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Neonatal respiratory distress syndrome is a potentially life-threatening condition that is often treated with the delivery of exogenous surfactants through a process called surfactant replacement therapy. This therapy includes the administration of the liquid surfactant through an endotracheal tube and mechanical ventilation. Due to the difficulty of imaging neonate lungs during this therapy, the success of surfactant delivery is often determined by observational techniques and evaluation of blood oxygen levels. The limitation of imaging creates challenges in evaluating the distribution of surfactant in airways. To address this limitation, we designed a computational, eight-generation, asymmetric neonate lung model using morphometric data to mimic the geometric structure of the human airway tree and fabricated it using an additive manufacturing technique. We used our model to study two-aliquot delivery of a clinically rated liquid surfactant under two different orientations to evaluate its distribution in airways. Our study offers a complex lung airway tree design that mimics the native geometry of the human airway tree to enable studies of therapeutics transport in airways. 

Abstract Colorectal cancer, a significant cause of cancer-related mortality, often exhibits drug resistance, highlighting the need for improved tumor models to advance personalized drug testing and precision therapy. We generated organoids from primary colorectal cancer cells cultured through the conditional reprogramming technique, establishing a framework to perform short-term drug testing studies on patient-derived cells. To model interactions with stromal cells in the tumor microenvironment, we combined cancer cell organoids with carcinoma-associated fibroblasts, a cell type implicated in disease progression and drug resistance. Our organotypic models revealed that carcinoma-associated fibroblasts promote cancer cell proliferation and stemness primarily through hepatocyte growth factor–MET paracrine signaling and activation of cyclin-dependent kinases. Disrupting these tumor–stromal interactions reduced organoid size while limiting oncogenic signals and cancer stemness. Leveraging this tumor model, we identified effective drug combinations targeting colorectal cancer cells and their tumorigenic activities. Our study highlights a path to incorporate patient-derived cells and tumor–stromal interactions into a drug testing workflow that could identify effective therapies for individual patients. 

Abstract Neonatal respiratory distress syndrome is mainly treated with the intratracheal delivery of pulmonary surfactants. The success of the therapy depends on the uniformity of distribution and efficiency of delivery of the instilled surfactant solution to the respiratory zone of the lungs. Direct imaging of the surfactant distribution and quantifying the efficiency of delivery is not feasible in neonates. To address this major limitation, we designed an eight-generation computational model of neonate lung airway tree using morphometric and geometric data of human lungs and fabricated it using additive manufacturing. Using this model, we performed systematic studies of delivery of a clinical surfactant either at a single aliquot or at two aliquots under different orientations of the airway tree in the gravitational space to mimic rolling a neonate on their side during the procedure. Our study offers novel insights into effects of the orientation of the lung airways and presence of a pre-existing surfactant film on how the instilled surfactant solution distributes in airways. 

Abstract The tumor microenvironment (TME) promotes proliferation, drug resistance, and invasiveness of cancer cells. Therapeutic targeting of the TME is an attractive strategy to improve outcomes for patients, particularly in aggressive cancers such as triple-negative breast cancer (TNBC) that have a rich stroma and limited targeted therapies. However, lack of preclinical human tumor models for mechanistic understanding of tumor–stromal interactions has been an impediment to identify effective treatments against the TME. To address this need, we developed a three-dimensional organotypic tumor model to study interactions of patient-derived cancer-associated fibroblasts (CAF) with TNBC cells and explore potential therapy targets. We found that CAFs predominantly secreted hepatocyte growth factor (HGF) and activated MET receptor tyrosine kinase in TNBC cells. This tumor–stromal interaction promoted invasiveness, epithelial-to-mesenchymal transition, and activities of multiple oncogenic pathways in TNBC cells. Importantly, we established that TNBC cells become resistant to monotherapy and demonstrated a design-driven approach to select drug combinations that effectively inhibit prometastatic functions of TNBC cells. Our study also showed that HGF from lung fibroblasts promotes colony formation by TNBC cells, suggesting that blocking HGF-MET signaling potentially could target both primary TNBC tumorigenesis and lung metastasis. Overall, we established the utility of our organotypic tumor model to identify and therapeutically target specific mechanisms of tumor–stromal interactions in TNBC toward the goal of developing targeted therapies against the TME. Implications: Leveraging a state-of-the-art organotypic tumor model, we demonstrated that CAFs-mediated HGF-MET signaling drive tumorigenic activities in TNBC and presents a therapeutic target.