Preclinical Theranostic Profiling of [64Cu]Cu-Acetate in Prostate Cancer
Bibliographic record
Abstract
Copper plays a critical role in cancer biology, with tumor cells exhibiting abnormal copper metabolism that drives proliferation and tumor growth. A limited number of preclinical and clinical studies have reported promising theranostic potential of copper-based radionuclides, such as 64Cu, for both diagnostic imaging and targeted radiotherapy in diverse cancers, including prostate cancer (PCa). In this work, we evaluated the cellular uptake and antitumor efficacy of [64Cu]Cu-acetate using both cellular and animal models of PCa. Uptake assays revealed that ~70% of the administered dose (10 kBq) was internalized by PC-3 cells within 24 h, predominantly localizing to the cytoplasm, with around 9% detected in the nucleus. These results were corroborated by comparable natural Cu-acetate uptake levels (at equimolar dose) in PC-3 cells, as quantified by ICP-MS. Clonogenic assays revealed a dose-dependent reduction in survival following treatment with [64Cu]Cu-acetate (3 and 6 MBq), whereas its non-radioactive counterpart [NatCu]Cu-acetate, even at excess concentrations (10 µM), had no significant effect. Ex vivo biodistribution studies showed selective tumor accumulation/retention alongside expected hepatic uptake. Clear tumor visualization was achieved using μPET imaging with [64Cu]Cu-acetate (10 MBq iv). A single higher dose (65 MBq iv) effectively reduced tumor growth in a subcutaneous PC-3 xenograft mouse model, without systemic toxicity, as evidenced by stable body weight. Together, these results further support the theranostic potential of [64Cu]Cu in PCa.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".