Comprehensive methylome sequencing reveals prognostic epigenetic biomarkers for prostate cancer mortality

前列腺癌 DNA甲基化 表观遗传学 肿瘤科 癌症 CpG站点 医学 比例危险模型 甲基化 疾病 内科学 生物 遗传学 基因 基因表达
作者
Ruth Pidsley,Dilys Lam,Wenjia Qu,Timothy J. Peters,Phuc‐Loi Luu,Darren J. Korbie,Clare Stirzaker,Roger J. Daly,Phillip D. Stricker,James G. Kench,Lisa Glen Horvath,Susan J. Clark
出处
期刊:Clinical and translational medicine [Springer Science+Business Media]
卷期号:12 (10): e1030-e1030 被引量:23
标识
DOI:10.1002/ctm2.1030
摘要

BACKGROUND: Prostate cancer is a clinically heterogeneous disease with a subset of patients rapidly progressing to lethal-metastatic prostate cancer. Current clinicopathological measures are imperfect predictors of disease progression. Epigenetic changes are amongst the earliest molecular changes in tumourigenesis. To find new prognostic biomarkers to enable earlier intervention and improved outcomes, we performed methylome sequencing of DNA from patients with localised prostate cancer and long-term clinical follow-up. METHODS: We used whole-genome bisulphite sequencing (WGBS) to comprehensively map and compare DNA methylation of radical prostatectomy tissue between patients with lethal disease (n = 7) and non-lethal (n = 8) disease (median follow-up 19.5 years). Validation of differentially methylated regions (DMRs) was performed in an independent cohort (n = 185, median follow-up 15 years) using targeted multiplex bisulphite sequencing of candidate regions. Survival was assessed via univariable and multivariable analyses including clinicopathological measures (log-rank and Cox regression models). RESULTS: WGBS data analysis identified cancer-specific methylation patterns including CpG island hypermethylation, and hypomethylation of repetitive elements, with increasing disease risk. We identified 1420 DMRs associated with prostate cancer-specific mortality (PCSM), which showed enrichment for gene sets downregulated in prostate cancer and de novo methylated in cancer. Through comparison with public prostate cancer datasets, we refined the DMRs to develop an 18-gene prognostic panel. Applying this panel to an independent cohort, we found significant associations between PCSM and hypermethylation at EPHB3, PARP6, TBX1, MARCH6 and a regulatory element within CACNA2D4. Strikingly in a multivariable model, inclusion of CACNA2D4 methylation was a better predictor of PCSM versus grade alone (Harrell's C-index: 0.779 vs. 0.684). CONCLUSIONS: Our study provides detailed methylome maps of non-lethal and lethal prostate cancer and identifies novel genic regions that distinguish these patient groups. Inclusion of our DNA methylation biomarkers with existing clinicopathological measures improves prognostic models of prostate cancer mortality, and holds promise for clinical application.

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