Purpose: Guselkumab is a highly effective biologic agent for treating psoriasis. This study aimed to explore potential transcription factors involved in psoriasis pathogenesis and response to guselkumab treatment, aiming to provide new therapeutic strategies for psoriasis.
Patients and Methods: We analyzed gene expression and single-cell RNA-seq data from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) that upregulated in psoriasis and downregulated after guselkumab treatment were subjected to enrichment analyses. Single-cell regulatory network inference and clustering (SENIC) and regulon module analyses identified different regulon activities between the lesion and non-lesion skin of psoriasis. Cell-cell communication analysis revealed interactions among specific cell clusters. Transcription factor (TF) regulons were identified from the guselkumab-specific regulon network. Gene set enrichment analysis (GSEA) confirmed the IRF7 regulon in the validation cohort. Finally, the expression level of IRF7 was identified in plaque psoriasis before and after 12 weeks of guselkumab therapy by immunohistochemical experiment.
Results: 799 DEGs were downregulated after guselkumab treatment. Enrichment analyses highlighted the interleukin-17 (IL-17) pathway in this gene set. The M2 module exhibited the primary difference in regulon activity. Strong cell-cell interactions were observed between keratinocytes and immune cells. IRF7 regulon had significant roles in psoriasis and treatment response, as validated by GSEA analysis using the IL-17 signaling pathway as a reference. The immunohistochemical analysis unveiled substantial differences in the expression levels of IRF7 in psoriatic skin samples before and after 12 weeks of guselkumab treatment.
Conclusion: IRF7 may be the key player in psoriasis pathogenesis and the therapeutic process involving guselkumab. Targeting IRF7 might offer new therapeutic strategies for psoriasis.

Keywords: guselkumab, plaque psoriasis, IL-23/IL-17 signaling pathway, SENIC analysis, TF regulon