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Immune-Epidermal Dual Targeting in Psoriasis: Emerging Technologies and Translational Therapeutic Strategies
Meijun Liu1, Pinzhi Dong1, Cong Yang1
1Department of Immunology, School of Basic Medicine & Key Laboratory of Cancer Prevention and Treatment of Guizhou Province, Center of Immunomolecular Engineering, Innovation & Practice Base for Graduate Students Education, Special Key Laboratory of Gene Detection & Therapy, Zunyi Medical University, Zunyi, Guizhou, China.
Abstract:
Although immune-targeted therapies, particularly agents targeting the IL-23/IL-17 axis, have markedly improved short-term disease control in psoriasis, inadequate responses in a subset of patients and relapse after treatment discontinuation remain unresolved challenges. One possible reason is that immune-centered therapies may not fully address the active contribution of epidermal keratinocytes (KCs) to inflammatory amplification and disease persistence. In this review, we integrate immune-driven inflammation and epidermal amplification mechanisms from a loop- and network-based perspective, and propose an immune-epidermal dual-targeting framework centred on pro-inflammatory feedback between immune cells and KCs. We systematically summarize three potential implementation routes: combination therapy, single-agent dual targeting and blockade of bridging nodes within immune-epidermal feedback circuits. We further discuss the potential roles and realistic boundaries of artificial intelligence and multi-omics analysis, organoids and engineered skin models, and precision local delivery technologies in target discovery, mechanistic validation and therapeutic translation. Importantly, this framework is not intended to replace existing therapeutic paradigms, but rather to refine their mechanistic interpretation and extend future therapeutic strategies. It may provide additional translational opportunities for stratified, stage-specific and precision management of psoriasis, although several components remain at the stage of mechanistic research and clinical validation.
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