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Record W3082635082 · doi:10.2967/jnumed.120.250738

<sup>177</sup>Lu-Labeled Albumin-Binder–Conjugated PSMA-Targeting Agents with Extremely High Tumor Uptake and Enhanced Tumor-to-Kidney Absorbed Dose Ratio

2020· article· en· W3082635082 on OpenAlexafffund
Hsiou‐Ting Kuo, Kuo‐Shyan Lin, Zhengxing Zhang, Carlos Uribe, Helen Merkens, Chengcheng Zhang, François Bénard

Bibliographic record

VenueJournal of Nuclear Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicRadiopharmaceutical Chemistry and Applications
Canadian institutionsUniversity of British ColumbiaBC Cancer Agency
FundersCanadian Institutes of Health Research
KeywordsBiodistributionChemistryAlbuminLNCaPKidneyRadioimmunotherapyNuclear medicineRadiochemistryMedicineProstateBiochemistryIn vitroCancerImmunologyInternal medicine

Abstract

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The use of an albumin binder has been shown to improve tumor uptake of prostate-specific membrane antigen (PSMA)–targeting radiotherapeutic agents. The aim of this study was to develop improved radiotherapeutic agents that combine an optimized affinity-modifying group and optimized albumin binders to maximize the tumor-to-kidney absorbed dose ratio. Methods:68Ga-labeled DOTA-conjugated lysine-ureido-glutamate–based PSMA-targeting agents bearing various affinity-modifying groups or albumin binders were synthesized and evaluated by PET/CT imaging and biodistribution studies in LNCaP tumor–bearing mice. The optimized affinity-modifying group and albumin binders were combined, and the resulting derivatives were radiolabeled with 177Lu and evaluated by SPECT/CT imaging and biodistribution studies in LNCaP tumor–bearing mice. Radiation dosimetry was calculated using the OLINDA/EXM software. Results: Affinity-modifying group optimization revealed that 68Ga-HTK03041 bearing a tranexamic acid-9-anthrylalanine affinity-modifying group had the highest tumor uptake (23.1 ± 6.11 percentage injected dose [%ID]/g at 1 h after injection). Albumin binder optimization showed that 68Ga-HTK03055 and 68Ga-HTK03086 bearing the N-(4-(p-chlorophenyl)butanoyl)-Gly and N-(4-(p-methoxyphenyl)butanoyl)-Gly motifs, respectively, had relatively faster tumor accumulation (∼30 %ID/g at 3 h after injection) and lower average kidney uptake (<55 %ID/g at both 1 and 3 h after injection). Combining the tranexamic acid-9-anthrylalanine affinity-modifying group with N-(4-(p-chlorophenyl)butanoyl)-Gly and N-(4-(p-methoxyphenyl)butanoyl)-Gly albumin-binding motifs generated HTK03121 and HTK03123, respectively. 177Lu-HTK03121 and 177Lu-HTK03123 had extremely high peak uptake (104 ± 20.3 and 70.8 ± 23.7 %ID/g, respectively) in LNCaP tumor xenografts, and this peak was sustained up to 120 h after injection. Dosimetry calculation showed that compared with 177Lu-PSMA-617, 177Lu-HTK03121 and 177Lu-HTK03123 delivered 18.7- and 12.7-fold higher absorbed dose to tumor but only 6.4- and 6.3-fold higher absorbed dose to kidneys, leading to 2.9- and 2.0-fold improvement in the tumor-to-kidney absorbed dose ratios. Conclusion: With greatly enhanced tumor uptake and tumor-to-kidney absorbed dose ratio, 177Lu-HTK03121 and 177Lu-HTK03123 have the potential to improve treatment efficacy using significantly lower quantities of 177Lu and are promising candidates for clinical translation to treat metastatic castration-resistant prostate cancer.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.031
GPT teacher head0.288
Teacher spread0.257 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations90
Published2020
Admission routes2
Has abstractyes

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