Xia Minqi, Tong Shiao, Gao Ling
Department of Endocrinology & Metabolism, Renmin Hospital of Wuhan University, Wuhan 430060, China.
Department of Neurosurgery, Renmin Hospital of Wuhan University, Wuhan 430060, China.
Biomedicines. 2024 Jan 1;12(1):92. doi: 10.3390/biomedicines12010092.
Tumor cells are commonly exposed to a hypoxic environment, which can easily induce the epithelial-mesenchymal transition (EMT) of tumor cells, further affecting tumor proliferation, invasion, metastasis, and drug resistance. However, the predictive role of hypoxia and EMT-related genes in glioblastoma (GBM) has not been investigated.
Intersection genes were identified by weighted correlation network analysis (WGCNA) and differential expression analyses, and a risk model was further constructed by LASSO and Cox analyses. Clinical, immune infiltration, tumor mutation, drug treatment, and enrichment profiles were analyzed based on the risk model. The expression level of the gene was tested using RT-PCR, immunohistochemistry, and immunofluorescence. CCK8 and EdU were employed to determine the GBM cells' capacity for proliferation while the migration and invasion ability were detected by a wound healing assay and transwell assay, respectively.
Based on the GBM data of the TCGA and GTEx databases, 58 intersection genes were identified, and a risk model was constructed. The model was verified in the CGGA cohort, and its accuracy was confirmed by the ROC curve (AUC = 0.807). After combining clinical subgroups, univariate and multivariate Cox regression analyses showed that risk score and age were independent risk factors for GBM patients. Furthermore, our subsequent analysis of immune infiltration, tumor mutation, and drug treatment showed that risk score and high- and low-risk groups were associated with multiple immune cells, mutated genes, and drugs. Enrichment analysis indicated that the differences between high- and low-risk groups were manifested in tumor-related pathways, including the PI3K-AKT and JAK-STAT pathways. Finally, in vivo experiments proved that the hypoxia environment promoted the expression of , and knockdown reduced the proliferation, migration, and EMT of GBM cells induced by hypoxia.
Our novel prognostic correlation model provided more potential treatment strategies for GBM patients.
肿瘤细胞通常处于缺氧环境中，这很容易诱导肿瘤细胞发生上皮-间质转化（EMT），进而影响肿瘤的增殖、侵袭、转移及耐药性。然而，缺氧及EMT相关基因在胶质母细胞瘤（GBM）中的预测作用尚未得到研究。
通过加权基因共表达网络分析（WGCNA）和差异表达分析鉴定交集基因，并进一步通过LASSO和Cox分析构建风险模型。基于该风险模型分析临床、免疫浸润、肿瘤突变、药物治疗及富集谱。采用RT-PCR、免疫组织化学和免疫荧光检测该基因的表达水平。使用CCK8和EdU检测GBM细胞的增殖能力，同时分别通过伤口愈合实验和Transwell实验检测其迁移和侵袭能力。
基于TCGA和GTEx数据库的GBM数据，鉴定出58个交集基因，并构建了风险模型。该模型在CGGA队列中得到验证，ROC曲线证实了其准确性（AUC = 0.807）。结合临床亚组后，单因素和多因素Cox回归分析表明，风险评分和年龄是GBM患者的独立危险因素。此外，我们随后对免疫浸润、肿瘤突变和药物治疗的分析表明，风险评分及高、低风险组与多种免疫细胞、突变基因和药物相关。富集分析表明，高、低风险组之间的差异体现在肿瘤相关通路中，包括PI3K-AKT和JAK-STAT通路。最后，体内实验证明缺氧环境促进了该基因的表达，而敲低该基因可降低缺氧诱导的GBM细胞的增殖、迁移和EMT。
我们的新型预后相关模型为GBM患者提供了更多潜在的治疗策略。
