p53 and Chemosensitivity in a Mouse Lymphoma Model

P53在一个复杂的肿瘤抑制网络中发挥作用，该网络介导细胞对应激的反应。因此，P53是 激活以响应各种细胞损伤，包括有丝分裂癌基因、低氧、氧化应激、 和DNA损伤。一旦被激活，P53可以触发多种抗增殖程序，包括 通过靶向每个程序效应器的多个组件来实现细胞凋亡和细胞衰老 机械制造。由于目前用于直接或间接治疗癌症的许多化疗药物 在损伤DNA的过程中，它们往往依赖于P53通路的完整性来诱导它们的抗肿瘤作用。作为一名 结果，耐药性可能作为肿瘤进化的副产品而出现。这个项目感兴趣的是 P53调节常规药物和靶向药物的作用，以及破坏P53的影响 从肿瘤演变到耐药的不同时间点的网络。为了研究这些过程，我们使用 E-MU-myc转基因B细胞淋巴瘤模型作为一种易处理的生理测试系统。在过去的几年里 在资助期间，我们开发了快速产生具有复杂基因类型的淋巴瘤的方法，然后 使用与临床平行的方法研究这些病变对肿瘤细胞治疗反应的影响 审判。利用这个系统，我们鉴定了一些生物学(细胞凋亡、衰老、翻译调控) 和遗传(P53、ARF、INK4a/ARF、Bcl2、Akt、elF4E)决定药物作用的因素。在目前的提案中， 我们将继续研究影响细胞凋亡和衰老的P53网络组件 对化疗敏感性的影响，并将研究PI3K/Akt网络中的生存信号是如何 影响P53促进化疗耐药的作用。然而，我们也将开始努力探索 用于研究新药的E-MU-myc系统，特别是通过测试逆转化疗耐药性的策略 活着。此外，我们将利用E-MU-MYC模型的独特功能来进行高吞吐量 筛选确定影响体内治疗反应的新基因。我们预计，我们的结果将 更好地了解P53和Akt网络以及它们如何影响药物敏感性和 体内抗药性。通过了解耐药性的机制和测试策略来规避它， 我们可以确定新的治疗靶点或治疗策略，可以扩展到临床试验。

p53 acts in a complex tumor suppressor network that mediates cellular responses to stress. Thus, p53 is activated in response to diverse cellular insults, including mitogenic oncogenes, hypoxia, oxidative stress, and DNA damage. Once activated, p53 can trigger a variety of anti-proliferative programs, including apoptosis and cellular senescence, by targeting multiple components of each program's effector machineries. Since many of the chemotherapeutic agents currently used to treat cancer directly or indirectly damage DNA, they often rely on the integrity of the p53 pathway to elicit their anti-tumor effects. As a consequence, drug resistance can arise as a byproduct of tumor evolution. This project is interested in how p53 modulates the action of conventional and targeted drugs, and the implications of disrupting the p53 network at different points from tumor evolution to drug resistance. To study these processes, we use the E-mu-myc transgenic model of B-cell lymphoma as a tractable yet physiological test system. Over the last funding period, we developed methods to rapidly produce lymphomas with complex genotypes, and then study the impact of these lesions on tumor cell responses to therapy using approaches that parallel clinical trials. Using this system, we identified a number of biological (apoptosis, senescence, translational control) and genetic (p53, ARF, INK4a/ARF, Bcl-2, Akt, elF4E) determinants of drug action. In the current proposal, we will continue to study components of the p53 network that influence apoptosis and senescence for their impact on chemosensitivity, and will examine how survival signaling through the PI3kinase/Akt network affects p53 action to promote chemoresistance. However, we also will initiate efforts to explore the utility of the E-mu-myc system to study new drugs, in particular, by testing strategies to reverse chemoresistance in vivo. Furthermore, we will exploit the unique features of the E-mu-myc model to conduct high throughput screens to identify new genes that influence treatment responses in vivo. We expect that our results will produce a better understanding of the p53 and Akt networks and how they influence drug sensitivity and resistance in vivo. By understanding mechanisms of drug resistance and testing strategies to circumvent it, we may identify new therapeutic targets or treatment strategies that can be extended to clinical trials.