Preclinical <i>In Vivo</i> Imaging of Multiple Myeloma with [ 18f]Fluorohomoleucine (FHL) PET/CT
Notice bibliographique
Résumé
Purpose: Imaging of patients with multiple myeloma (MM) remains challenging due to its multi-focal nature affecting bone marrow, bone structures and soft tissue. As a result, current diagnostic methods like X-rays, CT and MRI scans only provide a partial understanding of disease activity and treatment response, lacking a comprehensive overview. Although 2-deoxy-2-[ 18F]fluoro-D-glucose (FDG) positron emission tomography (PET) has become the standard for detecting multifocal cancer spread, its use in MM patients is limited due to metabolic heterogeneity of MM and limited sensitivity in detecting extramedullary disease leading to false negative and false positive scans. To overcome these limitations, we developed a novel radiopharmaceutical L-[ 18F]Fluorohomoleucine (FHL) targeting LAT1 amino acid transporter. LAT1 has been significantly correlated with the proliferative activity of MM cells, poor prognosis and response to treatment in MM patients, presenting an appealing molecular target for assessing disease activity. Methods: FHL was synthesized as described by Nodwell et al. (J Nucl Med, 2019) and FDG was obtained from BC Cancer. LAT1 expression in multiple myeloma (MM) cell lines was confirmed by flow cytometry. Cell uptake assays were conducted using luciferase-transfected MM1S, L363, NCI H929 and AMO1 MM cells, and 2-amino-bicyclo[2.2.1]heptanes-2-carboxylic acid (BCH) was used as a blocking agent. For in vivo studies, male NRG mice were injected either with 1 x 10 6 MM cells intravenously (i.v.) via the caudal vein or subcutaneously (SQ) with 1 x 10 7 cells. Tumor engraftment was monitored weekly on an in vivo bioluminescence imager Perkin Elmer's IVIS Ilumina 5, starting at 2 weeks post-injection (p.i.). Biodistribution and PET/CT imaging studies were conducted at 4-6 weeks p.i. Results: All MM cells tested exhibited LAT1-specific FHL uptake in vitro with L363 and NCI H929 demonstrating the highest tracer uptake and average blocking efficacy over 83% and 93%, respectively. We were able to observe weekly progression of disease in the i.v. cohort using IVIS imaging. Biodistribution and PET imaging studies revealed FHL accumulation in the SQ xenografts, pancreas and excretion via the urinary tract. The SQ tumor uptake values were 4.53±0.82 %ID/g in AMO1 xenografts, 5.55±0.82 %ID/g in NCI H929, and 6.37±0.70 %ID/g in L363 tumors. In the i.v. cohort, the mouse intravenously injected with L363 cells demonstrated accumulation of radioactivity in the skull and vertebrae, as anticipated from the IVIS images. Furthermore, preliminary data suggests that FHL was able to detect a more extensive bone and lymphatic involvement than FDG in MM xenografts. Conclusion: We have demonstrated the ability of FHL for in vivo imaging of three human multiple myeloma tumors in SQ murine models, with the tumor uptake ranging from 4.53±0.82 %ID/g in AMO1 xenografts to 6.37±0.70 %ID/g in L363 tumors. Work is underway to establish the utility of this tracer in detecting disease dissemination in the orthotopic murine models of multiple myeloma, with promising preliminary results presented herein.
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 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 | 0,000 | 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 ».