控的差异表达基因（DEGs）。本研究结果可能为参与胶质母细胞瘤发生发展的潜在治疗靶点提供依据。从基因表达综合数据库下载了GSE4290原始数据集，该数据集由23个非肿瘤样本和77个胶质母细胞瘤（4级）肿瘤样本组成。采用稳健多芯片平均法鉴定胶质母细胞瘤样本与非肿瘤样本之间的差异表达基因。还对差异表达基因进行了功能富集分析。基于TRANSFAC®数据库，利用与胶质母细胞瘤基因表达谱相关的转录因子构建调控网络。此外，根据计算出的Z值确定修剪后的子网。共鉴定出676个差异表达基因，其中190个上调，496个下调。基因本体分析表明，这些差异表达基因大多在功能上富集于突触传递、囊泡介导运输的调节和离子门控通道活性。此外，富集的京都基因与基因组百科全书通路包括神经活性配体-受体相互作用、钙信号通路、p53信号通路和细胞周期。基于TRANSFAC®数据库，构建了具有2246个节点和4515个调控对的转录调控网络。根据Z值，鉴定出以下候选转录因子：TP53、SP1、JUN、STAT3和SPI1；以及它们的下游差异表达基因。TP53是唯一差异表达的转录因子。这些候选转录因子及其下游差异表达基因可能在胶质母细胞瘤的进展中起重要作用，并且可能成为临床治疗的潜在生物标志物。
