Authors
Ponnamma Mandeda Madaiah, Rudra Nath Ghosh, Mathew Peter
Published in
RSC advances. Jul 03, 2026. Epub Jul 03, 2026.
Abstract
Osteosarcoma remains a leading cause of primary bone cancer mortality due to its aggressive growth, early metastasis, frequent recurrence, and chemoresistance despite multimodal therapies. Conventional 2D cultures inadequately replicate the tumor microenvironment, limiting their predictive value for drug screening. Here, we developed a 3D gelatin-based cryogel platform (GelCryo) as a biomimetic platform for osteosarcoma drug screening; owing to their interconnected macroporosity, high permeability, tunable mechanics, and structural resilience, cryogels provide a major advance over conventional planar cultures to better mimic in vivo architecture, mechanics, and drug barriers and offer a more biomimetic environment for long-term cell growth and therapeutic testing. GelCryo scaffolds were fabricated at two glutaraldehyde crosslinking densities and systemic characterization revealed their macroporous structure (pore sizes 347-678 µm, porosity >93%) tunable stiffness (bulk modulus ∼14-16 MPa), high swelling capacity, and collagenase-responsive degradability, with the denser formulation exhibiting smaller pores, reduced swelling, and greater enzymatic stability. Both formulations supported sustained viability (>80% over 21 days), and proliferation (Ki67+ nuclei) of MG63 osteosarcoma cells over extended culture, confirming the cytocompatibility of the platform using alamarBlue assay. Critically, MTX dose-response revealed progressively increased IC50 values for MG-63 cells on 2D cultures (36.2 ± 11.1 µM), spheroids culture (69.7 ± 11.2), 1% GelCryo seeded scaffold (53.7 ± 12.9 µM) and 1.5% GelCryo seeded scaffold (99.8 ± 22.2 µM) suggesting chemoresistance in our 3D model. The 1.5% GelCryo scaffold exhibited the highest IC50 and recapitulating the cell-matrix mediated drug resistance typical of solid tumors. These findings establish GelCryo as a tunable biomaterial platform for osteosarcoma modeling, with strong potential to improve the physiological relevance of preclinical anticancer drug screening.
PMID:
42405062
Bibliographic data and abstract were imported from PubMed on 06 Jul 2026.
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