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Record W2589210140 · doi:10.7150/thno.17117

Preclinical Melanoma Imaging with <sup>68</sup>Ga-Labeled α-Melanocyte-Stimulating Hormone Derivatives Using PET

2017· article· en· W2589210140 on OpenAlexafffund
Chengcheng Zhang, Zhengxing Zhang, Kuo‐Shyan Lin, Jinhe Pan, Iulia Dude, Navjit Hundal-Jabal, Nadine Colpo, François Bénard

Bibliographic record

VenueTheranostics · 2017
Typearticle
Languageen
FieldMedicine
TopicMonoclonal and Polyclonal Antibodies Research
Canadian institutionsUniversity of British ColumbiaBC Cancer Agency
FundersCanadian Institutes of Health ResearchBC Cancer FoundationLeading Edge Endowment Fund
KeywordsMelanocortin 1 receptorMelanomaPositron emission tomographyMelanocyte-stimulating hormoneIn vivoChemistryDOTAMolecular imagingNuclear medicineMelanocyteReceptorCancer researchMedicineBiologyBiochemistry

Abstract

fetched live from OpenAlex

It is estimated that melanoma accounted for 76,380 new cases and 10,130 deaths in the United States in 2016.The melanocortin 1 receptor (MC1R) is highly expressed in the vast majority of melanomas, which makes it an attractive target for molecular imaging and radionuclide therapy.Lactam bridge-cyclized α-melanocyte-stimulating hormone (Ac-Nle 4 -cyclo[Asp 5 -His-D-Phe 7 -Arg-Trp-Lys 10 ]-NH2, or Nle-CycMSHhex) analogues have been successfully developed and studied for MC1R-targeted imaging, predominantly with single-photon emission computed tomography (SPECT).The goal of this study was to design and evaluate novel peptides for melanoma imaging with positron emission tomography (PET).We designed and synthesized three peptides, DOTA-PEG2-Nle-CycMSHhex (CCZ01047), DOTA-4-amino-(1-carboxymethyl) piperidine (Pip)-Nle-CycMSHhex (CCZ01048), and DOTA-Pip-Pip-Nle-CycMSHhex (CCZ01056).All three peptides exhibited high binding affinity to MC1R with sub-nanomolar Ki values, rapid internalization into B16F10 melanoma cells and high in vivo stability with more than 93% remaining intact at 15 min post-injection (p.i.) in blood plasma.All three 68 Ga-labeled tracers produced high contrast PET images in C57BL/6J mice bearing B16F10 tumors, and their respective tumor uptakes were 8.0 ± 3.0, 12.3 ± 3.3, and 6.5 ± 1.4 %ID/g at 1 h p.i. Minimal normal organ activity was observed at 1 h p.i., except for kidneys (5.1 ± 1.4, 4.7 ± 0.5, and 6.2 ± 2.0 %ID/g, respectively), and thyroid (4.1 ± 0.6 %ID/g for CCZ01047 and 2.4 ± 0.6 %ID/g for CCZ01048).Due to high accumulation at tumor sites and rapid background clearance of 68 Ga-CCZ01048, we further evaluated it at 2 h p.i., and a tumor uptake of 21.9 ± 4.6 %ID/g was observed, with background activity further decreased.Exceptional image contrast was also achieved, i.e. tumor-to-blood, tumor-to-muscle, tumor-to-bone and tumor-to-kidney ratios were 96.4 ± 13.9, 210.9 ± 20.9, 39.6 ± 11.9 and 4.0 ± 0.9, respectively.A blocking study was also performed by co-injection of excess amount of non-radioactive Ga-coupled of CCZ01048, which confirmed that the tumor uptake was MC1R mediated.In conclusion, the introduction of a cationic Pip linker to Nle-CycMSHhex, CCZ01048, not only improved tumor uptake, but also generated high tumor-to-normal tissue contrast with PET imaging in a preclinical melanoma model.Therefore, CCZ01048 is a promising candidate for PET imaging of melanoma, and potentially as a theranostic agent for radionuclide therapy of melanoma when labeled with α or β emitters.

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.073
GPT teacher head0.379
Teacher spread0.306 · 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

Citations54
Published2017
Admission routes2
Has abstractyes

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