ArticleScientific reports2023
Bile metabolites as diagnostic biomarkers for perihilar cholangiocarcinoma.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Emerging omics diagnosis of perihilar cholangiocarcinoma.Journal of gastroenterology · 2026Article
- The Search for Risk, Diagnostic, and Prognostic Biomarkers of Cholangiocarcinoma and Their Biological and Clinicopathologic Significance.The American journal of pathology · 2025Review
- Investigating the causal relationship between the plasma lipidome and cholangiocarcinoma mediated by immune cells: a mediation Mendelian randomization study.Scientific reports · 2025Article
- Machine learning-driven prediction of immune checkpoint inhibitor responses against cholangiocarcinoma: a bile biopsy perspective.Frontiers in immunology · 2025Article
- Unveiling the potential of strain elastography in perihilar cholangiocarcinoma biopsies.Abdominal radiology (New York) · 2024Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
It is difficult to directly obtain pathological diagnosis of perihilar cholangiocarcinoma (pCCA). Analysis of bile in the pCCA microenvironment, based on metabolomics and statistical methods, can help in clinical diagnosis. Clinical information, bile samples, blood liver function, blood CA199, CEA, and other indicators were collected from 33 patients with pCCA and 16 patients with gallstones. Bile samples were analyzed using untargeted metabolomics methods. A combination of multivariate and univariate analyses were used to screen for potential differential metabolites Through Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment and differential metabolite remodeling, we explored changes in the pCCA pathway and potential therapeutic targets. There were significant differences in patient blood TBIL, ALT, AST, TBA, CA19-9, and CEA indices (p < 0.05, |log2(fc)| ≥ 1) between two groups. A significant correlation was found between these different indicators by Spearman's analysis. The clinical parameters were correlated with mass-to-charge ratios of 305 (Positive Ion Mode, POS) and 246 (Negative Ion Mode, NEG) in the metabolic group (|r| ≥ 0.7, P ≤ 10
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.