Identification of potential biomarkers and infiltrating immune cells from scalp psoriasis

Abstract

Background: Scalp psoriasis seriously affects the appearance and psychological status of patients. The aim of this study was to investigate the effect and potential mechanism of RPL9 and TIFA in scalp psoriasis, so as to provide a precise and effective way for the clinical treatment of scalp psoriasis.

Methods: The Gene Expression Omnibus (GEO) database was employed to download the GSE75343 dataset to search for differentially expressed genes (DEGs) in scalp psoriasis through Sangerbox. Gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) enrichment analysis, functional enrichment analysis, immune cell infiltration analysis, immune responses and correlation analysis with 12 hub genes were performed. Then, STRING was used to develop a protein-protein interaction (PPI) network, used Cytoscape to locate hub genes, and SVM-RFE and random forest were utilized to identified RPL9 as the targeted gene. TIFA-RPL9 interaction predictions were made viathe Open Targets Platform and Uniprot. Further, the RPL9 and TIFA expression, molecular mechanism, and function were assessed in scalp psoriasis.

Results: Immunohistochemistry, qPCR, and western blotting verified that RPL9 and TIFA were highly expressed in lesional tissues of scalp psoriasis and IL17A-stimulated HaCaT cells. RPL9 knockdown effectively suppressed the proliferative capacity of IL17A-stimulated HaCaT cells in the CCK8 assay. The co-immunoprecipitation results revealed that RPL9 could interact with TIFA in IL17A-stimulated HaCaT cells. In qPCR and western blotting, RPL9 knockdown significantly inhibited TIFA at the mRNA and protein levels in IL17A-stimulated HaCaT cells. In ELISA, the secretion of TNF-α was markedly inhibited after downregulating RPL9 in IL17A-stimulated HaCaT cells.

Conclusion: To our knowledge, we have elucidated the expression and role of RPL9 and TIFA in scalp psoriatic skin and keratinocytes, and our findings confirm that RPL9 might act as a candidate therapeutic target for scalp psoriasis.

Keywords: Bioinformatics analysis; HaCaT cells; RPL9; Scalp psoriasis; TIFA; Targeted therapy.