Department of Molecular Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, No.119 South 4th Ring Road West, Fengtai District, Beijing, 100070, China.
Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, 100070, China.
Cell Commun Signal. 2020 Jan 6;18(1):2. doi: 10.1186/s12964-019-0492-6.
Gliomas are the most common and malignant brain tumors. The standard therapy is surgery combined with radiotherapy, chemotherapy, and/or other comprehensive methods. However, the emergence of chemoresistance is the main obstacle in treatment and its mechanism is still unclear.
We firstly developed a multi-gene signature by integrated analysis of cancer stem cell and drug resistance related genes. The Chinese Glioma Genome Atlas (CGGA, 325 samples) and The Cancer Genome Atlas (TCGA, 699 samples) datasets were then employed to verify the efficacy of the risk signature and investigate its significance in glioma prognosis. GraphPad Prism, SPSS and R language were used for statistical analysis and graphical work.
This signature could distinguish the prognosis of patients, and patients with high risk score exhibited short survival time. The Cox regression and Nomogram model indicated the independent prognostic performance and high prognostic accuracy of the signature for survival. Combined with a well-known chemotherapy impact factor-MGMT promoter methylation status, this risk signature could further subdivide patients with distinct survival. Functional analysis of associated genes revealed signature-related biological process of cell proliferation, immune response and cell stemness. These mechanisms were confirmed in patient samples.
The signature was an independent and powerful prognostic biomarker in glioma, which would improve risk stratification and provide a more accurate assessment of personalized treatment. Additional file 8 Video abstract.
脑胶质瘤是最常见和最恶性的脑肿瘤。标准疗法是手术联合放疗、化疗和/或其他综合方法。然而，化疗耐药的出现是治疗的主要障碍，其机制尚不清楚。
我们首先通过整合分析癌症干细胞和耐药相关基因，开发了一个多基因特征。然后，利用中国脑胶质瘤基因组图谱（CGGA，325 个样本）和癌症基因组图谱（TCGA，699 个样本）数据集验证风险特征的疗效，并探讨其在脑胶质瘤预后中的意义。GraphPad Prism、SPSS 和 R 语言用于统计分析和图形处理。
该特征可区分患者的预后，高风险评分的患者生存时间短。Cox 回归和 Nomogram 模型表明该特征具有独立的预后表现和对生存的高预测准确性。结合一个著名的化疗影响因素——MGMT 启动子甲基化状态，该风险特征可以进一步细分具有不同生存时间的患者。相关基因的功能分析揭示了特征相关的细胞增殖、免疫反应和细胞干性的生物学过程。这些机制在患者样本中得到了证实。
该特征是脑胶质瘤中一个独立而强大的预后生物标志物，可改善风险分层，并为个性化治疗提供更准确的评估。
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