Abstract 1694: Combination of inhibitors of RAD51 and FLT-3 and other tyrosine kinase inhibitors synergistically inhibits proliferation of cultured human leukemia cell lines
Bibliographic record
Abstract
Abstract Ten to 20% of acute myeloid leukemias (AML) are driven by a mutation in FMS-like tyrosine kinase 3 (FLT3), a membrane-based ligand-inducible signal transducer. These FLT-3-mutant AMLs have a poor prognosis and high rate of relapse in spite of the use of inhibitors that specifically target this protein (Cancer Sci. 2019;111: 312-322. doi: 10.1111/cas.14274). However, FLT-3 remains an attractive therapeutic target if new iterations of these drugs are able to circumvent acquired mechanisms of resistance as well as target the wild-type (wt) FLT-3 protein to inhibit tumor growth. Also, chronic myeloid leukemia (CML) in blast crisis continues to have a poor prognosis. IBR2, an inhibitor of the DNA repair protein RAD51, was previously demonstrated to enhance the antiproliferative activity of imatinib against the CML blastoid cell line K562 (EMBO Mol Med 5: 353-365, 2013. DOI 10.1002/emmm.201201760). In our studies, IBR2 enhanced the antiproliferative activity of regorafenib, an inhibitor of multiple tyrosine kinases, in a concentration-dependent manner by up to 80% against K562 cells (J Pharmacol Expt Ther, 364: 46-54, 2018. doi.org/10.1124/jpet.117.241661). JKYN-1-mesylate, a derivative of IBR2, works synergistically with numerous anticancer agents to inhibit proliferation of cell lines derived from a broad range of tumor types (Proc Amer Assoc Cancer Res, 63: Abst. 346, 2022). In an effort to develop a potential drug combination to treat acute leukemias with either mutated or wt FLT-3 we tested combinations of JKYN-1-mesylate and FLT-3 inhibitors against FLT-3-wt HL-60 and FLT-3-mutant MV-4-11 AML cell lines. MV-4-11 cells were 100- to 1000-fold more sensitive to quizartinib and gilteritinib than HL-60. Proliferation of both cell lines (4 days, alamarBlue™ assay) was inhibited by monotherapy JKYN-1-mesylate with IC50 values in the range of 3 to 5 μM. The combination of JKYN-1-mesylate and quizartinib synergistically inhibited proliferation of HL-60 cells with an apparent decrease in the IC50 value of quizartinib by up to 80%. However, inhibition by the combination of JKYN-1-mesylate and gilteritinib was only additive in this FLT-3-wt cell line. As well, JKYN-1-mesylate was at best additive with quizartinib or gilteritinib against FLT-3-mutant MV-4-11. These findings suggest that: (1) the combination of quizartinib and a RAD51-inhibitor could be a useful treatment against FLT-3-wt AML; (2) quizartinib and gilteritinib may not act in exactly the same way against the FLT-3 target or other related targets; (3) novel combinations of a RAD51 inhibitor with non-traditional treatments for CML may provide a potential improvement in outcome for CML blast crisis; (4) RAD51 inhibitors may be active as monotherapy in myeloid leukemias. The combination of JKYN-1-mesylate with FLT-3 inhibitors under current development is being tested. Citation Format: Mark D. Vincent, Peter Ferguson, Morgan Black, Jenny Ho, James Koropatnick. Combination of inhibitors of RAD51 and FLT-3 and other tyrosine kinase inhibitors synergistically inhibits proliferation of cultured human leukemia cell lines [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 1694.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".