Xie Pan, Yan Han, Gao Ying, Li Xi, Zhou Dong-Bo, Liu Zhao-Qian
Department of Clinical Pharmacology, Hunan Key Laboratory of Pharmacogenetics, and National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China.
Institute of Clinical Pharmacology, Central South University, Changsha, China.
Front Oncol. 2022 Jun 2;12:920926. doi: 10.3389/fonc.2022.920926. eCollection 2022.
Glioblastoma multiforme (GBM), the most prevalent and aggressive of primary malignant central nervous system tumors (grade IV), has a poor clinical prognosis. This study aimed to assess and predict the survival of GBM patients by establishing an m6A-related lncRNA signaling model and to validate its validity, accuracy and applicability.
RNA sequencing data and clinical data of GBM patients were obtained from TCGA data. First, m6A-associated lncRNAs were screened and lncRNAs associated with overall survival in GBM patients were obtained. Subsequently, the signal model was established using LASSO regression analysis, and its accuracy and validity are further verified. Finally, GO enrichment analysis was performed, and the influence of this signature on the immune regulation response and anticancer drug sensitivity of GBM patients was discussed.
The signature constructed by four lncRNAs AC005229.3, SOX21-AS1, AL133523.1, and AC004847.1 is obtained. Furthermore, the signature proved to be effective and accurate in predicting and assessing the survival of GBM patients and could function independently of other clinical characteristics (Age, Gender and mutation). Finally, Immunosuppression-related factors, including APC co-inhibition, T-cell co-inhibition, CCR and Check-point, were found to be significantly up-regulated in GBM patients in the high-risk group. Some chemotherapeutic drugs (Doxorubicin and Methotrexate) and targeted drugs (AZD8055, BI.2536, GW843682X and Vorinostat) were shown to have higher IC50 values in patients in the high-risk group.
We constructed an m6A-associated lncRNA risk model to predict the prognosis of GBM patients and provide new ideas for the treatment of GBM. Further biological experiments can be conducted on this basis to validate the clinical value of the model.
多形性胶质母细胞瘤(GBM)是原发性恶性中枢神经系统肿瘤中最常见且侵袭性最强的(IV级),临床预后较差。本研究旨在通过建立一种与m6A相关的长链非编码RNA(lncRNA)信号模型来评估和预测GBM患者的生存情况,并验证其有效性、准确性和适用性。
从TCGA数据库获取GBM患者的RNA测序数据和临床数据。首先,筛选与m6A相关的lncRNAs,获得与GBM患者总生存相关的lncRNAs。随后,使用LASSO回归分析建立信号模型,并进一步验证其准确性和有效性。最后,进行基因本体(GO)富集分析,并讨论该特征对GBM患者免疫调节反应和抗癌药物敏感性的影响。
获得了由四个lncRNAs(AC005229.3、SOX21-AS1、AL133523.1和AC004847.1)构建的特征。此外,该特征在预测和评估GBM患者生存方面被证明是有效和准确的,并且可以独立于其他临床特征(年龄、性别和突变)发挥作用。最后,发现包括抗原呈递细胞共抑制、T细胞共抑制、趋化因子受体(CCR)和检查点等免疫抑制相关因子在高危组GBM患者中显著上调。一些化疗药物(阿霉素和甲氨蝶呤)和靶向药物(AZD8055、BI.2536、GW843682X和伏立诺他)在高危组患者中显示出较高的半数抑制浓度(IC50)值。
我们构建了一种与m6A相关的lncRNA风险模型来预测GBM患者的预后,并为GBM的治疗提供新思路。在此基础上可进一步开展生物学实验以验证该模型的临床价值。