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Novel Metabolic Signatures of Prostate Cancer Revealed by (1)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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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MDPI
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7909529/ https://www.ncbi.nlm.nih.gov/pubmed/33498542 http://dx.doi.org/10.3390/diagnostics11020149 |
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author | Yang, Bo Zhang, Chuan Cheng, Sheng Li, Gonghui Griebel, Jan Neuhaus, Jochen |
author_facet | Yang, Bo Zhang, Chuan Cheng, Sheng Li, Gonghui Griebel, Jan Neuhaus, Jochen |
author_sort | Yang, Bo |
collection | PubMed |
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 (1)H nuclear magnetic resonance ((1)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. |
format | Online Article Text |
id | pubmed-7909529 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-79095292021-02-27 Novel Metabolic Signatures of Prostate Cancer Revealed by (1)H-NMR Metabolomics of Urine Yang, Bo Zhang, Chuan Cheng, Sheng Li, Gonghui Griebel, Jan Neuhaus, Jochen Diagnostics (Basel) Article 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 (1)H nuclear magnetic resonance ((1)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. MDPI 2021-01-20 /pmc/articles/PMC7909529/ /pubmed/33498542 http://dx.doi.org/10.3390/diagnostics11020149 Text en © 2021 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 | Article Yang, Bo Zhang, Chuan Cheng, Sheng Li, Gonghui Griebel, Jan Neuhaus, Jochen Novel Metabolic Signatures of Prostate Cancer Revealed by (1)H-NMR Metabolomics of Urine |
title | Novel Metabolic Signatures of Prostate Cancer Revealed by (1)H-NMR Metabolomics of Urine |
title_full | Novel Metabolic Signatures of Prostate Cancer Revealed by (1)H-NMR Metabolomics of Urine |
title_fullStr | Novel Metabolic Signatures of Prostate Cancer Revealed by (1)H-NMR Metabolomics of Urine |
title_full_unstemmed | Novel Metabolic Signatures of Prostate Cancer Revealed by (1)H-NMR Metabolomics of Urine |
title_short | Novel Metabolic Signatures of Prostate Cancer Revealed by (1)H-NMR Metabolomics of Urine |
title_sort | novel metabolic signatures of prostate cancer revealed by (1)h-nmr metabolomics of urine |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7909529/ https://www.ncbi.nlm.nih.gov/pubmed/33498542 http://dx.doi.org/10.3390/diagnostics11020149 |
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