Epigenetic Scarring Leads to Irreversible NK Cell Dysfunction in Myeloid Malignancies
Bibliographic record
Abstract
Myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML) belong to the same spectrum of myeloid malignancies and have extremely poor outcomes in the relapsed/refractory setting. Despite advances in the understanding of the pathogenesis and molecular mechanisms of these disorders, and incremental improvements in treatment regimens, patients with MDS and AML often relapse and fail to achieve cure. These and other factors underscore the urgent need for new therapeutic alternatives that will improve the clinical outcomes of these patients. Immunotherapy using checkpoint molecule inhibitors and adoptive cell therapy using autologous immune effector cells have been mostly unsuccessful in patients with MDS and AML. This could be due to the immunosuppressive tumor microenvironment in the bone marrow niche or to intrinsic dysfunction in the immune effector cells of these patients. Natural killer (NK) cells are innate lymphocytes that play an important role in cancer immune surveillance and have distinct advantages over T cells as candidates for immunotherapy. Myeloid blasts are inherently susceptible to NK cell-mediated killing as they express many of the ligands recognized by NK cell activating receptors. However, malignant myeloid blasts are capable of adapting and developing defense mechanisms that allow them to evade NK cell-mediated cytotoxicity. Little is known about the mechanisms of NK cell immune evasion developed by myeloid blasts. Here, we show that NK cells from patients with myeloid malignancies display a global dysfunction with severely impaired secretory function and killing capacity. Single cell RNAseq and mass cytometry experiments revealed that these NK cells from MDS and AML patients display an exhausted phenotype at the transcriptomic and proteomic levels. We also show that these NK cells have an altered metabolism compared with age matched healthy control NK cells. We show that this dysfunction is mediated by a crosstalk between myeloid blasts and NK cells and cell-cell contact dependent release of transforming growth factor beta (TGF-β). This crosstalk leads to a profound epigenetic reprogramming of NK cells driven by transcription factors known to mediate exhaustion and immune suppression. Myeloid blast-induced NK dysfunction and epigenetic state of exhaustion can be prevented by pharmacologically inhibiting the TGF-β pathway or knockout of TGFBR2 in NK cells. However, our data reveal that once this dysfunction occurs it is irreversible owing to epigenetic scarring driven by the transcription factor BATF. In fact, we show that TGF-β induces the expression of BATF in NK cells, which in turn mediates a gene regulatory program leading to NK cell dysfunction by driving the expression of exhaustion and inhibitory genes (e.g. HAVCR2, ENTPD1, CTLA4, TGFBR2). Collectively, our findings reveal a novel mechanism of NK cell immune evasion manifested by stable epigenetic rewiring and inactivation of NK cells by myeloid blasts. Our data support the use of allogeneic sources for adoptive NK cell therapy in combination with strategies aiming at preventing immune suppression to treat myeloid malignancies rather than therapies aiming at reversing or rescuing the function of autologous NK cells.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".