ArticleScientific reports2020
Urinary charged metabolite profiling of colorectal cancer using capillary electrophoresis-mass spectrometry.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
25 citing papers in PubMed.
- Circulating Dipeptides in Cancer: Degradation Fragments or Functional Metabolites?International journal of molecular sciences · 2026Review
- A Multiomic Approach Integrating Genomic and Metabolomic Data Highlights Colorectal Cancer Pathways.Journal of proteome research · 2026Article
- AI-enabled multi-omics integration in colorectal cancer: from molecular stratification to clinical translation.Frontiers in cell and developmental biology · 2026Review
- A Citrate Synthase Splice Variant Rewires the TCA Cycle to Promote Colorectal Cancer Progression.Cancer research · 2025Article
- The Enteric Microbiome in Early-Onset Colorectal Cancer: A Comprehensive Review of Its Role as a Biomarker of Disease.Clinical and translational gastroenterology · 2025Review
- Noninvasive Urinary Biomarkers for Obesity-Related Metabolic Diseases: Diagnostic Applications and Future Directions.Biomolecules · 2025Review
- Energy Metabolism Profiling of Human Colorectal Tumours.Journal of cellular and molecular medicine · 2025Article
- Stage-Specific Plasma Metabolomic Profiles in Colorectal Cancer.Journal of clinical medicine · 2024Article
- Metabolomics analyses of cancer tissue from patients with colorectal cancer.Molecular medicine reports · 2023Article
- Molybdenum Disulfide as Tunable Electrochemical and Optical Biosensing Platforms for Cancer Biomarker Detection: A Review.Biosensors · 2023Review
- Comprehensive Insight into Colorectal Cancer Metabolites and Lipids for Human Serum: A Proof-of-Concept Study.International journal of molecular sciences · 2023Article
- From adenoma to CRC stages: the oral-gut microbiome axis as a source of potential microbial and metabolic biomarkers of malignancy.Neoplasia (New York, N.Y.) · 2023Observational
- Small molecule metabolites: discovery of biomarkers and therapeutic targets.Signal transduction and targeted therapy · 2023Review
- Implication of gut microbes and its metabolites in colorectal cancer.Journal of cancer research and clinical oncology · 2023Review
- Metabolomics Analysis of Blood, Urine, and Saliva Samples Based on Capillary Electrophoresis-Mass Spectrometry.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Multi-Omics Approaches in Colorectal Cancer Screening and Diagnosis, Recent Updates and Future Perspectives.Cancers · 2022Review
- Metabolomic Profiling of Plasma, Urine, and Saliva of Kidney Transplantation Recipients.International journal of molecular sciences · 2022Article
- Histone deacetylase-10 liberates spermidine to support polyamine homeostasis and tumor cell growth.The Journal of biological chemistry · 2022Article
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Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Colorectal cancer (CRC) has increasing global prevalence and poor prognostic outcomes, and the development of low- or less invasive screening tests is urgently required. Urine is an ideal biofluid that can be collected non-invasively and contains various metabolite biomarkers. To understand the metabolomic profiles of different stages of CRC, we conducted metabolomic profiling of urinary samples. Capillary electrophoresis-time-of-flight mass spectrometry was used to quantify hydrophilic metabolites in 247 subjects with stage 0 to IV CRC or polyps, and healthy controls. The 154 identified and quantified metabolites included metabolites of glycolysis, TCA cycle, amino acids, urea cycle, and polyamine pathways. The concentrations of these metabolites gradually increased with the stage, and samples of CRC stage IV especially showed a large difference compared to other stages. Polyps and CRC also showed different concentration patterns. We also assessed the differentiation ability of these metabolites. A multiple logistic regression model using three metabolites was developed with a randomly designated training dataset and validated using the remaining data to differentiate CRC and polys from healthy controls based on a panel of urinary metabolites. These data highlight the changes in metabolites from early to late stage of CRC and also the differences between CRC and polyps.
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