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基于泛凋亡的多形性胶质母细胞瘤生存与免疫预测特征

英文原题:A PANoptosis-Based Signature for Survival and Immune Predication in Glioblastoma Multiforme.

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A PANoptosis-Based Signature for Survival and Immune Predication in Glioblastoma Multiforme.

PubMed 2025/05/07(内容时间) Ann Clin Transl Neurol Q2 · IF 3.9(JCR 2025)

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研究概要

我们的数据展示了 PARGs 在 GBM 中的预后价值,并为 GBM 的发病机制和免疫治疗提供了新见解。

中文摘要

PAN凋亡是由细胞焦亡、凋亡和程序性坏死共同构成的一种全面细胞死亡概念。本研究旨在探讨PAN凋亡相关基因(PARG)在胶质母细胞瘤(GBM)中的临床意义。

从XENA数据库下载GBM表达谱作为训练数据集,构建基于差异表达PARG(DE-PARG)的风险评分(RS)模型;并在CGGA数据库和GSE108474中采用Kaplan-Meier(KM)曲线及受试者工作特征(ROC)曲线验证其预后预测作用。同时筛选独立预后临床因素,并通过列线图模型评估其预后预测能力。此外,分析关键DE-PARG与免疫细胞浸润及化疗药物敏感性的关系。

构建的RS模型包含5个DE-PARG:NOD2、NLRP2、NLRP7、GATA3和TERT。ROC和KM曲线证实,该RS预后模型在XENA数据库和GSE108474中均具有良好预测能力。筛选出包括化疗、药物治疗和RS模型在内的3项独立预后因素。列线图模型显示,RS对生存概率贡献最大,其次为化疗和药物治疗。高、低风险组的记忆B细胞、静息NK细胞和M1型巨噬细胞存在显著差异。与免疫检查点治疗无应答组相比,应答组中被划分为低风险组的患者比例较高。高、低风险组对顺铂、吉非替尼和伏立诺他这3种药物的敏感性存在显著差异。解读:我们的数据表明PARG在GBM中具有预后价值,并为理解GBM发病机制和免疫治疗提供了新见解。

展开英文摘要原文

PANoptosis is a concept of total cell death characterized by pyroptosis, apoptosis, and necroptosis. We aimed to explore the clinical significance of PANoptosis-related genes (PARGs) in glioblastoma multiforme (GBM).

Expression profiles of GBM were downloaded from the XENA database as a training dataset to construct a differentially expressed PARGs (DE-PARGs)-based risk score (RS) model, and the prognostic prediction role was validated in the CGGA database and GSE108474 using Kaplan-Meier (KM) curve and receiver operating characteristic (ROC) curve. Meanwhile, independent prognostic clinical factors were screened, and their prognosis predictive activity was evaluated by a nomogram model. Furthermore, the relationships between key DE-PARGs and immune cell infiltration, as well as chemotherapy drug sensitivity were analyzed.

The RS model consisting of five DE-PARGs was constructed, including NOD2, NLRP2, NLRP7, GATA3, and TERT. ROC and KM curves confirmed the good potency of the RS prognostic model both in XENA database and GSE108474. Three clinical prognostic factors, including chemotherapy, pharmaceutical therapy, and RS model, were selected as individual prognostic factors. The nomogram model showed RS contributed most to survival probability, followed by chemotherapy and pharmaceutical therapy. In high- and low-risk groups, B cell memory, NK cell resting, and macrophage M1 had significant differences. As compared with the immune checkpoint therapy non-responder group, the responder involved a higher ratio of patients sub-grouped into the low-risk group. Three drugs between high- and low-risk groups had significant differences, including Cisplatin, Gefitinib, and Vorinostat. INTERPRETATION: Our data exhibit the prognostic value of PARGs in GBM and offer new insights for GBM pathogenesis and immune treatment.

论文信息

作者
Yang J、Lin D、Liu D、Zhang D、Wang H
单位
Department of Neurosurgery, Beijing Luhe Hospital, Capital Medical University, Beijing, China.China
期刊
Annals of clinical and translational neurology2025 Jul
原文标识
PubMed 40333895 · DOI 10.1002/acn3.70066