Tian Yixin, Ke Yi-Quan, Ma Yanxia
Department of Neurosurgery, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
The National Key Clinical Specialty, The Engineering Technology Research Center of Education Ministry of China, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Guangzhou, China.
J Oncol. 2020 Oct 30;2020:2319194. doi: 10.1155/2020/2319194. eCollection 2020.
Glioma is the most common and deadly tumor in central nervous system. According to previous studies, long noncoding RNAs (lncRNA) and transcription factors were significant factors of gliomas progression by regulating gliomas immune microenvironment. In our study, we built two independent cohorts from CGGA and TCGA. And we extracted 253 immune-related lncRNA correlated with prognosis. After LASSO analysis and multivariate Cox regression analysis, 8 immune-related lncRNA were used to construct classifier. The effectiveness of classifier was confirmed in both CGGA (AUC = 0.869) and TCGA (AUC = 0.902) cohorts. The correlation between transcription factors and immune-related lncRNA was calculated by WCGNA. Eventually, we built a network between 8 lncRNA and transcription factors. The function of core immune-related lncRNA in gliomas immune microenvironment was also investigated by CIBERTSORT. Our research provided a strong classifier of immune-related lncRNA to predict gliomas patient outcome. We also found the correlation between core immune-related lncRNA and transcription factors. These results may stimulate new strategy of immunotherapy in gliomas patients.
胶质瘤是中枢神经系统中最常见且致命的肿瘤。根据以往研究，长链非编码RNA（lncRNA）和转录因子是通过调节胶质瘤免疫微环境影响胶质瘤进展的重要因素。在我们的研究中，我们从CGGA和TCGA构建了两个独立队列。我们提取了253个与预后相关的免疫相关lncRNA。经过LASSO分析和多变量Cox回归分析，使用8个免疫相关lncRNA构建分类器。分类器的有效性在CGGA（AUC = 0.869）和TCGA（AUC = 0.902）队列中均得到证实。通过WCGNA计算转录因子与免疫相关lncRNA之间的相关性。最终，我们构建了8个lncRNA与转录因子之间的网络。还通过CIBERTSORT研究了核心免疫相关lncRNA在胶质瘤免疫微环境中的功能。我们的研究提供了一个强大的免疫相关lncRNA分类器来预测胶质瘤患者的预后。我们还发现了核心免疫相关lncRNA与转录因子之间的相关性。这些结果可能会推动胶质瘤患者免疫治疗的新策略。
