Pre-clinical drug prioritization via prognosis-guided genetic interaction networks
文献类型：期刊论文
| 作者 | Xiong, Jianghui1,2; Liu, Juan1; Rayner, Simon3; Tian, Ze4; Li, Yinghui2; Chen, Shanguang2 |
| 刊名 | Plos one
 |
| 出版日期 | 2010-11-10 |
| 卷号 | 5期号:11页码:13 |
| ISSN号 | 1932-6203 |
| DOI | 10.1371/journal.pone.0013937 |
| 通讯作者 | Xiong, jianghui(laserxiong@gmail.com) |
| 英文摘要 | The high rates of failure in oncology drug clinical trials highlight the problems of using pre-clinical data to predict the clinical effects of drugs. patient population heterogeneity and unpredictable physiology complicate pre-clinical cancer modeling efforts. we hypothesize that gene networks associated with cancer outcome in heterogeneous patient populations could serve as a reference for identifying drug effects. here we propose a novel in vivo genetic interaction which we call 'synergistic outcome determination' (sod), a concept similar to 'synthetic lethality'. sod is defined as the synergy of a gene pair with respect to cancer patients' outcome, whose correlation with outcome is due to cooperative, rather than independent, contributions of genes. the method combines microarray gene expression data with cancer prognostic information to identify synergistic gene-gene interactions that are then used to construct interaction networks based on gene modules (a group of genes which share similar function). in this way, we identified a cluster of important epigenetically regulated gene modules. by projecting drug sensitivity-associated genes on to the cancer-specific intermodule network, we defined a perturbation index for each drug based upon its characteristic perturbation pattern on the inter-module network. finally, by calculating this index for compounds in the nci standard agent database, we significantly discriminated successful drugs from a broad set of test compounds, and further revealed the mechanisms of drug combinations. thus, prognosis-guided synergistic gene-gene interaction networks could serve as an efficient in silico tool for pre-clinical drug prioritization and rational design of combinatorial therapies. |
| WOS关键词 | CELL LUNG-CANCER ; BREAST-CANCER ; TARGETED THERAPIES ; IDENTIFICATION ; PHARMACOLOGY ; GEMCITABINE ; ROBUSTNESS ; MODULARITY ; INHIBITORS ; SIGNATURES |
| WOS研究方向 | Science & Technology - Other Topics |
| WOS类目 | Multidisciplinary Sciences |
| 语种 | 英语 |
| WOS记录号 | WOS:000284036800024 |
| 出版者 | PUBLIC LIBRARY SCIENCE |
| URI标识 | http://www.irgrid.ac.cn/handle/1471x/2375827 |
| 专题 | 武汉病毒研究所 |
| 通讯作者 | Xiong, Jianghui |
| 作者单位 | 1.Wuhan Univ, Sch Comp Sci, Wuhan 430072, Peoples R China 2.China Astronaut Res & Training Ctr, State Key Lab Space Med Fundamentals & Applicat, Bioinformat Syst Biol & Translat Med Grp, Beijing, Peoples R China 3.Chinese Acad Sci, Wuhan Inst Virol, State Key Lab Virol, Bioinformat Grp, Wuhan, Peoples R China 4.Harvard Univ, Sch Med, Dana Farber Canc Inst, Dept Med Oncol, Boston, MA 02115 USA |
| 推荐引用方式 GB/T 7714 | Xiong, Jianghui,Liu, Juan,Rayner, Simon,et al. Pre-clinical drug prioritization via prognosis-guided genetic interaction networks[J]. Plos one,2010,5(11):13. |
| APA | Xiong, Jianghui,Liu, Juan,Rayner, Simon,Tian, Ze,Li, Yinghui,&Chen, Shanguang.(2010).Pre-clinical drug prioritization via prognosis-guided genetic interaction networks.Plos one,5(11),13. |
| MLA | Xiong, Jianghui,et al."Pre-clinical drug prioritization via prognosis-guided genetic interaction networks".Plos one 5.11(2010):13. |
入库方式： iSwitch采集
来源：武汉病毒研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。