Theranostic Potential of a New 64Cu-Labeled NOTA-R954 Peptide Conjugate for Kinin B1R Expressing Prostate Cancer
Bibliographic record
Abstract
Background/Objectives: This study explores the potential of the inducible G protein-coupled kinin B1 receptor (B1R) as a target for the diagnosis and treatment of prostate cancer (PCa) and aims to develop the first theranostic agent targeting hB1R for both molecular imaging and radionuclide therapy. Methods: B1R expression was analyzed via qPCR and immunohistochemistry in human PCa cells and tissues specimens. A novel 64Cu/NOTA-conjugated peptide analog of the potent B1R antagonist R954 was synthetized and evaluated in vitro and in vivo. Results: B1R was confirmed to be expressed (RNA, protein) by varying degrees in all PCa cell lines and tissues investigated, with protein level significantly correlating with tumor grades. This finding was supported by similar analyses from the TCGA and MSKCC databases. In vitro, the 64Cu/NOTA-βAla-R954 conjugate showed nanomolar affinity/potency at hB1R, complete plasma stability over 24 h, significant cellular uptake (up to 33% of ID at 24 h), and dose-dependent anti-clonal growth effects. In vivo, the radioconjugate remained stable in circulation for up to 90 min and was primarily excreted intact via the kidneys following IV administration. Intravenous 64Cu/NOTA-βAla-R954 (7.5 MBq) effectively detected subcutaneous PCa xenografts via µPET imaging in male athymic nude mice. At a single higher dose (65 MBq; 50 µg/kg), it significantly reduced tumor growth without observable toxicity. This antitumor effect was associated with increased apoptosis (active caspase-3) and reduced proliferation (Ki67), as shown by immunohistochemistry. In contrast, the nonradioactive NatCu/NOTA-βAla-R954 had no therapeutic effect at the same dose. Conclusions: Our findings provide proof-of-concept for the potential theranostic use of 64Cu/NOTA-R954 in PCa, and potentially other types of B1R-positive solid cancers.
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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) | 0.001 | 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".