Synthesis and Preclinical Evaluation of Three Novel 68Ga-Labeled Bispecific PSMA/FAP-Targeting Tracers for Prostate Cancer Imaging
Bibliographic record
Abstract
Tumor heterogeneity limits the efficacy and reliability of monospecific radiopharmaceuticals in prostate cancer diagnosis and therapy. To overcome this limitation and improve lesion detection sensitivity, we developed and evaluated three bispecific radiotracers that can target both prostate-specific membrane antigen (PSMA) and fibroblast activation protein (FAP), which are the two key proteins overexpressed in prostate cancer. Three FAP-targeting ligands with various linker lengths were synthesized through multistep organic synthesis, and then connected to the PSMA-targeting motif. IC50(PSMA) and IC50(FAP) values of Ga-complexed bispecific ligands, Ga-AV01017, Ga-AV01030, and Ga-AV01038 were 25.2–71.6 and 1.25–2.74 nM, respectively. The uptake values in PSMA-expressing LNCaP tumor xenografts were 4.38 ± 0.55, 5.17 ± 0.51, and 4.25 ± 0.86 %ID/g for [68Ga]Ga-AV01017, [68Ga]Ga-AV01030, and [68Ga]Ga-AV01038, respectively, which were lower than the monospecific PSMA-targeting tracer [68Ga]Ga-HTK03041 (23.1 ± 6.11 %ID/g). The uptake values in FAP-expressing HEK293T:hFAP tumor xenografts were 2.99 ± 0.37, 3.69 ± 0.81, 3.64 ± 0.83 %ID/g for [68Ga]Ga-AV01017, [68Ga]Ga-AV01030, and [68Ga]Ga-AV01038, respectively, which were also lower than the monospecific FAP-targeting tracer, [68Ga]Ga-FAPI-04 (12.5 ± 2.00 %ID/g). We observed that the bispecific tracers had prolonged blood retention, in which tracers with a longer linker tend to have a higher blood uptake and lower tumor uptake. Further investigations are needed to optimize the linker selection to generate promising bispecific PSMA/FAP-targeting tracers for prostate cancer imaging.
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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 | 0.001 | 0.001 |
| 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) | 0.000 | 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".