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Comprehensive methylome sequencing reveals prognostic epigenetic biomarkers for prostate cancer mortality
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...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9523674/ https://www.ncbi.nlm.nih.gov/pubmed/36178085 http://dx.doi.org/10.1002/ctm2.1030 |
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author | Pidsley, Ruth Lam, Dilys Qu, Wenjia Peters, Timothy J. Luu, Phuc‐Loi Korbie, Darren Stirzaker, Clare Daly, Roger J. Stricker, Phillip Kench, James G. Horvath, Lisa G. Clark, Susan J. |
author_facet | Pidsley, Ruth Lam, Dilys Qu, Wenjia Peters, Timothy J. Luu, Phuc‐Loi Korbie, Darren Stirzaker, Clare Daly, Roger J. Stricker, Phillip Kench, James G. Horvath, Lisa G. Clark, Susan J. |
author_sort | Pidsley, Ruth |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9523674 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95236742022-10-05 Comprehensive methylome sequencing reveals prognostic epigenetic biomarkers for prostate cancer mortality Pidsley, Ruth Lam, Dilys Qu, Wenjia Peters, Timothy J. Luu, Phuc‐Loi Korbie, Darren Stirzaker, Clare Daly, Roger J. Stricker, Phillip Kench, James G. Horvath, Lisa G. Clark, Susan J. Clin Transl Med Research Articles 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. John Wiley and Sons Inc. 2022-09-30 /pmc/articles/PMC9523674/ /pubmed/36178085 http://dx.doi.org/10.1002/ctm2.1030 Text en © 2022 The Authors. Clinical and Translational Medicine published by John Wiley & Sons Australia, Ltd on behalf of Shanghai Institute of Clinical Bioinformatics. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Articles Pidsley, Ruth Lam, Dilys Qu, Wenjia Peters, Timothy J. Luu, Phuc‐Loi Korbie, Darren Stirzaker, Clare Daly, Roger J. Stricker, Phillip Kench, James G. Horvath, Lisa G. Clark, Susan J. Comprehensive methylome sequencing reveals prognostic epigenetic biomarkers for prostate cancer mortality |
title | Comprehensive methylome sequencing reveals prognostic epigenetic biomarkers for prostate cancer mortality |
title_full | Comprehensive methylome sequencing reveals prognostic epigenetic biomarkers for prostate cancer mortality |
title_fullStr | Comprehensive methylome sequencing reveals prognostic epigenetic biomarkers for prostate cancer mortality |
title_full_unstemmed | Comprehensive methylome sequencing reveals prognostic epigenetic biomarkers for prostate cancer mortality |
title_short | Comprehensive methylome sequencing reveals prognostic epigenetic biomarkers for prostate cancer mortality |
title_sort | comprehensive methylome sequencing reveals prognostic epigenetic biomarkers for prostate cancer mortality |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9523674/ https://www.ncbi.nlm.nih.gov/pubmed/36178085 http://dx.doi.org/10.1002/ctm2.1030 |
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