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Kang-Yun Lee

Publications and source records attributed to Kang-Yun Lee.

3 recordsLinked to original sources

Artificial intelligence for translational personalized neoantigen cancer vaccine development.

Personalized neoantigen cancer vaccine is a promising strategy for precision immunotherapy by targeting patient-specific and mutation-derived tumor antigens. Early clinical studies have demonstrated the feasibility, safety, and immunogenicity of these vaccines across multiple solid tumors, with encouraging outcomes particularly when combined with immune checkpoint blockade. However, broader clinical translation remains limited by sequential bottlenecks across the vaccine development pipeline, including false-positive neoantigen selection,  imperfect modeling of antigen processing and HLA presentation, limited prediction of T-cell receptor recognition, and challenges in formulation, delivery, and manufacturing. Artificial intelligence and advanced computational workflows are increasingly integrated into this pipeline to improve candidate prioritization and support more reproducible decision-making. In this review, we summarize clinical progress and key translational barriers in personalized neoantigen vaccination, and discuss how AI-enabled approaches may contribute across four major stages: multi-omics integration for neoantigen discovery, processing-aware HLA presentation prediction, structure-aware and TCR-informed immunogenicity modeling, and data-driven formulation optimization, particularly for lipid nanoparticle-based delivery systems. These approaches are able to help narrow biological and chemical search spaces, improve prioritization, and provide mechanistic insights into antigen presentation and immune recognition rather than replacing experimental validation. This articlefurther addresses future implementation challenges, including dataset diversity, model interpretability, prospective benchmarking, manufacturing traceability, and evolving regulatory frameworks for individualized mRNA cancer immunotherapies. Integrating computational innovation with rigorous immunological validation, scalable manufacturing, and regulatory oversight will be essential for advancing personalized neoantigen vaccines toward broader clinical implementation.

Cancer Vaccines

ITIH4 alleviates OVA-induced asthma by regulating lung-gut microbiota.

BACKGROUND: Inter-alpha-trypsin inhibitor heavy chain 4 (ITIH4), a Type 2 acute phase protein, is critical for resolving inflammation and promoting tissue repair. While its role in chronic respiratory diseases is recognized, its effects on asthma remain unclear. This study investigated the effects of ITIH4 on the modulation of lung and gut microbiota, the attenuation of allergic inflammation, and the improvement of respiratory outcomes in an asthma mouse model. METHODS: Six-week-old male Balb/c mice were divided into five groups: control, ITIH4, ovalbumin (OVA), and two OVA&#x2009;+&#x2009;ITIH4 treatment groups at different doses. Lung function and oxygen saturation were measured, and bronchoalveolar lavage fluid (BALF) was analyzed for white blood cell counts and cytokines. Lung and gut microbiota were profiled using 16&#xa0;S rRNA gene sequencing, and short-chain fatty acids (SCFAs) were measured using gas chromatography-mass spectrometry (GC-MS). Proteomic profiling of intestinal tissues was conducted to identify ITIH4-associated signaling pathways. RESULTS: ITIH4 administration significantly mitigated OVA-induced asthma symptoms by reducing weight loss, airway resistance, and tissue damping (p&#x2009;<&#x2009;0.05). Histological analysis showed decreased airway wall thickening and lung injury scores (p&#x2009;<&#x2009;0.05). ITIH4 also lowered BALF eosinophils and lymphocytes, IgE, and Th2 cytokines (IL-4, IL-5, and IL-13) (p&#x2009;<&#x2009;0.05). ITIH4 treatment modulated microbiome composition, enriching Gram-positive taxa (Nocardioidaceae and Acholeplasmataceae) and depleting Gram-negative Helicobacteraceae (p&#x2009;<&#x2009;0.05). SCFAs correlated with microbiome alterations, notably reduced 4-methylpentanoic acid levels (p&#x2009;<&#x2009;0.05). Proteomic analysis revealed a dose-dependent activation of granzyme A signaling and suppression of metabolic and solute transport pathways. CONCLUSIONS: ITIH4 ameliorates asthma symptoms by modulating lung and gut microbiota, dampening Th2-driven inflammation, and restoring mucosal immune balance. These findings support ITIH4 as a potential candidate for microbiome-targeted asthma therapy.

Animals