Department of Neuro-Oncology, Cancer Center, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Cancer Med. 2023 Nov;12(21):20639-20654. doi: 10.1002/cam4.6627. Epub 2023 Oct 21.
Glioblastoma (GBM), the most common primary malignant brain tumor, has a poor prognosis, with a median survival of only 14.6 months. The Warburg effect is an abnormal energy metabolism, which is the main cause of the acidic tumor microenvironment. This study explored the role of the Warburg effect in the prognosis and immune microenvironment of GBM.
A prognostic risk score model of Warburg effect-related genes (Warburg effect signature) was constructed using GBM cohort data from The Cancer Genome Atlas. Cox analysis was performed to identify independent prognostic factors. Next, the nomogram was built to predict the prognosis for GBM patients. Finally, the drug sensitivity analysis was utilized to find the drugs that specifically target Warburg effect-related genes.
Age, radiotherapy, chemotherapy, and WRGs score were confirmed as independent prognostic factors for GBM by Cox analyses. The C-index (0.633 for the training set and 0.696 for the validation set) and area under curve (>0.7) indicated that the nomogram exhibited excellent performance. The calibration curve also indicates excellent consistency of the nomogram between predictions and actual observations. In addition, immune microenvironment analysis revealed that patients with high WRGs scores had high immunosuppressive scores, a high abundance of immunosuppressive cells, and a low response to immunotherapy. The Cell Counting Kit-8 assays showed that the drugs targeting Warburg effect-related genes could inhibit the GBM cells growth in vitro.
Our research showed that the Warburg effect is connected with the prognosis and immune microenvironment of GBM. Therefore, targeting Warburg effect-related genes may provide novel therapeutic options.
胶质母细胞瘤（GBM）是最常见的原发性恶性脑肿瘤，预后差，中位生存期仅为 14.6 个月。沃伯格效应是一种异常的能量代谢，是酸性肿瘤微环境的主要原因。本研究探讨了沃伯格效应在 GBM 预后和免疫微环境中的作用。
使用来自癌症基因组图谱的 GBM 队列数据构建了与沃伯格效应相关基因的预后风险评分模型（沃伯格效应特征）。进行 Cox 分析以确定独立的预后因素。接下来，构建了诺莫图以预测 GBM 患者的预后。最后，进行药物敏感性分析以找到专门针对沃伯格效应相关基因的药物。
Cox 分析证实年龄、放疗、化疗和 WRGs 评分是 GBM 的独立预后因素。C 指数（训练集为 0.633，验证集为 0.696）和曲线下面积（>0.7）表明该诺莫图具有优异的性能。校准曲线也表明了该诺莫图在预测和实际观察之间的一致性很好。此外，免疫微环境分析表明，WRGs 评分高的患者具有高免疫抑制评分、高免疫抑制细胞丰度和对免疫治疗反应差。细胞计数试剂盒-8 测定表明，靶向沃伯格效应相关基因的药物可以抑制 GBM 细胞的体外生长。
我们的研究表明，沃伯格效应与 GBM 的预后和免疫微环境有关。因此，靶向沃伯格效应相关基因可能为新的治疗选择提供了依据。
