18F-Labeled Cyclized α-Melanocyte-Stimulating Hormone Derivatives for Imaging Human Melanoma Xenograft with Positron Emission Tomography
Bibliographic record
Abstract
Abstract Since metastatic melanoma is deadly, early diagnosis thereof is crucial for managing the disease. We recently developed α-melanocyte-stimulating hormone (αMSH) derivatives, [ 68 Ga]Ga-CCZ01048 and [ 18 F]CCZ01064, that target the melanocortin 1 receptor (MC1R) for mouse melanoma imaging. In this study, we aim to evaluate [ 18 F]CCZ01064 as well as a novel dual-ammoniomethyl-trifluoroborate (AmBF 3 ) derivative, [ 18 F]CCZ01096, for targeting human melanoma xenograft using μPET imaging. The peptides were synthesized on solid phase using Fmoc chemistry. Radiolabeling was achieved in a one-step 18 F- 19 F isotope-exchange reaction. μPET imaging and biodistribution studies were performed in NSG mice bearing SK-MEL-1 melanoma xenografts. The MC1R density on the SK-MEL-1 cell line was determined to be 972 ± 154 receptors/cell (n = 4) via saturation assays. Using [ 18 F]CCZ01064, moderate tumor uptake (3.05 ± 0.47%ID/g) and image contrast were observed at 2 h post-injection. Molar activity was determined to play a key role. CCZ01096 with two AmBF 3 motifs showed comparable sub-nanomolar binding affinity to MC1R and much higher molar activity. This resulted in improved tumor uptake (6.46 ± 1.42%ID/g) and image contrast (tumor-to-blood and tumor-to-muscle ratios were 30.6 ± 5.7 and 85.7 ± 11.3, respectively) at 2 h post-injection. [ 18 F]CCZ01096 represents a promising αMSH-based μPET imaging agent for human melanoma and warrants further investigation for potential 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".