Syntheses and Evaluation of Carbon-11- and Fluorine-18-Radiolabeled pan-Tropomyosin Receptor Kinase (Trk) Inhibitors: Exploration of the 4-Aza-2-oxindole Scaffold as Trk PET Imaging Agents
Bibliographic record
Abstract
Tropomyosin receptor kinases (TrkA/B/C) are critically involved in the development of the nervous system, in neurological disorders as well as in multiple neoplasms of both neural and non-neural origins. The development of Trk radiopharmaceuticals would offer unique opportunities toward a more complete understanding of this emerging therapeutic target. To that end, we first developed [(11)C]GW441756 ([(11)C]9), a high affinity photoisomerizable pan-Trk inhibitor, as a lead radiotracer for our positron emission tomography (PET) program. Efficient carbon-11 radiolabeling afforded [(11)C]9 in high radiochemical yields (isolated RCY, 25.9% ± 5.7%). In vitro autoradiographic studies in rat brain and TrkB-expressing human neuroblastoma cryosections confirmed that [(11)C]9 specifically binds to Trk receptors in vitro. MicroPET studies revealed that binding of [(11)C]9 in the rodent brain was mostly nonspecific despite initial high brain uptake (SUVmax = 2.0). Modeling studies of the 4-aza-2-oxindole scaffold led to the successful identification of a small series of high affinity fluorinated and methoxy derivatized pan-Trk inhibitors based on our lead compound 9. Out of this series, the fluorinated compound 10 was selected for initial evaluation and radiolabeled with fluorine-18 (isolated RCY, 2.5% ± 0.6%). Compound [(18)F]10 demonstrated excellent Trk selectivity in a panel of cancer relevant kinase targets and a promising in vitro profile in tumors and brain sections but high oxidative metabolic susceptibility leading to nonspecific brain distribution in vivo. The information gained in this study will guide further exploration of the 4-aza-2-oxindole scaffold as a lead for Trk PET ligand development.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; a candidate call from one source (direct Gemma or distilled Codex), 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".