DNA Damage Networks

该项目的长期目标是开发数学和物理化学模型，描述网络和系统生物学水平上细胞对DNA损伤的反应。这项工作涉及紧密整合集中的严格定量实验研究，监测大量细胞内蛋白激酶信号通路的活性，并使用各种定量数学模型将其活性与DNA损伤诱导的细胞周期停滞和重新进入，凋亡或衰老的细胞表型相关联。这些模型捕获相关的信令信息，并提供新的见解 深入到基本的生物学中。实验主要集中在具有直接翻译相关性的人类淋巴瘤和乳腺癌细胞上，并直接建立在我们在前一个资助期内进行的实验和建模工作的基础上。在淋巴瘤细胞中，我们的重点包括DNA损伤信号传导、细胞反应和转录调控之间的联系，因为我们的初步数据表明，转录变化可能在预测这种肿瘤类型对治疗的反应方面特别重要。在乳腺癌细胞中，我们专注于EGFR和DNA损伤信号通路之间的相互作用和串扰，因为我们的初步数据表明，这些信号可以B有利地操纵，以增强肿瘤细胞的杀伤作用，目前在临床上广泛使用的药物。从这项工作中产生的计算模型阐明了在遗传毒性应激后的不同时间，各种信号传导途径的哪些组分对于不同的细胞反应是最重要的，从而定义了细胞信号传导信息流动的关键途径。的预测 然后，以各种规模，包括体外细胞培养系统、鼠异种移植物和小鼠癌症模型，探索和测试这两种肿瘤类型的模型。在模型的指导下，将确定在DNA损伤后特定时间点至关重要的信号通路中的关键节点，为遗传毒性应激诱导的细胞表型提供机制分子基础。这些实验的结果将是在系统水平上对全球DNA损伤反应的显著增强的理解，包括癌症易感性和治疗抗性的潜在机制，以及识别关键信号通路和应该成为癌症治疗中治疗操作靶点的分子。

The long-term goal of this project is to develop mathematical and physico-chemical models that describe the cellular response to DNA damage at the network and systems biology level. The work involves the tight integration of focused rigorously quantitative experimental studies monitoring the activity of a large number of intracellular protein kinase signaling pathways and correlating their activity with the cellular phenotypes of DNA damage-induced cell cycle arrest and re-entry, apoptosis or senescence using a variety of quantitative mathematical models. These models capture the relevant signaling information, and provide new insights into the underlying biology. Experiments focus on human lymphoma and breast cancer cells with direct translational relevance, and build directly on our prior experimental and modeling work performed during the previous funding period. In lymphoma cells our focus includes t h e connection between DNA damage signaling, cellular response, and transcriptional regulation since our preliminary data suggests that transcriptional changes are likely to be especially important in predicting the response of this tumor type to treatment. In breast cancer cells, we focus on t h e interactions and cross-talk between the EGFR and DNA damage signaling pathways, since our preliminary data suggests that these signals can b e manipulated advantageously to enhance tumor cell killing using agents that are currently in wide clinical use. The computational models that result from this work illuminate which components of the various signaling pathways are most important for the different cellular responses at various times after the genotoxic stress, thereby defining the critical pathways through which cellular signaling information flows. Predictions from the models for both of these tumor types are then explored and tested at a variety of scales, including in vitro cell culture systems, murine xenografts, and mouse cancer models. Guided by t h e models, key nodes in the signaling pathways implicated as being critically important at particular time points after DNA damage will be identified, providing a mechanistic molecular basis underlying the observed cellular phenotype induced by genotoxic stress. The result of these experiments will be a significantly enhanced understanding of the global DNA damage response at the systems level including mechanisms underlying cancer predisposition and therapeutic resistance, and the identification of critical signaling pathways and molecules that should be targets for therapeutic manipulation in cancer treatment.