Identification of hub genes in colon cancer via bioinformatics analysis

J Int Med Res. 2020 Sep;48(9):300060520953234. doi: 10.1177/0300060520953234.

Abstract

Objectives: This study aimed to investigate hub genes and their prognostic value in colon cancer via bioinformatics analysis.

Methods: Differentially expressed genes (DEGs) of expression profiles (GSE33113, GSE20916, and GSE37364) obtained from Gene Expression Omnibus (GEO) were identified using the GEO2R tool and Venn diagram software. Function and pathway enrichment analyses were performed, and a protein-protein interaction (PPI) network was constructed. Hub genes were verified based on The Cancer Genome Atlas (TCGA) and Human Protein Atlas (HPA) databases.

Results: We identified 207 DEGs, 62 upregulated and 145 downregulated genes, enriched in Gene Ontology terms "organic anion transport," "extracellular matrix," and "receptor ligand activity", and in the Kyoto Encyclopedia of Genes and Genomes pathway "cytokine-cytokine receptor interaction." The PPI network was constructed and nine hub genes were selected by survival analysis and expression validation. We verified these genes in the TCGA database and selected three potential predictors (ZG16, TIMP1, and BGN) that met the independent predictive criteria. TIMP1 and BGN were upregulated in patients with a high cancer risk, whereas ZG16 was downregulated. The immunostaining results from HPA supported these findings.

Conclusion: This study indicates that these hub genes may be promising prognostic indicators or therapeutic targets for colon cancer.

Keywords: BGN; Bioinformatic analysis; TIMP1; ZG16; colon cancer; hub genes.

MeSH terms

  • Colonic Neoplasms* / genetics
  • Computational Biology*
  • Gene Expression Profiling
  • Gene Expression Regulation, Neoplastic
  • Gene Regulatory Networks
  • Humans