Table_1_Integrated Transcriptome Analyses and Experimental Verifications of Mesenchymal-Associated TNFRSF1A as a Diagnostic and Prognostic Biomarker in Gliomas.DOCX

Gliomas are the most prevalent malignant primary brain tumors with poor outcome, and four different molecular subtypes (Mesenchymal, Proneural, Neural, and Classical) are popularly applied in scientific researches and clinics of gliomas. Public databases contain an abundant genome-wide resource to explore the potential biomarker and molecular mechanisms using the informatics analysis. The aim of this study was to discover the potential biomarker and investigate its effect in gliomas. Weighted gene co-expression network analysis (WGCNA) was used to construct the co-expression modules and explore the biomarker among the dataset CGGA mRNAseq_693 carrying 693 glioma samples. Functional annotations, ROC, correlation, survival, univariate, and multivariate Cox regression analyses were implemented to investigate the functional effect in gliomas, and molecular experiments in vitro were performed to study the biological effect on glioma pathogenesis. The brown module was found to be strongly related to WHO grade of gliomas, and KEGG pathway analysis demonstrated that TNFRSF1A was enriched in MAPK signaling pathway and TNF signaling pathway. Overexpressed TNFRSF1A was strongly related to clinical features such as WHO grade, and functioned as an independent poor prognostic predictor of glioma patients. Notably, TNFRSF1A was preferentially upregulated in the Mesenchymal subtype gliomas (Mesenchymal-associated). Knockdown of TNFRSF1A inhibited proliferation and migration of glioma cell lines in vitro. Our findings provide a further understanding of the progression of gliomas, and Mesenchymal-associated TNFRSF1A might be a promising target of diagnosis, therapy, and prognosis of gliomas.

胶质瘤是发病率最高的恶性原发性脑肿瘤，预后不佳。在胶质瘤的科学研究和临床应用中，广泛采用四种不同的分子亚型（间充质型、神经倾向型、神经型和经典型）。公共数据库中蕴含着丰富的全基因组资源，可供通过信息学分析探索潜在的生物标志物和分子机制。本研究旨在发现潜在的生物标志物并探究其在胶质瘤中的效应。利用加权基因共表达网络分析（WGCNA）构建共表达模块，并在包含693个胶质瘤样本的CGGA mRNAseq_693数据集中探索生物标志物。通过实施功能注释、ROC曲线、相关性、生存分析、单变量和多变量Cox回归分析等方法，研究了其在胶质瘤中的功能效应，并在体外进行了分子实验以研究其对胶质瘤发病机制的影响。研究发现，棕色模块与胶质瘤的WHO分级密切相关，而KEGG通路分析显示TNFRSF1A在MAPK信号通路和TNF信号通路中富集。过表达的TNFRSF1A与临床特征如WHO分级显著相关，并作为胶质瘤患者独立的不良预后预测因子。值得注意的是，TNFRSF1A在间充质型胶质瘤（间充质相关）中优先上调。在体外敲低TNFRSF1A可抑制胶质瘤细胞系的增殖和迁移。我们的研究进一步揭示了胶质瘤的发展过程，且间充质相关TNFRSF1A可能成为胶质瘤诊断、治疗和预后中的有希望的目标。