Abstract 4498: Drug screens identify new therapeutic targets that synergize with EZH1/2 inhibition in adult T-cell leukemia/lymphoma
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".