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Title page for ETD etd-03252016-005143

Type of Document Dissertation
Author Dadwal, Ushashi Chand
URN etd-03252016-005143
Title Studying Tumor Induced Bone Disease using ex vivo Bone Analogue Systems to Aid Drug Prediction, Efficacy and Validation
Degree PhD
Department Chemical Engineering
Advisory Committee
Advisor Name Title
Scott Guelcher Committee Chair
Julie Sterling Committee Co-Chair
Mathew Lang Committee Member
Peter Cummings Committee Member
  • 3D models
  • Bioreactor
  • Metastasis
  • Tumor Induced Bone Disease
  • Polyurethane
Date of Defense 2016-03-18
Availability unrestricted
Patients with Tumor Induced Bone Disease (TIBD) arising from several primary cancers including breast, lung, prostate cancer, suffer from extreme pain, bone loss, and frequent fracture which contribute to loss in quality of life and increase in cancer-related deaths. This condition is incurable and managed by palliative interventions, focused on length and quality of life. While the importance of interactions between bone and tumors is well established, the mechanism by which the physical bone microenvironment regulates disease progression is limited by the lack of suitable models.

The aim of this work was to develop bone analogue model systems to study TIBD and test the efficacy, efficiency and effectiveness of therapeutics. First, we designed 3D-printed scaffolds with Fused Deposition Modeling (FDM) to investigate how the mechanical and topological properties of the bone microenvironment regulate bone-metastatic gene expression by tumor cells. The expression of specific genes associated with bone metastasis and destruction significantly increased with increasing substrate rigidity, flow rate and decreasing pore size. Importantly, drug response differed remarkably when tumors were cultured on bone-like 3D scaffolds compared to tissue culture well plates. When scaffolds seeded with tumor cells were implanted subcutaneously in mice, infiltration of host-immune cell populations further increased expression of bone-metastatic genes by the transplanted tumor cells.

Second, we simulated TIBD progression using a population dynamic model quantified with experimental data. We determined our computational model accurately reflects loss in bone mass, characteristic of TIBD and illustrates how treatment approaches may be investigated. These studies highlight the application of in vitro and in sillico models in investigating tumor and bone interactions and testing inhibitors of TIBD.

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