背景:胶质瘤是中枢神经系统最常见的原发性恶性肿瘤,neddylation可能是治疗神经胶质瘤的潜在靶点。我们的研究分析了Neddylation在不同病理类型的神经胶质瘤中的潜在作用及其与免疫治疗的相关性。
方法:模型构建所需的基因来自现有文献,并从TCGA和CGGA数据库中提取其表达数据。LASSO回归分析用于鉴定TCGA中与胶质瘤患者预后相关的基因并建立临床预后模型。使用CCK-8测定和transwell测定评估了hub基因干预后神经胶质瘤细胞系的生物学变化。使用Western印迹在各种细胞系中验证模型构建中涉及的基因。我们进行了分析,以检查模型评分和临床数据之间的相关性,肿瘤微环境,和免疫检查点。此外,我们研究了不同群体之间分子功能和机制的潜在差异。
结果:我们从Reactome数据库中鉴定了249个基因,并分析了它们在TCGA和CGGA数据库中的表达谱。使用LASSO-Cox后,四个基因(BRCA1,BIRC5,FBXL16和KLHL25,p<0.05)具有显着相关性。我们选择FBXL16进行体外实验验证。FBXL16过表达后,扩散,迁移,胶质瘤细胞系的侵袭能力均下降。然后,我们构建了神经胶质瘤的NEDD指数。列线图表明该模型可以作为独立的预后标志物。对肿瘤微环境和免疫检查点的分析表明,NEDD指数还与免疫细胞浸润和各种免疫检查点的表达水平相关。
结论:NEDD指数可以作为预测胶质瘤患者预后的实用工具,它与免疫细胞浸润和免疫检查点的表达水平有关。
BACKGROUND: Gliomas are the most common primary malignant tumours of the central nervous system, and neddylation may be a potential target for the treatment of gliomas. Our study analysed neddylation\'s potential role in gliomas of different pathological types and its correlation with immunotherapy.
METHODS: Genes required for model construction were sourced from existing literature, and their expression data were extracted from the TCGA and CGGA databases. LASSO regression was employed to identify genes associated with the prognosis of glioma patients in TCGA and to establish a clinical prognostic model. Biological changes in glioma cell lines following intervention with hub genes were evaluated using the CCK-8 assay and transwell assay. The genes implicated in the model construction were validated across various cell lines using Western blot. We conducted analyses to examine correlations between model scores and clinical data, tumor microenvironments, and immune checkpoints. Furthermore, we investigated potential differences in molecular functions and mechanisms among different groups.
RESULTS: We identified 249 genes from the Reactome database and analysed their expression profiles in the TCGA and CGGA databases. After using LASSO-Cox, four genes (BRCA1, BIRC5, FBXL16 and KLHL25, p < 0.05) with significant correlations were identified. We selected FBXL16 for validation in in vitro experiments. Following FBXL16 overexpression, the proliferation, migration, and invasion abilities of glioma cell lines all showed a decrease. Then, we constructed the NEDD Index for gliomas. The nomogram indicated that this model could serve as an independent prognostic marker. Analysis of the tumour microenvironment and immune checkpoints revealed that the NEDD index was also correlated with immune cell infiltration and the expression levels of various immune checkpoints.
CONCLUSIONS: The NEDD index can serve as a practical tool for predicting the prognosis of glioma patients, and it is correlated with immune cell infiltration and the expression levels of immune checkpoints.