Identification of novel candidate drivers connecting different dysfunctional levels for lung adenocarcinoma using protein-protein interactions and a shortest path approach

doi:10.1038/srep29849

CORC > 上海药物研究所 > 中国科学院上海药物研究所 > 药物发现与设计中心

	Identification of novel candidate drivers connecting different dysfunctional levels for lung adenocarcinoma using protein-protein interactions and a shortest path approach
	Chen, Lei 2,3; Huang, Tao 4; Zhang, Yu-Hang 4; Jiang, Yang 1; Zheng, Mingyue5 ; Cai, Yu-Dong 2
刊名	SCIENTIFIC REPORTS
	2016-07-14
卷号	6
ISSN号	2045-2322
DOI	10.1038/srep29849
文献子类	Article
英文摘要	Tumors are formed by the abnormal proliferation of somatic cells with disordered growth regulation under the influence of tumorigenic factors. Recently, the theory of "cancer drivers" connects tumor initiation with several specific mutations in the so-called cancer driver genes. According to the differentiation of four basic levels between tumor and adjacent normal tissues, the cancer drivers can be divided into the following: (1) Methylation level, (2) microRNA level, (3) mutation level, and (4) mRNA level. In this study, a computational method is proposed to identify novel lung adenocarcinoma drivers based on dysfunctional genes on the methylation, microRNA, mutation and mRNA levels. First, a large network was constructed using protein-protein interactions. Next, we searched all of the shortest paths connecting dysfunctional genes on different levels and extracted new candidate genes lying on these paths. Finally, the obtained candidate genes were filtered by a permutation test and an additional strict selection procedure involving a betweenness ratio and an interaction score. Several candidate genes remained, which are deemed to be related to two different levels of cancer. The analyses confirmed our assertions that some have the potential to contribute to the tumorigenesis process on multiple levels.
资助项目	National Natural Science Foundation of China[31371335] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDA12050201] ; Hi-Tech Research and Development Program of China[2014AA01A302]
WOS关键词	INTERACTION NETWORK ; MICRORNA TARGETS ; DRUG-RESISTANCE ; GENE-EXPRESSION ; KRAS MUTATIONS ; CANCER-CELLS ; PREDICTION ; DATABASE ; SURVIVAL ; TUMORS
WOS研究方向	Science & Technology - Other Topics
语种	英语
出版者	NATURE PUBLISHING GROUP
WOS记录号	WOS:000379577100001
内容类型	期刊论文
源URL	[http://119.78.100.183/handle/2S10ELR8/275960]
专题	药物发现与设计中心中科院受体结构与功能重点实验室新药研究国家重点实验室
通讯作者	Jiang, Yang; Zheng, Mingyue; Cai, Yu-Dong
作者单位	1.Jilin Univ, China Japan Union Hosp, Dept Surg, Changchun 130033, Peoples R China; 2.Shanghai Univ, Sch Life Sci, Shanghai 200444, Peoples R China; 3.Shanghai Maritime Univ, Coll Informat Engn, Shanghai 201306, Peoples R China; 4.Chinese Acad Sci, Shanghai Inst Biol Sci, Inst Hlth Sci, Shanghai 200031, Peoples R China; 5.Chinese Acad Sci, Drug Discovery & Design Ctr, Shanghai Inst Mat Med, State Key Lab Drug Res, Shanghai 201203, Peoples R China
推荐引用方式 GB/T 7714	Chen, Lei,Huang, Tao,Zhang, Yu-Hang,et al. Identification of novel candidate drivers connecting different dysfunctional levels for lung adenocarcinoma using protein-protein interactions and a shortest path approach[J]. SCIENTIFIC REPORTS,2016,6.
APA	Chen, Lei,Huang, Tao,Zhang, Yu-Hang,Jiang, Yang,Zheng, Mingyue,&Cai, Yu-Dong.(2016).Identification of novel candidate drivers connecting different dysfunctional levels for lung adenocarcinoma using protein-protein interactions and a shortest path approach.SCIENTIFIC REPORTS,6.
MLA	Chen, Lei,et al."Identification of novel candidate drivers connecting different dysfunctional levels for lung adenocarcinoma using protein-protein interactions and a shortest path approach".SCIENTIFIC REPORTS 6(2016).