Abstract
Studies of anticancer therapies in traditional cell culture models can demonstrate efficacy of direct-acting compounds but lack the 3-dimensional arrangement of the tumor cells and their tissue-specific microenvironments, both of which are important modulators of treatment effects in vivo. Bone cells reside in complex environments that regulate their fate and function. A bioengineered human bone-tumor model has been shown to provide a microphysiological niche for studies of cancer cell behavior. Here, we demonstrate successful transfer between 2 laboratories and utility of this model in efficacy studies using well-established chemotherapeutic agents. The bioengineered human bone-tumor model consisted of Ewing sarcoma (RD-ES) cancer cell aggregates infused into tissue-engineered bone that was grown from human mesenchymal stem cell-derived differentiated into osteoblasts within mineralized bone scaffolds. The tumor model was maintained in culture for over 5 weeks and subjected to clinically relevant doses of linsitinib, doxorubicin, cisplatin, methotrexate, vincristine, dexamethasone, or MAP (methotrexate, doxorubicin, and cisplatin combination). Drug administration cycles were designed to mimic clinical treatment regimens. The bioengineered tumors were evaluated days to weeks after the cessation of treatment to monitor the potential for relapse, using bioengineered bone and ES cell monolayers as controls. Drug binding to the scaffolds and media proteins and gene expression were also evaluated. We show that a bioengineered human bone tumor can be used as a microphysiological model for preclinical studies of anticancer drugs. We found that anticancer efficacy was achieved at concentrations approximating the human Cmax, in contrast to traditional ES cell monolayers. These studies show that the bone-tumor model can be successfully transferred between laboratories and has predictive power in preclinical studies. The effects of drugs on the bone tumors and healthy bone were studied in parallel, in support of the utility of this model for identification of new therapeutic targets.