Hub Genes and Key Pathway Identification in Colorectal Cancer Based on Bioinformatic Analysis

Biomed Res Int. 2019 Nov 6:2019:1545680. doi: 10.1155/2019/1545680. eCollection 2019.

Abstract

Colorectal cancer (CRC) is one of the most common malignant tumors. The aim of the present study was to identify key genes and pathways to improve the understanding of the mechanism of CRC. GSE87211, including 203 CRC samples and 160 control samples, was screened to identify differentially expressed genes (DEGs). In total, 853 DEGs were obtained, including 363 upregulated genes and 490 downregulated genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of DEGs were performed to obtain enrichment datasets. GO analysis showed that DEGs were significantly enriched in the extracellular region, cell-cell signaling, hormone activity, and cytokine activity. KEGG pathway analysis revealed that the DEGs were mainly enriched in the cytokine-cytokine receptor interaction, drug metabolism, androgen and estrogen metabolism, and neuroactive ligand-receptor interaction. The Protein-Protein Interaction (PPI) network of DEGs was constructed by using Search Tool for the Retrieval of Interacting Genes (STRING). The app MCODE plugged in Cytoscape was used to explore the key modules involved in disease development. 43 key genes involved in the top two modules were identified. Six hub genes (CXCL2, CXCL3, PTGDR2, GRP, CXCL11, and AGTR1) were statistically associated with patient overall survival or disease-free survival. The functions of six hub genes were mainly related to the hormone and chemokine activities. In conclusion, the present study may help understand the molecular mechanisms of CRC development.

MeSH terms

  • Colorectal Neoplasms / genetics*
  • Computational Biology / methods
  • Cytokines / genetics
  • Disease-Free Survival
  • Down-Regulation / genetics
  • ELAV-Like Protein 2 / genetics*
  • Gene Expression Regulation, Neoplastic / genetics
  • Gene Ontology
  • Gene Regulatory Networks / genetics
  • Humans
  • Protein Interaction Mapping / methods
  • Receptors, Cytokine / genetics
  • Signal Transduction / genetics*
  • Up-Regulation / genetics

Substances

  • Cytokines
  • ELAV-Like Protein 2
  • ELAVL2 protein, human
  • Receptors, Cytokine