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Record W7108461223 · doi:10.1182/blood-2025-7647

BCMA-targeted CAR-NK cell therapy using lipid nanoparticle mRNA delivery for multiple myeloma

2025· article· en· W7108461223 on OpenAlexaff

Bibliographic record

VenueBlood · 2025
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsOntario Institute for Cancer ResearchUniversity of Alberta
Fundersnot available
KeywordsChimeric antigen receptorMultiple myelomaGenetic enhancementImmunogenicityCancerCell therapyCytokine release syndromeImmunotherapy

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.033
GPT teacher head0.301
Teacher spread0.267 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2025
Admission routes1
Has abstractyes

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