CLC number: R73-34
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2012-10-31
Cited: 4
Clicked: 5986
Xiao-hui Zhai, Jie-kai Yu, Chen Lin, Li-dong Wang, Shu Zheng. Combining proteomics, serum biomarkers and bioinformatics to discriminate between esophageal squamous cell carcinoma and pre-cancerous lesion[J]. Journal of Zhejiang University Science B, 2012, 13(12): 964-971.
@article{title="Combining proteomics, serum biomarkers and bioinformatics to discriminate between esophageal squamous cell carcinoma and pre-cancerous lesion",
author="Xiao-hui Zhai, Jie-kai Yu, Chen Lin, Li-dong Wang, Shu Zheng",
journal="Journal of Zhejiang University Science B",
volume="13",
number="12",
pages="964-971",
year="2012",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.B1200066"
}
%0 Journal Article
%T Combining proteomics, serum biomarkers and bioinformatics to discriminate between esophageal squamous cell carcinoma and pre-cancerous lesion
%A Xiao-hui Zhai
%A Jie-kai Yu
%A Chen Lin
%A Li-dong Wang
%A Shu Zheng
%J Journal of Zhejiang University SCIENCE B
%V 13
%N 12
%P 964-971
%@ 1673-1581
%D 2012
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.B1200066
TY - JOUR
T1 - Combining proteomics, serum biomarkers and bioinformatics to discriminate between esophageal squamous cell carcinoma and pre-cancerous lesion
A1 - Xiao-hui Zhai
A1 - Jie-kai Yu
A1 - Chen Lin
A1 - Li-dong Wang
A1 - Shu Zheng
J0 - Journal of Zhejiang University Science B
VL - 13
IS - 12
SP - 964
EP - 971
%@ 1673-1581
Y1 - 2012
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.B1200066
Abstract: Objective: biomarker assay is a noninvasive method for the early detection of esophageal squamous cell carcinoma (ESCC). Searching for new biomarkers with high specificity and sensitivity is very important for the early detection of ESCC. Serum surface-enhanced laser desorption/ionization-time of flight mass spectrometry (SELDI-TOF-MS) is a high throughput technology for identifying cancer biomarkers using drops of sera. Methods: In this study, 185 serum samples were taken from ESCC patients in a high incidence area and screened by SELDI. A support vector machine (SVM) algorithm was adopted to analyze the samples. Results: The SVM patterns successfully distinguished ESCC from pre-cancerous lesions (PCLs). Also, types of PCL, including dysplasia (DYS) and basal cell hyperplasia (BCH), and healthy controls (HC) were distinguished with an accuracy of 95.2% (DYS), 96.6% (BCH), and 93.8% (HC), respectively. A marker of 25.1 kDa was identified in the ESCC patterns whose peak intensity was observed to increase significantly during the development of esophageal carcinogenesis, and to decrease obviously after surgery. Conclusions: We selected five ESCC biomarkers to form a diagnostic pattern which can discriminate among the different stages of esophageal carcinogenesis. This pattern can significantly improve the detection of ESCC.
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