Immuno-PET Imaging of EGFR with <sup>64</sup>Cu-NOTA Panitumumab in Subcutaneous and Metastatic Nonsmall Cell Lung Cancer Xenografts
Notice bibliographique
Résumé
High Resolution Image Download MS PowerPoint Slide Objective: About 65–90% of nonsmall cell lung cancer (NSCLC) express the epithelial growth factor receptor (EGFR) as a transmembrane protein that is activated by binding of specific ligands, including epidermal growth factor and transforming growth factor α (TGFα). Identifying EGFR as an oncogene has led to the development of anticancer therapeutics directed against EGFR, including the full-length human IgG 2 monoclonal antibody panitumumab. The main goal of the present study was to investigate 64 Cu-labeled panitumumab with immuno-PET in subcutaneous and metastatic EGFR-positive NSCLC xenografts. Methods: Bifunctional chelating agent 2- S -(4-isothiocyanatobenzyl)-1,4,7-triazacyclo-nonane-1,4,7-triacetic acid (NOTA-NCS) was attached to panitumumab. The number of chelators per panitumumab was determined using matrix-assisted laser desorption/ionization (MALDI) mass spectroscopy. The incorporation efficiency of 64 Cu into NOTA-panitumumab was measured by using radio-TLC. EGFR-expressing epithelial-like H1299-luc+ NSCLC cells were used for in vitro and in vivo experiments. Cell uptake of [ 64 Cu]Cu-NOTA-panitumumab was measured in the presence and absence of panitumumab. Subcutaneous and metastatic H1299-luc tumor models were grown in male NSG mice. The presence of tumors at lung and metastatic sites was analyzed by [ 18 F]FLT PET. Immuno-PET with [ 64 Cu]Cu-NOTA-panitumumab was performed as static PET imaging at 2, 24, and 48 h postinjection in both tumor models. Proof-of-target was confirmed by blocking experiments with panitumumab. Detailed ex vivo biodistribution experiments were performed in both animal tumor models to confirm biodistribution profiles obtained by immuno-PET imaging. Results: MALDI analysis confirmed the attachment of ∼1.5 NOTA per antibody. Radiolabeling efficiency with [ 64 Cu]CuCl 2 was 93.8 ± 5.7% and a molar activity of 0.65 MBq/μg. Cellular uptake studies with [ 64 Cu]Cu-NOTA-panitumumab in H1299 cells demonstrated increasing uptake over time, reaching 29.1 ± 2.9% radioactivity(Bq)/mg protein ( n = 3) and plateauing at 45 min. Addition of 25 μg of panitumumab reduced radioligand uptake to 1.22 ± 0.06% radioactivity/mg protein ( n = 3). PET imaging revealed high uptake of [ 64 Cu]Cu-NOTA-panitumumab in subcutaneous tumors: Standardized uptake values (SUV) mean reached 4.70 ± 0.42 and 5.37 ± 0.40 ( n = 5) after 24 and 48 h postinjection, respectively. Administration of 1 mg panitumumab reduced tumor uptake significantly to 1.94 ± 0.22 and 1.66 ± 0.08 ( n = 4; p < 0.001). In the metastatic model, the following SUV mean were analyzed from liver and lung lesions: 5.55 ± 0.34 and 6.28 ± 0.46 (both n = 23 lesions from 6 mice) after 24 and 48 h postinjection, which was also significantly reduced to 2.53 ± 0.39 and 2.31 ± 0.15 (both n = 16 lesions from 4 mice; p < 0.001) after injection of 1 mg panitumumab. Detailed ex vivo biodistribution confirmed immuno-PET analysis in both models. Panitumumab reduced radioactivity uptake into subcutaneous tumors from 11.01 ± 0.72 ( n = 4) to 3.67 ± 0.33% ID/g ( n = 5; p < 0.001), and in metastatic liver lesions from 29.44 ± 8.14 ( n = 4) to 8.35 ± 1.30% ID/g ( n = 5; p < 0.001), respectively. Conclusions: [ 64 Cu]Cu-NOTA-panitumumab was successfully used for immuno-PET imaging of EGFR-expressing subcutaneous and metastatic NSCLC tumors. This result represents the basis for developing radiotheranostics for targeting EGFR in cancers and for selecting the right patients for the right treatment at the right time.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».