ArticleFrontiers in medicine2026
Integrated systems toxicology identifies TCDD-responsive targets linked to immune dysregulation and treatment response in psoriasis.
Article in Frontiers in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Psoriasis is a chronic immune-mediated inflammatory skin disease driven by dysregulation of the IL-23/IL-17 axis and influenced by genetic and environmental factors. The role and molecular mechanisms of the environmental pollutant dibenzo-p-dioxins, particularly 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), in psoriasis remain unclear. Methods: An integrative strategy combining network toxicology, machine learning, bioinformatics analysis, molecular simulation, and Results: Eighty-seven overlapping genes were identified between TCDD-related targets and psoriasis-associated genes and were mainly enriched in IL- 17-, chemokine-, MAPK/ ERK-, and GPCR-related signaling pathways. Machine learning identified five core target genes-LCK, MMP9, CXCR2, PTAFR, and CCNB1-which were significantly upregulated in psoriatic lesions, showed strong diagnostic performance within the analyzed datasets, and were associated with local immune infiltration patterns. Structural analyses supported potential interactions between TCDD and these core targets, with CXCR2 showing the most favorable predicted docking score. A 24-h keratinocyte TCDD-response signature showed significant concordance with psoriatic lesional transcriptomes, and keratinocyte qRT-PCR validation showed increased expression of LCK, MMP9, CXCR2, and PTAFR, whereas CCNB1 showed only a modest change. In biologic-therapy cohorts, core genes were downregulated after 12 weeks, and higher baseline MMP9 was associated with poorer clinical improvement and may have potential relevance to treatment response. Conclusion: Our integrative analyses identify TCDD-associated genes and pathways potentially involved in psoriasis immune dysregulation. Structural modeling supports the
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