Toward Optimized 89Zr-Immuno-PET: Side-by-Side Comparison of [89Zr]Zr-DFO-, [89Zr]Zr-3,4,3-(LI-1,2-HOPO)- and [89Zr]Zr-DFO*-Cetuximab for Tumor Imaging: Which Chelator Is the Most Suitable?
Bibliographic record
Abstract
89Zr represents a highly favorable positron emitter for application in immuno-PET (Positron Emission Tomography) imaging. Clinically, the 89Zr4+ ion is introduced into antibodies by complexation with desferrioxamine B. However, producing complexes of limited kinetic inertness. Therefore, several new chelators for 89Zr introduction have been developed over the last years. Of these, the direct comparison of the most relevant ones for clinical translation, DFO* and 3,4,3-(LI-1,2-HOPO), is still missing. Thus, we directly compared DFO with DFO* and 3,4,3-(LI-1,2-HOPO) immunoconjugates to identify the most suitable agent stable 89Zr-complexation. The chelators were introduced into cetuximab, and an optical analysis method was developed, enabling the efficient quantification of derivatization sites per protein. The cetuximab conjugates were efficiently obtained and radiolabeled with 89Zr at 37 °C within 30 min, giving the [89Zr]Zr-cetuximab derivatives in high radiochemical yields and purities of >99% as well as specific activities of 50 MBq/mg. The immunoreactive fraction of all 89Zr-labeled cetuximab derivatives was determined to be in the range of 86.5−88.1%. In vivo PET imaging and ex vivo biodistribution studies in tumor-bearing animals revealed a comparable and significantly higher kinetic inertness for both [89Zr]Zr-3,4,3-(LI-1,2-HOPO)-cetuximab and [89Zr]Zr-DFO*-cetuximab, compared to [89Zr]Zr-DFO-cetuximab. Of these, [89Zr]Zr-DFO*-cetuximab showed a considerably more favorable pharmacokinetic profile with significantly lower liver and spleen retention than [89Zr]Zr-3,4,3-(LI-1,2-HOPO)-cetuximab. Since [89Zr]Zr-DFO* demonstrates a very high kinetic inertness, paired with a highly favorable pharmacokinetic profile of the resulting antibody conjugate, DFO* currently represents the most suitable chelator candidate for stable 89Zr-radiolabeling of antibodies and clinical translation.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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".