Molecular Medicine Reports · 2018 · 75 citations · 44 references
MedicineMolecular BiologyOncologyCancer GeneticsGene ExpressionMolecular OncologyCancer BiomarkersCancer GenomicsGastric CancerGastric DiseasesGene Expression ProfilingMolecular Tumor ProfilingBiomarkers Of Gastric CancerEnrichment AnalysisFunctional Annotation Of GenesGene Ontology EnrichmentMicroarray AnalysisMicroarray Differential Expression AnalysisPrognostic BiomarkersTumor Profiling
Gastric cancer (GC) is the fifth most common malignancy and the third leading cause of cancer‑associated mortality in the world. However, its mechanisms of occurrence and development have not been clearly elucidated. Furthermore, there is no effective tumor marker for GC. Using DNA microarray analysis, the present study revealed genetic alterations, screened out core genes as novel markers and discovered pathways for potential therapeutic targets. Differentially expressed genes (DEGs) between GC and adjacent normal tissues were identified, followed by pathway enrichment analysis of DEGs. Next, the protein‑protein interaction (PPI) network of DEGs was built and visualized. Analyses of modules in the PPI network were then performed to identify the functional core genes. Finally, survival analysis of core genes was conducted. A total of 256 genes were identified as DEGs between the GC samples and normal samples, including 169 downregulated and 87 upregulated genes. Through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, the present study identified a total of 143 GO terms and 21 pathways. Six clusters of functional modules were identified, and the genes associated with these modules were screened out as the functional core genes. Certain core genes, including collagen type 12 α1 chain (COL12A1), glutathione S‑transferase α3 (GSTA3), fibrinogen α chain (FGA) and fibrinogen γ chain (FGG), were the first reported to be associated with GC. Survival analysis suggested that these four genes, COL12A1 (P=0.002), GSTA3 (P=3.4x10‑6), FGA (P=0.00075) and FGG (P=1.4x10‑5), were significant poor prognostic factors and therefore, potential targets to improve diagnosis, optimize chemotherapy and predict prognostic outcomes.
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