A Systems Approach To Iron Metabolism In Cancer Cells

癌细胞铁代谢的系统方法

基本信息

批准号：
8191693
负责人：
REINHARD LAUBENBACHER
金额：
$ 18.2万
依托单位：
VIRGINIA POLYTECHNIC INST AND ST UNIV
依托单位国家：
美国
项目类别：
财政年份：
2011
资助国家：
美国
起止时间：
2011-08-01 至 2013-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8191693
关键词：
Appointment Binding Biochemical Pathway Bioinformatics Breast Breast Cancer Treatment Cancer Biology Cells Collaborations Complex Data Empiricism Epithelial Epithelial Cells Epithelium Exhibits Exposure to Faculty Feedback Future Generations Goals Growth Health Human Institutes Iron Joints Lead Learning Malignant - descriptor Malignant Neoplasms Mammary gland Messenger RNA Metabolic Metabolism Modeling Neoplasm Metastasis Nodal Normal Cell Pathogenesis Phenotype Proteins Publications Reactive Oxygen Species Recording of previous events Regulation Regulator Genes Research Personnel Research Project Grants Role Scientist Signal Transduction System Systems Biology Telephone Testing Therapeutic Time Universities Virginia Visit Work cancer cell career driving force experience forest human tissue insight interdisciplinary collaboration iron metabolism malignant breast neoplasm malignant phenotype mathematical model medical schools new therapeutic target novel strategies post-doctoral training predictive modeling professor protein metabolite symposium therapeutic target tool

项目摘要

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. PUBLIC HEALTH RELEVANCE: This project impacts our understanding of the role of iron metabolism in the transformation of epithelial breast cells to malignancy. It is relevant to the search for potential new therapeutic targets for the treatment of breast cancer.

描述（由申请人提供）：计算系统生物学通过代谢、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了解正常乳腺上皮转变为乳腺癌时的铁代谢。近年来，人们对铁代谢有了很多了解，揭示了一个具有相互交织的反馈回路的复杂调节网络。当上皮细胞发生恶性转化时，铁代谢蛋白表现出实质性变化；此外，细胞内不稳定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。拟议的项目将检验铁在正常细胞和恶性细胞中受到不同调节的假设。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，这些模型将用于制定有关细胞转变为癌症表型时网络发生变化的假设。然后将通过实验检验这些假设。仔细收集的时间过程数据将用于构建、验证、完善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质方面表现出显着差异，但之前利用这些差异获得治疗优势的尝试很大程度上是凭经验的并且令人失望。该项目的目标是超越经验主义，建立一个理性的预测模型，使人们能够了解在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，而且确定可能代表未来新治疗靶点的关键节点，这对人类健康可能产生非常大的影响。公共健康相关性：该项目影响了我们对铁代谢在乳腺上皮细胞向恶性肿瘤转化中作用的理解。它与寻找治疗乳腺癌的潜在新治疗靶点相关。