Analysis of Gastric Cancer Transcriptomic Data by Bioinformatics Tools and Detection of Candidate Diagnostic Biomarker Genes

Abstract

Background: Gastric cancer is one of the leading cause of deaths in the world and each year many new cases diagnosed worldwide. Although there has been a decrease in its incidence over the past century, gastric cancer is the second leading cause of cancer-related deaths. Objective: The main objective of this study is identification of candidate biomarker genes to be used in early diagnosis of gastric cancer. Methods: In this study, GSE54129 data set in the Gene Expression Omnibus (GEO) database was used. This data set contains gene expression data of 111 stomach cancer tumor tissues and 21 normal stomach tissues. Bioinformatics analyses performed on raw microarray data (CEL files). All the analyses were performed with Transcriptome Analysis Console 4.0 (TAC) algorithm. Results: According to the results, expression level of many genes during neoplastic transformation in gastric cancer significantly changes when compared to healthy control subjects. The upregulated genes which show high fold changes are SFRP2, EGR1, CHI3L1, COL8A1, NEAT1, INHBA, CXCL8 and AIYL9. Some of downregulated genes with higher fold changes are GAST, GIF, GKN2, GKN1, SCGB2A1 and HRASLS2. Conclusion: These genes have a potential for candidate biomarkers that can be used in the diagnosis or detection of molecular subtypes of gastric cancer.