Abstract PR-07: Optimally designed mRNA vaccine encoding tumor-specific antigens identified in a colorectal cancer model leads to complete tumor rejection in mice
Notice bibliographique
Résumé
Abstract mRNA vaccines can be designed to encode multiple epitopes of choice, which is a crucial advantage when aiming to include a broad coverage immune response. Upon translation, the cell machinery must process the vaccine-encoded poly-epitope protein to release individual peptides. This processing step is key in inducing an immune response toward selected epitopes, as efficient processing yields a higher amount of peptide available for MHC-I presentation. The efficiency of peptide processing is greatly influenced by the peptide surrounding context (i.e. the flanking amino acids in N-and C-terminal). Aberrantly expressed tumor-specific antigens (aeTSAs) are MHC-I-associated peptides (MAPs) resulting from cancer-specific epigenetic changes and splicing aberrations. In contrast to TSAs derived from mutated protein-coding exons, aeTSAs are highly shared by different tumors. Moreover, unlike commonly used tumor-associated antigens (TAAs), they are not expressed by normal healthy cells, which is pivotal for inducing strong CD8+ T cell responses. The present study aimed to determine whether RNA vaccines encoding aeTSAs would elicit protective anti-tumor responses against a colorectal cancer cell line model (MC38). We hypothesized that multiepitope mRNA vaccine efficacy would be improved if the mRNA construct was composed of minimal epitopes (here, cancer antigens) bordered by optimal (rather than natural) flanking sequences. Thus, we designed 2 vaccine constructs encoding 5 aeTSAs identified by mass spectrometry in MC38 tumor cells. The 2 constructs differ in the identity of the amino acids flanking the antigens (natural vs. substituted antigen flanking sequences). Mice were injected subcutaneously with MC38 cells on Day 0. Three mRNA vaccine doses were administered intravenously one week apart, starting at Day 4. Vaccination with our improved mRNA vaccine design showed a clear therapeutic effect. As opposed to the natural flanking sequences design resulting in delayed tumor growth, vaccination with the substituted flanking sequences design led to the complete elimination of tumors and the survival of all mice. Elispot and dextramer stainings revealed that at least 3 of the 5 MC38 aeTSAs were immunogenic and that the amplitude of antigen-specific CD8+ T cell responses was significantly higher in mice vaccinated with the substituted flanking sequences design. Our results confirm our hypothesis that highly proficient flanking regions have intrinsic benefits that can be carried over to different antigens. From a translational perspective, our work provides new insights into the therapeutic potential of optimally designed aeTSA-encoding mRNA vaccines for treating cancers. Citation Format: Marie-Pierre Hardy, Krystel Vincent, Gabriel Ouellet-Lavallée, Chantal Durette, Isabelle Caron, Joel Lanoix, Mathieu Courcelles, Jean-Philippe Laverdure, Pierre Thibault, Claude Perreault. Optimally designed mRNA vaccine encoding tumor-specific antigens identified in a colorectal cancer model leads to complete tumor rejection in mice [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor Immunology and Immunotherapy; 2024 Oct 18-21; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2024;12(10 Suppl):Abstract nr PR-07.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».