Epigenetic risk score improves prostate cancer risk assessment
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 se...
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Published in | The Prostate Vol. 77; no. 12; pp. 1259 - 1264 |
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Main Authors | , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
Wiley Subscription Services, Inc
01.09.2017
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Subjects | |
Online Access | Get full text |
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Summary: | 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 GS ≥ 7 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 GS ≥ 7, 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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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0270-4137 1097-0045 |
DOI: | 10.1002/pros.23385 |