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SEP 17, 2020 12:15 PM EDT

Metabolic imaging of cellular heterogeneity in patient-derived cancer organoids

Speaker
  • Morgridge Institute for Research, Madison WI
    Biography
      Melissa Skala received her B.S. in Physics at Washington State University in 2002, her M.S. in Biomedical Engineering at the University of Wisconsin-Madison in 2004, and her Ph.D. in Biomedical Engineering at Duke University in 2007. Her postdoctoral training was also in Biomedical Engineering at Duke University, from 2007-2010. From 2010-2016, she was an Assistant Professor of Biomedical Engineering at Vanderbilt University. In 2016 she moved her lab to the Morgridge Institute for Research and Department of Biomedical Engineering at the University of Wisconsin - Madison. Her lab focuses on developing biomedical optical imaging technologies, personalized cancer treatment technologies, and more effective cancer therapies.

    Abstract

    Abnormal cellular metabolism is a hallmark of many diseases, yet there is an absence of quantitative methods to dynamically image metabolism with cellular-level resolution. Optical metabolic imaging (OMI) quantifies the fluorescence intensities and lifetimes of the metabolic co-enzymes NAD(P)H and FAD using two-photon microscopy. OMI is a label-free, high-resolution, quantitative tool for monitoring cellular metabolism within intact samples. OMI has been applied to 3D primary tumor organoids derived from patients to rapidly test multi-drug response. This platform has been validated in mouse models of breast and pancreas cancer, and feasibility has been tested in human tumors with chemotherapies, targeted therapies, radiation, and experimental drugs. The cellular-level assessment of OMI allows for sub-populations of cells with varying response to drug treatment to be tracked over time, to monitor therapeutic effect in resistant cell populations. OMI has recently been extended to image immune cell activation and function. These metabolic imaging tools have significant implications for rapid cellular-level assessment of metabolic response to drug treatment within engineered tissues, which could impact drug development and clinical treatment planning.


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