Preclinical Determination of the Efficacy of Epigenetic Therapy in High Risk Myeloid Disease Using the Zebrafish Model
Notice bibliographique
Résumé
Abstract Epigenetic therapy implies the use of drugs that target regulators of gene expression, such as DNA and histone methylation or histone acetylation, without altering the DNA coding sequence. Epigenetic mechanisms have been found to be perturbed in myeloid diseases, and in fact, the DNA demethylating agents, 5-azacytadine and decitabine are FDA approved drugs for myelodysplastic syndrome. However, use of epigenetic therapies in other types of myeloid disease including acute myeloid leukemia (AML) has been met with variable success, suggesting efficacy might be improved by preselecting subtypes of disease in which there is a high degree of epigenetic dysregulation. AML has recently been found to be associated with a host of epigenetic abnormalities including mutations in DNA methyltransferase 3A (DNMT3A), ten-eleven translocation-2 (TET2) and enhancer of zeste homolog 2 (EZH2). We generated a transgenic zebrafish model of high risk myeloid disease expressing the human NUP98-HOXA9 (NHA9) fusion oncogene, a genetic lesion for which epigenetic dysregulation has not previously been identified. Transgenic embryos exhibit an increase in immature myeloid cells at the expense of erythroid cells and adult fish develop a myeloproliferative neoplasm (MPN). Leveraging this model in a microarray screen, we identified 3-fold elevated levels of the epigenetic regulator, dnmt1, the major maintenance methyltransferase, for the first time in high risk AML. Decitabine specifically inhibits DNMT1 and treatment of NHA9 transgenic embryos with 75µM decitabine restored normal hematopoiesis, as evidenced by normal numbers of leukocytes and red cells. Moreover, using hematopoietic stem cell (HSC) reporter lines and whole mount in situ hybridization, we identified a 2-3 fold increase in this population in NHA9 embryos, suggesting the HSC as the cell of origin in this disease. Interestingly, 75µM decitabine therapy also restored normal HSC numbers. Strikingly, we discovered synergy when we combined sub-monotherapeutic doses of DNMT1 inhibitors, decitabine (10-25µM) or zebularine (100µM), plus histone deacetylase inhibitors, valproic acid (25-100µM) or trichostatin A (250nM), to inhibit the effects of NHA9 on hematopoiesis. To determine if NHA9 expression directly results in changes to DNA methylation, we performed MeDIP-Seq on genomic DNA from pools of untreated and decitabine-treated NHA9 or control embryos. Untreated NHA9 embryos displayed significantly higher methylation levels at the regions of gene promoters compared to control embryos, which were restored to control levels following treatment with 75µM decitabine. Similarly, combination therapy with 10µM decitabine and 25µM valproic acid significantly reduced methylation to near control levels following a 5 hour treatment, while prolonged exposures to these same doses resulted in profound global hypomethylation. These findings elucidate underlying mechanisms in the pathogenesis of NHA9-induced myeloid disease and propose novel actionable epigenetic drug targets. Furthermore, we highlight the opportunities inherent in the zebrafish model as a unique in vivo platform for the preclinical screening of epigenetic based combination therapy. 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 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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
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.
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 ».