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BioMed Research International
Volume 2014 (2014), Article ID 193817, 13 pages
Research Article

Drug Repositioning Discovery for Early- and Late-Stage Non-Small-Cell Lung Cancer

1Department of Computer Science and Information Engineering, National Formosa University, 64 Wen-Hwa Road, Hu-Wei, Yun-Lin 632, Taiwan
2Division of Hematology and Oncology, Department of Medicine, Taipei Veterans General Hospital, Faculty of Medicine, National Yang-Ming University, Taipei 112, Taiwan
3Cancer Center, Keelung Chang Gang Memorial Hospital, Keelung 204, Taiwan
4Institute of Biopharmaceutical Sciences, National Yang-Ming University, No. 155, Section 2, Linong Street, Taipei 112, Taiwan
5Genome Research Center, National Yang-Ming University, Taipei 112, Taiwan
6Department of Biomedical Informatics, Asia University, 500 Lioufeng Road, Wufeng Shiang, Taichung 41354, Taiwan
7Department of Medical Research, China Medical University Hospital, China Medical University, Taichung 40402, Taiwan

Received 10 April 2014; Revised 7 July 2014; Accepted 12 July 2014; Published 18 August 2014

Academic Editor: X. Li

Copyright © 2014 Chien-Hung Huang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Drug repositioning is a popular approach in the pharmaceutical industry for identifying potential new uses for existing drugs and accelerating the development time. Non-small-cell lung cancer (NSCLC) is one of the leading causes of death worldwide. To reduce the biological heterogeneity effects among different individuals, both normal and cancer tissues were taken from the same patient, hence allowing pairwise testing. By comparing early- and late-stage cancer patients, we can identify stage-specific NSCLC genes. Differentially expressed genes are clustered separately to form up- and downregulated communities that are used as queries to perform enrichment analysis. The results suggest that pathways for early- and late-stage cancers are different. Sets of up- and downregulated genes were submitted to the cMap web resource to identify potential drugs. To achieve high confidence drug prediction, multiple microarray experimental results were merged by performing meta-analysis. The results of a few drug findings are supported by MTT assay or clonogenic assay data. In conclusion, we have been able to assess the potential existing drugs to identify novel anticancer drugs, which may be helpful in drug repositioning discovery for NSCLC.