Novel Therapeutics That Can Target and Eradicate Leukemic Stem Cells in Acute Myeloid Leukemia: Investigating FDA-Approved Anti-Inflammatory Compounds
Bibliographic record
Abstract
Acute myeloid leukemia (AML) is an aggressive form of blood cancer defined by the uncontrolled proliferation of immature myeloblast cells in the blood and bone marrow, leading to hematopoietic failure. The 5-year survival rate is 28% in patients aged 20 years and older and 64% in patients aged 19 years and younger (SEER 2019). A large portion of these patients succumb to the disease partially due to the chemo-resistant nature of leukemic stem cells (LSCs). Hence, novel therapies targeting unique LSC biology that spare hematopoietic stem cells (HSCs) are needed to eliminate and avoid reoccurrence of this disease. We had previously identified FDA-approved anti-inflammatory glucocorticoids mometasone, halcinonide, and budesonide as compounds that induce terminal differentiation of the LSC (CD34+CD38-) and progenitor cell (CD34+CD38+) populations to leukemic blast cells (CD15+CD34-) in refractory human AML (Laverdière & Boileau et al., Blood Can. J. 2018). Following the paradigm of successful differentiation treatment in AML (acute promyelocytic leukemia with all-trans retinoic acid), the effects and mechanism of action of the glucocorticoids on LSCs need to be further investigated for other AML subtypes. Furthermore, dexamethasone, a glucocorticoid currently used to successfully treat acute lymphoblastic leukemia (ALL), is being studied in a Phase II clinical trial for induction and post-remission chemotherapy in older patients with de novo or therapy-related AML (clinicalTrials.gov, NCT03609060). To identify the subtypes of AML that are sensitive to steroid-induced LSC differentiation, we began by screening a panel of cell lines (F36P, MOLM-13, Kasumi-6, Kasumi-1 and K562) and observed that only Kasumi-1, a pediatric leukemia carrying the t(8;21) mutation leading to the fused RUNX1-RUNX1T1 gene, was responsive to glucocorticoid treatment, although without differentiation. This is consistent with the finding of Simon et al. who observed a loss of bulk AML cells in RUNX1 AML samples following dexamethasone treatment (Simon et al., Clin Cancer Res. 2017). However, we observed expansion of bulk cells following differentiation of LSCs in primary AML, indicating different mechanisms of steroid response in different samples: differentiation of LSCs or overall loss of AML cells. We will further investigate these compounds in a panel of 10 genetically defined primary AML samples to classify which oncogenetic drivers or subtypes of AML are linked to sensitivity to the three glucocorticoids, including which drive cell death vs LSC differentiation. We will perform ex vivo and in vivo studies of the glucocorticoids to assess the extent of engraftment in treated versus DMSO treated samples. This additional data will be presented at the annual meeting. In addition, to explore the mechanism of action of these steroids in AML, we investigated the roles of the cytokines interleukin-3 (IL-3), interleukin-6 (IL-6), stem cell factor (SCF), granulocyte colony stimulating factor (GCSF), thrombopoietin (TPO) and FMS-like tyrosine kinase 3 ligand (FLT3L), used to culture AML, on the differentiation effects induced by the glucocorticoids. We observed that only FLT3L was required for the complete differentiation of LSCs. In summary, we have observed that the three glucocorticoid steroids (mometasone, halcinonide, and budesonide), as well as dexamethasone to a lesser extent, can induce two different responses in a sample-dependent manner: terminal differentiation of LSCs or overall cell loss. We have also observed that the differentiation response requires FLT3L for maturation of the AML cells. Our current studies involve in vivo and genomic assays to determine the effect on functional LSCs and the genetic markers of sensitivity and we will present these results. Disclosures Minden: Trillium Therapetuics: Other: licensing agreement.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".