PDF(Pubmed)
Abstract：
Introduction: The most common primary brain tumor in adults is glioblastoma multiforme (GBM), accounting for 45.2% of all cases. The characteristics of GBM, a highly aggressive brain tumor, include rapid cell division and a propensity for necrosis. Regretfully, the prognosis is extremely poor, with only 5.5% of patients surviving after diagnosis. Methodology: To eradicate these kinds of complicated diseases, significant focus is placed on developing more effective drugs and pinpointing precise pharmacological targets. Finding appropriate biomarkers for drug discovery entails considering a variety of factors, including illness states, gene expression levels, and interactions between proteins. Using statistical techniques like p-values and false discovery rates, we identified differentially expressed genes (DEGs) as the first step in our research for identifying promising biomarkers in GBM. Of the 132 genes, 13 showed upregulation, and only 29 showed unique downregulation. No statistically significant changes in the expression of the remaining genes were observed. Results: Matrix metallopeptidase 9 (MMP9) had the greatest degree in the hub biomarker gene identification, followed by (periostin (POSTN) at 11 and Hes family BHLH transcription factor 5 (HES5) at 9. The significance of the identification of each hub biomarker gene in the initiation and advancement of glioblastoma multiforme was brought to light by the survival analysis. Many of these genes participate in signaling networks and function in extracellular areas, as demonstrated by the enrichment analysis.We also identified the transcription factors and kinases that control proteins in the proteinprotein interactions (PPIs) of the DEGs. Discussion: We discovered drugs connected to every hub biomarker. It is an appealing therapeutic target for inhibiting MMP9 involved in GBM. Molecular docking investigations indicated that the chosen complexes (carmustine, lomustine, marimastat, and temozolomide) had high binding affinities of -6.3, -7.4, -7.7, and -8.7 kcal/mol, respectively, the mean root-mean-square deviation (RMSD) value for the carmustine complex and marimastat complex was 4.2 Å and 4.9 Å, respectively, and the lomustine and temozolomide complex system showed an average RMSD of 1.2 Å and 1.6 Å, respectively. Additionally, high stability in root-mean-square fluctuation (RMSF) analysis was observed with no structural conformational changes among the atomic molecules. Thus, these in silico investigations develop a new way for experimentalists to target lethal diseases in future.
摘要：
简介：成人最常见的原发性脑肿瘤是多形性胶质母细胞瘤（GBM），占所有病例的45.2%。GBM的特点,一种高度侵袭性的脑肿瘤,包括快速细胞分裂和坏死倾向。遗憾的是,预后极差,只有5.5%的患者在诊断后存活。方法：为了根除这些复杂的疾病，重点是开发更有效的药物和精确的药理学靶点。为药物发现寻找合适的生物标志物需要考虑各种因素，包括疾病状态，基因表达水平，和蛋白质之间的相互作用。使用统计技术，如p值和错误发现率，我们确定差异表达基因(DEGs)是我们研究中识别GBM有前景的生物标志物的第一步.在132个基因中,13显示上调，只有29个显示出独特的下调。未观察到其余基因表达的统计学显著变化。结果:基质金属肽酶9(MMP9)在hub生物标志物基因鉴定中具有最大程度的,其次是（骨膜素（POSTN）在11和Hes家族BHLH转录因子5（HES5）在9。生存分析揭示了每个枢纽生物标志物基因在多形性胶质母细胞瘤的发生和发展中的重要性。许多这些基因参与信号网络和功能在细胞外区域，正如富集分析所证明的那样。我们还鉴定了在DEGs的蛋白质相互作用（PPI）中控制蛋白质的转录因子和激酶。讨论：我们发现了与每个集线器生物标志物相关的药物。它是抑制GBM中涉及的MMP9的有吸引力的治疗靶标。分子对接研究表明，所选择的复合物(卡莫司汀，洛莫司汀,marimastat,和替莫唑胺）具有-6.3，-7.4，-7.7和-8.7kcal/mol的高结合亲和力，分别,卡马斯汀复合物和马马司他复合物的平均均方根偏差（RMSD）值分别为4.2和4.9，分别,洛莫司汀和替莫唑胺复杂系统的平均RMSD为1.2和1.6，分别。此外,在均方根波动（RMSF）分析中观察到高稳定性，原子分子之间没有结构构象变化。因此，这些计算机模拟研究为实验家在未来针对致命疾病开发了一种新的方法。
