Department of Molecular Biology of Genetics, Kırşehir Ahi Evran University, Kırşehir, Turkey.
Department of Biomedical Engineering, Düzce University, Düzce, Turkey.
Gene. 2022 May 25;824:146395. doi: 10.1016/j.gene.2022.146395. Epub 2022 Mar 11.
One of the most prevailing primary brain tumors in adult human male is glioblastoma multiforme (GBM), which is categorized by rapid cellular growth. Even though the combination therapy comprises surgery, chemotherapy, and adjuvant therapies, the survival rate, on average, is 14.6 months. Glioma stem cells (GSCs) have key roles in tumorigenesis, progression, and defiance against chemotherapy and radiotherapy. In our study, firstly, the gene expression dataset GSE124145 was retrieved; the non-negative matrix factorization (NMF) method was applied on GBM dataset, and differentially expressed genes analysis (DEGs) was performed. After which, overlapping genes between metagenes and DEGs were detected to examine the Gene Ontology (GO) categories in the biological process (BP) in the stemness of GBM. The common hub genes were used to construct protein-protein interaction (PPI) network and further GO, while Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway was utilized to pinpoint the real hub genes. The analysis of hub genes particular for the same GO categories demonstrated that specific hub genes triggered distinct features of the same biological processes. After utilizing GSE124145 and The Cancer Genome Atlas (TCGA) dataset for survival analysis, we screened five real hub genes: GUCA1A, RFC2, GNG11, MMP19, and NRG1, which are strongly associated with the progression and prognosis of GBM. The DEGs analysis revealed that all real hub genes were overexpressed in GBM and TCGA datasets, which further validates our results. The constructed study of PPI, GO, and KEGG pathway on common hub genes was performed. Finally, the KEGG pathways performed on the top 15 candidate hub genes (including six real hub genes) of the PPI network in the GBM gene expression dataset study found mitogen-activated protein kinase (Mapk) signaling pathway to be the most significant pathway. The rest of the hub genes reviewed throughout the analysis might be favorable targets for diagnosing and treating GBM and lower-grade gliomas.
成人男性中最常见的原发性脑肿瘤之一是多形性胶质母细胞瘤(GBM),其特征是细胞快速生长。尽管联合治疗包括手术、化疗和辅助治疗,但平均存活率仅为 14.6 个月。神经胶质瘤干细胞(GSCs)在肿瘤发生、进展和对化疗和放疗的抵抗中起关键作用。在我们的研究中,首先检索了基因表达数据集 GSE124145;应用非负矩阵分解(NMF)方法对 GBM 数据集进行分析,并进行差异表达基因分析(DEGs)。之后,检测了基因之间的重叠metagenes 和 DEGs,以检查基因本体论(GO)在 GBM 干性中的生物学过程(BP)中的类别。共同的枢纽基因用于构建蛋白质-蛋白质相互作用(PPI)网络和进一步的 GO,而京都基因与基因组百科全书(KEGG)途径则用于确定真正的枢纽基因。对相同 GO 类别的共同枢纽基因的分析表明,特定的枢纽基因引发了相同生物过程的不同特征。利用 GSE124145 和癌症基因组图谱(TCGA)数据集进行生存分析后,我们筛选出了五个真正的枢纽基因:GUCA1A、RFC2、GNG11、MMP19 和 NRG1,它们与 GBM 的进展和预后密切相关。DEGs 分析表明,所有真正的枢纽基因在 GBM 和 TCGA 数据集中均过度表达,进一步验证了我们的结果。对共同枢纽基因进行 PPI、GO 和 KEGG 途径的构建研究。最后,对 PPI 网络中 15 个候选枢纽基因(包括 6 个真正的枢纽基因)的 GBM 基因表达数据集研究中的 top15 候选枢纽基因进行了 KEGG 途径分析,发现丝裂原激活蛋白激酶(Mapk)信号通路是最重要的通路。在整个分析过程中回顾的其余枢纽基因可能是诊断和治疗 GBM 和低级别神经胶质瘤的有利靶点。