Glioblastoma (GBM) is the most aggressive and heterogeneous malignant primary tumor of the central nervous system in adults, resulting in a 5-year survival rate of 9%. Radiotherapy (RT) is one of the standard therapies, but the resistance to RT is still dismal by reducing the therapy efficiency. Cumulative evidence suggests that patient–derived glioma stem-like cells (GSCs) play important roles in tumor maintenance and response to chemotherapy and radiation. Using radiation clonogeneic experiment on GSCs, a set of signatures was derived by the differential methylation pattern of RT sensitive vs. resistant GSCs. When applied to the GBM cases that received upfront RT, survival by methylation class in this subset was significantly diffident, suggesting this signature is predictive of clinical RT response. However, it is still a urgent need to explore the underlying biological mechanisms. The first aim of this project is to explore the key biological driver events and pathways that are associated with the methylation signatures. The second aim is to study the identify the key CpG methylation cites which are predictive to RT by integrating multiple molecular datasets. Furthermore, we are trying to identify the association between the methylation signatures and the GBM recurrence. Our study will benefit to decipher the potential biological mechanism of radioresistance of GBM, personalizing RT treatment of GBM patients and provides insights into RT sensitivity phenotypes.
胶质母细胞瘤(Glioblastoma,GBM)是一类具有高度异质性的中枢神经系统恶性肿瘤,患者5年生存率仅为9%。放射治疗是GBM最重要治疗方法之一,但极易产生的放疗抵抗降低了治疗的有效性。胶质瘤干细胞(Glioma Stem-like Cells,GSC)已被证实在产生放疗抵抗中扮演重要角色。申请人前期研究表明:具有放疗应答差异的GSC间存在显著的特定区域甲基化差异,进一步的大样本研究表明这些新发现的异常甲基化区域能有效预测GBM患者的放疗预后,但其生物学机制有待明确。本课题拟首先探明这些异常甲基化区域影响的关键生物学途径和驱动事件(体突变、扩增、缺失等),接着整合多分子水平数据精细识别与放疗预后关联的关键甲基化位点,在此基础上进一步研究特定区域甲基化水平异常对GBM放疗后复发的影响。本课题的研究成果将进一步阐明GBM放疗抵抗的生物学机制,为基于基因组水平的个体化放疗提供崭新途径。
胶质母细胞瘤(Glioblastoma, GBM)患者5年生存率仅为9%。放射治疗是GBM最重要治疗方法之一,但极易产生的放疗抵抗降低了治疗的有效性。胶质瘤干细胞(Glioma Stem-like Cells, GSC)已被证实在产生放疗抵抗中扮演重要角色。本项目通过构建胶质瘤干细胞放疗模型,利用细胞克隆形成实验识别放疗抵抗和放疗敏感细胞系,并在此基础上解析肿瘤放疗敏感的关键DNA甲基化分子特征,这些分子特征构建的预测模型可以有效评估患者放疗预后。在此基础上,得到以下主要研究结论:1. 通过联合GBM样本的基因组数据分析,显示基因组不稳定性与肿瘤放疗应答状态相关。2. 携带更高的肿瘤突变负荷(Tumor mutation burden, TMB)或拷贝数变异的肿瘤对放射更为敏感。3. 放疗抵抗的肿瘤组织中M2型巨噬细胞等免疫细胞浸润比例显著提高,表明肿瘤微环境在肿瘤放疗抵抗中扮演重要角色。
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数据更新时间:2023-05-31
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