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Serum biomarker panels for diagnosis of gastric cancer

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 g...

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Autores principales: Tong, Weihua, Ye, Fei, He, Liang, Cui, Lifeng, Cui, Miao, Hu, Yuan, Li, Wei, Jiang, Jing, Zhang, David Y, Suo, Jian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove Medical Press 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4853138/
https://www.ncbi.nlm.nih.gov/pubmed/27217769
http://dx.doi.org/10.2147/OTT.S86139
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author Tong, Weihua
Ye, Fei
He, Liang
Cui, Lifeng
Cui, Miao
Hu, Yuan
Li, Wei
Jiang, Jing
Zhang, David Y
Suo, Jian
author_facet Tong, Weihua
Ye, Fei
He, Liang
Cui, Lifeng
Cui, Miao
Hu, Yuan
Li, Wei
Jiang, Jing
Zhang, David Y
Suo, Jian
author_sort Tong, Weihua
collection PubMed
description 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.
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spelling pubmed-48531382016-05-23 Serum biomarker panels for diagnosis of gastric cancer Tong, Weihua Ye, Fei He, Liang Cui, Lifeng Cui, Miao Hu, Yuan Li, Wei Jiang, Jing Zhang, David Y Suo, Jian Onco Targets Ther Original Research 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. Dove Medical Press 2016-04-26 /pmc/articles/PMC4853138/ /pubmed/27217769 http://dx.doi.org/10.2147/OTT.S86139 Text en © 2016 Tong et al. This work is published by Dove Medical Press Limited, and licensed under Creative Commons Attribution – Non Commercial (unported, v3.0) License The full terms of the License are available at http://creativecommons.org/licenses/by-nc/3.0/. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. Permissions beyond the scope of the License are administered by Dove Medical Press Limited.
spellingShingle Original Research
Tong, Weihua
Ye, Fei
He, Liang
Cui, Lifeng
Cui, Miao
Hu, Yuan
Li, Wei
Jiang, Jing
Zhang, David Y
Suo, Jian
Serum biomarker panels for diagnosis of gastric cancer
title Serum biomarker panels for diagnosis of gastric cancer
title_full Serum biomarker panels for diagnosis of gastric cancer
title_fullStr Serum biomarker panels for diagnosis of gastric cancer
title_full_unstemmed Serum biomarker panels for diagnosis of gastric cancer
title_short Serum biomarker panels for diagnosis of gastric cancer
title_sort serum biomarker panels for diagnosis of gastric cancer
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4853138/
https://www.ncbi.nlm.nih.gov/pubmed/27217769
http://dx.doi.org/10.2147/OTT.S86139
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