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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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Autores principales: Lin, Dong, Ettinger, Susan L., Qu, Sifeng, Xue, Hui, Nabavi, Noushin, Chuen Choi, Stephen Yiu, Bell, Robert H., Mo, Fan, Haegert, Anne M., Gout, Peter W., Fleshner, Neil, Gleave, Martin E., Pollak, Michael, Collins, Colin C., Wang, Yuzhuo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5432227/
https://www.ncbi.nlm.nih.gov/pubmed/28460430
http://dx.doi.org/10.18632/oncotarget.15237
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author Lin, Dong
Ettinger, Susan L.
Qu, Sifeng
Xue, Hui
Nabavi, Noushin
Chuen Choi, Stephen Yiu
Bell, Robert H.
Mo, Fan
Haegert, Anne M.
Gout, Peter W.
Fleshner, Neil
Gleave, Martin E.
Pollak, Michael
Collins, Colin C.
Wang, Yuzhuo
author_facet Lin, Dong
Ettinger, Susan L.
Qu, Sifeng
Xue, Hui
Nabavi, Noushin
Chuen Choi, Stephen Yiu
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 Lin, Dong
collection PubMed
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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spelling pubmed-54322272017-05-17 Metabolic heterogeneity signature of primary treatment-naïve prostate cancer Lin, Dong Ettinger, Susan L. Qu, Sifeng Xue, Hui Nabavi, Noushin Chuen Choi, Stephen Yiu Bell, Robert H. Mo, Fan Haegert, Anne M. Gout, Peter W. Fleshner, Neil Gleave, Martin E. Pollak, Michael Collins, Colin C. Wang, Yuzhuo Oncotarget Research Paper 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. Impact Journals LLC 2017-02-09 /pmc/articles/PMC5432227/ /pubmed/28460430 http://dx.doi.org/10.18632/oncotarget.15237 Text en Copyright: © 2017 Lin et al. http://creativecommons.org/licenses/by/3.0/ This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) (CC-BY), which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Research Paper
Lin, Dong
Ettinger, Susan L.
Qu, Sifeng
Xue, Hui
Nabavi, Noushin
Chuen Choi, Stephen Yiu
Bell, Robert H.
Mo, Fan
Haegert, Anne M.
Gout, Peter W.
Fleshner, Neil
Gleave, Martin E.
Pollak, Michael
Collins, Colin C.
Wang, Yuzhuo
Metabolic heterogeneity signature of primary treatment-naïve prostate cancer
title Metabolic heterogeneity signature of primary treatment-naïve prostate cancer
title_full Metabolic heterogeneity signature of primary treatment-naïve prostate cancer
title_fullStr Metabolic heterogeneity signature of primary treatment-naïve prostate cancer
title_full_unstemmed Metabolic heterogeneity signature of primary treatment-naïve prostate cancer
title_short Metabolic heterogeneity signature of primary treatment-naïve prostate cancer
title_sort metabolic heterogeneity signature of primary treatment-naïve prostate cancer
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5432227/
https://www.ncbi.nlm.nih.gov/pubmed/28460430
http://dx.doi.org/10.18632/oncotarget.15237
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