68Ga-Labeled [Leu13ψThz14]Bombesin(7–14) Derivatives: Promising GRPR-Targeting PET Tracers with Low Pancreas Uptake
Bibliographic record
Abstract
The gastrin-releasing peptide receptor (GRPR) is a G-protein-coupled receptor that is overexpressed in many solid cancers and is a promising target for cancer imaging and therapy. However, high pancreas uptake is a major concern in the application of reported GRPR-targeting radiopharmaceuticals, particularly for targeted radioligand therapy. To lower pancreas uptake, we explored Ga-complexed TacsBOMB2, TacsBOMB3, TacsBOMB4, TacsBOMB5, and TacsBOMB6 derived from a potent GRPR antagonist sequence, [Leu13ψThz14]Bombesin(7–14), and compared their potential for cancer imaging with [68Ga]Ga-RM2. The Ki(GRPR) values of Ga-TacsBOMB2, Ga-TacsBOMB3, Ga-TacsBOMB4, Ga-TacsBOMB5, Ga-TacsBOMB6, and Ga-RM2 were 7.08 ± 0.65, 4.29 ± 0.46, 458 ± 38.6, 6.09 ± 0.95, 5.12 ± 0.57, and 1.51 ± 0.24 nM, respectively. [68Ga]Ga-TacsBOMB2, [68Ga]Ga-TacsBOMB3, [68Ga]Ga-TacsBOMB5, [68Ga]Ga-TacsBOMB6, and [68Ga]Ga-RM2 clearly show PC-3 tumor xenografts in positron emission tomography (PET) images, while [68Ga]Ga-TacsBOMB5 shows the highest tumor uptake (15.7 ± 2.17 %ID/g) among them. Most importantly, the pancreas uptake values of [68Ga]Ga-TacsBOMB2 (2.81 ± 0.78 %ID/g), [68Ga]Ga-TacsBOMB3 (7.26 ± 1.00 %ID/g), [68Ga]Ga-TacsBOMB5 (1.98 ± 0.10 %ID/g), and [68Ga]Ga-TacsBOMB6 (6.50 ± 0.36 %ID/g) were much lower than the value of [68Ga]Ga-RM2 (41.9 ± 10.1 %ID/g). Among the tested [Leu13ψThz14]Bombesin(7–14) derivatives, [68Ga]Ga-TacsBOMB5 has the highest tumor uptake and tumor-to-background contrast ratios, which is promising for clinical translation to detect GRPR-expressing tumors. Due to the low pancreas uptake of its derivatives, [Leu13ψThz14]Bombesin(7–14) represents a promising pharmacophore for the design of GRPR-targeting radiopharmaceuticals, especially for targeted radioligand therapy application.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 | 0.001 |
| 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 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".