title: In silico identification of potential targets and drugs for non-small cell lung cancer.
abstract: Lung cancer is one of the leading causes of death in both the USA and Taiwan, and it is thought that the cause of cancer could be because of the gain of function of an oncoprotein or the loss of function of a tumour suppressor protein. Consequently, these proteins are potential targets for drugs. In this study, differentially expressed genes are identified, via an expression dataset generated from lung adenocarcinoma tumour and adjacent non-tumour tissues. This study has integrated many complementary resources, that is, microarray, protein-protein interaction and protein complex. After constructing the lung cancer protein-protein interaction network (PPIN), the authors performed graph theory analysis of PPIN. Highly dense modules are identified, which are potential cancer-associated protein complexes. Up- and down-regulated communities were used as queries to perform functional enrichment analysis. Enriched biological processes and pathways are determined. These sets of up- and down-regulated genes were submitted to the Connectivity Map web resource to identify potential drugs. The authors' findings suggested that eight drugs from DrugBank and three drugs from NCBI can potentially reverse certain up- and down-regulated genes' expression. In conclusion, this study provides a systematic strategy to discover potential drugs and target genes for lung cancer.
authors.affiliation: Department of Computer Science and Information Engineering, National Formosa University, 64, Wen-Hwa Road, Hu-wei 632, Yun-Lin, Taiwan.
authors.forename: Chien-Hung
authors.initials: CH
authors.lastname: Huang
authors.affiliation: Department of Computer Science and Information Engineering, National Formosa University, 64, Wen-Hwa Road, Hu-wei 632, Yun-Lin, Taiwan.
authors.forename: Min-You
authors.initials: MY
authors.lastname: Wu
authors.affiliation: Division of Hematology and Oncology, Department of Medicine, Taipei Veterans General Hospital, Faculty of Medicine, National Yang Ming University, Taipei 112, Taiwan.
authors.forename: Peter Mu-Hsin
authors.initials: PM
authors.lastname: Chang
authors.affiliation: Institute of Biopharmaceutical Sciences, National Yang-Ming University, 155, Sec. 2, Linong Street, Taipei 112, Taiwan.
authors.forename: Chi-Ying
authors.initials: CY
authors.lastname: Huang
authors.affiliation: School of Pharmacy, China Medical University, Taichung 40402, Taiwan. ppiddi@gmail.com.
authors.forename: Ka-Lok
authors.initials: KL
authors.lastname: Ng
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000970:Antineoplastic Agents / Q000737:chemistry; D002289:Carcinoma, Non-Small-Cell Lung / Q000188:drug therapy* / Q000235:genetics / Q000378:metabolism; D045744:Cell Line, Tumor; D002470:Cell Survival; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D055808:Drug Discovery; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D008175:Lung Neoplasms / Q000188:drug therapy* / Q000235:genetics; D008875:Middle Aged; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D015398:Signal Transduction; D013678:Technology, Pharmaceutical
chemical_list: D000970:Antineoplastic Agents