Bioinformatics analysis of a-three-gene signature as an independent prediction of survival in follicular gastritis developing into gastric cancer

Abstract

Background and aimFrom follicular gastritis (FG) to gastric cancer (GC), the expression of genes has changed and the function of these genes has not been elucidated. Materials and methodsData of FG samples and GC samples were downloaded from GSE106656 and GSE116312 in GEO database. Clinical data of GC were downloaded from TCGA database. The common differential expression genes (DEGs) were enriched and analyzed by GO and KEGG in David. The interaction information of proteins was obtained from the STRING database and the core genes in the Cytoscape software were excavated. After KEGG, PPI and KM survival analysis of DEGs, the significant genes were intersected to fulfill the predicted genes. Univariate/Multivariate Cox regression analysis were used to get the prediction signatures. Results96 up-regulated genes were obtained from the data set. Three genes, CAV1 COL12A1 and ANGPT2, were acquired by survival analysis screening. Age, gender, lymph node status, and the 3-gene signature were selected as independent survival variables in the nomogram. The nomogram showed that C-index was 0.68 (95% CI, 0.60 to 0.75). ConclusionOur study identified the proposed nomogram may be used to predict the prognosis of patients from FG to GC, which may provide a potential useful guidance for preventive and epidemiological applications in GC.