OBJECTIVES: This study was designed to explore the pathogenesis of psoriasis and to identify potential bio-targets. Genome array technology was used to analyze the gene expression profiles of lesional and non-lesional psoriatic skin samples and normal skin samples. METHODS: Gene expression profile GSE14905 was downloaded from the Gene Expression Omnibus (GEO) database. This included skin biopsy samples from normal healthy donors (n = 21), lesional skin biopsy samples from psoriasis patients (n = 33), and non-lesional skin biopsy samples from psoriasis patients (n = 28). Differentially expressed genes (DEGs) were identified using the Limma package in R language. Functions of specific DEGs were predicted by Gene Ontology (GO) enrichment analysis. A protein-protein interaction network was constructed to display the interactions among common DEGs. Finally, DAVID and WebGestalt were used to achieve a functional analysis of common DEGs. RESULTS: Totals of 1020, 562, and 643 genes, respectively, were identified as being differentially expressed in normal versus lesional, normal versus non-lesional, and lesional versus non-lesional samples. The specific DEGs in the three groups were enriched for several GO terms, including mitotic cell cycle, immune response, and response to organic matter. The 40 common DEGs in the three groups may be involved in the defense response pathway in the development of psoriasis. Furthermore, three genes (RGS1, SOCS3, and NAMPT) may play key roles in distinguishing lesional and non-lesional tissues from normal tissues, and 10 genes (PTRRC, ALDH1A3, SAMSA1, C15orf48, ZC3H12A, SOD2, IL8, LTF, RHCG, and IL7R) may play key roles in distinguishing non-lesional from normal and lesional samples. CONCLUSIONS: These genes may be considered as potential diagnostic markers and targets of therapeutics in psoriasis.
OBJECTIVES: This study was designed to explore the pathogenesis of psoriasis and to identify potential bio-targets. Genome array technology was used to analyze the gene expression profiles of lesional and non-lesional psoriatic skin samples and normal skin samples. METHODS: Gene expression profile GSE14905 was downloaded from the Gene Expression Omnibus (GEO) database. This included skin biopsy samples from normal healthy donors (n = 21), lesional skin biopsy samples from psoriasispatients (n = 33), and non-lesional skin biopsy samples from psoriasispatients (n = 28). Differentially expressed genes (DEGs) were identified using the Limma package in R language. Functions of specific DEGs were predicted by Gene Ontology (GO) enrichment analysis. A protein-protein interaction network was constructed to display the interactions among common DEGs. Finally, DAVID and WebGestalt were used to achieve a functional analysis of common DEGs. RESULTS: Totals of 1020, 562, and 643 genes, respectively, were identified as being differentially expressed in normal versus lesional, normal versus non-lesional, and lesional versus non-lesional samples. The specific DEGs in the three groups were enriched for several GO terms, including mitotic cell cycle, immune response, and response to organic matter. The 40 common DEGs in the three groups may be involved in the defense response pathway in the development of psoriasis. Furthermore, three genes (RGS1, SOCS3, and NAMPT) may play key roles in distinguishing lesional and non-lesional tissues from normal tissues, and 10 genes (PTRRC, ALDH1A3, SAMSA1, C15orf48, ZC3H12A, SOD2, IL8, LTF, RHCG, and IL7R) may play key roles in distinguishing non-lesional from normal and lesional samples. CONCLUSIONS: These genes may be considered as potential diagnostic markers and targets of therapeutics in psoriasis.