Background: Due to the lack of effective drugs, gastric cancer(GC) has a high mortality rate among other cancers, with a low 5-year survival rate and an inferior prognosis. Thus, screening of meaningful tumor biomarkers or therapeutic targets could play a vital role in the diagnosis, treatment, prognosis, and follow-up of GC.
Methods: Gene expression profiles and comprehensive clinical information of 407 patients with GC were downloaded from The Cancer Genome Atlas (TCGA) database. GC-related single-cell RNA sequencing data from the GSE118916 dataset was downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were screened from transcriptomic data in GC and normal samples by R language. The DAVID database was also used to analyze the functions and pathways of DEGs. After combining differential genes with patient survival information, target genes were identified. The interaction of DEGs in the protein-protein interaction (PPI) network was also studied.
Results: Our study identified a total of 209 differential genes, which might be positively related to GC. Gene Ontology (GO) analysis indicated numerous enrichment of DEGs in the extracellular matrix organization, extracellular structure organization, and muscle contraction. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that the DEGs were mainly enriched in focal adhesion, protein digestion and absorption, AGE-RAGE signaling pathway in diabetic complications. Further analysis showed the higher expression of Carboxypeptidase vitellogenic-like gene (CPVL) was related to the better prognosis of GC patients in both TCGA and the GEO database. FAM3 metabolism regulating signaling molecule D (FAM3D) and oxidized low-density lipoprotein receptor 1 (OLR1) were significantly associated with GC patients’ prognosis only in the GEO database. Lastly, the PPI network shows the gene expression proteins that interact most closely with CPVL protein.
Conclusion: Our study revealed that CPVL gene could be a promising target for the diagnosis and treatment of GC, which has a great significance for the future research on GC. In addition, we were the first to find a close relationship between FAM3D and GC.