LSD1 Inhibition Enhances Antigen Presentation and Co-Stimulation in AML to Promote T Cell-Mediated Anti-Leukemia Immune Responses
Bibliographic record
Abstract
Allogeneic hematopoietic stem cell transplantation (allo-HSCT) can provide a curative treatment option for acute myeloid leukemia (AML). Donor T cells play an important role in the curative potential of allo-HSCT by recognizing and eliminating residual leukemic cells, inducing the desirable graft-versus-leukemia (GVL) effect. Evading from this effect of donor T cell immune surveillance through the downregulation of human leukocyte antigen class II (HLA-II) molecules has been shown to contribute to AML relapse after allo-HSCT. Lysine-specific demethylase 1 (LSD1) is an emerging epigenetic therapeutic target in AML due to its role in regulating myeloid differentiation pathways. We hypothesized that LSD1 inhibition has the potential to enhance anti-leukemic immune responses by differentiating AML cells and inducing the acquisition of markers typical for antigen-presenting cells. We have studied these effects by treating human AML cell lines with the LSD1 inhibitor bomedemstat and investigated the expression of antigen-presenting molecules by flow cytometry and quantitative PCR (qPCR). At a concentration of 100 nM, bomedemstat upregulated the expression of CIITA by a log2 fold change of 2.23 ± 0.68 (p < 0.01) in OCI-AML3, 2.17 ± 0.28 (p < 0.01) in HL60 and 1.80 ± 0.67 (p < 0.05) in MOLM-13. To assess if the observed upregulation of CIITA can lead to a re-expression of HLA-DR in these HLA-DR negative cell lines, we then treated these cell lines with 100 nM of bomedemstat with additional IFN-γ stimulation. Expression of HLA-DR and the co-stimulatory molecule CD86 was determined by flow cytometry. Bomedemstat increased the expression of HLA-DR and CD86 across all three cell lines leading to the generation of 26.63 ± 3.07% (p < 0.0001) HLA-DR +/CD86 + cells in OCI-AML3, 4.19 ± 1.68% (p < 0.001) HLA-DR +/CD86 + cells in HL-60 and 14.67 ± 2.03% (p < 0.001) HLA-DR +/CD86 + cells in MOLM-13. We further assessed the effects of bomedemstat treatment on cytokine production by qPCR. Notably, bomedemstat treatment increased the expression of CXCL-10 by a log2 fold change of 2.59 ± 0.66 (p < 0.001) in MOLM-13 and 4.12 ± 0.88 (p < 0.001) in HL-60 at 100 nM concentration. The upregulation of CXCL-10 was also validated using bead-based ELISA assays. To investigate the molecular mechanism of the observed concomitant upregulation of MHC-II molecules and CD86, we then used murine myeloid progenitor cells transformed by overexpression of Hoxa9 and Meis1 (H9M) or MN1. In H9M-transformed cells, bomedemstat concurrently upregulated MHC-II (I-A/I-E) and CD86 even in the absence of IFN-γ stimulation, leading to an increase in MHC-II +/CD86 + cells from 2.52 ± 1.22% at baseline to 29.95 ± 14.11 (p < 0.05). This effect was not observed in MN1-transformed cells. H9M-transformed progenitor cells from Irf8 knockout mice (H9M- Irf8-KO) did not show any upregulation of MHC-II, pointing towards a role for Irf8 in this process. To interrogate whether the concurrent upregulation of MHC-II and CD86 can enhance CD4 + T cell activation, we used ovalbumin-expressing H9M-transformed cells that were co-cultured with OT-II T cells after bomedemstat treatment. We could show that bomedemstat-treatment enhanced the ability of H9M-OVA cells to activate T cells as demonstrated by an enhanced expression of the T cell activation markers CD25 and CD69. Furthermore, bomedemstat also increased the immune killing of OVA-peptide pulsed H9M cells at an effector-to-target (E:T) ratio of 1:1 from 1.12 ± 4.01 to 19.70 ± 6.20% (p < 0.01). It also enhanced the killing of OVA-expressing H9M cells from 5.80 ± 2.95% to 17.70 ± 3.16% (p < 0.05). No significant killing effect was observed for MN1 cells. In conclusion, we demonstrate both phenotypically and functionally that LSD1 inhibition by bomedemstat can enhance the immunogenicity of human and murine AML models. These findings point towards a potential role of LSD1 inhibition as a maintenance therapy after allo-HSCT.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".