PLoS ONE (Jan 2015)

DNA Methylation-Guided Prediction of Clinical Failure in High-Risk Prostate Cancer.

  • Kirill Litovkin,
  • Aleyde Van Eynde,
  • Steven Joniau,
  • Evelyne Lerut,
  • Annouschka Laenen,
  • Thomas Gevaert,
  • Olivier Gevaert,
  • Martin Spahn,
  • Burkhard Kneitz,
  • Pierre Gramme,
  • Thibault Helleputte,
  • Sofie Isebaert,
  • Karin Haustermans,
  • Mathieu Bollen

DOI
https://doi.org/10.1371/journal.pone.0130651
Journal volume & issue
Vol. 10, no. 6
p. e0130651

Abstract

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BackgroundProstate cancer (PCa) is a very heterogeneous disease with respect to clinical outcome. This study explored differential DNA methylation in a priori selected genes to diagnose PCa and predict clinical failure (CF) in high-risk patients.MethodsA quantitative multiplex, methylation-specific PCR assay was developed to assess promoter methylation of the APC, CCND2, GSTP1, PTGS2 and RARB genes in formalin-fixed, paraffin-embedded tissue samples from 42 patients with benign prostatic hyperplasia and radical prostatectomy specimens of patients with high-risk PCa, encompassing training and validation cohorts of 147 and 71 patients, respectively. Log-rank tests, univariate and multivariate Cox models were used to investigate the prognostic value of the DNA methylation.ResultsHypermethylation of APC, CCND2, GSTP1, PTGS2 and RARB was highly cancer-specific. However, only GSTP1 methylation was significantly associated with CF in both independent high-risk PCa cohorts. Importantly, trichotomization into low, moderate and high GSTP1 methylation level subgroups was highly predictive for CF. Patients with either a low or high GSTP1 methylation level, as compared to the moderate methylation groups, were at a higher risk for CF in both the training (Hazard ratio [HR], 3.65; 95% CI, 1.65 to 8.07) and validation sets (HR, 4.27; 95% CI, 1.03 to 17.72) as well as in the combined cohort (HR, 2.74; 95% CI, 1.42 to 5.27) in multivariate analysis.ConclusionsClassification of primary high-risk tumors into three subtypes based on DNA methylation can be combined with clinico-pathological parameters for a more informative risk-stratification of these PCa patients.