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Phenotype-independent DNA methylation changes in prostate cancer

BACKGROUND: 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. METHODS: W...

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Detalles Bibliográficos
Autores principales: Pellacani, Davide, Droop, Alastair P., Frame, Fiona M., Simms, Matthew S., Mann, Vincent M., Collins, Anne T., Eaves, Connie J., Maitland, Norman J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6219500/
https://www.ncbi.nlm.nih.gov/pubmed/30318509
http://dx.doi.org/10.1038/s41416-018-0236-1
Descripción
Sumario:BACKGROUND: 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. METHODS: We generated genome-wide DNA methylation profiles of cell subpopulations with basal or luminal features isolated from matched prostate cancer and normal tissue samples. RESULTS: 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. CONCLUSIONS: 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.