Center for Modeling Tumor Cell Migration Mechanics

点击翻译按钮获取中文摘要

Abstract At their most fundamental level, cancers are initiated by genetic alterations that drive hyperactive cell division and cell migration. A common therapeutic strategy has been to target the proteins in the often-mutated signaling pathways that regulate cell proliferation. However, so far this strategy has achieved only limited success despite large public and private investment, which is likely due to functional redundancies in signaling pathways that give multiple avenues for the emergence of drug-resistance. An alternative strategy, which defines the organizing framework of our Center, is to directly target the internal or external mechanical machinery or structural elements that drive cell migration. As it is these elements that serve as the most downstream convergence point of the upstream genetic alterations, disruption of these critical elements provides viable, clinically-relevant targets. Since cell migration is a common feature of high-grade cancer, and invasion and metastasis are the primary cause of cancer related death, our Center will focus on understanding the fundamental mechanics and chemistry of how cells generate forces to move through complex and mechanically challenging tumor microenvironments. By focusing directly on the “nuts and bolts” of cell migration, we will be targeting the most vital and non-redundant part of the system. Specifically, we propose integrated modeling and experiments to investigate the molecular mechanics of cell migration and how the tumor microenvironment regulates disease progression as a function of the underlying carcinoma genetics. We will experimentally test our computational cell migration simulator, v1.0 (CMS1.0) for the mechanical dynamics of cell migration that will ultimately be used to: 1) identify novel drug targets/target combinations in silico, 2) define molecular mechanical subtypes of tumors for patient stratification, 3) guide the engineering of in vitro microsystems and in vivo animal models to better mimic the human disease, and 4) simulate tumor progression under different potential treatment strategies. Finally, we will develop a simulator-driven reverse genetics approach to elucidate the functional mechanical consequences of driver mutations and seek to manipulate the physical characteristics of a tumor to simultaneously bias against immune suppressor cells and promote the antitumor immune response.