Single test-based diagnosis of multiple cancer types using Exosome-SERS-AI for early stage cancers

Early cancer detection has significant clinical value, but there remains no single method that can comprehensively identify multiple types of early-stage cancer. Here, we report the diagnostic accuracy of simultaneous detection of 6 types of early-stage cancers (lung, breast, colon, liver, pancreas, and stomach) by analyzing surface-enhanced Raman spectroscopy profiles of exosomes using artificial intelligence in a retrospective study design. It includes classification models that recognize signal patterns of plasma exosomes to identify both their presence and tissues of origin. Using 520 test samples, our system identified cancer presence with an area under the curve value of 0.970. Moreover, the system…

• SN
  Seoul National University Bundang Hospital
• KU
  Korea University Guro Hospital
• KM
  Korea Medical Device Development Fund

  Awards: 1711174279, RS-2020-KD000094
• SN
  Seoul National University
• AU
  Ajou University
• KU
  Korea University
• MO
  Ministry of Trade, Industry and Energy
• MO
  Ministry of Food and Drug Safety
• KI
  Korea Institute of Radiological and Medical Sciences
• MO
  Ministry of Science and ICT, South Korea