Metabolic heterogeneity signature of primary treatment-naïve prostate cancer
To avoid over- or under-treatment of primary prostate tumours, there is a critical need for molecular signatures to discriminate indolent from aggressive, lethal disease. Reprogrammed energy metabolism is an important hallmark of cancer, and abnormal metabolic characteristics of cancers have been im...
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Veröffentlicht in: | Oncotarget 2017-04, Vol.8 (16), p.25928-25941 |
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creator | Lin, Dong Ettinger, Susan L Qu, Sifeng Xue, Hui Nabavi, Noushin Choi, Stephen Yiu Chuen Bell, Robert H Mo, Fan Haegert, Anne M Gout, Peter W Fleshner, Neil Gleave, Martin E Pollak, Michael Collins, Colin C Wang, Yuzhuo |
description | To avoid over- or under-treatment of primary prostate tumours, there is a critical need for molecular signatures to discriminate indolent from aggressive, lethal disease. Reprogrammed energy metabolism is an important hallmark of cancer, and abnormal metabolic characteristics of cancers have been implicated as potential diagnostic/prognostic signatures. While genomic and transcriptomic heterogeneity of prostate cancer is well documented and associated with tumour progression, less is known about metabolic heterogeneity of the disease. Using a panel of high fidelity patient-derived xenograft (PDX) models derived from hormone-naïve prostate cancer, we demonstrated heterogeneity of expression of genes involved in cellular energetics and macromolecular biosynthesis. Such heterogeneity was also observed in clinical, treatment-naïve prostate cancers by analyzing the transcriptome sequencing data. Importantly, a metabolic gene signature of increased one-carbon metabolism or decreased proline degradation was identified to be associated with significantly decreased biochemical disease-free patient survival. These results suggest that metabolic heterogeneity of hormone-naïve prostate cancer is of biological and clinical importance and motivate further studies to determine the heterogeneity in metabolic flux in the disease that may lead to identification of new signatures for tumour/patient stratification and the development of new strategies and targets for therapy of prostate cancer. |
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Reprogrammed energy metabolism is an important hallmark of cancer, and abnormal metabolic characteristics of cancers have been implicated as potential diagnostic/prognostic signatures. While genomic and transcriptomic heterogeneity of prostate cancer is well documented and associated with tumour progression, less is known about metabolic heterogeneity of the disease. Using a panel of high fidelity patient-derived xenograft (PDX) models derived from hormone-naïve prostate cancer, we demonstrated heterogeneity of expression of genes involved in cellular energetics and macromolecular biosynthesis. Such heterogeneity was also observed in clinical, treatment-naïve prostate cancers by analyzing the transcriptome sequencing data. Importantly, a metabolic gene signature of increased one-carbon metabolism or decreased proline degradation was identified to be associated with significantly decreased biochemical disease-free patient survival. These results suggest that metabolic heterogeneity of hormone-naïve prostate cancer is of biological and clinical importance and motivate further studies to determine the heterogeneity in metabolic flux in the disease that may lead to identification of new signatures for tumour/patient stratification and the development of new strategies and targets for therapy of prostate cancer.</description><identifier>ISSN: 1949-2553</identifier><identifier>EISSN: 1949-2553</identifier><identifier>DOI: 10.18632/oncotarget.15237</identifier><identifier>PMID: 28460430</identifier><language>eng</language><publisher>United States: Impact Journals LLC</publisher><subject>Animals ; Cell Line, Tumor ; Cluster Analysis ; Disease Models, Animal ; Energy Metabolism - genetics ; Gene Expression Profiling ; Heterografts ; High-Throughput Nucleotide Sequencing ; Humans ; Male ; Metabolic Networks and Pathways ; Mice ; Prognosis ; Prostatic Neoplasms - genetics ; Prostatic Neoplasms - metabolism ; Prostatic Neoplasms - mortality ; Prostatic Neoplasms - pathology ; Research Paper ; Transcriptome</subject><ispartof>Oncotarget, 2017-04, Vol.8 (16), p.25928-25941</ispartof><rights>Copyright: © 2017 Lin et al. 2017</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c422t-11f98f1fbb4173c6b36a50e1058f81bd05fb6f24be072f40d2f29625e78b3f143</citedby><cites>FETCH-LOGICAL-c422t-11f98f1fbb4173c6b36a50e1058f81bd05fb6f24be072f40d2f29625e78b3f143</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5432227/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5432227/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,27901,27902,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28460430$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Lin, Dong</creatorcontrib><creatorcontrib>Ettinger, Susan L</creatorcontrib><creatorcontrib>Qu, Sifeng</creatorcontrib><creatorcontrib>Xue, Hui</creatorcontrib><creatorcontrib>Nabavi, Noushin</creatorcontrib><creatorcontrib>Choi, Stephen Yiu Chuen</creatorcontrib><creatorcontrib>Bell, Robert H</creatorcontrib><creatorcontrib>Mo, Fan</creatorcontrib><creatorcontrib>Haegert, Anne M</creatorcontrib><creatorcontrib>Gout, Peter W</creatorcontrib><creatorcontrib>Fleshner, Neil</creatorcontrib><creatorcontrib>Gleave, Martin E</creatorcontrib><creatorcontrib>Pollak, Michael</creatorcontrib><creatorcontrib>Collins, Colin C</creatorcontrib><creatorcontrib>Wang, Yuzhuo</creatorcontrib><title>Metabolic heterogeneity signature of primary treatment-naïve prostate cancer</title><title>Oncotarget</title><addtitle>Oncotarget</addtitle><description>To avoid over- or under-treatment of primary prostate tumours, there is a critical need for molecular signatures to discriminate indolent from aggressive, lethal disease. Reprogrammed energy metabolism is an important hallmark of cancer, and abnormal metabolic characteristics of cancers have been implicated as potential diagnostic/prognostic signatures. While genomic and transcriptomic heterogeneity of prostate cancer is well documented and associated with tumour progression, less is known about metabolic heterogeneity of the disease. Using a panel of high fidelity patient-derived xenograft (PDX) models derived from hormone-naïve prostate cancer, we demonstrated heterogeneity of expression of genes involved in cellular energetics and macromolecular biosynthesis. Such heterogeneity was also observed in clinical, treatment-naïve prostate cancers by analyzing the transcriptome sequencing data. Importantly, a metabolic gene signature of increased one-carbon metabolism or decreased proline degradation was identified to be associated with significantly decreased biochemical disease-free patient survival. These results suggest that metabolic heterogeneity of hormone-naïve prostate cancer is of biological and clinical importance and motivate further studies to determine the heterogeneity in metabolic flux in the disease that may lead to identification of new signatures for tumour/patient stratification and the development of new strategies and targets for therapy of prostate cancer.</description><subject>Animals</subject><subject>Cell Line, Tumor</subject><subject>Cluster Analysis</subject><subject>Disease Models, Animal</subject><subject>Energy Metabolism - genetics</subject><subject>Gene Expression Profiling</subject><subject>Heterografts</subject><subject>High-Throughput Nucleotide Sequencing</subject><subject>Humans</subject><subject>Male</subject><subject>Metabolic Networks and Pathways</subject><subject>Mice</subject><subject>Prognosis</subject><subject>Prostatic Neoplasms - genetics</subject><subject>Prostatic Neoplasms - metabolism</subject><subject>Prostatic Neoplasms - mortality</subject><subject>Prostatic Neoplasms - pathology</subject><subject>Research Paper</subject><subject>Transcriptome</subject><issn>1949-2553</issn><issn>1949-2553</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNpVUctOwzAQtBCIVqUfwAXlyCXFzzwuSKjiJbXiAmfLdtdpUBIX263Ur-Ij-DGitkDZy640u7OzOwhdEjwhRcbojeuMi8pXECdEUJafoCEpeZlSIdjpUT1A4xDecR-C5wUtz9GAFjzDnOEhms8hKu2a2iRLiOBdBR3UcZuEuupUXHtInE1Wvm6V3ybRg4otdDHt1NfnBnrAhagiJEZ1BvwFOrOqCTA-5BF6e7h_nT6ls5fH5-ndLDWc0pgSYsvCEqs1JzkzmWaZEhgIFoUtiF5gYXVmKdeAc2o5XlBLy4wKyAvNLOFshG73vKu1bmFhekVeNfIgUzpVy_9IVy9l5TZScEYpzXuC6wOBdx9rCFG2dTDQNKoDtw6SFCUXlGQE961k32r6W4MH-7uGYLlzQv45IXdO9DNXx_p-J37-zr4BGnuKJA</recordid><startdate>20170418</startdate><enddate>20170418</enddate><creator>Lin, Dong</creator><creator>Ettinger, Susan L</creator><creator>Qu, Sifeng</creator><creator>Xue, Hui</creator><creator>Nabavi, Noushin</creator><creator>Choi, Stephen Yiu Chuen</creator><creator>Bell, Robert H</creator><creator>Mo, Fan</creator><creator>Haegert, Anne M</creator><creator>Gout, Peter W</creator><creator>Fleshner, Neil</creator><creator>Gleave, Martin E</creator><creator>Pollak, Michael</creator><creator>Collins, Colin C</creator><creator>Wang, Yuzhuo</creator><general>Impact Journals LLC</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>7X8</scope><scope>5PM</scope></search><sort><creationdate>20170418</creationdate><title>Metabolic heterogeneity signature of primary treatment-naïve prostate cancer</title><author>Lin, Dong ; Ettinger, Susan L ; Qu, Sifeng ; Xue, Hui ; Nabavi, Noushin ; Choi, Stephen Yiu Chuen ; Bell, Robert H ; Mo, Fan ; Haegert, Anne M ; Gout, Peter W ; Fleshner, Neil ; Gleave, Martin E ; Pollak, Michael ; Collins, Colin C ; Wang, Yuzhuo</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c422t-11f98f1fbb4173c6b36a50e1058f81bd05fb6f24be072f40d2f29625e78b3f143</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Animals</topic><topic>Cell Line, Tumor</topic><topic>Cluster Analysis</topic><topic>Disease Models, Animal</topic><topic>Energy Metabolism - genetics</topic><topic>Gene Expression Profiling</topic><topic>Heterografts</topic><topic>High-Throughput Nucleotide Sequencing</topic><topic>Humans</topic><topic>Male</topic><topic>Metabolic Networks and Pathways</topic><topic>Mice</topic><topic>Prognosis</topic><topic>Prostatic Neoplasms - genetics</topic><topic>Prostatic Neoplasms - metabolism</topic><topic>Prostatic Neoplasms - mortality</topic><topic>Prostatic Neoplasms - pathology</topic><topic>Research Paper</topic><topic>Transcriptome</topic><toplevel>online_resources</toplevel><creatorcontrib>Lin, Dong</creatorcontrib><creatorcontrib>Ettinger, Susan L</creatorcontrib><creatorcontrib>Qu, Sifeng</creatorcontrib><creatorcontrib>Xue, Hui</creatorcontrib><creatorcontrib>Nabavi, Noushin</creatorcontrib><creatorcontrib>Choi, Stephen Yiu Chuen</creatorcontrib><creatorcontrib>Bell, Robert H</creatorcontrib><creatorcontrib>Mo, Fan</creatorcontrib><creatorcontrib>Haegert, Anne M</creatorcontrib><creatorcontrib>Gout, Peter W</creatorcontrib><creatorcontrib>Fleshner, Neil</creatorcontrib><creatorcontrib>Gleave, Martin E</creatorcontrib><creatorcontrib>Pollak, Michael</creatorcontrib><creatorcontrib>Collins, Colin C</creatorcontrib><creatorcontrib>Wang, Yuzhuo</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><collection>PubMed Central (Full Participant titles)</collection><jtitle>Oncotarget</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lin, Dong</au><au>Ettinger, Susan L</au><au>Qu, Sifeng</au><au>Xue, Hui</au><au>Nabavi, Noushin</au><au>Choi, Stephen Yiu Chuen</au><au>Bell, Robert H</au><au>Mo, Fan</au><au>Haegert, Anne M</au><au>Gout, Peter W</au><au>Fleshner, Neil</au><au>Gleave, Martin E</au><au>Pollak, Michael</au><au>Collins, Colin C</au><au>Wang, Yuzhuo</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Metabolic heterogeneity signature of primary treatment-naïve prostate cancer</atitle><jtitle>Oncotarget</jtitle><addtitle>Oncotarget</addtitle><date>2017-04-18</date><risdate>2017</risdate><volume>8</volume><issue>16</issue><spage>25928</spage><epage>25941</epage><pages>25928-25941</pages><issn>1949-2553</issn><eissn>1949-2553</eissn><abstract>To avoid over- or under-treatment of primary prostate tumours, there is a critical need for molecular signatures to discriminate indolent from aggressive, lethal disease. Reprogrammed energy metabolism is an important hallmark of cancer, and abnormal metabolic characteristics of cancers have been implicated as potential diagnostic/prognostic signatures. While genomic and transcriptomic heterogeneity of prostate cancer is well documented and associated with tumour progression, less is known about metabolic heterogeneity of the disease. Using a panel of high fidelity patient-derived xenograft (PDX) models derived from hormone-naïve prostate cancer, we demonstrated heterogeneity of expression of genes involved in cellular energetics and macromolecular biosynthesis. Such heterogeneity was also observed in clinical, treatment-naïve prostate cancers by analyzing the transcriptome sequencing data. Importantly, a metabolic gene signature of increased one-carbon metabolism or decreased proline degradation was identified to be associated with significantly decreased biochemical disease-free patient survival. 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subjects | Animals Cell Line, Tumor Cluster Analysis Disease Models, Animal Energy Metabolism - genetics Gene Expression Profiling Heterografts High-Throughput Nucleotide Sequencing Humans Male Metabolic Networks and Pathways Mice Prognosis Prostatic Neoplasms - genetics Prostatic Neoplasms - metabolism Prostatic Neoplasms - mortality Prostatic Neoplasms - pathology Research Paper Transcriptome |
title | Metabolic heterogeneity signature of primary treatment-naïve prostate cancer |
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