mRNA vaccine with unmodified uridine induces robust type I interferon-dependent anti-tumor immunity in a melanoma model
Bibliographic record
Abstract
An mRNA with unmodified nucleosides induces type I interferons (IFN-I) through the stimulation of innate immune sensors. Whether IFN-I induced by mRNA vaccine is crucial for anti-tumor immune response remains to be elucidated. In this study, we investigated the immunogenicity and anti-tumor responses of mRNA encoding tumor antigens with different degrees of N1-methylpseudouridine (m1Ψ) modification in B16 melanoma model. Our results demonstrated that ovalbumin (OVA) encoding mRNA formulated in a lipid nanoparticle (OVA-LNP) induced substantial IFN-I production and the maturation of dendritic cells (DCs) with negative correlation with increasing percentages of m1Ψ modification. In B16-OVA murine melanoma model, unmodified OVA-LNP significantly reduced tumor growth and prolonged survival, compared to OVA-LNP with m1Ψ modification. This robust anti-tumor effect correlated with the increase in intratumoral CD40 + DCs and the frequency of granzyme B + /IFN-γ + /TNF-α + polyfunctional OVA peptide-specific CD8 + T cells. Blocking type I IFN receptor completely reversed the anti-tumor immunity of unmodified mRNA-OVA reflected in a significant decrease in OVA-specific IFN-γ secreting T cells and enrichment of PD-1 + tumor-infiltrating T cells. The robust anti-tumor effect of unmodified OVA-LNP was also observed in the lung metastatic tumor model. Finally, this mRNA vaccine was tested using B16 melanoma neoantigens ( Pbk - Actn4 ) which resulted in delayed tumor growth. Taken together, our findings demonstrated that an unmodified mRNA vaccine induces IFN-I production or the downstream signaling cascades which plays a crucial role in inducing robust anti-tumor T cell response for controlling tumor growth and metastasis.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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 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".