Identifying novel biomarkers of gastric cancer through integration analysis of single nucleotide polymorphisms and gene expression profile.

Abstract

Single nucleotide polymorphisms (SNPs) are an important cause of functional variation in proteins leading to tumorigenesis. We aimed to identify candidate biomarkers with polymorphisms in gastric cancer (GC). The SNP microarray profile GSE29996 including 50 GC samples and 50 normal controls, and gene expression data GSE56807 consisting of 5 GC samples and 5 controls were downloaded from the Gene Expression Omnibus database. After preprocessing of raw data, GC-associated SNPs were identified using the Cochran-Armitage trend test, and differentially expressed genes (DEGs) were screened out using the limma package in R. Significant DEGs with risk associated SNP loci were screened using the Fisher combination test. Gene ontology function and pathway enrichment analyses were performed for DEGs with risk associated SNP loci by GenCLip online tool. Transcriptional regulatory analysis was also conducted for transcription factor and target DEGs. A total of 79 DEGs with risk associated SNP loci were identified from GC samples compared with normal controls. These DEGs were mainly enriched in anatomical structure development, including embryo development. Additionally, DEGs were significantly involved in the NO1 pathway, including actin, alpha 1, skeletal muscle (ACTA1). In the regulatory network, transcription factor forkhead box L1 (FOXL1) regulated 26 DEGs with risk associated SNP loci, including Iroquois homeobox 1 (IRX1) rs11134044, sex determining region Y (SRY)-box1 (SOX1) rs9549447 and msh homeobox 1 (MSX1) rs41451149. IRX1, SOX1 and MSX1 with risk associated SNP loci may serve as candidate biomarkers for diagnosis and prognosis of GC.