A Novel Transgenic Mouse Model of Multiple Myeloma Reliably Predicts Drug Response.
Notice bibliographique
Résumé
Abstract The search for novel and clinically effective anti-myeloma therapies has been hampered by a paucity of good pre-clinical animal models. Most established animal models of multiple myeloma (MM) fail in one or more crucial features to resemble human MM, frequently exhibiting extramedullary tumors or lacking a competent immune system. In addition, competing models are either too expensive or time consuming to generate and maintain. Finally, no model has been shown to reliably predict both drug response and drug inactivity. We have previously described a C57Bl6/J transgenic mouse model in which the expression of the human c-myc oncogene is activated in post-germinal B cells by somatic hypermutation. These mice (Vk*myc) spontaneously develop monoclonal gammopathies and plasma cell expansion beginning at 20 weeks of age. However, in contrast to other models, their plasma cells cannot be found in secondary lymphoid tissues. Now, we report that this model closely reproduces the clinical behavior of human MM. Serum protein electrophoresis (SPEP) as well as ELISA for serum IgG demonstrate that the incidence and quantity of monoclonal paraproteinemia are greatly elevated in the Vk*myc mice as compared to age matched wild type C57Bl6/J controls (50 weeks mean IgG 1.92g/dL Vk*myc vs 0.2g/dL controls; peak IgG levels up to 7.5g/dL). As these mice age, their paraproteins continue rising and remain far higher than that of controls at every time point. Mice with significant paraproteinemia demonstrate marrow with up to 50% plasma cells with evidence of a low proliferative index, similar to what is observed in human MM and unlike what is seen in other models of MM. Anemia is observed, with a mean hemoglobin of 8.9g/dL in the Vk*myc mice vs 13.4g/dL in the wild type. Vk*myc mice analyzed show marked bone thinning with a 20% reduction in total bone volume and in the number of trabeculae per unit area as shown by microCT. In addition a 15% reduction in bone mineral density was demonstrated in affected mice. We next demonstrated the efficacy of 3 drugs, used commonly in clinical practice to treat myeloma (melphalan, dexamethasone and bortezomib). These were given as single courses of daily IP injections for 5 days, for the first two drugs, and bi-weekly IP for 4 weeks for the third. As early as two weeks post treatment, a statistically significant reduction in serum paraprotein levels was observed in the treated mice versus vehicle treated controls. The reductions were maximal at 21d post treatment in the melphalan (−77.2%±39 p<0.02) and dexamethasone (−67.4%±29 p<0.02) groups and at 28d in the bortezomib group (−68.9%±9 p<.001). No reduction was seen in the vehicle treated controls at any time point. As with human myeloma, the effect of one course of treatment was transient in nature. In contrast, treatment of VK*myc mice with 3 drugs that have not shown clinical activity against myeloma as single agents (hydroxyurea, vincristine and fludarabine) did not reduce serum monoclonal proteins. We conclude that our Vk*myc model closely reproduces the clinical characteristics of human MM. We have also shown that this model responds to drugs known to be clinically active, while showing no response to drugs that have little or no effect against human MM. To our knowledge, this is the first time that this level of fidelity to human MM has been demonstrated in a pre-clinical animal model. Our model therefore represents a unique and powerful tool for pre-clinical anti-myeloma drug development.
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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 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».