Neoplasma Vol.70, No.1, p. 36–45, 2023
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Title: Identification and validation of circulating biomarkers for detection of liver cancer with antibody array |
Author: Shuangzhe Zhang, Chunhui Gao, Qi Zhou, Lipai Chen, Gordon Fan Huang, Hao Tang, Xuedong Song, Zhuo Zhang, Kelly Whittaker, Xiaofeng Chen, Ruo-Pan Huang |
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Abstract: The aim of this study was to find new protein biomarkers that could be used to detect hepatocellular carcinoma (HCC) in the serum. We identified 11 proteins in the tissue that could be used to classify samples from HCC and control subjects. The 11 identified tissue biomarkers were combined with 10 commonly used serum HCC biomarkers for further verification in a large number of serum samples from HCC patients and healthy controls. 17 of the 21 prospective serum biomarkers were determined to be differentially expressed through collinearity and significance analysis. Through the method of supervised learning, a random forest model was constructed to reduce the dimensionality of the number of differentially expressed proteins, and finally, 4 differentially expressed proteins were identified: AFP, GDF15, CEACAM-1, and MMP-9, and suggested to have potential application in clinical diagnosis of HCC.
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Keywords: liver cancer; protein biomarkers; antibody array; random forest; tissue and serum detection; combination of biomarkers |
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Published online: 09-Jan-2023
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Year: 2023, Volume: 70, Issue: 1 |
Page From: 36, Page To: 45 |
doi:10.4149/neo_2022_220606N600
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