Dr. Dong-Jiunn Jeffery Truong

ENVLPE improves gene and cell therapy

Scientists at German Helmholtz Centre Munich have presented a new transport system for gene and cell therapy that overcomes the limitations of viral vectors. An in vivo gene therapy for hereditary blindness corrected the defect in the Rpe65 gene ten times more efficiently than was possible with viral vectors.

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The new ENVLPE technology (Engineered Nucleocytosolic Vehicles for Loading of Programmable Editors) developed by Dong-Jiunn Jeffery Truong’s group at the Helmholtz Institute for Synthetic Medicine solves several problems that doctors have with in vivo gene therapy: The nucleotide sequences required for targeted gene correction and the Cas nuclease sequence are not introduced into long-lived viral vectors such as the adeno-associated virus (AAV) or into lipid nanoparticles (LNPs), expressed individually at the target site and assembled into a functional CRISPR-Cas complex that repairs genetic defects. According to Troung, this strategy has several disadvantages: Prolonged expression of the gene editors and Cas nuclease can trigger immune reactions. Theoretically, the nucleotide sequences can be incorporated into the target genome at sites that drastically increase the risk of cancer. In addition, the intrinsically unstable gene editors sg-RNA and sge-RNA can be degraded or the Cas nuclease cutting the defective gene can work suboptimally. In addition, the target control of the viral and LNP vectors is too unspecific.

ENVLPE ten times more efficient
The ENVLPE technology works in a fundamentally different way: for better targeting, virus-like particles (VLPs) are assembled in the cytosol, which package the complete, functioning Cas ribonucleoprotein (RNPs) into virus-like particles (VLPs). These are viral envelopes that carry glycoproteins on the outside that have an affinity for certain target cell receptors and thus a defined cell tropism for the purpose of target control. On the inside, they carry adaptors to which correctly assembled RNPs bind using RNA aptamers, which are released at the target site for a short time and carry out gene correction using gene scissors – too short, incidentally, to induce an immune response. To prevent RNP degradation, particularly of the labile gene-editor strands, the RNA strands also carry a protective cap at the 3′ end that prevents this very
degradation. Applied in a mouse model with hereditary blindness, the defective Rpe65 was repaired ten times more efficiently than with classical gene therapy vectors. Compared with other VLPs, the amount of VLP required per gene correction was lower with ENVLPE.

Revolution for cell therapy
But that’s not all. ENVLPE also promises significant progress in highly efficient ex vivo cell therapies that are accompanied by strong immune reactions, such as CAR-T, TCR-T or RNA-based therapies. The system presented in Cell (10.1016/j.cell.2025.03.015) allows the targeted genetic modification of immunogenic proteins on T cells using gene editing and major histocompatibility complex I (MHC I). In T-cell recipients, the physicians at the Technical University of Munich observed no rejection reaction after ENVLPE administration. This promises to make cancer immunotherapies significantly cheaper, as the T cells, which have become hypoallergenic through targeted protein engineering, no longer have to be removed from cancer patients and then undergo lengthy modification and multiplication, which is a major cost factor in cancer immunotherapies.

“These innovations address challenges in both in vivo gene therapies for genetically inherited diseases and ex vivo cell therapies for cancer and pave the way for important translational advances. The highly modular ENVLPE system also brings us much closer to on-demand and precise genetic modification of complex cellular models,” commented Prof Dr Gil Westmeyer, Director of the Institute of Synthetic Biomedicine and co-author of the study. ‘It is an example of how synthetic biology can help drive medical innovation.’ The next task now is to further improve the accuracy of the patent-pending vector system through AI-supported protein design.

Translated with DeepL.com (free version)

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