Abstract 953: Oncolytic viruses as in situ personalized tumor vaccines for durable efficacy
Bibliographic record
Abstract
Tumor vaccines have shown clinical promise in treating certain cancers. However, their long-term effectiveness is often hindered by two major challenges: 1. The immune-suppressive tumor microenvironment (TME). 2. Selective targeting of antigen-positive tumor cells, which can lead to the expansion of antigen-negative cells and eventual tumor relapse. To address these challenges, we explored a combination approach using mRNA tumor vaccines and oncolytic virotherapy in HPV and HER2 mouse tumor models. Our findings reveal that while mRNA vaccines effectively eradicate antigen-positive tumors and suppress tumor growth, resistance quickly emerges, enabling tumors to evade the vaccine's effects. When mRNA vaccination was followed by intratumoral administration of an oncolytic virus—either with or without HPV or HER2 antigen expression—a significantly more durable anti-tumor response was achieved in both models. The oncolytic virus initiated broad tumor antigen presentation by lysing tumor cells, releasing diverse tumor-associated antigens, and increasing the overall antigenic load within the tumor. Furthermore, the lytic activity of the virus reprogrammed the TME, transforming it from an immune-suppressive environment into one more favorable for anti-tumor immune responses. This combination therapy elicited a potent local immune response, leveraging enhanced antigen presentation by the virus. The modified TME allowed the systemic immune response generated by the mRNA vaccine to penetrate and act effectively within the tumor. Additionally, the treatment induced systemic antigen-specific T-cell responses, and treated animals developed resistance to subsequent tumor challenges, demonstrating the establishment of immune memory. Our study highlights the unique role of oncolytic virotherapy as an intratumoral "boost" mechanism. By lysing tumor cells, oncolytic viruses amplify the range of tumor antigens presented to the immune system and reshape the TME to support robust immune activity. This synergy between mRNA vaccination and oncolytic virotherapy—when employed in a prime-boost regimen—produces a powerful and durable anti-tumor immune response that is both localized and systemically protective against recurrence. In conclusion, this research underscores the potential of combining mRNA tumor vaccines with oncolytic virotherapy to overcome immune evasion mechanisms, enhance tumor antigen presentation, and reprogram the TME, providing a promising strategy for achieving long-lasting anti-tumor immunity. Citation Format: William WEI GUO Jia. Oncolytic viruses as in situ personalized tumor vaccines for durable efficacy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 953.
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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 | 0.001 | 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".