Large-Scale Analysis of Drug Side Effects via Complex Regulatory Modules Composed of microRNAs, Transcription Factors and Gene Sets.
Large-Scale Analysis of Drug Side Effects via Complex Regulatory Modules Composed of microRNAs, Transcription Factors and Gene Sets.
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通过由 microRNA、转录因子和基因集组成的复杂调控模块大规模分析药物副作用
DOI：
10.1038/s41598-017-06083-5
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发表时间：
2017-07-20
影响因子：
4.6
通讯作者：
Chen X
中科院分区：
文献类型：
--
作者：
Jia X;Jin Q;Liu X;Bian X;Wang Y;Liu L;Ma H;Tan F;Gu M;Chen X
明确药物副作用的发生机制对于药物靶点设计和新药开发具有重要意义。生物过程中基因的表达受转录因子（TF）和/或microRNA的调控。以往的研究大多集中在基因或基因组的单一水平上，而对转录因子、miRNA与生物学过程的调控关系的研究非常少见。揭示转录因子、基因组和miRNAs之间复杂的调控关系有助于研究者更全面地了解副反应的发生机制。本研究提出了一个框架来构建副作用相关基因集、miRNAs和TF的关系网络。通过该网络的构建，再现了副作用发生过程中潜在的复杂调控关系。SE-基因集网络被用来描述显著的调节SE-基因集相互作用和伴随副作用的分子基础。从SE-gene sets-miRNA/TF复合物调控网络中共获得117个副作用复合物模块，包括4种调控模式。此外，通过两个案例验证了复杂的调控模块，可以更全面地解释副作用的发生机制。
Identifying the occurrence mechanism of drug-induced side effects (SEs) is critical for design of drug target and new drug development. The expression of genes in biological processes is regulated by transcription factors(TFs) and/or microRNAs. Most of previous studies were focused on a single level of gene or gene sets, while studies about regulatory relationships of TFs, miRNAs and biological processes are very rare. Discovering the complex regulating relations among TFs, gene sets and miRNAs will be helpful for researchers to get a more comprehensive understanding about the mechanism of side reaction. In this study, a framework was proposed to construct the relationship network of gene sets, miRNAs and TFs involved in side effects. Through the construction of this network, the potential complex regulatory relationship in the occurrence process of the side effects was reproduced. The SE-gene set network was employed to characterize the significant regulatory SE-gene set interaction and molecular basis of accompanied side effects. A total of 117 side effects complex modules including four types of regulating patterns were obtained from the SE-gene sets-miRNA/TF complex regulatory network. In addition, two cases were used to validate the complex regulatory modules which could more comprehensively interpret occurrence mechanism of side effects.
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影响因子：
5.8
作者：
Liberzon, Arthur;Subramanian, Aravind;Mesirov, Jill P.
通讯作者：
Mesirov, Jill P.
影响因子：
64.8
作者：
Dickinson ME;Flenniken AM;Ji X;Teboul L;Wong MD;White JK;Meehan TF;Weninger WJ;Westerberg H;Adissu H;Baker CN;Bower L;Brown JM;Caddle LB;Chiani F;Clary D;Cleak J;Daly MJ;Denegre JM;Doe B;Dolan ME;Edie SM;Fuchs H;Gailus-Durner V;Galli A;Gambadoro A;Gallegos J;Guo S;Horner NR;Hsu CW;Johnson SJ;Kalaga S;Keith LC;Lanoue L;Lawson TN;Lek M;Mark M;Marschall S;Mason J;McElwee ML;Newbigging S;Nutter LM;Peterson KA;Ramirez-Solis R;Rowland DJ;Ryder E;Samocha KE;Seavitt JR;Selloum M;Szoke-Kovacs Z;Tamura M;Trainor AG;Tudose I;Wakana S;Warren J;Wendling O;West DB;Wong L;Yoshiki A;International Mouse Phenotyping Consortium;Jackson Laboratory;Infrastructure Nationale PHENOMIN, Institut Clinique de la Souris (ICS);Charles River Laboratories;MRC Harwell;Toronto Centre for Phenogenomics;Wellcome Trust Sanger Institute;RIKEN BioResource Center;MacArthur DG;Tocchini-Valentini GP;Gao X;Flicek P;Bradley A;Skarnes WC;Justice MJ;Parkinson HE;Moore M;Wells S;Braun RE;Svenson KL;de Angelis MH;Herault Y;Mohun T;Mallon AM;Henkelman RM;Brown SD;Adams DJ;Lloyd KC;McKerlie C;Beaudet AL;Bućan M;Murray SA
通讯作者：
Murray SA
影响因子：
9.9
作者：
Kuhn M;Campillos M;Letunic I;Jensen LJ;Bork P
通讯作者：
Bork P
影响因子：
3.6
作者：
Gulati N;Løvendorf MB;Zibert JR;Akat KM;Renwick N;Tuschl T;Krueger JG
通讯作者：
Krueger JG
DOI：
10.1111/j.2517-6161.1995.tb02031.x
发表时间：
1995-01-01
影响因子：
5.8
作者：
BENJAMINI, Y;HOCHBERG, Y
通讯作者：
HOCHBERG, Y