DataSheet1_Prognosis and therapeutic significance of IGF-1R-related signaling pathway gene signature in glioma.docx

BackgroundGlioma is the most common cancer of the central nervous system with poor therapeutic response and clinical prognosis. Insulin-like growth factor 1 receptor (IGF-1R) signaling is implicated in tumor development and progression and induces apoptosis of cancer cells following functional inhibition. However, the relationship between the IGF-1R-related signaling pathway genes and glioma prognosis or immunotherapy/chemotherapy is poorly understood.
MethodsLASSO–Cox regression was employed to develop a 16-gene risk signature in the TCGA-GBMLGG cohort, and all patients with glioma were divided into low-risk and high-risk subgroups. The relationships between the risk signature and the tumor immune microenvironment (TIME), immunotherapy response, and chemotherapy response were then analyzed. Immunohistochemistry was used to evaluate the HSP90B1 level in clinical glioma tissue.
ResultsThe gene risk signature yielded superior predictive efficacy in prognosis (5-year area under the curve: 0.875) and can therefore serve as an independent prognostic indicator in patients with glioma. The high-risk subgroup exhibited abundant immune infltration and elevated immune checkpoint gene expression within the TIME. Subsequent analysis revealed that patients in the high-risk subgroup benefited more from chemotherapy. Immunohistochemical analysis confirmed that HSP90B1 was overexpressed in glioma, with significantly higher levels observed in glioblastoma than in astrocytoma or oligodendrocytoma.
ConclusionThe newly identified 16-gene risk signature demonstrates a robust predictive capacity for glioma prognosis and plays a pivotal role in the TIME, thereby offering valuable insights for the exploration of novel biomarkers and targeted therapeutics.

研究背景
胶质瘤是中枢神经系统最常见的恶性肿瘤，其治疗应答不佳且临床预后较差。胰岛素样生长因子1受体（Insulin-like growth factor 1 receptor, IGF-1R）信号通路参与肿瘤的发生与进展，且其功能抑制可诱导癌细胞凋亡。然而，目前对于IGF-1R相关信号通路基因与胶质瘤预后、免疫治疗及化疗之间的关联仍知之甚少。

研究方法
采用LASSO-Cox回归分析在TCGA-GBMLGG队列中构建了16基因风险评分模型，并将所有胶质瘤患者划分为低风险亚组与高风险亚组。随后分析了该风险评分模型与肿瘤免疫微环境（tumor immune microenvironment, TIME）、免疫治疗应答及化疗应答之间的关联。采用免疫组化技术检测临床胶质瘤组织中HSP90B1的表达水平。

研究结果
该基因风险评分模型在预后预测中表现出优异的效能（5年曲线下面积达0.875），可作为胶质瘤患者的独立预后指标。高风险亚组的肿瘤免疫微环境中存在大量免疫细胞浸润，且免疫检查点基因的表达水平显著升高。后续分析显示，高风险亚组患者可从化疗中获得更显著的获益。免疫组化分析证实，HSP90B1在胶质瘤中呈过表达状态，且胶质母细胞瘤中的表达水平显著高于星形细胞瘤与少突胶质细胞瘤。

研究结论
本研究新构建的16基因风险评分模型对胶质瘤预后具有可靠的预测能力，且在肿瘤免疫微环境中发挥关键调控作用，可为新型生物标志物的开发与靶向治疗策略的探索提供重要参考。