Detection for disease tipping points by landscape dynamic network biomarkers

doi:10.1093/nsr/nwy162

	Detection for disease tipping points by landscape dynamic network biomarkers
	Liu, Xiaoping 1,2,3; Chang, Xiao 3,4; Leng, Siyang 3; Tang, Hui1,5 ; Aihara, Kazuyuki 3; Chen, Luonan1,3,5,6,7
	2019-07
发表期刊	NATIONAL SCIENCE REVIEW
ISSN	2095-5138
卷号	6 期号:4 页码:775-785
发表状态	已发表
DOI	10.1093/nsr/nwy162
摘要	A new model-free method has been developed and termed the landscape dynamic network biomarker (l-DNB) methodology. The method is based on bifurcation theory, which can identify tipping points prior to serious disease deterioration using only single-sample omics data. Here, we show that l-DNB provides early-warning signals of disease deterioration on a single-sample basis and also detects critical genes or network biomarkers (i.e. DNB members) that promote the transition from normal to disease states. As a case study, l-DNB was used to predict severe influenza symptoms prior to the actual symptomatic appearance in influenza virus infections. The l-DNB approach was then also applied to three tumor disease datasets from the TCGA and was used to detect critical stages prior to tumor deterioration using an individual DNB for each patient. The individual DNBs were further used as individual biomarkers in the analysis of physiological data, which led to the identification of two biomarker types that were surprisingly effective in predicting the prognosis of tumors. The biomarkers can be considered as common biomarkers for cancer, wherein one indicates a poor prognosis and the other indicates a good prognosis.
关键词	single-sample network dynamic network biomarkers tipping points of complex disease
URL	查看原文
收录类别	SCI ; SCIE ; EI ; CSCD
语种	英语
资助项目	JST CREST, Japan[JPMJCR14D2]
WOS研究方向	Science & Technology - Other Topics
WOS类目	Multidisciplinary Sciences
WOS记录号	WOS:000489296400026
CSCD记录号	CSCD:6605641
出版者	OXFORD UNIV PRESS
EI入藏号	20194007489297
EI主题词	Bifurcation (mathematics) ; Deterioration ; Diagnosis ; Tumors ; Viruses
EI分类号	Bioengineering and Biology:461 ; Materials Science:951
WOS关键词	CANCER ; CELLS ; PROLIFERATION ; SOX15
原始文献类型	Article
引用统计
文献类型	期刊论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/80391
专题	生命科学与技术学院_硕士生生命科学与技术学院_特聘教授组_陈洛南组
通讯作者	Aihara, Kazuyuki; Chen, Luonan
作者单位	1.Chinese Acad Sci, Shanghai Inst Biol Sci, Inst Biochem & Cell Biol, Ctr Excellence Mol Cell Sci,Key Lab Syst Biol, Shanghai 200031, Peoples R China 2.Shandong Univ Weihai, Sch Math & Stat, Weihai 264209, Peoples R China 3.Univ Tokyo, Inst Ind Sci, Tokyo 1538505, Japan 4.Anhui Univ Finance & Econ, Inst Stat & Appl Math, Bengbu 233030, Peoples R China 5.ShanghaiTech Univ, Sch Life Sci & Technol, Shanghai 201210, Peoples R China 6.Ctr Excellence Anim Evolut & Genet, Kunming 650223, Yunnan, Peoples R China 7.Res Ctr Brain Sci & Brain Inspired Intelligence, Shanghai 201210, Peoples R China
通讯作者单位	生命科学与技术学院
推荐引用方式 GB/T 7714	Liu, Xiaoping,Chang, Xiao,Leng, Siyang,et al. Detection for disease tipping points by landscape dynamic network biomarkers[J]. NATIONAL SCIENCE REVIEW,2019,6(4):775-785.
APA	Liu, Xiaoping,Chang, Xiao,Leng, Siyang,Tang, Hui,Aihara, Kazuyuki,&Chen, Luonan.(2019).Detection for disease tipping points by landscape dynamic network biomarkers.NATIONAL SCIENCE REVIEW,6(4),775-785.
MLA	Liu, Xiaoping,et al."Detection for disease tipping points by landscape dynamic network biomarkers".NATIONAL SCIENCE REVIEW 6.4(2019):775-785.