Systemic Delivery of the Cancer Gene Therapy Biologic, SNS01, Has Significant Anti-Tumoral Activity in a Murine Model of Multiple Myeloma.
Notice bibliographique
Résumé
Abstract Abstract 2462 Poster Board II-439 The eukaryotic translation initiation factor 5A (eIF5A) is highly conserved and the only known protein to contain the amino acid hypusine. Hypusinated eIF5A and deoxyhypusine synthase, one of the enzymes mediating eIF5A post-translational hypusination, have been identified as markers of neoplastic growth and metastasis, respectively. However, recent studies have indicated that, in its unhypusinated form, eIF5A is pro-apoptotic and thus functionally distinct from hypusine-modified eIF5A. SNS01 is a cancer gene therapy biologic targeted to the treatment of multiple myeloma. SNS01 is comprised of three components: a DNA vector containing a B-cell-specific (B29) promoter driving expression of a pro-apoptotic mutant of eIF5A (eIF5AK50R) that cannot be hypusinated; an siRNA that targets the native hypusinated eIF5A that promotes growth of cancer cells; and a synthetic polymer called polyethylenimine (PEI). RT-qPCR experiments demonstrated that treatment of the human myeloma cell line, KAS-6/1, with SNS01 results in a 90 % reduction in the expression of eIF5A mRNA (mediated by the siRNA) as well as the accumulation of ∼ 22,000 copies of the plasmid-derived eIF5AK50R mRNA per ng of total RNA. SNS01 was found to induce apoptosis in both IL-6-dependent (KAS-6/1) and IL-6-independent (U266) myeloma cell lines and was found to be more effective at inducing apoptosis than PEI nanoparticles carrying either the eIF5A siRNA or the eIF5AK50R plasmid alone. Apoptosis assays were used to optimize the ratio of DNA:siRNA in the nanoparticles and a ratio of 2:1 was found to be optimal for the induction of apoptosis in myeloma cells. The anti-tumoral activity of SNS01 was assessed in SCID mice bearing subcutaneous human multiple myeloma (KAS-6/1) tumors using twice-weekly intra-venous injections and a dose range between 0.15 mg/kg and 1.5 mg/kg. Control mice treated with PEI nanoparticles containing a non-expressing plasmid and a non-targeting siRNA had an average tumor volume of 284 mm3 at the time of sacrifice, whereas mice treated with 1.5 mg/kg or 0.75 mg/kg SNS01 exhibited significant tumor regression and had average tumor volumes of 13 mm3 (95 % inhibition; *p = 0.026) and 24.5 mm3 (91 % inhibition; *p = 0.03), respectively. In addition, for mice treated with 1.5 mg/kg SNS01, there was no evidence of tumors under the skin. Lower doses of SNS01 also demonstrated anti-tumoral activity with mice treated with 0.38 mg/kg and 0.15 mg/kg exhibiting a 73 % and 61 % inhibition of tumor growth, respectively. TUNEL-labeling revealed evidence of apoptotic cells in the treated tumors indicating that tumor regression occurs through the induction of apoptosis. Twice weekly dosing of SNS01 was found to be critical for effective tumor control. In a separate study, twice weekly dosing of SNS01 at 1.5 mg/kg was found to inhibit tumor growth by 88 % (p = 0.01) while once weekly dosing did not significantly reduce tumor burden. Since SNS01 is intended as a therapy for multiple myeloma, a bone marrow neoplasm, the biodistribution of PEI nanoparticles containing a GFP plasmid with the B-cell-specific B29 promoter and a fluorescently (DY547)-labeled siRNA was assessed following i.v. administration in Balb/c mice. The fluorescent siRNA was observed in the liver, lung, spleen, and bone marrow, while GFP expression was primarily observed in the bone marrow. In summary, our preclinical data indicate that systemic administration of SNS01 is an effective anti-cancer therapy in an animal model of multiple myeloma. Additionally, since PEI nanoparticles are taken up by cells of the bone marrow following systemic delivery, SNS01 may be an effective treatment option for multiple myeloma patients and is currently being evaluated for use in clinical trials. Disclosures: Taylor: Senesco Technologies Inc.: Patents & Royalties, stock options. Lust:Senesco Technologies Inc.: Research Funding. Dondero:Senesco Technologies Inc.: Employment, Equity Ownership, Patents & Royalties. Galton:Senesco Technologies Inc.: Employment, Equity Ownership, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties. Donovan:Senesco Technologies Inc.: Research Funding. Thompson:Senesco Technologies Inc.: Consultancy, Equity Ownership, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties, Research Funding.
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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 | 0,000 |
| 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 | 0,000 |
| 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 ».