Development of an interdisciplinary program in transforming computational science and engineering tools for cancer research

本文的主要目的是应用新兴技术开发多尺度计算方法来研究异型细胞-细胞碰撞和在动态剪切力作用下与基底的粘附。特别地，重点是白细胞(PMN)-黑色素瘤细胞在非线性剪切流中的栓塞形成，以及随后作为细胞-细胞聚集的结果捆绑到血管内皮（EC）。肿瘤细胞粘附血管壁的程度受受体配体键的动力学形成/破坏、流体动力学剪切和循环内的异型细胞群的影响。该项目将为微循环中转移性癌细胞向EC募集过程中微循环中微血流动力学、异型细胞群、分泌趋化因子和pmn -黑色素瘤粘附的复杂作用提供理解。将应用多尺度计算流体动力学（CFD）代码进行直接数值模拟，其中系统中的每个单元都被显式解析。这项研究将促进新的跨学科研究和教育方法，整合生物医学工程，物理科学和生命科学。将利用研究文献中的及时出版物以及通过研究者的网站和研讨会讲座积极传播研究结果。研究人员将通过将工程原理应用于细胞生物学，并结合应用数学、力学、计算科学、生物工程和医学科学来促进教育。

0729091DongThe main objective of this proposal is to apply emerging technologies in developing multi-scale computational approaches for studying heterotypic cell-cell collision and adhesion to a substrate under dynamic shear forces. In particular, the focus is on leukocyte (PMN)-melanoma cell emboli formation in a non-linear shear flow and subsequent tethering to the vascular endothelium (EC) as a result of cell-cell aggregation. The extent of tumor cell adhesion to a vessel wall is governed by the kinetic formation/disruption of receptor ligand bonds, the hydrodynamic shear and the heterotypic cell populations within the circulation. The project will provide understanding for the complex role of micro-hemodynamics, heterotypic cell populations, secreted chemokines, and PMN-melanoma adhesion in the recruitment of metastatic cancer cells to the EC in the microcirculation. A multi-scale computational fluid dynamics (CFD) code will be applied to perform direct numerical simulation, where each cell in the system is explicitly resolved. This research will promote new crossdisciplinary approaches in research and education, integrating biomedical engineering, physical sciences and life sciences. The research results will be actively disseminated, using timely publications in the research literature as well as through the investigator's web sites and seminar lectures. The investigators will foster education through the application of engineering principles to cell biology, integrated with applied mathematics, mechanics, computational science, bioengineering and medical sciences.