DataSheet1_Identification of a Five-mRNA Signature as a Novel Potential Prognostic Biomarker for Glioblastoma by Integrative Analysis.DOCX

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 (p < 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 (p < 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 (p < 0.05). Our study developed a novel candidate model that provides new prospective prognostic biomarkers for GBM.

尽管已有先进的多模式治疗手段可用，但胶质母细胞瘤（glioblastoma, GBM）患者的预后仍然不佳。本研究针对来自基因表达综合数据库（Gene Expression Omnibus, GEO）、癌症基因组图谱（The Cancer Genome Atlas, TCGA）及基因型-组织表达（Genotype-Tissue Expression, GTEx）项目的302份胶质母细胞瘤组织样本与209份正常脑组织样本的mRNA表达谱开展全基因组整合分析，以探究特定mRNA在胶质母细胞瘤中的预后与预测价值。最终共筛选出26种与胶质母细胞瘤患者总生存期（Overall Survival, OS）显著相关的mRNA（p < 0.05）。本研究借助生存分析与Cox回归模型，从上述26种mRNA中筛选出5种mRNA（PTPRN、ABCC3、MDK、NMB及RALYL），该特征可在训练集中将患者划分为高风险组与低风险组，两组患者的总生存期存在统计学显著性差异。该五mRNA生物标志物特征模型已在测试集及独立验证集中得到成功验证。此外，多变量Cox回归分析结果显示，该五mRNA生物标志物特征可作为胶质母细胞瘤患者生存的独立预后因素，不受临床特征与分子特征的影响（p < 0.05）。基因集富集分析（Gene Set Enrichment Analysis, GSEA）结果表明，该五mRNA生物标志物特征可能通过参与已知的癌症相关通路、信号分子及免疫系统过程，参与胶质母细胞瘤的发生与发展。且与生物信息学分析结果一致，NMB、ABCC3及MDK的mRNA在4株人胶质母细胞瘤细胞中的表达水平显著升高，而PTPRN与RALYL的mRNA在胶质母细胞瘤细胞中的表达水平显著降低（p < 0.05）。本研究构建了一种全新的候选模型，可为胶质母细胞瘤提供新的潜在预后生物标志物。