Abstract B004: Neoantigen adenoviral cancer vaccine generates improved CD8+ T-cell responses compared to adjuvanted peptide vaccine
Bibliographic record
Abstract
Abstract Development of large, functional CD8+ T cell responses is crucial for successful cancer vaccine therapeutics. Neoantigens have demonstrated their potential as cancer vaccine immunogens, but improvements in delivery method are still necessary. In this work, we characterized five candidate Adenovirus Serotype 26 (Ad26) cancer vaccines for prophylactic efficacy in the MC-38 cancer model. All five single shot vaccines generated cellular immune responses at a higher level than prime boost peptide vaccination. The vaccines generated varying degrees of protection against tumor growth. The best Ad26 vaccine candidates showed improved protection compared to long synthetic peptide vaccines containing the same immunogens, the current standard in the field. Ad26 expressing seven neoantigens conjugated to the Herpes Viral Protein 22 (VP22) (Ad26.VP22.7Epi) was found to reduce tumor growth the most. Ad26.VP227Epi was compared to peptide vaccination in immune recall post challenge studies, in both the spleen and the tumor. Both Ad26.VP22.7Epi and Peptide showed a clear recall response after challenge in the spleen. This response was primarily focused on the Adpgk neoantigen but Ad26.VP22.7Epi additionally induced responses to the Irgq neoantigen while the peptide vaccine had stronger responses against the Reps1 neoantigen. The Ad26.VP227Epi vaccine generated increased numbers of infiltrating CD8+ T-cells, IFN+ CD8+ T-cells, and CD107a+ CD8+ T-cells, which all correlated with reduced tumor growth. We used single cell RNA-seq (scRNA-seq) to characterize tumor infiltrating lymphocyte populations (defined as CD45+) generated by the two platforms. We found that both Ad26.VP22.7Epi and Peptide induced higher numbers of infiltrating CD8+ T-cells within the tumor as compared to Sham. Single-cell analysis also showed higher numbers of tumor infiltrating Tregs in peptide vaccinated mice. Higher numbers of CD8+ T-cells correlated with protection as expected but interestingly increased numbers of Tregs positively correlated with tumor volume only among vaccinated mice, which could further explain differences between Ad vector and peptide vaccination. Differential gene expression analysis of CD8+ T-cells showed an upregulation of Th1 pathways and general T cell activation when comparing Ad vector vaccinated mice to peptide vaccinated. Peptide vaccinated CD8+ T-cells showed upregulation in the IL-10 pathway, potentially caused by an increased Tregs. Further investigation of these differences among CD8+ T cell and Treg populations could further elucidate potential mechanisms explaining the differences in platform efficacy. Citation Format: Gabriel Dagotto, Alessandro Colarusso, Robert Patio, David Li, Tochi Anioke, Victoria Giffin, Malika Aid, Dan Barouch. Neoantigen adenoviral cancer vaccine generates improved CD8+ T-cell responses compared to adjuvanted peptide vaccine [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor Immunology and Immunotherapy; 2023 Oct 1-4; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Immunol Res 2023;11(12 Suppl):Abstract nr B004.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".