A novel analysis method for biomarker identification based on horizontal relationship: identifying potential biomarkers from large-scale hepatocellular carcinoma metabolomics data

doi:10.1007/s00216-019-02011-w

	A novel analysis method for biomarker identification based on horizontal relationship: identifying potential biomarkers from large-scale hepatocellular carcinoma metabolomics data
	Su, Benzhe 1; Luo, Ping 2; Yang, Zhao 3,4; Yu, Pei 3,4; Li, Zaifang 2; Yin, Peiyuan 2; Zhou, Lina 2; Fan, Jinhu 3,4; Huang, Xin 1; Lin, Xiaohui 1
刊名	ANALYTICAL AND BIOANALYTICAL CHEMISTRY
	2019-09-01
卷号	411 期号:24 页码:6377-6386
关键词	LC-MS/MS Biomarker identification Networks Metabolomics HCC
ISSN号	1618-2642
DOI	10.1007/s00216-019-02011-w
通讯作者	Yin, Peiyuan(yinperry@126.com) ; Fan, Jinhu(Fanjh@cicams.ac.cn) ; Lin, Xiaohui(datas@dlut.edu.cn)
英文摘要	Omics techniques develop quickly and have made a great contribution to disease study. Omics data are usually complex. How to analyze the data and mine important information has been a key part in omics research. To study the nature of disease mechanisms systematically, we propose a new data analysis method to define the network biomarkers based on horizontal comparison (DNB-HC). DNB-HC performs molecule horizontal relationships to characterize the physiological status and differential network analysis to screen the biomarkers. We applied DNB-HC to analyze a large-scale metabolomics data, which contained 550 samples from a nested case-control hepatocellular carcinoma (HCC) study. A network biomarker was defined, and its areas under curves (AUC) in the receiver-operating characteristic (ROC) analysis for HCC discrimination were larger than those defined by six efficient feature selection methods in most cases. The effectiveness was further corroborated by another nested HCC dataset. Besides, the performance of the defined biomarkers was better than that of alpha-fetoprotein (AFP), a commonly used clinical biomarker for distinguishing HCC from high-risk population of liver cirrhosis in other two independent metabolomics validation sets. All and 90.3% of the AFP false-negative patients with HCC were correctly diagnosed in these two sets, respectively. The experimental results illustrate that DNB-HC can mine more important information reflecting the nature of the research problems by studying the feature horizontal relationship systematically and identifying effective disease biomarkers in clinical practice.
资助项目	National Natural Science Foundation of China[21375011] ; Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences (CIFMS)[2017-I2M-BR-03]
WOS关键词	NUTRITION INTERVENTION TRIALS ; LIVER-DISEASE MORTALITY ; CANCER ; NETWORKS ; LINXIAN ; CLASSIFICATION ; ASSOCIATION ; DIAGNOSIS ; SELECTION ; PROTEIN
WOS研究方向	Biochemistry & Molecular Biology ; Chemistry
语种	英语
出版者	SPRINGER HEIDELBERG
WOS记录号	WOS:000483638800015
资助机构	National Natural Science Foundation of China ; National Natural Science Foundation of China ; Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences (CIFMS) ; Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences (CIFMS) ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences (CIFMS) ; Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences (CIFMS) ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences (CIFMS) ; Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences (CIFMS) ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences (CIFMS) ; Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences (CIFMS)
内容类型	期刊论文
源URL	[http://cas-ir.dicp.ac.cn/handle/321008/173016]
专题	大连化学物理研究所_中国科学院大连化学物理研究所
通讯作者	Yin, Peiyuan; Fan, Jinhu; Lin, Xiaohui
作者单位	1.Dalian Univ Technol, Sch Comp Sci & Technol, Dalian 116024, Peoples R China 2.Chinese Acad Sci, Dalian Inst Chem Phys, CAS Key Lab Separat Sci Analyt Chem, Dalian 116023, Peoples R China 3.Chinese Acad Med Sci, Natl Clin Res Ctr Canc, Dept Canc Epidemiol, Canc Hosp,Natl Canc Ctr, Beijing 100021, Peoples R China 4.Peking Union Med Coll, Beijing 100021, Peoples R China
推荐引用方式 GB/T 7714	Su, Benzhe,Luo, Ping,Yang, Zhao,et al. A novel analysis method for biomarker identification based on horizontal relationship: identifying potential biomarkers from large-scale hepatocellular carcinoma metabolomics data[J]. ANALYTICAL AND BIOANALYTICAL CHEMISTRY,2019,411(24):6377-6386.
APA	Su, Benzhe.,Luo, Ping.,Yang, Zhao.,Yu, Pei.,Li, Zaifang.,...&Xu, Guowang.(2019).A novel analysis method for biomarker identification based on horizontal relationship: identifying potential biomarkers from large-scale hepatocellular carcinoma metabolomics data.ANALYTICAL AND BIOANALYTICAL CHEMISTRY,411(24),6377-6386.
MLA	Su, Benzhe,et al."A novel analysis method for biomarker identification based on horizontal relationship: identifying potential biomarkers from large-scale hepatocellular carcinoma metabolomics data".ANALYTICAL AND BIOANALYTICAL CHEMISTRY 411.24(2019):6377-6386.