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

Hyunku Shin, Byeong Hyeon Choi, On Shim, Jihee Kim, Yong Park, Suk Ki Cho, Hyun Koo Kim, Yeonho Choi

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)

Abstract

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 classified the tumor organ type of 278 early-stage cancer patients with a mean area under the curve of 0.945. The final integrated decision model showed a sensitivity of 90.2% at a specificity of 94.4% while predicting the tumor organ of 72% of positive patients. Since our method utilizes a non-specific analysis of Raman signatures, its diagnostic scope could potentially be expanded to include other diseases.

Original languageEnglish
Article number1644
JournalNature communications
Volume14
Issue number1
DOIs
Publication statusPublished - 2023 Dec

Bibliographical note

Funding Information:
This study was supported by a grant from the Seoul R&BD Program through the Seoul Business Agency (SBA) funded by the Seoul Metropolitan Government (BT210040, PI: H.S.) and the Korea Medical Device Development Fund grant funded by the Korean government (the Ministry of Science and ICT, the Ministry of Trade, Industry and Energy, the Ministry of Health & Welfare, the Ministry of Food and Drug Safety) (Project Number: 1711174279, RS-2020-KD000094, PI: Y.C.). The biospecimen and data used in this study were provided by the Korea Institute of Radiological and Medical Sciences (KIRAMS) Radiation Biobank (KRB, KRB-2021-E002), the Human Biobank of Seoul National University Bundang Hospital (Distribution No. DT-2020-013-01), the Biobank of Korea University Guro Hospital, the Asan Bio-Resource Center (2021-02(219)), and the Biobank of Ajou University Hospital, a member of Korea Biobank Network.

Funding Information:
This study was supported by a grant from the Seoul R&BD Program through the Seoul Business Agency (SBA) funded by the Seoul Metropolitan Government (BT210040, PI: H.S.) and the Korea Medical Device Development Fund grant funded by the Korean government (the Ministry of Science and ICT, the Ministry of Trade, Industry and Energy, the Ministry of Health & Welfare, the Ministry of Food and Drug Safety) (Project Number: 1711174279, RS-2020-KD000094, PI: Y.C.). The biospecimen and data used in this study were provided by the Korea Institute of Radiological and Medical Sciences (KIRAMS) Radiation Biobank (KRB, KRB-2021-E002), the Human Biobank of Seoul National University Bundang Hospital (Distribution No. DT-2020-013-01), the Biobank of Korea University Guro Hospital, the Asan Bio-Resource Center (2021-02(219)), and the Biobank of Ajou University Hospital, a member of Korea Biobank Network.

Publisher Copyright:
© 2023, The Author(s).

ASJC Scopus subject areas

  • General Physics and Astronomy
  • General Chemistry
  • General Biochemistry,Genetics and Molecular Biology

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