MétaCan
Menu
Back to cohort

<sup>64</sup>Cu-Labeled Trastuzumab Fab-PEG<sub>24</sub>-EGF Radioimmunoconjugates Bispecific for HER2 and EGFR: Pharmacokinetics, Biodistribution, and Tumor Imaging by PET in Comparison to Monospecific Agents

2017· article· en· W2563445076 on OpenAlexafffund
Luke Yongkyu Kwon, Deborah A. Scollard, Raymond M. Reilly

Bibliographic record

VenueMolecular Pharmaceutics · 2017
Typearticle
Languageen
FieldMedicine
TopicHER2/EGFR in Cancer Research
Canadian institutionsUniversity Health NetworkUniversity of Toronto
FundersCanadian Institutes of Health ResearchInstitute of Cancer ResearchOntario Institute for Cancer ResearchUniversity of Toronto
KeywordsBiodistributionTrastuzumabChemistryPharmacokineticsCancer researchIn vitroPharmacologyCancerMedicineBreast cancerBiochemistryInternal medicine

Abstract

fetched live from OpenAlex

Heterodimerization of EGFR with HER2 coexpressed in breast cancer (BC) promotes tumor growth, and increased EGFR expression is associated with trastuzumab resistance. Our aim was to construct 64 Cu-labeled bispecific radioimmunoconjugates (bsRIC) composed of trastuzumab Fab, which binds HER2 linked through a polyethylene glycol (PEG 24 ) spacer to EGF, and to compare their pharmacokinetic, biodistribution, and tumor imaging characteristics by positron-emission tomography (PET). bsRICs were generated by linking maleimide modified trastuzumab Fab with thiolated EGF through a thioether bond. HER2 and EGFR binding were assessed in vitro in MDA-MB-231 (EGFR mod /HER2 low ), MDA-MB-468 (EGFR high /HER2 neg ), MDA-MB-231-H2N (EGFR mod /HER2 mod ), and SKOV3 (EGFR low /HER2 high ) cells by competition and saturation cell binding assays to estimate the dissociation constant ( K d ). The elimination of the 64 Cu-NOTA-trastuzumab Fab-PEG 24 -EGF bsRICs from the blood of Balb/c mice was compared to monospecific 64 Cu-NOTA-trastuzumab Fab and 64 Cu-NOTA-EGF. MicroPET/CT imaging was performed in NOD/SCID mice bearing subcutaneous MDA-MB-468, MDA-MB-231/H2N, or SKOV3 human BC xenografts at 24 and 48 h postinjection (p.i.) of bsRICs. Tumor and normal tissue uptake were quantified by biodistribution studies and compared to monospecific agents. The binding of bsRICs to MDA-MB-231 cells was decreased to 24.5 ± 5.2% by excess EGF, while the binding of bsRICs to SKOV3 cells was decreased to 38.6 ± 5.4% by excess trastuzumab Fab, demonstrating specific binding to both EGFR and HER2. 64 Cu-labeled bsRICs incorporating the PEG 24 spacer were eliminated more slowly from the blood than 64 Cu-bsRICs without the PEG spacer and were cleared much more slowly than 64 Cu-NOTA-Fab or 64 Cu-NOTA-EGF. All three tumor xenografts were visualized by microPET/CT at 24 and 48 h p.i. of bsRICs. Biodistribution studies at 48 h p.i. in NOD/SCID mice with MDA-MB-231/H2N tumors demonstrated significantly greater tumor uptake of 64 Cu-NOTA-Fab-PEG 24 -EGF (4.9 ± 0.4%ID/g) than 64 Cu-NOTA-Fab (1.9 ± 0.3%ID/g; P < 0.0001) and 64 Cu-NOTA-EGF (0.7 ± 0.2%ID/g; P < 0.0001). Furthermore, preadministration of an excess of trastuzumab Fab or trastuzumab Fab-PEG 24 -EGF significantly decreased the tumor uptake of 64 Cu-NOTA-Fab-PEG 24 -EGF in SK-OV-3 and MDA-MB-468 xenografts by 4.4-fold ( P = 0.0012) and 1.8-fold ( P = 0.0031), respectively. 64 Cu-labeled bsRICs bound HER2 or EGFR and were taken up specifically in vivo in tumor xenografts expressing one or both receptors. The PEG 24 linker prolonged the blood residence time contributing to the higher tumor uptake of the bsRICs than monospecific agents.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.122
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.050
GPT teacher head0.386
Teacher spread0.336 · 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 teacher head, not a consensus.

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

Citations31
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueMolecular PharmaceuticsSame topicHER2/EGFR in Cancer ResearchFrench-language works237,207