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Title page for ETD etd-03092015-132912

Type of Document Dissertation
Author Walsh, Alexandra Jule
Author's Email Address alex.walsh@vanderbilt.edu
URN etd-03092015-132912
Title Development of Optical Imaging of Metabolism for Monitoring and Predicting Drug Efficacy
Degree PhD
Department Biomedical Engineering
Advisory Committee
Advisor Name Title
Melissa C. Skala Committee Chair
Anita Mahadevan-Jansen Committee Member
H. Charles Manning Committee Member
Jamey Young Committee Member
Rebecca S. Cook Committee Member
  • NADH
  • fluorescence lifetime imaging
  • cellular metabolism
  • FAD
  • breast cancer
  • organoids
Date of Defense 2015-02-26
Availability unrestricted
A clinical need exists for improved methods to identify cancer patients with tumors prone to drug resistance, and prescribe effective alternative therapies. Cellular metabolism is a powerful marker of tumor response to treatment, because the oncogenic drivers targeted by anti-cancer drugs often regulate cellular metabolism. In this dissertation, optical metabolic imaging (OMI) is developed to detect drug-induced metabolism changes in breast cancer cells, in vivo xenograft tumors, and primary-tumor derived organoids. OMI probes the auto-fluorescence intensity and lifetime of NAD(P)H and FAD, coenzymes of metabolism, to quantify protein concentrations and protein-binding dynamics. A composite endpoint, the OMI index, provides a robust, dynamic readout of cellular metabolism. OMI endpoints were evaluated and characterized in a panel of breast cancer cell lines and three xenograft models in vivo with and without drug treatment. For optimal clinical utility, protocols were developed to generate 3D organoid cultures of primary tumor biopsies for high-throughput testing of potential drugs. In xenograft tumor derived organoids, the OMI index decreased in responsive organoids treated with anti-cancer drugs, corroborating with in vivo tumor growth curves. Feasibility experiments on organoids derived from human patient biopsies demonstrated viability of organoids and drug-induced changes in OMI index. The high-resolution images of OMI allow cellular-level analysis of heterogeneity. Heterogeneity profiles of resistant cell populations within organoids were identified and tracked over 72 hours. With these findings, OMI shows potential for development into a high-throughput organoid screen to test the efficacy of a panel of drugs and drug combinations to direct clinical therapy selection and expedite pre-clinical studies.
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