Research Papers:

Metabolic heterogeneity signature of primary treatment-naïve prostate cancer

Dong Lin, Susan L. Ettinger, Sifeng Qu, Hui Xue, Noushin Nabavi, Stephen Yiu Chuen Choi, Robert H. Bell, Fan Mo, Anne M. Haegert, Peter W. Gout, Neil Fleshner, Martin E. Gleave, Michael Pollak, Colin C. Collins and Yuzhuo Wang _

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Oncotarget. 2017; 8:25928-25941. https://doi.org/10.18632/oncotarget.15237

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Dong Lin1,2,*, Susan L. Ettinger1,*, Sifeng Qu1,2, Hui Xue2, Noushin Nabavi1,2, Stephen Yiu Chuen Choi1,2, Robert H. Bell1, Fan Mo1, Anne M. Haegert1, Peter W. Gout2, Neil Fleshner3, Martin E. Gleave1, Michael Pollak4, Colin C. Collins1 and Yuzhuo Wang1,2

1 The Vancouver Prostate Centre, Vancouver General Hospital and Department of Urologic Sciences, The University of British Columbia, Vancouver, British Columbia, Canada

2 Department of Experimental Therapeutics, BC Cancer Research Centre, Vancouver, British Columbia, Canada

3 Division of Urology, University of Toronto, Department of Urology, University Health Network, Princess Margaret Hospital, Toronto, Ontario, Canada

4 Lady Davis Research Institute and McGill University, Montreal, Quebec, Canada

* Co-first Authors

Correspondence to:

Yuzhuo Wang, email:

Colin C. Collins, email:

Michael Pollak, email:

Keywords: prostate cancer; tumour heterogeneity; metabolic heterogeneity; patient-derived xenografts

Received: January 20, 2017 Accepted: January 25, 2017 Published: February 09, 2017


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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