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Metabolomic Biomarkers of Prostate Cancer: Prediction, Diagnosis, Progression, Prognosis, and Recurrence

Author(s)
Kelly, R. S.; Giovannucci, E.; Mucci, L. A.; Vander Heiden, Matthew G.
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Abstract
Metabolite profiling is being increasing employed in the study of prostate cancer as a means of identifying predictive, diagnostic, and prognostic biomarkers. This review provides a summary and critique of the current literature. Thirty-three human case-control studies of prostate cancer exploring disease prediction, diagnosis, progression, or treatment response were identified. All but one demonstrated the ability of metabolite profiling to distinguish cancer from benign, tumor aggressiveness, cases who recurred, and those who responded well to therapy. In the subset of studies where biomarker discriminatory ability was quantified, high AUCs were reported that would potentially outperform the current gold standards in diagnosis, prognosis, and disease recurrence, including PSA testing. There were substantial similarities between the metabolites and the associated pathways reported as significant by independent studies, and important roles for abnormal cell growth, intensive cell proliferation, and dysregulation of lipid metabolism were highlighted. The weight of the evidence therefore suggests metabolic alterations specific to prostate carcinogenesis and progression that may represent potential metabolic biomarkers. However, replication and validation of the most promising biomarkers is currently lacking and a number of outstanding methodologic issues remain to be addressed to maximize the utility of metabolomics in the study of prostate cancer.
Date issued
2016-04
URI
http://hdl.handle.net/1721.1/116917
Department
Koch Institute for Integrative Cancer Research at MIT
Journal
Cancer Epidemiology Biomarkers & Prevention
Publisher
American Association for Cancer Research (AACR)
Citation
Kelly, R. S. et al “Metabolomic Biomarkers of Prostate Cancer: Prediction, Diagnosis, Progression, Prognosis, and Recurrence.” Cancer Epidemiology Biomarkers & Prevention 25, 6 (April 2016): 887–906 © 2016 American Association for Cancer Research
Version: Author's final manuscript
ISSN
1055-9965
1538-7755

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