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Metabolomics Biomarkers of Prostate Cancer: A Systematic Review
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,...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6468767/ https://www.ncbi.nlm.nih.gov/pubmed/30791464 http://dx.doi.org/10.3390/diagnostics9010021 |
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author | Kdadra, Marouane Höckner, Sebastian Leung, Hing Kremer, Werner Schiffer, Eric |
author_facet | Kdadra, Marouane Höckner, Sebastian Leung, Hing Kremer, Werner Schiffer, Eric |
author_sort | Kdadra, Marouane |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6468767 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-64687672019-04-19 Metabolomics Biomarkers of Prostate Cancer: A Systematic Review Kdadra, Marouane Höckner, Sebastian Leung, Hing Kremer, Werner Schiffer, Eric Diagnostics (Basel) Review 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. MDPI 2019-02-19 /pmc/articles/PMC6468767/ /pubmed/30791464 http://dx.doi.org/10.3390/diagnostics9010021 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Kdadra, Marouane Höckner, Sebastian Leung, Hing Kremer, Werner Schiffer, Eric Metabolomics Biomarkers of Prostate Cancer: A Systematic Review |
title | Metabolomics Biomarkers of Prostate Cancer: A Systematic Review |
title_full | Metabolomics Biomarkers of Prostate Cancer: A Systematic Review |
title_fullStr | Metabolomics Biomarkers of Prostate Cancer: A Systematic Review |
title_full_unstemmed | Metabolomics Biomarkers of Prostate Cancer: A Systematic Review |
title_short | Metabolomics Biomarkers of Prostate Cancer: A Systematic Review |
title_sort | metabolomics biomarkers of prostate cancer: a systematic review |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6468767/ https://www.ncbi.nlm.nih.gov/pubmed/30791464 http://dx.doi.org/10.3390/diagnostics9010021 |
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