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Anti-Egfr Bioengineered Bacterial Outer Membrane Vesicles As Targeted Immunotherapy Candidate in Triple-Negative Breast Tumor Murine Model Publisher Pubmed



Rezaei Adriani R1 ; Mousavi Gargari SL1 ; Bakherad H2 ; Amani J3
Authors

Source: Scientific Reports Published:2023


Abstract

Cancer immunotherapy employing checkpoint inhibitors holds great promise across diverse cancers; nonetheless, a substantial proportion of patients (ranging from 55 to 87%) remain unresponsive to this treatment. To amplify therapeutic efficiency, we propose a synergistic therapeutic strategy that entails the deployment of targeted nano-sized particles carrying Toll-like receptor (TLR) agonists to the tumor site. This innovative approach seeks to activate intratumoral antigen-presenting cells using bioengineered outer membrane vesicles (OMVs) derived from gram-negative bacteria. These OMVs possess inherent attributes of surface-exposed immune stimulators and TLR-activating components, rendering them intriguing candidates for investigation. These OMVs were meticulously designed to selectively target cancer cells exhibiting an overexpression of epidermal growth factor receptor (EGFR). To gauge the precision of this targeting, the conducted affinity-based assays aimed at determining the equilibrium dissociation constant of the single-chain variable fragment employed for this purpose. In vitro experiments confirmed the OMVs' proficiency in adhering to EGFR-overexpressed cancer cells. Moreover, the evaluation extended to an in vivo context, where the therapeutic effect of nanovesicles was appraised within the tumor microenvironment of the triple-negative breast cancer mouse model. Notably, both intraperitoneal and intratumoral administrations of nanovesicles exhibited the ability to activate natural killer cells and skew M2 macrophage towards an M1 phenotype. The combined scrutiny of in vitro and in vivo findings underscores the potential efficiency of OMVs as a promising strategy for future anti-tumor endeavors. © 2023, Springer Nature Limited.
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