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Metabolic detection and systems analyses of pancreatic ductal adenocarcinoma through machine learning, lipidomics, and multi-omics

文献类型：期刊论文

作者Wang, Guangxi3; Yao, Hantao2; Gong, Yan1,11; Lu, Zipeng7; Pang, Ruifang6; Li, Yang3; Yuan, Yuyao3; Song, Huajie3; Liu, Jia3; Jin, Yan3
刊名SCIENCE ADVANCES
出版日期2021-12-01
卷号7期号:52页码:13
ISSN号2375-2548
DOI10.1126/sciadv.abh2724
通讯作者Jiang, Kuirong(jiangkuirong@njmu.edu.cn) ; Zeng, Qiang(zq301@126.com) ; Guo, Limei(guolimei@bjmu.edu.cn) ; Yin, Yuxin(yinyuxin@bjmu.edu.cn)
英文摘要Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers, characterized by rapid progression, metastasis, and difficulty in diagnosis. However, there are no effective liquid-based testing methods available for PDAC detection. Here we introduce a minimally invasive approach that uses machine learning (ML) and lipidomics to detect PDAC. Through greedy algorithm and mass spectrum feature selection, we optimized 17 characteristic metabolites as detection features and developed a liquid chromatography-mass spectrometry-based targeted assay. In this study, 1033 patients with PDAC at various stages were examined. This approach has achieved 86.74% accuracy with an area under curve (AUC) of 0.9351 in the large external validation cohort and 85.00% accuracy with 0.9389 AUC in the prospective clinical cohort. Accordingly, single-cell sequencing, proteomics, and mass spectrometry imaging were applied and revealed notable alterations of selected lipids in PDAC tissues. We propose that the ML-aided lipidomics approach be used for early detection of PDAC.
WOS关键词FATTY-ACID SYNTHASE ; EARLY EVENT ; CANCER ; HALLMARKS ; BIOMARKERS ; GENETICS ; DISEASES ; PATHWAY ; MS
资助项目National Key Research and Development Program of China[2016YFA0500302] ; National Natural Scientific Foundation of China[82030081] ; National Natural Scientific Foundation of China[81430056] ; National Natural Scientific Foundation of China[31420103905] ; National Natural Scientific Foundation of China[81874235] ; National Natural Scientific Foundation of China[30700349] ; National Natural Scientific Foundation of China[30440012] ; Beijing Municipal Science and Technology Commission[Z131100004013036] ; Shu Fan Education and Research Foundation ; Lam Chung Nin Foundation for Systems Biomedicine
WOS研究方向Science & Technology - Other Topics
语种英语
出版者AMER ASSOC ADVANCEMENT SCIENCE
WOS记录号WOS:000733258700010
资助机构National Key Research and Development Program of China ; National Natural Scientific Foundation of China ; Beijing Municipal Science and Technology Commission ; Shu Fan Education and Research Foundation ; Lam Chung Nin Foundation for Systems Biomedicine
源URL[http://ir.ia.ac.cn/handle/173211/47301]  
专题自动化研究所_模式识别国家重点实验室_多媒体计算与图形学团队
通讯作者Jiang, Kuirong; Zeng, Qiang; Guo, Limei; Yin, Yuxin
作者单位1.Chinese Peoples Liberat Army Gen Hosp, Med Ctr 2, Hlth Management Inst, Beijing 100853, Peoples R China
2.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
3.Peking Univ, Peking Tsinghua Ctr Life Sci, Sch Basic Med Sci, Inst Syst Biomed,Dept Pathol,Hlth Sci Ctr, Beijing 100191, Peoples R China
4.Peking Univ, Analyt Instrumentat Ctr, Beijing 100871, Peoples R China
5.Peking Univ, Dept Gen Surg, Hosp 1, Beijing 100034, Peoples R China
6.Peking Univ, Inst Precis Med, Shenzhen Hosp, Shenzhen 518036, Peoples R China
7.Nanjing Med Univ, Pancreas Ctr, Affiliated Hosp 1, Nanjing 210029, Peoples R China
8.Beijing Univ Posts & Telecommun, Beijing Key Lab Network Syst & Network Culture, Beijing 100876, Peoples R China
9.Peking Univ, Dept Thorac Surg, Peoples Hosp, Beijing 100044, Peoples R China
10.Peking Univ, Dept Pathol, Hosp 3, Beijing 100191, Peoples R China
推荐引用方式
GB/T 7714		 Wang, Guangxi,Yao, Hantao,Gong, Yan,et al. Metabolic detection and systems analyses of pancreatic ductal adenocarcinoma through machine learning, lipidomics, and multi-omics[J]. SCIENCE ADVANCES,2021,7(52):13.
APA Wang, Guangxi.,Yao, Hantao.,Gong, Yan.,Lu, Zipeng.,Pang, Ruifang.,...&Yin, Yuxin.(2021).Metabolic detection and systems analyses of pancreatic ductal adenocarcinoma through machine learning, lipidomics, and multi-omics.SCIENCE ADVANCES,7(52),13.
MLA Wang, Guangxi,et al."Metabolic detection and systems analyses of pancreatic ductal adenocarcinoma through machine learning, lipidomics, and multi-omics".SCIENCE ADVANCES 7.52(2021):13.

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来源：自动化研究所

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