Xu Huifang, Zhang Linfang, Xia Xiujuan, Shao Wei
Department of Neurology, Wuhan No. 1 Hospital, Huazhong University of Science and Technology, Wuhan, China.
Department of Gastroenterology, The Third Xiangya Hospital, Central South University, Changsha, China.
Front Genet. 2022 Jul 8;13:931938. doi: 10.3389/fgene.2022.931938. eCollection 2022.
Despite the availability of advanced multimodal therapy, the prognosis of patients suffering from glioblastoma (GBM) remains poor. We conducted a genome-wide integrative analysis of mRNA expression profiles in 302 GBM tissues and 209 normal brain tissues from the Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), and the Genotype-Tissue Expression (GTEx) project to examine the prognostic and predictive value of specific mRNAs in GBM. A total of 26 mRNAs were identified to be closely related to GBM patients' OS ( < 0.05). Utilizing survival analysis and the Cox regression model, we discovered a set of five mRNAs (PTPRN, ABCC3, MDK, NMB, and RALYL) from these 26 mRNAs that displayed the capacity to stratify patients into high- and low-risk groups with statistically different overall survival in the training set. The model of the five-mRNA biomarker signature was successfully verified on a testing set and independent sets. Moreover, multivariate Cox regression analysis revealed that the five-mRNA biomarker signature was a prognostic factor for the survival of patients with GBM independent of clinical characteristics and molecular features ( < 0.05). Gene set enrichment analysis indicated that the five-mRNA biomarker signature might be implicated in the incidence and development of GBM through its roles in known cancer-related pathways, signaling molecules, and the immune system. Moreover, consistent with the bioinformatics analysis, NMB, ABCC3, and MDK mRNA expression was considerably higher in four human GBM cells, and the expression of PTPRN and RALYL was decreased in GBM cells ( < 0.05). Our study developed a novel candidate model that provides new prospective prognostic biomarkers for GBM.
尽管有先进的多模态治疗方法，但胶质母细胞瘤（GBM）患者的预后仍然很差。我们对来自基因表达综合数据库（GEO）、癌症基因组图谱（TCGA）和基因型-组织表达（GTEx）项目的302个GBM组织和209个正常脑组织的mRNA表达谱进行了全基因组综合分析，以研究特定mRNA在GBM中的预后和预测价值。共鉴定出26种mRNA与GBM患者的总生存期密切相关（<0.05）。利用生存分析和Cox回归模型，我们从这26种mRNA中发现了一组5种mRNA（PTPRN、ABCC3、MDK、NMB和RALYL），它们能够将患者分为高风险和低风险组，在训练集中总体生存期有统计学差异。五mRNA生物标志物特征模型在测试集和独立集上得到了成功验证。此外，多变量Cox回归分析显示，五mRNA生物标志物特征是GBM患者生存的一个预后因素，独立于临床特征和分子特征（<0.05）。基因集富集分析表明，五mRNA生物标志物特征可能通过其在已知癌症相关途径、信号分子和免疫系统中的作用参与GBM的发生和发展。此外，与生物信息学分析一致，在四种人GBM细胞中，NMB、ABCC3和MDK mRNA表达明显更高，而在GBM细胞中PTPRN和RALYL的表达降低（<0.05）。我们的研究开发了一种新的候选模型，为GBM提供了新的前瞻性预后生物标志物。
