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In vivo Fluorescent Molecular Imaging Using Nanobodies Labeled with Next-Generation FNIR-Tag-Dyes
Dora M Chigoho1, Marcus C M Stroet1, Jelena Saliën1
1Laboratory for Molecular Imaging and Therapy (MITH), Vrije Universiteit Brussel, Laarbeeklaan 103, 1090, Brussels, Belgium.
Molecular Imaging and Biology
|July 23, 2026
Summary
Fluorescently labeled Nanobodies (Nbs) with FNIR-Tag dyes enable effective tumor visualization within 1 hour. Dye selection impacts detection sensitivity, influencing clinical imaging applications.
Area of Science:
- Molecular imaging
- Nanotechnology
- Bioconjugation chemistry
Background:
- Fluorescently labeled Nanobodies (Nbs) offer high-contrast molecular imaging for applications like fluorescence-guided surgery.
- Dye properties significantly impact the performance of imaging tracers.
Purpose of the Study:
- Evaluate three next-generation FNIR-Tag dyes conjugated to an anti-EGFR Nanobody (Nb) for molecular imaging.
- Assess the impact of different dye properties on tracer performance in vivo.
Main Methods:
- Conjugated anti-EGFR Nb 7D12 to FNIR-Tag-1.0, FNIR-Tag-766, and FNIR-Tag-804.
- Performed in vitro characterization and in vivo imaging and biodistribution studies.
- Assessed pharmacokinetics, tumor uptake, tumor-to-background ratios, contrast-to-noise ratios, and renal clearance.
Main Results:
- All Nb-based tracers showed rapid tumor accumulation and clearance from blood and non-target tissues, with predominant renal elimination.
- 7D12-FNIR-Tag-1.0 had higher tumor uptake; 7D12-FNIR-Tag-766 showed improved tumor-to-background and contrast-to-noise ratios.
- 7D12-FNIR-Tag-804 had lower tumor signal but comparable contrast due to reduced background; distinct renal handling was observed between dyes.
Conclusions:
- FNIR-Tag labeled Nbs facilitate effective tumor visualization as early as 1 hour post-injection.
- While overall biodistribution was similar, differences in tissue uptake, brightness, and system compatibility influence detection sensitivity.
- Careful dye selection is crucial for optimizing detection sensitivity in clinical imaging applications.
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