Department of Neurosurgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
Department of Neonatology, Third Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
J Mol Neurosci. 2023 Aug;73(7-8):608-627. doi: 10.1007/s12031-023-02142-x. Epub 2023 Jul 25.
Inflammatory response plays a crucial role in the development and progression of gliomas. Whereas the prognostic esteem of inflammatory response-related genes has never been comprehensively explored in glioma, the RNA-seq information and clinical data of patients with glioma were extracted from TCGA, CGGA, and Rembrandt databases. The differentially expressed genes (DEGs) were picked out between glioma tissue and non-tumor brain tissue (NBT). Then, the least absolute shrinkage and selection operator (LASSO) regression analysis was performed to construct the prognostic signature in the TCGA cohort and verified in other cohorts. Kaplan-Meier survival analyses were conducted to compare the overall survival (OS) between the high and low-risk groups. Univariate and multivariate Cox analyses were subsequently used to confirm the independent prognostic factors of OS, and then, the nomogram was established based them. Furthermore, immune infiltration, immune checkpoints, and immunotherapy were also probed and compared between high and low-risk groups. The four genes were also analyzed by qRT-PCR, immunohistochemistry, and western blot trials between glioma tissue and NBT. The 39 DEGs were identified between glioma tissue and NBT, of which 31 genes are associated to the prognosis of glioma. The 8 optimal inflammatory response-related genes were selected to construct the prognostic inflammatory response-related signature (IRRS) through the LASSO regression. The effectiveness of the IRRS was verified in the TCGA, CGGA, and Rembrandt cohorts. Meanwhile, a nomogram with better accuracy was established to predict OS based on the independent prognostic factors. The IRRS was highly correlated with clinicopathological features, immune infiltration, and genomic alterations in glioma patients. In addition, four selective genes also verified the difference between glioma tissue and NBT. A novel prognostic signature was associated with the prognosis, immune infiltration, and immunotherapy effect in patients with gliomas. Thus, this study could provide a perspective for glioma prognosis and treatment.
炎症反应在神经胶质瘤的发生和发展中起着至关重要的作用。然而,炎症反应相关基因的预后评估在神经胶质瘤中从未被全面探索过,本研究从 TCGA、CGGA 和 Rembrandt 数据库中提取了神经胶质瘤患者的 RNA-seq 信息和临床数据。在肿瘤组织和非肿瘤脑组织(NBT)之间筛选出差异表达基因(DEGs)。然后,在 TCGA 队列中进行最小绝对收缩和选择算子(LASSO)回归分析,构建预后模型,并在其他队列中进行验证。Kaplan-Meier 生存分析比较了高低风险组之间的总生存期(OS)。随后进行单因素和多因素 Cox 分析,以确定 OS 的独立预后因素,并基于这些因素建立列线图。此外,还对高低风险组之间的免疫浸润、免疫检查点和免疫治疗进行了探讨和比较。通过 qRT-PCR、免疫组织化学和 Western blot 试验对胶质瘤组织和 NBT 之间的这四个基因进行了分析。在胶质瘤组织和 NBT 之间鉴定出 39 个 DEGs,其中 31 个基因与神经胶质瘤的预后相关。通过 LASSO 回归选择 8 个最佳的炎症反应相关基因构建预后炎症反应相关特征(IRRS)。该模型在 TCGA、CGGA 和 Rembrandt 队列中得到了验证。同时,基于独立的预后因素,建立了一个预测 OS 的列线图,具有更高的准确性。IRRS 与神经胶质瘤患者的临床病理特征、免疫浸润和基因组改变高度相关。此外,四个选择基因也验证了胶质瘤组织和 NBT 之间的差异。一种新的预后标志物与神经胶质瘤患者的预后、免疫浸润和免疫治疗效果相关。因此,本研究为神经胶质瘤的预后和治疗提供了新的视角。