Guo Kai, Duan Xinxin, Zhao Jiahui, Sun Boyu, Liu Xiaoming, Zhao Zongmao
Department of Neurosurgery, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Department of Neurosurgery, Affiliated Xing Tai People Hospital of Hebei Medical University, Xingtai, China.
Front Mol Biosci. 2022 Aug 30;9:984712. doi: 10.3389/fmolb.2022.984712. eCollection 2022.
Glioma is the most fatal neoplasm among the primary intracranial cancers. Necroptosis, a form of programmed cell death, is correlated with tumor progression and immune response. But, the role of necroptosis-related genes (NRGs) in glioma has not been well-uncovered. Single-cell and bulk RNA sequencing data, obtained from publicly accessed databases, were used to establish a necroptosis-related gene signature for predicting the prognosis of glioma patients. Multiple bioinformatics algorithms were conducted to evaluate the efficacy of the signature. The relative mRNA level of each signature gene was validated by quantitative real-time reverse transcription PCR (qRT-PCR) in glioma cell lines compared to human astrocytes. In this predicted prognosis model, patients with a high risk score showed a shorter overall survival, which was verified in the testing cohorts. The signature risk score was positively related with immune cell infiltration and some immune check points, such as CD276 (B7-H3), CD152 (CTLA-4), CD223 (LAG-3), and CD274 (PD-L1). Single-cell RNA sequencing analysis confirmed that the glioma microenvironment consists of various immune cells with different markers. The eight NRGs of the signature were detected to be expressed in several immune cells. QRT-PCR results verified that all the eight signature genes were differentially expressed between human astrocytes and glioma cells. The eight NRGs correlate with the immune microenvironment of glioma according to our bioinformatics analysis. This necroptosis-related gene signature may evaluate the precise methodology of predicting prognosis of glioma and provide a novel thought in glioma investigation.
胶质瘤是原发性颅内癌症中最致命的肿瘤。坏死性凋亡是一种程序性细胞死亡形式，与肿瘤进展和免疫反应相关。但是，坏死性凋亡相关基因（NRGs）在胶质瘤中的作用尚未得到充分揭示。从公开获取的数据库中获得的单细胞和批量RNA测序数据被用于建立一种坏死性凋亡相关基因特征，以预测胶质瘤患者的预后。采用多种生物信息学算法来评估该特征的有效性。与人类星形胶质细胞相比，通过定量实时逆转录PCR（qRT-PCR）验证了胶质瘤细胞系中每个特征基因的相对mRNA水平。在这个预测预后模型中，高风险评分的患者总生存期较短，这在测试队列中得到了验证。特征风险评分与免疫细胞浸润以及一些免疫检查点呈正相关，如CD276（B7-H3）、CD152（CTLA-4）、CD223（LAG-3）和CD274（PD-L1）。单细胞RNA测序分析证实，胶质瘤微环境由具有不同标志物的各种免疫细胞组成。检测到该特征的八个NRGs在几种免疫细胞中表达。QRT-PCR结果证实，这八个特征基因在人类星形胶质细胞和胶质瘤细胞之间均存在差异表达。根据我们的生物信息学分析，这八个NRGs与胶质瘤的免疫微环境相关。这种坏死性凋亡相关基因特征可能为评估胶质瘤预后预测的精确方法提供一种新的思路。
