Large-Scale Analysis of Drug Side Effects via Complex Regulatory Modules Composed of microRNAs, Transcription Factors and Gene Sets

Abstract 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 sin...

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Autores principales:	Xiaodong Jia, Qing Jin, Xiangqiong Liu, Xiusen Bian, Yunfeng Wang, Lei Liu, Hongzhe Ma, Fujian Tan, Mingliang Gu, Xiujie Chen
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/239946725e554e61914fbcd41eb0f1d1
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spelling	oai:doaj.org-article:239946725e554e61914fbcd41eb0f1d12021-12-02T15:04:58ZLarge-Scale Analysis of Drug Side Effects via Complex Regulatory Modules Composed of microRNAs, Transcription Factors and Gene Sets10.1038/s41598-017-06083-52045-2322https://doaj.org/article/239946725e554e61914fbcd41eb0f1d12017-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-06083-5https://doaj.org/toc/2045-2322Abstract 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.Xiaodong JiaQing JinXiangqiong LiuXiusen BianYunfeng WangLei LiuHongzhe MaFujian TanMingliang GuXiujie ChenNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-11 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Xiaodong Jia Qing Jin Xiangqiong Liu Xiusen Bian Yunfeng Wang Lei Liu Hongzhe Ma Fujian Tan Mingliang Gu Xiujie Chen Large-Scale Analysis of Drug Side Effects via Complex Regulatory Modules Composed of microRNAs, Transcription Factors and Gene Sets
description	Abstract 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.
format	article
author	Xiaodong Jia Qing Jin Xiangqiong Liu Xiusen Bian Yunfeng Wang Lei Liu Hongzhe Ma Fujian Tan Mingliang Gu Xiujie Chen
author_facet	Xiaodong Jia Qing Jin Xiangqiong Liu Xiusen Bian Yunfeng Wang Lei Liu Hongzhe Ma Fujian Tan Mingliang Gu Xiujie Chen
author_sort	Xiaodong Jia
title	Large-Scale Analysis of Drug Side Effects via Complex Regulatory Modules Composed of microRNAs, Transcription Factors and Gene Sets
title_short	Large-Scale Analysis of Drug Side Effects via Complex Regulatory Modules Composed of microRNAs, Transcription Factors and Gene Sets
title_full	Large-Scale Analysis of Drug Side Effects via Complex Regulatory Modules Composed of microRNAs, Transcription Factors and Gene Sets
title_fullStr	Large-Scale Analysis of Drug Side Effects via Complex Regulatory Modules Composed of microRNAs, Transcription Factors and Gene Sets
title_full_unstemmed	Large-Scale Analysis of Drug Side Effects via Complex Regulatory Modules Composed of microRNAs, Transcription Factors and Gene Sets
title_sort	large-scale analysis of drug side effects via complex regulatory modules composed of micrornas, transcription factors and gene sets
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/239946725e554e61914fbcd41eb0f1d1
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Large-Scale Analysis of Drug Side Effects via Complex Regulatory Modules Composed of microRNAs, Transcription Factors and Gene Sets

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