ArticlePloS one2015
DNA Methylation-Guided Prediction of Clinical Failure in High-Risk Prostate Cancer.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed, 38 citations in OpenAlex.
- The Years 2015-2025 as a Prospective Decade for the Identification of Specific Methylation Biomarkers of Prostate Cancer.Biomolecules · 2025Review
- Prostate cancer epigenetics - from pathophysiology to clinical application.Nature reviews. Urology · 2025Review
- Genomic, epigenomic, and transcriptomic signatures of prostate cancer between African American and European American patients.Frontiers in oncology · 2023Review
- The Potential Role of Mitochondrial Acetaldehyde Dehydrogenase 2 in Urological Cancers From the Perspective of Ferroptosis and Cellular Senescence.Frontiers in cell and developmental biology · 2022Review
- Electrochemically detecting DNA methylation in the EN1 gene promoter: implications for understanding ageing and disease.Bioscience reports · 2020Article
- Review
- Genomic data imputation with variational auto-encoders.GigaScience · 2020Article
- Random forest-based modelling to detect biomarkers for prostate cancer progression.Clinical epigenetics · 2019Article
- Clinical protein science in translational medicine targeting malignant melanoma.Cell biology and toxicology · 2019Article
- The impact of DNA methylation on the cancer proteome.PLoS computational biology · 2019Article
- Integrative (epi) Genomic Analysis to Predict Response to Androgen-Deprivation Therapy in Prostate Cancer.EBioMedicine · 2018Article
- Epigenetic Signature: A New Player as Predictor of Clinically Significant Prostate Cancer (PCa) in Patients on Active Surveillance (AS).International journal of molecular sciences · 2017Review
- The Genomic Impact of DNA CpG Methylation on Gene Expression; Relationships in Prostate Cancer.Biomolecules · 2017Review
- Article
- DNA Methylation and Urological Cancer, a Step Towards Personalized Medicine: Current and Future Prospects.Molecular diagnosis & therapy · 2016Review
- Methylation in benign prostate and risk of disease progression in men subsequently diagnosed with prostate cancer.International journal of cancer · 2016Article
- Biomarkers in localized prostate cancer.Future oncology (London, England) · 2016Review
Corrections and comments
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Authors and funding
14 authors at 2 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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