Identification of hepatocellular carcinoma-associated hub genes and pathways by integrated microarray analysis

Tumori. 2015 Mar-Apr;101(2):206-14. doi: 10.5301/tj.5000241. Epub 2015 Mar 13.

Abstract

Aims and background: Hepatocellular carcinoma (HCC) is a dismal malignancy associated with multiple molecular changes. The purpose of this study was to identify the differentially expressed genes and analyze the biological processes related to HCC.

Methods and study design: Datasets of HCC were obtained from the NCBI Gene Expression Omnibus. Integrated analysis of differentially expressed genes was performed using the INMEX program. Then Gene Ontology enrichment analyses and pathway analysis were performed based on the Gene Ontology website and Kyoto Encyclopedia of Genes and Genomes. A protein-protein interaction network was constructed using the Cytoscape software; the netwerk served to find hub genes for HCC. Real-time RT-PCR was used to validate the microarray data for hub genes.

Results: We identified 273 genes that were differentially expressed in HCC. Gene Ontology enrichment analyses revealed response to cadmium ion, cellular response to cadmium ion, and cellular response to zinc ion for these genes. Pathway analysis showed that significant pathways included fatty acid metabolism, butanoate metabolism, and PPAR signaling pathway. The protein-protein interaction network indicated that CDH1, ECHS1, ACAA1, MT2A, and MYC were important genes which participated in many interactions. Experimental validation of the role of four upregulated genes (ECHS1, ACAA1, MT2A and MYC) in the progression of HCC was carried out.

Conclusions: Our study displayed genes that were consistently differentially expressed in HCC. The biological pathways and protein-protein interaction networks associated with those genes were also identified. We predicted that CDH1, ECHS1, ACAA1, MT2A, and MYC might be target genes for diagnosing HCC.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Carcinoma, Hepatocellular / genetics*
  • Computational Biology
  • Down-Regulation
  • Gene Expression Profiling* / methods
  • Gene Expression Regulation, Neoplastic
  • Gene Regulatory Networks*
  • Humans
  • Japan
  • Liver Neoplasms / genetics*
  • Microarray Analysis* / methods
  • Oncogenes* / genetics
  • Protein Interaction Maps
  • Real-Time Polymerase Chain Reaction
  • Reverse Transcriptase Polymerase Chain Reaction
  • Signal Transduction / genetics*
  • Up-Regulation