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Converting a Microarray Signature into a Diagnostic Test: A Trial of Custom 74 Gene Array for Clarification and Prediction the Prognosis of Gastric Cancer

BACKGROUND: Gastric cancer (GC) is associated with high mortality rates and an unfavorable prognosis at advanced stages. In addition, there are no effective methods for diagnosing gastric cancer at an early stage or for predicting the outcome for the purpose of selecting patient-specific treatment o...

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Autores principales: Yin, Ying, Zhuo, Wei, Zhao, Yuan, Chen, Shujie, Li, Jun, Wang, Lan, Zhou, Tianhua, Si, Jian-Min
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3849172/
https://www.ncbi.nlm.nih.gov/pubmed/24312559
http://dx.doi.org/10.1371/journal.pone.0081561
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author Yin, Ying
Zhuo, Wei
Zhao, Yuan
Chen, Shujie
Li, Jun
Wang, Lan
Zhou, Tianhua
Si, Jian-Min
author_facet Yin, Ying
Zhuo, Wei
Zhao, Yuan
Chen, Shujie
Li, Jun
Wang, Lan
Zhou, Tianhua
Si, Jian-Min
author_sort Yin, Ying
collection PubMed
description BACKGROUND: Gastric cancer (GC) is associated with high mortality rates and an unfavorable prognosis at advanced stages. In addition, there are no effective methods for diagnosing gastric cancer at an early stage or for predicting the outcome for the purpose of selecting patient-specific treatment options. Therefore, it is important to investigate new methods for GC diagnosis. METHODOLOGY/PRINCIPAL FINDINGS: To facilitate its use in a diagnostic setting, a group of 74 genes with diagnostic and prognostic information was translated into a customized microarray containing a reduced set of 1,042 probes suitable for high throughput processing. In this report, we demonstrate for the first time that the custom mini-array can be used as a reliable diagnostic tool in gastric cancer. With an AUC value of 0.565 (95% CI 0.305-0.825) indicating a perfect test, the sensitivity and specificity of diagnosis from the ROC curve were calculated to be 70% and 80%, respectively. CONCLUSIONS/SIGNIFICANCE: The data clearly demonstrate the reproducibility and robustness of the small custom-made microarray. The array is an excellent tool for classifying and predicting the outcome of disease in gastric cancer patients.
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spelling pubmed-38491722013-12-05 Converting a Microarray Signature into a Diagnostic Test: A Trial of Custom 74 Gene Array for Clarification and Prediction the Prognosis of Gastric Cancer Yin, Ying Zhuo, Wei Zhao, Yuan Chen, Shujie Li, Jun Wang, Lan Zhou, Tianhua Si, Jian-Min PLoS One Research Article BACKGROUND: Gastric cancer (GC) is associated with high mortality rates and an unfavorable prognosis at advanced stages. In addition, there are no effective methods for diagnosing gastric cancer at an early stage or for predicting the outcome for the purpose of selecting patient-specific treatment options. Therefore, it is important to investigate new methods for GC diagnosis. METHODOLOGY/PRINCIPAL FINDINGS: To facilitate its use in a diagnostic setting, a group of 74 genes with diagnostic and prognostic information was translated into a customized microarray containing a reduced set of 1,042 probes suitable for high throughput processing. In this report, we demonstrate for the first time that the custom mini-array can be used as a reliable diagnostic tool in gastric cancer. With an AUC value of 0.565 (95% CI 0.305-0.825) indicating a perfect test, the sensitivity and specificity of diagnosis from the ROC curve were calculated to be 70% and 80%, respectively. CONCLUSIONS/SIGNIFICANCE: The data clearly demonstrate the reproducibility and robustness of the small custom-made microarray. The array is an excellent tool for classifying and predicting the outcome of disease in gastric cancer patients. Public Library of Science 2013-12-03 /pmc/articles/PMC3849172/ /pubmed/24312559 http://dx.doi.org/10.1371/journal.pone.0081561 Text en © 2013 Yin et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Yin, Ying
Zhuo, Wei
Zhao, Yuan
Chen, Shujie
Li, Jun
Wang, Lan
Zhou, Tianhua
Si, Jian-Min
Converting a Microarray Signature into a Diagnostic Test: A Trial of Custom 74 Gene Array for Clarification and Prediction the Prognosis of Gastric Cancer
title Converting a Microarray Signature into a Diagnostic Test: A Trial of Custom 74 Gene Array for Clarification and Prediction the Prognosis of Gastric Cancer
title_full Converting a Microarray Signature into a Diagnostic Test: A Trial of Custom 74 Gene Array for Clarification and Prediction the Prognosis of Gastric Cancer
title_fullStr Converting a Microarray Signature into a Diagnostic Test: A Trial of Custom 74 Gene Array for Clarification and Prediction the Prognosis of Gastric Cancer
title_full_unstemmed Converting a Microarray Signature into a Diagnostic Test: A Trial of Custom 74 Gene Array for Clarification and Prediction the Prognosis of Gastric Cancer
title_short Converting a Microarray Signature into a Diagnostic Test: A Trial of Custom 74 Gene Array for Clarification and Prediction the Prognosis of Gastric Cancer
title_sort converting a microarray signature into a diagnostic test: a trial of custom 74 gene array for clarification and prediction the prognosis of gastric cancer
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3849172/
https://www.ncbi.nlm.nih.gov/pubmed/24312559
http://dx.doi.org/10.1371/journal.pone.0081561
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