Signaling Networks in Glioblastoma Drug Resistance

描述（由申请人提供）：不幸的是，胶质母细胞瘤是脑癌的最常见和最恶性的形式，占所有脑肿瘤的约50%。胶质母细胞瘤的治疗本质上是多模式的，包括主要肿瘤块的手术切除，然后伴随化疗和放疗。胶质母细胞瘤是一种高度浸润性肿瘤，癌细胞侵入到健康的邻近组织中，突出了有效化疗以靶向这些扩散细胞的必要性。尽管有积极的治疗，耐药性和复发是疾病的标志，强调需要确定胶质母细胞瘤细胞获得耐药性的机制。胶质母细胞瘤的一线化疗由替莫唑胺（一种DNA单烷基化剂）组成。平均而言，TMZ仅延长生存期一到两个月，复发性胶质母细胞瘤显示出对烷化剂的强烈抗性。p53转录因子由于其广泛的抗肿瘤活性而通常被描述为基因组的监护人。虽然在35%的胶质母细胞瘤中发生突变，但其作为疾病预后指标的作用尚未明确。最近，有人建议，p53活性可能会保护胶质母细胞瘤细胞从DNA损伤剂，包括替莫唑胺，并可能有助于在p53熟练的肿瘤化疗耐药性。然而，由于对替莫唑胺的耐药性也发生在p53缺陷型肿瘤中，我们假设导致替莫唑胺耐药性的基因组和细胞信号网络改变在p53精通型和p53缺陷型细胞中非常不同。在这项研究中，我将检查胶质母细胞瘤细胞的反应，替莫唑胺在p53的精通和p53缺陷的情况下。使用计算建模，将细胞信号传导网络测量（包括定量免疫印迹和转录谱分析）与增殖、细胞周期、衰老和细胞死亡测量进行比较，以鉴定响应于损伤的途径与细胞对替莫唑胺治疗的表型响应之间的相关性。此外，这些技术将应用于从p53熟练和p53缺陷胶质母细胞瘤细胞产生的替莫唑胺耐药细胞系，以研究信号网络如何作为获得性耐药性的结果而变化。最后，从我们的模型中预测的导致替莫唑胺敏感性或耐药性的分子水平的通路扰动将确定最有可能改变治疗结果的靶点。

DESCRIPTION (provided by applicant): Glioblastoma is unfortunately both the most common and the most malignant form of brain cancer comprising approximately 50% of all brain tumors. Treatment for glioblastoma is multimodal in nature, consisting of surgical resection of the main tumor mass followed by concomitant chemo- and radio- therapy. Glioblastoma is a highly infiltrative tumor with cancer cells invading far into healthy adjacent tissue highlighting the nee for efficient chemotherapy to target these diffusive cells. Despite aggressive treatment, resistance and recurrence are hallmarks of the disease, underscoring the need to identify mechanisms by which glioblastoma cells acquire resistance to therapy. Frontline chemotherapy for glioblastoma consists of temozolomide, a DNA mono-alkylating agent. On average, TMZ extends survival by only one to two months, with recurrent glioblastoma showing a strong resistance to the alkylating agent. The p53 transcription factor is commonly described as the guardian of the genome due to its vast anti-tumorigenic activities. Although mutated in 35% of glioblastoma tumors its role as a prognostic indicator in the disease is not well defined. Recently, it has been suggested that p53 activity may protect glioblastoma cells from DNA damaging agents including temozolomide and may contribute to chemoresistance in p53 proficient tumors. However, as resistance to temozolomide also occurs in p53 deficient tumors, we hypothesize that the genomic and cellular signaling network alterations leading to temozolomide resistance are very different in p53 proficient and p53 deficient cells. In this study I will examine the response of glioblastoma cells to temozolomide in p53 proficient and p53 deficient contexts. Using computational modeling, cellular signaling network measurements, including quantitative immunoblotting and transcriptional profiling, will be compared to proliferation, cell cycle, senescence and cell death measurements to identify correlations between pathways responsive to damage and the phenotypic response of cells to temozolomide treatment. Furthermore, these techniques will be applied to temozolomide resistant cell lines produced from p53 proficient and p53 deficient glioblastoma cells to investigate how the signaling network changes as a result of acquired chemoresistance. Finally, perturbations at the molecular level of pathways predicted from our model to lead to sensitivity or resistance to temozolomide will identify targets most likely to alter therapeutic outcome.