Bacterial protoplast-derived nanovesicles carrying CRISPR-Cas9 tools re-educate tumor-associated macrophages for enhanced cancer immunotherapy.
Mingming ZhaoXiaohui ChengPingwen ShaoYao DongYongjie WuLin XiaoZhiying CuiXuedi SunChuancheng GaoJiangning ChenZhen HuangJunfeng ZhangPublished in: Nature communications (2024)
The CRISPR-Cas9 system offers substantial potential for cancer therapy by enabling precise manipulation of key genes involved in tumorigenesis and immune response. Despite its promise, the system faces critical challenges, including the preservation of cell viability post-editing and ensuring safe in vivo delivery. To address these issues, this study develops an in vivo CRISPR-Cas9 system targeting tumor-associated macrophages (TAMs). We employ bacterial protoplast-derived nanovesicles (NVs) modified with pH-responsive PEG-conjugated phospholipid derivatives and galactosamine-conjugated phospholipid derivatives tailored for TAM targeting. Utilizing plasmid-transformed E. coli protoplasts as production platforms, we successfully load NVs with two key components: a Cas9-sgRNA ribonucleoprotein targeting Pik3cg, a pivotal molecular switch of macrophage polarization, and bacterial CpG-rich DNA fragments, acting as potent TLR9 ligands. This NV-based, self-assembly approach shows promise for scalable clinical production. Our strategy remodels the tumor microenvironment by stabilizing an M1-like phenotype in TAMs, thus inhibiting tumor growth in female mice. This in vivo CRISPR-Cas9 technology opens avenues for cancer immunotherapy, overcoming challenges related to cell viability and safe, precise in vivo delivery.
Keyphrases
- crispr cas
- cancer therapy
- genome editing
- drug delivery
- immune response
- photodynamic therapy
- escherichia coli
- toll like receptor
- dna methylation
- big data
- single molecule
- fatty acid
- inflammatory response
- signaling pathway
- gene expression
- dendritic cells
- machine learning
- climate change
- liver injury
- cell free
- adipose tissue
- smoking cessation
- skeletal muscle
- insulin resistance
- artificial intelligence