title: Metabolomic Biomarkers of Prostate Cancer: Prediction, Diagnosis, Progression, Prognosis, and Recurrence.
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. Cancer Epidemiol Biomarkers Prev; 25(6); 887-906. ©2016 AACR.
authors.affiliation: Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts. Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts. hprke@channing.harvard.edu.
authors.forename: Rachel S
authors.initials: RS
authors.lastname: Kelly
authors.affiliation: Koch Institute for Integrative Cancer Research at Massachusetts Institute of Technology, Cambridge, Massachusetts. Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts. Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts.
authors.forename: Matthew G
authors.initials: MG
authors.lastname: Vander Heiden
authors.affiliation: Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts. Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts. Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
authors.forename: Edward
authors.initials: E
authors.lastname: Giovannucci
authors.affiliation: Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts. Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts.
authors.forename: Lorelei A
authors.initials: LA
authors.lastname: Mucci
mesh_terms: D015415:Biomarkers; D006801:Humans; D008297:Male; D055442:Metabolome; D009364:Neoplasm Recurrence, Local; D011379:Prognosis; D011471:Prostatic Neoplasms / Q000175:diagnosis* / Q000378:metabolism* / Q000473:pathology
chemical_list: D015415:Biomarkers