Identification of key pathways and genes in nasopharyngeal carcinoma based on WGCNA

Abstract

Objective: We aim to identify the potential genes and signaling pathways associated with the nasopharyngeal carcinoma (NPC) prognosis using Weighted Gene Co-Expression Network Analysis (WGCNA).

Methods: Gene Expression Omnibus (GEO) query was utilized to download two NPC mRNA microarray data. WGCNA was conducted on differentially expressed genes (DEGs) to obtain tumor-associated gene modules. Genes in core modules were intersected with DEGs for gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analysis. GSE102349 dataset was devoted to identifying prognostic hub genes by survival analysis and the results were confirmed by quantitative polymerase chain reaction (qPCR).

Results: Co-expression networks were built, and we detected 12 gene modules. The Brown module and Magenta module were extremely associated with NPC samples. GO functional analysis and KEGG pathway analysis was carried out to the genes in the Brown and Magenta modules. Our data indicated that DEGs in Brown module and Magenta module were correlated with the biological regulation, metabolic process, reproduction, and cellular proliferation. Twenty-six hub genes were obtained and were considered to be closely related to NPC. GSE102349 dataset was devoted to identifying prognostic hub genes by survival analysis. The expression of IL33, MPP3 and SLC16A7 in GSE102349 dataset was significantly correlated with the progression-free survival (PFS). The results of qPCR indicated a strong correlation between SLC16A7 expression and the overall survival (OS).

Conclusions: WGCNA contributed to the detection of gene modules and identification of hub genes and crucial genes. These crucial genes might be potential targets for pharmaceutic therapies with potential clinical significance.

Keywords: Nasopharyngeal carcinoma; Prognosis; SLC16A7; Weighted Gene Co-Expression Network Analysis.