Is Thiourea the Weak Link? An Investigation of the In Vitro and In Vivo Destabilization of [ <sup>203</sup> Pb]- and [ <sup>212</sup> Pb]Pb <sup>2+</sup> Thiourea-Based Bioconjugates
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Fibroblast activation protein (FAP) is overexpressed in a variety of cancers, making it an attractive target for bifunctional chelator-based radiopharmaceuticals. This study initially aimed to assess the effect of chelator structure on the biodistribution of 203 Pb/ 212 Pb-labeled FAP inhibitor (FAPI) bioconjugates. However, suboptimal in vivo biodistribution and imaging results suggested the bioconjugate was unstable. RadioHPLC analysis of urine samples suggest the thiourea bond, formed during conjugation between an amine on the biomolecule, and an isothiocyanate-functionalized chelator, is unstable in vivo, resulting in detachment of the radiometal-chelator complex from the targeting vector, resulting in poor tumor accumulation. To determine whether this instability was specific to the FAPI system, a peptide-based (Cyclic melanocyte stimulating hormone, CycMSH) bioconjugate targeting the melanocortin-1 receptor was synthesized using the same thiourea linkage. Identical metabolites were observed, supporting the hypothesis that thiourea bonds are unstable in vivo with this theranostic isotope pair. Subsequently, the effect of bioconjugation chemistry, specifically thiourea and amide bonds, on the stability and biodistribution of 203 Pb/ 212 Pb-labeled bioconjugates was assessed. Modifying the bioconjugation linker to be an amide bond, formed by utilizing a chelate containing an active ester instead of an isothiocyanate, led to significantly improved in vitro and in vivo stability, as demonstrated by radioHPLC and biodistribution and imaging studies in both models. These findings highlight the importance of the choice of bioconjugation chemistry in the development of lead-based radiopharmaceuticals and emphasize the importance of selecting stable linkages to ensure optimal radiometal retention and tumor targeting.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".