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使用决策树算法建立用于胆管癌诊断和预后的潜在血清生物标志物面板。

Establishment of a Potential Serum Biomarker Panel for the Diagnosis and Prognosis of Cholangiocarcinoma Using Decision Tree Algorithms.

作者信息

Kimawaha Phongsaran, Jusakul Apinya, Junsawang Prem, Thanan Raynoo, Titapun Attapol, Khuntikeo Narong, Techasen Anchalee

机构信息

Biomedical Sciences Program, Graduate School, Khon Kaen University, Khon Kaen 40002, Thailand.

Cholangiocarcinoma Research Institute, Khon Kaen University, Khon Kaen 40002, Thailand.

出版信息

Diagnostics (Basel). 2021 Mar 25;11(4):589. doi: 10.3390/diagnostics11040589.

Abstract

Potential biomarkers which include S100 calcium binding protein A9 (S100A9), mucin 5AC (MUC5AC), transforming growth factor β1 (TGF-β1), and angiopoietin-2 have previously been shown to be effective for cholangiocarcinoma (CCA) diagnosis. This study attempted to measure the sera levels of these biomarkers compared with carbohydrate antigen 19-9 (CA19-9). A total of 40 serum cases of CCA, gastrointestinal cancers (non-CCA), and healthy subjects were examined by using an enzyme-linked immunosorbent assay. The panel of biomarkers was evaluated for their accuracy in diagnosing CCA and subsequently used as inputs to construct the decision tree (DT) model as a basis for binary classification. The findings showed that serum levels of S100A9, MUC5AC, and TGF-β1 were dramatically enhanced in CCA patients. In addition, 95% sensitivity and 90% specificity for CCA differentiation from healthy cases, and 70% sensitivity and 83% specificity for CCA versus non-CCA cases was obtained by a panel incorporating all five candidate biomarkers. In CCA patients with low CA19-9 levels, S100A9 might well be a complementary marker for improved diagnostic accuracy. The high levels of TGF-β1 and angiopoietin-2 were both associated with severe tumor stages and metastasis, indicating that they could be used as a reliable prognostic biomarkers panel for CCA patients. Furthermore, the outcome of the CCA burden from the Classification and Regression Tree (CART) algorithm using serial CA19-9 and S100A9 showed high diagnostic efficiency. In conclusion, results have shown the efficacy of CCA diagnosis and prognosis of the novel CCA-biomarkers panel examined herein, which may prove be useful in clinical settings.

摘要

包括S100钙结合蛋白A9(S100A9)、粘蛋白5AC(MUC5AC)、转化生长因子β1(TGF-β1)和血管生成素-2在内的潜在生物标志物此前已被证明对胆管癌(CCA)诊断有效。本研究试图测量这些生物标志物与糖类抗原19-9(CA19-9)相比的血清水平。通过酶联免疫吸附测定法对40例CCA血清病例、胃肠道癌症(非CCA)和健康受试者进行了检测。评估了该生物标志物组在诊断CCA方面的准确性,随后将其用作构建决策树(DT)模型的输入,作为二元分类的基础。研究结果表明,CCA患者血清中S100A9、MUC5AC和TGF-β1水平显著升高。此外,通过纳入所有五种候选生物标志物的组合,区分CCA与健康病例的敏感性为95%,特异性为90%;区分CCA与非CCA病例的敏感性为70%,特异性为83%。在CA19-9水平较低的CCA患者中,S100A9很可能是提高诊断准确性的补充标志物。TGF-β1和血管生成素-2的高水平均与严重肿瘤分期和转移相关,表明它们可作为CCA患者可靠的预后生物标志物组。此外,使用系列CA19-9和S100A9的分类与回归树(CART)算法对CCA负荷的评估结果显示出较高的诊断效率。总之,结果表明本文检测的新型CCA生物标志物组在CCA诊断和预后方面具有有效性,这可能在临床环境中有用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/54fd/8064492/22a600625da4/diagnostics-11-00589-g001.jpg

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