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Enregistrement W2593611659 · doi:10.1182/blood.v118.21.233.233

Inhibition of Mitochondrial Translation As a Therapeutic Strategy for Acute Myeloid Leukemia (AML)

2011· article· en· W2593611659 sur OpenAlexaff
Marko Škrtić, Shrivani Sriskanthadevan, Bozhena Livak, Marinella Gebbia, Xiaoming Wang, Zezhou Wang, Rose Hurren, Yulia Jitkova, Marcela Gronda, Neil MacLean, Courteney Lai, Yanina Eberhard, Justyna Bartoszko, Paul A. Spagnuolo, Angela C. Rutledge, Alessandro Datti, Troy Ketela, Jason Moffat, Brian H. Robinson, Jessie M. Cameron, Jeffrey L. Wrana, Connie J. Eaves, Mark D. Minden, Jean Wang, John E. Dick, R. Keith Humphries, Corey Nislow, Guri Giaever, Aaron D. Schimmer

Notice bibliographique

RevueBlood · 2011
Typearticle
Langueen
DomaineChemistry
ThématiqueClick Chemistry and Applications
Établissements canadiensHospital for Sick ChildrenLunenfeld-Tanenbaum Research InstituteMount Sinai HospitalUniversity of TorontoUniversity Health NetworkPrincess Margaret Cancer CentreBC Cancer AgencyOntario Institute for Cancer Research
Organismes subventionnairesnon disponible
Mots-clésMyeloid leukemiaStem cellBiologyCancer researchHaematopoiesisClonogenic assayHematopoietic stem cellCell cultureMolecular biologyCell biologyGenetics

Résumé

récupéré en direct d'OpenAlex

Abstract Abstract 233 To identify novel therapeutic strategies that can eliminate AML and AML stem cells, we screened a library of on and off-patent drugs for candidates that could reduce the viability of engineered human AML cell lines that display the stem cell properties of differentiation, self-renewal, and marrow repopulation. This screen identified the anti-microbial agent tigecycline (TIG) as a top candidate with an LD50 of 3 to 8 uM, on 5 human AML cell lines. A lethal action was also demonstrated on 13 of 20 1°AML samples with similar potency (LD50 <5 uM). In contrast, normal hematopoietic cells, including the CD34+ subset, were more resistant (LD50 >10 uM). We also found that 5 mM TIG reduced the clonogenic growth of 1°AML samples by 93±4% and was effective in reducing the ability of AML cells to regenerate disease in transplanted immunodeficient mice. In contrast, 5 uM TIG had no effect on the clonogenic growth or repopulating potential of normal human hematopoietic cells. To determine the mechanism of action of TIG, we used Haplo-Insufficiency Profiling, a functional chemical genomic screen, in S. cerevisiae. The Gene Ontology component that was the most enriched for TIG was the mitochondrial ribosome. We subsequently demonstrated that TIG inhibited mitochondrial but not cytoplasmic translation in AML cell lines and in 1°AML samples. Consistent with the inhibition of mitochondrial translation, TIG decreased the enzyme activity of Complex I and IV, which contain mitochondrially-translated subunits, but not complex II (nuclear-encoded subunits only). TIG also decreased oxygen consumption and decreased mitochondrial-membrane potential in AML cell lines and 1°AML samples, but not normal hematopoietic cells. Interestingly, unlike many mitochondrial inhibitors, TIG did not increase ROS production in AML cells. Additional experiments demonstrated that inhibition of mitochondrial translation was functionally important for the anti-leukemia activity of TIG. Next, we asked whether genetic strategies in leukemia cells would produce similar anti-leukemic effects as obtained with TIG. Knockdown of the mitochondrial-elongation factor EF-Tu mimicked the ability of TIG to inhibit mitochondrial translation, decrease mitochondrial membrane potential, decrease complex I and IV activity and induce cell death in AML cells. Also, EF-Tu knockdown did not increase ROS production. To investigate the basis of the hypersensitivity of AML cells to mitochondrial translation inhibition, we assessed baseline mitochondrial characteristics of 1°AML cells and their normal counterparts. 1°AML cells (including CD34+CD38- AML cells) had higher intrinsic mitochondrial-biogenesis (mtDNA copy number, mitochondrial mass) than normal CD34+ hematopoietic cells. Furthermore, rates of oxygen consumption were higher in 1°AML cells as compared to normal hematopoietic cells. Baseline mitochondrial-mass in AML cells also predicted in vitro toxicity to TIG, as 1° AML cells with higher mitochondrial mass were more sensitive to TIG (r = −0.71, p <0.05). To assess the anti-leukemia efficacy of mitochondrial translation inhibition in vivo, we investigated human AML cells in mouse xenograft models. TIG significantly delayed tumor growth of OCI-AML2 xenografts in SCID compared to untreated control mice. We then assessed the effect of TIG on AML stem cells defined by their ability to sustain leukemic cell growth in vivo. NOD/SCID mice engrafted with human AML cells and then treated with TIG showed a decrease in human AML cells by up to 77% without toxicity including alterations in liver and muscle enzymes. In contrast, NOD/SCID mice engrafted with normal cord blood did not show reduced engraftment after TIG treatment. Importantly, the human AML cells harvested from the bone marrow of the TIG-treated 1° mice generated fewer leukemic cells in secondary mice, compared to the AML cells harvested from control (untreated) primary mice, thus demonstrating an in vivo effect on the AML stem cells. In conclusion, mitochondrial translation inhibition selectively kills AML vs. normal cells, including those defined functionally as AML progenitors and stem cells. This selectivity appears attributable to the higher rate of mitochondrial biogenesis found in AML cells. Given these results and the known pharmacology and toxicology of TIG in humans, targeting mitochondrial translation inhibition as a therapeutic strategy in AML is attractive. Disclosures: Off Label Use: Tigecycline is currently used as an a broad spectrum antibiotic, and is here discussed as an AML agent.

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 enseignants0,033
Score d'incertitude au seuil0,525

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 Opus0,042
Tête enseignante GPT0,281
Écart entre enseignants0,239 · 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
Publié2011
Routes d'admission1
Résumé présentoui

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