Phenotype-independent DNA methylation changes in prostate cancer View Full Text


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Article Info

DATE

2018-10

AUTHORS

Davide Pellacani, Alastair P. Droop, Fiona M. Frame, Matthew S. Simms, Vincent M. Mann, Anne T. Collins, Connie J. Eaves, Norman J. Maitland

ABSTRACT

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. More... »

PAGES

1133-1143

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/s41416-018-0236-1

    DOI

    http://dx.doi.org/10.1038/s41416-018-0236-1

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1107542081

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/30318509


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    curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1038/s41416-018-0236-1'

    N-Triples is a line-based linked data format ideal for batch operations.

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/s41416-018-0236-1'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/s41416-018-0236-1'

    RDF/XML is a standard XML format for linked data.

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