Exploiting Response Surface Methodology to Advance Alginate-based Hydrogels for Precision Medicine

Tissue composition and cell organization rely on the extracellular matrix (ECM) which generates and transmits mechanical signals, triggering different cellular responses. Alginates are used in precision medicine, but as substrate for cells growth they lack adhesive domains and do not degrade. To overcome these key challenges, we developed a library of alginate-based hydrogels prepared following a two-step crosslinking. The compressive moduli and stability of hydrogels in vitro were modelled using a response surface method, enabling to decouple biochemical and biophysical properties. As biological systems use mechanical forces to regulate several processes, from tissue regeneration to cancer development, we selected alginate-based hydrogels with compressive moduli of breast tissues (1-20 kPa) model different stages of breast cancer development in vitro, and as new drug screening technologies. Human breast cancer cells (MDA-MB-231) were cultured on several hydrogels and as different in vitro models (i.e., 3D models and 2.5D models). All hydrogels are cytocompatible, allowing cells growth up to 1 week. We selected 2.5D in vitro models to investigate the correlation between drug efficacy and microenvironment/ECM stiffness, as more similar to standard 2D in vitro models (i.e., 2D/TCP). We selected doxorubicin as models drug, as first-line treatment for breast cancer. Interestingly, doxorubicin was less effective in cells cultured in softer hydrogels (EC50 0.495 ± 0.248 μM, 6.9 ± 0.6 kPa) than in stiffer ones (EC50 0.189 ± 0.032 μM, 21.0 ± 3.8 kPa), with the latter being similar to 2D/TCP controls (EC50 0.129 ± 0.028 μM, > 106 kPa). Obtained results demonstrate that the proposed hydrogel library with decoupled biophysical and biochemical properties enables to better study how microenvironmental cues impact on cell behaviour in vitro. Moreover, results suggest the need to use new approaches in precision medicine to study drug efficacy and resistance in the context of cancer, using in vitro models able to mimic different tumour progression microenvironments as in vivo.