IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v10y2019i1d10.1038_s41467-019-10122-2.html
   My bibliography  Save this article

Hydro-Seq enables contamination-free high-throughput single-cell RNA-sequencing for circulating tumor cells

Author

Listed:
  • Yu-Heng Cheng

    (University of Michigan)

  • Yu-Chih Chen

    (University of Michigan
    University of Michigan)

  • Eric Lin

    (University of Michigan)

  • Riley Brien

    (University of Michigan)

  • Seungwon Jung

    (University of Michigan
    University of Michigan)

  • Yu-Ting Chen

    (Computer Science Department UCLA, Boelter Hall)

  • Woncheol Lee

    (University of Michigan)

  • Zhijian Hao

    (University of Michigan)

  • Saswat Sahoo

    (University of Michigan)

  • Hyun Min Kang

    (University of Michigan)

  • Jason Cong

    (Computer Science Department UCLA, Boelter Hall)

  • Monika Burness

    (University of Michigan)

  • Sunitha Nagrath

    (University of Michigan)

  • Max S. Wicha

    (University of Michigan)

  • Euisik Yoon

    (University of Michigan
    University of Michigan)

Abstract

Molecular analysis of circulating tumor cells (CTCs) at single-cell resolution offers great promise for cancer diagnostics and therapeutics from simple liquid biopsy. Recent development of massively parallel single-cell RNA-sequencing (scRNA-seq) provides a powerful method to resolve the cellular heterogeneity from gene expression and pathway regulation analysis. However, the scarcity of CTCs and the massive contamination of blood cells limit the utility of currently available technologies. Here, we present Hydro-Seq, a scalable hydrodynamic scRNA-seq barcoding technique, for high-throughput CTC analysis. High cell-capture efficiency and contamination removal capability of Hydro-Seq enables successful scRNA-seq of 666 CTCs from 21 breast cancer patient samples at high throughput. We identify breast cancer drug targets for hormone and targeted therapies and tracked individual cells that express markers of cancer stem cells (CSCs) as well as of epithelial/mesenchymal cell state transitions. Transcriptome analysis of these cells provides insights into monitoring target therapeutics and processes underlying tumor metastasis.

Suggested Citation

  • Yu-Heng Cheng & Yu-Chih Chen & Eric Lin & Riley Brien & Seungwon Jung & Yu-Ting Chen & Woncheol Lee & Zhijian Hao & Saswat Sahoo & Hyun Min Kang & Jason Cong & Monika Burness & Sunitha Nagrath & Max S, 2019. "Hydro-Seq enables contamination-free high-throughput single-cell RNA-sequencing for circulating tumor cells," Nature Communications, Nature, vol. 10(1), pages 1-11, December.
  • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-10122-2
    DOI: 10.1038/s41467-019-10122-2
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-019-10122-2
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-019-10122-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xiaoxu Guo & Fanghe Lin & Chuanyou Yi & Juan Song & Di Sun & Li Lin & Zhixing Zhong & Zhaorun Wu & Xiaoyu Wang & Yingkun Zhang & Jin Li & Huimin Zhang & Feng Liu & Chaoyong Yang & Jia Song, 2022. "Deep transfer learning enables lesion tracing of circulating tumor cells," Nature Communications, Nature, vol. 13(1), pages 1-14, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-10122-2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.