Therapy-Induced MHC I Ligands Shape Neo-Antitumor CD8 T Cell Responses during Oncolytic Virus-Based Cancer Immunotherapy
Bibliographic record
Abstract
Oncolytic viruses (OVs), known for their cancer-killing characteristics, also overturn tumor-associated defects in antigen presentation through the MHC class I pathway and induce protective neo-antitumor CD8 T cell responses. Nonetheless, whether OVs shape the tumor MHC-I ligandome remains unknown. Here, we investigated if an OV induces the presentation of novel MHC I-bound tumor antigens (termed tumor MHC-I ligands). Using comparative mass spectrometry (MS)-based MHC-I ligandomics, we determined differential tumor MHC-I ligand expression following treatment with oncolytic reovirus in a murine ovarian cancer model. In vitro, we found that reovirus changes the tumor ligandome of cancer cells. Concurrent multiplexed quantitative proteomics revealed that the reovirus-induced changes in tumor MHC-I ligand presentation were mostly independent of their source proteins. In an in vivo model, tumor MHC-I ligands induced by reovirus were detectable not only in tumor tissues but also the spleens (a source of antigen-presenting cells) of tumor-bearing mice. Most importantly, therapy-induced MHC-I ligands stimulated antigen-specific IFNγ responses in antitumor CD8 T cells from mice treated with reovirus. These data show that therapy-induced MHC-I ligands may shape underlying neo-antitumor CD8 T cell responses. As such, they should be considered in strategies promoting the efficacy of OV-based cancer immunotherapies.
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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 | 0.004 | 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 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".