Early cancer detection by serum biomolecular fingerprinting spectroscopy with machine learning

被引:48
作者
Dong, Shilian [1 ]
He, Dong [1 ]
Zhang, Qian [2 ]
Huang, Chaoning [1 ]
Hu, Zhiheng [3 ]
Zhang, Chenyang [1 ]
Nie, Lei [4 ]
Wang, Kun [4 ]
Luo, Wei [5 ]
Yu, Jing [6 ]
Tian, Bin [7 ]
Wu, Wei [7 ]
Chen, Xu [3 ]
Wang, Fubing [2 ,11 ]
Hu, Jing [8 ,9 ,10 ]
Xiao, Xiangheng [1 ,11 ]
机构
[1] Wuhan Univ, Natl Demonstrat Ctr Expt Phys Educ, Dept Phys, Wuhan 430072, Peoples R China
[2] Wuhan Univ, Dept Lab Med, Zhongnan Hosp, Wuhan 430071, Peoples R China
[3] Wuhan Univ, Sch Comp Sci, Wuhan 430072, Peoples R China
[4] Huazhong Univ Sci & Technol, Hubei Canc Hosp, Tongji Med Coll, Dept Hepatobiliary & Pancreat Surg, Wuhan 430079, Peoples R China
[5] Tianjin Med Univ, Gen Hosp, Dept Clin Lab, Tianjin 300052, Peoples R China
[6] Huazhong Univ Sci & Technol, Wuhan Hosp Tradit Chinese & Western Med, Tongji Med Coll, Dept Blood Transfus, Wuhan 430022, Peoples R China
[7] Wuhan Univ, Res Ctr Commun Graph Printing & Packaging, Lab Printable Funct Mat & Printed Elect, Wuhan 430072, Peoples R China
[8] Univ Elect Sci & Technol, Sichuan Prov Key Lab Human Dis Gene Study, Chengdu 611731, Peoples R China
[9] Univ Elect Sci & Technol, Sichuan Acad Med Sci & Sichuan Prov Peoples Hosp, Ctr Med Genet, Dept Lab Med, Chengdu 611731, Peoples R China
[10] Univ Elect Sci & Technol China, Sch Med, Chengdu 611731, Peoples R China
[11] Chinese Acad Med Sci, Wuhan Res Ctr Infect Dis & Canc, Wuhan 430071, Peoples R China
来源
ELIGHT | 2023年 / 3卷 / 01期
关键词
CLASSIFICATION; VECTOR; TOOL;
D O I
10.1186/s43593-023-00051-5
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Label-free surface-enhanced Raman scattering (SERS) technique with ultra-sensitivity becomes more and more desirable in biomedical analysis, which is yet hindered by inefficient follow-up data analysis. Here we report an integrative method based on SERS and Artificial Intelligence for Cancer Screening (SERS-AICS) for liquid biopsy such as serum via silver nanowires, combining molecular vibrational signals processing with large-scale data mining algorithm. According to 382 healthy controls and 1582 patients from two independent cohorts, SERS-AICS not only distinguishes pan-cancer patients from health controls with 95.81% overall accuracy and 95.87% sensitivity at 95.40% specificity, but also screens out those samples at early cancer stage. The supereminent efficiency potentiates SERS-AICS a promising tool for detecting cancer with broader types at earlier stage, accompanying with the establishment of a data platform for further deep analysis.
引用
收藏
页数:11
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