DNA methylation-based chromatin compartments and ChIP-seq profiles reveal transcriptional drivers of prostate carcinogenesis
File(s)
Published version
Author(s)
Simmonds, P
Loomis, E
Curry, E
Type
Journal Article
Abstract
Background – Profiles of DNA methylation of many tissues relevant in human disease have been obtained from microarrays and are publically available. These can be used to generate maps of chromatin compartmentalization, demarcating open and closed chromatin genome-wide. Additionally, large sets of genome-wide transcription factor binding profiles have been made available thanks to ChIP-seq technology.
Methods – We have identified genomic regions with altered chromatin compartmentalization in prostate adenocarcinoma tissue relative to normal prostate tissue, using DNA methylation microarray data from The Cancer Genome Atlas. DNA binding profiles from ENCODE ChIP-seq studies have been systematically screened to find transcription factors with inferred DNA-binding sites located in discordantly open/closed chromatin in malignant tissue (compared with non-cancer control tissue). We have combined this with tests for corresponding up-/down-regulation of the transcription factors' putative target genes to obtain an integrated measure of cancer-specific regulatory activity to identify likely transcriptional drivers of prostate cancer.
Results – Generally, we find that the degree to which transcription factors preferentially bind regions of chromatin that become more accessible during prostate carcinogenesis is significantly associated to the level of systematic upregulation of their targets, at the level of gene expression. Our approach has yielded 11 transcription factors that show strong cancer-specific transcriptional activation of targets, including the novel candidates KAT2A and TRIM28, alongside established drivers of prostate cancer MYC, ETS1, GABP and YY1.
Conclusions – This approach to integrated epigenetic and transcriptional profiling using publically available data represents a cheap and powerful technique for identifying potential drivers of human disease. In our application to prostate adenocarcinoma data, the fact that well known drivers are among the top candidates suggests that the discovery of novel candidate drivers may unlock pathways to future medicines.
Methods – We have identified genomic regions with altered chromatin compartmentalization in prostate adenocarcinoma tissue relative to normal prostate tissue, using DNA methylation microarray data from The Cancer Genome Atlas. DNA binding profiles from ENCODE ChIP-seq studies have been systematically screened to find transcription factors with inferred DNA-binding sites located in discordantly open/closed chromatin in malignant tissue (compared with non-cancer control tissue). We have combined this with tests for corresponding up-/down-regulation of the transcription factors' putative target genes to obtain an integrated measure of cancer-specific regulatory activity to identify likely transcriptional drivers of prostate cancer.
Results – Generally, we find that the degree to which transcription factors preferentially bind regions of chromatin that become more accessible during prostate carcinogenesis is significantly associated to the level of systematic upregulation of their targets, at the level of gene expression. Our approach has yielded 11 transcription factors that show strong cancer-specific transcriptional activation of targets, including the novel candidates KAT2A and TRIM28, alongside established drivers of prostate cancer MYC, ETS1, GABP and YY1.
Conclusions – This approach to integrated epigenetic and transcriptional profiling using publically available data represents a cheap and powerful technique for identifying potential drivers of human disease. In our application to prostate adenocarcinoma data, the fact that well known drivers are among the top candidates suggests that the discovery of novel candidate drivers may unlock pathways to future medicines.
Date Issued
2017-06-07
Date Acceptance
2017-05-23
Citation
Genome Medicine, 2017, 9
ISSN
1756-994X
Publisher
BioMed Central
Journal / Book Title
Genome Medicine
Volume
9
Copyright Statement
© The Author(s). 2017. Open Access
This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Subjects
0604 Genetics
1103 Clinical Sciences
Publication Status
Published
Article Number
54