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Identification and validation of circulating biomarkers for detection of liver cancer with antibody array

Shuangzhe Zhang, Chunhui Gao, Qi Zhou, Lipai Chen, Gordon Huang, Hao Tang, Xuedong Song, Zhuo Zhang, Kelly Whittaker, Xiaofeng Chen,  Ruo-Pan Huang

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.

Received date: 06/06/2022

Accepted date: 12/09/2022

Ahead of print publish date: 01/09/2023

Issue: 1/2023

Volume: 70

Pages: 36 — 45

Keywords: liver cancer, protein biomarkers, antibody array, random forest, tissue and serum detection, combination of biomarkers

Supplementary files:
N600 Suppl TableS1-TE1.docx
N600 Suppl TableS2-TE1.docx
N600 Suppl TableS3-TE1.docx
N600 Suppl TableS4-TE1.docx
N600 Suppl TableS5-TE1.docx

DOI: 10.4149/neo_2022_220606N600

Pubmed

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