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Enregistrement W2553044273 · doi:10.1182/blood.v126.23.1567.1567

Identification and Characterization of New Microrna Biomarkers and Target Genes in Drug-Insensitive CD34+ CML Stem/Progenitor Cells Using Global Comparative RNA-Seq Analyses

2015· article· en· W2553044273 sur OpenAlexaff
Hanyang Lin, Jonathan Zeng, Katharina Rothe, Jens Rüschmann, Oleh I. Petriv, Kieran O’Neill, Tobias Maetzig, David J. H. F. Knapp, Ryan R. Brinkman, İnanç Birol, Donna L. Forrest, Carl L. Hansen, Connie J. Eaves, R. Keith Humphries, Xiaoyan Jiang

Notice bibliographique

RevueBlood · 2015
Typearticle
Langueen
DomaineMedicine
ThématiqueChronic Myeloid Leukemia Treatments
Établissements canadiensCanada's Michael Smith Genome Sciences CentreUniversity of British ColumbiaBC Cancer Agency
Organismes subventionnairesnon disponible
Mots-clésmicroRNACD34Stem cellProgenitor cellBiologyCancer researchHaematopoiesisMiRBaseGeneGenetics

Résumé

récupéré en direct d'OpenAlex

Abstract Therapeutic targeting of BCR-ABL with selective ABL tyrosine kinase inhibitors (TKIs) has led to a significant survival benefit for early phase CML. However, TKI monotherapies are rarely curative, with persistence of leukemic stem cells, emergence of resistance and relapses remaining as challenges. To identify differentially expressed and new miRNAs in CD34+ CML stem/progenitor cells that might serve as potential biomarkers and/or therapeutic targets, we have performed Illumina Deep Sequencing to obtain absolute miRNA expression profiles of highly purified CD34+ cells obtained at newly diagnosed stage from six CML patients. Three of the patients were classified retrospectively, after imatinib (IM) therapy, as IM-responders and three as IM-nonresponders. CD34+ cells isolated from five normal bone marrow (NBM) samples were similarly analyzed as controls. Bioconductor DESeq2 analysis revealed 63 differentially expressed miRNAs between CML and NBM samples (adjusted P<0.05). Most differentially expressed miRNAs identified were down-regulated in CML compared to NBM, while 17 were up-regulated. Interestingly, 12 miRNAs were found to be differentially expressed between the IM-responders and IM-nonresponders. In addition, 34 novel miRNAs were identified in the CD34+ CML stem/progenitor cells. We next validated the sequencing data in a larger cohort of samples. CD34+ cells from IM-responders (n=12), IM-nonresponders (n=10) and normal individuals (n=11) were analyzed using a high-throughput qPCR microfluidics device. These studies confirmed the differential expression in CD34+ CML cells of 32 of the 63 miRNAs (adjusted P<0.05), including an increased level of oncomirs miR-155 and miR-17-92, and a decreased level of tumor suppressors miR-145, miR-151, and miR-452. Importantly, significant changes in some of these miRNAs were detected in CD34+ cells from CML patients (n=60) after three months of nilotinib (NL) treatment compared to the same patient samples before the treatment: expression of 18 miRNAs were normalized after NL therapy, whereas 10 showed little change. To further identify potential miRNA target genes, RNA-seq analysis was performed on the same RNA samples to correlate miRNA profiles with corresponding mRNA expression changes. Bioconductor RmiR analysis was performed to match miRNA target genes whose expression was inversely correlated with the expression of deregulated miRNAs based on three of six prediction algorithms (mirBase, TargetScan, miRanda, tarBase, mirTarget2, and PicTar). We have identified 1,210 differentially expressed mRNAs that are predicted targets of the deregulated miRNAs in the comparison of CML and NBM data. Interestingly, only seven differentially expressed genes were predicted targets of the deregulated miRNAs identified in a comparison of IM-responders and IM-nonresponders. Most of the predicted target genes are involved in cell cycle regulation, MAPK signaling and TGF-beta signaling pathways according to DAVID Bioinformatics Resources analysis, which clusters predicted target genes to known KEGG pathways. To elucidate the biological significance of the differentially expressed miRNAs in TKI-insensitive CML stem/progenitor cells, a number of functional assays were performed. An initial screen of eight miRNAs, selected for their novelty and CML-related potential target genes, was performed by transiently transfecting CML cells with miRNA mimics or inhibitors, and chemically synthesized RNAs which mimic or inhibit mature endogenous miRNAs. Four of the eight miRNA mimics/inhibitors transfected cells displayed significant growth disadvantages and enhanced sensitivity to TKI treatments based on trypan-blue exclusion, thymidine incorporation, apoptosis, and colony-forming cell assays. Q-RT-PCR analysis further showed reduced expression of their predicted target genes in cells transfected with miRNA mimics. Taken together, we have identified aberrant, differentially expressed miRNAs and their target genes in TKI-insensitive CML stem/progenitor cells that may serve as useful biomarkers to predict clinical response of CML patients to TKI therapy and ultimately lead to identification of new therapeutic targets for improved treatment options in CML. 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 seuil0,003

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 Opus0,071
Tête enseignante GPT0,331
Écart entre enseignants0,260 · 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
Publié2015
Routes d'admission1
Résumé présentoui

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