Single-Cell Imaging Using Radioluminescence Microscopy Reveals Unexpected Binding Target for [18F]HFB

Cell-based therapies are showing great promise for a variety of diseases, but remain hindered by the limited information available regarding the biological fate, migration routes and differentiation patterns of infused cells in trials. Previous studies have demonstrated the feasibility of using positron emission tomography (PET) to track single cells utilising an approach known as positron emission particle tracking (PEPT). The radiolabel hexadecyl-4-[¹⁸F]fluorobenzoate ([¹⁸F]HFB) was identified as a promising candidate for PEPT, due to its efficient and long-lasting labelling capabilities. The purpose of this work was to characterise the labelling efficiency of [¹⁸F]HFB in vitro at the single-cell level prior to in vivo studies.

The binding efficiency of [¹⁸F]HFB to MDA-MB-231 and Jurkat cells was verified in vitro using bulk gamma counting. The measurements were subsequently repeated in single cells using a new method known as radioluminescence microscopy (RLM) and binding of the radiolabel to the single cells was correlated with various fluorescent dyes.

Similar to previous reports, bulk cell labelling was significantly higher with [¹⁸F]HFB (18.75 ± 2.47 dpm/cell, n = 6) than 2-deoxy-2-[¹⁸F]fluoro-D-glucose ([¹⁸F]FDG) (7.59 ± 0.73 dpm/cell, n = 7; p ≤ 0.01). However, single-cell imaging using RLM revealed that [¹⁸F]HFB accumulation in live cells (8.35 ± 1.48 cpm/cell, n = 9) was not significantly higher than background levels (4.83 ± 0.52 cpm/cell, n = 12; p > 0.05) and was 1.7-fold lower than [¹⁸F]FDG uptake in the same cell line (14.09 ± 1.90 cpm/cell, n = 13; p < 0.01). Instead, [¹⁸F]HFB was found to bind significantly to fragmented membranes associated with dead cell nuclei, suggesting an alternative binding target for [¹⁸F]HFB.

This study demonstrates that bulk analysis alone does not always accurately portray the labelling efficiency, therefore highlighting the need for more routine screening of radiolabels using RLM to identify heterogeneity at the single-cell level.