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Enregistrement W2910526560 · doi:10.1182/blood-2018-99-113559

Global Transcriptome Profiling Identifies a Key Mir-185-PAK6 Axis That Promotes Survival of Leukemic Stem Cells and Drug-Insensitive Blasts in BCR-ABL+ Human Leukemia

2018· article· en· W2910526560 sur OpenAlexaff
Andrew Wu, Katharina Rothe, Min Chen, Jens Rüschmann, Oleh I. Petriv, Kieran O’Neill, Tobias Maetzig, David J. H. F. Knapp, Naoto Nakamichi, Ryan R. Brinkman, İnanç Birol, Donna L. Forrest, Carl L. Hansen, R. Keith Humphries, Connie J. Eaves, Xiaoyan Jiang

Notice bibliographique

RevueBlood · 2018
Typearticle
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueMicroRNA in disease regulation
Établissements canadiensCanada's Michael Smith Genome Sciences CentreUniversity of British ColumbiaTerry Fox Research InstituteBC Cancer Agency
Organismes subventionnairesnon disponible
Mots-clésCD34Stem cellCancer researchProgenitor cellNilotinibTranscriptomeBiologymicroRNAMyeloid leukemiaGene expression profilingLeukemiaHaematopoiesisImmunologyGene expressionCell biologyImatinibGene

Résumé

récupéré en direct d'OpenAlex

Abstract Chronic myeloid leukemia (CML) stem/progenitor cells and BCR-ABL+ acute lymphoblastic leukemia (ALL) blast cells are insensitive to tyrosine kinase inhibitor (TKI) monotherapies. These cells rapidly generate therapy-resistant clones in vitro and in vivo and are often responsible for disease relapse. Therefore, identification of predictive biomarkers and novel treatments that target key molecular events active in leukemic stem cells (LSCs) are needed. MicroRNAs (miRNAs) are small molecules that regulate the gene expression network and are highly deregulated in many cancers. Through global transcriptome profiling, we have recently identified 66 differentially expressed miRNAs in pre-treatment CD34+ stem/progenitor cells from CML patients (n=6) compared to healthy bone marrow (NBM) controls (n=3, adjusted P<0.05); 26 differentially expressed miRNAs were identified between subsequent IM-nonresponders and IM-responders (P<0.05). 21 differentially expressed miRNAs were successfully validated in additional IM-responders (n=11), IM-nonresponders (n=11) and NBM (n=11). Interestingly, miR-185 was discovered to be one of the most highly deregulated miRNAs, with significant reduction in CD34+ cells from IM-nonresponders compared to IM-responders (p=0.0006). This significant change was further demonstrated in CD34+ cells from CML patients (n=60) before and after 3-month TKI nilotinib treatment in a clinical trial (p<0.05). We further demonstrated that miR-185 functions as a tumor suppressor; its restored expression by lentiviral transduction in CD34+ IM-nonresponder cells significantly impaired survival of these cells and sensitized them to TKI treatment in vitro. Restored miR-185 expression in BCR-ABL+ ALL blasts led to a profound decrease in leukemia burden and significantly enhanced survival compared to controls in vivo (median survival 65 vs. 47 days, P=0.0005). Strikingly, mice injected with miR-185-transduced cells and treated with dasatinib (DA) survived much longer than recipients of control cells treated with DA (median survival 83 vs. 60 days, P=0.0018). Moreover, restoration of miR-185 expression combined with DA treatment greatly reduced in vivo long-term regenerative activity of LSCs from IM-nonresponders as compared to control cells treated with DA in NRG mice (<0.2% vs. 5% GFP+ patient cells in the BM, 25 weeks post-transplantation). We observed not only a marked reduction in GFP+CD34+ cells, but also a near elimination of GFP+CD34+CD38- LSCs that were transduced with miR-185 and treated with DA compared to control cells treated with DA, indicating that restored miR-185 expression combined with DA preferentially prevents the growth of patient-derived long-term leukemia-initiating cells in vivo. Several miRNA target genes were further identified by integrating miRNA expression profiles with gene expression profiles from the same patient samples using strand-specific RNA-seq. Based on three out of six prediction algorithms (mirBase, TargetScan, miRanda, tarBase, mirTarget2, and PicTar), PAK6, a serine/threonine-protein kinase, was found to be highly expressed in CD34+ IM-nonresponder cells compared to IM-responders (p<0.003), which correlated with reduced expression of miR-185 in these cells (p=0.0002). PAK6 was confirmed as a target gene of miR-185 by a luciferase reporter assay. Western blot analysis showed that restored miR-185 expression caused a marked decrease in protein levels of PAK6 in miR-185-transduced cells and suppression of PAK6 reduced viability of these cells. These results indicate that PAK6 is a critical target of miR-185, and that loss of miR-185 expression in CML may lead to up-regulation of PAK6, which in turn contributes to disease progression and drug resistance. Indeed, the use of a pre-clinically validated pan PAK inhibitor (PF-3758309) significantly inhibited the growth of IM-resistant cells and CD34+ IM-nonresponder cells and these effects could be enhanced by TKIs (p<0.05). Mechanistically, we observed that p-ERK and p-AKT were significantly reduced in PAK6 knockdown or miR185-restored IM-resistant cells in response to IM treatment. Thus, we infer that downregulation of PAK6 may sensitize TKI-resistant cells to TKI therapy through inhibition of the RAS/MAPK pathway. Taken together, PAK6, a novel target of miR-185, emerges as an attractive druggable target for combination therapy of TKI-resistant patients. 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 machine sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut 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 enseignants0,001
Score d'incertitude au seuil0,004

Scores du classifieur distillé par catégorie (deux têtes)

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)0,0010,000

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 Opus0,012
Tête enseignante GPT0,242
Écart entre enseignants0,230 · 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 source (Gemma direct ou Codex distillé), 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
Publié2018
Routes d'admission1
Résumé présentoui

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