Scaffold-based 3D cellular models mimicking the heterogeneity of osteosarcoma stem cell niche

TLDR

Conventional osteosarcoma therapies fail because they poorly target cancer stem cells and rely on 2D in‑vitro models with limited translational relevance. The study introduces two tumor‑engineering strategies designed to better model osteosarcoma and improve therapeutic outcomes. Two hydroxyapatite‑based bone‑mimicking scaffolds were used to recreate the CSC niche, and human osteosarcoma cell lines (MG63, SAOS‑2) and enriched CSCs were cultured and analyzed within these 3D systems. The 3D models successfully recapitulated the osteosarcoma stem cell niche, showing that the tumor microenvironment is essential and that these systems enhance preclinical predictivity and clinical translation.

Abstract

Abstract The failure of the osteosarcoma conventional therapies leads to the growing need for novel therapeutic strategies. The lack of specificity for the Cancer Stem Cells (CSCs) population has been recently identified as the main limitation in the current therapies. Moreover, the traditional two-dimensional (2D) in vitro models, employed in the drug testing and screening as well as in the study of cell and molecular biology, are affected by a poor in vitro-in vivo translation ability. To overcome these limitations, this work provides two tumour engineering approaches as new tools to address osteosarcoma and improve therapy outcomes. In detail, two different hydroxyapatite-based bone-mimicking scaffolds were used to recapitulate aspects of the in vivo tumour microenvironment, focusing on CSCs niche. The biological performance of human osteosarcoma cell lines (MG63 and SAOS-2) and enriched-CSCs were deeply analysed in these complex cell culture models. The results highlight the fundamental role of the tumour microenvironment proving the mimicry of osteosarcoma stem cell niche by the use of CSCs together with the biomimetic scaffolds, compared to conventional 2D culture systems. These advanced 3D cell culture in vitro tumour models could improve the predictivity of preclinical studies and strongly enhance the clinical translation.