Synthesis and Evaluation of 99mTc-Labeled PSMA-Targeted Tracers Based on the Lys-Urea-Aad Pharmacophore for Detecting Prostate Cancer with Single Photon Emission Computed Tomography
Bibliographic record
Abstract
Prostate-specific membrane antigen (PSMA) is a well-validated prostate cancer marker but reported PSMA-targeted tracers derived from the Lys-urea-Glu pharmacophore including the clinically validated [99mTc]Tc-EDDA/HYNIC-iPSMA have high off-target uptake in kidneys, spleen, and salivary glands. In this study, we synthesized and evaluated three novel 99mTc-labeled PSMA-targeted tracers and investigated if the tracers derived from the Lys-urea-Aad pharmacophore could have minimized uptake in off-target organs/tissues. In vitro competition binding assays showed that compared with HYNIC-iPSMA, the three novel ligands had slightly weaker PSMA binding affinity (average Ki = 3.11 vs. 8.96–11.6 nM). Imaging and ex vivo biodistribution studies in LNCaP tumor-bearing mice showed that [99mTc]Tc-EDDA/HYNIC-iPSMA and the three novel tracers successfully visualized LNCaP tumor xenografts in SPECT images and were excreted mainly via the renal pathway. The average tumor uptake at 1 h post-injection varied from 5.40 to 18.8%ID/g, and the tracers derived from the Lys-urea-Aad pharmacophore had much lower uptake in the spleen and salivary glands. Compared with the clinical tracer [99mTc]Tc-EDDA/HYNIC-iPSMA, the Lys-urea-Aad-derived [99mTc]Tc-EDDA-KL01127 had lower background uptake and superior tumor-to-background contrast ratios and is therefore promising for clinical translation to detect prostate cancer lesions with SPECT.
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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 | 0.000 | 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 | 0.000 |
| 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".