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- Title
Identification of a novel bile marker clusterin and a public online prediction platform based on deep learning for cholangiocarcinoma.
- Authors
Gao, Long; Lin, Yanyan; Yue, Ping; Li, Shuyan; Zhang, Yong; Mi, Ningning; Bai, Mingzhen; Fu, Wenkang; Xia, Zhili; Jiang, Ningzu; Cao, Jie; Yang, Man; Ma, Yanni; Zhang, Fanxiang; Zhang, Chao; Leung, Joseph W.; He, Shun; Yuan, Jinqiu; Meng, Wenbo; Li, Xun
- Abstract
Background: Cholangiocarcinoma (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. Methods: A 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. Results: The 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. Conclusions: This 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.
- Subjects
DEEP learning; CLUSTERIN; CHOLANGIOCARCINOMA; BIOMARKERS; BODY fluids
- Publication
BMC Medicine, 2023, Vol 21, Issue 1, p1
- ISSN
1741-7015
- Publication type
Article
- DOI
10.1186/s12916-023-02990-9