Imaging of human bradykinin B1 receptor expression: Impact of in vivo metabolic stability on tumor visualization
Bibliographic record
Abstract
1173 Objectives The Bradykinin (BK) B1 receptor (hB1R) is upregulated in various cancers. BK is mainly metabolized by angiotensin coverting enzyme (ACE) and neutral endopeptidase (NEP). We evaluated tumor uptake with 68Ga-DOTA-Ahx-Lys-[Leu8,desArg9]BK (P03083), a radioligand based on natural BK sequence, with/without peptidase inhibition, compared to 68Ga-DOTA-Ahx-Lys-[Hyp3,Cha5,Leu8,desArg9]BK (SH01078), a peptide designed to improve metabolic stability. Methods Peptides were synthesized in-house, with Hyp3 and Cha5 substitutions for SH01078 to improve in vivo stability. Binding affinity (Ki) was measured by competitive binding assays using CHO:hB1R membrane. 68Ga labelling was performed in NaOAc buffer (pH 4.1) with microwave heating for 1 min. PET imaging and biodistribution studies were conducted in NSG mice bearing wild-type HEK293T (WT) and transfected HEK293T:hB1R (T) tumors. Results P03083 and SH01078 bound hB1R with high affinity, with Ki values of 2.6 ± 7.2 nM, and 27.8 ± 4.9 nM. Both [68Ga] compounds were obtained in high radiochemical yield (>70%) and purity (>99%). PET imaging and biodistribution studies showed essentially pure renal elimination of the radiotracers. Relatively low receptor-mediated uptake was observed with the natural sequence (average uptake ratios of HEK293T:hB1R to HEK293T tumor (T/WT), blood (T/B) and muscle (T/M) at 1h p.i. of 4, 10.4, 8.2 for [68Ga]P03083), while excellent tumor visualization was achieved with the [68Ga]SH01078 analog (6.8, 20.6, 11.2). Pretreatment with NEP inhibitor phosphoramidon significantly improved tumor uptake of [68Ga]P03083 (contrast ratios of 10.4, 38, 36.4), while ACE inhibitor enalaprilat was ineffective. Conclusions The metabolic stability of hB1R targeting peptides is critical for their ability to visualize hB1R overexpressing tissues. Peptidase inhibition with phosphoramidon but not enalaprilat was effective in improving tumor uptake. Substituting unnatural amino acids at key peptidase cleavage sites was also effective to improve tumor visualization.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".