BCMA-targeted CAR-NK cell therapy using lipid nanoparticle mRNA delivery for multiple myeloma
Notice bibliographique
Résumé
Abstract Multiple myeloma (MM) is the second most common hematologic malignancy (Mikhael et al. Am J Med 2023). Despite advances in treatment, relapsed and refractory MM (RRMM) remains a major clinical challenge (Vu et al. Front Oncol 2023). Chimeric Antigen Receptor (CAR) T-cell therapy, which involves genetically modifying a patient's T cells to recognize and destroy cancer cells, has shown significant efficacy in RRMM (Sheykhhasan et al. Cancer Gene Ther 2024). In particular, CAR-T therapies targeting B-cell maturation antigen (BCMA), a critical protein for MM cell survival, have produced durable responses (Yang et al. Cancer Lett 2023). However, CAR-T therapy is limited by severe toxicities (e.g., neurotoxicity, cytokine release syndrome), risk of graft-versus-host disease (GVHD), and a costly, time-intensive production process, reducing accessibility for patients (Sterner et al. Blood Cancer J 2021). Natural killer (NK) cells represent a promising alternative, offering potent anti-tumor activity while mitigating risks associated with T cells (Vu et al. Front Oncol 2023). Unlike autologous CAR-T therapies, allogeneic CAR-NK cells can be pre-manufactured, cryopreserved, and delivered as readily available “off-the-shelf” therapy. Furthermore, the viral vector gene delivery traditionally used in CAR-T manufacturing is costly and carries risks of insertional mutagenesis and immunogenicity (Balke-Want et al. Immunooncol Technol 2023). Lipid nanoparticles (LNPs) delivering mRNA overcome these limitations by enabling transient CAR expression, minimizing off-target effects, and improving scalability and safety (Douka et al. J Control Release 2023). In this study, we are developing a BCMA-targeted CAR-NK therapy using LNP-mediated mRNA delivery to improve CAR therapy safety and accessibility. The mRNA CAR construct encodes an anti-BCMA single-chain variable fragment (scFv), CD8 transmembrane domain, 4-1BB costimulatory domain, and CD3ζ signaling domain. LNPs were formulated with lipid 5, β-sitosterol, distearoylphosphatidylcholine (DSPC), and 1,2-dimyristoyl-rac-glycero-3-methoxypolyethylene glycol (DMG-PEG)-2000. LNP encapsulation of the anti-BCMA CAR mRNA was achieved via rapid hand mixing and characterized by dynamic light scattering for particle size and polydispersity index (PI), and by the ribogreen assay for encapsulation efficiency. The mRNA-CAR constructs were delivered into NK-92 cells via LNP transfection and incubated for 24 hours to allow expression. Western blotting against CD3ζ confirmed CAR production, while flow cytometry using a BCMA peptide quantified transfection efficiency. Engineered NK-92 cells were co-cultured with BCMA-expressing MM cell lines (RPMI 8226 and KMS12) for 4 hours, and cytotoxicity was evaluated using flow cytometry, impedance-based assays, and ongoing luciferase-based assays. Optimized mRNA-LNP formulations demonstrated >95% encapsulation efficiency, with particle sizes <200 nm and a PI <0.2, confirming their stability and uniformity. Using this approach, we achieved 75–85% transfection efficiency in NK-92 cells at 24 hours post-transfection, with >90% viability. CAR expression remained high for up to 3 days and diminished by 7 days post-transfection. To prolong expression, we are investigating the use of self-amplifying RNA (saRNA). Preliminary cytotoxicity studies using flow cytometry and impedance-based assays at a 1:1 effector-to-target (E:T) ratio demonstrated >10% BCMA-specific killing compared to non-transfected NK controls, confirming functional activity of the modified NK cells. Current studies are evaluating anti-BCMA CAR constructs incorporating NK-specific intracellular signaling domains, along with degranulation and cytokine release assays to quantify granzyme, perforin, and IFN-γ secretion respectively. Future work will extend these experiments to primary NK cells and in vivo models. Our findings demonstrate that optimized mRNA-LNP formulations achieve high transfection efficiencies in NK-92 cells and induce BCMA-specific cytotoxicity, confirming the feasibility of this platform and supporting the development of allogeneic mRNA-LNP CAR-NK therapies. Ultimately, the development of a CAR-NK cell library will provide the necessary building blocks to integrate various targeting receptors onto a CAR-NK cell backbone, enabling a therapeutic strategy adaptable to a range of cancers beyond multiple myeloma.
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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) | 0,002 | 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 ».