Heterogeneous patterns of DNA methylation-based field effects in histologically normal prostate tissue from cancer patients

Sci Rep. 2017 Jan 13;7:40636. doi: 10.1038/srep40636.


Prostate cancer (PC) diagnosis is based on histological evaluation of prostate needle biopsies, which have high false negative rates. Here, we investigated if cancer-associated epigenetic field effects in histologically normal prostate tissue may be used to increase sensitivity for PC. We focused on nine genes (AOX1, CCDC181 (C1orf114), GABRE, GAS6, HAPLN3, KLF8, MOB3B, SLC18A2, and GSTP1) known to be hypermethylated in PC. Using quantitative methylation-specific PCR, we analysed 66 malignant and 134 non-malignant tissue samples from 107 patients, who underwent ultrasound-guided prostate biopsy (67 patients had at least one cancer-positive biopsy, 40 had exclusively cancer-negative biopsies). Hypermethylation was detectable for all genes in malignant needle biopsy samples (AUC: 0.80 to 0.98), confirming previous findings in prostatectomy specimens. Furthermore, we identified a four-gene methylation signature (AOX1xGSTP1xHAPLN3xSLC18A2) that distinguished histologically non-malignant biopsies from patients with vs. without PC in other biopsies (AUC = 0.65; sensitivity = 30.8%; specificity = 100%). This signature was validated in an independent patient set (59 PC, 36 adjacent non-malignant, and 9 normal prostate tissue samples) analysed on Illumina 450 K methylation arrays (AUC = 0.70; sensitivity = 40.6%; specificity = 100%). Our results suggest that a novel four-gene signature may be used to increase sensitivity for PC diagnosis through detection of epigenetic field effects in histologically non-malignant prostate tissue samples.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Aged, 80 and over
  • Biomarkers, Tumor
  • Biopsy, Needle
  • DNA Methylation*
  • Epigenesis, Genetic
  • Epigenomics / methods
  • Genetic Heterogeneity*
  • Humans
  • Male
  • Middle Aged
  • Neoplasm Grading
  • Prostate / metabolism*
  • Prostatic Neoplasms / genetics*
  • Prostatic Neoplasms / pathology*
  • Prostatic Neoplasms / surgery
  • ROC Curve
  • Reproducibility of Results


  • Biomarkers, Tumor