Implications of a novel glioblastoma classification defined by miR-21-Sox2 status

描述(申请人提供)：多形性胶质母细胞瘤(GBM)是最常见和最具侵袭性的人脑肿瘤。然而，尽管有几十年的基础科学和临床研究，对于GBM患者来说，还没有一个快速、广泛使用的预后标准(除了 非分子参数，如年龄；低存活率与高龄相关)，而GBM患者的结局仍然令人沮丧，平均生存时间仅为15个月。因此，新的创新的、基于机制的方法对于GBM患者的管理是必要的。通过生物信息学和生化研究，我们在GBM患者和患者胶质母细胞瘤来源的干细胞中发现了一个基于新的miR-21-Sox2轴的新调节轴。这个轴似乎将GBM患者分为不同的类别。基于这些结果，我们建议证明或反驳新的中心假设，即我们基于miR-21-Sox2轴的GBM分类可以为GBM患者产生新的预后方法，并且这一机制也可以用于开发更有效、毒性较低的针对GBM患者的个体化治疗方案 公共卫生相关性：多形性胶质母细胞瘤(GBM)是最常见的胶质瘤形式，其患者的平均生存期约为15个月，目前尚无有效的治疗方法。如果这项拨款申请的特定目标完成，我们不仅将了解基底膜肿瘤发生的新机制轴，而且这些信息还将在检测、预测患者结局和设计比目前使用的更有效的治疗方法方面产生潜在的新的和非传统的翻译影响。

DESCRIPTION (provided by applicant): Glioblastoma multiforme (GBM) is the most common and most aggressive human brain tumor. However, despite decades of basic science and clinical research, there is no quick, widely used prognostic criterion for GBM patients (except for non-molecular parameters, such as age; lower survival is correlated with older age) and the outcome for GBM patients remains dismal, with an average survival duration of only 15 months. Thus, new innovative, mechanism-based approaches are necessary for the management of patients with GBM. We have discovered a new regulatory axis based on a novel miR-21-Sox2 axis in GBM patients and patient glioblastoma-derived stem cells through bioinformatic and biochemical studies. This axis appears to classify GBM patients into distinct classes. Based on these results, here we propose to prove or disprove the novel central hypothesis that our GBM classification based on the miR-21-Sox2 axis can produce new prognostic approaches for GBM patients and that this mechanism can also be utilized to develop more effective, less toxic "personalized" treatment regimens for GBM patient care PUBLIC HEALTH RELEVANCE: The mean survival duration of patients with glioblastoma multiforme (GBM), the most common form of glioma, is approximately 15 months and there is no effective therapy. If the Specific Aims of this grant application are completed, not only we wil have the understanding of a new mechanistic axis of GBM tumorigenesis, but this information will also have potentially novel and unconventional translational impact in terms of detection, predict patient outcome and design more effective therapeutic approaches than what is currently used.