Identification of alternative protein targets of glutamate-ureido-lysine associated with PSMA tracer uptake in prostate cancer cells
Bibliographic record
Abstract
Prostate-specific membrane antigen (PSMA) is highly overexpressed in most prostate cancers and is clinically visualized using PSMA-specific probes incorporating glutamate-ureido-lysine (GUL). PSMA is effectively absent from certain high-mortality, treatment-resistant subsets of prostate cancers, such as neuroendocrine prostate cancer (NEPC); however, GUL-based PSMA tracers are still reported to have the potential to identify NEPC metastatic tumors. These probes may bind unknown proteins associated with PSMA-suppressed cancers. We have identified the up-regulation of PSMA-like aminopeptidase NAALADaseL and the metabotropic glutamate receptors (mGluRs) in PSMA-suppressed prostate cancers and find that their expression levels inversely correlate with PSMA expression and are associated with GUL-based radiotracer uptake. Furthermore, we identify that NAALADaseL and mGluR expression correlates with a unique cell cycle signature. This provides an opportunity for the future study of the biology of NEPC and potential therapeutic directions. Computationally predicting that GUL-based probes bind well to these targets, we designed and synthesized a fluorescent PSMA tracer to investigate these proteins in vitro, where it shows excellent affinity for PSMA, NAALADaseL, and specific mGluRs associated with poor prognosis.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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".