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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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2017-07-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-017-06083-5 |
| _version_ | 1819040022057189376 |
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| 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 |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-12-21T09:02:29Z |
| format | Article |
| id | doaj.art-239946725e554e61914fbcd41eb0f1d1 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-12-21T09:02:29Z |
| publishDate | 2017-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-239946725e554e61914fbcd41eb0f1d12022-12-21T19:09:26ZengNature PortfolioScientific Reports2045-23222017-07-017111110.1038/s41598-017-06083-5Large-Scale Analysis of Drug Side Effects via Complex Regulatory Modules Composed of microRNAs, Transcription Factors and Gene SetsXiaodong Jia0Qing Jin1Xiangqiong Liu2Xiusen Bian3Yunfeng Wang4Lei Liu5Hongzhe Ma6Fujian Tan7Mingliang Gu8Xiujie Chen9College of Bioinformatics Science and Technology, Harbin Medical UniversityCollege of Bioinformatics Science and Technology, Harbin Medical UniversityCollege of Bioinformatics Science and Technology, Harbin Medical UniversityCollege of Bioinformatics Science and Technology, Harbin Medical UniversityCollege of Bioinformatics Science and Technology, Harbin Medical UniversityCollege of Bioinformatics Science and Technology, Harbin Medical UniversityCollege of Bioinformatics Science and Technology, Harbin Medical UniversityCollege of Bioinformatics Science and Technology, Harbin Medical UniversityJoint Laboratory for Translational Medicine Research, Beijing Institute of Genomics, Chinese Academy of Sciences & Liaocheng People’s HospitalCollege of Bioinformatics Science and Technology, Harbin Medical UniversityAbstract 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.https://doi.org/10.1038/s41598-017-06083-5 |
| spellingShingle | 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 Scientific Reports |
| title | 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_short | 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 |
| url | https://doi.org/10.1038/s41598-017-06083-5 |
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