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On February 2, 2022, the team of Professor Yin Yuxin from Peking University School of Basic Medicine and the team of Academician Wang Jun from People's Hospital jointly published an online publication titled "Lung cancer scRNA-seq and lipidomics reveal aberrant lipid metabolism for early-stage" in the journal Science Translational Medicine.
Diagnosis" research paper, applied single-cell transcriptomics, plasma lipidomics, machine learning and mass spectrometry imaging to comprehensively analyze the lipid metabolism characteristics of early-stage lung cancer, developed a set of artificial intelligence-assisted early-stage lung cancer metabolism detection methods, and revealed related molecular mechanisms
Research strategy of metabolome combined with artificial intelligence for early detection of lung cancer
The mortality rate of lung cancer ranks first among malignant tumors, and early detection is the key to improving the survival rate of lung cancer
.
However, there is currently no reliable blood test for the early diagnosis of lung cancer
The method, named Lung Cancer Artificial Intelligence Detector (LCAID) , can be used for early detection of lung cancer or mass screening of high-risk groups
.
The successful establishment of this method clarified and opened up an efficient strategy and a new direction for machine learning-assisted metabolomics for early lung cancer detection and screening
It is worth noting that this method was also developed by Yin Yuxin’s team and collaborators after the detection of pancreatic adenocarcinoma ( Wang et al .
, Sci.
Adv (2021) ) and esophageal cancer ( Yuan et al .
, Br J Cancer (2021) ).
Another AI-assisted tumor metabolism detection method
.
Dr.
Wang Guangxi, postdoctoral fellow of Peking University School of Basic Medicine, Dr.
Qiu Mantang, assistant researcher of thoracic surgery, Peking University People's Hospital, and Dr.
Xing Xudong, postdoctoral fellow of Peking University Biomedical Frontier Innovation Center are the co-first authors of the paper, Academician Wang Jun of Peking University People's Hospital, Peking University Professor Yin Yuxin from the Institute of Systems Biomedicine is the co-corresponding author
.
The work was also supported by Associate Researcher Yao Hantao of the Institute of Automation, Chinese Academy of Sciences, Chief Physician Pan Shuli and Deputy Chief Physician Li Mingru of China Aerospace 731 Hospital, Deputy Chief Physician Yin Rong of Jiangsu Cancer Hospital, Associate Researcher Hou Yan of Peking University School of Public Health, and Chief Physician Huang Yuqing of Haidian Hospital , Chief Physician Yang Fan of Peking University People’s Hospital, Prof.
The project was supported by the National Key R&D Program, the National Natural Science Foundation of China, the Beijing Natural Science Foundation of China, and the Peking University - Tsinghua Joint Center for Life Sciences
Original link: https:// Peking University School of Basic Medicine )
