Wednesday, May 21, 2025
5/21/2025
Increasing organoid reproducibility and complexity for drug testing and disease modeling - Abstract The failure of preclinical models to accurately predict cancer drug efficacy costs patient lives and slows the development of new therapies. Most cancer drugs fail because they are not effective in vivo or are not targeted to the appropriate patient population. Next generation tissue models that predict efficacy would therefore advance drug development and provide personalized models of disease for patients who do not respond to first line treatments. Patient Derived Organoids (PDOs) are an emerging next generation tissue model that self- organize from human tumor cells. When sourced from appropriate clinical specimens and cultured in appropriate three-dimensional (3D) environments they have demonstrated the potential to predict the efficacy of drugs in both the preclinical and clinical setting. Modern clinical trials like I-SPY 2 are potential sources of such tumor specimens that are associated with deep molecular profiling and information about clinical response. However, applying these specimens to PDO for clinical and preclinical drug testing requires transformative improvements in scalability, speed, physiological relevance, complexity, and reproducibility. We propose an approach called “4D tissue fabrication” which provides such improvements. Central to our approach is guiding organoid self- organization by careful consideration of the mechanics, chemical composition, and geometry of tissue interfaces. To control these features we developed a new piezoelectric extrusion bioprinter that delivers organoid cell slurries at tissue-like densities to specific 3D coordinates in hydrogel support baths carefully optimized for organoid self- organization and growth. The result is organoids with dramatically more homogeneous size, morphology, and phenotype. In a proof of principle drug response assay using 4D tissue fabrication we demonstrated a nine order-of-magnitude improvement in statistical power compared to traditional organoid culture. Here we propose to bring this enormous improvement in organoid uniformity to breast cancer PDOs derived from tissue gathered during the I-SPY 2 clinical trial and from an ongoing UCSF breast biobanking effort. Our proposal has three primary aims. First we will develop rapid, sensitive and reproducible platforms for screening drugs in a preclinical setting. Second we will develop workflows to grow and assay PDOs from rare or slow growing cell sources. Third we will optimize existing workflows to build more complex assays for DCIS organoids, immune cells, and perfusable vasculature. Performance metrics are provided for all aims. If successful, we will accomplish two important goals with significance to cancer patients: producing more sensitive and predictive pre-clinical models for the development of new drugs targeting intractable cancers like subsets of Triple Negative Breast Cancer, and producing clinical models of a patient’s own tumor with the potential to identify silver bullets capable of targeting tumor types that suffer from low clinical response rates.
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