Fabrication of Size-Controllable and Arrangement-Orderly HepG2 Spheroids for Drug Screening via Decellularized Liver...

Three-dimensional (3D) culture via micropattern arrays to generate cellular spheroids seems a promising in vitro biomimetic system for liver tissue engineering applications, such as drug screening. Recently, organ-derived decellularized extracellular matrix emerges as arguably the most biomimetic bioink. Herein, decellularized liver matrix (DLM)-derived micropattern array chips were developed to fabricate size-controllable and arrangement-orderly HepG2 spheroids for drug screening. The porcine DLM was obtained by the removal of cellular components and then ground into powder, followed by enzymolysis. DLM as a coating substrate was compared with collagen type I (Col I) and Matrigel in terms of biological performance for enhancing cell adhesion, proliferation, and functions. Subsequently, we used poly(dimethylsiloxane) (PDMS) to adsorb DLM as the bioink to fabricate micropattern array chips. The optimal shape and size of micropattern were determined by evaluating the morphology, viability, and functions of HepG2 3D cellular aggregates. In addition, drug-susceptibility testing (paclitaxel, doxorubicin HCl, and disulfiram) was performed on this novel platform. The DLM provided the tissue-specific microenvironment that provided suitable supports for HepG2 cells, compared to Col I and Matrigel. A circular micropattern with a diameter of 100 μm was the optimal processing parameter to rapidly fabricate large-scale, size-controllable, and arrangement-orderly HepG2 cellular aggregates with 3D spheroid's shape and high cell viability. Drug screening testing showed that the effect of a drug could be directly demonstrated on-chip by confocal microscopy measuring the viability of spheroids. We provide a novel platform for the large-scale generation of HepG2 spheroids with uniform size and arrangement, thus bringing convenience, reducing error, and increasing reproducibility for a rapid drug discovery by fluorescence quantitative analysis. This methodology may be possible to apply in advancing personalized medicine and drug discovery.