Novel Metabolic Signatures of Prostate Cancer Revealed by <sup>1</sup>H-NMR Metabolomics of Urine

Prostate cancer (PC) is one of the most common male cancers worldwide. Until now, there is no consensus about using urinary metabolomic profiling as novel biomarkers to identify PC. In this study, urine samples from 50 PC patients and 50 non-cancerous individuals (control group) were collected. Base...

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Main Authors: Bo Yang, Chuan Zhang, Sheng Cheng, Gonghui Li, Jan Griebel, Jochen Neuhaus
Format: Article
Language:English
Published: MDPI AG 2021-01-01
Series:Diagnostics
Subjects:
Online Access:https://www.mdpi.com/2075-4418/11/2/149
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spelling doaj-d12d3e5b65a94d05bc32b6f8dc76f9c32021-01-21T00:06:02ZengMDPI AGDiagnostics2075-44182021-01-011114914910.3390/diagnostics11020149Novel Metabolic Signatures of Prostate Cancer Revealed by <sup>1</sup>H-NMR Metabolomics of UrineBo Yang0Chuan Zhang1Sheng Cheng2Gonghui Li3Jan Griebel4Jochen Neuhaus5Department of Urology, University of Leipzig, 04103 Leipzig, GermanyDepartment of Urology, University of Leipzig, 04103 Leipzig, GermanyDepartment of Urology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310016, ChinaDepartment of Urology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310016, ChinaLeibniz Institute of Surface Engineering (IOM), Permoserstraße 15, 04318 Leipzig, GermanyDepartment of Urology, University of Leipzig, 04103 Leipzig, GermanyProstate cancer (PC) is one of the most common male cancers worldwide. Until now, there is no consensus about using urinary metabolomic profiling as novel biomarkers to identify PC. In this study, urine samples from 50 PC patients and 50 non-cancerous individuals (control group) were collected. Based on <sup>1</sup>H nuclear magnetic resonance (<sup>1</sup>H-NMR) analysis, 20 metabolites were identified. Subsequently, principal component analysis (PCA), partial least squares-differential analysis (PLS-DA) and ortho-PLS-DA (OPLS-DA) were applied to find metabolites to distinguish PC from the control group. Furthermore, Wilcoxon test was used to find significant differences between the two groups in metabolite urine levels. Guanidinoacetate, phenylacetylglycine, and glycine were significantly increased in PC, while L-lactate and L-alanine were significantly decreased. The receiver operating characteristics (ROC) analysis revealed that the combination of guanidinoacetate, phenylacetylglycine, and glycine was able to accurately differentiate 77% of the PC patients with sensitivity = 80% and a specificity = 64%. In addition, those three metabolites showed significant differences in patients stratified for Gleason score 6 and Gleason score ≥7, indicating potential use to detect significant prostate cancer. Pathway enrichment analysis using the KEGG (Kyoto Encyclopedia of Genes and Genomes) and the SMPDB (The Small Molecule Pathway Database) revealed potential involvement of KEGG “Glycine, Serine, and Threonine metabolism” in PC. The present study highlights that guanidinoacetate, phenylacetylglycine, and glycine are potential candidate biomarkers of PC. To the best knowledge of the authors, this is the first study identifying guanidinoacetate, and phenylacetylglycine as potential novel biomarkers in PC.https://www.mdpi.com/2075-4418/11/2/149prostate cancerurine metabolomics1H-Nuclear Magnetic Resonancemetabolite biomarkers
collection DOAJ
language English
format Article
sources DOAJ
author Bo Yang
Chuan Zhang
Sheng Cheng
Gonghui Li
Jan Griebel
Jochen Neuhaus
spellingShingle Bo Yang
Chuan Zhang
Sheng Cheng
Gonghui Li
Jan Griebel
Jochen Neuhaus
Novel Metabolic Signatures of Prostate Cancer Revealed by <sup>1</sup>H-NMR Metabolomics of Urine
Diagnostics
prostate cancer
urine metabolomics
1H-Nuclear Magnetic Resonance
metabolite biomarkers
author_facet Bo Yang
Chuan Zhang
Sheng Cheng
Gonghui Li
Jan Griebel
Jochen Neuhaus
author_sort Bo Yang
title Novel Metabolic Signatures of Prostate Cancer Revealed by <sup>1</sup>H-NMR Metabolomics of Urine
title_short Novel Metabolic Signatures of Prostate Cancer Revealed by <sup>1</sup>H-NMR Metabolomics of Urine
title_full Novel Metabolic Signatures of Prostate Cancer Revealed by <sup>1</sup>H-NMR Metabolomics of Urine
title_fullStr Novel Metabolic Signatures of Prostate Cancer Revealed by <sup>1</sup>H-NMR Metabolomics of Urine
title_full_unstemmed Novel Metabolic Signatures of Prostate Cancer Revealed by <sup>1</sup>H-NMR Metabolomics of Urine
title_sort novel metabolic signatures of prostate cancer revealed by <sup>1</sup>h-nmr metabolomics of urine
publisher MDPI AG
series Diagnostics
issn 2075-4418
publishDate 2021-01-01
description Prostate cancer (PC) is one of the most common male cancers worldwide. Until now, there is no consensus about using urinary metabolomic profiling as novel biomarkers to identify PC. In this study, urine samples from 50 PC patients and 50 non-cancerous individuals (control group) were collected. Based on <sup>1</sup>H nuclear magnetic resonance (<sup>1</sup>H-NMR) analysis, 20 metabolites were identified. Subsequently, principal component analysis (PCA), partial least squares-differential analysis (PLS-DA) and ortho-PLS-DA (OPLS-DA) were applied to find metabolites to distinguish PC from the control group. Furthermore, Wilcoxon test was used to find significant differences between the two groups in metabolite urine levels. Guanidinoacetate, phenylacetylglycine, and glycine were significantly increased in PC, while L-lactate and L-alanine were significantly decreased. The receiver operating characteristics (ROC) analysis revealed that the combination of guanidinoacetate, phenylacetylglycine, and glycine was able to accurately differentiate 77% of the PC patients with sensitivity = 80% and a specificity = 64%. In addition, those three metabolites showed significant differences in patients stratified for Gleason score 6 and Gleason score ≥7, indicating potential use to detect significant prostate cancer. Pathway enrichment analysis using the KEGG (Kyoto Encyclopedia of Genes and Genomes) and the SMPDB (The Small Molecule Pathway Database) revealed potential involvement of KEGG “Glycine, Serine, and Threonine metabolism” in PC. The present study highlights that guanidinoacetate, phenylacetylglycine, and glycine are potential candidate biomarkers of PC. To the best knowledge of the authors, this is the first study identifying guanidinoacetate, and phenylacetylglycine as potential novel biomarkers in PC.
topic prostate cancer
urine metabolomics
1H-Nuclear Magnetic Resonance
metabolite biomarkers
url https://www.mdpi.com/2075-4418/11/2/149
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