Human ABC and SLC Transporters: The Culprit Responsible for Unspecific PSMA-617 Uptake?
Bibliographic record
Abstract
[177Lu]Lu-PSMA-617 has recently been successfully approved by the FDA, the MHRA, Health Canada and the EMA as Pluvicto®. However, salivary gland (SG) and kidney toxicities account for its main dose-limiting side-effects, while its corresponding uptake and retention mechanisms still remain elusive. Recently, the presence of different ATP-binding cassette (ABC) transporters, such as human breast cancer resistance proteins (BCRP), multidrug resistance proteins (MDR1), multidrug-resistance-related proteins (MRP1, MRP4) and solute cassette (SLC) transporters, such as multidrug and toxin extrusion proteins (MATE1, MATE2-K), organic anion transporters (OAT1, OAT2v1, OAT3, OAT4) and peptide transporters (PEPT2), has been verified at different abundances in human SGs and kidneys. Therefore, our aim was to assess whether [177Lu]Lu-PSMA-617 and [225Ac]Ac-PSMA-617 are substrates of these ABC and SLC transporters. For in vitro studies, the novel isotopologue ([α,β-3H]Nal)Lu-PSMA-617 was used in cell lines or vesicles expressing the aforementioned human ABC and SLC transporters for inhibition and uptake studies, respectively. The corresponding probe substrates and reference inhibitors were used as controls. Our results indicate that [177Lu]Lu-PSMA-617 and [225Ac]Ac-PSMA-617 are neither inhibitors nor substrates of the examined transporters. Therefore, our results show that human ABC and SLC transporters play no central role in the uptake and retention of [177Lu]Lu-PSMA-617 and [225Ac]Ac-PSMA-617 in the SGs and kidneys nor in the observed toxicities.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".