Estrogen Receptor Beta Is a Novel Target in Acute Myeloid Leukemia
Notice bibliographique
Résumé
Abstract Acute myeloid leukemia (AML) is a heterogeneous and aggressive malignant disease characterized by poor patient outcome and suboptimal front-line chemotherapy. To identify novel anti-AML compounds and potential molecular markers that confer drug-specificity, we performed a high-throughput screen of an in-house library consisting only of food-derived bioactive molecules (n=300). This screen was performed against the AML cell line (TEX), which has several properties of leukemia stem cells, the cells responsible for disease pathophysiology and patient relapse. This screen identified diosmetin as a novel anti-leukemia agent (IC50: 6.8 ± 1.7µm). Diosmetin (10µM) reduced clonogenic growth of primary AML patient cells with no effect on normal hematopoetic stem cells. In leukemia mouse xenografts, administration of diosmetin (50mg/kg) reduced tumor weight (>40%) without evidence of toxicity. Collectively, this shows that diosmetin is a novel anti-AML agent. Diosmetin-induced apoptosis (e.g., increased Annexin V staining and DNA fragmentation) was abolished in the presence of caspase-inhibitors. Importantly, diosmetin, which is a flavonoid and a known ROS-inducer, induced death in the presence of anti-oxidants demonstrating that death was not related to ROS activity. Instead, we demonstrate that diosmetin-induced caspase 8-, not caspase 9, mediated apoptosis that was facilitated by increased TNF-α. To identify diosmetin's molecular target we employed a novel method utilizing several free-online bioinformatics tools. Here, the protein data base (PBD), Pocket Similarity Search using Multi-Sketches (PoSSuM) and Database for Annotation, Visualization and Integrated Discovery (DAVID) tool, were used sequentially to identify potential diosmetin binding partners. This method identified the estrogen receptor (ER) as a potential molecular target for diosmetin's anti-leukemia activity. There are two types of ERs. When activated, ERα increases cell proliferation whereas ERβ inhibits proliferation. These opposite and opposing roles have led to the hypothesis that ER expression patterns dictate the cell's response to estrogen, as hormones like estradiol can bind to both ERα and ERβ with different affinities. To first determine to which ER diosmetin bound, we mapped the binding sites of both ERα and ERβ using the Discovery Studio (DS), Structure-Based-Design program and determined the relative affinity of diosmetin to these ERs. Diosmetin bound with far greater affinity to ERβ than ERα. Next, we interrogated publically available AML patient datasets to determine the expression pattern of ERα versus ERβ. Interestingly, we noted a subset of AML patients that upregulate ERβ but not ERα expression (log4 fold increase; p<0.001) suggesting the clinical relevance of targeting ERβ in a subset of AML patients. To assess the cell and molecular role of ERs, we measured ERα and ERβ levels in diosmetin sensitive and insensitive cell lines. Interestingly, diosmetin sensitive cell lines (TEX, LP1, AML2) display significantly elevated ER-β protein and mRNA levels (4 fold, as determined by Western blotting and qtPCR, respectively) compared to diosmetin insensitive cell lines (K562, DU145). This pattern was not observed for ER-α. Furthermore, this ER expression pattern was also observed in primary AML cells; as AML cells sensitive to diosmetin displayed an increase in ERβ, but not ERα, mRNA. Finally, ER reporter assays demonstrated that diosmetin binds and acts as a partial agonist in ERβ but not ERα reporter cells. Together, these results show that diosmetin binds to ERβ and that ERβ is functionally important to diosmetin's activity. In summary, these studies highlight ERβ as a potential novel therapeutic target for the treatment of AML. 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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».