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Noninvasive Imaging of Natural Killer Cell-Mediated Apoptosis in a Mouse Tumor Model
Thoudam Debraj Singh1, Jaetae Lee2,3, Yong Hyun Jeon4,5
1Department of Nuclear Medicine, Kyungpook National University Hospital, Daegu, South Korea.
Abstract:
Natural killer (NK) cells are cytotoxic lymphocytes that induce apoptosis in cancer cells infected with viruses and bacteria through a caspase-3-dependent pathway. Effective NK cell-based immunotherapy requires highly sensitive imaging tools for in vivo monitoring of the dynamic events involved in apoptosis. Here, we describe a noninvasive bioluminescence imaging approach to determine the antitumor effects of NK cell-based therapy by serial imaging of caspase-3-dependent apoptosis in a mouse model of human glioma.
Insights
Natural killer (NK) cells fight cancer by triggering apoptosis. This study introduces a new bioluminescence imaging method to track NK cell therapy
Area of Science:
- Immunology
- Oncology
- Biomedical Imaging
Background:
- Natural killer (NK) cells are crucial cytotoxic lymphocytes.
- NK cells induce apoptosis in cancer cells via a caspase-3-dependent pathway.
- Effective NK cell immunotherapy necessitates sensitive in vivo monitoring tools.
Purpose of the Study:
- To develop and validate a noninvasive bioluminescence imaging (BLI) approach.
- To monitor the dynamic events of caspase-3-dependent apoptosis in vivo.
- To assess the antitumor effects of NK cell-based therapy for human glioma.
Main Methods:
- Utilized a mouse model of human glioma.
- Employed serial bioluminescence imaging.
- Focused on tracking caspase-3-dependent apoptosis as a readout.
Main Results:
- Demonstrated the feasibility of noninvasive in vivo imaging of apoptosis.
- Successfully monitored the antitumor effects of NK cell therapy.
- Provided a dynamic visualization of therapeutic response.
Conclusions:
- Noninvasive BLI is a powerful tool for evaluating NK cell therapy.
- This method allows for real-time assessment of apoptosis-induced tumor regression.
- The approach holds promise for optimizing cancer immunotherapy strategies.
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