Bioinformatics Analysis of Key Genes and Pathways in Colorectal Cancer

J Comput Biol. 2019 Apr;26(4):364-375. doi: 10.1089/cmb.2018.0237. Epub 2019 Feb 27.

Abstract

Colorectal cancer (CRC) is the third most prevalent cancer in the world. Although great progress has been made, the specific molecular mechanism remains unclear. This study aimed to explore the differentially expressed genes (DEGs) and underlying mechanisms of CRC using bioinformatics analysis. In this study, we identified a total of 1353 DEGs in the database of GSE113513, including 715 up- and 638 downregulated genes. Gene ontology analysis results showed that upregulated DEGs were significantly enriched in cell division, cell proliferation, and DNA replication. The downregulated DEGs were enriched in immune response, relation of cell growth and inflammatory response. The Kyoto Encyclopedia of Genes and Genomes pathway analysis showed that upregulated DEGs were enriched in cell cycle and p53 signaling pathway, whereas the downregulated DEGs were enriched in drug metabolism, metabolism of xenobiotics by cytochrome P450, and nitrogen metabolism. A total of 124 up-key genes and 35 down-key genes were identified from the protein-protein interaction networks. Furthermore, we identified five up-modules (up-A, up-B, up-C, up-D, and up-E) and three down-modules (d-A, d-B, and d-C) by module analysis. The module up-A was enriched in sister chromatid cohesion, cell division, and mitotic nuclear division. Pathways associated with cell cycle, progesterone-mediated oocyte maturation, oocyte meiosis, and p53 signaling pathway. Whereas the d-A was mainly enriched in G-protein coupled receptor signaling pathway, cell chemotaxis, and chemokine-mediated signaling pathway. The pathways enriched in chemokine signaling pathway, cytokine-cytokine receptor interaction, and alcoholism. These key genes and pathways might be used as molecular targets and diagnostic biomarkers for the treatment of CRC.

Keywords: colorectal cancer; key genes; molecular mechanisms.

MeSH terms

  • Biomarkers, Tumor / genetics
  • Cell Cycle
  • Colorectal Neoplasms / genetics*
  • Computational Biology / methods*
  • Databases, Genetic
  • Gene Expression Profiling
  • Gene Expression Regulation, Neoplastic
  • Gene Regulatory Networks*
  • Humans
  • Protein Interaction Maps
  • Signal Transduction

Substances

  • Biomarkers, Tumor