Liver cancer is one of the most common and lethal malignant tumors worldwide, of which hepatocellular carcinoma (HCC) accounts for 80%. Most HCC patients are already in the middle or late stages when diagnosed, having missed the best time for treatment. However, the existing diagnostic methods for this disease cannot reveal its dynamic mechanism and also have disadvantages such as detecting incurable disease, a poor effect, side effects, and high costs. Thanks to microfluidic technology, in this article, a biomimetic capillary network is designed and fabricated to reproduce the microenvironment of the capillaries in vitro. The topology of the biomimetic microcapillary network plays a crucial role in investigating the metastasis mechanism in liver cancer cells. The smallest capillary has a diameter between 12 and 13 μm, and the network of capillaries is connected to a main inlet or outlet channel with a diameter of 50 μm.
Firstly, simulation results for the microfluidic behaviors within the microcapillary network were established to analyze the influence of the topology and its microenvironment on the cells' microcirculation characteristics. As the flow rate was equal to 10 μL/min, applying Poiseuille flow theory, the linear relationship between pressure and flow was taken into consideration: the velocity of the flux at the inlet was 12.03 μm/s. Equally, the difference in pressure between the inlet and the outlet as well as the fluidic viscosity are taken into account. In general, the flow rate of the cell suspension decreases as it passes through the network. Secondly, several methods for fabricating the biomimetic microvascular network were compared: thanks to a combination of maskless direct laser writing and backside lithography, a biomimetic vascular network with a semicircular cross-section and a highly gradual gradient was produced. Finally, the cells' circulation within the microfluidic network is observed and analyzed to estimate the bionicity of the vascular network. The velocity in the middle of the vascular network is 3 to 4 times slower compared to that on both sides of the capillaries.
Compared with the traditional detection methods, the biomimetic microfluidic vascular network developed in this study would be helpful for reproducing the microenvironment of a biomimetic vascular network, which is significant for studying liver cancer cell metastasis. This method can achieve high-throughput, dynamic, and accurate detection of multiple types of health indicators, which have important clinical value in improving the early detection rate for lung cancer and optimizing individualized treatment plans.
