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

doi:10.1126/sciadv.abh2724

	Metabolic detection and systems analyses of pancreatic ductal adenocarcinoma through machine learning, lipidomics, and multi-omics
	Wang, Guangxi 1; Yao, Hantao2 ; Gong, Yan 3,4; Lu, Zipeng 5; Pang, Ruifang 6; Li, Yang 1; Yuan, Yuyao 1; Song, Huajie 1; Liu, Jia 1; Jin, Yan 1; Ma, Yongsu 7; Yang, Yinmo 7; Nie, Honggang 8; Zhang, Guangze 1; Meng, Zhu 9; Zhou, Zhe 1; Zhao, Xuyang 1; Qiu, Mantang 10; Zhao, Zhicheng 9; Jiang, Kuirong 5; Zeng, Qiang 3,4; Guo, Limei 1,11; Yin, Yuxin 1,6
发表期刊	SCIENCE ADVANCES
ISSN	2375-2548
	2021-12-01
卷号	7 期号:52 页码:13
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)
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.
DOI	10.1126/sciadv.abh2724
关键词[WOS]	FATTY-ACID SYNTHASE ; EARLY EVENT ; CANCER ; HALLMARKS ; BIOMARKERS ; GENETICS ; DISEASES ; PATHWAY ; MS
收录类别	SCI
语种	英语
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
项目资助者	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
WOS研究方向	Science & Technology - Other Topics
WOS类目	Multidisciplinary Sciences
WOS记录号	WOS:000733258700010
出版者	AMER ASSOC ADVANCEMENT SCIENCE
引用统计	被引频次：17[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/47302
专题	多模态人工智能系统全国重点实验室_多媒体计算
通讯作者	Jiang, Kuirong; Zeng, Qiang; Guo, Limei; Yin, Yuxin
作者单位	1.Peking Univ, Peking Tsinghua Ctr Life Sci, Sch Basic Med Sci, Inst Syst Biomed,Dept Pathol,Hlth Sci Ctr, Beijing 100191, Peoples R China 2.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 3.Chinese Peoples Liberat Army Gen Hosp, Med Ctr 2, Hlth Management Inst, Beijing 100853, Peoples R China 4.Chinese Peoples Liberat Army Gen Hosp, Natl Clin Res Ctr Geriatr Dis, Beijing 100853, Peoples R China 5.Nanjing Med Univ, Pancreas Ctr, Affiliated Hosp 1, Nanjing 210029, Peoples R China 6.Peking Univ, Inst Precis Med, Shenzhen Hosp, Shenzhen 518036, Peoples R China 7.Peking Univ, Dept Gen Surg, Hosp 1, Beijing 100034, Peoples R China 8.Peking Univ, Analyt Instrumentat Ctr, Beijing 100871, Peoples R China 9.Beijing Univ Posts & Telecommun, Beijing Key Lab Network Syst & Network Culture, Beijing 100876, Peoples R China 10.Peking Univ, Dept Thorac Surg, Peoples Hosp, Beijing 100044, Peoples R China 11.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.