In silico identification of potential targets and drugs for non-small cell lung cancer
In silico identification of potential targets and drugs for non-small cell lung cancer
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DOI：
10.1049/iet-syb.2013.0035
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发表时间：
2014-04-01
影响因子：
2.3
通讯作者：
Ng, Ka-Lok
中科院分区：
文献类型：
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作者：
Huang, Chien-Hung;Wu, Min-You;Ng, Ka-Lok
肺癌是美国和台湾的主要原因之一，人们认为癌症的原因可能是由于癌蛋白功能的获得或肿瘤抑制蛋白功能的丧失。因此，这些蛋白质是药物的潜在靶标。在这项研究中，通过从肺腺癌肿瘤和邻近非肿瘤组织生成的表达数据集来鉴定差异表达的基因。这项研究整合了许多互补的资源，即微阵列、蛋白质-蛋白质相互作用和蛋白质复合物。在构建肺癌蛋白质-蛋白质相互作用网络（PPIN）后，作者对PPIN进行了图论分析。鉴定出高密度模块，它们是潜在的癌症相关蛋白复合物。上调和下调的社区用作查询来执行功能富集分析。确定了丰富的生物过程和途径。这些上调和下调基因组被提交到连接图网络资源以识别潜在的药物。作者的研究结果表明，DrugBank 的八种药物和 NCBI 的三种药物可能逆转某些上调和下调基因的表达。总之，本研究为发现肺癌的潜在药物和靶基因提供了系统策略。
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.