Background Successful drug screening ultimately relies on highly representative therapeutic testing models. In addition to the regulation of the resident tumor cells, regulation of immune evasion involves tumor microenvironment (TME) parameters such as extracellular matrix (ECM), cell-matrix interactions, growth factors, cytokines, and oxygenation, all have an impact on the tumor and its treatment. Recapitulation of TME in terms of immune and oxygenation states allows for a comprehensive assessment of the impact of the drug. For a thorough evaluation of the drug effect under physiologically relevant conditions we investigated the role of heat shock protein 90 inhibitor (HSP90i) in Human Uterine Adenosarcoma Patient Derived Tumoroid that has immune and oxygen components of TME. We hypothesize that evaluating the drug’s impact without the presence of immune system and oxygen status prevents omitting critical information of clinical relevance.
Methods Human Uterine Adenosarcoma models were prepared across two types of 3D immunocompetent PDT-Scaffold-based platforms: 1) S-PDT-V1(Matrigel based model without oxygenation) and 2) S-PDT-V3d (PBMCs with oxygenation). The previous is based on a static, apical oxygenation only set-up, the latter involves a dynamic, matrix-liquid-liquid interface via an in-well perfusion system with the aid of synthetic hemoglobin. The addition of activated peripheral blood mononuclear cells (PBMCs) adds an allogenic immune system to the model. Each model system has three treatment groups: a) Control, b) 50 nM HSP90i, c) 100 nM HS90i. Comparative histological assessment (tumoroid volume) was carried out via phase contrast imaging initially on Days 1, 3 and 7. Statistical analysis was done using One-way ANOVA for significance (*p<0.05), n=3
Results Tumoroid morphology results indicate an overall slower growth rate for tumoroids in dynamic models compared to static ones. The HSP90i reduces tumor volume in the S-PDT-V1 (figures A1-C2 and 2). When we treated the dynamic HSP90i within S-PDT-V3d, tumor volume reduction was not observed (figure D1-F2 and 3).
Conclusions To better evaluate the impact of drug treatment it is necessary to perform experiments under conditions that account for physiology of the tumor. The differences in effect of the same drug observed on our different model platforms suggests that a physiologically accurate model platform adds to understanding the drug’s impact. The oxygenation status in an immunocompetent model provides a critical influence that would not have been observable otherwise. These model systems offer a new tool in the broader drug discovery process by enhancing our understanding of the complex tumor-immune-drug interactions.
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