Department of Neurosurgery, The First Affiliated Hospital of Hainan Medical University, Haikou, Hainan, China.
Department of Geriatrics Center, The First Affiliated Hospital of Hainan Medical University, Haikou, Hainan, China.
Front Immunol. 2024 Oct 30;15:1462064. doi: 10.3389/fimmu.2024.1462064. eCollection 2024.
To investigate the association between disulfidptosis-related genes (DFRGs) and patient prognosis, while concurrently identifying potential therapeutic targets in glioblastoma (GBM).
We retrieved RNA sequencing data and clinical characteristics of GBM patients from the TCGA database. We found there was a total of 6 distinct clusters in GBM, which was identified by the t-SNE and UMAP dimension reduction analysis. Prognostically significant genes in GBM were identified using the limma package, coupled with univariate Cox regression analysis. Machine learning algorithms were then applied to identify central genes. The CIBERSORT algorithm was utilized to assess the immunological landscape across different GBM subtypes. and experiments were conducted to investigate the role of SPAG4 in regulating the proliferation, invasion of GBM, and its effects within the immune microenvironment.
23 genes, termed DFRGs, were successfully identified, demonstrating substantial potential for establishing a prognostic model for GBM. Single cell analysis revealed a significant correlation between DFRGs and the progression of GBM. Utilizing individual risk scores derived from this model enabled the stratification of patients into two distinct risk groups, revealing significant variations in immune infiltration patterns and responses to immunotherapy. Utilizing the random survival forests algorithm, SPAG4 was identified as the gene with the highest prognostic significance within our model. studies have elucidated SPAG4's significant role in GBM pathogenesis, potentially through the regulation of fatty acid metabolism pathways. Our investigations using a subcutaneous xenograft model have confirmed SPAG4's influence on tumor growth and its capacity to modulate the immune microenvironment. Advanced research hints that SPAG4 might achieve immune evasion by increasing CD47 expression, consequently reducing phagocytosis.
These findings highlight SPAG4 as a potential GBM therapeutic target and emphasize the complexity of the immune microenvironment in GBM progression.
研究二硫键相关基因（DFRGs）与胶质母细胞瘤（GBM）患者预后的关系，同时寻找潜在的治疗靶点。
我们从 TCGA 数据库中检索了 GBM 患者的 RNA 测序数据和临床特征。通过 t-SNE 和 UMAP 降维分析，我们发现 GBM 共有 6 个不同的簇。使用 limma 包结合单因素 Cox 回归分析确定 GBM 中具有预后意义的基因。然后应用机器学习算法识别核心基因。利用 CIBERSORT 算法评估不同 GBM 亚型的免疫景观。进行了 和 实验，以研究 SPAG4 在调节 GBM 增殖、侵袭中的作用及其在免疫微环境中的作用。
成功鉴定出 23 个基因，称为 DFRGs，它们具有为 GBM 建立预后模型的巨大潜力。单细胞分析显示 DFRGs 与 GBM 的进展之间存在显著相关性。利用该模型得出的个体风险评分可将患者分为两个不同的风险组，揭示了免疫浸润模式和对免疫治疗反应的显著差异。利用随机生存森林算法，确定 SPAG4 是我们模型中具有最高预后意义的基因。进一步的研究阐明了 SPAG4 在 GBM 发病机制中的重要作用，可能是通过调节脂肪酸代谢途径。我们使用皮下异种移植模型的研究证实了 SPAG4 对肿瘤生长的影响及其调节免疫微环境的能力。深入的研究提示 SPAG4 可能通过增加 CD47 的表达来实现免疫逃逸，从而减少吞噬作用。
这些发现强调了 SPAG4 作为 GBM 治疗靶点的潜力，并强调了免疫微环境在 GBM 进展中的复杂性。
