Abstract 4498: Drug screens identify new therapeutic targets that synergize with EZH1/2 inhibition in adult T-cell leukemia/lymphoma
Notice bibliographique
Résumé
Adult T-cell leukemia/lymphoma (ATLL), a rare form of non-Hodgkin lymphoma, affects approximately 2-5% of individuals infected by the retrovirus Human T-cell Lymphotropic Virus- 1 (HTLV-1). The disease has a dismal prognosis and resistance to chemotherapy is commonly seen in most patients. A significant characteristic of ATLL pathogenesis involves the disruption of normal epigenetic regulation, which results in transcriptional repression of tumour suppressors, mediated by the polycomb repressor complex 2 protein. Within this protein complex, the histone methyltransferases EZH1 and EZH2 play vital roles in catalyzing the excessive trimethylation of histone 3 lysine 27 (H3K27me3). In light of these mechanisms, a phase II clinical trial evaluated the efficacy of Valemetostat (VAL), a dual EZH1/2 inhibitor, in ATLL patients. Half of the patients responded to VAL; however, the median progression-free survival was only 7 months.To address these challenges and unbiasedly identify agents that could synergize with VAL, we conducted extensive high-throughput drug screens across four ATLL cell lines (ATL1K, ATL43T-, ATL55, and ED41214+). We initially screened 3,113 FDA-approved drugs to assess their pharmacological relevance in the presence of VAL. Additionally, given the important role of epigenetic deregulation in the pathogenesis of ATLL, we also tested 68 epigenetic chemical probes (ECPs) from the Structural Genomics Consortium with and without VAL. From these screens, we narrowed down the top 98 candidates from the FDA-approved drugs, based on the average cell viability minus two standard deviations, and the top five synergistically effective ECPs based on Bliss syngery score calculated by Synergy Finder across all four cell lines. We next screened these hits from FDA-approved drugs and the synergistically effective ECPs along with the corresponding negative non-functional probes across a wider ten-point dose range(2.5nM to 1uM for FDA-approved drugs and 10nM to 5uM for ECPs), both in the presence or absence of VAL. Based on the observed synergy, we identified our top nine hits that included bromodomain and methyltransferase inhibitors. Finally, we tested these nine hits in 6x6 combination matrices to precisely determine the optimal dosing with VAL.Currently, we are expanding our validation across additional ATLL cell lines and optimizing dosage schedules for in vivo testing on our established ATLL models to ensure synergistic effective.This research aims to identify novel targets that will sensitize resistant ATLL to epigenetic therapies. These findings may contribute to developing strategies to address drug resistance and offer additional treatment opportunities for this difficult-to-treat disease. Citation Format: Noorhan Ghanem, Carman K.M. Ip, Kit Tong, Mehran Bakhtiari, Michael Y. He, Aaron Schimmer, Robert Kridel. Drug screens identify new therapeutic targets that synergize with EZH1/2 inhibition in adult T-cell leukemia/lymphoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 4498.
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 | 0,000 | 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 | 0,001 |
| 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) | 0,000 | 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 ».