School of Biomedical Engineering, Capital Medical University, Beijing 100069, People's Republic of China.
Mol Omics. 2019 Dec 2;15(6):406-419. doi: 10.1039/c9mo00126c.
Glioblastoma multiforme (GBM) is the most malignant brain tumor with a poor prognosis. A molecular level classification of GBM can provide insight into accurate patient-specific treatment. Competitive endogenous RNAs (ceRNAs), such as long non-coding RNAs (lncRNAs), play an essential role in the development of tumors and are associated with survival. However, the pattern of lncRNA-mediated ceRNA (LMce) crosstalk in different GBM subtypes is still unclear. In this study, we present a computational cascade to construct LMce networks of different GBM subtypes and investigate the lncRNA-mRNA regulations among them. Our results showed that although most lncRNAs and mRNAs in the different GBM subtype networks were the same, the regulation relationships of these RNAs were different among subtypes. 42.5%, 50.9%, 43.5% and 65.0% lncRNA-mRNA regulatory pairs were classic (CL)-, mesenchymal (MES)-, proneural (PN)- and neural (NE)-specific. In addition, our study identified 61, 132, 24 and 16 modules in which lncRNAs and mRNAs synergically competed with each other for miRNAs as CL-, MES-, PN- and NE-specific. CL- and MES-specific modules were mainly involved in biological functions such as cell proliferation, apoptosis and migration, while PN- and NE-specific modules were mainly related to DNA damage and cell cycle dysregulation. Survival analysis demonstrated that some modules could be potential prognostic markers of patients of CL and MES subtypes. This study uncovered the LMce interaction patterns in different GBM subtypes, identified subtype-specific modules with distinct biological functions, and revealed the potential prognostic markers of patients of different GBM subtypes. These results might contribute to the discovery of the GBM prognostic biomarkers and development of a more accurate therapeutic process.
胶质母细胞瘤(GBM)是预后最差的最恶性脑肿瘤。GBM 的分子水平分类可以深入了解针对特定患者的准确治疗方法。竞争性内源性 RNA(ceRNA),如长非编码 RNA(lncRNA),在肿瘤的发展中起着至关重要的作用,并与生存相关。然而,不同 GBM 亚型中 lncRNA 介导的 ceRNA(LMce)串扰模式尚不清楚。在这项研究中,我们提出了一种计算级联方法来构建不同 GBM 亚型的 LMce 网络,并研究它们之间的 lncRNA-mRNA 调控关系。我们的结果表明,尽管不同 GBM 亚型网络中的大多数 lncRNA 和 mRNA 是相同的,但这些 RNA 之间的调控关系在亚型之间是不同的。42.5%、50.9%、43.5%和 65.0%的 lncRNA-mRNA 调控对是经典(CL)、间充质(MES)、前神经(PN)和神经(NE)特异性的。此外,我们的研究还确定了 61、132、24 和 16 个模块,其中 lncRNA 和 mRNA 协同竞争 miRNA,作为 CL、MES、PN 和 NE 特异性。CL 和 MES 特异性模块主要涉及细胞增殖、凋亡和迁移等生物学功能,而 PN 和 NE 特异性模块主要与 DNA 损伤和细胞周期失调有关。生存分析表明,一些模块可能是 CL 和 MES 亚型患者的潜在预后标志物。本研究揭示了不同 GBM 亚型中 LMce 的相互作用模式,鉴定了具有不同生物学功能的亚型特异性模块,并揭示了不同 GBM 亚型患者的潜在预后标志物。这些结果可能有助于发现 GBM 的预后生物标志物,并开发更准确的治疗过程。