Cargando…
Identification of a DNA methylation signature to predict disease-free survival in locally advanced rectal cancer
In locally advanced rectal cancer a preoperative predictive biomarker is necessary to adjust treatment specifically for those patients expected to suffer relapse. We applied whole genome methylation CpG island array analyses to an initial set of patients (n=11) to identify differentially methylated...
Autores principales: | , , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals LLC
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4226671/ https://www.ncbi.nlm.nih.gov/pubmed/25261372 |
_version_ | 1782343656988999680 |
---|---|
author | Gaedcke, Jochen Leha, Andreas Claus, Rainer Weichenhan, Dieter Jung, Klaus Kitz, Julia Grade, Marian Wolff, Hendrik A. Jo, Peter Doyen, Jérôme Gérard, Jean-Pierre Johnsen, Steven A. Plass, Christoph Beißbarth, Tim Ghadimi, Michael |
author_facet | Gaedcke, Jochen Leha, Andreas Claus, Rainer Weichenhan, Dieter Jung, Klaus Kitz, Julia Grade, Marian Wolff, Hendrik A. Jo, Peter Doyen, Jérôme Gérard, Jean-Pierre Johnsen, Steven A. Plass, Christoph Beißbarth, Tim Ghadimi, Michael |
author_sort | Gaedcke, Jochen |
collection | PubMed |
description | In locally advanced rectal cancer a preoperative predictive biomarker is necessary to adjust treatment specifically for those patients expected to suffer relapse. We applied whole genome methylation CpG island array analyses to an initial set of patients (n=11) to identify differentially methylated regions (DMRs) that separate a good from a bad prognosis group. Using a quantitative high-resolution approach, candidate DMRs were first validated in a set of 61 patients (test set) and then confirmed DMRs were further validated in additional independent patient cohorts (n=71, n=42). We identified twenty highly discriminative DMRs and validated them in the test set using the MassARRAY technique. Ten DMRs could be confirmed which allowed separation into prognosis groups (p=0.0207, HR=4.09). The classifier was validated in two additional cohorts (n=71, p=0.0345, HR=3.57 and n=42, p=0.0113, HR=3.78). Interestingly, six of the ten DMRs represented regions close to the transcriptional start sites of genes which are also marked by the Polycomb Repressor Complex component EZH2. In conclusion we present a classifier comprising 10 DMRs which predicts patient prognosis with a high degree of accuracy. These data may now help to discriminate between patients that may respond better to standard treatments from those that may require alternative modalities. |
format | Online Article Text |
id | pubmed-4226671 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Impact Journals LLC |
record_format | MEDLINE/PubMed |
spelling | pubmed-42266712014-11-17 Identification of a DNA methylation signature to predict disease-free survival in locally advanced rectal cancer Gaedcke, Jochen Leha, Andreas Claus, Rainer Weichenhan, Dieter Jung, Klaus Kitz, Julia Grade, Marian Wolff, Hendrik A. Jo, Peter Doyen, Jérôme Gérard, Jean-Pierre Johnsen, Steven A. Plass, Christoph Beißbarth, Tim Ghadimi, Michael Oncotarget Clinical Research Paper In locally advanced rectal cancer a preoperative predictive biomarker is necessary to adjust treatment specifically for those patients expected to suffer relapse. We applied whole genome methylation CpG island array analyses to an initial set of patients (n=11) to identify differentially methylated regions (DMRs) that separate a good from a bad prognosis group. Using a quantitative high-resolution approach, candidate DMRs were first validated in a set of 61 patients (test set) and then confirmed DMRs were further validated in additional independent patient cohorts (n=71, n=42). We identified twenty highly discriminative DMRs and validated them in the test set using the MassARRAY technique. Ten DMRs could be confirmed which allowed separation into prognosis groups (p=0.0207, HR=4.09). The classifier was validated in two additional cohorts (n=71, p=0.0345, HR=3.57 and n=42, p=0.0113, HR=3.78). Interestingly, six of the ten DMRs represented regions close to the transcriptional start sites of genes which are also marked by the Polycomb Repressor Complex component EZH2. In conclusion we present a classifier comprising 10 DMRs which predicts patient prognosis with a high degree of accuracy. These data may now help to discriminate between patients that may respond better to standard treatments from those that may require alternative modalities. Impact Journals LLC 2014-10-27 /pmc/articles/PMC4226671/ /pubmed/25261372 Text en Copyright: © 2014 Gaedcke et al. http://creativecommons.org/licenses/by/2.5/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited |
spellingShingle | Clinical Research Paper Gaedcke, Jochen Leha, Andreas Claus, Rainer Weichenhan, Dieter Jung, Klaus Kitz, Julia Grade, Marian Wolff, Hendrik A. Jo, Peter Doyen, Jérôme Gérard, Jean-Pierre Johnsen, Steven A. Plass, Christoph Beißbarth, Tim Ghadimi, Michael Identification of a DNA methylation signature to predict disease-free survival in locally advanced rectal cancer |
title | Identification of a DNA methylation signature to predict disease-free survival in locally advanced rectal cancer |
title_full | Identification of a DNA methylation signature to predict disease-free survival in locally advanced rectal cancer |
title_fullStr | Identification of a DNA methylation signature to predict disease-free survival in locally advanced rectal cancer |
title_full_unstemmed | Identification of a DNA methylation signature to predict disease-free survival in locally advanced rectal cancer |
title_short | Identification of a DNA methylation signature to predict disease-free survival in locally advanced rectal cancer |
title_sort | identification of a dna methylation signature to predict disease-free survival in locally advanced rectal cancer |
topic | Clinical Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4226671/ https://www.ncbi.nlm.nih.gov/pubmed/25261372 |
work_keys_str_mv | AT gaedckejochen identificationofadnamethylationsignaturetopredictdiseasefreesurvivalinlocallyadvancedrectalcancer AT lehaandreas identificationofadnamethylationsignaturetopredictdiseasefreesurvivalinlocallyadvancedrectalcancer AT clausrainer identificationofadnamethylationsignaturetopredictdiseasefreesurvivalinlocallyadvancedrectalcancer AT weichenhandieter identificationofadnamethylationsignaturetopredictdiseasefreesurvivalinlocallyadvancedrectalcancer AT jungklaus identificationofadnamethylationsignaturetopredictdiseasefreesurvivalinlocallyadvancedrectalcancer AT kitzjulia identificationofadnamethylationsignaturetopredictdiseasefreesurvivalinlocallyadvancedrectalcancer AT grademarian identificationofadnamethylationsignaturetopredictdiseasefreesurvivalinlocallyadvancedrectalcancer AT wolffhendrika identificationofadnamethylationsignaturetopredictdiseasefreesurvivalinlocallyadvancedrectalcancer AT jopeter identificationofadnamethylationsignaturetopredictdiseasefreesurvivalinlocallyadvancedrectalcancer AT doyenjerome identificationofadnamethylationsignaturetopredictdiseasefreesurvivalinlocallyadvancedrectalcancer AT gerardjeanpierre identificationofadnamethylationsignaturetopredictdiseasefreesurvivalinlocallyadvancedrectalcancer AT johnsenstevena identificationofadnamethylationsignaturetopredictdiseasefreesurvivalinlocallyadvancedrectalcancer AT plasschristoph identificationofadnamethylationsignaturetopredictdiseasefreesurvivalinlocallyadvancedrectalcancer AT beißbarthtim identificationofadnamethylationsignaturetopredictdiseasefreesurvivalinlocallyadvancedrectalcancer AT ghadimimichael identificationofadnamethylationsignaturetopredictdiseasefreesurvivalinlocallyadvancedrectalcancer |