Department of Neurosurgery, Qilu Hospital of Shandong University and Institute of Brain and Brain-Inspired Science, Shandong University, Shandong, Jinan 250012, China.
Department of Radiation Oncology, Qilu Hospital of Shandong University, Shandong, Jinan 250012, China.
Aging (Albany NY). 2023 Dec 29;15(24):15578-15598. doi: 10.18632/aging.205422.
Glioblastoma multiforme (GBM) is one of the most common and aggressive brain tumors. The microenvironment of GBM is characterized by its highly immunosuppressive nature with infiltration of immunosuppressive cells and the expression levels of cytokines. Efferocytosis is a biological process in which phagocytes remove apoptotic cells and vesicles from tissues. Efferocytosis plays a noticeable function in the formation of immunosuppressive environment. This study aimed to develop an efferocytosis-related prognostic model for GBM. The bioinformatic methods were utilized to analyze the transcriptomic data of GBM and normal samples. Clinical and RNA-seq data were sourced from TCGA database comprising 167 tumor samples and 5 normal samples, and 167 tumor samples for which survival information was available. Transcriptomic data of 1034 normal samples were collected from the Genotype-Tissue Expression (GTEx) database as a control sample supplement to the TCGA database. In the end, 167 tumor samples and 1039 normal samples were obtained for transcriptome analysis. Efferocytosis-related differentially expressed genes (ERDEGs) were obtained by intersecting 7487 differentially expressed genes (DEGs) between GBM and normal samples along with 1189 hub genes. Functional enrichment analyses revealed that ERDEGs were mainly involved in cytokine-mediated immune responses. Moreover, 9 prognosis-related genes (PRGs) were identified by the least absolute shrinkage and selection operator (LASSO) regression analysis, and a prognostic model was therefore developed. The nomogram combining age and risk score could effectively predict GBM patients' prognosis. GBM patients in the high-risk group had higher immune infiltration, invasion, epithelial-mesenchymal transition, angiogenesis scores and poorer tumor purity. In addition, the high-risk group exhibited higher half maximal inhibitory concentration (IC50) values for temozolomide, carmustine, and vincristine. Expression analysis indicated that PRGs were overexpressed in GBM cells. PDIA4 knockdown reduced efferocytosis . In summary, the proposed prognostic model for GBM based on efferocytosis-related genes exhibited a robust performance.
胶质母细胞瘤（GBM）是最常见和侵袭性最强的脑肿瘤之一。GBM 的微环境以其高度免疫抑制特性为特征，包括免疫抑制细胞的浸润和细胞因子的表达水平。吞噬作用是一种生物过程，其中吞噬细胞从组织中清除凋亡细胞和囊泡。吞噬作用在形成免疫抑制环境中起着显著的作用。本研究旨在为 GBM 开发一种与吞噬作用相关的预后模型。利用生物信息学方法分析 GBM 和正常样本的转录组数据。临床和 RNA-seq 数据来自 TCGA 数据库，包括 167 个肿瘤样本和 5 个正常样本，以及 167 个具有生存信息的肿瘤样本。从 TCGA 数据库中获取了 1034 个正常样本的转录组数据，作为对 TCGA 数据库的补充。最终，获得了 167 个肿瘤样本和 1039 个正常样本进行转录组分析。通过 intersecting 7487 个 GBM 和正常样本之间差异表达基因（DEGs）和 1189 个枢纽基因，获得了与吞噬作用相关的差异表达基因（ERDEGs）。功能富集分析表明，ERDEGs 主要参与细胞因子介导的免疫反应。此外，通过最小绝对收缩和选择算子（LASSO）回归分析确定了 9 个预后相关基因（PRGs），因此建立了一个预后模型。结合年龄和风险评分的列线图可以有效地预测 GBM 患者的预后。风险评分较高的 GBM 患者具有更高的免疫浸润、侵袭、上皮-间充质转化、血管生成评分和较差的肿瘤纯度。此外，高风险组的替莫唑胺、卡莫司汀和长春新碱的半最大抑制浓度（IC50）值更高。表达分析表明，PRGs 在 GBM 细胞中过表达。PDIA4 敲低降低了吞噬作用。总之，基于吞噬作用相关基因的 GBM 预后模型表现出良好的性能。
