Peyton:Research

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Matrix Physicochemical Cues as Chemotherapeutic Protective Agents in Hepatocellular Carcinoma Thuy Nguyen Thuy is building a highthroughput biomaterial system in which to quantify how cancer cells respond to drugs in the presence of physiologically relevent stiffness and adhesive protein cues. Inflammatory Feedback Loops in Cardiovascular Disease Will Herrick Funding: ICE IGERT Cardiovascular disease has been the number one killer in the United States since 1900 for every year except one, and will be responsible for 37% of all deaths in the U.S. this year alone. Arteriosclerosis is defined by hardening of the arteries: a general term for arterial wall thickening and loss of elasticity. Matrix properties in atherosclerotic arteries, such as the existence of macrophages and cytokines from atherosclerotic plaques, arterial wall elasticity, and the portfolio of insoluble adhesive proteins, are altered in the onset of cardiovascular disease. Coincident with these matrix changes, smooth muscle cells (SMCs) are observed to undergo phenotypic dedifferentiation, described by gene transcription, motility/invasion, and matrix degradation/production. We are investigating the ability of matrix state to trigger SMC motility and invasion via a specific signaling network. With a novel set of tools, including biomaterials and a small shRNA library coding for genes important to SMC differentiation and motility, we can control both of the inputs to this hypothesized feedback loop. This research will generate synthetic engineered arterial mimics in which to study the biophysical crosstalk between SMCs and the chemical and physical microenvironment. These studies will lead to identification of druggable signaling nodes, to regulate SMC phenotype in patients with atherosclerosis. Stiffness Sensing as a Metastatic Indicator Collaboration with the Al Crosby Lab at the University of Massachusetts, Polymer Science Dannielle Ryman Funding: MRSEC Metastasis is the leading cause of fatality for women diagnosed with breast cancer. It is well known that tumor environments stiffen: palpitation remains a powerful tool for early tumor detection. More recently, this matrix stiffening event at the sites of tumors has been linked to morphological changes in the tumor itself, and it is hypothesized by us and others that these stiffness changes may contribute to single cell metastasis. However, the mechanisms by which metastatic cells sense and respond to stiffness is unclear, and it is not yet known if metastatic cells respond to stiffness cues in a unique way. We are working with Yuri Ebata and Yujie Liu from Al Crosby's lab in PSE to make novel substrates with unique presentation of stiffness arrays and mechanical length scales. We are visualizing how breast cancer cells of varying known metastatic capability sense and respond (namely, migration and mitosis) to these changes in stiffness. From there, we will identify the molecular mechanisms by which these cells have either heightened or dampened stiffness sensing, in order to develop novel druggable targets to prevent metastasis in vivo. Predicting Tissue Tropism in Metastasis Erinn Dandley While specific genetic signatures have been correlated with metastatic potential, and, in some cases, prediction of metastatic tissue site, there exists no biophysical explanation for metastatic site determination. Increasing evidence suggests that the physicochemical factors within the extracellular milieu may regulate tumor growth, morphology, and tumor cell motility. The overwhelmingly complex nature of the tumor microenvironment in vivo, which includes numerous extracellular matrix proteins, cell types, inflammatory chemokines, and proteolytic enzymes, presents a significant challenge in parsing the role of physicochemical cues involved in regulating metastasis. There exists a critical need for novel in vitro experimental systems that can mimic the metastatic niche in a well-defined, controllable, and reproducible manner. We are developing novel biomaterials to systematically measure breast cancer metastasis in response to physiologically relevant physiochemical cues. We are employing mathematical modeling tools to both describe and predict the relationship between physicochemical cues of the metastatic site and the predetermined signaling network within metastatic breast cancer cell lines. Within the scope of this project, we will identify components of intracellular signaling pathways involved in metastatic site preference. These pathways could serve as checkpoints for pharmaceutical intervention, and, in the long term, control of breast cancer metastasis. Anomalous Diffusion Methods to Predict 3D Stem Cell Motility in Porous Scaffolds Jaclyn Somadelis and Tyler Vlass Design of 3D scaffolds that can facilitate proper survival, proliferation, and differentiation of stem cells is a challenge for clinical applications involving large connective tissue defects. Cell migration within such scaffolds is a critical process governing tissue integration. We are currently using mathematical modeling techniques based on anomalous diffusion parameters to connect the effects of scaffold pore diameter, in concert with matrix stiffness and adhesivity, as independently tunable parameters to marrow-derived stem cell invasion into 3D synthetic scaffolds.