Mining of Gene Modules and Identification of Key Genes for early diagnosis of gastric cancer

Abstract

Abstract Background Gastric cancer (GC) is one of the most common malignant tumors with high incidence and mortality rates. Most patients with GC are not diagnosed until the advanced stage of cancer or during tumor screening, resulting in missing the best treatment time. Methods This study identified key modules and hub genes associated with GC by weighted gene co-expression network analysis (WGCNA). RNA sequencing profiles and clinical information data were downloaded from The Cancer Genome Atlas (TCGA). Compared with normal samples, the “limma” package in R was used to identify differentially expressed genes (DEGs) in GC samples. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted to detect the related pathways and functions of DEGs. Gene modules associated with clinical characteristics were identified with WGCNA in tumor and normal samples. Hub genes of key modules were identified using survival and expression analysis. Finally, one-way ANOVA was used to explore the relationship between hub gene expression in normal tissues and different pathological stages of GC. Results A total of 4892 DEGs were screened. These DEGs were primarily associated with extracellular matrix organization, DNA replication, cell cycle, and p53 signaling pathway. Based on WGCNA, six gene modules were obtained, of which two modules were significantly correlated with GC. Through survival and expression analysis, a total of 19 genes with good prognosis and significantly different expression in tumor tissues (compared with normal tissues) were identified. There were significant differences in the expression levels of hub genes in normal tissues and different pathological stages of GC, indicating that these genes have important diagnostic value for early GC. Conclusions In this study, the expression levels of 19 hub genes were significantly different in different GC pathological stages from normal samples, indicating that these hub genes can be used as auxiliary indicators in the diagnosis of early GC.