A Systems Approach To Iron Metabolism In Cancer Cells

描述（申请人提供）：计算系统生物学通过对代谢、基因调控和信号网络的定量分析，为癌症生物学带来了许多新的见解。该项目的目标是应用系统生物学方法来理解正常乳腺上皮细胞向乳腺癌过渡时的铁代谢。近年来，人们对铁代谢有了很多了解，揭示了一个复杂的调节网络，其中有相互交织的反馈回路。上皮细胞发生恶性转化时，铁代谢蛋白发生实质性变化；此外，细胞内不稳定的铁有助于活性氧的产生，这与乳腺癌的发病机制有关。然而，细胞内铁代谢尚未受益于系统生物学方法。该计划将测试铁在正常细胞和恶性细胞中调节不同的假设。这将通过构建正常乳腺细胞核心铁代谢网络的预测数学模型来完成。然后，这些模型将被用来制定关于细胞向癌症表型转变时网络变化的假设。这些假设将在实验中得到验证。仔细收集的时间过程数据将用于构建、验证、改进和测试模型的预测能力。尽管正常细胞和癌细胞在铁代谢蛋白方面表现出实质性的差异，但之前利用这些差异进行治疗的尝试在很大程度上是经验主义的，令人失望。该项目的目标是超越经验主义，建立一个理性的预测模型，使人们能够理解恶性进展过程中驱动铁代谢变化的基本力量。最终目的是利用这种方法不仅了解铁在癌症形成、生长和转移中的作用，而且确定未来可能代表新的治疗靶点的关键节点，这可能对人类健康产生非常大的影响。

DESCRIPTION (provided by applicant): Computational systems biology has brought many new insights to cancer biology through the quantitative analysis of metabolic, gene regulatory and signaling networks. The goal of this project is to apply a systems biology approach to the understanding of iron metabolism in normal breast epithelium as it transitions to breast cancer. In recent years, much has been learned about iron metabolism, revealing a complex regulatory network with intertwined feedback loops. Proteins of iron metabolism exhibit substantial changes as epithelial cells undergo malignant transformation; further, intracellular labile iron contributes to the generation of reactive oxygen species, which have been implicated in the pathogenesis of breast cancer. However, intracellular iron metabolism has not yet benefited from a systems biology approach. The proposed project will test the hypothesis that iron is regulated differently in normal and malignant cells. This will be done by constructing predictive mathematical models of a core iron metabolism network in normal breast cells. These models will then be used to formulate hypotheses about changes in the network that occur as cells transition to a cancer phenotype. These hypotheses will then be tested experimentally. Carefully gathered time course data will be used to construct, validate, refine, and to test the predictive power of the models. Although normal and cancer cells exhibit substantial differences in proteins of iron metabolism, previous attempts to exploit these differences to therapeutic advantage have been largely empirical and disappointing. The project goal is to move beyond empiricism to a rational predictive model that will enable an understanding of basic forces that drive changes in iron metabolism during malignant progression. The ultimate aim is to use this approach not only to understand the role of iron in cancer formation, growth and metastasis, but to identify key nodal points that may represent new therapeutic targets in the future, a potentially very high impact on human health.