Identifying critical differentiation state of MCF-7 cells for breast cancer by dynamical network biomarkers

被引：29

作者：

Chen, Pei ^{[1
]}

Liu, Rui ^{[2
]}

Chen, Luonan ^{[3
,4
]}

Aihara, Kazuyuki ^{[3
]}

机构：

[1] S China Univ Technol, Sch Comp Sci, Guangzhou, Guangdong, Peoples R China

[2] S China Univ Technol, Sch Math, Guangzhou, Guangdong, Peoples R China

[3] Univ Tokyo, Collaborat Res Ctr Innovat Math Modeling, Tokyo, Japan

[4] Chinese Acad Sci, Shanghai Inst Biol Sci, Inst Biochem & Cell Biol, Key Lab Syst Biol,Innovat Ctr Cell Signaling Netw, Shanghai, Peoples R China

来源：

FRONTIERS IN GENETICS | 2015年 / 6卷

基金：

中国国家自然科学基金;

关键词：

LEADING BIOMOLECULAR NETWORKS; EARLY-WARNING SIGNALS; COMPLEX DISEASES; CRITICAL TRANSITIONS; EPILEPTIC SEIZURES; MODULE BIOMARKERS; SINGLE-SAMPLE; GENES; PHENOTYPES; BRAIN;

D O I：

10.3389/fgene.2015.00252

中图分类号：

Q3 [遗传学];

学科分类号：

071007 ; 090102 ;

摘要：

Identifying the pre-transition state just before a critical transition during a complex biological process is a challenging task, because the state of the system may show neither apparent changes nor clear phenomena before this critical transition during the biological process. By exploring rich correlation information provided by high-throughput data, the dynamical network biomarker (DNB) can identify the pre-transition state. In this work, we apply DNB to detect an early-warning signal of breast cancer on the basis of gene expression data of MCF-7 cell differentiation. We find a number of the related modules and pathways in the samples, which can be used not only as the biomarkers of cancer cells but also as the drug targets. Both functional and pathway enrichment analyses validate the results.

引用

页数：7

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