Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China.
Laboratory Animal Department, Kunming Medical University, Kunming, 650031, Yunnan, China.
Sci Rep. 2024 Feb 23;14(1):4478. doi: 10.1038/s41598-024-51973-0.
Glycosylation is currently considered to be an important hallmark of cancer. However, the characterization of glycosylation-related gene sets has not been comprehensively analyzed in glioma, and the relationship between glycosylation-related genes and glioma prognosis has not been elucidated. Here, we firstly found that the glycosylation-related differentially expressed genes in glioma patients were engaged in biological functions related to glioma progression revealed by enrichment analysis. Then seven glycosylation genes (BGN, C1GALT1C1L, GALNT13, SDC1, SERPINA1, SPTBN5 and TUBA1C) associated with glioma prognosis were screened out by consensus clustering, principal component analysis, Lasso regression, and univariate and multivariate Cox regression analysis using the TCGA-GTEx database. A glycosylation-related prognostic signature was developed and validated using CGGA database data with significantly accurate prediction on glioma prognosis, which showed better capacity to predict the prognosis of glioma patients than clinicopathological factors do. GSEA enrichment analysis based on the risk score further revealed that patients in the high-risk group were involved in immune-related pathways such as cytokine signaling, inflammatory responses, and immune regulation, as well as glycan synthesis and metabolic function. Immuno-correlation analysis revealed that a variety of immune cell infiltrations, such as Macrophage, activated dendritic cell, Regulatory T cell (Treg), and Natural killer cell, were increased in the high-risk group. Moreover, functional experiments were performed to evaluate the roles of risk genes in the cell viability and cell number of glioma U87 and U251 cells, which demonstrated that silencing BGN, SDC1, SERPINA1, TUBA1C, C1GALT1C1L and SPTBN5 could inhibit the growth and viability of glioma cells. These findings strengthened the prognostic potentials of our predictive signature in glioma. In conclusion, this prognostic model composed of 7 glycosylation-related genes distinguishes well the high-risk glioma patients, which might potentially serve as caner biomarkers for disease diagnosis and treatment.
糖基化目前被认为是癌症的一个重要标志。然而，糖基化相关基因集在神经胶质瘤中的特征尚未得到全面分析，糖基化相关基因与神经胶质瘤预后之间的关系也尚未阐明。在这里，我们首先发现，通过富集分析揭示了神经胶质瘤患者中糖基化差异表达基因参与了与神经胶质瘤进展相关的生物学功能。然后，我们使用 TCGA-GTEx 数据库通过共识聚类、主成分分析、Lasso 回归以及单变量和多变量 Cox 回归分析筛选出与神经胶质瘤预后相关的 7 个糖基化基因（BGN、C1GALT1C1L、GALNT13、SDC1、SERPINA1、SPTBN5 和 TUBA1C）。使用 CGGA 数据库数据开发并验证了一个糖基化相关的预后标志物，该标志物对神经胶质瘤预后的预测具有显著的准确性，其预测神经胶质瘤患者预后的能力优于临床病理因素。基于风险评分的 GSEA 富集分析进一步表明，高风险组患者参与了免疫相关途径，如细胞因子信号、炎症反应和免疫调节，以及聚糖合成和代谢功能。免疫相关性分析表明，高风险组中多种免疫细胞浸润增加，如巨噬细胞、激活的树突状细胞、调节性 T 细胞（Treg）和自然杀伤细胞。此外，功能实验评估了风险基因在神经胶质瘤 U87 和 U251 细胞活力和细胞数量中的作用，结果表明沉默 BGN、SDC1、SERPINA1、TUBA1C、C1GALT1C1L 和 SPTBN5 可抑制神经胶质瘤细胞的生长和活力。这些发现增强了我们在神经胶质瘤中预测特征的预后潜力。总之，由 7 个糖基化相关基因组成的这个预后模型能够很好地区分高危神经胶质瘤患者，这可能为疾病诊断和治疗提供潜在的生物标志物。
