Title |
Identifying aggressive prostate cancer foci using a DNA methylation classifier
|
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Published in |
Genome Biology, January 2017
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DOI | 10.1186/s13059-016-1129-3 |
Pubmed ID | |
Authors |
Kamilla Mundbjerg, Sameer Chopra, Mehrdad Alemozaffar, Christopher Duymich, Ranjani Lakshminarasimhan, Peter W. Nichols, Manju Aron, Kimberly D. Siegmund, Osamu Ukimura, Monish Aron, Mariana Stern, Parkash Gill, John D. Carpten, Torben F. Ørntoft, Karina D. Sørensen, Daniel J. Weisenberger, Peter A. Jones, Vinay Duddalwar, Inderbir Gill, Gangning Liang |
Abstract |
Slow-growing prostate cancer (PC) can be aggressive in a subset of cases. Therefore, prognostic tools to guide clinical decision-making and avoid overtreatment of indolent PC and undertreatment of aggressive disease are urgently needed. PC has a propensity to be multifocal with several different cancerous foci per gland. Here, we have taken advantage of the multifocal propensity of PC and categorized aggressiveness of individual PC foci based on DNA methylation patterns in primary PC foci and matched lymph node metastases. In a set of 14 patients, we demonstrate that over half of the cases have multiple epigenetically distinct subclones and determine the primary subclone from which the metastatic lesion(s) originated. Furthermore, we develop an aggressiveness classifier consisting of 25 DNA methylation probes to determine aggressive and non-aggressive subclones. Upon validation of the classifier in an independent cohort, the predicted aggressive tumors are significantly associated with the presence of lymph node metastases and invasive tumor stages. Overall, this study provides molecular-based support for determining PC aggressiveness with the potential to impact clinical decision-making, such as targeted biopsy approaches for early diagnosis and active surveillance, in addition to focal therapy. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United Kingdom | 1 | 33% |
Unknown | 2 | 67% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 2 | 67% |
Scientists | 1 | 33% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Germany | 1 | 2% |
Unknown | 58 | 98% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Bachelor | 12 | 20% |
Researcher | 11 | 19% |
Student > Ph. D. Student | 9 | 15% |
Student > Doctoral Student | 4 | 7% |
Student > Master | 4 | 7% |
Other | 10 | 17% |
Unknown | 9 | 15% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 22 | 37% |
Biochemistry, Genetics and Molecular Biology | 7 | 12% |
Agricultural and Biological Sciences | 7 | 12% |
Computer Science | 3 | 5% |
Business, Management and Accounting | 2 | 3% |
Other | 6 | 10% |
Unknown | 12 | 20% |