Liu Ruifei, Gao Zhengzheng, Li Qiwei, Fu Qiang, Han Dongwei, Wang Jixi, Li Ji, Guo Ying, Shi Yuchen
Second Affiliated Hospital, Heilongjiang University of Chinese Medicine, Harbin, China.
College of Basic Medicine, Inner Mongolia Medical University, Hohhot, China.
Front Genet. 2022 Feb 14;12:803257. doi: 10.3389/fgene.2021.803257. eCollection 2021.
Glioblastoma (GBM), originating in the brain, is a universally aggressive malignant tumor with a particularly poor prognosis. Therefore, insight into the critical role of underlying genetic mechanisms is essential to developing new therapeutic approaches. This study aims to identify potential markers with clinical and prognostic significance in GBM. To this end, increasing numbers of differentially expressed RNA have been identified used to construct competitive endogenous RNA networks for prognostic analysis via comparison and analysis of RNA expression levels of tumor and normal tissues in glioblastoma. This analysis demonstrated that the RNA expression patterns of normal and tumor samples were significantly different. Thus, the resulting differentially expressed RNAs were used to construct competitive endogenous RNA (competing endogenous RNA, ceRNA) networks. The functional enrichment indicated mRNAs in the network are critically involved in a variety of biological functions. Additionally, the prognostic analysis suggested 27 lncRNAs, including LOXL1-AS1, AL356414.1, etc., were significantly associated with patient survival. Given the prognostic significance of these 27 lncRNAs in GBM, we sought to classify the samples. Importantly, Kaplan-Meier analysis revealed that survival times varied significantly among the different categories. Overall, these results identify that the candidate lncRNAs are potential prognostic markers of GBM and its corresponding mRNAs may be a potential target for therapy.
胶质母细胞瘤（GBM）起源于大脑，是一种具有普遍侵袭性的恶性肿瘤，预后特别差。因此，深入了解潜在遗传机制的关键作用对于开发新的治疗方法至关重要。本研究旨在鉴定GBM中具有临床和预后意义的潜在标志物。为此，通过比较和分析胶质母细胞瘤肿瘤组织和正常组织的RNA表达水平，已鉴定出越来越多的差异表达RNA用于构建竞争性内源性RNA网络进行预后分析。该分析表明，正常样本和肿瘤样本的RNA表达模式存在显著差异。因此，所得的差异表达RNA被用于构建竞争性内源性RNA（ceRNA）网络。功能富集表明网络中的mRNA严重参与多种生物学功能。此外，预后分析表明27种lncRNA，包括LOXL1-AS1、AL356414.1等，与患者生存显著相关。鉴于这27种lncRNA在GBM中的预后意义，我们试图对样本进行分类。重要的是，Kaplan-Meier分析显示不同类别之间的生存时间存在显著差异。总体而言，这些结果表明候选lncRNA是GBM的潜在预后标志物，其相应的mRNA可能是潜在的治疗靶点。
