Saturday, September 7, 2024
9/7/2024
PROJECT SUMMARY The overarching goal of our research program is to couple computational tools with three-dimensional models of epithelial barriers to interrogate how the epithelial extracellular matrix (ECM) is influenced by extrinsic factors, how changes to the epithelial ECM affect drug delivery, and how the epithelial ECM can be harnessed to tailor drug bioavailability. Epithelial barriers are what lies between us and the outside world, serving as protective barriers and sites of selective permeability. For each type of epithelial tissue, each layer of stratified epithelium has its own unique ECM, a complex network of fibrous proteins that provides mechanical and chemical cues that drive cell proliferation, survival, differentiation, cell polarity, and migration. Dysregulation of epithelial barriers can be indicative of local or systemic disease and permeability of epithelial barriers directly affects how drug is delivered across the ECM and into the circulation. Recently, it has been appreciated that the ECM cannot be fully studied as the fibrous proteins alone, but instead should be evaluated as the interconnected network of proteins that make up the structural core of the ECM along with proteins that are critical to ECM function and maintenance such as receptors and ECM-bound soluble factors. This interconnected network has been defined as the matrisome, a curated collection of 1027 genes, roughly 4% of the known human proteome. While the roles of individual ECM proteins and ECM downstream signaling networks on epithelial function and permeability have been investigated, three key knowledge gaps persist: 1) How does the epithelial matrisome change with extrinsic factors such as age, menstrual cycle, and inflammation? 2) How do changes to the epithelial matrisome affect drug absorption and transport? 3) How can we modulate the epithelial matrisome for selective bioavailability? To address the first knowledge gap, in Project 1 we will evaluate publicly available datasets and biospecimens using our novel machine learning and image analysis techniques to reveal the interconnected relationships between matrisome changes and extrinsic factors such as age, menstrual cycle phase, and immune landscape. These studies will be complemented by orthogonal in vitro studies using our library of tissue engineered models that capture the layered morphology of epithelium. To address the second knowledge gap, in Project 2 we will couple our in vitro models with statistical modeling and systems biology tools to determine key matrisome proteins that influence drug delivery across epithelial surfaces and their corresponding mechanisms of action. Lastly, to address the third knowledge gap, in Project 3 we will identify novel compounds that modulate bioavailability through matrisome-driven mechanisms, opening new avenues of direction for the design and delivery of novel therapeutics with selective bioavailability. Critically, the methods that we are developing are tissue, organ, and disease agnostic, facilitating an increased understanding of a wide variety of biological processes at a molecular, cellular, and tissue level.
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