<i>MMP14</i> is a diagnostic gene of intrahepatic cholangiocarcinoma associated with immune cell infiltration

Wu, Jun; Guo, Yang; Zuo, Zhifan; Zhu, Zi-Wei; Han, Lei

doi:10.3748/wjg.v29.i19.2961

Cited by 2 publications

(2 citation statements)

References 38 publications

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“…Human gene expression profiles of the ICC GEO database were investigated to screen out the differentially expressed genes with three algorithms (LASSO, SVM-RFE, RF). MMP14 was finally determined with high accuracy and an AUC of 0.999, which affects the infiltration of monocytes and the activation of memory CD4 T cells ( 58 ). Six hundred seventy-two mutations in 45 different CCA genes were also detected by Ali Shah et al.…”

Section: Ai and Diagnosismentioning

confidence: 99%

“…Different from the previous study concerning gene expression profiles, several phases of the CE-CT were enrolled in the study to investigate the different radiological features in different CCA-related gene expression levels ( 58 , 59 ). The IDH gene, which translated key enzymes in the tricarboxylic acid cycle, frequently mutated and participated in the carcinogenesis of ICC.…”

Section: Ai and Diagnosismentioning

confidence: 99%

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Application of AI on cholangiocarcinoma

Huang,

Bai,

Qiu

et al. 2024

Front. Oncol.

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Cholangiocarcinoma, classified as intrahepatic, perihilar, and extrahepatic, is considered a deadly malignancy of the hepatobiliary system. Most cases of cholangiocarcinoma are asymptomatic. Therefore, early detection of cholangiocarcinoma is significant but still challenging. The routine screening of a tumor lacks specificity and accuracy. With the application of AI, high-risk patients can be easily found by analyzing their clinical characteristics, serum biomarkers, and medical images. Moreover, AI can be used to predict the prognosis including recurrence risk and metastasis. Although they have some limitations, AI algorithms will still significantly improve many aspects of cholangiocarcinoma in the medical field with the development of computing power and technology.

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Section: Ai and Diagnosismentioning

confidence: 99%

Section: Ai and Diagnosismentioning

confidence: 99%

Application of AI on cholangiocarcinoma

Huang,

Bai,

Qiu

et al. 2024

Front. Oncol.

View full text Add to dashboard Cite

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A new biomarker panel for differential diagnosis of cholangiocarcinoma: Results from an exploratory analysis

Köhler,

Bes,

Chan

et al. 2024

Int J Biol Markers

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Introduction Diagnosis of cholangiocarcinoma (CCA) can be challenging due to unclear imaging criteria and difficulty obtaining adequate tissue biopsy. Although serum cancer antigen 19-9 and carcinoembryonic antigen have been proposed as potential diagnostic aids, their use remains limited by insufficient sensitivity and specificity. This exploratory analysis aimed to identify individual- and combinations of serum biomarkers to distinguish CCA from hepatocellular carcinoma (HCC) and chronic liver disease (CLD) controls using samples from a published study. Methods This prospective, multicenter, case-control study included patients aged ≥18 years at high-risk of HCC. Serum and ethylene diamine tetraacetic acid-plasma samples were collected prior to any treatment and confirmed diagnosis of HCC or CCA. Fourteen biomarkers (measured by electrochemiluminescence immunoassays or enzyme-linked immunosorbent assays) were subjected to univariate analysis and 13 included in a multivariate analysis (per selected combinations and exhaustive search). Results Overall, 55 CCA, 306 HCC, and 733 CLD control samples were analyzed. For distinguishing CCA from HCC, alpha-fetoprotein and matrix metalloproteinase-2 (MMP-2) showed the best individual performance (area under the curve (AUC) 86.6% and 84.4%, respectively); tissue inhibitor of metalloproteinase-1 (TIMP-1) was most able to distinguish CCA from CLD (AUC 94.5%) and from HCC + CLD (AUC 88.6%). The combination of MMP-2 and TIMP-1 was the best-performing two-marker panel, with AUC >90% for all comparisons. Conclusion MMP-2 and TIMP-1 are promising biomarkers that could support differential diagnosis of CCA. Incorporating these assays into the diagnostic algorithm could provide additional diagnostic information in a non-invasive, rapid manner, and could supplement existing diagnostic methods.

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MMP14 is a diagnostic gene of intrahepatic cholangiocarcinoma associated with immune cell infiltration

Cited by 2 publications

References 38 publications

Application of AI on cholangiocarcinoma

Application of AI on cholangiocarcinoma

A new biomarker panel for differential diagnosis of cholangiocarcinoma: Results from an exploratory analysis

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