Re-Exploring Biomarkers and Therapeutic Targets in Primary Melanoma Patients: Insights from Network-Based Analysis of Microarray Data

Abstract

ABSTRACT: Objective: To identify novel biomarkers and therapeutic targets for primary melanoma using network-based microarray data analysis. Methods: Eligible microarray datasets from the Gene Expression Omnibus (GEO) database were used to identify differentially expressed genes (DEGs). The protein-protein interaction (PPI) network, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to identify hub genes and pathways that might affect the survival of melanoma patients. Immunohistochemistry results obtained from the Human Protein Atlas (HPA) database confirmed the protein expression levels of hub genes. The Cancer Genome Atlas (TCGA) database was used to further verify the gene expression levels and conduct survival analysis. Results: Three microarray datasets (GSE3189, GSE15605, and GSE46517) containing 122 melanoma and 30 normal skin tissue samples were included. A total of 262 common differentially expressed genes (cDEGs) were identified based on three statistical approaches (Fisher's method, the random effects model (REM), and vote counting) with strict criteria. Of these, two upregulated genes, centromere protein F (CENPF) and pituitary tumor-transforming gene 1 (PTTG1), were selected as hub genes. HPA and TCGA database analyses confirmed that CENPF and PTTG1 were overexpressed in melanoma. Survival analysis showed that high expression levels of CENPF were significantly correlated with decreased overall survival (OS) (P=0.028). Conclusion: The expression level of CENPF was significantly upregulated in melanoma and correlated with decreased OS. Thus, CENPF may represent a novel biomarker and therapeutic target for melanoma patients.

Keywords

• Melanoma
• Network-based analysis
• Microarray
• Centromere protein F
• Biomarkers