Leukemia inhibitory factor drives transcriptional programs that promote lipid accumulation and M2 polarization in macrophages
Bibliographic record
Abstract
Leukemia inhibitory factor, a member of the interleukin-6 cytokine family, plays a central role in homeostasis and disease. Interestingly, some of the pleiotropic effects of leukemia inhibitory factor have been attributed to the modulation of macrophage functions although the molecular underpinnings have not been explored at a genome-wide scale. Herein, we investigated leukemia inhibitory factor-driven transcriptional changes in murine bone marrow-derived macrophages by RNA sequencing. In silico analyses revealed a selective and time-dependent remodeling of macrophage gene expression programs associated with lipid metabolism and cell activation. Accordingly, a subset of leukemia inhibitory factor-upregulated transcripts related to cholesterol metabolism and lipid internalization was validated by real-time quantitative polymerase chain reaction. This was accompanied by a leukemia inhibitory factor-enhanced capacity for lipid accumulation in macrophages upon incubation with oxidized low-density lipoprotein. Mechanistically, leukemia inhibitory factor triggered the phosphorylation (Y705 and S727) and nuclear translocation of the transcription factor STAT3 in bone marrow-derived macrophages. Consistent with this, ingenuity pathway analysis identified STAT3 as an upstream regulator of a subset of transcripts, including Il4ra, in leukemia inhibitory factor-treated macrophages. Notably, leukemia inhibitory factor priming enhanced bone marrow-derived macrophage responses to interleukin-4-mediated M2 polarization (i.e. increased arginase activity and accumulation of transcripts encoding for M2 markers). Conversely, leukemia inhibitory factor stimulation had no significant effect in bone marrow-derived macrophage responses to M1-polarizing stimuli (interferon-γ and lipopolysaccharide). Thus, our study provides insight into the transcriptional landscape of leukemia inhibitory factor-treated macrophages, shedding light on its role in lipid metabolism and M2 polarization responses. A better understanding of the regulatory mechanisms governing leukemia inhibitory factor-driven changes might help informing novel therapeutic approaches aiming to reprogram macrophage phenotypes in diseased states (e.g. cancer, atherosclerosis, and infection).
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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".