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Enregistrement W2149573012 · doi:10.1038/bcj.2014.51

High DNA-methyltransferase 3B expression predicts poor outcome in acute myeloid leukemia, especially among patients with co-occurring NPM1 and FLT3 mutations

2014· letter· en· W2149573012 sur OpenAlexaff
Davide Monteferrario, Sylvie M. Noordermeer, Saskia M. Bergevoet, Gerwin Huls, Joop H. Jansen, Bert A. van der Reijden

Notice bibliographique

RevueBlood Cancer Journal · 2014
Typeletter
Langueen
DomaineMedicine
ThématiqueAcute Myeloid Leukemia Research
Établissements canadiensMount Sinai HospitalLunenfeld-Tanenbaum Research Institute
Organismes subventionnairesnon disponible
Mots-clésNPM1DNMT3BCEBPAMethyltransferaseOncologyMyeloid leukemiaHazard ratioInternal medicineMedicineHematologyTransplantationBiologyImmunologyCancer researchGeneticsConfidence intervalMutationMethylationKaryotypeGene

Résumé

récupéré en direct d'OpenAlex

DNA methyltransferases (DNMTs) are epigenetic regulators targeted to the treatment of hematological malignancies. 1 , 2 , 3 , 4 Mutations in the DNA methyltransferase DNMT3A and high expression of its paralogue DNMT3B have been associated with inferior outcome in acute myeloid leukemia (AML) and other hematological malignancies. 5 , 6 , 7 , 8 Using a publicly available gene expression data set, 9 we studied whether DNMT3B expression correlates with outcome in genetically well-defined AML subgroups. We first validated the expression data from the microarray by quantitative PCR, using 39 patient samples ( Supplementary Figure S1A ). DNMT3B micro-array analyses showed that the expression was not normally distributed among AML patients; in the quartile with highest expression, a larger variation in expression was observed compared to the three quartiles with relatively lower expression ( Supplementary Figure S1B ). The median DNMT3B expression in AML samples was significantly lower compared with that observed in normal bone marrow (NBM)-derived CD34 + cells ( P <0.0001), while it was higher compared to NBM cells, but the latter difference was not statistically significant ( Supplementary Figure S1B ). Subsequently, we investigated the correlation between DNMT3B expression and overall survival (OS) and event-free survival (EFS). In univariate Cox regression analyses, continuous DNMT3B expression was significantly associated with poor survival ( P <0.001 for both OS and EFS, data not shown). To visualize the prognostic impact, we performed Kaplan–Meier analyses on the four quartiles based on expression levels. The quartile including the patients with the highest DNMT3B expression, exhibiting the largest variation in expression, showed a significantly reduced OS and EFS compared to the other quartiles ( Supplementary Fig. S2 ). As the survival between the lower three quartiles did not differ significantly, we grouped these patients together as having lower DNMT3B expression, whereas the remaining patients were ranked as having higher DNMT3B expression. Using these criteria, the 5-year OS and EFS were 17.2%±3.3% and 13.6%±3.0% for patients with higher DNMT3B expression compared to 43.8%±2.5% and 34.4%±2.4% for patients with lower DNMT3B levels ( P <0.001, Figure 1a ). We next performed a multivariate Cox regression analysis including known prognostic factors (including age >60 years; white blood cell counts >100 × 10 9 /l; transplantation status; karyotypes t(8;21), t(15;17) and inv(16); nucleophosmin 1 ( NPM1 ), FLT3-ITD , DNMT3A and double CEBPA mutations, and ecotropic viral integration site 1 ( EVI1 ) overexpression), which revealed that higher DNMT3B expression carried an independent prognostic risk for both OS and EFS (hazard ratio (HR): 1.768, 95% confidence interval (CI): 1.384–2.260; P <0.001 and HR: 1.706, 95% CI: 1.342–2.168; P <0.001, respectively, Table 1 ), in line with a recently published study. 7 In fact, higher DNMT3B expression showed a higher hazard ratio for OS than that of well-known adverse prognostic factors such as internal tandem duplications of the fms-related tyrosine kinase 3 ( FLT3-ITD , HR: 1.675, 95% CI: 1.287–2.179; P <0.001) and overexpression of the EVI1 gene (HR: 1.430, 95% CI: 0.999–2.047; P =0.051). Figure 1 Higher DNMT3B expression correlates with inferior OS and EFS in AML. ( a ) Kaplan–Meier plots for OS and EFS showed that higher DNMT3B expression correlated significantly with a poor OS and EFS among AML patients (5-year OS: 17.2%±3.3% vs 43.8%±2.5% and 5-year EFS: 13.6%±3.0% vs 34.4%±2.4% for patients with higher and lower DNMT3B expression, respectively). ( b ) Higher DNMT3B expression predicted a very poor OS and EFS among patients with normal karyotype carrying NPM1 and FLT3-ITD mutations compared to patients with lower DNMT3B expression (5-year OS: 16.7±6.2% vs 47.6±8.8%, P =0.001 and 5-year EFS: 16.7±6.2% vs 39.0±8.6%, P =0.005 for patients with higher and lower DNMT3B expression, respectively). ( c ) Within the group of patients with normal karyotype that carries NPM1 mutations with high FLT3-ITD allelic burden, higher DNMT3B expression correlated with an extremely poor OS and EFS compared to patients with lower DNMT3B expression (5-year OS: 0%±0.0% vs 38.9%±12.9%, P <0.001 and 5-year EFS: 0%±0.0% vs 32.0%±12.4%, P <0.001 for patients with higher and lower DNMT3B expression, respectively). P values were determined with the log-rank test. In agreement with de Jonge et al., 13 high FLT3-ITD allelic burden was defined as an allelic FLT3-ITD / FLT3 ratio >1. Full size image Table 1 Data proving that DNMT3B expression is a prognostic factor in AML, particularly in NPM1 + / FLT3-ITD + patients with normal karyotype Full size table

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)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,002
Score d'incertitude au seuil0,007

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,001

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 Opus0,014
Tête enseignante GPT0,283
Écart entre enseignants0,268 · 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'étudeObservationnel
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

Citations4
Publié2014
Routes d'admission1
Résumé présentoui

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