GD2-targeting CAR-T cells enhanced by transgenic IL-15 expression are an effective and clinically feasible therapy for glioblastoma
Notice bibliographique
Résumé
Abstract Background Aggressive primary brain tumors such as glioblastoma are uniquely challenging to treat. The intracranial location poses barriers to therapy, and the potential for severe toxicity. Effective treatments for primary brain tumors are limited, and 5-year survival rates remain poor. Immune checkpoint inhibitor therapy has transformed treatment of some other cancers but has yet to significantly benefit patients with glioblastoma. Early phase trials of CAR-T cell therapy have demonstrated that this approach is safe and feasible, but with limited evidence of its effectiveness. The choices of appropriate target antigens for CAR-T cell therapy also remain limited. Methods We profiled an extensive biobank of patients’ biopsy tissues and patient-derived early passage glioma neural stem cell lines for GD2 expression using immunomicroscopy and flow cytometry. We then employed an approved clinical manufacturing process to make CAR-T cells from peripheral blood of glioblastoma and diffuse midline glioma patients and characterized their phenotype and function in vitro . Finally, we tested intravenously administered CAR-T cells in an aggressive intracranial xenograft model of glioblastoma and used multicolor flow cytometry, multicolor whole-tissue immunofluorescence and next-generation RNA sequencing to uncover markers associated with effective tumor control. Results Here we show that the tumor-associated antigen GD2 is highly and consistently expressed in primary glioblastoma tissue removed at surgery. Moreover, despite glioblastoma patients having perturbations in their immune system, highly functional GD2-specific CAR-T cells can be produced from their peripheral T cells using an approved clinical manufacturing process. Finally, after intravenous administration, GD2-CAR-T cells effectively infiltrated the brain and controlled tumor growth in an aggressive orthotopic xenograft model of glioblastoma. Tumor control was further improved using CAR-T cells manufactured with a clinical retroviral vector encoding an IL-15 transgene alongside the GD2-specific CAR. These CAR-T cells achieved a striking 50% complete response rate by bioluminescence imaging in established intracranial tumors. Markers associated with tumor control included those related to T-cell homing, infiltration, and cytotoxicity. Conclusions Targeting GD2 using a clinically deployed CAR-T therapy has a sound scientific and clinical rationale as a treatment for glioblastoma and other aggressive primary brain tumors. What is already known on this topic GD2 is a tumor antigen of significant interest for targeting immunotherapy. A single preclinical study has shown the effectiveness of GD2-CAR-T cell therapy in an orthotopic xenograft model of diffuse midline glioma. Similarly, there is one previous preclinical study of GD2-CAR-T therapy in a orthotopic glioblastoma xenograft model but tumor control was achieved only following intracranial injection of CAR-T cells. Given that GD2-CAR-T therapy is already being evaluated clinically for other tumor indications, it is important to establish whether there is an acceptable rationale for its use in brain tumors. What this study adds This is the first description of a GD2-targeted CAR-T cell therapy that shows antitumor effectiveness in a preclinical model of human glioblastoma following intravenous administration. It is also the first study to investigate the potential effects that the immune profile of glioblastoma patients may have on the feasibility of CAR-T cell manufacturing. How this study might affect research, practice, or policy The results of this study have led to the initiation of an Australian phase 1 clinical trial program aiming to test GD2-specific CAR-T cells for the treatment of childhood and adult primary brain tumors. The study provides valuable insights into the microenvironmental factors that influence the effectiveness of CAR-T cell therapy for this type of tumor, paving the way for further optimization of CAR-T cell technology for treatment of aggressive primary brain tumors such as glioblastoma.
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) | 0,001 | 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 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 ».