Abstract 1520: Targetable immunogenic tumor specific antigens can be identified in non-coding regions of the genome
Notice bibliographique
Résumé
Abstract CD8+ cytotoxic T cells are the main mediators of immune responses during cancer immunotherapy. Effective T cell functionality depends on the specific interaction with major histocompatibility (MHC) class I-bound peptide antigens. Significant efforts are being dedicated to the identification of novel tumor specific antigens (TSAs), investigating not only the known proteome, but also non-coding regions of the genome, that would allow for improved discrimination between cancer cells and healthy tissues. Through extensive comparisons of tumor and healthy tissues at the transcriptional and MHC-presented peptidome levels, TSAs were identified that derived from the translation in canonical and non-canonical reading frames of non-mutated non-coding genomic regions, including 5'- and 3'-untranslated regions (UTRs), introns and intergenic regions. A remarkable feature of these TSAs is that they are shared among patients and solid tumor types, thus representing ideal targets for cancer immunotherapies, including vaccines and adoptive cell therapies. To identify TSAs that can elicit T cell responses, a high throughput screening procedure was used to investigate the immunogenicity of 47 TSAs in the context of five common HLA types. Constructs harboring the TSA sequences were developed and transfected into HLA-matched monocyte-derived dendritic cells (mDCs) that were used to stimulate autologous CD8+ T cells. TSA-reactive T cells were enriched upon stimulation with antigen-positive and -negative cells using the T cell activation marker CD137 and sorted as single cells. Reactivity of individual T cell clones towards specific TSAs was confirmed by measuring cytokine release upon co-culture with HLA-matched TSA-positive and negative cell lines. Ten immunogenic TSAs were identified with this procedure, including at least one immunogenic TSA for each of the five analyzed HLAs. For some of these antigens, specific T cells were found in multiple healthy donors. The identified immunogenic TSAs derive from a variety of non-coding regions, such as introns, 5'-UTRs and non-coding RNAs. The T cell receptor (TCR) α and β chain sequences of TSA-reactive T cell clones were identified by NGS, engineered into a retroviral expression construct and transduced into CD8+ T cells. The reactivity of TCR-transgenic T cells against TSA-positive target cells was confirmed by recognition of TSA-peptide-loaded cell lines and target cells internally processing and presenting the TSAs. In conclusion, our high throughput screening approach successfully detected immunogenic TSAs. Furthermore, it can be used for the identification of TSA-reactive TCRs, thus representing a key tool in the development of novel TCR-based cancer immunotherapies targeting this novel class of TSAs. Citation Format: Tiziana Franceschetti, Qingchuan Zhao, Krystel Vincent, Claude Perreault, Slavoljub Milosevic, Daniel Sommermeyer. Targetable immunogenic tumor specific antigens can be identified in non-coding regions of the genome [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1520.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| 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 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,002 |
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 source (Gemma direct ou Codex distillé), 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 ».