MétaCan
Menu
Retour à la cohorte
Enregistrement W2565056379 · doi:10.1182/blood.v124.21.2121.2121

Pharmacokinetic (PK) and Pharmacodynamic (PD) Results of a Novel, First-in-Class Modulator of Eukaryotic Translation Initiation Factor 5A (eIF5A) in Patients (pts) with Relapsed or Refractory B-Cell Malignancies: Data from a Phase 1-2 Study

2014· article· en· W2565056379 sur OpenAlexaff
Alice Bexon, Michael Craig, David S. Siegel, William Bensinger, Nicolás Novitzky, Andrew McDonald, Martin Gutierrez, Edward N. Libby, Frits van Rhee, Jeremy D. Heidel, John E. Thompson, Charles Barranco, Catherine A. Taylor, Kathleen A. Donovan, Laurie L. Moon‐Tasson, Leslie J. Browne, Michael R. Kurman, John A. Lust, Richard Dondero

Notice bibliographique

RevueBlood · 2014
Typearticle
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiquePolyamine Metabolism and Applications
Établissements canadiensUniversity of Waterloo
Organismes subventionnairesnon disponible
Mots-clésMedicineCancer researchApoptosisIn vivoMolecular biologyPharmacologyBiologyImmunology

Résumé

récupéré en direct d'OpenAlex

Abstract Introduction eIF5A is the only known protein to be modified by hypusination and is highly conserved across species. Hypusinated eIF5A, the predominant form in normal and cancer cells, is involved in cell survival and inflammatory pathway activation. siRNAs targeting eIF5A inhibit NF-kB activation and reduce pro-inflammatory cytokine production. Accumulation of the unhypusinated lysine form of eIF5A is associated with apoptosis. Mutants of eIF5A that cannot be hypusinated (e.g. eIF5AK50R) are pro-apoptotic in vitro and have anti-tumoral activity in vivo in multiple cancer types including melanoma and lung cancer. SNS01-T is a novel therapeutic with a dual mechanism of eIF5A modulation: inducing cell death via siRNA-mediated inhibition of hypusinated eIF5A while simultaneously causing over-expression of pro-apoptotic eIF5AK50R via a DNA plasmid with a B-cell promoter to induce tumor cell death. SNS01-T significantly inhibited tumor growth and increased survival in mouse models of myeloma (MM), mantle cell and diffuse large B-cell lymphoma. The phase 1-2 study of SNS01-T has completed 4 planned dosing cohorts 0.0125, 0.05, 0.2 and 0.375 mg/kg twice weekly IV for 6 weeks in pts with refractory B-cell cancers. Methods PK and PD secondary endpoints included characterization of PK by measuring pExp5A plasmid DNA and eIF5A siRNA in blood and bone marrow (BM), assessing potential immunogenicity of SNS01-T by measuring serum concentrations of antibodies against SNS01-T nanoparticles, and measuring serum concentrations of select proinflammatory cytokines by enzyme-linked immunosorbent assay in serum and plasma samples. Blood PK timepoints were 30 minutes before the first infusion and at 30 minutes, 2, 6, and 24 hours after the first infusions on Week 1, Week 3, and Week 6 and at the 4, 8, and 12 week visits after the last infusion; BM samples were collected 1 day after the final infusion. Serum and plasma PD sampling timepoints were 30 minutes before and at 2, 6, and 24 hours after the first infusion on Week 1, Week 3, and Week 6, and at 4 weeks after the final infusion. Cytokines assayed included TNF-α, IFN-α, IFN-ß, IFN-g, CXCL1, IL-1ß, IL-2, IL-4, IL-5, IL-6, IL-10, and IL-12. Results Table 1 shows data available for interpretation as of August 2014. The remaining samples are under analysis and will be presented. Abstract 2121. Table 1:Data available for interpretation (number of patients)SNS01-T DoseOverall(n=18)0.0125 mg/kg(n=6)0.05 mg/kg(n=4)0.2 mg/kg(n=4)0.375 mg/kg(n=4)Blood PK DNA and RNA156441Bone marrow PK82321Serum antibodies to SNS01-T nanoparticles186444Serum and plasma cytokines156441 Plasmid and siRNA blood levels generally peaked 30 minutes post-dosing at weeks 1, 3 and 6 of dosing. Both plasmid and siRNA exhibited rapid clearance from the blood, with levels dropping to near pre-dosing levels within 24 hours of administration. pExp5A plasmid DNA was detectable in the bone marrow of 2 pts at cohort 1, 2 at cohort 2, 1 at cohort 3 and 1 at cohort 4. eIF5A siRNA was not detectable in bone marrow. No antibodies to SNS01-T nanoparticles were detected at any timepoint at any dose level. Cytokines remained within the expected range of inter-patient variability, similar to baseline across all timepoints at the first 2 dose levels. At dose level 3, levels of IL-6, IL-8 and TNF-α in particular increased at the 2 and 6 hour timepoints but had recovered to baseline levels 24-hours post dosing. This effect was more pronounced at the first infusion. Conclusions PCR analysis demonstrated the presence of both plasmid DNA and siRNA components of SNS01-T in blood at all dose levels, with a dose-dependent increase in plasmid copy number. Plasmid DNA was also detected in bone marrow collected 24 hours after the final infusion of SNS01-T. Pro-inflammatory cytokines did increase within hours of infusion but returned to baseline within 24 hours, synchronous with the clinical infusion reactions (see Abstract 70148). No evidence of an anti-SNS01-T antibody response was observed in any subject. Phase 2 trials are planned. Disclosures Bexon: Senesco: Consultancy. Craig:Senesco: PI Other. Siegel:Senesco: PI Other. Bensinger:Senesco: PI Other. Novitzky:Senesco: PI Other. McDonald:Senesco: PI Other. Gutierrez:Senesco: PI Other. Libby:Senesco: PI Other. van Rhee:Senesco: PI Other. Heidel:Senesco: Consultancy. Thompson:Senesco: Consultancy, Employment, Equity Ownership, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties, Research Funding. Barranco:Senesco: Consultancy. Taylor:Senesco: Research Funding. Browne:Senesco: Employment. Kurman:Senesco: Consultancy. Lust:Senesco: PI Other. Dondero:Senesco: Employment.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,619
Score d'incertitude au seuil0,605

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,026
Tête enseignante GPT0,281
Écart entre enseignants0,255 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2014
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueBloodMême sujetPolyamine Metabolism and ApplicationsTravaux en français237 207