The Landscape of Prognostic Outlier Genes in High-Risk Prostate Cancer
There is a clear need to improve risk stratification and to identify novel therapeutic targets in aggressive prostate cancer. The goal of this study was to investigate genes with outlier expression with prognostic association in high-risk prostate cancer patients as potential biomarkers and drug tar...
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| Veröffentlicht in: | Clinical cancer research 2016-04, Vol.22 (7), p.1777-1786 |
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| creator | Zhao, Shuang G Evans, Joseph R Kothari, Vishal Sun, Grace Larm, Ashley Mondine, Victor Schaeffer, Edward M Ross, Ashley E Klein, Eric A Den, Robert B Dicker, Adam P Karnes, R Jeffrey Erho, Nicholas Nguyen, Paul L Davicioni, Elai Feng, Felix Y |
| description | There is a clear need to improve risk stratification and to identify novel therapeutic targets in aggressive prostate cancer. The goal of this study was to investigate genes with outlier expression with prognostic association in high-risk prostate cancer patients as potential biomarkers and drug targets.
We interrogated microarray gene expression data from prostatectomy samples from 545 high-risk prostate cancer patients with long-term follow-up (mean 13.4 years). Three independent clinical datasets totaling an additional 545 patients were used for validation. Novel prognostic outlier genes were interrogated for impact on oncogenic phenotypes in vitro using siRNA-based knockdown. Association with clinical outcomes and comparison with existing prognostic instruments was assessed with multivariable models using a prognostic outlier score.
Analysis of the discovery cohort identified 20 prognostic outlier genes. Three top prognostic outlier genes were novel prostate cancer genes; NVL, SMC4, or SQLE knockdown reduced migration and/or invasion and outlier expression was significantly associated with poor prognosis. Increased prognostic outlier score was significantly associated with poor prognosis independent of standard clinicopathologic variables. Finally, the prognostic outlier score prognostic association is independent of, and adds to existing genomic and clinical tools for prognostication in prostate cancer (Decipher, the cell-cycle progression signature, and CAPRA-S).
To our knowledge, this study represents the first unbiased high-throughput investigation of prognostic outlier genes in prostate cancer and demonstrates the potential biomarker and therapeutic importance of this previously unstudied class of cancer genes. |
| doi_str_mv | 10.1158/1078-0432.ccr-15-1250 |
| format | Article |
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We interrogated microarray gene expression data from prostatectomy samples from 545 high-risk prostate cancer patients with long-term follow-up (mean 13.4 years). Three independent clinical datasets totaling an additional 545 patients were used for validation. Novel prognostic outlier genes were interrogated for impact on oncogenic phenotypes in vitro using siRNA-based knockdown. Association with clinical outcomes and comparison with existing prognostic instruments was assessed with multivariable models using a prognostic outlier score.
Analysis of the discovery cohort identified 20 prognostic outlier genes. Three top prognostic outlier genes were novel prostate cancer genes; NVL, SMC4, or SQLE knockdown reduced migration and/or invasion and outlier expression was significantly associated with poor prognosis. Increased prognostic outlier score was significantly associated with poor prognosis independent of standard clinicopathologic variables. Finally, the prognostic outlier score prognostic association is independent of, and adds to existing genomic and clinical tools for prognostication in prostate cancer (Decipher, the cell-cycle progression signature, and CAPRA-S).
To our knowledge, this study represents the first unbiased high-throughput investigation of prognostic outlier genes in prostate cancer and demonstrates the potential biomarker and therapeutic importance of this previously unstudied class of cancer genes.</description><identifier>ISSN: 1078-0432</identifier><identifier>EISSN: 1557-3265</identifier><identifier>DOI: 10.1158/1078-0432.ccr-15-1250</identifier><identifier>PMID: 26631616</identifier><language>eng</language><publisher>United States</publisher><subject>Biomarkers, Tumor ; Case-Control Studies ; Cell Line, Tumor ; Follow-Up Studies ; Gene Expression Profiling ; Gene Expression Regulation, Neoplastic ; Humans ; Kaplan-Meier Estimate ; Male ; Neoplasm Grading ; Neoplasm Metastasis ; Neoplasm Staging ; Prognosis ; Prostatic Neoplasms - diagnosis ; Prostatic Neoplasms - genetics ; Prostatic Neoplasms - mortality ; Prostatic Neoplasms - surgery ; Reproducibility of Results ; Sensitivity and Specificity</subject><ispartof>Clinical cancer research, 2016-04, Vol.22 (7), p.1777-1786</ispartof><rights>2015 American Association for Cancer Research.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c422t-8c23436ccad343fa138e5d75354082a47639149c4f84ff5606fbcc6678b8cd43</citedby><cites>FETCH-LOGICAL-c422t-8c23436ccad343fa138e5d75354082a47639149c4f84ff5606fbcc6678b8cd43</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,3356,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26631616$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Zhao, Shuang G</creatorcontrib><creatorcontrib>Evans, Joseph R</creatorcontrib><creatorcontrib>Kothari, Vishal</creatorcontrib><creatorcontrib>Sun, Grace</creatorcontrib><creatorcontrib>Larm, Ashley</creatorcontrib><creatorcontrib>Mondine, Victor</creatorcontrib><creatorcontrib>Schaeffer, Edward M</creatorcontrib><creatorcontrib>Ross, Ashley E</creatorcontrib><creatorcontrib>Klein, Eric A</creatorcontrib><creatorcontrib>Den, Robert B</creatorcontrib><creatorcontrib>Dicker, Adam P</creatorcontrib><creatorcontrib>Karnes, R Jeffrey</creatorcontrib><creatorcontrib>Erho, Nicholas</creatorcontrib><creatorcontrib>Nguyen, Paul L</creatorcontrib><creatorcontrib>Davicioni, Elai</creatorcontrib><creatorcontrib>Feng, Felix Y</creatorcontrib><title>The Landscape of Prognostic Outlier Genes in High-Risk Prostate Cancer</title><title>Clinical cancer research</title><addtitle>Clin Cancer Res</addtitle><description>There is a clear need to improve risk stratification and to identify novel therapeutic targets in aggressive prostate cancer. The goal of this study was to investigate genes with outlier expression with prognostic association in high-risk prostate cancer patients as potential biomarkers and drug targets.
We interrogated microarray gene expression data from prostatectomy samples from 545 high-risk prostate cancer patients with long-term follow-up (mean 13.4 years). Three independent clinical datasets totaling an additional 545 patients were used for validation. Novel prognostic outlier genes were interrogated for impact on oncogenic phenotypes in vitro using siRNA-based knockdown. Association with clinical outcomes and comparison with existing prognostic instruments was assessed with multivariable models using a prognostic outlier score.
Analysis of the discovery cohort identified 20 prognostic outlier genes. Three top prognostic outlier genes were novel prostate cancer genes; NVL, SMC4, or SQLE knockdown reduced migration and/or invasion and outlier expression was significantly associated with poor prognosis. Increased prognostic outlier score was significantly associated with poor prognosis independent of standard clinicopathologic variables. Finally, the prognostic outlier score prognostic association is independent of, and adds to existing genomic and clinical tools for prognostication in prostate cancer (Decipher, the cell-cycle progression signature, and CAPRA-S).
To our knowledge, this study represents the first unbiased high-throughput investigation of prognostic outlier genes in prostate cancer and demonstrates the potential biomarker and therapeutic importance of this previously unstudied class of cancer genes.</description><subject>Biomarkers, Tumor</subject><subject>Case-Control Studies</subject><subject>Cell Line, Tumor</subject><subject>Follow-Up Studies</subject><subject>Gene Expression Profiling</subject><subject>Gene Expression Regulation, Neoplastic</subject><subject>Humans</subject><subject>Kaplan-Meier Estimate</subject><subject>Male</subject><subject>Neoplasm Grading</subject><subject>Neoplasm Metastasis</subject><subject>Neoplasm Staging</subject><subject>Prognosis</subject><subject>Prostatic Neoplasms - diagnosis</subject><subject>Prostatic Neoplasms - genetics</subject><subject>Prostatic Neoplasms - mortality</subject><subject>Prostatic Neoplasms - surgery</subject><subject>Reproducibility of Results</subject><subject>Sensitivity and Specificity</subject><issn>1078-0432</issn><issn>1557-3265</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNo9kE1PwkAQhjdGI4j-BM0evazu7DdH0wiYkGAI982y3YVqabHbHvz3tgE8vXN43pnJg9Aj0BcAaV6BakOo4OzF-4aAJMAkvUJjkFITzpS87ucLM0J3KX1RCgKouEUjphQHBWqMZpt9wEtX5cm7Y8B1xJ9Nvavq1BYer7q2LEKD56EKCRcVXhS7PVkX6XugUuvagDNX-dDco5voyhQezjlBm9n7JluQ5Wr-kb0tiReMtcR4xgVX3ru8z-iAmyBzLbkU1DAntOJTEFMvohExSkVV3HqvlDZb43PBJ-j5tPbY1D9dSK09FMmHsnRVqLtkQWs9NQBU9ag8ob7_NDUh2mNTHFzza4HawaAd7NjBjs2ytQVpB4N97-l8otseQv7fuijjf73raug</recordid><startdate>20160401</startdate><enddate>20160401</enddate><creator>Zhao, Shuang G</creator><creator>Evans, Joseph R</creator><creator>Kothari, Vishal</creator><creator>Sun, Grace</creator><creator>Larm, Ashley</creator><creator>Mondine, Victor</creator><creator>Schaeffer, Edward M</creator><creator>Ross, Ashley E</creator><creator>Klein, Eric A</creator><creator>Den, Robert B</creator><creator>Dicker, Adam P</creator><creator>Karnes, R Jeffrey</creator><creator>Erho, Nicholas</creator><creator>Nguyen, Paul L</creator><creator>Davicioni, Elai</creator><creator>Feng, Felix Y</creator><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>7X8</scope></search><sort><creationdate>20160401</creationdate><title>The Landscape of Prognostic Outlier Genes in High-Risk Prostate Cancer</title><author>Zhao, Shuang G ; Evans, Joseph R ; Kothari, Vishal ; Sun, Grace ; Larm, Ashley ; Mondine, Victor ; Schaeffer, Edward M ; Ross, Ashley E ; Klein, Eric A ; Den, Robert B ; Dicker, Adam P ; Karnes, R Jeffrey ; Erho, Nicholas ; Nguyen, Paul L ; Davicioni, Elai ; Feng, Felix Y</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c422t-8c23436ccad343fa138e5d75354082a47639149c4f84ff5606fbcc6678b8cd43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Biomarkers, Tumor</topic><topic>Case-Control Studies</topic><topic>Cell Line, Tumor</topic><topic>Follow-Up Studies</topic><topic>Gene Expression Profiling</topic><topic>Gene Expression Regulation, Neoplastic</topic><topic>Humans</topic><topic>Kaplan-Meier Estimate</topic><topic>Male</topic><topic>Neoplasm Grading</topic><topic>Neoplasm Metastasis</topic><topic>Neoplasm Staging</topic><topic>Prognosis</topic><topic>Prostatic Neoplasms - diagnosis</topic><topic>Prostatic Neoplasms - genetics</topic><topic>Prostatic Neoplasms - mortality</topic><topic>Prostatic Neoplasms - surgery</topic><topic>Reproducibility of Results</topic><topic>Sensitivity and Specificity</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhao, Shuang G</creatorcontrib><creatorcontrib>Evans, Joseph R</creatorcontrib><creatorcontrib>Kothari, Vishal</creatorcontrib><creatorcontrib>Sun, Grace</creatorcontrib><creatorcontrib>Larm, Ashley</creatorcontrib><creatorcontrib>Mondine, Victor</creatorcontrib><creatorcontrib>Schaeffer, Edward M</creatorcontrib><creatorcontrib>Ross, Ashley E</creatorcontrib><creatorcontrib>Klein, Eric A</creatorcontrib><creatorcontrib>Den, Robert B</creatorcontrib><creatorcontrib>Dicker, Adam P</creatorcontrib><creatorcontrib>Karnes, R Jeffrey</creatorcontrib><creatorcontrib>Erho, Nicholas</creatorcontrib><creatorcontrib>Nguyen, Paul L</creatorcontrib><creatorcontrib>Davicioni, Elai</creatorcontrib><creatorcontrib>Feng, Felix Y</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Clinical cancer research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhao, Shuang G</au><au>Evans, Joseph R</au><au>Kothari, Vishal</au><au>Sun, Grace</au><au>Larm, Ashley</au><au>Mondine, Victor</au><au>Schaeffer, Edward M</au><au>Ross, Ashley E</au><au>Klein, Eric A</au><au>Den, Robert B</au><au>Dicker, Adam P</au><au>Karnes, R Jeffrey</au><au>Erho, Nicholas</au><au>Nguyen, Paul L</au><au>Davicioni, Elai</au><au>Feng, Felix Y</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The Landscape of Prognostic Outlier Genes in High-Risk Prostate Cancer</atitle><jtitle>Clinical cancer research</jtitle><addtitle>Clin Cancer Res</addtitle><date>2016-04-01</date><risdate>2016</risdate><volume>22</volume><issue>7</issue><spage>1777</spage><epage>1786</epage><pages>1777-1786</pages><issn>1078-0432</issn><eissn>1557-3265</eissn><abstract>There is a clear need to improve risk stratification and to identify novel therapeutic targets in aggressive prostate cancer. The goal of this study was to investigate genes with outlier expression with prognostic association in high-risk prostate cancer patients as potential biomarkers and drug targets.
We interrogated microarray gene expression data from prostatectomy samples from 545 high-risk prostate cancer patients with long-term follow-up (mean 13.4 years). Three independent clinical datasets totaling an additional 545 patients were used for validation. Novel prognostic outlier genes were interrogated for impact on oncogenic phenotypes in vitro using siRNA-based knockdown. Association with clinical outcomes and comparison with existing prognostic instruments was assessed with multivariable models using a prognostic outlier score.
Analysis of the discovery cohort identified 20 prognostic outlier genes. Three top prognostic outlier genes were novel prostate cancer genes; NVL, SMC4, or SQLE knockdown reduced migration and/or invasion and outlier expression was significantly associated with poor prognosis. Increased prognostic outlier score was significantly associated with poor prognosis independent of standard clinicopathologic variables. Finally, the prognostic outlier score prognostic association is independent of, and adds to existing genomic and clinical tools for prognostication in prostate cancer (Decipher, the cell-cycle progression signature, and CAPRA-S).
To our knowledge, this study represents the first unbiased high-throughput investigation of prognostic outlier genes in prostate cancer and demonstrates the potential biomarker and therapeutic importance of this previously unstudied class of cancer genes.</abstract><cop>United States</cop><pmid>26631616</pmid><doi>10.1158/1078-0432.ccr-15-1250</doi><tpages>10</tpages><oa>free_for_read</oa></addata></record> |
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| source | MEDLINE; American Association for Cancer Research; EZB-FREE-00999 freely available EZB journals; Alma/SFX Local Collection |
| subjects | Biomarkers, Tumor Case-Control Studies Cell Line, Tumor Follow-Up Studies Gene Expression Profiling Gene Expression Regulation, Neoplastic Humans Kaplan-Meier Estimate Male Neoplasm Grading Neoplasm Metastasis Neoplasm Staging Prognosis Prostatic Neoplasms - diagnosis Prostatic Neoplasms - genetics Prostatic Neoplasms - mortality Prostatic Neoplasms - surgery Reproducibility of Results Sensitivity and Specificity |
| title | The Landscape of Prognostic Outlier Genes in High-Risk Prostate Cancer |
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