Background: Psoriasis extends beyond its dermatological inflammatory manifestations, encompassing systemic inflammation. Existing studies have indicated a potential risk of cervical cancer among patients with psoriasis, suggesting a potential mechanism of co-morbidity. This study aims to explore the key genes, pathways, and immune cells that may link psoriasis and cervical squamous cell carcinoma (CESC).Methods: The cervical squamous cell carcinoma dataset (GSE63514) was downloaded from the Gene Expression Omnibus (GEO). Two psoriasis-related datasets (GSE13355 and GSE14905) were merged into one comprehensive dataset after removing batch effects. Differentially expressed genes were identified using Limma and co-expression network analysis (WGCNA), and machine learning random forest algorithm (RF) was used to screen the hub genes. We analyzed relevant gene enrichment pathways using GO and KEGG, and immune cell infiltration in psoriasis and CESC samples using CIBERSORT. The miRNA-mRNA and TFs-mRNA regulatory networks were then constructed using Cytoscape, and the biomarkers for psoriasis and CESC were determined. Potential drug targets were obtained from the cMAP database, and biomarker expression levels in hela and psoriatic cell models were quantified by RT-qPCR.Results: In this study, we identified 27 key genes associated with psoriasis and cervical squamous cell carcinoma. NCAPH, UHRF1, CDCA2, CENPN and MELK were identified as hub genes using the Random Forest machine learning algorithm. Chromosome mitotic region segregation, nucleotide binding and DNA methylation are the major enrichment pathways for common DEGs in the mitotic cell cycle. Then we analyzed immune cell infiltration in psoriasis and cervical squamous cell carcinoma samples using CIBERSORT. Meanwhile, we used the cMAP database to identify ten small molecule compounds that interact with the central gene as drug candidates for treatment. By analyzing miRNA-mRNA and TFs-mRNA regulatory networks, we identified three miRNAs and nine transcription factors closely associated with five key genes and validated their expression in external validation datasets and clinical samples. Finally, we examined the diagnostic effects with ROC curves, and performed experimental validation in hela and psoriatic cell models.Conclusions: We identified five biomarkers, NCAPH, UHRF1, CDCA2, CENPN, and MELK, which may play important roles in the common pathogenesis of psoriasis and cervical squamous cell carcinoma, furthermore predict potential therapeutic agents. These findings open up new perspectives for the diagnosis and treatment of psoriasis and squamous cell carcinoma of the cervix.

Background: The aim of this study was to analyze and compare melanoma gene expression profiles in TCGA database through the application of different genes to explore the pathogenesis of melanoma. Furthermore, we confirmed the extent of the role of KYNU in melanoma and whether it can be a potential target for the diagnosis and treatment of melanoma. Methods: The gene expression profiles of melanoma samples were downloaded from TCGA database, and matrix files were synthesized to screen differential genes. The Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway analysis and GCDA broad institute were used to analyze common gene locus mutations and expression changes in melanoma, as well as methylation. In addition, the expression patterns of KYNU in melanoma were quantified by immunohistochemistry, Western blotting, qRT-PCR, software such as GEO DataSets and the Human Protein Atlas, and meta-analysis of skin diseases. KYNU was overexpressed in keratinocytes (HaCaT and HEKα) and melanoma cells (A375 and H1205-lu). CFDA-SE, Annexin V–PI double staining, and PI single staining were used to investigate the mechanism of KYNU in melanoma and its effects on melanoma proliferation, apoptosis, invasion, and migration. Results: The main signaling pathways involved in melanoma were EGF/EGFR–RAS–BRAF–MEK–ERK–CyclinD1/CDK4, Ras–PI3K–PTEN–PKB/AKT, and p14/p16 (CDKN2A)–MDM2–p53–p21–cyclinD1/CDK4/6–Rb/E2F. Moreover, MITF, KIT, CDH1. NRAS, AKT1, EGFR, TP53, KIT, and CDK4 were elevated in melanoma, whereas PTEN, cAMP, and BCL2 were reduced in melanoma. The copy number of tumor-promoting genes increased, while the copy number of tumor suppressor genes decreased. Changes in the copy number of the above tumor genes enriched in chromosomes were found through SNP gene mutations. The genes whose expression was negatively regulated by DNA methylation in melanoma included KRT18, CDK2, JAK3, BCL2, MITF, MET, CXCL10, EGF, SOX10, SOCS3, and KIT. The mutation rate of KYNU was high according to TCGA database. The KYNU level was decreased in melanoma. Overexpression of KYNU can promote changes in apoptotic BCL-2, metabolic KYN, 3-HAA, invasion and migration MMP9, E-cadherin, and other related proteins in melanoma. Fluorescence staining and flow analysis showed that a slower proliferation rate led to a stronger fluorescence intensity. In melanoma tumor cells with a low expression of KYNU, overexpression of KYNU could promote tumor cell apoptosis. IL-10 induced immunoregulatory changes in melanoma. The expression of MMP9 and AMPK decreased in A375, but the change in BCL-2 was not obvious. The expression of BCL-2 decreased significantly in H1205-lu. A375 showed cell-cycle arrest, indicating that IL-10 could slow down the cell cycle of melanoma. Conclusions: These results provide insights into the pathologic mechanisms of melanoma target genes and KYNU as a biomarker and potential therapeutic factor for melanoma.

Anoikis is a programmed cell death that occurs when cells detach from the extracellular matrix (ECM). Its role in psoriasis remains unclear. This study aims to explore the relationship between psoriasis and apoptosis, focusing on anoikis-related mechanisms. Differentially expressed genes (DEGs) in psoriasis were identified using the GEO database and overlapped with anoikis-related genes from GeneCards to find differentially expressed anoikis-related genes (DE-ARGs). A PPI network was constructed, revealing eight hub DE-ARGs. These were then analyzed using GO, KEGG and ssGSEA. Immune infiltration cells and molecules were examined, and single-cell data analysis, immunohistochemistry, qRT-PCR, Western blotting, gene mapping, and drug prediction were performed. Eighteen DE-ARGs were identified, with STAT3 and BIRC5 as key DEGs. Enrichment analysis showed DE-ARGs were related to the regulation of anoikis and positive regulation of epithelial cell proliferation. Notable differences in dendritic and mast cells were observed between psoriasis lesions and no-lesion samples. Elevated expression of BIRC5 and STAT3 in psoriasis lesions was confirmed through qRT-PCR, western blotting and immunohistochemistry. This study establishes a relationship between anoikis and psoriasis, where STAT3 and BIRC5 play important roles. STAT3 and BIRC5 may serve as potential targets for the prevention and treatment of psoriasis.