Evaluating anticancer agents on 3D bioprinted organoid tumors (BOT) to reduce cost and accelerate therapeutic discovery.

e13500 Background: Despite recent advances in therapeutics, cancer remains the second leading cause of death worldwide. Next generation cancer models hold the promise of breaking this stranglehold. However, extracting adequate tissue for precision and personalized medicine ex vivo models can be difficult depending on tumor type and tissue site. Mechanisms to expand tissue include patient derived xenografts and patient derived organoids. The former imposes a large time window to establish while the latter is constrained in space by sizescales. Advances in 3D bioprinting have improved the ability to reproduce the three-dimensionality and heterogeneity of the tumor microenvironment. Here we present a novel mechanism to address space and time constrains with 3D bioprinted organoid tumors (BOT) that mimic core needle biopsy tissue to reduce both cost and time to market for novel therapeutics making effective cancer therapy more accessible and equitable. The aim of this study is to produce and use BOT core biopsy tissue in ex vivo precision and personalized medicine applications. Methods: Bioinks prepared with MDA-MB-231 cells, fibrinogen, and thrombin will be deposited layer-by-layer on microporous substrate, in various geometrical configurations, and cured in stages to allow cells and matrix to self-assemble with limited degrees of freedom. Bioprinted organoid tissue will be fully cured to mimic patient biopsy cores, which will then be loaded in ex vivo bioreactors to evaluate sensitivity and resistance of small molecule and biologics. Results: Tissue 3D microarchitecture was validated using high-content fluorescence imaging and custom image processing applications. Diffusion of mock agents, small molecule, and nucleic acid stains was measured 200 mm deep in tissue. Differential activity in spatially distinct regions of intact BOT cores was quantified using advanced image processing modules. Conclusions: Patient derived BOT cores could be used both as a predictive model to screen drugs on an individualized basis and to uncover new therapeutic targets to improve efficacy and reduce toxicity. Due to their ability to replicate the physical and biochemical characteristics of a tumor and its microenvironment, BOT based precision and personalized medicine models can provide more accurate data on drug efficacy and toxicology when compared to in vitro cancer models.