283 Functional profiling of CAR T cells using high-dimensional CyTOF: integrating cytokine, transcription factor and immune checkpoint marker signatures
Notice bibliographique
Résumé
Background Adoptive immunotherapy using chimeric antigen receptor (CAR) T cells is a revolutionary treatment in cancer therapy. CAR T therapy has achieved remarkable success in hematological B cell malignancies. However, it has faced significant challenges in solid tumors due to various factors, such as complex tumor microenvironments, restricted trafficking, impersistent antitumor activity and toxicities. A better understanding of CAR T biology will accelerate development of CAR T therapies with improved antitumor efficacy, durability and decreased toxicities.High-parameter cytometry is a powerful tool to functionally characterize CAR T cells at multiple stages of clinical development, from product characterization during manufacturing to longitudinal evaluation of the infused product in patients. Fluorescence-based cytometry faces significant challenges with signal overlap and autofluorescence, limiting sensitivity and the number of targets detected in CAR T cells. Consequently, rare cell populations and functional readouts of CAR T cells are difficult to resolve. CyTOF™ technology overcomes these limitations with low signal spillover and absence of autofluorescence. To minimize technical variation, metal-tagged antibody cocktails and stained cell samples can be frozen for later use and acquisition, enabling a streamlined and flexible workflow in clinical research. Here, we present a 40-plus-marker CyTOF panel to simultaneously analyze phenotypic and functional protein expression in CAR T cells from in vitro co-culture with tumor cells.Methods CD19-targeted CAR T cells were expanded in vitro and co-cultured with Nalm6 cells at an E:T (effector cell: target cell) ratio of 1:3 for 2–4 days. A high-parameter CyTOF panel including 43 surface, cytoplasmic and nuclear markers was used to stain CAR T cells. The co-culture samples collected at different time points were stained using a pre-aliquoted frozen antibody cocktail following surface and intracellular (simultaneous cytoplasmic and nuclear targets) staining procedures. Stained samples were frozen and simultaneously acquired on a CyTOF XT system later.Results The cytotoxicity, activation, proliferation, differentiation and exhaustion of CAR T cells were evaluated. Comprehensive profiling revealed that CAR T cells became activated, proliferated and produced cytokines in in vitro co-culture with tumor cells and exhibited an exhaustive-like Treg phenotype at the end of a four-day co-culture. A diverse polyfunctional antitumor signature in the CD8 TEMRA cell subset was discovered during the co-culture.Conclusions Overall, we demonstrate that the high-parameter CyTOF panel enables deep functional characterization of CAR T cells by simultaneous detection of surface, cytoplasmic and nuclear markers, supporting advancing clinical development of CAR T therapies.For Research Use Only. Not for use in diagnostic procedures.
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 | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 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) | 0,002 | 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 ».