IRF3 Knockout Results in Partial or Complete Rejection of Murine Mesothelioma
Bibliographic record
Abstract
Background: Malignant pleural mesothelioma (MESO) has a poor prognosis despite aggressive treatment with surgery, radiation and chemotherapy, and novel therapeutic approaches are needed. IRF3 is a downstream molecule of the cGAS/STING signaling pathway, but its roles have not been investigated in MESO. Methods: Various murine mesothelioma cell lines were inoculated into wild type (WT) and IRF3 knockout (IRF3KO) mice to compare tumor growth. AE17-bearing mice were treated with local radiotherapy (LRT) to evaluate the effect on tumor growth, and immune cell infiltration was analyzed by flow cytometry 20 days after tumor inoculation. TCGA data were used to examine the relationship between mRNA expression of IRF3 and genes of the cGAS/STING signaling cascade on prognosis in MESO. Correlations between gene expression of IRF3, cGAS/STING signaling pathway, and immune checkpoints were analyzed in TCGA MESO and our scRNA-Seq data from MESO patients. Results: In mouse mesothelioma models, AK7, RN5 and ZiP3 were completely rejected in IRF3KO mice 20 days after the tumor challenge. AE17tumor volume was slightly larger than WT mice around day 10 before shrinking and becoming significantly smaller than WT mice on day 20. LRT accelerated tumor shrinkage of AE17 tumors in IRF3KO mice. Compared with WT mice, the number of macrophages infiltrating the tumor of IRF3KO mice was significantly reduced, and CD4+ T cells and CD8+IFNγ+ T cells were significantly increased. TCGA data showed that IRF3 expression was an unfavorable prognostic factor in MESO patients. IRF3 expression, the cGAS/STING signaling pathway, and immune checkpoints were positively correlated. Conclusion: IRF3 could play a critical role in the tumor immune microenvironment of MESO.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".