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Epigenetic risk score improves prostate cancer risk assessment

  • Van Neste, Leander
  • Groskopf, Jack
  • Grizzle, William E
  • Adams, George W
  • DeGuenther, Mark S
  • Kolettis, Peter N
  • Bryant, James E
  • Kearney, Gary P
  • Kearney, Michael C
  • Van Criekinge, Wim
  • Gaston, Sandra M
Publication Date
Jan 01, 2017
Ghent University Institutional Archive
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Background: Early detection of aggressive prostate cancer (PCa) remains crucial for effective treatment of patients. However, PCa screening remains controversial due to a high rate of overdiagnosis and overtreatment. To better reconcile both objectives, more effective methods for assessing disease severity at the time of diagnosis are needed. Methods: The relationship between DNA-methylation and high-grade PCa was examined in a cohort of 102 prospectively enrolled men who received standard 12-core prostate biopsies. EpiScore, an algorithm that quantifies the relative DNA methylation intensities of GSTP1, RASSF1, and APC in prostate biopsy tissue, was evaluated as a method to compensate for biopsy under-sampling and improve risk stratification at the time of diagnosis. Results: DNA-methylation intensities of GSTP1, RASSF1, and APC were higher in biopsy cores from men diagnosed with GS7 cancer compared to men with diagnosed GS 6 disease. This was confirmed by EpiScore, which was significantly higher for subjects with high-grade biopsies and higher NCCN risk categories (both P<0.001). In patients diagnosed with GS7, increased levels of DNA-methylation were present, not only in the high-grade biopsy cores, but also in other cores with no or low-grade disease (P<0.001). By combining EpiScore with traditional clinical risk factors into a logistic regression model, the prediction of high GS reached an AUC of 0.82 (95%CI: 0.73-0.91) with EpiScore, DRE, and atypical histological findings as most important contributors. Conclusions: In men diagnosed with PCa, DNA-methylation profiling can detect under-sampled high-risk PCa in prostate biopsy specimens through a field effect. Predictive accuracy increased when EpiScore was combined with other clinical risk factors. These results suggest that EpiScore could aid in the detection of occult high-grade disease at the time of diagnosis, thereby improving the selection of candidates for Active Surveillance.

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