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Differential regulation analysis reveals dysfunctional regulatory mechanism involving transcription factors and microRNAs in gastric carcinogenesis

文献类型：期刊论文

作者Li, Quanxue1,4; Li, Yi-Xue1,2,3,4,5; Li, Junyi4; Dai, Wentao4; Li, Yuan-Yuan2,3,4; Li, Junyi5; Dai, Wentao2,3; ,
刊名ARTIFICIAL INTELLIGENCE IN MEDICINE
出版日期2017
卷号77期号:-页码:12-22
关键词Gastric cancer Differential coexpression analysis Differential regulation analysis Combinatorial gene regulatory network
ISSN号0933-3657
DOI10.1016/j.artmed.2017.02.006
文献子类Article
英文摘要Gastric cancer (GC) is one of the most incident malignancies in the world. Although lots of featured genes and microRNAs (miRNAs) have been identified to be associated with gastric carcinogenesis, underlying regulatory mechanisms still remain unclear. In order to explore the dysfunctional mechanisms of GC, we developed a novel approach to identify carcinogenesis relevant regulatory relationships, which is characterized by quantifying the difference of regulatory relationships between stages. Firstly, we applied the strategy of differential coexpression analysis (DCEA) to transcriptomic datasets including paired mRNA and miRNA of gastric samples to identify a set of genes/miRNAs related to gastric cancer progression. Based on these genes/miRNAs, we constructed conditional combinatorial gene regulatory networks (cGRNs) involving both transcription factors (TFs) and miRNAs. Enrichment of known cancer genes/miRNAs and predicted prognostic genes/miRNAs was observed in each cGRN. Then we designed a quantitative method to measure differential regulation level of every regulatory relationship between normal and cancer, and the known cancer genes/miRNAs proved to be ranked significantly higher. Meanwhile, we defined differentially regulated link (DRL) by combining differential regulation, differential expression and the regulation contribution of the regulator to the target. By integrating survival analysis and DRL identification, three master regulators TCF7L1, TCF4, and MEIS1 were identified and testable hypotheses of dysfunctional mechanisms underlying gastric carcinogenesis related to them were generated. The fine-tuning effects of miRNAs were also observed. We propose that this differential regulation network analysis framework is feasible to gain insights into dysregulated mechanisms underlying tumorigenesis and other phenotypic changes. (C) 2017 Published by Elsevier B.V.
学科主题Computer Science ; Engineering ; Medical Informatics
WOS关键词NETWORK ANALYSIS ; TUMOR-SUPPRESSOR ; COMBINATORIAL NETWORK ; CELL-PROLIFERATION ; COEXPRESSED GENES ; SEQUENCING DATA ; CANCER GROWTH ; R PACKAGE ; EXPRESSION ; DATABASE
语种英语
WOS记录号WOS:000402943500002
出版者ELSEVIER SCIENCE BV
版本出版稿
源URL[http://202.127.25.144/handle/331004/790]  
专题中国科学院上海生命科学研究院营养科学研究所
作者单位1.East China Univ Sci & Technol, Sch Biotechnol, Shanghai, Peoples R China;
2.Shanghai Engn Res Ctr Pharmaceut Translat, Shanghai, Peoples R China,
3.Shanghai Ind Technol Inst, Shanghai, Peoples R China;
4.Shanghai Ctr Bioinformat Technol, Keyuan Rd 1278, Shanghai, Peoples R China;
5.Chinese Acad Sci, Shanghai Inst Biol Sci, CAS MPG Partner Inst Computat Biol, Key Lab Computat Biol, Shanghai, Peoples R China;
推荐引用方式
GB/T 7714		 Li, Quanxue,Li, Yi-Xue,Li, Junyi,et al. Differential regulation analysis reveals dysfunctional regulatory mechanism involving transcription factors and microRNAs in gastric carcinogenesis[J]. ARTIFICIAL INTELLIGENCE IN MEDICINE,2017,77(-):12-22.
APA Li, Quanxue.,Li, Yi-Xue.,Li, Junyi.,Dai, Wentao.,Li, Yuan-Yuan.,...&,.(2017).Differential regulation analysis reveals dysfunctional regulatory mechanism involving transcription factors and microRNAs in gastric carcinogenesis.ARTIFICIAL INTELLIGENCE IN MEDICINE,77(-),12-22.
MLA Li, Quanxue,et al."Differential regulation analysis reveals dysfunctional regulatory mechanism involving transcription factors and microRNAs in gastric carcinogenesis".ARTIFICIAL INTELLIGENCE IN MEDICINE 77.-(2017):12-22.

入库方式： OAI收割

来源：上海营养与健康研究所

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