Identification of Critical Genes and Five Prognostic Biomarkers Associated with Colorectal Cancer

Med Sci Monit. 2018 Jul 5:24:4625-4633. doi: 10.12659/MSM.907224.

Abstract

BACKGROUND Colorectal cancer (CRC) is a common malignant tumor with high incidence and mortality worldwide. The aim of this study was to evaluate the association between differentially expressed genes (DEGs), which may function as biomarkers for CRC prognosis and therapies, and the clinical outcome in patients with CRC. MATERIAL AND METHODS A total of 116 normal mucous tissue and 930 CRC tissue datasets were downloaded from the Gene Expression Omnibus database (GEO) and The Cancer Genome Atlas (TCGA). After screening DEGs based on limma package in R. Gene Ontology (GO) and KEGG enrichment analysis as well as the protein-protein interaction (PPI) networks were performed to predict the function of these DEGs. Meanwhile, Cox proportional hazards regression was used to build a prognostic model of these DEGs. Then, Kaplan-Meier risk analysis was used to test the model in TCGA datasets and validation datasets. RESULTS In the present study, 300 DEGs with 100 upregulated genes and 200 downregulated genes were identified. The PPI networks including 162 DEGs and 256 nodes were constructed and 2 modules with high degree were selected. Moreover, 5 genes (MMP1, ACSL6, SMPD1, PPARGC1A, and HEPACAM2) were identified using the Cox proportional hazards stepwise regression. Kaplan-Meier risk curve in the TCGA and validation cohorts showed that high-risk group had significantly poor overall survival than the low-risk group. CONCLUSIONS Our study provided insights into the mechanisms of CRC formation and found 5 prognostic genes, which could potentially inform further studies and clinical therapies.

MeSH terms

  • Biomarkers, Tumor / genetics
  • Cell Cycle Proteins
  • Coenzyme A Ligases / genetics
  • Colorectal Neoplasms / diagnosis*
  • Colorectal Neoplasms / genetics*
  • Colorectal Neoplasms / metabolism
  • Computational Biology / methods
  • Databases, Genetic
  • Gene Expression
  • Gene Expression Profiling / methods
  • Gene Expression Regulation, Neoplastic
  • Gene Ontology
  • Gene Regulatory Networks
  • Humans
  • Kaplan-Meier Estimate
  • Matrix Metalloproteinase 1 / genetics
  • Peroxisome Proliferator-Activated Receptor Gamma Coactivator 1-alpha / genetics
  • Prognosis
  • Protein Interaction Maps
  • Proteins / genetics
  • Sphingomyelin Phosphodiesterase / genetics
  • Transcriptome / genetics

Substances

  • Biomarkers, Tumor
  • Cell Cycle Proteins
  • HEPACAM protein, human
  • PPARGC1A protein, human
  • Peroxisome Proliferator-Activated Receptor Gamma Coactivator 1-alpha
  • Proteins
  • SMPD1 protein, human
  • Sphingomyelin Phosphodiesterase
  • MMP1 protein, human
  • Matrix Metalloproteinase 1
  • Coenzyme A Ligases
  • ACSL6 protein, human