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Enregistrement W2505350742 · doi:10.1182/blood.v114.22.4920.4920

Trolox Improves the Sensitivity of Multiple Myeloma to Arsenic Trioxide in Vitro and In Vivo.

2009· article· en· W2505350742 sur OpenAlexaff
Michaël Sébag, Xian-Fang Huang, Nicolas Garnier, Wilson H. Miller, Koren K. Mann

Notice bibliographique

RevueBlood · 2009
Typearticle
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueRetinoids in leukemia and cellular processes
Établissements canadiensMcGill UniversityMcGill University Health Centre
Organismes subventionnairesnon disponible
Mots-clésTroloxArsenic trioxideViability assayCell cultureAcute promyelocytic leukemiaIn vivoCell growthApoptosisCancer researchToxicityChemistryPharmacologyMedicineBiologyBiochemistryInternal medicineRetinoic acidAntioxidant

Résumé

récupéré en direct d'OpenAlex

Abstract Abstract 4920 Arsenic trioxide (ATO) induces apoptosis and promotes differentiation of acute promyelocytic leukemia (APL) cells, but has less activity in other types of cancers. One factor that may impede ATO success outside of APL is its toxicity profile, which limits in vivo concentrations and therefore, therapeutic benefit. We have reported that trolox, an analogue of alpha tocopherol, can augment ATO sensitivity in a variety of malignant cells, while protecting non-malignant cells from ATO toxicity. In this current study, we have focused on Multiple Myeloma (MM), a plasma cell malignancy that often shows resistance to apoptosis, drug inhibition and remains incurable despite tremendous recent advances. Although ATO has activity against MM cells in vitro, clinical trials of ATO, given as a solo agent, in MM have shown limited promise. To see if the addition of trolox could augment ATO toxicity, a panel of human myeloma cell lines (HMCLs, n=9) representing the genetic diversity seen in this disease, were treated with increasing concentration of ATO with and without 100uM trolox. Cell growth was assessed by MTT viability assays and virtually all cell lines were sensitive to varying doses of ATO. Four cell lines (U266, KMS11, MM1R, MM1S) showed profound inhibition of cell growth with very low concentrations of ATO (<1uM). Trolox (100uM) alone had no effect on cell growth, but in concert with ATO further decreased cell growth by up to 50% as compared to the same dose of ATO alone in virtually all cell lines. To further elucidate the mechanism of growth inhibition, annexin V assays were performed by flow cytometry to measure apoptosis. In all cell lines (n=9), a clear increase in the apoptotic fraction was noted when trolox was added to varying doses of arsenic. To test whether oxidative stress plays a role in ATO-mediated apoptosis of myeloma cells, we looked at the induction of a stress response protein (HO-1), a marker of oxidative stress induced by ATO. Western blot analysis revealed that in all myeloma cells tested, HO-1 was dramatically and quickly induced by ATO and further induced by the addition of trolox, indicating a pro-oxidant activity of trolox in the malignant cells. While the mechanism of trolox enhancement of ATO function remains largely unknown, intracellular concentrations of ATO in MM cells, as measured by inductively coupled plasma mass spectrometry, suggest that trolox does not work by augmenting ATO import or intracellular accumulation. To test the efficacy of ATO with trolox in vivo, we used a novel transgenic mouse model of MM that has been shown to faithfully mimic the human disease and its response to treatment (Chesi et al, Cancer Cell 2008 Feb;13(2):167-80). We first treated MM afflicted mice with a low dose of ATO (5.0mg/kg) and Trolox (50mg/kg) to assess for toxicity and tolerability. This dose was well tolerated in all mice when given for 10 days with no obvious toxic effects. Serum protein electrophoresis performed at the end of the 10 day treatment period revealed that even at this low starting dose, one of three mice showed a 30% reduction in its paraprotein peak, while the others remained stable. Further studies with higher ATO concentrations in the same mouse model are underway. In conclusion, these data support the role of ATO plus Trolox, as a promising anti-myeloma therapy. Disclosures No relevant conflicts of interest to declare.

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: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,021
Score d'incertitude au seuil0,289

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 Opus0,004
Tête enseignante GPT0,212
Écart entre enseignants0,207 · 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

Citations1
Publié2009
Routes d'admission1
Résumé présentoui

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