Rapid receptor internalization potentiates CD7-targeted lipid nanoparticles for efficient mRNA delivery to T cells and in vivo CAR T-cell engineering.
Level 5 - mechanism / opinion, no new human data
Preclinical in vitro human cell assays and in vivo humanized mouse model
PubMed 42173446 · doi:10.1016/j.jconrel.2026.115043
What was done
Researchers systematically compared targeted lipid nanoparticles (tLNPs) conjugated with antibody-based moieties targeting CD2, CD4, CD5, CD7, CD8, or a CD4 + CD8 dual-targeting combination under identical conditions. They evaluated mRNA delivery efficiency in vitro using human T cells and peripheral blood mononuclear cells (PBMCs). The best-performing formulation was then tested in vivo in humanized mice to generate functional anti-CD20 (aCD20) chimeric antigen receptor (CAR) T cells. They also analyzed the mechanistic roles of receptor internalization rate versus receptor abundance across different antibody clones.
What was found
The abstract reports no numerical values, effect sizes, or statistical metrics. Qualitatively, CD7-targeted tLNPs achieved the highest mRNA delivery to T cells among all tested targets and generated functional aCD20 CAR T cells in vivo in humanized mice. Mechanistic analysis showed that delivery efficiency was primarily dictated by intrinsic receptor internalization kinetics rather than cell-surface receptor abundance, largely independent of the antibody clone used.
Why it matters
Generating CAR T cells directly in vivo eliminates costly and logistically challenging ex vivo cell manufacturing. Establishing CD7 as an effective target and identifying receptor internalization as the primary driver of mRNA delivery provides a mechanistic basis for designing future in situ cellular engineering platforms.
Limits
This study is preclinical, relying on in vitro assays and humanized mouse models; safety, persistence, immunogenicity, and clinical efficacy in humans were not evaluated. The abstract provides no sample sizes, numerical transfection efficiencies, dosing details, or data on off-target delivery.