综合分析揭示了与胆固醇代谢相关的特征，用于预测胶质瘤的预后并指导个体化治疗。
Comprehensive analysis reveals cholesterol metabolism-related signature for predicting prognosis and guiding individualized treatment of glioma.
作者信息
Lu Dengfeng, Wang Fei, Yang Yayi, Duan Aojie, Ren Yubo, Feng Yun, Teng Haiying, Chen Zhouqing, Sun Xiaoou, Wang Zhong
机构信息
Department of Neurosurgery & Brain and Nerve Research Laboratory, The First Affiliated Hospital of Soochow University, 188Shizi Street, Suzhou, 215006, Jiangsu Province, China.
Suzhou Medical College of Soochow University, Suzhou, Jiangsu Province, China.
出版信息
Heliyon. 2025 Jan 2;11(1):e41601. doi: 10.1016/j.heliyon.2024.e41601. eCollection 2025 Jan 15.
OBJECTIVE
Gliomas are the most common intracranial tumors with the highest degree of malignancy. Disturbed cholesterol metabolism is one of the key features of many malignant tumors, including gliomas. This study aimed to investigate the significance of cholesterol metabolism-related genes in prognostic prediction and in guiding individualized treatment of patients with gliomas.
METHODS
Transcriptional data and clinicopathological data were obtained from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases. Intraoperative glioma samples retained in our unit and the corresponding clinicopathological information were also collected with the patients' knowledge. Firstly, cholesterol metabolism-related gene signatures (CMRGS) were identified and constructed based on difference analysis, least absolute shrinkage and selection operator (LASSO) regression analysis, and univariate/multivariate COX analysis. Then, the role of CMRGS in predicting the prognosis of gliomas and distinguishing immune landscapes was evaluated by using nomograms, survival analysis, enrichment analysis, and immune-infiltration analysis. Finally, the drug sensitivity of gliomas in different risk groups was evaluated using the oncoPredict algorithm, and potentially sensitive chemotherapeutic and molecular-targeted drugs were identified.
RESULTS
The prognostic CMRGS contained seven genes: APOE, SCD, CXCL16, FABP5, S100A11, TNFRSF12A, and ELOVL2. Patients were divided into high- and low-risk groups based on the median cholesterol metabolic index (CMI). There were significant differences in clinicopathological characteristics and overall survival between groups. COX analysis suggested that CMRGS was an independent risk factor for glioma prognosis and had a better predictive performance than several classical indicators. In addition, GSEA, immune infiltration analysis showed that CMRGS could differentiate the immune landscapes of patients in groups. The reliability of CMRGS was validated in the CGGA cohort and our Gusu cohort. Finally, 14 drugs sensitive to high-risk patients and 16 drugs sensitive to low-risk patients were identified.
CONCLUSION
The CMRGS reliably predicts glioma prognosis in multiple cohorts and may be useful in guiding individualized treatment.
目的
胶质瘤是最常见且恶性程度最高的颅内肿瘤。胆固醇代谢紊乱是包括胶质瘤在内的许多恶性肿瘤的关键特征之一。本研究旨在探讨胆固醇代谢相关基因在胶质瘤患者预后预测及指导个体化治疗中的意义。
方法
从癌症基因组图谱（TCGA）和中国胶质瘤基因组图谱（CGGA）数据库获取转录数据和临床病理数据。在患者知情的情况下，收集本单位留存的术中胶质瘤样本及相应的临床病理信息。首先，基于差异分析、最小绝对收缩和选择算子（LASSO）回归分析以及单因素/多因素COX分析，识别并构建胆固醇代谢相关基因特征（CMRGS）。然后，通过列线图、生存分析、富集分析和免疫浸润分析，评估CMRGS在预测胶质瘤预后及区分免疫格局中的作用。最后，使用oncoPredict算法评估不同风险组胶质瘤的药物敏感性，确定潜在敏感的化疗药物和分子靶向药物。
结果
预后CMRGS包含7个基因：APOE、SCD、CXCL16、FABP5、S100A11、TNFRSF12A和ELOVL2。根据胆固醇代谢指数（CMI）中位数将患者分为高风险组和低风险组。两组间临床病理特征和总生存期存在显著差异。COX分析表明，CMRGS是胶质瘤预后的独立危险因素，其预测性能优于几个经典指标。此外，基因集富集分析（GSEA）、免疫浸润分析表明，CMRGS可区分不同组患者的免疫格局。CMRGS的可靠性在CGGA队列和我们的姑苏队列中得到验证。最后，确定了14种对高风险患者敏感的药物和16种对低风险患者敏感的药物。
结论
CMRGS在多个队列中可靠地预测胶质瘤预后，可能有助于指导个体化治疗。
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