Department of Neurosurgery, Shanghai Pudong New Area People's Hospital, Shanghai, China.
Key Molecular Lab, Shanghai Pudong New Area People's Hospital, Shanghai, China.
Oxid Med Cell Longev. 2023 Feb 20;2023:2926655. doi: 10.1155/2023/2926655. eCollection 2023.
Glioblastoma (GBM) is one of the most malignant forms of brain cancer, with the extremely lower survival rate. Necroptosis (NCPS) is also one of the most wide types of cell death, and its clinical importance in GBM is not clear.
We first identified necroptotic genes in GBM by single-cell RNA sequencing analysis of our surgical samples and weighted coexpression network analysis (WGNCA) from TCGA GBM data. The cox regression model with least absolute shrinkage and selection operator (LASSO) was used to construct the risk model. Then, KM plot and reactive operation curve (ROC) analysis were used to assess the prediction ability of the model. At last, the infiltrated immune cells and gene mutation profiling were investigated between the high- and low-NCPS groups as well.
The risk model including ten necroptosis-related genes was identified as an independent risk factor for the outcome. In addition, we found that the risk model is correlated with the infiltrated immune cells and tumor mutation burden in GBM. NDUFB2 is identified to be a risk gene in GBM with bioinformatical analysis and in vitro experiment validation.
This risk model of necroptosis-related genes might provide clinical evidence for GBM interventions.
胶质母细胞瘤(GBM)是最恶性的脑癌之一,其生存率极低。细胞坏死性凋亡(NCPS)也是最广泛的细胞死亡类型之一,但其在 GBM 中的临床意义尚不清楚。
我们首先通过对我们的手术样本进行单细胞 RNA 测序分析和来自 TCGA GBM 数据的加权共表达网络分析(WGNCA)来确定 GBM 中的坏死性凋亡基因。然后,使用具有最小绝对收缩和选择算子(LASSO)的 Cox 回归模型构建风险模型。接下来,使用 KM 图和反应操作曲线(ROC)分析来评估模型的预测能力。最后,在高和低 NCPS 组之间研究了浸润免疫细胞和基因突变分析。
确定了包括十个坏死性凋亡相关基因的风险模型,该模型是 GBM 预后的独立危险因素。此外,我们发现该风险模型与 GBM 中浸润的免疫细胞和肿瘤突变负荷相关。生物信息学分析和体外实验验证表明,NDUFB2 是 GBM 中的风险基因。
该坏死性凋亡相关基因的风险模型可能为 GBM 的干预提供临床依据。