Direct Aromatic F-18-labeling of Tetrazines:A Rapid and Convenient Entry to Tetrazines for Pretargeted PET Imaging [Meeting Abstract]
Bibliographic record
Abstract
<b>134</b> <h3><b>Introduction:</b></h3> Recently, tetrazines have been successfully developed as pretargeted imaging agents. Particularly, they have been of interest when used with trans-cyclooctene (TCO) modified mAbs for pretargeted immunoimaging due to their fast reaction kinetics <i>in vivo</i> as well as their high specificity. (1) Pretargeting is based on a two-step process in which a TCO-tagged nanomedicine, for example an antibody, is administered and allowed to accumulate followed by a short-lived radiolabeled tetrazine. The latter reagent is able to form a stable covalent conjugate with the TCO through a bioorthogonal reaction. (2,3) This approach results in an enhanced safety profile as well as a higher image quality when compared to conventional radioimmunoimaging. (4) Many attempts to label highly reactive tetrazines with <sup>18</sup>F, the most ideal nuclide for PET imaging, have been attempted. However, no successful <sup>18</sup>F-direct labeling approach has been reported so far with enough radiochemical yields (RCYs). (5) In this work, we successfully developed a direct aromatic <sup>18</sup>F-labeling approach of tetrazines. <h3><b>Methods:</b></h3> Initially, a low reactive methyl-tetrazine was selected as a model compound to evaluate the feasibility of the synthesis and radiolabelling of a set of precursors through direct aromatic fluorinations (<i>Figure 1</i>). Thereafter, the best labeling approach was optimized in respect to labeling conditions varying temperature, time and base amount. In a next step, we studied the substrate scope of the reaction on a set of tetrazines including methyl-, H-, phenyl- and pyridyl- tetrazines (<i>Figure 2</i>). The effect of electron withdrawing and electron donating groups on the aromatic ring was evaluated in terms of synthetic accessibility, radiochemical conversion (RCC) and RCY (<i>Figure 3</i>). <h3><b>Results:</b></h3> Out of all tested labeling reactions, radiolabeling only succeeded through Cu-mediated <sup>18</sup>F-fluorination using stannate precursors (<i>Figure 1)</i>. Moderate to good RCYs (10-24%) were obtained for methyl-, phenyl- and H-tetrazines. 2-Pyridyl structures were prohibitive, most likely due to a chelation effect of copper with the respective pyridyl moieties of the tetrazines <i>(Figure 2</i>). Subsequently, we investigated which substitution pattern of the H-tetrazine yielded in highest RCYs. Best results were obtained with a 3,5-substitution pattern (<i>Figure 3</i>). <h3><b>Conclusions:</b></h3> This work showed the first <sup>18</sup>F-direct labeling strategy of highly reactive tetrazines, starting from organotin precursors via a Cu-mediated approach. The developed procedure is simple, short, reproducible as well as scalable and as such, superior to previously used <sup>18</sup>F-multistep labeling strategies with regard to clinical applications. Currently, we are working on the first directly <sup>18</sup>F-radiolabeled tetrazine structures, which will be used for pretargeted brain and cancer imaging. <b>Acknowledgments:</b> This project has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No 813528. This project has also received funding from the European Union9s Horizon 2020 research and innovation program under grant agreement No 668532: Click-it.<b><i>Figure 1</i></b><i>. Radiolabeling strategies using different methyl-tetrazine precursors to probe the fluorination.</i><b><i>Figure 2</i></b><i>. Radiolabeling with Cu-mediated fluorination reaction of higher reactive tetrazines. *The radiolabeled compound was never isolated. †Preliminary studies based on n=2.</i><b><i>Figure 3</i></b><i>. Study of the RCCs when including in the aromatic ring different linkers. *The stannate precursor was never isolated. **The radiolabeled compound was never isolated.</i><i>†Preliminary studies based on n=2.</i>
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.065 | 0.001 |
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; both teacher heads agree on what is shown here.
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".