Preclinical validations of [18F]FPyPEGCBT-c(RGDfK): a 18F-labelled RGD peptide prepared by ligation of 2-cyanobenzothiazole and 1,2-aminothiol to image angiogenesis
Bibliographic record
Abstract
α V β 3 , α V β 5 and α 5 β 1 integrins are known to be involved in carcinogenesis and are overexpressed in many types of tumours compared to healthy tissues; thereby they have been selected as promising therapeutic targets. Positron emission tomography (PET) is providing a unique non-invasive screening assay to discriminate which patient is more prone to benefit from antiangiogenic therapies, and extensive research has been carried out to develop a clinical radiopharmaceutical that binds specifically to integrin receptors. We recently reported the synthesis of a new 18 F-labelled RGD peptide prepared by 2-cyanobenzothiazole (CBT)/1,2-aminothiol conjugation. This study aims at characterising the preclinical biologic properties of this new tumour-targeting ligand, named [ 18 F]FPyPEGCBT- c (RGDfK). The in vitro binding properties of [ 18 F]FPyPEGCBT- c (RGDfK) were analysed by standard binding assay in U-87 MG and SKOV-3 cancer models and its selectivity towards integrins by siRNA depletions. Its preclinical potential was studied in mice bearing subcutaneous tumours by ex vivo biodistribution studies and in vivo microPET/CT imaging. In vitro, FPyPEGCBT- c (RGDfK) efficiently bound RGD-recognising integrins as compared to a control c (RGDfV) peptide (IC 50 = 30.8 × 10 −7 M vs. 6.0 × 10 −7 M). [ 18 F]FPyPEGCBT- c (RGDfK) cell uptake was mediated by an active transport through binding to α V , β 3 and β 5 but not to β 1 subunits. In vivo, this new tracer demonstrated specific tumour uptake with %ID/g of 2.9 and 2.4 in U-87 MG and SKOV-3 tumours 1 h post injection. Tumour-to-muscle ratios of 4 were obtained 1 h after intravenous administration of the tracer allowing good visualisation of the tumours. However, unfavourable background accumulation and high hepatobiliary excretion were observed. [ 18 F]FPyPEGCBT- c (RGDfK) specifically detects tumours expressing RGD-recognising integrin receptors in preclinical studies. Further optimisation of this radioligand may yield candidates with improved imaging properties and would warrant the further use of this efficient labelling technique for alternative targeting vectors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".