A preclinical PET dual-tracer imaging protocol for ER and HER2 phenotyping in breast cancer xenografts
Notice bibliographique
Résumé
Abstract Background Nuclear medicine is on the constant search of precision radiopharmaceutical approaches to improve patient management. Although discordant expression of the estrogen receptor (ER) and the human epidermal growth factor receptor 2 (HER2) in breast cancer is a known dilemma for appropriate patient management, traditional tumor sampling is often difficult or impractical. While 2-deoxy-2[18F]fluoro-D-glucose (18F-FDG)-positron emission tomography (PET) is an option to detect subclinical metastases, it does not provide phenotype information. Radiolabeled antibodies are able to specifically target expressed cell surface receptors. However, their long circulating half-lives (days) require labeling with long-lived isotopes, such as89Zr, in order to allow sufficient time for tracer clearance from the blood compartment and to accumulate adequately in target tumors and, thus, generate high-quality PET images. The aim of this study was to develop a dual-tracer PET imaging approach consisting of a fast-clearing small molecule and a slow-clearing antibody. This approach was evaluated in a model consisting of mice harboring separate breast cancer xenografts with either an ER+/HER2− or ER−/HER2+ phenotype, comparable to human metastatic disease with intertumor heterogeneity. Lastly, the aim of our study was to determine the feasibility of specifically identifying these two important phenotypes in an acceptable time window. Methods Female nude mice were subcutaneously implanted on opposite shoulders with the ER+/HER2− and ER−/HER2+ MCF-7 and JIMT-1 tumor cell lines, respectively. A second model was developed consisting of mice implanted orthotopically with either MCF-7 or JIMT-1 cells. Pharmacokinetic analysis, serial PET imaging, and biodistribution were first performed for [89Zr]Zr-DFO-trastuzumab (89Zr-T) up to 8 days post-injection (p.i.) in JIMT-1 bearing mice. Region-of-interest (ROI) and biodistribution-derived uptake (% injected-activity/gram of tissue [%IA/g]) values and tumor-to-background ratios were obtained. Results were compared in order to validate ROI and identify early time points that provided high contrast tumor images. For the dual-tracer approach, cohorts of tumor-bearing mice were then subjected to sequential tracer PET imaging. On day 1, mice were administered 4-fluoro-11β-methoxy-16α-[18F]-fluoroestradiol (4FMFES) which targets ER and imaged 45 min p.i. This was immediately followed by the injection of89Zr-T. Mice were then imaged on day 3 or day 7. ROI analysis was performed, and uptake was calculated in tumors and selected healthy organs for all radiotracers. Quality of tumor targeting for all tracers was evaluated by tumor contrast visualization, tumor and normal tissue uptake, and tumor-to-background ratios. Results 89Zr-T provided sufficiently high tumor and low background uptake values that furnished high contrast tumor images by 48 h p.i. For the dual-tracer approach, 4FMFES provided tumor uptake values that were significantly increased in MCF-7 tumors. When89Zr-T-PET was combined with18F-4FMFES-PET, the entire dual-tracer sequential-imaging procedure provided specific high-quality contrast images of ER+/HER2− MCF-7 and ER−/HER2+ JIMT-1 tumors for 4FMFES and89Zr-T, respectively, as short as 72 h from start to finish. Conclusions This protocol can provide high contrast images of tumors expressing ER or HER2 within 3 days from injection of 4FMFES to final scan of89Zr-T and, hence, provides a basis for future dual-tracer combinations that include antibodies.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
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 source (Gemma direct ou Codex distillé), 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 ».