Numerous studies have highlighted the pivotal role of mitochondria-related genes (MRGs) in the initiation and progression of glioblastoma (GBM). However, the specific contributions of MRGs coding proteins to GBM pathology remain incompletely elucidated. The identification of prognostic MRGs in GBM holds promise for the development of personalized targeted therapies and the enhancement of patient prognosis. We combined differential expression with univariate Cox regression analysis to screen prognosis-associated MRGs in GBM. Based on the nine MRGs, the hazard ratio model was conducted using a multivariate Cox regression algorithm. SHC-related survival, pathway, and immune analyses in GBM cohorts were obtained from the Biomarker Exploration of the Solid Tumor database. The proliferation and migration of U87 cells were measured by CCK-8 and transwell assay. Apoptosis in U87 cells was evaluated using flow cytometry. Confocal microscopy was employed to measure mitochondrial reactive oxygen species (ROS) levels and morphology. The expression levels of SHC1 and other relevant proteins were examined via western blotting. We screened 15 prognosis-associated MRGs and constructed a 9 MRGs-based model. Validation of the model's risk score confirmed its efficacy in predicting the prognosis of patients with GBM. Furthermore, analysis revealed that SHC1, a constituent MRG of the prognostic model, was upregulated and implicated in the progression, migration, and immune infiltration of GBM. In vitro experiments elucidated that p66Shc, the longest isoform of SHC1, modulates mitochondrial ROS production and morphology, consequently promoting the proliferation and migration of U87 cells. The 9 MRGs-based prognostic model could predict the prognosis of GBM. SHC1 was upregulated and correlated with the prognosis of patients by involvement in immune infiltration. Furthermore, in vitro experiments demonstrated that p66Shc promotes U87 cell proliferation and migration by mediating mitochondrial ROS production. Thus, p66Shc may serve as a promising biomarker and therapeutic target for GBM.

大量研究强调了线粒体相关基因（MRG）在胶质母细胞瘤（GBM）发生和进展中的关键作用。然而，MRG 编码蛋白对 GBM 病理学的具体贡献仍未完全阐明。 GBM 中预后 MRG 的鉴定为个性化靶向治疗的开发和改善患者预后带来了希望。我们将差异表达与单变量 Cox 回归分析相结合，筛选 GBM 中与预后相关的 MRG。基于九个 MRG，使用多元 Cox 回归算法建立风险比模型。 GBM 队列中 SHC 相关的生存、通路和免疫分析是从实体瘤数据库的生物标志物探索中获得的。通过CCK-8和Transwell实验检测U87细胞的增殖和迁移。使用流式细胞术评估U87细胞的凋亡。采用共聚焦显微镜测量线粒体活性氧（ROS）水平和形态。通过蛋白质印迹法检查SHC1和其他相关蛋白的表达水平。我们筛选了 15 个与预后相关的 MRG，并构​​建了一个基于 9 个 MRG 的模型。该模型风险评分的验证证实了其在预测 GBM 患者预后方面的功效。此外，分析显示，预后模型的 MRG 组成部分 SHC1 上调，并与 GBM 的进展、迁移和免疫浸润有关。体外实验表明，SHC1 最长的亚型 p66Shc 可以调节线粒体 ROS 的产生和形态，从而促进 U87 细胞的增殖和迁移。基于9个MRG的预后模型可以预测GBM的预后。 SHC1 表达上调，并通过参与免疫浸润与患者的预后相关。此外，体外实验表明 p66Shc 通过介导线粒体 ROS 产生来促进 U87 细胞增殖和迁移。因此，p66Shc 可能作为 GBM 的有前途的生物标志物和治疗靶点。