Humanization and Pre-Clinical Validation of an Anti-HLA-A*02
Notice bibliographique
Résumé
Introduction Achieving transplant tolerance with regulatory T cell (Treg) adoptive immunotherapy is currently under investigation as a therapy to reduce graft rejection and improve long-term outcomes. Traditional approaches involve the of polyclonal Tregs, which are known to be less potent than antigen-specific cells, or antigen-expanded Tregs, which have several technical limitations. We and others have developed an alternate approach to generate antigen-specific Tregs by expressing a chimeric antigen receptor specific for HLA-A*02:01 (A2-CAR). In our initial studies the antigen-binding region (scFV) of the A2-CAR was derived from the mouse BB7.2 hybridoma, which, due to the high degree of homology between HLA molecules, has been reported to bind to HLA-A alleles in addition to *02:01. Here we sought to systematically define the antigen-specificity of the A2-CAR as well as humanize the sequence to minimize the risk of immunogenicity. Methods We designed 20 humanized versions of the A2-CAR and systematically tested them to determine which were highly expressed on the surface of human Tregs and capable of mediating A2-stimulated activation, expansion, and suppression. We also developed a novel method to systematically, and comprehensively test HLA-allele specificity. Results Of the 20 humanized A2-CARs, 10 were expressed on Tregs and retained A*02:01 binding capacity. We used a series of functional screens to define which of these 10 A2-CARs most effectively stimulated Treg activation, proliferation and proliferation. We then took advantage of the Panel Reactive Antibody (PRA) assay (One Lambda) and created a new method to test CAR-expressing Tregs to bind to specific HLA-alleles. We found that the majority of the humanized A2-CARs had a significantly reduced reactivity to binding to alleles other than A*02:01. We also tested the biological relevance of HLA cross reactivity by stimulating A2-CAR expressing Tregs with cell lines expressing HLA alleles that were or were not found to be cross reactive using the PRA assay. Ultimately, six humanized anti-A2 CARs showed the desired properties, with an ability to activate Tregs, bind to HLA-A2 but not to a comprehensive panel of other common A or B alleles. The potent ability of one of these variants to suppress rejection was confirmed in a humanized model of xenogeneic graft-versus-host disease. Conclusion We successfully developed a series of humanized A2-CARs which were comprehensively screened for desirable properties to generate antigen-specific Tregs. This body of pre-clinical data will support the development of a first-in-human clinical trial of A2-CAR-engineered Tregs to prevent organ allograft rejection.
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 | 0,003 | 0,001 |
| 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 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
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 ».