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Serum biomarker panels for diagnosis of gastric cancer

Authors Tong W, Ye F, He L, Cui L, Cui M, Hu Y, Li W, Jiang J, Zhang D, Suo J

Received 6 April 2015

Accepted for publication 22 June 2015

Published 26 April 2016 Volume 2016:9 Pages 2455—2463

DOI https://doi.org/10.2147/OTT.S86139

Checked for plagiarism Yes

Review by Single-blind

Peer reviewer comments 3

Editor who approved publication: Professor Daniele Santini


Weihua Tong,1 Fei Ye,2 Liang He,1 Lifeng Cui,1 Miao Cui,2 Yuan Hu,2 Wei Li,1 Jing Jiang,3 David Y Zhang,2 Jian Suo1

1Department of Gastrointestinal Surgery, The First Hospital, Jilin University, Changchun, Jilin, People’s Republic of China; 2Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, NY, USA; 3Division of Clinical Epidemiology, The First Hospital, Jilin University, Changchun, Jilin, People’s Republic of China

Purpose: Currently, serum biomarkers that are sufficiently sensitive and specific for early detection and risk classification of gastric adenocarcinomas are not known. In this study, ten serum markers were assessed using the Luminex system and enzyme-linked immunosorbent assay for the diagnosis of gastric cancer and analysis of the relation between prognosis and metastases.
Patients and methods: A training set consisting of 228 gastric adenocarcinoma and 190 control samples was examined. A Luminex multiplex panel with nine biomarkers, consisting of three proteins discovered through our previous studies and six proteins previously reported to be cancer-associated, was constructed. One additional biomarker was detected using a commercial kit containing EDTA. Logistic regression, random forest (RF), and support vector machine (SVM) were used to identify the panel of discriminatory biomarkers in the training set. After selecting five proteins as candidate biomarkers, multivariate classification analyses were used to identify algorithms for diagnostic biomarker combinations. These algorithms were independently validated using a set of 57 gastric adenocarcinoma and 48 control samples.
Results: Serum pepsinogen I, serum pepsinogen II, A Disintegrin And Metalloproteinase domain-containing protein 8 (ADAM8), vascular endothelial growth factor (VEGF), and serum IgG to Helicobacter pylori were selected as classifiers in the three algorithms. These algorithms differentiated between the majority of gastric adenocarcinoma and control serum samples in the training/test set with high accuracy (RF 79.0%, SVM 83.8%, logistic regression 76.2%). These algorithms also differentiated the samples in the validation set (accuracy: RF 82.5%, SVM 86.1%, logistic regression 78.7%).
Conclusion: A panel of combinatorial biomarkers comprising VEGF, ADAM8, IgG to H. pylori, serum pepsinogen I, and pepsinogen II were developed. The use of biomarkers is a less invasive method for the diagnosis of gastric adenocarcinoma. They may supplement clinical gastroscopic evaluation of symptomatic gastric cancer patients and enhance the diagnostic accuracy.

Keywords: gastric adenocarcinoma, cancer diagnosis, cancer screening, Luminex

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