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5-ALA photodynamic metabolite-powered zero-waste “ferroptosis amplifier” for enhanced hypertrophic scar therapy

GSE300586 Homo sapiens Expression profiling by high throughput sequencing 8 samples Submitted 2025/06/24 Platform GPL24676
Summary
Hypertrophic scar (HS) is a somatopsychic disease that significantly affects quality of life. 5-aminolevulinic acid (5-ALA)-mediated photodynamic therapy (PDT) holds promise for HS treatment, while challenges like poor transdermal delivery and rapid metabolism into non_xfffe_photosensitive heme restrict its effectiveness. Inspired by the natural phenomenon of a whale fall nourishing life, this study innovatively repurposes 5-ALA metabolic waste, heme, as a “whale-like” energy source to drive ferroptosis, thus establishing a zero-waste therapy. This is achieved by encapsulating 5-ALA and baicalin within human H-ferritin (HFn), subsequently incorporated into polyvinylpyrrolidone (PVP) microneedles (FAB@MN). The FAB@MN exhibits excellent targeting towards hypertrophic scar fibroblasts (HSFs) with pH-responsive programmed drug release. Upon application, 5-ALA is converted into PpIX to initiate PDT. Subsequently, baicalin is released, triggering ferroptosis while also synergizing with the ROS and heme accumulated during PDT to overstimulate the HO-1-heme metabolic axis. This activation releases Fe2+ and CO, further potentiating ferroptosis. Moreover, the enhanced ferroptotic response driven by FAB@MN induces mitophagy, leading to increased Fe²⁺ release from the mitochondria. Unlike conventional PDT only focuses on immediate effects, this approach uses 5-ALA photodynamic waste to fuel a sustained ferroptosis response post-PDT, offering new avenues for HS treatments.
Published in
5-ALA photodynamic metabolite-powered zero-waste ferroptosis amplifier for enhanced hypertrophic scar therapy
Chen Y, Wang S, Mao C et al. · Nature communications 2025 · PMID 40968167 · doi:10.1038/s41467-025-63438-7
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Also filed as BioProject PRJNA1281503 and SRA study SRP594174. Searching any of these in the dataset finder brings you back here.

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