Diagnosing phenotypes of single-sample individuals by edge biomarkers
Zhang, Wanwei1; Zeng, Tao1; Liu, Xiaoping1; Chen, Luonan1,2
2015-06
发表期刊JOURNAL OF MOLECULAR CELL BIOLOGY
ISSN1674-2788
卷号7期号:3页码:231-241
发表状态已发表
DOI10.1093/jmcb/mjv025
摘要Network or edge biomarkers are a reliable form to characterize phenotypes or diseases. However, obtaining edges or correlations between molecules for an individual requires measurement of multiple samples of that individual, which are generally unavailable in clinical practice. Thus, it is strongly demanded to diagnose a disease by edge or network biomarkers in one-sample-for-one-individual context. Here, we developed a new computational framework, EdgeBiomarker, to integrate edge and node biomarkers to diagnose phenotype of each single test sample. By applying the method to datasets of lung and breast cancer, it reveals new marker genes/gene-pairs and related sub-networks for distinguishing earlier and advanced cancer stages. Our method shows advantages over traditional methods: (i) edge biomarkers extracted from non-differentially expressed genes achieve better cross-validation accuracy of diagnosis than molecule or node biomarkers from differentially expressed genes, suggesting that certain pathogenic information is only present at the level of network and under-estimated by traditional methods; (ii) edge biomarkers categorize patients into low/high survival rate in a more reliable manner; (iii) edge biomarkers are significantly enriched in relevant biological functions or pathways, implying that the association changes ina network, rather than expression changes in individual molecules, tend to be causally related to cancer development. The new framework of edge biomarkers paves the way for diagnosing diseases and analyzing their molecular mechanisms by edges or networks in one-sample-for-one-individual basis. This also provides a powerful tool for precision medicine or big-data medicine.
关键词edge biomarker edge feature progressive stages disease diagnosis big biological data
收录类别SCI
语种英语
资助项目Knowledge Innovation Program of SIBS of CAS[2013KIP218]
WOS研究方向Cell Biology
WOS类目Cell Biology
WOS记录号WOS:000357857100005
出版者OXFORD UNIV PRESS
WOS关键词IDENTIFYING CRITICAL TRANSITIONS ; UNFOLDED PROTEIN RESPONSE ; BREAST-CANCER CELLS ; P53 MESSENGER-RNA ; COMPLEX DISEASES ; NETWORK BIOMARKERS ; TUMOR-METASTASIS ; PATHWAY ; PROGRESSION ; PREDICTION
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/2203
专题生命科学与技术学院_特聘教授组_陈洛南组
通讯作者Chen, Luonan
作者单位1.Chinese Acad Sci, Shanghai Inst Biol Sci, Inst Biochem & Cell Biol, Key Lab Syst Biol,Innovat Ctr Cell Signaling Netw, Shanghai 200031, Peoples R China
2.ShanghaiTech Univ, Sch Life Sci & Technol, 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
Zhang, Wanwei,Zeng, Tao,Liu, Xiaoping,et al. Diagnosing phenotypes of single-sample individuals by edge biomarkers[J]. JOURNAL OF MOLECULAR CELL BIOLOGY,2015,7(3):231-241.
APA Zhang, Wanwei,Zeng, Tao,Liu, Xiaoping,&Chen, Luonan.(2015).Diagnosing phenotypes of single-sample individuals by edge biomarkers.JOURNAL OF MOLECULAR CELL BIOLOGY,7(3),231-241.
MLA Zhang, Wanwei,et al."Diagnosing phenotypes of single-sample individuals by edge biomarkers".JOURNAL OF MOLECULAR CELL BIOLOGY 7.3(2015):231-241.
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