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Abstract：
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.
摘要：
许多研究强调了线粒体相关基因（MRGs）在胶质母细胞瘤（GBM）的发生和发展中的关键作用。然而,MRGs编码蛋白对GBM病理的具体贡献仍未完全阐明.GBM中预后性MRGs的鉴定为开发个性化靶向治疗和增强患者预后提供了希望。我们将差异表达与单变量Cox回归分析相结合，以筛选GBM中与预后相关的MRGs。根据九个MRG，风险比模型采用多变量Cox回归算法.SHC相关生存,通路,GBM队列中的免疫分析来自实体瘤数据库的生物标志物探索。通过CCK-8和transwell测定法测量U87细胞的增殖和迁移。使用流式细胞术评估U87细胞中的凋亡。使用共聚焦显微镜来测量线粒体活性氧（ROS）水平和形态。通过蛋白质印迹检查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MRGs，并构建了一个基于9个MRGs的模型。模型风险评分的验证证实了其在预测GBM患者预后方面的有效性。此外，分析表明，SHC1是预后模型的一个组成MRG，被上调并参与了进展，迁移,和GBM的免疫浸润。体外实验阐明了p66Shc，SHC1的最长同工型，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MRGs的预后模型可以预测GBM的预后。通过参与免疫浸润，SHC1上调并与患者预后相关。此外，体外实验表明p66Shc通过介导线粒体ROS的产生促进U87细胞增殖和迁移。因此，p66Shc可以作为GBM的有希望的生物标志物和治疗靶标。
