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Identifying aggressive prostate cancer foci using a DNA methylation classifier
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 can...
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Published in: | Genome Biology 2017-01, Vol.18 (1), p.3-3, Article 3 |
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creator | Mundbjerg, Kamilla Chopra, Sameer Alemozaffar, Mehrdad Duymich, Christopher Lakshminarasimhan, Ranjani Nichols, Peter W Aron, Manju Siegmund, Kimberly D Ukimura, Osamu Aron, Monish Stern, Mariana Gill, Parkash Carpten, John D Ørntoft, Torben F Sørensen, Karina D Weisenberger, Daniel J Jones, Peter A Duddalwar, Vinay Gill, Inderbir Liang, Gangning |
description | 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. |
doi_str_mv | 10.1186/s13059-016-1129-3 |
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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.</description><identifier>ISSN: 1474-760X</identifier><identifier>ISSN: 1474-7596</identifier><identifier>EISSN: 1474-760X</identifier><identifier>DOI: 10.1186/s13059-016-1129-3</identifier><identifier>PMID: 28081708</identifier><language>eng</language><publisher>England: BioMed Central</publisher><subject>aggression ; Biomarkers, Tumor ; Biopsy ; Cluster Analysis ; Decision making ; Disease Progression ; DNA Methylation ; DNA probes ; early diagnosis ; Epigenesis, Genetic ; Epigenomics - methods ; Gene Expression Profiling ; Humans ; Invasiveness ; Lymph nodes ; Lymphatic Metastasis ; Male ; Metastases ; metastasis ; monitoring ; Neoplasm Metastasis ; Neoplasm Staging ; patients ; Prognosis ; Prostate cancer ; prostatic neoplasms ; Prostatic Neoplasms - genetics ; Prostatic Neoplasms - pathology ; Prostatic Neoplasms - surgery ; Quantitative Trait Loci ; Reproducibility of Results ; Transcriptome ; Tumor Burden ; Tumors</subject><ispartof>Genome Biology, 2017-01, Vol.18 (1), p.3-3, Article 3</ispartof><rights>2017. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>The Author(s). 2017</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c595t-2495892b5570940901181673ec9cf86538fc4b69d993b5b223660363017810d23</citedby><cites>FETCH-LOGICAL-c595t-2495892b5570940901181673ec9cf86538fc4b69d993b5b223660363017810d23</cites><orcidid>0000-0001-8664-922X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5234101/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2208008847?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,25731,27901,27902,36989,36990,44566,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28081708$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Mundbjerg, Kamilla</creatorcontrib><creatorcontrib>Chopra, Sameer</creatorcontrib><creatorcontrib>Alemozaffar, Mehrdad</creatorcontrib><creatorcontrib>Duymich, Christopher</creatorcontrib><creatorcontrib>Lakshminarasimhan, Ranjani</creatorcontrib><creatorcontrib>Nichols, Peter W</creatorcontrib><creatorcontrib>Aron, Manju</creatorcontrib><creatorcontrib>Siegmund, Kimberly D</creatorcontrib><creatorcontrib>Ukimura, Osamu</creatorcontrib><creatorcontrib>Aron, Monish</creatorcontrib><creatorcontrib>Stern, Mariana</creatorcontrib><creatorcontrib>Gill, Parkash</creatorcontrib><creatorcontrib>Carpten, John D</creatorcontrib><creatorcontrib>Ørntoft, Torben F</creatorcontrib><creatorcontrib>Sørensen, Karina D</creatorcontrib><creatorcontrib>Weisenberger, Daniel J</creatorcontrib><creatorcontrib>Jones, Peter A</creatorcontrib><creatorcontrib>Duddalwar, Vinay</creatorcontrib><creatorcontrib>Gill, Inderbir</creatorcontrib><creatorcontrib>Liang, Gangning</creatorcontrib><title>Identifying aggressive prostate cancer foci using a DNA methylation classifier</title><title>Genome Biology</title><addtitle>Genome Biol</addtitle><description>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.</description><subject>aggression</subject><subject>Biomarkers, Tumor</subject><subject>Biopsy</subject><subject>Cluster Analysis</subject><subject>Decision making</subject><subject>Disease Progression</subject><subject>DNA Methylation</subject><subject>DNA probes</subject><subject>early diagnosis</subject><subject>Epigenesis, Genetic</subject><subject>Epigenomics - methods</subject><subject>Gene Expression Profiling</subject><subject>Humans</subject><subject>Invasiveness</subject><subject>Lymph nodes</subject><subject>Lymphatic Metastasis</subject><subject>Male</subject><subject>Metastases</subject><subject>metastasis</subject><subject>monitoring</subject><subject>Neoplasm Metastasis</subject><subject>Neoplasm Staging</subject><subject>patients</subject><subject>Prognosis</subject><subject>Prostate cancer</subject><subject>prostatic neoplasms</subject><subject>Prostatic Neoplasms - genetics</subject><subject>Prostatic Neoplasms - pathology</subject><subject>Prostatic Neoplasms - surgery</subject><subject>Quantitative Trait Loci</subject><subject>Reproducibility of Results</subject><subject>Transcriptome</subject><subject>Tumor Burden</subject><subject>Tumors</subject><issn>1474-760X</issn><issn>1474-7596</issn><issn>1474-760X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><recordid>eNqFkc1OGzEUha2qqEDaB2CDRuqmm4F7_Tf2BglR_iQEG5C6szyOJzGazAR7Bilvj0NSlHbDypb83SOf-xFyhHCCqORpQgZCl4CyRKS6ZF_IAfKKl5WEP1937vvkMKVnANScym9knypQWIE6IPe3U98NoVmFblbY2Sz6lMKrL5axT4MdfOFs53wsmt6FYkzvVPH7_rxY-GG-au0Q-q5wrc1TTfDxO9lrbJv8j-05IU9Xl48XN-Xdw_Xtxfld6YQWQ0m5FkrTWogKNAcNuQ7KinmnXaOkYKpxvJZ6qjWrRU0pkxKYZICVQphSNiFnm9zlWC_81OUO0bZmGcPCxpXpbTD_vnRhbmb9qxGUcQTMAb-2AbF_GX0azCIk59vWdr4fk6EAIGilUX6KZhPIJYJgGf35H_rcj7HLmzCUggJQileZwg3l8pJT9M3HvxHMWqzZiDVZrFmLNevk493CHxN_TbI3xSGceQ</recordid><startdate>20170112</startdate><enddate>20170112</enddate><creator>Mundbjerg, Kamilla</creator><creator>Chopra, Sameer</creator><creator>Alemozaffar, Mehrdad</creator><creator>Duymich, Christopher</creator><creator>Lakshminarasimhan, Ranjani</creator><creator>Nichols, Peter W</creator><creator>Aron, Manju</creator><creator>Siegmund, Kimberly D</creator><creator>Ukimura, Osamu</creator><creator>Aron, Monish</creator><creator>Stern, Mariana</creator><creator>Gill, Parkash</creator><creator>Carpten, John D</creator><creator>Ørntoft, Torben F</creator><creator>Sørensen, Karina D</creator><creator>Weisenberger, Daniel J</creator><creator>Jones, Peter A</creator><creator>Duddalwar, Vinay</creator><creator>Gill, Inderbir</creator><creator>Liang, Gangning</creator><general>BioMed Central</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M7P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>7S9</scope><scope>L.6</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0001-8664-922X</orcidid></search><sort><creationdate>20170112</creationdate><title>Identifying aggressive prostate cancer foci using a DNA methylation classifier</title><author>Mundbjerg, Kamilla ; Chopra, Sameer ; Alemozaffar, Mehrdad ; Duymich, Christopher ; Lakshminarasimhan, Ranjani ; Nichols, Peter W ; Aron, Manju ; Siegmund, Kimberly D ; Ukimura, Osamu ; Aron, Monish ; Stern, Mariana ; Gill, Parkash ; Carpten, John D ; Ørntoft, Torben F ; Sørensen, Karina D ; Weisenberger, Daniel J ; Jones, Peter A ; Duddalwar, Vinay ; Gill, Inderbir ; Liang, Gangning</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c595t-2495892b5570940901181673ec9cf86538fc4b69d993b5b223660363017810d23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>aggression</topic><topic>Biomarkers, Tumor</topic><topic>Biopsy</topic><topic>Cluster Analysis</topic><topic>Decision making</topic><topic>Disease Progression</topic><topic>DNA Methylation</topic><topic>DNA probes</topic><topic>early diagnosis</topic><topic>Epigenesis, Genetic</topic><topic>Epigenomics - 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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.</abstract><cop>England</cop><pub>BioMed Central</pub><pmid>28081708</pmid><doi>10.1186/s13059-016-1129-3</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0001-8664-922X</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | aggression Biomarkers, Tumor Biopsy Cluster Analysis Decision making Disease Progression DNA Methylation DNA probes early diagnosis Epigenesis, Genetic Epigenomics - methods Gene Expression Profiling Humans Invasiveness Lymph nodes Lymphatic Metastasis Male Metastases metastasis monitoring Neoplasm Metastasis Neoplasm Staging patients Prognosis Prostate cancer prostatic neoplasms Prostatic Neoplasms - genetics Prostatic Neoplasms - pathology Prostatic Neoplasms - surgery Quantitative Trait Loci Reproducibility of Results Transcriptome Tumor Burden Tumors |
title | Identifying aggressive prostate cancer foci using a DNA methylation classifier |
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