Identification of Biomarkers for Esophageal Squamous Cell Carcinoma Using Feature Selection and Decision Tree Methods
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 desi...
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| Format: | Article |
| Language: | English |
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Wiley
2013-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2013/782031 |
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| author | Chun-Wei Tung Ming-Tsang Wu Yu-Kuei Chen Chun-Chieh Wu Wei-Chung Chen Hsien-Pin Li Shah-Hwa Chou Deng-Chyang Wu I-Chen Wu |
| author_facet | Chun-Wei Tung Ming-Tsang Wu Yu-Kuei Chen Chun-Chieh Wu Wei-Chung Chen Hsien-Pin Li Shah-Hwa Chou Deng-Chyang Wu I-Chen Wu |
| author_sort | Chun-Wei Tung |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-084a57a0b9b246b098b1a649ed72f5ca |
| institution | Kabale University |
| issn | 1537-744X |
| language | English |
| publishDate | 2013-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-084a57a0b9b246b098b1a649ed72f5ca2025-02-03T01:21:31ZengWileyThe Scientific World Journal1537-744X2013-01-01201310.1155/2013/782031782031Identification of Biomarkers for Esophageal Squamous Cell Carcinoma Using Feature Selection and Decision Tree MethodsChun-Wei Tung0Ming-Tsang Wu1Yu-Kuei Chen2Chun-Chieh Wu3Wei-Chung Chen4Hsien-Pin Li5Shah-Hwa Chou6Deng-Chyang Wu7I-Chen Wu8School of Pharmacy, Kaohsiung Medical University, Kaohsiung 80708, TaiwanDepartment of Family Medicine, Kaohsiung Medical University Hospital, Kaohsiung 80708, TaiwanDepartment of Food Science and Nutrition, Meiho University, Pingtung 91202, TaiwanDepartment of Pathology, Kaohsiung Medical University Hospital, Kaohsiung 80708, TaiwanDivision of Chest Surgery, Kaohsiung Municipal Hsiao-Kang Hospital, Kaohsiung 812, TaiwanDivision of Chest Surgery, Kaohsiung Municipal Hsiao-Kang Hospital, Kaohsiung 812, TaiwanDivision of Chest Surgery, Department of Surgery, Kaohsiung Medical University Hospital, Kaohsiung 80708, TaiwanDivision of Gastroenterology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung 80708, TaiwanDivision of Gastroenterology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung 80708, TaiwanEsophageal 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.http://dx.doi.org/10.1155/2013/782031 |
| spellingShingle | Chun-Wei Tung Ming-Tsang Wu Yu-Kuei Chen Chun-Chieh Wu Wei-Chung Chen Hsien-Pin Li Shah-Hwa Chou Deng-Chyang Wu I-Chen Wu Identification of Biomarkers for Esophageal Squamous Cell Carcinoma Using Feature Selection and Decision Tree Methods The Scientific World Journal |
| title | Identification of Biomarkers for Esophageal Squamous Cell Carcinoma Using Feature Selection and Decision Tree Methods |
| title_full | Identification of Biomarkers for Esophageal Squamous Cell Carcinoma Using Feature Selection and Decision Tree Methods |
| title_fullStr | Identification of Biomarkers for Esophageal Squamous Cell Carcinoma Using Feature Selection and Decision Tree Methods |
| title_full_unstemmed | Identification of Biomarkers for Esophageal Squamous Cell Carcinoma Using Feature Selection and Decision Tree Methods |
| title_short | Identification of Biomarkers for Esophageal Squamous Cell Carcinoma Using Feature Selection and Decision Tree Methods |
| title_sort | identification of biomarkers for esophageal squamous cell carcinoma using feature selection and decision tree methods |
| url | http://dx.doi.org/10.1155/2013/782031 |
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