ArticleFrontiers in oncology2023
LC-MS based urine untargeted metabolomic analyses to identify and subdivide urothelial cancer.
Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed.
- Evaluation of FASP for Mass Spectrometry-Based Untargeted Metabolomics Analysis of Urine Samples.Journal of proteome research · 2026Article
- 2'-deoxyinosine ameliorates multiple sclerosis through modulating Th1/Th2 and Th17/Treg cell balance with potential involvement of AMPK phosphorylation.Frontiers in pharmacology · 2026Article
- Urinary metabolomic profiling in 22q11.2 deletion syndrome reveals microbial and mitochondrial signatures related to autism and psychosis risk.PCN reports : psychiatry and clinical neurosciences · 2025Article
- Determination of nine prostaglandins in the arachidonic acid metabolic pathway with UHPLC-QQQ-MS/MS and application toFrontiers in pharmacology · 2025Article
- Untargeted metabolomics revealed urinary metabolic pattern for discriminating prostate cancer from benign prostatic hyperplasia in Chinese participants.Frontiers in oncology · 2025Article
- What is the relationship between microorganisms in the human body and upper tract urothelial carcinoma?Frontiers in immunology · 2025Review
- Magnetic 3D macroporous MOF oriented urinary exosome metabolomics for early diagnosis of bladder cancer.Journal of nanobiotechnology · 2024Article
- Improving platelet-RNA-based diagnostics: a comparative analysis of machine learning models for cancer detection and multiclass classification.Molecular oncology · 2024Article
- BLCA prognostic model creation and validation based on immune gene-metabolic gene combination.Discover oncology · 2023Article
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Abstract
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.
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