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Near-infrared light-driven metabolic reprogramming of synoviocytes for the treatment of rheumatoid arthritis

GSE294905 Mus musculus Expression profiling by high throughput sequencing 9 samples Submitted 2025/04/17 Platform GPL24247
Summary
Rheumatoid arthritis is a common autoimmune disease characterized by chronic synovial inflammation and joint destruction, primarily driven by imbalance cellular metabolism and inflammatory microenvironment. While gene therapy offers a promising therapeutic approach, its effectiveness is limited by the challenges of non-specific gene expression in healthy tissues. In the present study, we developed a gene delivery system (namely APPC), in which near-infrared (NIR)-responsive gold nanorods (AR) were coated with chondroitin sulfate-modified polyethyleneimine (CS-PEI) to facilitate the heat-responsive targeted delivery of heme oxygenase 1 (HO-1) gene. The APPC showed favorable transfection efficiency due to its targeting ability and significantly facilitate the HO-1 expression under NIR irradiation. The combination of APPC/pHO-1 and NIR could effectively reprogram the cellular metabolism and repolarize the macrophages and fibroblast-like synoviocytes (FLSs), thereby inhibiting the inflammation by suppressing the glycolysis. Meanwhile, APPC could specifically enhance the HO-1 expression in inflamed tissues through NIR-mediated the activation of HSP70 promoter, ensuring the precise gene expression via photothermal conversion. In a collagen-induced arthritis (CIA) model, APPC/pHO-1 under NIR irradiation exhibited potent therapeutic efficacy, restoring the articular microenvironmental homeostasis and mitigating the symptoms of RA. These findings highlighted the potential of APPC/pHO-1 nanoparticles in the gene therapy of RA and other inflammatory diseases.
Published in
Near-infrared light-driven metabolic reprogramming of synoviocytes for the treatment of rheumatoid arthritis
Zhang H, Jia J, Liu H et al. · Nature communications 2025 · PMID 40676021 · doi:10.1038/s41467-025-61923-7
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Also filed as BioProject PRJNA1252014 and SRA study SRP579523. Searching any of these in the dataset finder brings you back here.

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