418 Dendritic cell-activation of T cells provides metabolic signals for improved <i>in vivo</i> persistence and anti-tumour performance
Notice bibliographique
Résumé
<h3>Background</h3> Adoptive cellular therapy (ACT), such as chimeric antigen receptor (CAR)-T cell therapy, has provided impressive clinical efficacy for treatment of patients with hematological malignancies.<sup>1</sup> However, its efficacy for solid tumours has been limited<sup>2</sup> largely due to immunosuppressive signals and competition for metabolic resources in the tumour microenvironment (TME) that can limit the efficacy and killing capacity of T cells.<sup>3</sup> Overcoming these metabolic challenges is vital for enhancing the efficacy of ACT. Many strategies for reprogramming T cell metabolism have emerged in the literature, however the impact of the clinical activation strategy – bead-bound anti-CD3 and anti-CD28 antibodies – remains largely unexplored. This study aims to compare the metabolic programming, effector function, persistence and resilience to metabolic stress of T cells activated with bead-bound antibodies (beads) or with dendritic cells (DCs). <h3>Methods</h3> We isolated CD8+ T cells from P14 mice that have a transgenic T cell receptor recognizing the gp33 peptide from lymphocytic choriomeningitis virus (LCMV). These T cells are co-cultured with either LPS-activated bone-marrow derived DCs pulsed with gp33 peptide, or with beads at ratios of 1:1 or 10:1 (beads:T cells). These T cells were activated for 72 hours followed by baseline analysis, transfer into <i>in vitro</i> stress conditions, or use for ACT in mice with established B16-gp33 melanoma tumours. <h3>Results</h3> Increasing the ratio of beads resulted in increased oxidative and glycolytic metabolism to a level comparable with DC-activated T cells. Despite the comparable bioenergetic profile, DC-activated T cells demonstrated superior tumour clearance compared to all ratios of bead-activated T cells. Additionally, <i>in vivo</i> in the same TME, DC-activated T cells showed significantly improved survival, suggesting DC-activation provides additional signals that confer resiliency to stress and improved function. Similar resiliency was observed in DC-activated T cells <i>in vitro</i> after exposure to stress conditions such as IL-2 withdrawal. Metabolomics and RNA-sequencing analyses have revealed distinct signaling and phospholipid metabolism between DC and bead-activated T cells. <h3>Conclusions</h3> DC-activation of T cells provides superior programming for efficacy, survival and resiliency to stress compared to bead-activation. These enhanced metrics are associated with unique metabolic and transcriptional programming. Current investigations are ongoing to determine if altering phospholipid metabolism in bead-activated T cells is sufficient to enhance their efficacy and resilience. This could then be incorporated into clinical protocols to improve ACT outcomes for patients. <h3>References</h3> Cappell KM, Kochenderfer JN. Long-term outcomes following CAR T cell therapy: what we know so far. <i>Nat Rev Clin Oncol</i> 2023;<b>20</b>:359–71. Hou B, Tang Y, Li W, Zeng Q, Chang D. Efficiency of CAR-T therapy for treatment of solid tumor in clinical trials: a meta-analysis. <i>Dis Markers</i> 2019;<b>2019</b>:e3425291. Hou AJ, Chen LC, Chen YY. Navigating CAR-T cells through the solid-tumour microenvironment. <i>Nat Rev Drug Discov</i> 2021;<b>20</b>:531–50. <h3>Ethics Approval</h3> This study was approved by the University Health Network Animal Care Committee approval number 929 and 6895.
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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 | 0,000 | 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) | 0,000 | 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 ».