METTL3-mediated m6A methylation regulates ovarian cancer progression by recruiting myeloid-derived suppressor cells
Bibliographic record
Abstract
BACKGROUND: Ovarian cancer (OC) typically develops an immunosuppressive microenvironment by funtional changes of host immune cells. Dysregulated m6A level is associated with cancer progression via the intrinsic oncogenic pathways. However, the role of m6A in regulating host immune cell function during anti-tumor immunity needs comprehensive analysis. This study aimed to investigate the role of METTL3, a catalytic subunit of the methyltransferase complex, in regulating host immune cell response against OC. METHODS: In this study, myeloid-specific Mettl3 gene knockout (Mettl3-cKO) mice were bred using the Cre-LoxP system. Intraperitoneally injection of ID8 cells was used as a syngeneic OC model. Furthermore, the compositions of immune cell populations were analyzed by flow cytometry and single-cell sequencing. Moreover, chemokines and cytokines secretion were assessed using ELISA. Lastly, the role of METTL3 in regulating IL-1β secretion and inflammasome activation in bone marrow-derived macrophages cocultured with ID8 cells was specified by ELISA and immunoblotting. RESULTS: It was revealed that OC cell growth was enhanced in Mettl3-cKO mice. Furthermore, a shift of decreased M1 to increased M2 macrophage polarization was observed during OC progression. Moreover, Mettl3 depletion in myeloid lineage cells increased secretion of CCL2 and CXCL2 in peritoneal lavage fluild. Interestingly, Mettl3 deficiency enhanced IL-1β secretion induced by viable ID8 cells independent of inflammasome activation and cell death. Therefore, OC cells in tumor-bearing mice trigger a slight inflammatory response with a low-to-moderate secretion of pro-inflammatory cytokines and chemokines. CONCLUSION: This study provides new insights into METTL3-mediated m6A methylation, which regulates host immune response against OC.
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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) | 0.002 | 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 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".