DFO-Km: A Modular Chelator as a New Chemical Tool for the Construction of Zirconium-89-Based Radiopharmaceuticals
Bibliographic record
Abstract
Zirconium-89-labeled monoclonal antibodies and other large macromolecules such as nanoparticles hold great promise as positron emission tomography imaging agents. In general, zirconium-89 is an ideal radionuclide for long-circulating vectors such as antibodies or nanoparticles. It is also a promising radionuclide for theranostic radiopharmaceuticals due to its suitable match in half-life with actinium-225, thorium-227, lutetium-177, and others. As such, demand for new and optimized bifunctional chelators for zirconium-89 continues to grow. Herein, we present the modular chelator DFO-Km, which is octadentate and features lysine as a modular amino acid linker. The modular amino acid linker can be changed to other natural or unnatural amino acids to access different bioconjugation chemistries, while the chelating portion is unchanged thus retaining identical metal ion coordination properties to DFO-Km. The epsilon-amine in the DFO-Km linker (lysine) was used to complete synthesis of a bifunctional derivative bearing a p -SCN-Ph moiety. The chelator DFO-Km includes a redesigned hydroxamic acid, which provides more flexibility for metal ion coordination relative to the monomer used in the previously published DFO-Em. Moreover, a set of comprehensive DFT calculations were performed to model and evaluate 16 geometric isomers of Zr-(DFO-Km), which suggested the complex would form the optimum cic–cis–trans–trans octadentate Zr(IV) coordination geometry with no aqua or hydroxide ligands present. The bifunctional derivative p -SCN-Ph-DFO-Km was compared directly with the commercially available p -SCN-Ph-DFO, and both underwent efficient conjugation to a nonspecific human serum antibody (IgG) to yield two model immunoconjugates. The behavior of [ 89 Zr]Zr-DFO-Km-IgG was studied in healthy mice for 2 weeks and compared to an equivalent cohort injected with [ 89 Zr]Zr-DFO-IgG as a clinical “gold standard” control. PET-CT and biodistribution results revealed higher stability of [ 89 Zr]Zr-(DFO-Km)-IgG in vivo over [ 89 Zr]Zr-DFO-IgG, as demonstrated by the significant reduction of zirconium-89 in the whole skeleton as visualized and quantified by PET-CT at 1, 3, 7, and 14 days post-injection. Using CT-gated regions of interest over these PET-CT images, the whole skeleton was selected and uptake values were measured at 14 days post-injection of 3.6 ± 0.9 (DFO) vs 1.9 ± 0.1 (DFO-Km) %ID/g ( n = 4, * p = 0.02), which represents a ∼48% reduction in bone uptake with DFO-Km relative to DFO. Biodistribution experiments performed on these same mice following the 14 day imaging time point revealed bone (both tibia) uptake values of 3.7 ± 1.3 (DFO) vs 2.0 ± 0.6 (DFO-Km) %ID/g ( n = 6, * p < 0.05), with the tibia uptake values in close agreement with whole-skeleton ROI PET-CT data. These results indicate that DFO-Km is an improved chelator for [ 89 Zr]Zr 4+ applications relative to DFO. The bifunctional chelator p -SCN-Ph-DFO-Km shows potential as a new chemical tool for creating bioconjugates using targeting vectors such as antibodies, peptides, and nanoparticles.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".