Table1_System biology approach to identify the novel biomarkers in glioblastoma multiforme tumors by using computational analysis.DOCX

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.

引言：成人最常见的原发性脑肿瘤为多形性胶质母细胞瘤（glioblastoma multiforme, GBM），占所有脑肿瘤病例的45.2%。作为一种高度侵袭性的脑肿瘤，多形性胶质母细胞瘤的特征包括细胞快速分裂及易发生坏死。令人遗憾的是，其预后极差，确诊后患者存活率仅为5.5%。
研究方法：为攻克这类复杂疾病，当前研究重点聚焦于开发更有效的药物及精准定位药理学靶点。为筛选适用于药物研发的生物标志物，需综合考量疾病状态、基因表达水平及蛋白质间相互作用等多类因素。本研究首先通过p值、错误发现率（false discovery rate, FDR）等统计学方法鉴定差异表达基因（differentially expressed genes, DEGs），以期筛选出多形性胶质母细胞瘤中具有潜力的生物标志物。在本次鉴定的132个基因中，13个呈现上调表达，仅29个呈现特异性下调表达，其余基因的表达水平未观察到统计学显著变化。
研究结果：在核心生物标志物基因筛选中，基质金属蛋白酶9（matrix metallopeptidase 9, MMP9）的分值最高，其次为骨桥蛋白（periostin, POSTN，分值11）及Hes家族bHLH转录因子5（Hes family BHLH transcription factor 5, HES5，分值9）。生存分析揭示了每一种核心生物标志物基因在多形性胶质母细胞瘤发生与进展中的关键作用。富集分析结果显示，此类基因多参与信号通路并在细胞外区域发挥功能。此外，本研究还在差异表达基因的蛋白质相互作用（protein-protein interactions, PPIs）网络中鉴定出调控相关蛋白的转录因子及激酶。
讨论：本研究筛选出了与每一种核心生物标志物相关的药物。靶向参与多形性胶质母细胞瘤进程的MMP9是极具吸引力的治疗策略。分子对接实验结果表明，所选的四种药物复合物（卡莫司汀、洛莫司汀、马里司他及替莫唑胺）均具有较高的结合亲和力，其结合能分别为-6.3、-7.4、-7.7及-8.7 kcal/mol。卡莫司汀复合物与马里司他复合物的平均根均方偏差（root-mean-square deviation, RMSD）分别为4.2 Å与4.9 Å，洛莫司汀复合物与替莫唑胺复合物的平均根均方偏差则分别为1.2 Å与1.6 Å。此外，根均方波动（root-mean-square fluctuation, RMSF）分析显示体系具有较高稳定性，原子分子未出现明显的构象变化。综上，本项计算机模拟（in silico）研究为未来实验研究者靶向治疗这类致死性疾病提供了全新思路。