Abstract A042: Quantitative multiplex immunoprecipitation reveals distinct protein interaction networks responsible for discrepant <i>in vivo</i> activity exhibited by two second generation CD22-targeted chimeric antigen receptors
Notice bibliographique
Résumé
Abstract The Pediatric Leukemia Adoptive Therapy (PLAT) trials at Seattle Children’s Hospital have pioneered the use of chimeric antigen receptor (CAR) T cell (CAR-T) therapies in pediatric patients with B cell Acute Lymphoblastic Leukemia. The landmark PLAT-02 trial (n=45), utilizing a second-generation CD19-directed CAR, observed a 93% remission rate following CAR-T infusion. However, approximately half of these subjects relapsed within one year and nearly a third of those tumors no longer expressed the CD19 target. The PLAT-04 trial (n=4) was subsequently conceived with a second-generation CAR (SCRI-C22v1) engineered to target CD22, an alternative antigen expressed on the B cell surface. Despite promising preclinical data, SCRI-C22v1 failed to generate anti-leukemic activity in all four subjects and the trial was halted. In response, a different second-generation CD22-directed CAR (SCRI-C22v2) was engineered, replacing the CD28 transmembrane domain and IgG4 hinge domain in SCRI-C22v1 with a continuous CD8 hinge and transmembrane domain while retaining identical 4-1BB and CD3ζ intracellular signaling domains. The modified SCRI-C22v2 displayed improved anti-tumor activity in preclinical models and was ultimately tested in patients in the PLAT-07 trial (n=4), where it exhibited strong in vivo expansion and persistence while inducing complete remission after 1 month in all four subjects. To investigate the molecular signaling responsible for clinical differences observed between SCRI-C22v1 and SCRI-C22v2, we applied an emerging proteomic technology, Quantitative Multiplex Immunoprecipitation (QMI), that captures medium-throughput quantitative data about fold changes in protein interaction networks downstream of the CAR. CAR-T products from healthy donors expressing either SCRI-C22v1 or SCRI-C22v2 were stimulated with fixed K562 cells expressing CD22 and protein interaction networks were profiled with QMI, revealing distinct differences in signal transduction downstream of the CAR. Contrary to expectation, it was the ineffective SCRI-C22v1 that exhibited significantly enhanced signalosome formation, engaging more strongly than SCRI-C22v2 with both the classical CD3ζ-ZAP70-LAT-SLP76 pathway as well as the non-classical TRAF pathway. Interestingly, the clinically successful SCRI-C22v2 demonstrated stronger baseline engagement with inhibitory molecules that attenuate canonical TCR signaling such as SHP2 and UBASH3A, suggesting regulatory control of CAR signaling is crucial for optimal clinical responses. Since the CAR is a synthetic receptor, it should be possible to bioengineer optimized signal transduction to some extent, and our group continues to work towards identifying an optimized QMI signature that can be used as a CAR-tune network for the rational design of more effective CAR-T therapies. Citation Format: Eric Bueter, Corinne Summers, Isabella Draper, Joshua Gustafson, Stephen EP Smith, Kamila Gwiazda, Julie Park, Colleen Annesley, Rebecca Gardner, Michael Jensen. Quantitative multiplex immunoprecipitation reveals distinct protein interaction networks responsible for discrepant in vivo activity exhibited by two second generation CD22-targeted chimeric antigen receptors [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 A042.
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 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 | 0,004 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».