Biomaterials ScienceBioengineeringPeer-reviewed journal article
Towards Reliable Tracking of Natural Killer Cells Using Commercial Iron Oxide Nanoparticles and Magnetic Particle Imaging
Suzanne E. LightseyiD, Victoria ConsalvoiD, Sk Rajab AliiD, Daniela Paola ValdésiD, Jeremiah L. OyeriD, Grace Gloger, Alicja Joanna CopikiD, Carlos RinaldiiD, Blanka SharmaiD
Abstract
Non-invasive tracking of natural killer (NK) cells remains a major challenge in cancer immunotherapy, limiting our understanding of their in vivo migration and persistence. Magnetic particle imaging (MPI) offers a quantitative, real-time method for visualizing labeled cells, yet optimal labeling protocols for NK cells have not been established. Here, we evaluate commercially available iron oxide nanoparticles (IONPs) for MPI labeling of both NK92MI cells and primary human NK cells. Labeled cells retained viability and cytotoxicity, including activity against three-dimensional tumor spheroids, and were detectable by MPI. To further examine imaging performance in a biologically relevant context, we employed mouse phantoms that recapitulate organ-specific signal distributions, enabling evaluation of quantification and liver spillover effects. We identify key tradeoffs between particle colloidal stability and per-cell iron content: VivoTrax and VivoTrax Plus provided higher MPI signal but required post-labeling purification, reducing cell recovery, whereas Synomag-D and Perimag were more stable and preserved cell yield despite lower signal intensity per cell. These results provide a framework for selecting nanoparticles that balance detection sensitivity, cell viability, and workflow practicality, advancing non-invasive NK cell tracking.
- organism: human
- organism: mouse
- assay: imaging
- research focus: cell type annotation
- research focus: cell-cell communication
- research focus: drug response / drug discovery
- research focus: benchmarking
- approach: experimental assay
- approach: microscopy & imaging analysis
- Citations
- 0
- FWCI
- 0.00
- Field percentile
- 21th percentile
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