Signaling Networks in Glioblastoma Drug Resistance

描述（由申请人提供）：胶质母细胞瘤是最常见和最恶性的脑癌，约占所有脑肿瘤的50%。胶质母细胞瘤的治疗本质上是多模式的，包括手术切除主要肿瘤块，然后辅以化疗和放疗。胶质母细胞瘤是一种高度浸润性的肿瘤，癌细胞可以侵入到健康的邻近组织，因此需要针对这些弥漫性细胞进行有效的化疗。尽管进行了积极的治疗，但耐药和复发是该疾病的特征，这强调了确定胶质母细胞瘤细胞获得耐药机制的必要性。胶质母细胞瘤的一线化疗包括替莫唑胺，一种DNA单烷基化剂。平均而言，TMZ仅延长生存期一至两个月，复发性胶质母细胞瘤对烷基化剂表现出强烈的抗性。p53转录因子由于其巨大的抗肿瘤活性，通常被描述为基因组的守护者。虽然在35%的胶质母细胞瘤肿瘤中发生突变，但其作为疾病预后指标的作用尚未得到很好的定义。最近，有研究表明p53活性可能保护胶质母细胞瘤细胞免受包括替莫唑胺在内的DNA损伤剂的伤害，并可能有助于p53精通肿瘤的化疗耐药。然而，由于对替莫唑胺的耐药也发生在p53缺陷肿瘤中，我们假设基因组和细胞信号网络的改变导致替莫唑胺耐药在p53精通细胞和p53缺陷细胞中是非常不同的。在这项研究中，我将检查胶质母细胞瘤细胞在p53精通和p53缺乏的情况下对替莫唑胺的反应。使用计算模型，细胞信号网络测量，包括定量免疫印迹和转录谱，将与增殖、细胞周期、衰老和细胞死亡测量进行比较，以确定对损伤的反应途径与细胞对替莫唑胺治疗的表型反应之间的相关性。此外，这些技术将应用于由p53精通和p53缺乏的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随着获得性化疗耐药而变化。最后，从我们的模型中预测的导致对替莫唑胺敏感或耐药的分子水平通路的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. PUBLIC HEALTH RELEVANCE: Glioblastoma is unfortunately both the most common and most malignant form of brain cancer, which, despite aggressive treatment, displays a strong radio- and chemo-resistant phenotype. This proposal focuses on identifying mechanisms of cellular response and resistance to temozolomide, the frontline chemotherapeutic used in glioblastoma treatment, in the context of p53 proficient and p53 deficient glioblastoma cells. Using computational, systems biology and molecular biology approaches we aim to identify novel combinatorial therapies to potentiate temozolomide toxicity as well as ways to target resistant disease.