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Single-cell metabolic fingerprints discover a cluster of circulating tumor cells with distinct metastatic potential

Author

Listed:
  • Wenjun Zhang

    (Nanjing Medical University)

  • Feifei Xu

    (Nanjing Medical University)

  • Jiang Yao

    (Nanjing Medical University)

  • Changfei Mao

    (Jiangsu Cancer Hospital (Jiangsu Institute of Cancer Research, Nanjing Medical University Affiliated Cancer Hospital))

  • Mingchen Zhu

    (Jiangsu Cancer Hospital (Jiangsu Institute of Cancer Research, Nanjing Medical University Affiliated Cancer Hospital))

  • Moting Qian

    (Nanjing Medical University)

  • Jun Hu

    (Nanjing Medical University)

  • Huilin Zhong

    (Nanjing Normal University)

  • Junsheng Zhou

    (Nanjing Normal University)

  • Xiaoyu Shi

    (Nanjing Medical University)

  • Yun Chen

    (Nanjing Medical University
    State Key Laboratory of Reproductive Medicine
    Key Laboratory of Cardiovascular and Cerebrovascular Medicine)

Abstract

Circulating tumor cells (CTCs) are recognized as direct seeds of metastasis. However, CTC count may not be the “best” indicator of metastatic risk because their heterogeneity is generally neglected. In this study, we develop a molecular typing system to predict colorectal cancer metastasis potential based on the metabolic fingerprints of single CTCs. After identification of the metabolites potentially related to metastasis using mass spectrometry-based untargeted metabolomics, setup of a home-built single-cell quantitative mass spectrometric platform for target metabolite analysis in individual CTCs and use of a machine learning method composed of non-negative matrix factorization and logistic regression, CTCs are divided into two subgroups, C1 and C2, based on a 4-metabolite fingerprint. Both in vitro and in vivo experiments demonstrate that CTC count in C2 subgroup is closely associated with metastasis incidence. This is an interesting report on the presence of a specific population of CTCs with distinct metastatic potential at the single-cell metabolite level.

Suggested Citation

  • Wenjun Zhang & Feifei Xu & Jiang Yao & Changfei Mao & Mingchen Zhu & Moting Qian & Jun Hu & Huilin Zhong & Junsheng Zhou & Xiaoyu Shi & Yun Chen, 2023. "Single-cell metabolic fingerprints discover a cluster of circulating tumor cells with distinct metastatic potential," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-38009-3
    DOI: 10.1038/s41467-023-38009-3
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    References listed on IDEAS

    as
    1. Michael Eisenstein, 2023. "Seven technologies to watch in 2023," Nature, Nature, vol. 613(7945), pages 794-797, January.
    2. Monika Haemmerle & Morgan L. Taylor & Tony Gutschner & Sunila Pradeep & Min Soon Cho & Jianting Sheng & Yasmin M. Lyons & Archana S. Nagaraja & Robert L. Dood & Yunfei Wen & Lingegowda S. Mangala & Je, 2017. "Platelets reduce anoikis and promote metastasis by activating YAP1 signaling," Nature Communications, Nature, vol. 8(1), pages 1-15, December.
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