All ETDs from UAB

Advisory Committee Chair

Mk Sewell-Loftin

Document Type


Date of Award


Degree Name by School

Master of Science in Biomedical Engineering (MSBME) School of Engineering


Ovarian cancer is the 5th leading cause of cancer deaths for women, primarily due to treatment resistant and/or recurrent disease. Most cases of ovarian cancer are not diagnosed until distant metastases have formed, which drastically reduces overall survival. The median age at diagnosis is 63 and most cases occur in patients who are peri- and post-menopausal. There is a critical gap between the clinical presentation of ovarian cancer and the preclinical models used to study the disease. Most preclinical in vivo investigations use mice who are between 6 and 12 weeks old, which corresponds to roughly a 20-year-old human. Therefore, there is a significant need to address the discrepancy between current in vivo and in vitro models to elucidate how the changes in the tumor microenvironment (TME) related to extracellular matrix (ECM) composition alter disease progression. The combination of age-related and cancer-related ECM remodeling poses a unique challenge to fully understanding the role of the ECM in ovarian cancer progression. In response to this challenge, we propose that a 3D TME model will allow for isolation and observation of the effects of ECM remodeling on ovarian cancer progression and serve as a model for ovarian cancer in aged patients. In this project, we fabricated matrices that correspond to different levels of maturity and both initial and advanced disease by altering hyaluronic acid and collagen content and evaluated changes in cell proliferation and SNAIL1, a protein implicated in cancer metastasis, expression in response to changes in the ECM. Generally, our results show that SNAIL1 expression and proliferation increased with increasing HA and collagen content in the matrices. Additionally, we utilized a microfluidic device to analyze migration between matrices of different compositions. Our results suggest that matrix cues alone may not be sufficient to drive migration of ovarian cancer cells. Overall, we successfully fabricated a model of the ovarian TME that allows for precise control of the ECM to evaluate how changes affect proliferation of cells and other markers of disease progression.

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Engineering Commons



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