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Record W3024732984 · doi:10.2967/jnumed.120.243113

Radiolabeled cCPE Peptides for SPECT Imaging of Claudin-4 Overexpression in Pancreatic Cancer

2020· article· en· W3024732984 on OpenAlexfundno aff
Júlia Baguña Torres, Michael Mosley, Sofia Koustoulidou, Samantha L. Hopkins, Stefan Knapp, A. Chaikuad, Masuo Kondoh, Keisuke Tachibana, Veerle Kersemans, Bart Cornelissen

Bibliographic record

VenueJournal of Nuclear Medicine · 2020
Typearticle
Languageen
FieldNeuroscience
TopicBarrier Structure and Function Studies
Canadian institutionsnot available
FundersInnovative Medicines InitiativeCancer Research UKGenome CanadaMedical Research CouncilEuropean Federation of Pharmaceutical Industries and AssociationsMerck KGaAJohns Hopkins University
KeywordsClaudinHT1080In vivoMolecular biologyTransfectionPancreatic cancerLigand (biochemistry)ChemistryCancer researchBiologyIn vitroCancerBiochemistryTight junctionReceptorGene

Abstract

fetched live from OpenAlex

Overexpression of tight-junction protein claudin-4 has been detected in primary and metastatic pancreatic cancer tissue and is associated with better prognosis in patients. Noninvasive measurement of claudin-4 expression by imaging methods could provide a means for accelerating detection and stratifying patients into risk groups. Clostridium perfringens enterotoxin (CPE) is a natural ligand for claudin-4 and holds potential as a targeting vector for molecular imaging of claudin-4 overexpression. A glutathione S-transferases (GST)–tagged version of the C terminus of CPE (cCPE) was previously used to delineate claudin-4 overexpression by SPECT but showed modest binding affinity and slow blood clearance in vivo. Methods: On the basis of the crystal structure of cCPE, a series of smaller cCPE194–319 mutants with putatively improved binding affinity for claudin-4 was generated by site-directed mutagenesis. All peptides were conjugated site-specifically on a C-terminal cysteine using maleimide-diethylenetriamine pentaacetate to enable radiolabeling with 111In. The binding affinity of all radioconjugates was evaluated in claudin-4–expressing PSN-1 cells and HT1080-negative controls. The specificity of all cCPE mutants to claudin-4 was assessed in HT1080 cells stably transfected with claudin-4. SPECT/CT imaging of BALB/c nude mice bearing PSN-1 or HT1080 tumor xenografts was performed to determine the claudin-4–targeting ability of these peptides in vivo. Results: Uptake of all cCPE-based radioconjugates was significantly higher in PSN-1 cells than in HT1080-negative controls. All peptides showed a marked improvement in affinity for claudin-4 in vitro when compared with previously reported values (dissociation constant: 2.2 ± 0.8, 3 ± 0.1, 4.2 ± 0.5, 10 ± 0.9, and 9.7 ± 0.7 nM). Blood clearance of [111In]In-cCPE194–319, as measured by SPECT, was considerably faster than that of [111In]In-cCPE.GST (half-life, <1 min). All radiopeptides showed significantly higher accumulation in PSN-1 xenografts than in HT1080 tumors at 90 min after injection of the tracer ([111In]In-cCPE194–319, 2.7 ± 0.8 vs. 0.4 ± 0.1 percentage injected dose per gram [%ID/g], P < 0.001; [111In]In-S313A, 2.3 ± 0.9 vs. 0.5 ± 0.1 %ID/g, P < 0.01; [111In]In-S307A + N309A + S313A, 2 ± 0.4 vs. 0.3 ± 0.1 %ID/g, P < 0.01; [111In]In-D284A, 2 ± 0.2 vs. 0.7 ± 0.1 %ID/g, P < 0.05; [111In]In-L254F + K257D, 6.3 ± 0.9 vs. 0.7 ± 0.2 %ID/g, P < 0.001). Conclusion: These optimized cCPE-based SPECT imaging agents show great promise as claudin-4–targeting vectors for in vivo imaging of claudin-4 overexpression in pancreatic 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.045
GPT teacher head0.304
Teacher spread0.259 · 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

Citations27
Published2020
Admission routes1
Has abstractyes

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