ArticleBMC medicine2023
Identification of a novel bile marker clusterin and a public online prediction platform based on deep learning for cholangiocarcinoma.
Article in BMC medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 14 citations in OpenAlex.
- Emerging omics diagnosis of perihilar cholangiocarcinoma.Journal of gastroenterology · 2026Article
- Advances in In Vitro Diagnostics for Cholangiocarcinoma: From Biomarker Discovery to Artificial Intelligence.International journal of molecular sciences · 2026Review
- Plasma POSTN Derived From Bile Proteome Is a Promising Biomarker for Cholangiocarcinoma With Efficacy Comparable and Complementary to CA19.9.United European gastroenterology journal · 2025Article
- The Future of Tumor Markers: Advancing Early Malignancy Detection Through Omics Technologies, Continuous Monitoring, and Personalized Reference Intervals.Biomolecules · 2025Review
- Performance of large language models in the differential diagnosis of benign and malignant biliary stricture.Frontiers in oncology · 2025Article
- Review
- Correction: Identification of a novel bile marker clusterin and a public online prediction platform based on deep learning for cholangiocarcinoma.BMC medicine · 2024Article
- Research trends and hotspots evolution of artificial intelligence for cholangiocarcinoma over the past 10 years: a bibliometric analysis.Frontiers in oncology · 2024Review
- Application of AI on cholangiocarcinoma.Frontiers in oncology · 2024Review
- Correction: Identification of a novel bile marker clusterin and a public online prediction platform based on deep learning for cholangiocarcinoma.BMC medicine · 2023Article
Corrections and comments
- Erratum issued
- Erratum issued
Authors and funding
20 authors at 7 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCholangiocarcinoma (CCA) is a highly aggressive malignant tumor, and its diagnosis is still a challenge. This study aimed to identify a novel bile marker for CCA diagnosis based on proteomics and establish a diagnostic model with deep learning.
methodsA total of 644 subjects (236 CCA and 408 non-CCA) from two independent centers were divided into discovery, cross-validation, and external validation sets for the study. Candidate bile markers were identified by three proteomics data and validated on 635 clinical humoral specimens and 121 tissue specimens. A diagnostic multi-analyte model containing bile and serum biomarkers was established in cross-validation set by deep learning and validated in an independent external cohort.
resultsThe results of proteomics analysis and clinical specimen verification showed that bile clusterin (CLU) was significantly higher in CCA body fluids. Based on 376 subjects in the cross-validation set, ROC analysis indicated that bile CLU had a satisfactory diagnostic power (AUC: 0.852, sensitivity: 73.6%, specificity: 90.1%). Building on bile CLU and 63 serum markers, deep learning established a diagnostic model incorporating seven factors (CLU, CA19-9, IBIL, GGT, LDL-C, TG, and TBA), which showed a high diagnostic utility (AUC: 0.947, sensitivity: 90.3%, specificity: 84.9%). External validation in an independent cohort (n = 259) resulted in a similar accuracy for the detection of CCA. Finally, for the convenience of operation, a user-friendly prediction platform was built online for CCA.
conclusionsThis is the largest and most comprehensive study combining bile and serum biomarkers to differentiate CCA. This diagnostic model may potentially be used to detect CCA.
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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 OpenQuestion graph.