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The current drug development pipeline takes approximately fifteen years and $2.6 billion to get a new drug to market. Typically, drugs are tested on two-dimensional (2D) cell cultures and animal models to estimate their efficacy before reaching human trials. However, these models are often not representative of the human body. The 2D culture changes the morphology and physiology of cells, and animal models often have a vastly different anatomy and physiology than humans. The use of bioengineered human cell-based organoids may increase the probability of success during human trials by providing human-specific preclinical data. They could also be deployed for personalized medicine diagnostics to optimize therapies in diseases such as cancer. However, one limitation in employing organoids in drug screening has been the difficulty in creating large numbers of homogeneous organoids in form factors compatible with high-throughput screening (e.g., 96-and 384-well plates). Bioprinting can be used to scale up deposition of such organoids and tissue constructs. Unfortunately, it has been challenging to 3D print hydrogel bioinks into small-sized wells due to well-bioink interactions that can result in bioinks spreading out and wetting the well surface instead of maintaining a spherical form. Here, we demonstrate an immersion printing technique to bioprint tissue organoids in 96-well plates to increase the throughput of 3D drug screening. A hydrogel bioink comprised of hyaluronic acid and collagen is bioprinted into a viscous gelatin bath, which blocks the bioink from interacting with the well walls and provides support to maintain a spherical form. This method was validated using several cancerous cell lines, and then applied to patient-derived glioblastoma (GBM) and sarcoma biospecimens for drug screening.

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Glioblastoma (GBM) is a lethal, incurable form of cancer in the brain. Even with maximally aggressive surgery and chemoradiotherapy, median patient survival is 14.5 months. These tumors infiltrate normal brain tissue, are surgically incurable, and universally recur. GBMs are characterized by genetic, epigenetic, and microenvironmental heterogeneity, and they evolve spontaneously over time and as a result of treatment. However, tracking such heterogeneity in real time in response to drug treatments has been impossible. Here we describe the development of an in vitro GBM tumor organoid model that is comprised of five distinct cellular subpopulations (4 GBM cell lines that represent GBM subpopulations and 1 astrocyte line), each fluorescently labeled with a different color. These multi-cell type GBM organoids are then embedded in a brain-like hyaluronic acid hydrogel for subsequent studies involving drug treatments and tracking of changes in relative numbers of each fluorescently unique subpopulation. This approach allows for the visual assessment of drug influence on individual subpopulations within GBM, and in future work can be expanded to supporting studies using patient tumor biospecimenderived cells for personalized diagnostics.

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Glioblastoma (GBM) is one of most aggressive forms of brain cancer, with a median survival time of 14.6 months following diagnosis. This low survival rate could in part be attributed to the lack of model systems of this type of cancer that faithfully recapitulate the tumor architecture and microenvironment seen in vivo in humans. Therapeutic studies would provide results that could be translated to the clinic efficiently. Here, we assess the role of the tumor microenvironment physical parameters on the tumor, and its potential use as a biomarker using a hyaluronic acid hydrogel system capable of elastic modulus tuning and dynamic elastic moduli changes. Experiments were conducted to assess the sensitivity of glioblastoma cell populations with different mutations to varying elastic moduli. Cells with aberrant epithelial growth factor receptor (EGFR) expression have a predilection for a stiffer environment, sensing these parameters through focal adhesion kinase (FAK). Importantly, the inhibition of FAK or EGFR generally resulted in reversed elastic modulus preference. Lastly, we explore the concept of therapeutically targeting the elastic modulus and dynamically reducing it via chemical or enzymatic degradation, both showing the capability to reduce or stunt proliferation rates of these GBM populations.