Characterizing Transcriptional and Epigenetic Signatures Induced By FLT3-ITD Activation
Notice bibliographique
Résumé
Abstract Molecular studies have shown that specific somatic mutations impact therapeutic response and overall outcome in acute myeloid leukemia (AML) and have informed the development of molecularly targeted therapies. Previous studies have shown that the FLT3-ITD mutant disease allele predicts a poor prognosis in AML. Despite this important insight and the established role of FLT3-ITD mutations in AML pathogenesis, the impact of this mutation on gene regulation has not been extensively investigated. We hypothesized that transcriptional and epigenetic studies using genetically accurate murine models, cell lines, and primary AML samples would allow us to identify how FLT3 activation induces changes in gene expression and chromatin state. To assess the impact of FLT3-ITD associated FLT3 activation on gene expression, we performed RNA-sequencing studies on two FLT3-ITD cell lines (MOLM-13 and MV4-11) in the presence/absence of AC-220, a potent, specific FLT3 inhibitor. We also treated mice expressing a constitutive FLT3-ITD knock-in allele with AC-220 or vehicle, and performed RNA-sequencing on purified granulocyte-macrophage progenitors (GMPs). We assessed the impact of transient (4-12 hours drug treatment) and chronic (10-14 days) FLT3 inhibition on gene expression; we hypothesized that chronic drug exposure would result in more robust FLT3-mutant gene expression changes. In each case, the effects of FLT3-ITD activation/inhibition on gene expression were compared to RNA-seq data from FLT3-ITD mutant patients from TCGA. We first investigated the impact of short-term and chronic drug exposure on FLT3-ITD dependent gene expression in vitro. Comparison of short-term drug and vehicle treated cells revealed 159 differentially expressed (DE) genes (Benjamini-Hochberg false discovery rate (BH FDR) p < 0.05 and an absolute log2 fold change (FC) > 0.8). By contrast, we found that chronic FLT3 inhibition identified 743 DE genes. Comparison between the acutely and chronically treated cell lines revealed overlap of only 19 genes, suggesting important differences between the acute and steady-state effects of FLT3-inhibition. We found more significant overlap between chronic FLT3-inhibitor gene expression and FLT3-ITD specific gene expression in TCGA, demonstrating that long-term drug exposure more robustly delineates mutant-specific effects on gene expression. We next investigated the impact of short and long term FLT3-inhibition on gene expression in vivo. Analysis of DE genes identified 93 genes in the acutely treated mice vs. vehicle, and 274 genes in chronically treated mice (BH FDR p < 0.05 and absolute log2 FC of > 0.5). Only 12 DE genes were shared between these two perturbations compared with vehicle control. We then compared these gene expression signatures to FLT3-ITD specific gene expression from TCGA; we noted a significant inverse correlation between the signatures of chronic FLT3 inhibition in vivo with FLT3-ITD specific gene expression in TCGA (R2=0.47), but no correlation between the gene expression changes of acute FLT3 inhibition and FLT3-ITD TCGA patients (R2=0.09). We next integrated the FLT3 signatures from our in vivo work and TCGA with ChIP-sequencing for H3K4me3 and H3K27me3 in primary samples with FLT3-ITD compared to normal controls. We found that 3.6% of DE genes in our in vivo system, and 7.2% of DE genes in TCGA, had significant changes in H3K4me3 or H3K27me3. The most common alteration in chromatin state observed with FLT3 activation was an increase in H3K4me3 and transcriptional activation, with a smaller set of genes showing increased H3K27me3 and reduced expression, consistent with FLT3-mediated epigenetic repression. Motif analysis showed that DE loci with significant changes in chromatin state were enriched for ELF5, NF-E2, Pu.1, and Bach1 binding sequences, implicating these transcription factors in mediating FLT3-dependent gene expression effects. By studying the global transcriptional changes that occur with chronic, steady-state FLT3 inhibition in in vitro and in vivo systems, we identified a set of gene expression changes characteristic of FLT3-activation. In addition, integrating changes in gene expression and chromatin state allowed us to identify loci with alterations in epigenetic state in the setting of FLT3-ITD associated FLT3 activation, and to identify candidate transcription factors that mediate FLT3-dependent effects on gene expression. Disclosures No relevant conflicts of interest to declare.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».