A hydrogel-based tumor model for the evaluation of nanoparticle-based cancer therapeutics
Sabanayagam, Chandran R.
Harrington, Daniel A.
Farach-Carson, Mary C.
Three-dimensional (3D) tissue-engineered tumor models have the potential to bridge the gap between monolayer cultures and patient-derived xenografts for the testing of nanoparticle (NP)-based cancer therapeutics. In this study, a hydrogel-derived prostate cancer (PCa) model was developed for the in vitro evaluation of doxorubicin (Dox)-loaded polymer NPs (Dox-NPs). The hydrogels were synthesized using chemically modified hyaluronic acid (HA) carrying acrylate groups (HA-AC) or reactive thiols (HA-SH). The crosslinked hydrogel networks exhibited an estimated pore size of 70–100 nm, similar to the spacing of the extracellular matrices (ECM) surrounding tumor tissues. LNCaP PCa cells entrapped in the HA matrices formed distinct tumor-like multicellular aggregates with an average diameter of 50 μm after 7 days of culture. Compared to cells grown on two-dimensional (2D) tissue culture plates, cells from the engineered tumoroids expressed significantly higher levels of multidrug resistance (MDR) proteins, including multidrug resistance protein 1 (MRP1) and lung resistance-related protein (LRP), both at the mRNA and the protein levels. Separately, Dox-NPs with an average diameter of 54 ± 1 nm were prepared from amphiphilic block copolymers based on poly(ethylene glycol) (PEG) and poly(ε-caprolactone) (PCL) bearing pendant cyclic ketals. Dox-NPs were able to diffuse through the hydrogel matrices, penetrate into the tumoroid and be internalized by LNCaP PCa cells through caveolae-mediated endocytosis and macropinocytosis pathways. Compared to 2D cultures, LNCaP PCa cells cultured as multicellular aggregates in HA hydrogel were more resistant to Dox and Dox-NPs treatments. Moreover, the NP-based Dox formulation could bypass the drug efflux function of MRP1, thereby partially reversing the resistance to free Dox in 3D cultures. Overall, the engineered tumor model has the potential to provide predictable results on the efficacy of NP-based cancer therapeutics.