Comprehensive gene expression analysis reveals multiple signal pathways associated with prostate cancer

J Appl Genet. 2014 Feb;55(1):117-24. doi: 10.1007/s13353-013-0174-9. Epub 2013 Oct 24.

Abstract

Prostate cancer (PC) depends on androgenic signaling for growth and survival. To data, the exact molecular mechanism of hormone controlling proliferation and tumorigenesis in the PC remains unclear. Therefore, in this study, we explored the differentially expressed genes (DEGs) and identified featured genes related to hormone stimulus from PC. Two sets of gene expression data, including PC and normal control sample, were downloaded from Gene Expression Omnibus (GEO) database. The t-test was used to identify DEGs between PC and controls. Gene ontology (GO) functional annotation was applied to analyze the function of DEGs and screen hormone-related DEGs. Then these hormone-related DEGs were further analyzed in constructed cancer network and Human Protein Reference Database to screen important signaling pathways they participated in. A total of 912 DEGs were obtained which included 326 up-regulated genes and 586 down-regulated genes. GO functional enrichment analysis identified 50 hormone-related DEGs associated with PC. After pathway and PPI network analysis, we found these hormone-related DEGs participated in several important signaling pathways including TGF-β (TGFB2, TGFB3 and TGFBR2), MAPK (TGFB2, TGFB3 and TGFBR2), insulin (PIK3R3, SHC1 and EIF4EBP1), and p53 signaling pathways (CCND2 and CDKN1A). In addition, a total of five hormone-related DEGs (SHC1, CAV1, RXRA, CDKN1A and SRF) were located in the center of PPI network and 12 hormone-related DEGs formed six protein modules. These important signal pathways and hormone-related DEGs may provide potential therapeutic targets for PC.

Publication types

  • Retracted Publication

MeSH terms

  • Down-Regulation
  • Gene Expression Profiling
  • Gene Expression Regulation, Neoplastic
  • Gene Regulatory Networks*
  • Humans
  • Male
  • Oligonucleotide Array Sequence Analysis
  • Prostatic Neoplasms / genetics*
  • Protein Interaction Maps
  • Signal Transduction / genetics*
  • Up-Regulation