The Transcription Factor IRF8 Regulates the Sensitivity of AML Cells to LSD1 Inhibition and All-Trans Retinoic Acid
Notice bibliographique
Résumé
Introduction:Acute myeloid leukemia (AML) is a hematological neoplasm with poor outcomes owing to genetic heterogeneity with many mutations in epigenetic genes. One promising target is histone demethylase LSD1/KDM1A; inhibition of LSD1 (LSD1i) induces differentiation, targets leukemic stem cells (Harris et al., 2012) and facilitates the responsiveness of AML cells to all-trans retinoic acid (ATRA) induced differentiation (Schenk et al., 2012). In patients with AML, inhibitors of LSD1 have shown modest clinical responses. The factors influencing responsiveness of AML cells to LSD1i are not known. We have previously observed in murine models of AML, that leukemias driven by overexpression of Hoxa9 and Meis1 (H9M) showed morphological differentiation in response to LSD1i and were sensitized to ATRA. Leukemias overexpressing meningioma1 (MN1) did not show these effects. Based on transcriptomic analysis, we found a differential modulation of down-stream targets of the key monocytic transcription factor IRF8 (Barth et al., 2019). In this study we investigated the role IRF8 plays in determining the responsiveness of leukemic cells to LSD1i and ATRA. Methods:In murine retrovirally-induced AML cells (Hoxa9-Meis1, H9M; MN1) treated with LSD1 inhibitor (Bomedemstat) and ATRA, we assessed proliferation via the methoxynitrosulfophenyl-tetrazolium carboxanilide (XTT) assay, and the differentiation effect by flow cytometry. Gene expression levels of key myeloid transcription factors (TFs) and targets of ATRA (Spi1, Gfi1/1b, Rara, Tgm2) were determined via quantitative PCR. We generated H9M-transformed myeloid progenitor cells on an Irf8 knockout (KO) background, each line engrafted and generated AML. Results: H9M wild-type (WT) cells had an IC50 for ATRA in the nanomolar range (47 nM) which increased 151-fold to the micromolar range (7.1 µM) in H9M Irf8 KO (p≤ 0.05). The IC50 for Bomedemstat also increased 9.7-fold in the Irf8 KO (p≤ 0.05). While both H9M WT and H9M Irf8 KO demonstrated a reduction in the proportion of c-Kit+ cells, the upregulation of CD11b was significantly dampened in H9M Irf8 KO population, leading to a reduction in CD11b mean fluorescence intensity by 2.1-fold after treatment (p≤0.0001). To determine the relationship between IRF8 expression and the sensitivity of leukemic cells to ATRA, we examined the effect of the Irf8 KO on the expression of Rara and the regulation of RARA targets upon treatment. Based on the published data (Oki, S; Ohta, T (2015): ChIP-Atlas) we identified several direct binding sites for IRF8 in key regulatory regions of Rara. When comparing the expression of Rara between H9M and H9M Irf8 KO we found a 2.1-fold lower expression of Rara in Irf8 KO cells. Consistently, H9M Irf8 KO showed decreased responsiveness of an important ATRA target gene (Tgm2) upon treatment with ATRA. We investigated changes in core myeloid transcription factors interacting with LSD1i by qPCR. H9M Irf8 KO had 2.35-fold higher expression of Gfi1 compared to H9M WT cells but showed 26-fold lower expression of Gfi1b at baseline. Upon treatment with Bomedemstat, both H9M and H9M Irf8 KO cells showed a decrease in Gfi1 expression by 4.6 / 1.7-fold and a strong upregulation of Gfi1b by 38-fold / 460-fold, respectively. However, we observed a differential regulation of Gata1 and Gata2 between the models. While Gata1 expression is increased after treatment with Bomedemstat in H9M WT cells, it decreases in H9M Irf8 KO. Gata2 is showing the opposite trend consistent with the mutual regulation of these transcription factors. Conclusion : In summary, we found that IRF8 expression modulates the response of AML cells to both LSD1 inhibition and ATRA. These findings suggest IRF8 expression is a potential biomarker for selecting patients for treatment with an LSD1 inhibitor and ATRA.
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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 | 0,001 |
| 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 ».