Wang Xingqiao, Bian Yusong, Chen Weiguang
Emergency Department, Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai, Shandong, China.
Front Immunol. 2024 Dec 12;15:1504629. doi: 10.3389/fimmu.2024.1504629. eCollection 2024.
Subarachnoid hemorrhage (SAH) and tumorigenesis share numerous biological complexities; nevertheless, the specific gene expression profiles and underlying mechanisms remain poorly understood. This study aims to identify differentially expressed genes (DEGs) that could serve as biomarkers for diagnosis and prognosis.
Gene expression datasets (GSE122063, GSE13353, GSE161870) were analyzed using machine learning algorithms and logistic regression to identify DEGs associated with both SAH and tumorigenesis. Lasso regression and receiver operating characteristic (ROC) curve analysis were employed to evaluate the classification accuracy of these genes. Validation of critical DEGs was performed through pan-cancer analysis and experimental studies, focusing on the role of DOK3 in modulating inflammation and oxidative stress in U251MG glioblastoma and BV2 microglia cells.
Fifteen common DEGs were identified, with DOK3 and PAPOLA highlighted as crucial genes implicated in SAH and neurodegenerative processes. Experimental validation demonstrated that DOK3 overexpression significantly reduced pro-inflammatory cytokine levels and oxidative stress markers while enhancing antioxidant enzyme activity. Additionally, DOK3 influenced tumorigenic processes such as apoptosis, cell cycle regulation, and proliferation, effectively mitigating LPS-induced cytotoxicity and inflammation in BV2 microglial cells.
DOK3 and PAPOLA play critical roles in both SAH and related neurodegeneration, presenting themselves as potential prognostic biomarkers and therapeutic targets. Notably, DOK3 exhibits potential as an antitumor agent with anti-inflammatory and antioxidative properties, offering therapeutic benefits for both cancer and neuroinflammatory conditions.
蛛网膜下腔出血(SAH)和肿瘤发生具有众多生物学复杂性;然而,具体的基因表达谱和潜在机制仍知之甚少。本研究旨在鉴定可作为诊断和预后生物标志物的差异表达基因(DEGs)。
使用机器学习算法和逻辑回归分析基因表达数据集(GSE122063、GSE13353、GSE161870),以鉴定与SAH和肿瘤发生相关的DEGs。采用套索回归和受试者工作特征(ROC)曲线分析来评估这些基因的分类准确性。通过泛癌分析和实验研究对关键DEGs进行验证,重点关注DOK3在调节U251MG胶质母细胞瘤和BV2小胶质细胞炎症和氧化应激中的作用。
鉴定出15个常见的DEGs,其中DOK3和PAPOLA被突出显示为参与SAH和神经退行性过程的关键基因。实验验证表明,DOK3过表达显著降低促炎细胞因子水平和氧化应激标志物,同时增强抗氧化酶活性。此外,DOK3影响细胞凋亡、细胞周期调控和增殖等肿瘤发生过程,有效减轻BV2小胶质细胞中脂多糖诱导的细胞毒性和炎症。
DOK3和PAPOLA在SAH和相关神经退行性变中起关键作用,可作为潜在的预后生物标志物和治疗靶点。值得注意的是,DOK3具有作为具有抗炎和抗氧化特性的抗肿瘤药物的潜力,为癌症和神经炎症性疾病提供治疗益处。