Predictive experiment-based multiscale models of angiogenesis in breast cancer

点击翻译按钮获取中文摘要

DESCRIPTION (provided by applicant): Project Summary/Abstract Tumors are angiogenesis-dependent as they require blood supply to grow and metastasize. Angiogenesis is regulated by a multitude of stimulators and inhibitors that maintain vascular homeostasis under physiological conditions. This angiogenic balance is tipped in favor of proangiogenic factors in cancer. The proangiogenic factors include many growth factors among which vascular endothelial growth factor (VEGF) plays a prominent role. Among endogenous antiangiogenic factors several whole proteins, e.g. thrombospondin-1, as well as protein fragments have been identified; most of the known fragments reside in the extracellular matrix. A quantitative understanding of how these factors interact to result in a growing vasculature and how to control this growth is presently lacking. To achieve a better understanding of these processes, the development of predictive experiment-based molecular-detailed multiscale computational models of tumor angiogenesis is necessary. This research will focus on breast cancer. The long-term goal of this project is to develop such models of the breast cancer angiogenesis physiome. The computational developments will be tightly coupled to state of the art breast cancer imaging at the molecular, cellular, microvascular, and tissue levels using animal models. The invasive human breast cancer cell line MDA-MB-231 and the less invasive human breast cancer cell line MCF-7 will be used to generate orthotopic xenografts in the mammary fat pad in female severe combined immune deficient (SCID) mice. The measurements will include the characterization and localization of receptor and ligand expression at the different stages of tumor development; temporal and spatial development of hypoxia and microvasculature in growing tumor; and functional characteristics of the tumor microvasculature such as blood volume and vascular permeability, and the extracellular matrix. Part of these data will serve as input to the computational models whereas other data will serve as a means for their validation. The models will be extended to human disease. The research will contribute to a better fundamental understanding of the tumor vascular biology and to the design of novel therapeutics and quantitative interpretation of clinical data. The synergistic combination of computational and experimental studies should provide significant insights into the nature of the disease. PUBLIC HEALTH RELEVANCE: Narrative Breast cancer is the most commonly diagnosed female malignancy in the United States. Angiogenesis or neovascular growth plays a key role in breast cancer development, invasion and metastasis. Using synergistic combination of computational and experimental methods, the project will provide a better quantitative understanding of angiogenesis stimulation and inhibition, leading to translation of fundamental knowledge into novel therapeutics.