Department of Bioengineering, Lehigh University, Bethlehem, Pennsylvania18015, United States.
Department of Mechanical Engineering & Mechanics, Lehigh University, Bethlehem, Pennsylvania18015, United States.
ACS Appl Mater Interfaces. 2023 Feb 8;15(5):6431-6441. doi: 10.1021/acsami.2c19453. Epub 2023 Jan 24.
The vascular system in living tissues is a highly organized system that consists of vessels with various diameters for nutrient delivery and waste transport. In recent years, many vessel construction methods have been developed for building vascularized on-chip tissue models. These methods usually focused on constructing vessels at a single scale. In this work, a method that can build a hierarchical and perfusable vessel networks was developed. By providing flow stimuli and proper HUVEC concentration, spontaneous anastomosis between endothelialized lumens and the self-assembled capillary network was induced; thus, a perfusable network containing vessels at different scales was achieved. With this simple method, an -like hierarchical vessel-supported tumor model was prepared and its application in anticancer drug testing was demonstrated. The tumor growth rate was predicted by combining computational fluid dynamics simulation and a tumor growth mathematical model to understand the vessel perfusability effect on tumor growth rate in the hierarchical vessel network. Compared to the tumor model without capillary vessels, the hierarchical vessel-supported tumor shows a significantly higher growth rate and drug delivery efficiency.
生物组织中的脉管系统是一个高度组织化的系统,由具有不同直径的血管组成,用于输送营养物质和运输废物。近年来,已经开发出许多用于构建血管化芯片组织模型的血管构建方法。这些方法通常侧重于构建单一尺度的血管。在这项工作中,开发了一种可以构建分层和可灌注血管网络的方法。通过提供流动刺激和适当的 HUVEC 浓度,诱导内皮化管腔与自组装毛细血管网络之间的自发吻合,从而实现了包含不同尺度血管的可灌注网络。通过这种简单的方法,制备了类似于的分层血管支持的肿瘤模型,并证明了其在抗癌药物测试中的应用。通过结合计算流体动力学模拟和肿瘤生长数学模型来预测肿瘤生长速度,以了解在分层血管网络中血管灌注性对肿瘤生长速度的影响。与没有毛细血管的肿瘤模型相比,分层血管支持的肿瘤显示出更高的生长速度和药物输送效率。