Experimental Validation of an Immune Cell Infiltration Signature in Psoriasis: Translating Computational Modeling to In Vivo Efficacy.

OBJECTIVE

The psoriatic immune microenvironment (PIME) is central to psoriasis pathogenesis, yet its mechanistic drivers are incompletely defined. This study aimed to delineate immune cell infiltration patterns and identify pivotal disease-related immune genes through a systematic analysis of the PIME.

METHODS

We evaluated the infiltration levels of 28 immune cell subtypes in 11 psoriasis-related microarray datasets using single-sample gene set enrichment analysis (ssGSEA). Subsequent differential expression, consensus clustering, and weighted gene co-expression network analysis (WGCNA) were employed to identify key genes. These findings were validated using human psoriatic tissue samples and an imiquimod-induced murine psoriasis model to construct a predictive model termed IMscore.

RESULTS

Our analysis identified five pivotal immune-related differentially expressed genes (ImDEGs): CXCL8, CXCL9, CCL18, RGS1, and SAMSN1. A novel predictive model, IMscore, was constructed based on these ImDEGs to assess psoriasis risk. Furthermore, immune infiltration profiling and gene set enrichment analysis demonstrated that these ImDEGs are functionally associated with psoriasis-related inflammatory pathways, validating the diagnostic utility of the IMscore framework.

CONCLUSION

These results provide new insights into the immunological mechanisms underlying psoriasis and establish a multi-gene signature with potential for improving early diagnosis and therapeutic development.