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    Cancer Technologies

    Autofluorescence lifetime imaging reveals the role of metabolism in cancer immunosuppressive response to interferon gamma

    (F-210) Autofluorescence lifetime imaging reveals the role of metabolism in cancer immunosuppressive response to interferon gamma

    Saturday, October 14, 2023
    9:30 AM – 10:30 AM PDT
    Location: Exhibit Hall - Row F - Poster # 210

      Presenting Author(s)

    • CW

      Cole Weaver

      Undergraduate Research Assistant
      Department of Biomedical Engineering, University of Wisconsin-Madison
      McFarland, Wisconsin, United States

      • Co-Author(s)

    • DP

      Dan Pham

      Graduate Student
      Department of Biomedical Engineering, University of Wisconsin-Madison, United States

      • Primary Investigator(s)

    • MS

      Melissa Skala

      Professor of Biomedical Engineering, Medical Physics
      University of Wisconsin - Madison, United States

    Introduction:: Membrane expression of Programmed Cell Death Ligand 1 (PD-L1) mediates tumor immune escape and poses a major challenge for translation of immunotherapy against solid tumors. PD-L1 acts as an immunosuppressant that binds to the programmed cell death-1 (PD-1) receptor on T cells and deactivates them. In several solid tumor models, PD-L1 expression is induced by Interferon Gamma (IFN-γ), an inflammatory cytokine produced by activated T cells. However, the role of cancer metabolism during this process is poorly understood. In this project, we used optical metabolic imaging (OMI) to study the effect of IFN-γ on PD-L1 expression and metabolism of 3 human cancer models: PanC-1 (pancreatic ductal adenocarcinoma (PDAC)), CHLA-20 (neuroblastoma), and HeLa (cervical cancer). Among these, PDAC, with the lowest 5-year overall survival rate of less than 8%, has a dense stroma that limits immune cell infiltration. OMI is a non-invasive method to monitor cell metabolism that relies on autofluorescence intensity and lifetime microscopy of metabolic coenzymes NAD(P)H and FAD. The intensity of NAD(P)H indicates the prevalence of NAD(P)H in the cells and the mean lifetime (τm) is a weighted average of free- and protein-bound lifetimes.

    (Note: Sub Track is Cancer Immunoengineering, Immunomodulation and Immunotherapy)

    Materials and Methods::

    24 hours prior to imaging, PanC-1, HeLa, and CHLA-20 cells were plated onto a 35mm glass-bottom Petri dish in DMEM (10% FBS and 1% Pen:Strep) +/- 10ng IFN-γ. Both the control and IFN-g treated cells were stained with 2.5ml of PerCP/Cyanine5.5 anti-human PD-L1 before imaging. OMI was performed on a two-photon microscope to generate autofluorescence (NAD(P)H and FAD) and immunofluorescence (PD-L1) images. NAD(P)H and FAD fluorescence lifetimes were analyzed using SPCImage software, and individual cell cytoplasms were segmented in CellProfiler. NAD(P)H intensity was normalized to the mean of respective control group for each replicate.



    Results, Conclusions, and Discussions:: Results and Discussion: IFN-γ treatment induced PD-L1 expression in CHLA-20 and HeLa cells, but not in PanC-1 cells (Fig. 1A). PanC-1 cells also showed different metabolic changes when treated with IFN-γ compared to CHLA-20 and HeLa cells. IFN-γ treatment significantly decreased NAD(P)H tm and increased NAD(P)H intensity in CHLA-20 and HeLa cells (Fig. 1B-C). Meanwhile, IFN-γ treated PanC-1 cells have a significantly higher NAD(P)H tm and a significantly lower normalized NAD(P)H intensity than control group (Fig. 1B-C). These autofluorescence changes indicate an increased dependence of IFN-γ treated PanC-1 on an oxidative metabolic pathway (potentially oxidative phosphorylation). Meanwhile IFN-γ treated CHLA-20 and HeLa cells shifted their metabolism towards a reduced metabolic pathway (potentially glycolysis).

    Conclusion: Our results demonstrated that compared to HeLa and CHLA-20, PanC-1 showed different responses in metabolism and PD-L1 expression towards inflammatory cytokine IFN-g. These differences indicate a potential relationship between cancer cell metabolism and their immunosuppressive functions. Our future work will further investigate this relationship to better understand the metabolic irregularities of PDAC and support the development of metabolic therapy or immunotherapy for PDAC treatment.


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