Inhibition of histone H3K27 demethylases selectively modulates inflammatory phenotypes of natural killer cells
Bibliographic record
Abstract
Natural killer (NK) cells are innate lymphocytes, important in immune surveillance and elimination of stressed, transformed, or virus-infected cells. They critically shape the inflammatory cytokine environment to orchestrate interactions of cells of the innate and adaptive immune systems. Some studies have reported that NK cell activation and cytokine secretion are controlled epigenetically but have yielded only limited insight into the mechanisms. Using chemical screening with small-molecule inhibitors of chromatin methylation and acetylation, further validated by knockdown approaches, we here identified Jumonji-type histone H3K27 demethylases as key regulators of cytokine production in human NK cell subsets. The prototypic JMJD3/UTX (Jumonji domain-containing protein 3) H3K27 demethylase inhibitor GSK-J4 increased global levels of the repressive H3K27me3 mark around transcription start sites of effector cytokine genes. Moreover, GSK-J4 reduced IFN-γ, TNFα, granulocyte-macrophage colony-stimulating factor (GM-CSF), and interleukin-10 levels in cytokine-stimulated NK cells while sparing their cytotoxic killing activity against cancer cells. The anti-inflammatory effect of GSK-J4 in NK cell subsets, isolated from peripheral blood or tissue from individuals with rheumatoid arthritis (RA), coupled with an inhibitory effect on formation of bone-resorbing osteoclasts, suggested that histone demethylase inhibition has broad utility for modulating immune and inflammatory responses. Overall, our results indicate that H3K27me3 is a dynamic and important epigenetic modification during NK cell activation and that JMJD3/UTX-driven H3K27 demethylation is critical for NK cell function.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.002 | 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".