Three-dimensional, PEG-based hydrogels induce spheroid formation and enhance viability of A2058 melanoma cells.
Kata Nóra EnyediGábor EnyediEszter LajkóPublished in: FEBS open bio (2023)
Traditional drug screening methods use monolayer (2D) tumor cell cultures, which lack basic features of tumor complexity. As an alternative, 3D hydrogels have begun to emerge as simple, time- and cost-saving systems. One of the most promising candidates, synthetic alkoxysilane-PEG (polyethylene glycol)-based hydrogels, are formed by "sol-gel" polymerization in an aqueous medium, which allows control over the incorporated elements. Our aims were to optimize siloxane-PEG hydrogels for three different cell lines of skin origin and utilize these 3D hydrogels as a feasible drug (e.g. daunorubicin) screening assay. A drastic increase in survival and the formation of cellular aggregates (spheroids) could be observed in A2058 melanoma cells, but not in keratinocyte and endothelial cell lines. A deep-learning neural network was trained to recognize and distinguish between the cellular formations and allowed the fast processing of hundreds of microscopic images. We developed an artificial intelligence (AI)-assisted application (https://github.com/enyecz/CancerDetector2), which indicated that, in terms of average area of the spheroids treated with daunorubicin, A2058 melanoma cell 3D aggregates have better survival in a hydrogel containing 15% bis-mono-ethoxysilane-PEG.
Keyphrases
- drug delivery
- artificial intelligence
- deep learning
- hyaluronic acid
- wound healing
- drug release
- tissue engineering
- neural network
- machine learning
- big data
- extracellular matrix
- single cell
- convolutional neural network
- cell therapy
- ionic liquid
- optical coherence tomography
- emergency department
- endothelial cells
- stem cells
- free survival
- resistance training