Human prostate cancers display numerous DNA methylation changes compared to normal tissue samples. However, definitive identification of features related to the cells’ malignant status has been compromised by the predominance of cells with luminal features in prostate cancers.
We generated genome-wide DNA methylation profiles of cell subpopulations with basal or luminal features isolated from matched prostate cancer and normal tissue samples.
Many frequent DNA methylation changes previously attributed to prostate cancers are here identified as differences between luminal and basal cells in both normal and cancer samples. We also identified changes unique to each of the two cancer subpopulations. Those specific to cancer luminal cells were associated with regulation of metabolic processes, cell proliferation and epithelial development. Within the prostate cancer TCGA dataset, these changes were able to distinguish not only cancers from normal samples, but also organ-confined cancers from those with extraprostatic extensions. Using changes present in both basal and luminal cancer cells, we derived a new 17-CpG prostate cancer signature with high predictive power in the TCGA dataset.
This study demonstrates the importance of comparing phenotypically matched prostate cell populations from normal and cancer tissues to unmask biologically and clinically relevant DNA methylation changes.
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Ethics approval and consent to participate:The study was conducted in accordance with the Declaration of Helsinki. All participating patients allowed the use of their medical records for clinical research purposes (if alive at the time of data collection). As an observational study, no approval ethics approval was required.
Consent for publication:this manuscript does not contain any individual person’s data.
Note: This work is published under the standard license to publish agreement. After 12 months the work will become freely available and the license terms will switch to a Creative Commons Attribution-NonCommercial-Share Alike 4.0 Unported License)
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The authors thank the urology surgeons and patients from Castle Hill Hospital for kind donations of clinical prostate samples. We thank Artem Babaian, Rod Docking, Dr. Kieran O Neill, Hye-Jung E. Chun, Dr. Misha Bilenky, Dr. Alireza Heravi-Moussavi and Dr. Martin Hirst for the useful discussions regarding the bioinformatic analyses conducted in this study.
D.P. and N.J.M. designed the project. M.S.S. and V.M.M. procured the tissue samples. D.P. processed and sorted the tissue samples, and performed all other experiments. D.P., F.M.F. and A.T.C. developed the tissue processing and sorting protocol. D.P. and A.P.D. conducted all bioinformatic analyses. D.P., C.J.E. and N.J.M. wrote the manuscript. All authors contributed to the interpretation of the results and read and approved the manuscript.