Background
Gastric cancer (GC), a common malignancy of the human digestive system, represents the second leading cause of cancer-related deaths worldwide. Early detection of GC has a significant impact on clinical outcomes. The aim of this study was to identify potential GC biomarkers.
Methods
In this study, we conducted a multi-step analysis of expression profiles in GC clinical samples downloaded from TCGA database to identify differentially expressed miRNAs (DEMs) and differentially expressed mRNAs (DEGs). Potential prognostic biomarkers from the available DEMs were then established using the Cox regression method. Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to investigate the biological role of the predicted target genes of the miRNA biomarkers. Then, the prognostic DEM-mediated regulatory network was constructed based on transcription factor (TF)–miRNA–target interaction. Subsequently, the consensus genes were further determined based on the overlap between DEGs and these target genes of DEMs. Besides, expression profile, co-expression analysis, immunity, and prognostic values of these prognostic genes were also investigated to further explore the roles in the mechanism of GC tumorigenesis.
Results
We got five miRNAs, including miR-23b, miR-100, miR-143, miR-145, and miR-409, which are associated with the overall survival of GC patients. Subsequently, enrichment analysis of the target genes of the miRNA biomarkers shown that the GO biological process terms were mainly enriched in mRNA catabolic process, nuclear chromatin, and RNA binding. In addition, the KEGG pathways were significantly enriched in fatty acid metabolism, extracellular matrix (ECM) receptor interaction, and proteoglycans in cancer pathways. The transcriptional regulatory network consisting of 68 TFs, 4 DEMs, and 58 targets was constructed based on the interaction of TFs, miRNAs, and targets. The downstream gene ETS1 of miR-23b and TCF4 regulated by ETS1 were obtained by the regulatory network construction and co-expression analysis. High expression of ETS1 and TCF4 indicated poor prognosis in GC patients, particularly in the advanced stages. The expression of ETS1 and TCF4 was correlated with CD4+ T cells, CD8+ T cells, and B cells.
Conclusions
miR-23b, ETS1, and TCF4 were identified as the prognostic biomarkers. ETS1 and TCF4 had potential immune function in GC, which provided a theoretical basis for molecular-targeted combined immunotherapy in the future.