Next Article in Journal
Understanding Real-Time Fluorescence Signals from Bacteria and Wound Tissues Observed with the MolecuLight i:XTM
Previous Article in Journal
Machine-Learning-Based Laboratory Developed Test for the Diagnosis of Sepsis in High-Risk Patients
Previous Article in Special Issue
Imaging as a Personalized Biomarker for Prostate Cancer Risk Stratification

Metabolomics Biomarkers of Prostate Cancer: A Systematic Review

Numares AG, Am BioPark 9, 93053 Regensburg, Germany
Institute of Cancer Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow G61 1QH, UK
CRUK Beatson Institute, Bearsden, Glasgow G61 1BD, UK
Institute of Biophysics and Physical Biochemistry, University of Regensburg, 93053 Regensburg, Germany
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Diagnostics 2019, 9(1), 21;
Received: 23 January 2019 / Revised: 13 February 2019 / Accepted: 14 February 2019 / Published: 19 February 2019
(This article belongs to the Special Issue Diagnostic Biomarkers in Prostate Cancer)
Prostate cancer (PCa) diagnosis with current biomarkers is difficult and often results in unnecessary invasive procedures as well as over-diagnosis and over-treatment, highlighting the need for novel biomarkers. The aim of this review is to provide a summary of available metabolomics PCa biomarkers, particularly for clinically significant disease. A systematic search was conducted on PubMed for publications from July 2008 to July 2018 in accordance with PRISMA guidelines to report biomarkers with respect to their application in PCa diagnosis, progression, aggressiveness, recurrence, and treatment response. The vast majority of studies report biomarkers with the ability to distinguish malignant from benign prostate tissue with a few studies investigating biomarkers associated with disease progression, treatment response or tumour recurrence. In general, these studies report high dimensional datasets and the number of analysed metabolites often significantly exceeded the number of available samples. Hence, observed multivariate differences between case and control samples in the datasets might potentially also be associated with pre-analytical, technical, statistical and confounding factors. Giving the technical and methodological hurdles, there are nevertheless a number of metabolites and pathways repeatedly reported across various technical approaches, cohorts and sample types that appear to play a predominant role in PCa tumour biology, progression and recurrence. View Full-Text
Keywords: prostate cancer; metabolomics; biomarkers; systematic review; metabolites; profiling prostate cancer; metabolomics; biomarkers; systematic review; metabolites; profiling
Show Figures

Figure 1

MDPI and ACS Style

Kdadra, M.; Höckner, S.; Leung, H.; Kremer, W.; Schiffer, E. Metabolomics Biomarkers of Prostate Cancer: A Systematic Review. Diagnostics 2019, 9, 21.

AMA Style

Kdadra M, Höckner S, Leung H, Kremer W, Schiffer E. Metabolomics Biomarkers of Prostate Cancer: A Systematic Review. Diagnostics. 2019; 9(1):21.

Chicago/Turabian Style

Kdadra, Marouane, Sebastian Höckner, Hing Leung, Werner Kremer, and Eric Schiffer. 2019. "Metabolomics Biomarkers of Prostate Cancer: A Systematic Review" Diagnostics 9, no. 1: 21.

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Back to TopTop