OncoTargets and Therapy (Dec 2017)

Identification of epigenetically altered genes and potential gene targets in melanoma using bioinformatic methods

  • Duan HH,
  • Jiang K,
  • Wei DK,
  • Zhang LJ,
  • Cheng DL,
  • Lv M,
  • Xu YB,
  • He AM

Journal volume & issue
Vol. Volume 11
pp. 9 – 15

Abstract

Read online

Honghao Duan, Ke Jiang, Dengke Wei, Lijun Zhang, Deliang Cheng, Min Lv, Yuben Xu, Aimin He Department of Hand Surgery, Honghui Hospital, Xi’an Jiaotong University Health Science Center, Xi’an, Shaanxi, People’s Republic of China Abstract: This study aimed to analyze epigenetically and genetically altered genes in melanoma to get a better understanding of the molecular circuitry of melanoma and identify potential gene targets for the treatment of melanoma. The microarray data of GSE31879, including mRNA expression profiles (seven melanoma and four melanocyte samples) and DNA methylation profiles (seven melanoma and five melanocyte samples), were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) and differentially methylated positions (DMPs) were screened using the linear models for microarray data (limma) package in melanoma compared with melanocyte samples. Gene ontology (GO) and pathway enrichment analysis of the DEGs were carried out using the Database for Annotation, Visualization, and Integrated Discovery. Moreover, differentially methylated genes (DMGs) were identified, and a transcriptional regulatory network was constructed using the University of California Santa Cruz genome browser database. A total of 1,215 DEGs (199 upregulated and 1,016 downregulated) and 14,094 DMPs (10,450 upregulated and 3,644 downregulated) were identified in melanoma compared with melanocyte samples. Additionally, the upregulated and downregulated DEGs were significantly associated with different GO terms and pathways, such as pigment cell differentiation, biosynthesis, and metabolism. Furthermore, the transcriptional regulatory network showed that DMGs such as Aristaless-related homeobox (ARX), damage-specific DNA binding protein 2 (DDB2), and myelin basic protein (MBP) had higher node degrees. Our results showed that several methylated genes (ARX, DDB2, and MBP) may be involved in melanoma progression. Keywords: melanoma, DNA methylation, differentially expressed genes, gene ontology, pathway enrichment analysis, transcriptional regulatory network

Keywords