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LC-MS based urine untargeted metabolomic analyses to identify and subdivide urothelial cancer
INTRODUCTION: Urine metabolomics has been a promising technique in the liquid biopsy of urothelial cancer (UC). The comparison of upper tract urothelial cancer (UTUC), lower tract urothelial cancer (BCa), and healthy controls (HCs) need to be performed to find related biomarkers. METHODS: In our inv...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10226587/ https://www.ncbi.nlm.nih.gov/pubmed/37256175 http://dx.doi.org/10.3389/fonc.2023.1160965 |
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author | Yang, Ming Liu, Xiaoyan Tang, Xiaoyue Sun, Wei Ji, Zhigang |
author_facet | Yang, Ming Liu, Xiaoyan Tang, Xiaoyue Sun, Wei Ji, Zhigang |
author_sort | Yang, Ming |
collection | PubMed |
description | INTRODUCTION: Urine metabolomics has been a promising technique in the liquid biopsy of urothelial cancer (UC). The comparison of upper tract urothelial cancer (UTUC), lower tract urothelial cancer (BCa), and healthy controls (HCs) need to be performed to find related biomarkers. METHODS: In our investigation, urine samples from 35 UTUCs, 44 BCas, and 53 gender- and age-matched HCs were analyzed using liquid chromatography-high resolution mass spectrometry (LC-HRMS). In different groups, the differential metabolites and the disturbed metabolism pathways were explored. Transcriptomics and urine metabolomics are combined to identify the probably disturbed gene in BCa. RESULTS: With an area under the curve (AUC) of 0.815, the panel consisting of prostaglandin I2, 5-methyldeoxycytidine, 2,6-dimethylheptanoyl carnitine, and deoxyinosine was able to discriminate UC from HCs. With an AUC of 0.845, the validation group also demonstrated strong predictive ability. UTUC and BCa without hematuria could be distinguished using the panel of 5'-methylthioadenosine, L-beta-aspartyl-L-serine, dehydroepiandrosterone sulfate, and N'-formylkynurenine (AUC=0.858). The metabolite panel comprising aspartyl-methionine, 7-methylinosine, and alpha-CEHC glucuronide could discriminate UTUC from BCa with hematuria with an AUC of 0.83. Fatty acid biosynthesis, purine metabolism, tryptophan metabolism, pentose and glucuronate interconversions, and arachidonic acid metabolism were dysregulated when comparing UC with HCs. PTGIS and BCHE, the genes related to the metabolism of prostaglandin I2 and myristic acid respectively, were significantly associated with the survival of BCa. DISCUSSION: Not only could LC-HRMS urine metabolomic investigations distinguish UC from HCs, but they could also identify UTUC from BCa. Additionally, urine metabolomics combined with transcriptomics can find out the potential aberrant genes in the metabolism. |
format | Online Article Text |
id | pubmed-10226587 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-102265872023-05-30 LC-MS based urine untargeted metabolomic analyses to identify and subdivide urothelial cancer Yang, Ming Liu, Xiaoyan Tang, Xiaoyue Sun, Wei Ji, Zhigang Front Oncol Oncology INTRODUCTION: Urine metabolomics has been a promising technique in the liquid biopsy of urothelial cancer (UC). The comparison of upper tract urothelial cancer (UTUC), lower tract urothelial cancer (BCa), and healthy controls (HCs) need to be performed to find related biomarkers. METHODS: In our investigation, urine samples from 35 UTUCs, 44 BCas, and 53 gender- and age-matched HCs were analyzed using liquid chromatography-high resolution mass spectrometry (LC-HRMS). In different groups, the differential metabolites and the disturbed metabolism pathways were explored. Transcriptomics and urine metabolomics are combined to identify the probably disturbed gene in BCa. RESULTS: With an area under the curve (AUC) of 0.815, the panel consisting of prostaglandin I2, 5-methyldeoxycytidine, 2,6-dimethylheptanoyl carnitine, and deoxyinosine was able to discriminate UC from HCs. With an AUC of 0.845, the validation group also demonstrated strong predictive ability. UTUC and BCa without hematuria could be distinguished using the panel of 5'-methylthioadenosine, L-beta-aspartyl-L-serine, dehydroepiandrosterone sulfate, and N'-formylkynurenine (AUC=0.858). The metabolite panel comprising aspartyl-methionine, 7-methylinosine, and alpha-CEHC glucuronide could discriminate UTUC from BCa with hematuria with an AUC of 0.83. Fatty acid biosynthesis, purine metabolism, tryptophan metabolism, pentose and glucuronate interconversions, and arachidonic acid metabolism were dysregulated when comparing UC with HCs. PTGIS and BCHE, the genes related to the metabolism of prostaglandin I2 and myristic acid respectively, were significantly associated with the survival of BCa. DISCUSSION: Not only could LC-HRMS urine metabolomic investigations distinguish UC from HCs, but they could also identify UTUC from BCa. Additionally, urine metabolomics combined with transcriptomics can find out the potential aberrant genes in the metabolism. Frontiers Media S.A. 2023-05-12 /pmc/articles/PMC10226587/ /pubmed/37256175 http://dx.doi.org/10.3389/fonc.2023.1160965 Text en Copyright © 2023 Yang, Liu, Tang, Sun and Ji https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Oncology Yang, Ming Liu, Xiaoyan Tang, Xiaoyue Sun, Wei Ji, Zhigang LC-MS based urine untargeted metabolomic analyses to identify and subdivide urothelial cancer |
title | LC-MS based urine untargeted metabolomic analyses to identify and subdivide urothelial cancer |
title_full | LC-MS based urine untargeted metabolomic analyses to identify and subdivide urothelial cancer |
title_fullStr | LC-MS based urine untargeted metabolomic analyses to identify and subdivide urothelial cancer |
title_full_unstemmed | LC-MS based urine untargeted metabolomic analyses to identify and subdivide urothelial cancer |
title_short | LC-MS based urine untargeted metabolomic analyses to identify and subdivide urothelial cancer |
title_sort | lc-ms based urine untargeted metabolomic analyses to identify and subdivide urothelial cancer |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10226587/ https://www.ncbi.nlm.nih.gov/pubmed/37256175 http://dx.doi.org/10.3389/fonc.2023.1160965 |
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