p53 and Chemosensitivity in a Mouse Lymphoma Model

小鼠淋巴瘤模型中的 p53 和化疗敏感性

• 批准号: 7495191
• 负责人: SCOTT W. LOWE
• 金额: $ 40.39万
• 依托单位: COLUMBIA UNIV NEW YORK MORNINGSIDE
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/7495191
• 关键词: Affect; Apoptosis; B-Cell Lymphomas; Biological; Cell Aging; Clinical Trials; Complex; DNA Damage; Drug Delivery Systems; Drug effect disorder; Drug resistance; Evolution; Funding; Genes; Genetic; Genotype; Hypoxia; Lesion; Lymphoma; Malignant Neoplasms; Mediating; Methods; Modeling; Mus; Numbers; Oncogenes; Oxidative Stress; Pathway interactions; Pharmaceutical Preparations; Physiological; Process; Resistance; Signal Transduction; Stress; System; TP53 gene; Testing; Transgenic Model; Tumor Suppressor Proteins; chemotherapeutic agent; drug sensitivity; high throughput screening; in vivo; interest; neoplastic cell; novel therapeutics; programs; response; senescence; therapeutic target; tumor

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.

p53作用于复杂的肿瘤抑制网络，介导细胞对应激的反应。因此，p53是 因响应各种细胞损伤而激活，包括有丝分裂的致癌基因，缺氧，氧化应激， 和DNA损伤。一旦激活，p53可以触发各种反增殖程序，包括 凋亡和细胞衰老，通过靶向每个程序效应子的多个组成部分 机械。由于许多化学治疗剂目前用于直接或间接治疗癌症 损坏DNA，他们通常依靠p53途径的完整性来引起其抗肿瘤作用。作为 结果，耐药性可能是肿瘤进化的副产品。这个项目对如何感兴趣 p53调节常规药物和靶向药物的作用，以及破坏p53的含义 从肿瘤进化到耐药性的不同点的网络。为了研究这些过程，我们使用 B细胞淋巴瘤的E-MU-MYC转基因模型作为一种可探讨但生理测试系统。最后 资金期，我们开发了快速生产具有复杂基因型的淋巴瘤的方法，然后 研究这些病变对使用平行临床的方法对肿瘤细胞对治疗的反应的影响 试验。使用该系统，我们确定了许多生物学（凋亡，衰老，翻译控制） 和遗传（p53，arf，ink4a/arf，bcl-2，akt，elf4e）药物作用决定因素。在当前的提议中 我们将继续研究影响其凋亡和衰老的p53网络的组成部分 对化学敏度的影响，并将检查如何通过PI3Kinase/AKT网络进行生存信号传导 影响p53的作用以促进化学抗性。但是，我们还将开始努力探索 E-MU-MYC系统，特别是通过测试逆转化学抗性的策略来研究新药 体内。此外，我们将利用E-MU-MYC模型的独特特征进行高吞吐量 筛选以识别影响体内治疗反应的新基因。我们希望我们的结果将会 对p53和Akt网络有更好的了解以及它们如何影响药物敏感性和 体内抗性。通过了解耐药性和测试策略的机制来规避它， 我们可能会确定可以扩展到临床试验的新的治疗靶标或治疗策略。