Identification of Biomarkers for Esophageal Squamous Cell Carcinoma Using Feature Selection and Decision Tree Methods

MUIR > Graduate Institute of Health Care > Department of Food Science and Nutrition > Papers > Item 987654321/2622

Please use this identifier to cite or link to this item: http://ir.meiho.edu.tw/ir/handle/987654321/2622

Title:	Identification of Biomarkers for Esophageal Squamous Cell Carcinoma Using Feature Selection and Decision Tree Methods
Authors:	Chun-Wei Tung;Ming-Tsang Wu;Yu-Kuei Chen;Chun-Chieh Wu;Wei-Chung Chen;Hsien-Pin Li;Shah-Hwa Chou
Contributors:	健康暨護理學院
Date:	2013
Issue Date:	2014-11-13T02:22:34Z (UTC)
Abstract:	Esophageal squamous cell cancer (ESCC) is one of the most common fatal human cancers. The identification of biomarkers for early detection could be a promising strategy to decrease mortality. Previous studies utilized microarray techniques to identify more than one hundred genes; however, it is desirable to identify a small set of biomarkers for clinical use. This study proposes a sequential forward feature selection algorithm to design decision tree models for discriminating ESCC from normal tissues. Two potential biomarkers of RUVBL1 and CNIH were identified and validated based on two public available microarray datasets. To test the discrimination ability of the two biomarkers, 17 pairs of expression profiles of ESCC and normal tissues from Taiwanese male patients were measured by using microarray techniques. The classification accuracies of the two biomarkers in all three datasets were higher than 90%. Interpretable decision tree models were constructed to analyze expression patterns of the two biomarkers. RUVBL1 was consistently overexpressed in all three datasets, although we found inconsistent CNIH expression possibly affected by the diverse major risk factors for ESCC across different areas.
Relation:	The ScientificWorld Journal
Appears in Collections:	[Department of Food Science and Nutrition] Papers

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