A 2-compartment bone tumor model to investigate interactions between healthy and tumor cells.

We produced a novel three dimensional (3D) bone tumor model (BTM) to study the interactions between healthy and tumor cells in a tumor microenvironment, migration tendency of the tumor cells, and the efficacy of an anticancer drug, Doxorubicin, on cancer cells. Model consisted of two compartments: (a) healthy bone tissue mimic, made of poly(lactic acid-co-glycolic acid) (PLGA)/beta-tricalcium phosphate (β-TCP) sponge seeded with human fetal osteoblastic cells (hFOB) and human umbilical vein endothelial cells (HUVECs), and (b) tumor mimic, made of lyophilized collagen sponge seeded with human osteosarcoma cells (Saos-2). The tumor mimic component was placed into the central cavity created in healthy bone mimic and together they constituted total 3D bone tumor model (3D-BTM). Porosities of both sponges were higher than 85% and average diameters of the pores were 199±52 µm for PLGA/TCP and 50-150 μm for collagen scaffolds. Compression Young's modulus of PLGA/TCP and collagen sponges were determined as 4.76 MPa and 140 kPa, respectively. Cell proliferation, morphology, calcium phosphate forming capacity and ALP production were studied separately on both healthy and tumor mimics. All cells demonstrated cellular extensions and spread well in porous scaffolds indicating good cell-material interactions. Confocal microscopy analysis showed direct contact between the cells present in different parts of the 3D-BTM. Migration of HUVECs from healthy bone mimic to the tumor compartment was confirmed by the increase in the levels of angiogenic factors VEGF, bFGF, and IL-8 in the tumor component. Doxorubicin (2.7 µg.mL-1) administered to the 3D-BTM caused a 7-fold decrease in the cell number after 24 h of interaction with the anticancer drug. Caspase-3 enzyme activity assay results demonstrated apoptosis of the osteosarcoma cells. This novel 3D-BTM prepared has a high potential for use in studying metastatic capabilities of cancer cells, and to determine the effective drug types and combinations for personalized treatments.