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全面分析反相蛋白阵列数据揭示胶质母细胞瘤亚型的特征性独特蛋白质组学特征。

Comprehensive analysis of Reverse Phase Protein Array data reveals characteristic unique proteomic signatures for glioblastoma subtypes.

机构信息

Department of Bio-Medical Sciences, School of Biosciences and Technology, VIT University, Vellore 632014, India.

Department of Bio-Medical Sciences, School of Biosciences and Technology, VIT University, Vellore 632014, India.

出版信息

Gene. 2019 Feb 15;685:85-95. doi: 10.1016/j.gene.2018.10.069. Epub 2018 Oct 25.

Abstract

The most common and lethal type of intracranial tumors include the astrocytomas. Grade IV astrocytoma or Glioblastoma (GBM) is highly aggressive and treatment-refractory with a median survival of only 14 to 16 months. Molecular profiling of GBMs reveals a high degree of intra- and inter-tumoral heterogeneity, and hence it is important to understand the important signalling axes that get deregulated in different GBM subtypes to provide effective tailor-made therapies. In this study, we have carried out extensive analysis of Reverse Phase Protein Array (RPPA) data from TCGA cohort to develop protein signatures that define glioma grades or subtypes. The protein signatures that distinguished Grade II or III from GBM had largely overlapped, and pathway analysis revealed the positive enrichment of extracellular matrix proteins (ECM), MYC pathway, uPAR pathway and G2/M checkpoint genes in GBM. We also identified protein signatures for GBMs with genetic alterations (IDH mutation, p53 mutation, EGFR amplification or mutation, CDKN2A/CDKN2B deletion, and PTEN mutation) that occur at high frequency. G-CIMP positive GBM-specific protein signature showed a large similarity with IDH1-mutant protein signature, thus signifying the importance of IDH1 mutation driving the G-CIMP. Gene expression subtype analysis revealed an association of specific proteins to classical (EGFR and phosphor variants), mesenchymal (SERPINE1, TAZ, and Myosin-IIa_pS1943), neural (TUBA1B), and proneural (GSK3_pS9) types. Univariate Cox regression analysis identified several proteins showing significant correlation with GBM survival. Multivariate analysis revealed that IGFBP2 and RICTOR_pT1135 are independent predictors of survival. Overall, our analyses reveal that specific proteins are regulated in different glioma subtypes underscoring the importance of diverse signalling axes playing important role in the pathogenesis of glioma tumors.

摘要

最常见和致命的颅内肿瘤类型包括星形细胞瘤。IV 级星形细胞瘤或胶质母细胞瘤(GBM)侵袭性强且对治疗有抗性,中位生存期仅为 14 到 16 个月。GBM 的分子谱分析显示出高度的肿瘤内和肿瘤间异质性,因此了解不同 GBM 亚型中失调的重要信号轴对于提供有效的定制治疗非常重要。在这项研究中,我们对 TCGA 队列的反向蛋白质阵列(RPPA)数据进行了广泛分析,以开发定义神经胶质瘤等级或亚型的蛋白质特征。将 II 级或 III 级与 GBM 区分开来的蛋白质特征在很大程度上重叠,通路分析显示 GBM 中细胞外基质蛋白(ECM)、MYC 通路、uPAR 通路和 G2/M 检查点基因的阳性富集。我们还鉴定了具有高频发生的遗传改变(IDH 突变、p53 突变、EGFR 扩增或突变、CDKN2A/CDKN2B 缺失和 PTEN 突变)的 GBM 的蛋白质特征。G-CIMP 阳性 GBM 特异性蛋白质特征与 IDH1 突变蛋白质特征具有很大的相似性,因此表明 IDH1 突变驱动 G-CIMP 的重要性。基因表达亚型分析显示特定蛋白质与经典(EGFR 和磷酸变体)、间充质(SERPINE1、TAZ 和肌球蛋白-IIa_pS1943)、神经(TUBA1B)和原神经(GSK3_pS9)类型相关。单变量 Cox 回归分析确定了几个与 GBM 生存显著相关的蛋白质。多变量分析显示 IGFBP2 和 RICTOR_pT1135 是生存的独立预测因子。总的来说,我们的分析表明,不同的神经胶质瘤亚型中存在特定的蛋白质调节,这强调了不同信号轴在神经胶质瘤发病机制中发挥重要作用的重要性。

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