Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Yang, Ming, Liu, Xiaoyan, Tang, Xiaoyue, Sun, Wei, Ji, Zhigang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
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
_version_ 1785050604561760256
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
work_keys_str_mv AT yangming lcmsbasedurineuntargetedmetabolomicanalysestoidentifyandsubdivideurothelialcancer
AT liuxiaoyan lcmsbasedurineuntargetedmetabolomicanalysestoidentifyandsubdivideurothelialcancer
AT tangxiaoyue lcmsbasedurineuntargetedmetabolomicanalysestoidentifyandsubdivideurothelialcancer
AT sunwei lcmsbasedurineuntargetedmetabolomicanalysestoidentifyandsubdivideurothelialcancer
AT jizhigang lcmsbasedurineuntargetedmetabolomicanalysestoidentifyandsubdivideurothelialcancer